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GSED 3.0 User's Manual (April 2010)

1. 2 3 3 Genotype frequencies in deme If the sign of LocusNoy in a deme specification line equals see 2 3 1 then each genotype is interpreted as having been found in a number of individuals The frequency of a genotype in the deme is given in the second field In this case each genotype line specifies the following integers DemeNo Frequency Locus Allele Locus Alleley LocusnAllelez Locusn Alleley where DemeNo Deme number referring to the list of demes in header Frequency Number of individuals possessing the genotype Locus Alleley First allele at locus i as an integer gt 1 C MIR UY If gametic sex is specified for this locus then Locus Allele stems from the maternal parent Locus Alleleo Second allele at locus i as an integer 2 1 EL If gametic sex is specified for this locus then Locus Alleleg stems from the paternal parent 12 A null allele at locus i is designated by Locus Allele 0 zero 7 l or 2 An unknown allele is specified by Locus Allele 1 j 1 or 2 Note that unknown alleles in a random deme of genotypes can present a problem for the calculation of frequency distributions see 5 2 3 4 End of deme line e For unformatted input either an empty line or the integer 9999 somewhere on the line e For formatted input either an empty line or a line containing the integer 9999 in columns w 3 to w where w is the width
2. In the first run of GSED with a new input file options are chosen by answering a sequence of questions described in more detail in the following also see App D GSED saves the choices in a configuration file that is called up in subsequent runs using this input file see 3 3 bgp For questions to be answered by Y or N uncapitalized letters y and n are also accepted Enter name of input file max 256 characters 7 Type the name of the input file see 2 including path specification if necessary A maxi mum of 60 characters is allowed Enter prefix for names of output files default example txt Enter a short prefix for the names of all output files By pressing Return the name of the input file is used Select the locus configuration Locus configuration O all single loci 2 multilocus some loci 1 some single loci 3 multilocus all loci Option 7 The four options are explained as follows Option 0 Calculations will be carried out for every single locus Option 1 25 Calculations will be carried out for some of the single loci As an example the loci 2 and 4 are specified in reply to the following question Number of different single loci 2 Which gene loci separated by commas and using as many lines as necessary 7 2 4 Option 2 Calculations will be carried out for multilocus genotypes defined by the genotypes at dif ferent sets of ge
3. 65 relative e 0 867 0 900 0 933 for No types 3 2 3 Deme 1 2 3 1 0 000 2 0 300 0 000 3 0 400 0 650 0 000 SUBPOPULATION DIFFERENTIATION D j delta RELATIVE SUBPOPULATION SIZE PROPORTIONAL TO DEME SIZE Deme 1 2 3 Cj 0 333 0 333 0 333 Dj 0 325 0 475 0 500 delta 0 433 SUBPOPULATION_DIFFERENTIATION_D_j _delta RELATIVE SUBPOPULATION SIZES ALL EQUAL TO 1 NO SUBPOPS Deme 1 2 3 Cj 0 333 0 333 0 333 Dj 0 325 0 475 0 500 delta 0 433 TEST OF HOMOGENEITY Deme 1 2 3 Allele Sum 101 24 0 6 11 7 E 8 00 8 00 8 00 121 170 8 9 0 E 5 67 5 67 5 67 132 70 0 0 7 E 2 33 2 33 2 33 136 12 0 6 0 6 E 4 00 4 00 4 00 60 20 20 20 Level_of C V of CHI 2 Test statistics significance DF 6 G 40 641 xxx 0 050 12 592 X 2 30 338 0 010 16 812 0 001 22 458 RR RC WARNING gt xxxxx lt WARNING gt xxxxx lt WARNING gt xxxxx lt WARNING gt xxxxx Test statistics are inflated due to expected frequencies less xx xx than 5 and may falsely recommend rejection of hypothesis xx xx Suggestion Pool alleles in input data and recalculate xx kxxxx lt WARNING gt xxxxx lt WARNING gt xxxxx lt WARNING gt xxxxx lt WARNING gt xx xxx Deme 1 2 3 Gam sex spec no no no Deme size 10 10 10 No identified 10 10 10 alpha 0 334 0 334 0 334 No unknown 0 0 0 Deme 1 2 3 Genotype 101 x 101 1 3 2 101 x 121 2 5 0 101 x 136 2 0 3 121 x 121 2 2 0 121 x 136 2 0 0
4. A E y yr y yr yr yr y y lpha HWP 0 2010 0 2010 0 2010 vnInfRel 0 8000 0 6667 0 8000 deltaEgS 0 6000 0 6000 0 6000 v2 Divers 5 5556 2 6316 3 8462 EvnInfNum 5 0000 3 0000 4 0000 PropHeter 0 6000 0 5000 0 6000 H Output file example txt multi out txt The output file named example txt multi out txt for multilocus genotypes in the sample input file example txt out txt KKK K K FK FK K K K K K K FK FK FK ok ok ok de oko ok fe FK ok oe oe K fe K ok FK FK FK ok FK oe oe dd oko oe oe FK ok oe KK KK FK FK FK FK K FK K o eoe 2 2K ok KK KK gt K ok K GGGGGGG SSSSSSS EEEEEEE DDDDDD Genetic G G S E D D Structures G S E D D from G SSSSSSS EEEE D D Electrophoresis G GGGG S E D D Data G G S E D D Version 3 0beta GGGGGGG SSSSSSS EEEEEEE DDDDDD April 2010 KKK ak ak 3k 3k 3K 3K K K K K aK aK gt K 2K 2k ak 3K 3K 3K 3K 3K 3K 3K 3K 3K 3K K K aK aK aK 2K aK aK 2 2K 3K 3K 3K 3K 3K 3K 3K 3K 3K 3K K K K K gt K 2K 2K K 2K 2K 3K 3K 3K 3K 3K 3K 3K 3K 3K 3K K K K GSED Copyright 1990 2010 Elizabeth M Gillet egillet gwdg de www uni goettingen de de 95607 html GSED is free software you can redistribute it under the terms of the GNU General Public License GPL v 3 as published by the Free Software Foundation GSED is distributed in the hope that it will be useful but WITHOUT ANY WARRANTY without even the implied warranty of merchant ability or fitness for a particular purpose
5. Haplotype frequencies among paternal contributions Haplotype frequencies Genotype frequencies if gametic sex is inferable e g as the allele or multilocus haplotype contributed by the maternal seed parent to the megagametophyte of conifer seeds to chloroplasts or to mi tochondria angiosperms if gametic sex is inferable e g as the allele or multilocus haplotype contributed by the paternal pollen parent to the embryo of conifer seeds as determined by megagame tophyte embryo analysis or to chloroplasts conifers The combined set of all maternal and paternal alleles or multilocus haplotypes 1 1 Genetic structures and their characterization The foundation of this system of data analysis is the quantification of differences between demes as the proportion of individuals that must be changed in one of the demes to make its genetic structure match the structure in the other deme This descriptive concept of difference is applicable to all types of demes in any situation since it does not rely on assumptions of specific models e g drift lack of mutation special mating systems Table 2 Characterization of genetic structures by GSED e ANALYSIS OF ALLELIC HAPLOTYPIC AND GENOTYPIC STRUCTURES Measures of variation within demes Diversity v9 x Total population differentiation r Evenness e Measures of variation between demes Genetic distance do Subpopulation differentiation D and Test of h
6. Level of C V of CHI 2 Test statistics significance DF 1 G 0 156 n s 0 050 3 841 Xxx2 0 160 n s 0 010 xx 6 635 X 2 c 5 0 004 n s 0 001 xxx 10 828 69 G Output file example txt tab txt Beginning of the output file for single locus genotypes at Locus 1 in the sample input file example txt out txt GSED INPUT FILE path example txt GSED OUTPUT FILE path example txt out txt Date 12 Apr 2010 12 24 42 LOCUS NO 1 Locusi ALLELE_FREQUENCIES Absolute_frequencies Deme_No 1 2 3 Type_1 6 11 7 101 3 Type_2 8 9 0 121 Type_3 0 0 T 132 Type_4 6 0 6 136 Sum 20 20 20 Relative_frequencies Deme_No 1 2 3 Type_1 0 300 0 550 0 350 101 Type_2 0 400 0 450 0 000 121 Type_3 0 000 0 000 0 350 132 Type_4 0 300 0 000 0 300 136 Measures_of_genetic_variation Deme_No DemeName DemeSize Alpha Alpha HWP v2 Divers 1 Popi 20 0 2010 0 1170 2 9412 2 Pop2 G 20 0 2010 0 1170 1 9802 3 Pop3 E 20 0 2010 0 1170 2 9851 wrapped deltaT EvnFinAbs EvnFinRel EvnFinNum EvnInfAbs EvnInfRel EvnInfNum 0 6947 0 9500 0 9000 3 0000 0 9333 0 8667 3 0000 0 5211 0 9500 0 9000 2 0000 0 9500 0 9000 2 0000 0 7000 1 0000 1 0000 3 0000 0 9667 0 9333 3 0000 wrapped CjDemSiz DjDemSiz deltaDmS CjEquSiz DjEquSiz deltaEgS 0 3333 0 3250 0 4333 0 3333 0 3250 0 4333 0 3333 0 4750 0 4333 0 3333 0 4750 0 4333 0 3333 0 5000 0 4333 0 3333 0 5000 0 4333 Genetic distance d 0 Deme No 1 2 3
7. Y finite population size Y infinite population size Y Measures of variation between demes Genetic distance d_0 7 Y Subpopulation differentiation D j delta Y subpopulations weighted proportional to deme size 7 Y subpopulations equally weighted 7 Y Test of homogeneity of the deme distributions Y Analysis of genotypic structure Heterozygosity Y Tests of single locus structure Test of Hardy Weinberg structure and heterozygosity Y Test of product structure only if gametic sex is specified Y Options saved in file example txt cfg Deme 1 Population 1 Deme 2 Population 2 Deme 3 Population 3 Demes for output 7 O all demes 1 some demes Option O Output unit S screen F file Option 7 F Width of output min of 75 characters line as number of demes per line No demes line 1 10 No characters line 15 For example O for ALL 3 demes 75 char line 6 for 6 demes 75 chars line as for DIN A4 paper upright 10 for 10 demes 115 chars line as for DIN A4 paper crosswise 11 for 11 demes 125 chars line as in condensed mode Option O Reading input file example txt 3 4 Locus Locus2 Locus3 Locus4 Popi Pop2 Pop3 unformatted 1 0 1 0 2 0 3 0 4 0 1 1 121 121 83 95 118 193 42 42 KA O O 0 4 O O AUNE Rp 44 3 10 132 136 83 83 89106 48 48 45 End of input file Sorting haplotypes Sorting genotypes Calculating and out
8. unknown 0 0 1 Deme 1 2 3 Genotype 1 101 101 76 76 121 193 36 48 2 101 101 d 83 89 106 36 48 gt 3 101 101 16 83 106 166 42 25 gt 4 101 101 ee 106 108 48 ig gt 5 4101 101 83 83 106 106 36 48 gt 6 101 101 83 102 106 195 36 36 T 7 101 121 m 95 89 E 36 T gt 8 101 121 76 95 118 fj 42 ag gt 9 101 121 TTE 89 193 36 48 10 101 121 ie dob 121 D 36 48 gt 11 101 121 85 95 106 193 36 48 12 101 121 83 102 89 T 36 g gt 13 101 121 a 95 89 196 42 ag gt 14 101 136 go 83 106 113 42 g gt 15 101 136 a 95 121 Di 36 b gt 16 101 136 83 102 89 88 36 42 gt 17 101 136 SE did 106 Di 42 48 gt 18 121 121 16 76 121 188 36 ag gt 19 121 121 T6 83 89 153 36 36 20 4121 121 83 83 89 B 36 ad gt 21 121 121 85 95 118 is 42 ag gt 22 4121 136 5 405 106 118 36 ag gt 23 121 136 33 108 106 193 36 36 24 132 132 ix 76 89 42 do gt 73 25 26 2T 28 29 132 132 132 132 1136 132 136 136 136 136 0 89 121 0 89 106 0 89 106 0 121 121 0 118 121 42 48 36 42 48 48 36 48 42 48 Deme Genoty 1 2 3 oO N Q 10 11 12 13 14 15 16 17 18 19 20 21 pe 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 101 121 121 121 121 101 101 101 101 101 101 121 121 121 121 121 121
9. 1 0 0000 2 0 3000 0 0000 3 0 4000 0 6500 0 0000 LOCUS NO 1 Locusi GENOTYPE_FREQUENCIES Absolute_frequency_distribution Deme_No 1 2 3 Type 1 1 3 2 101 101 3 Type 2 2 5 0 101 121 3 Type_3 2 0 3 101 136 70 Type 4 2 2 0 121 Type 5 2 0 0 121 Type 6 0 0 2 132 Type 7 0 0 3 132 Type_8 1 0 0 136 Sum 10 10 10 Relative frequency distribution Deme No 1 2 3 Type 1 0 100 0 300 0 200 Type 2 0 200 0 500 0 000 Type 3 0 200 0 000 0 300 Type 4 0 200 0 200 0 000 Type 5 0 200 0 000 0 000 Type_6 0 000 0 000 0 200 Type_7 0 000 0 000 0 300 Type_8 0 100 0 000 0 000 Measures_of_genetic_variation Deme_No DemeName DemeSize 1 Popi 7 10 2 Pop2 10 3 Pop3 10 wrapped deltaT EvnFinAbs EvnFinRel EvnFinNum 0 9111 1 0000 1 0000 6 0000 0 6889 0 9000 0 8000 3 0000 0 8222 1 0000 1 0000 4 0000 wrapped CjDemSiz DjDemSiz deltaDmS CjEqusiz 0 3333 0 4500 0 6000 0 3333 0 3333 0 6500 0 6000 0 3333 0 3333 0 7000 0 6000 0 3333 wrapped CondHeter 0 6000 0 5556 0 6000 Genetic distance d 0 Deme No 1 2 3 1 0 0000 2 0 5000 0 0000 3 0 7000 0 8000 0 0000 71 121 136 132 136 136 0 0 0 EvnI 0 0 0 DjE 0 0 0 qu qu qu qu qu 101 101 101 121 121 132 132 136 Alpha 3340 3340 3340 nfAbs 9000 8333 9000 qu8iz 4500 6500 7000 101 121 136 121 136 132 136 136
10. Reassembling is not permit ted See the GNU General Public License GPL A copy of the GNU GPL is contained in the file COPYING or see lt www gnu org licenses gt Plot and widget routines DISLIN lt www dislin de gt Compiler GNU Fortran SUSE Linux 4 3 2 gcc 4 3 branch revision 141291 Input file path example txt Date 19 Apr 2010 15 52 46 Deme 1 Popi Deme 2 Pop2 Deme 3 Pop3 Combination No 1 Locus 1 Locusi Locus 2 Locus2 Locus 3 Locus3 Locus 4 Locus4 Abbreviations 0 or E Observed or Expected absolute frequency in a test _ Denotes_multilocus_haplotype_or_genotype NA Denotes_undefinable_parameter_value Gam sex spec Abbreviation_of_ Gametic_sex_specification yes if maternal paternal alleles distinguishable no otherwise alpha All alleles haplotypes genotypes of relative frequency not less than alpha in deme appear in sample with replacement with probability 0 95 alpha HWP As above if genotypes in deme are in Hardy Weinberg Proportions HWP JR hhh E E E Ekk kk kkk kkk k k k k ale dd KK k k K 2K 2K al KK K ade al ode abad KK KK a ok ak Combination_No 1 Locus 1 Locus1 Locus 2 Locus2 Locus 3 Locus3 Locus 4 Locus4 De da de de de da de a de k k kk kk k k k kkk kk k k k k k kkk k k K 2K EEE ak Haplotype_frequencies_not_specifiable Genotype frequencies Deme 1 2 3 Gam sex spec no no no Deme size 10 10 10 No identified 10 10 9 alpha 0 334 0 334 0 334 No
11. The file prefix tab txt contains all frequency distributions and all calculated variation parameters deme by deme Its tabular form allows it to be imported into any spread sheet program by indicating that columns are separated by a single tab character See the example in App G The following list relates the abbreviations used in the tabular output file prefix tab txt with the headings of the output file prefix out txt prefix out txt prefix tab txt Deme No Deme Type_1 Allele or Genotype DemeSize No _identified Alpha alpha Alpha HWP alpha HWP v2 Diver DIVERSITY v 2 deltaT TOTAL POPULATION DIFFERENTIATION delta T EVENNESS e FOR FINITE POPULATION SIZE EvnFinAbs absolute_e EvnFinRel relative e EvnFinNum for No types EVENNESS e FOR INFINITE POPULATION SIZE EvnInfAbs absolute e EvnInfRel relative e EvnInfNum for No types SUBPOPULATION DIFFERENTIATION D j delta RELATIVE SUBPOPULATION SIZE PROPORTIONAL TO DEME SIZE CjDemSiz Cj DjDemSiz Dj deltaDmS delta RELATIVE SUBPOPULATION SIZES ALL EQUAL TO 1 NO SUBPOPS CjEqu8iz Cj DjEquSiz Dj deltaEqs delta 35 4 3 The output directory prefix Snails If the calculation of subpopulation differentiation was selected this directory contains snail graphics of file format WMF Windows Metafile and or EPS Enhanced Postscript See examples in Sec 3 1 The names of the snail files are composed by concatenating one element from each of the following
12. and the frequency N of the allele A in the deme of N paternal alleles equals N x N Conditioning on the allele frequencies in the 9 deme i e assuming that the true frequency p and p of allele A among the maternal and paternal gametes produced in the population equals D N N and p N N respectively the genotypic frequencies expected under the null hypothesis of a product structure equal E Nij NEN N i j 1 k The number of degrees of freedom equals k 1 k 1 where k and k are the numbers of alleles with non zero frequency among maternal and paternal contributions respectively Reference Elandt Johnson 1971 pp 360 f 46 8 Analysis of the gene pool The gene pool of a population with respect to the number L of non homologous gene loci located at a certain section of the genome is thought of as the set of all gene alleles at these loci realized in all individuals Gregorius 1978 The following types of gene pool can be constructed the first two only if gametic sex is specified at all contributing loci e Gene pool of maternal contributions e Gene pool of paternal contributions e Gene pool of single locus genotypes 8 1 Measures of variation within demes 8 1 1 Diversity v of the gene pool Let a collection be characterized at each of L loci by the frequency vector pi pu Pal Pri for I 1 L where n IN and for i 1 n py gt 0 and Mua Pu
13. designated 1 3 4 5 and 6 gametic sex is specified at all loci Population 2 consists of the 4 locus genotypes of the 5 individuals 1 5 gametic sex is specified at loci 1 and 2 but not loci 3 and 4 In Population 3 nine different genotypes were found in a deme of 100 individuals the frequencies of the different genotypes in the deme equalling 32 19 gametic sex is not specified at any locus This constellation of gametic sex specification may not be very realistic but it demonstrates the form of data input and in particular the meaning of the key line see 2 3 1 3 4 LAP A LAP B IDH PGI Population 1 Population 2 Population 3 unformatted 1 O 11 21 31 41 1 113 12 33 23 1 3 31 11 33 22 1 4 31 11 33 22 1 5 11 11 33 22 1 6 33 21 13 33 2 O 11 21 30 40 2 133 12 11 23 2 2 13 21 13 23 2 3 31 11 33 23 2 4 11 11 13 22 2 5 33 12 33 23 3 0 10 20 30 40 3 32 33 12 11 23 3 19 13 12 13 23 3 4 13 11 33 23 3 7 11 11 13 22 3 25 33 12 33 23 3 4 13 11 13 23 3 3 33 12 33 23 3 3 13 11 13 33 3 3 13 12 13 23 57 Example 2 This example shows microsatellite data in which the qdesignation of each allele correspond to its number of amplified base pairs In fact the allele designation in data can be any positive integer The allele designation 1 indicates missing data Gametic sex is not specified as indicated by the 0 following each locus number in the deme speci
14. 000 10 000 9 000 TOTAL POPULATION DIFFERENTIATION delta T Deme 1 2 3 1 000 1 000 1 000 EVENNESS e FOR FINITE POPULATION SIZE Deme 1 2 3 absolute e 1 000 1 000 1 000 relative e 1 000 1 000 1 000 for No types 10 10 9 EVENNESS e FOR INFINITE POPULATION SIZE Deme 1 2 3 absolute e 1 000 1 000 1 000 relative e 1 000 1 000 1 000 for No types 10 10 9 Deme 1 2 3 1 0 000 2 1 000 0 000 3 1 000 1 000 0 000 SUBPOPULATION DIFFERENTIATION D j delta RELATIVE SUBPOPULATION SIZE PROPORTIONAL TO DEME SIZE Deme 1 2 3 Cj 0 345 0 345 0 310 Dj 1 000 1 000 1 000 delta 1 000 SUBPOPULATION DIFFERENTIATION D j delta RELATIVE SUBPOPULATION SIZES ALL EQUAL TO 1 NO SUBPOPS Deme 1 2 3 75 Cj 0 333 0 333 0 333 Dj 1 000 1 000 1 000 delta 1 000 TEST OF HOMOGENEITY Deme 1 2 3 Genotype Sum 1 101 101 76 76 121 193 36 48 10 0 1 0 E 0 34 0 34 0 31 2 101 101 76 83 89 106 36 48 10 0 1 0 E 0 34 0 34 0 31 3 4101 101 76 83 106 106 42 42 10 0 0 1 E 0 34 0 34 0 31 4 101 101 76 102 106 106 48 48 10 0 0 1 E 0 34 0 34 0 31 5 4101 101 83 83 106 106 36 48 10 0 1 0 E 0 34 0 34 0 31 6 101 101 83 102 106 193 36 36 10 1 0 0 E 0 34 0 34 0 31 7 101 121 76 95 89 89 36 48 10 0 1 0 E 0 34 0 34 0 31 8 101 121 76 95 118 121 42 42 10 1 0 0 E 0 34 0 34 0 31 9 101 121 76 102 89 193 36 48 10 0 1 0 E 0 34 0 34 0 31 10 101 121 76 102 121 121 36 48 1
15. 3 Locus3 for Locus 4 Locus4 for gene pool Additional calculations using same input file and locus configuration Option Complete output gt example txt out txt Tabular output gt example txt tab txt Snail diagrams gt In directory example txt Snails Press Return or Enter to terminate program Return 64 F Output file example txt out txt Beginning of the output file for single locus genotypes in the sample input file example txt out txt KKK K K FK FK K K ook ok ok ok ok ok ok K oko ok ok FK ok ok ok K fe ok ok oe oe FK FK K eoe oe K 2K eoe oe oe FK FK FK KK KK FK FK FK oko ok K K KK KK KK KK OK ok K Locus 1 Locus JR k k k ed KK dd 3K 2K 2K 2K K K K 2K 2K 2K EEE ak Deme 1 2 3 Gam sex spec no no no Deme_size 10 10 10 No _identified 10 10 10 alpha 0 334 0 334 0 334 alpha HWP 0 201 0 201 0 201 No _unknown 0 0 0 Deme 1 2 3 Allele 101 6 11 7 121 8 9 0 132 0 0 7 136 6 0 6 20 20 20 Relative_frequency_distribution Deme 1 2 3 Allele 101 0 300 0 550 0 350 121 0 400 0 450 0 000 132 0 000 0 000 0 350 136 0 300 0 000 0 300 Measures_of_variation_within_demes DIVERSITY_v_2 Deme 1 2 3 2 941 1 980 2 985 TOTAL POPULATION DIFFERENTIATION delta T Deme 1 2 3 0 695 0 521 0 700 EVENNESS e FOR FINITE POPULATION SIZE Deme 1 2 3 absolute e 0 950 0 950 1 000 relative e 0 900 0 900 1 000 for No types 3 2 3 EVENNESS e FOR INFINITE POPULATION SIZE Deme 1 2 3 absolute e 0 933 0 950 0 967
16. Execution terminated 19 The following example shows a GSED Interactive input window in which multilocus genotypes comprising loci 2 3 and 4 are to be constructed for demes 1 and 2 ME GSED Interactive input Exit Help SELECT CONFIGURATION SINGLE LOCI OR MULTILOCUS Single locus genetic types Multilocus genetic types LIST OF LOCI 2 3 4 LIST OF DEMES N SELECT CALCULATIONS SHOWING SELECTIONS SAYED IN example txt cfg FREQUENCY DISTRIBUTIONS Maternal allele haplotype frequencies if gametic sex is specified in data Paternal allele haplotype frequencies if gametic sex is specified in data Allelehaplotype frequencies Genotype frequencies Ignore gametic sex if specified in data Include frequency distributions and loss probabilities in output Diversity Total population differentiation deltaT Evenness Genetic distance d0 Subpopulation differentiation Dj delta Test of homogeneity Bei AAR ade VARIATION WITHIN DEMES VARIATION BETWEEN DEMES PER lt lt lt lt lt SI GENOTYPIC STRUCTURE OR If the checkbox Subpopulation differentiation Dj delta in the GSED Interactive input window is marked a window entitled GSED Draw differentiation snails appears Wil GSED Draw differentiation snails Exit FOR SUBPOPULATION DIFFERENTIATION Dj delta Select one or both methods of calculating relative subpopulation sizes Cj iv Proportional to sample size
17. Ie All equal to 1 No of subpopulations Draw subpopulation differentiation snails in one or both of the formats i WMF Windows Metafile iv EPS Enhanced Postscript Under Select one or both methods of calculating relative subpopulation sizes Cj the first option Proportional to sample size is useful if the differing sizes of the demes e g sample total base population are to be considered and All equal to 1 No of subpopulations if deme size is of no interest e g all underlying populations are considered to be of equal size 20 Under Draw subpopulation differentiation snails in one or both of the formats checking WMF Windows Metafile causes each snail to be stored in a vector graphic file in the Metafile format and altered using office programs Microsoft Word Dokument1 TOX l Datei Bearbeiten Ansicht Einf gen Format Extras Tabele Fenster leixi D d SRA BS 0 07 GE BORGES mss Standard y Times New Roman 10 lt F XU ss HE Differentiation enail Equal population sizes Alleles__Locus_1 Doto exomple txt 0 0 delio 0 4333 Bei 2 5 cm Sp2 we fro mw Le Cx 21 Checking EPS Enhanced Postscript stores each snail as an eps file which can be viewed by programs such as ghostview or GSview ds example txt Snail EquPopSiz Alleles__Locus_1 eps GSview File Edit Options View Orientation Media Help 112 ied da eds SCI Differentiation snail Equal
18. R Roberds J H 1986 Measurement of genetical differentiation among subpopulations Theor Appl Genet 71 826 834 http dx doi org 10 1007 BF00276425 Gregorius H R 1987 The relationship between the concepts of genetic diversity and differ entiation Theor Appl Genet 74 397 401 http dx doi org 10 1007 BF00274724 Gregorius H R 1988 The meaning of genetic variation within and between subpopula tions Theor Appl Genet 76 947 951 http dx doi org 10 1007 BF00273686 Gregorius H R 1989 Characterization and Analysis of Mating Systems Ekopan Verlag Witzenhausen http webdoc sub gwdg de ebook y 2001 gregorius matesys pdf 52 Gregorius H R 1990 A diversity independent measure of evenness American Natural ist 136 701 711 http dx doi org 10 1086 285124 Gregorius H R 1996 Differentiation between populations and its measurement Acta Bio theoretica 44 23 36 http dx doi org 10 1007 BF00046433 Gregorius H R 2009 Distribution of variation over populations Theory in Biosciences 128 179 189 http dx doi org 10 1007 s12064 009 0064 1 Gregorius H R Krauhausen J amp M ller Starck G 1986 Spatial and temporal genetic differentiation among the seed in a stand of Fagus sylvatica L Heredity 57 255 262 http dx doi org 10 1038 hdy 1986 116 Hattemer H H Bergmann F amp Ziehe M 1993 Einf hrung in die Genetik f r Studierende der Forstwissenschaft 2 Aufl J D Sauerl nder s
19. Sons Inc New York London Sydney Toronto Emigh T H 1980 A comparison of tests for Hardy Weinberg equilibrium Biometrics 36 627 642 http www jstor org stable 2556115 Gillet E M 1996 Qualitative inheritance analysis of isoenzymes in haploid gametophytes Principles and a computerized method Silvae Genetica 45 8 16 http www bfafh de inst2 sg pdf 45_1_8 pdf Gregorius H R 1974a Genetischer Abstand zwischen Populationen I Zur Konzeption der genetischen Abstandsmessung Silvae Genetica 23 22 27 http www bfafh de inst2 sg pdf 289 1 8 22 pdf Gregorius H R 1974b On the concept of genetic distance between populations based on gene frequencies Proc Joint IUFRO Meeting S02 04 1 3 Stockholm Session I 17 26 Gregorius H R 1978 The concept of genetic diversity and its formal relationship to het erozygosity and genetic distance Math Biosciences 41 253 271 http dx doi org 10 1016 0025 5564 78 90040 8 Gregorius H R 1980 The probability of losing an allele when diploid genotypes are sam pled Biometrics 36 643 652 http www jstor org stable 2556116 Gregorius H R 1984a A unique genetic distance Biometrical Journal 26 13 18 http dx doi org 10 1002 bimj 4710260103 Gregorius H R 1984b Measurement of genetic differentiation in plant populations Pp 276 285 in Gregorius H R ed Population Genetics in Forestry Springer Verlag Berlin Heidelberg New York Tokyo Gregorius H
20. and paternal haplotype 4 1 2 see Tab 4 Obtaining unordered genotypes when gametic sex is specified Note that if gametic sex is specified and the response to the question Should gametic sex specification if given be retained is Y see 3 2 then the ordered genotype frequency distribution will be calculated and all measures will be based on this distribution In order to obtain the unordered distribution and measures calculated for it GSED must be restarted using the same input file but a reply of N must be given to the above question Gene pool If all of the locus combinations that were chosen for calculation were single loci then the gene pool made up of the genes at these loci is automatically constructed This will be the case if option 0 or 1 was given in answer to Locus configuration of 38 the interactive sequence see 3 2 Although the frequency distribution of the gene pool is not explicitly included in the output all of the chosen measures of variation within and between demes are also calculated for the gene pool see 8 and listed at the end of the output Unknown alleles and genotypes Sometimes it is not possible to determine the genotype or if gametic sex is specified one of the parental contributions to an individual at one or more of the investigated loci In this case it is up to the user to make sure that the unknown types represent random demes of the respective types in the p
21. following line of data namely 2 193 110 0 4 33 2123 12 23 35 21 23 21 11 11 22 33 Example 2 20 14 14 10 212 9X 10 212 reads 42 integers including a 20 locus genotype from the following two lines of data 2 2345 9 1 0 ld 22345 21 23 24 22 33 11 21 21 23 21 32 33 12 23 23 31 32 23 32 11 2 3 Deme data The third part of an input file consists of the deme data t e a block of data lines for each of the demes Allele designations or names must be non negative integers The allele 0 is meant to denote a null allele if its presence can be determined A missing allele is denoted by 1 Alleles can thus be designated as 1 2 3 as is common for isoenzymes or for example as the numbers of base pairs 101 122 143 of microsatellite alleles Deme data specifies the single locus or multilocus genotypes or haplotypes in each deme see Tab 3 Specification of diploid genotypes requires knowledge of both alleles at the locus i e which in general necessitates the codominance of the mode of inheritance see Gillet 1996 If the gametic sex of the alleles making up a single locus genotype is known such as for the combined megagametophyte embryo analysis of conifer seeds the genotypes can be designated as ordered genotypes in this case the maternal allele is listed first and the paternal allele second Organelle cytotypes can be specified as ordered genotypes in which the allele of
22. genotype causes the individual to be ignored in calculations 1 3 Implementation GSED reads input data from a text file that was prepared using an editor or spreadsheet The user interactively chooses which frequency distributions are determined from the data and which calculations are performed In this newest version of GSED two interactive modes are provided 1 Menu directed choice of input file genetic structures measures and tests 2 alternatively those who prefer keyboard entry may choose to answer queries as in earlier versions of GSED T wo text files are produced as output one of which contains the complete output The other lists the measures of variation in a compact form that is designed to be imported into a spreadsheet program e g Excel OpenOffice GSED is written in FORTRAN and compiled using a GNU Fortran95 compiler Executables for the operating systems Win and Linux openSUSE 11 1 are available for downloading at http www uni goettingen de de 95607 html Version 3 0 of GSED contains several major improvements over earlier versions 1 Menu directed choice of options 2 sim plification of the format of the input data file and the allowance for commentary lines 3 improvement of the importability of the tabular output file into spreadsheet programs 1 4 Organization of this manual The following sections 2 3 4 of this manual deal with practical matters namely con struction of an input file execution of
23. gsed Return The following graphics illustrate execution in WinXP In Linux similar windows appear 14 First a console window opens that shows the GSED header including the version numbers of GSED and the FORTRAN compiler sw C Dokumente und Einstellungen All Users Dokumente gsed30 gsed exe lolx DE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE DE JE JE JE JE JE JE J GGGGGGG SSSSSSS EEEEEEE DDDDDD Genetic G S E D D Structures S 3 D from SSSSSSS EEEE D Electrophoresis GGGG S E D D Data D S E D D Version 3 0beta GGGGGGG SSSSSSS EEEEEEE DDDDDD April 2010 XX XX XX DE JE E XC JE JE JE JE JE JE JE DE JE JE JE JE JE JE JE JE JE JE DE JE JE JE JE JE JE JE JE JE JE JE JE JE JE JE DE JE JE JE JE JE JE JE JE JE JE DE JE JE JE JE JE JE JE JE JE JE JE DE JE JE HH DE DE N GSED Copyright 1990 2010 Elizabeth M Gillet egillet gwdg de GSED is free software you can redistribute it under the terms of the GNU General Public License GPL v 3 as published by the Free Software Foundation GSED is distributed in the hope that it will be useful but WITHOUT ANY WARRANTY without even the implied warranty of merchant ability or fitness for a particular purpose Reassembling is not permit ted See the GNU General Public License GPL A copy of the GNU GPL is contained in the file COPYING or see lt
24. observed structures to the corresponding expected structures under certain models of association 7 1 Heterozygosity 7 1 1 Proportion of heterozygosity of single locus genotypes Given the genotypes of all individuals in a collection at a single gene locus the proportion of heterozygosity equals the proportion of heterozygous individuals in the collection Reference Gregorius Krauhausen M ller Starck 1986 7 1 2 Conditional heterozygosity of single locus genotypes The conditional heterozygosity at a single gene locus takes into account that the pro portion of heterozygosity is conditional on the allele frequencies It results from division of the actual heterozygosity proportion of heterozygosity at a single locus by the corre sponding maximum proportion of heterozygosity Hmax obtainable for the underlying allele frequencies where Hmax equals 1 if all allele frequencies are less than or equal to 0 5 and Hmax 2 1 p if the most frequent allele has frequency p greater than 0 5 References Gregorius 1978 Gregorius Krauhausen M ller Starck 1986 7 1 3 Degree of heterozygosity of multilocus genotypes The degree of heterozygosity is defined for an individual with respect to a specified number of gene loci and is identical to the proportion of loci at which this individual is heterozygous The average degree of heterozygosity refers to the distribution of this degree in a collection of individuals Hence it can be prov
25. population sizes Alleles Locus 1 Data example txt d 0 0 delta 0 4333 EquPopSiz Alleles Locus 1 eps Page 1 1of1 Upon completion of all calculations a message window appears that shows the names of the output files GSED Output files Complete output gt C Dokumente und EinstellungentAll Users Dokumente gsed30 example txt out txt Tabular output gt C Dokumente und Einstellungen Users Dokumente gsed30 example txt tab txt Snail diagrams gt In directory C Dokumente und Einstellungen MI Users Dokumente gsed30 example txt Snails 22 At the same time the console window contains the following text 41 101 101 42 132 132 43 101 136 44 1 132 136 45 End of input file Sorting haplotypes Sorting genotypes Calculating and outputting results for Locus 1 Locus1 for Locus 3 Locus3 for Locus 4 Locus for_gene_pool Complete output gt C Dokumente und Einstellungen All Users Dokumente gsed30 e xample txt out txt Tabular output gt C Dokumente und Einstellungen All Users Dokumente gsed30 e xample txt tab txt Snail diagrams gt In directory C Dokumente und Einstellungen All Users Dokum ente gsed30 example txt Snails xx Press Return or Enter to terminate program xx To terminate execution press Return or Enter in the console window The output files example txt out txt and example txt tab txt and the directory example txt Snail
26. the bulk seed of a stand of a conifer species and subjecting only the primary endosperm of each seed to isoenzyme electrophoresis see 5 The specification of gametic sex is indicated by the 1 following each locus number in the deme specification line The unknown paternal contribution at each locus is designated by 1 1 4 Locus Locus Locus Locus Scots pine forest 4 2i4 4 13 i12 11 21 BQWN KA f LO K C O 1 1 1 1 1 9 60 D Keyboard driven execution for first run This example of keyboard input shows the first run of GSED for an input file named example txt GSED heading Enter name of input file max 256 characters example txt Enter prefix for names of output files default example txt Return Locus 1 LAP A Locus 2 LAP B Deme 1 Population 1 Locus 3 IDH Deme 2 Population 2 Locus 4 PGI Deme 3 Population 3 Locus configuration O all single loci 2 multilocus some loci 1 some single loci 3 multilocus all loci Choice of frequency distributions Answer Y yes or N no Allele haplotype frequencies among maternal contributions N Allele haplotype frequencies among paternal contributions N Allele haplotype frequencies Y Genotype frequencies Y Choice of calculations Answer Y yes or N no Frequency distributions Y Measures of variation within demes Diversity v_2 Y Total population differentiation delta T Y Evenness
27. the program and understanding the output The following four sections 5 6 7 8 are concerned with the concepts behind the program The first of these sections 5 reviews the different types of frequency distribution that can be calculated from demes of multilocus genotypes Three sections 6 7 8 outline the measures and tests that are performed for the various frequency distributions including references to mostly original articles containing detailed descriptions of the underlying concepts A list of references follows denoted in the text by numbers in square brackets Appendices contain technical specifications compiler limitations on data and examples of input and output files lusing graphical user interface GUI routines from the scientific data plot software DISLIN Michels 2009 2 Constructing an input file A GSED input file is constructed using any text editor word processor or spreadsheet pro gram The input file must contain only ASCII characters which means that any formatting information must be eliminated before running GSED e Simple text editors automatically save the data in the correct form as a text only file with default extension txt e For word processors formatting information is eliminated by saving the input as a text file usually with extension txt e For spreadsheets each line of input can be constructed by putting each piece of data name or number into a field of its own After saving
28. www gnu org licenses gt Compiler GNU Fortran SUSE Linux 4 3 2 gcc 4_3 branch revision 141291 Date 07 Apr 2010 17 40 28 15 Then a File Select window opens requesting the name of the input file The input file need not be in the same directory as the executable gsed exe Win or gsed Linux For illustration purposes we clicked on the input file example txt that is included in the download package Select input file Suchen in gsed30 Rek 4 esp exe 5 Zuletzt verwendete Dok Eigene Dateien Dateiname example t4 gt Dateityp Mask v Abbrechen Schreibgeschiitzt ffnen Bibeisplate Ed Neiswerbumnsbu Then a window entitled GSED Prefix for output files opens It suggests that the name of the input file be used as a prefix for the names of all output files If desired a different prefix can be typed in The prefix is submitted by clicking on the OK button Wil GSED Input prefix for output files Exit INPUT FILE CADokumente und EinstellungentAll UsersiDokumentelgsed30 example txt PREFIX FOR OUTPUT FILES ap Y 16 If an output file named with the chosen prefix followed by out txt already exists a window entitled GSED Check existence of output files using prefix opens Hi GSED Check existence of output files using prefix Exit OUTPUT FILE ALREADY EXISTS example txt out txt SELECT OPTION Overwrite existing output f
29. 0 overwrite old output P enter new prefix Option To overwrite the previous contents of the file which are thus lost enter the following note that this option is indicated by the letter 0 and not the numeric character 0 zero Option O To choose a different prefix for the output files enter the following Option P If the option is P then the following line appears Enter new prefix for output files in which case one enters a new prefix such as xxx This is followed by Width of output min of 75 characters line as number of demes per line 7 No demes line 1 10 No characters line 15 For example O for ALL 3 demes 75 char line 6 for 6 demes 75 chars line as for DIN A4 paper upright 10 for 10 demes 115 chars line as for DIN A4 paper crosswise 11 for 11 demes 125 chars line as in condensed mode Option O 28 The width of the output medium e g paper can vary and with it the number of demes that fit onto one line If the available number of characters per line is known the formula on the second line above yields the maximal number of demes rounding down to the nearest integer if necessary If not all of the demes fit onto one line the tables of results are cut off after the specified number of demes and continued on the next lines of output The minimum number of characters per line is set to 75 One reason is that this is the length of the comme
30. 0 0 1 0 E 0 34 0 34 0 31 11 101 121 83 95 106 193 36 48 10 0 1 0 E 0 34 0 34 0 31 12 101 121 83 102 89 193 36 48 10 0 1 0 E 0 34 0 34 0 31 13 101 121 95 95 89 106 42 48 10 1 0 0 E 0 34 0 34 0 31 14 101 136 83 83 106 193 42 48 10 1 0 0 E 0 34 0 34 0 31 15 101 136 83 95 121 121 36 42 10 0 0 1 E 0 34 0 34 0 31 16 i101 136 83 102 89 89 36 42 10 0 0 1 E 0 34 0 34 0 31 17 i101 136 95 102 106 121 42 48 10 1 0 0 E 0 34 0 34 0 31 18 121 121 76 76 121 193 36 42 10 0 1 0 N c E 0 34 0 34 0 31 19 121 121 76 83 89 193 36 36 10 1 0 0 E 0 34 0 34 0 31 20 121 121 83 83 89 89 36 42 10 0 1 0 E 0 34 0 34 0 31 21 121 121 83 95 118 193 42 42 10 1 0 0 E 0 34 0 34 0 31 22 121 136 83 102 106 118 36 42 10 1 0 0 E 0 34 0 34 0 31 23 121 136 83 102 106 193 36 36 10 1 0 0 E 0 34 0 34 0 31 24 132 132 76 76 89 89 42 42 10 0 0 1 E 0 34 0 34 0 31 25 132 132 95 95 89121 42 48 10 0 0 1 E 0 34 0 34 0 31 26 132 136 76 83 89106 36 42 10 0 0 1 E 0 34 0 34 0 31 27 132 136 83 83 89106 48 48 10 0 0 1 E 0 34 0 34 0 31 28 132 136 95 95 121 121 36 48 10 0 0 1 E 0 34 0 34 0 31 29 136 136 76 95 118 121 42 48 TL 10 1 0 0 E 0 34 0 34 0 31 29 10 10 9 Level of C V of CHI 2 Test statistics significance DF 56 G 63 650 n s 0 050 74 468 Xxx2 58 000 n s 0 010 83 513 0 001 xxx 94 461 Heterozygosity Deme 1 2 3 Deme size 10 10 10 No identified 10 10 9 No unknow
31. 0 000 0 100 0 000 Type_6 0 100 0 000 0 000 Type_7 0 000 0 100 0 000 Type_8 0 100 0 000 0 000 Type_9 0 000 0 100 0 000 Type_10 0 000 0 100 0 000 Type_11 0 000 0 100 0 000 Type_12 0 000 0 100 0 000 Type_13 0 100 0 000 0 000 Type 14 0 100 0 000 0 000 Type_15 0 000 0 000 0 111 Type_16 0 000 0 000 0 111 Type_17 0 100 0 000 0 000 Type_18 0 000 0 100 0 000 Type_19 0 100 0 000 0 000 Type_20 0 000 0 100 0 000 Type_21 0 100 0 000 0 000 Type_22 0 100 0 000 0 000 Type_23 0 100 0 000 0 000 Type_24 0 000 0 000 0 111 Type_25 0 000 0 000 0 111 Type_26 0 000 0 000 0 111 Type_27 0 000 0 000 0 111 Type_28 0 000 0 000 0 111 Type_29 0 100 0 000 0 000 Measures_of_genetic_variation Deme_No DemeName 1 n Pop 1 2 n Pop2 3 n Pop3 wrapped deltaT EvnFinAbs EvnFinRel 1 0000 1 0000 1 0000 1 0000 1 0000 1 0000 1 0000 1 0000 1 0000 wrapped CjDemSiz DjDemSiz deltaDms 0 3448 1 0000 1 0000 0 3448 1 0000 1 0000 0 3103 1 0000 1 0000 Genetic distance d 0 Deme No 1 2 1 0 0000 2 1 0000 0 0000 3 1 0000 1 0000 ut 101 101 101 101 101 101 101 101 101 101 101 101 101 121 121 121 121 121 121 132 132 132 132 132 136 136 DemeSize 10 10 9 EvnFinNum 10 0000 10 0000 9 0000 CjEquSiz 0 3333 0 3333 0 3333 0 0000 80 83 83 106 106 36 48 Ln 83 102 106 193 36 36 1 76 95 89 89 36 48 Ln 76 95 118 1
32. 01 101 83 102 106 193 36 36 J Type 7 0 1 0 101 121 76 95 89 89 36 48 Type 8 1 0 0 101 121 76 95 118 121 42 42 Jj Type 9 0 1 0 101 121 TG 102 89 193 36 48 Type 10 0 1 0 101 121 TG 102 121 121 36 48 Type 11 0 1 0 101 121 83 95 106 193 36 48 Type 12 0 1 0 101 121 83 102 89 193 36 48 Type 13 1 0 0 101 121 95 95 89 106 42 48 Ln Type 14 1 0 0 101 136 83 83 106 193 42 48 Type 15 0 0 1 101 136 83 95 121 121 36 42 Type 16 0 0 1 101 136 83 102 89 89 36 42 Type 17 1 0 0 101 136 95 102 106 121 42 48 Type_18 0 1 0 121 121 76 76 121 193 36 42 Type 19 1 0 0 121 121 76 83 89 193 36 36 Type 20 0 1 0 121 121 83 83 89 89 36 42 Type 21 1 0 0 121 121 83 95 118 193 42 42 Type 22 1 0 0 121 136 83 102 106 118 36 42 Type 23 1 0 0 121 136 83 102 106 193 36 36 Type 24 0 0 1 132 132 76 76 89 89 42 42 Type_25 0 0 1 132 132 95 95 89 121 42 48 Type 26 0 0 1 132 136 76 83 89 106 36 42 Type 27 0 0 1 132 136 83 83 89 106 48 48 Ln Type 28 0 0 1 132 136 95 95 121 121 36 48 Type 29 1 0 0 136 136 76 95 118 121 42 48 Ln Sum 10 10 9 Relative frequency distribution Deme No 1 2 3 Type 1 0 000 0 100 0 000 101 101 76 76 121 193 36 48 J Type 2 0 000 0 100 0 000 101 101 76 83 89 106 36 48 Type_3 0 000 0 000 0 111 101 101 76 83 106 106 42 42 Type 4 0 000 0 000 0 111 101 101 76 102 106 106 48 48 Ln 79 Type 5
33. 1 Denoting by E E va gt i i l the allelic diversity at the th locus the gene pool genic diversity v of the collection was proved to equal the harmonic mean of the single locus diversities t e 1 1 L U E Em ia EES ps Reference Gregorius 1987 8 1 2 Diversity vgam of the hypothetical gametic output Let a collection be characterized at locus 1 L by the frequency vector pi Pu Pot Pri Where n IN and fori 1 n py gt 0 and 35 py 1 Denoting by n 1 va Y i i l the allelic diversity at the th locus the hypothetical gametic diversity vgam of the collection is defined as vgam Ivo l 1 47 The hypothetical gametic output is defined by the set of gametes that results from stochas tically independent association between loci free recombination and equal gametic produc tion for all members vgam therefore measures the potential of a population for producing genetically diverse gametes Reference Gregorius 1978 8 1 3 Total population differentiation r of the gene pool Let a collection of subpopulations have the total population differentiation dr at locus 1 L Then the total population differentiation r of the gene pool was proven to equal the arithmetic mean of the total population differentiation at each locus that is Reference Gregorius 1987 8 2 Measures of variation between demes 8 2 1 D
34. 121 136 136 136 136 121 121 121 121 76 83 76 102 0 000 83 83 0 000 83 102 0 100 76 95 0 000 76 95 0 100 76 102 0 000 76 102 0 000 83 95 0 000 83 102 0 000 95 95 0 100 83 83 0 100 83 95 0 000 83 102 0 000 95 102 0 100 76 76 0 000 76 83 0 100 83 83 83 95 0 100 121 193 0 100 89 106 0 100 106 106 0 000 106 106 0 000 106 106 0 100 106 193 0 000 89 89 0 100 118 121 0 000 89 193 0 100 121 121 0 100 106 193 0 100 89 193 0 100 89 106 0 000 106 193 0 000 121 121 0 000 89 89 0 000 106 121 0 000 121 193 0 100 89 193 0 000 89 89 0 100 118 193 0 000 36 48 0 000 36 48 0 000 42 42 0 111 48 48 0 111 36 48 0 000 36 36 0 000 36 48 0 000 42 42 0 000 36 48 0 000 36 48 0 000 36 48 0 000 36 48 0 000 42 48 0 000 42 48 0 000 36 42 0 111 36 42 0 111 42 48 0 000 36 42 0 000 36 36 0 000 36 42 0 000 42 42 0 000 74 o x v Y CP yyy Ye YY YY YY e YY YY YY YY o 22 121 136 83 102 106 118 36 42 0 100 0 000 0 000 23 121 136 83 102 106 193 36 36 0 100 0 000 0 000 24 132 132 76 76 89 89 42 42 0 000 0 000 0 111 25 132 132 95 95 89121 42 48 TL 0 000 0 000 0 111 26 132 136 76 83 89106 36 42 0 000 0 000 0 111 27 132 136 83 83 89106 48 48 0 000 0 000 0 111 28 132 136 95 95 121 121 36 48 0 000 0 000 0 111 29 136 136 76 95 118 121 42 48 TL 0 100 0 000 0 000 DIVERSITY v 2 Deme 1 2 3 10
35. 132 x 132 0 0 2 132 x 136 0 0 3 136 x 136 1 0 0 10 10 10 Relative_frequency_distribution Deme 1 2 3 Genotype 101 x 101 0 100 0 300 0 200 101 x 121 0 200 0 500 0 000 101 x 136 0 200 0 000 0 300 121 x 121 0 200 0 200 0 000 121 x 136 0 200 0 000 0 000 132 x 132 0 000 0 000 0 200 132 x 136 0 000 0 000 0 300 136 x 136 0 100 0 000 0 000 Measures_of_variation_within_demes DIVERSITY_v_2 Deme 1 2 3 5 556 2 632 3 846 TOTAL POPULATION DIFFERENTIATION delta T Deme 1 2 3 0 911 0 689 0 822 EVENNESS e FOR FINITE POPULATION SIZE Deme 1 2 3 absolute e 1 000 0 900 1 000 relative e 1 000 0 800 1 000 for No types 6 3 4 EVENNESS e FOR INFINITE POPULATION SIZE Deme 1 2 3 absolute e 0 900 0 833 0 900 relative e 0 800 0 667 0 800 for No types 5 3 4 67 GENETIC DISTANCE d 0 Deme 1 2 3 1 0 000 2 0 500 0 000 3 0 700 0 800 0 000 SUBPOPULATION DIFFERENTIATION D j delta RELATIVE SUBPOPULATION SIZE PROPORTIONAL TO DEME SIZE Deme 1 2 3 Cj 0 333 0 333 0 333 Dj 0 450 0 650 0 700 delta 0 600 SUBPOPULATION_DIFFERENTIATION_D_j _delta RELATIVE_SUBPOPULATION_SIZES_ALL_EQUAL_TO_ 1 NO _SUBPOPS Deme 1 2 3 Cj 0 333 0 333 0 333 Dj 0 450 0 650 0 700 delta 0 600 TEST_OF_HOMOGENEITY Deme 1 2 3 Genotype Sum 101 x101 6 0 1 3 2 E 2 00 2 00 2 00 101 x121 70 2 5 0 E 2 33 2 33 2 33 101 x136 50 2 0 3 E 1 67 1 67 1 67 121 x121 40 2 2 0 E 1 33 1 33 1 33 121 x136 20 2 0 0 E 0 67 0 67 0 67 1
36. 21 42 42 76 102 89 193 36 48 Ln 76 102 121 121 36 48 Ln 83 95 106 193 36 48 Ln 83 102 89 193 36 48 Ln 95 95 89106 42 48 Jj 83 83 106 193 42 48 Jj 83 95 121 121 36 42 83 102 89 89 36 42 95 102 106 121 42 48 Jj 76 76 121 193 36 42 76 83 89 193 36 36 1 83 83 89 89 36 42 83 95 118 193 42 42 y 83 102 106 118 36 42 83 102 106 193 36 36 1 76 76 89 89 42 42 y 95 95 89 121 42 48 Jj 76 83 89 106 36 42 83 83 89 106 48 48 Jj 95 95 121 121 36 48 Ln 76 95 118 121 42 48 Jj Alpha v2 Divers 0 3340 10 0000 0 3340 10 0000 0 3340 9 0000 EvnInfAbs EvnInfRel EvninfNum 1 0000 1 0000 10 0000 1 0000 1 0000 10 0000 1 0000 1 0000 9 0000 DjEquSiz deltaEqS MeanHeter 1 0000 1 0000 0 7250 1 0000 1 0000 0 6750 1 0000 1 0000 0 5000
37. 3 eps BKB PostScript N example txt Snai SmpPopSiz Alleles_Locus_3 wmf 12KB WMF Bild Bilexample txt Snail SmpPopSiz Alleles_Locus_4 eps BKB PostScript jexample txt Snai SmpPopSiz Alleles__Locus_4 wmmf 11KB WMF Bild J example bxt Snai SmpPopSiz Genotypes__Locus_1 eps 10 KB Postscript Dexample txt Snail SmpPopSiz Genotypes_Locus_1 wmf 13KB WMF Bild example txt Snail SmpPopSiz Genotypes__Locus_2 eps 9KB PostScript SJexample txt Snai SmpPopSiz Genotypes__Locus_2 wmf 12KB WMF Bild J example txt snal SmpPopSiz Genotypes Locus 3 eps 10KB Postscript IS example txt snal SmpPopSiz Genotypes Locus 3 wmf 14KB WMF Bild A example txt Snai SmpPopSiz Genotypes__Locus_4 eps 10 KB PostScript example txt Snail SmpPopSiz Genotypes__Locus_4 wmf 14KB VVMF Bid lilt 24 3 2 Reyboard driven execution In keyboard driven execution of GSED the user answers a sequence of questions through the keyboard An example is given in App D After specifying a preconstructed input file see Sec 2 the user may choose any or all of the frequency distributions listed in Tab 1 and request calculation of any of the measures and tests listed in Tab 2 Additional questions concern the format of the output After all questions have been answered GSED performs the desired calculations Results can either be written into an output file or typed on the screen Start keyboard driven execution of GSED by opening a console window and typing gt gsed nomenu Return
38. 32 x132 20 0 0 2 E 0 67 0 67 0 67 132 x136 30 0 0 3 E 1 00 1 00 1 00 136 x136 10 1 0 0 E 0 33 0 33 0 33 30 10 10 10 Level of C V of CHI 2 Test statistics significance DF 14 G 33 129 xx 0 050 23 685 X 2 27 229 0 010 29 141 0 001 Ge 36 123 Xoekeek WARNING gt xxxxx lt WARNING gt xxxxx lt WARNING gt xxxxx lt WARNING xeekekek Test statistics are inflated due to expected frequencies less xx xx than 5 and may falsely recommend rejection of hypothesis xx xx Suggestion Pool alleles in input data and recalculate xx xkxxxx lt WARNING gt xxxxx lt WARNING gt xxxxx lt WARNING gt xxxxx lt WARNING gt xx x x Deme size 10 10 10 No identified 10 10 10 No unknown 0 0 0 PROPORTION OF HETEROZYGOSITY Deme 1 2 3 0 600 0 500 0 600 CONDITIONAL HETEROZYGOSITY Deme 1 2 3 0 600 0 556 0 600 EEEE EK k k k k k kk kk k k k 2k 2k k Kk K k 2k 2K 2K 2K K K k dde KK ok Locus 1 Locus Deme 1 Popi SRI oko ok ok K 2K 2K 2K 2K 2K K K al ed dead ld al K K al ade lod ae KK e K KK a ok ak Deme_size 10 No _individuals_of_identified_genotype 10 No _individuals_of_unknown_genotype 0 Allele 101 121 136 Freq 101 0 1 2 2 6 E 0 90 2 40 1 80 121 0 2 2 8 E 1 60 2 40 136 0 1 6 E 0 90 20 Level of C V of CHI 2 Test statistics significance DF 3 G 0 277 n s 0 050 7 815 X 2 0 278 n s 0 010 11 345 0 001 Geox 16 266 Homozygote excess over Hardy Weinberg expectation
39. G S ED Version 3 0 Genetic Structures from Electrophoresis Data User s Manual April 2010 http www uni goettingen de de 95607 html Elizabeth M Gillet Abteilung Forstgenetik und Forstpflanzenz chtung Universitat Gottingen B sgenweg 2 37077 G ttingen Germany Email egillet gwdg de GSED Version 3 0 User s Manual April 2010 Elizabeth M Gillet Abt Forstgenetik u Forstpflanzenz chtung Univ G ttingen 1994 2010 All rights reserved Revision of GSED User s Manual of April 1998 E M Gillet Download at URL http www uni goettingen de de 95607 html Author Elizabeth M Gillet Abt Forstgenetik und Forstpflanzenz chtung Universitat Gottingen Busgenweg 2 37077 Gottingen Germany Email egillet gwdg de Contents 1 Introduction 1 1 1 Genetic structures and their characterization 2 2 2 2 Q LL LL LL LL 1 1 2 Requirements on the data 04 921467 ue ae Er S SEO SS 4 1 3 Implementation 6 4 Ed Ar ivi qr ES eh acu ae e P ae ay qup he is 5 1 4 Organization of this manal 5 2 Constructing an input file 6 21 Headers ou A a A e es Rex EE a EE A 6 2 2 READ format line pe moo ee Red LE PS 7 al Unformatted IPUR ap eed 7 429 RormattediNput Ams EAS e AA T 23 Deme TTT 9 2 3 1 Deme specification line ue due donee wer ae ar en 9 2 3 2 Genotypes of single individuals 12 2 3 3 Genotype frequencies in deme 12 2 3 4 End of deme li
40. Iw of the first field defined by the FORTRAN READ format see 2 2 2 An end of deme line can but need not be followed by any number of empty lines before beginning the data for the next deme 2 4 End of input Reading of the input file terminates when no further data 7 e non empty lines follows an end of deme line 13 3 Running GSED 3 1 Menu driven execution Version 3 0 of GSED introduces the option of menu driven execution thanks to rou tines provided by the scientific data plotting software DISLIN of H Michels http www dislin de To date GSED has been compiled for WinXP and openSUSE http www uni goettingen de de 95607 html In Windows menu driven execution is started either by clicking on the file name gsed exe in a file manager MY esed30 Datei Bearbeiten Ansicht Favoriten Extras 2 r Q ari OB Osuchen ode fr Adresse l C Dokumente und Einstellungen All Users Dokumente gsed30 v Wechseln zu Mame a Gr e Typ Datei und Ordneraufgaben E example txt 2KB Textdokument 1 902KB Anwendung Andere Orte Details or by opening a console window changing the current directory to the one containing the file gsed exe and entering at the cursor gt gsed Return In Linux either click on the file gsed exe in a file manager or start execution of GSED by opening a console window changing the current directory to the one containing the file gsed and entering at the cursor gt
41. LU N HL Examples demonstrating designation of alleles haplotypes and genotypes in DO OU DOL 246 RE Ed ds o OE PERE P LE RDA EE ped 1 Introduction The purpose of GSED Genetic Structures from Electrophoresis Data is to characterize the genetic variation observed in one or more demes of individuals of the same species e g populations stands ontogenetic stages generations Alleles can be coded by any non negative integers thus allowing for the designation of microsatellite alleles by their numbers of base pairs For any combination of gene loci and any of the genetic structures i e frequency distributions that can be constructed from the alleles haplotypes gene pools or genotypes at any combination of loci in the demes see Table 1 GSED calculates measures of genetic variation see Table 2 These variation measures are based on a conceptually and mathematically unified system of data analysis for population genetic investigations that has been and continues to be developed at the Institut f r Forstgenetik und Forstpflanzenz chtung of the Universitat G ttingen and at the Institut f r Populations und kologische Genetik http www ipoeg de in G ttingen Table 1 Genetic structures calculated by GSED Single locus Allele frequencies among maternal contributions Allele frequencies among paternal contributions Allele frequencies Genotype frequencies Multilocus Haplotype frequencies among maternal contributions
42. Verlag Frankfurt am Main Jost L 2008 Gyr and its relatives do not measure differentiation Molecular Ecology 17 4015 4026 http dx doi org 10 1111 3j 1365 294X 2008 03887 x Kim Z S 1985 Viability selection at an allozyme locus during development in European beech Fagus sylvatica L Silvae Genetica 34 181 186 http www bfafh de inst2 sg pdf 34 4 5 181 pdf Ledwina T Gnot S 1980 Testing for Hardy Weinberg equilibrium Biometrics 36 161 165 http www jstor org stable 2530507 Louis E J Dempster E R 1987 An exact test for Hardy Weinberg and multiple alleles Biometrics 43 805 811 http www jstor org stable 2531534 Michels H 2009 DISLIN Scientific Plotting Software Helmut Michels Max Planck Institut f r Sonnensystemforschung Katlenburg Lindau http www dislin de M ller Starck G 1977a Untersuchungen ber die nat rliche Selbstbefruchtung in Best nden der Fichte Picea abies L Karst und Kiefer Pinus sylvestris L Silvae Genetica 26 207 217 http www bfafh de inst2 sg pdf 26 5 6 207 pdf Miiller Starck G 1977b Cross fertilization in a conifer stand inferred from enzyme gene markers in seeds Silvae Genetica 26 223 226 http www bfafh de inst2 sg pdf 26 5 6 223 pdf Pamilo P Varvio Aho S 1984 Testing genotype frequencies and heterozygosities Marine Biology 79 99 100 http dx doi org 10 1007 BF00404990 Robertson A Hill W G 1984 Deviations from Hardy Weinb
43. a T Allelefhaplotype frequencies Genotype frequencies Ignore gametic sex if specified in data Include frequency distributions and loss probabilities in output Diversity Total population differentiation deltaT Evenness Genetic distance d0 Subpopulation differentiation Dj delta Test of homogeneity Heterozygosity Test of Hardy Weinberg structure heterozygosity single locus VARIATION WITHIN DEMES VARIATION BETWEEN DEMES GENOTYPIC STRUCTURE Part 1 SELECT CONFIGURATION In the option SINGLE LOCI OR MULTILOCUS the preset choice of Single locus genetic types results in calculation of parameters for each single locus and for the gene pool defined by all of these loci Choice of Multilocus genetic types causes all parameters to be calculated for genetic types defined by their genes at multiple loci For example the two locus genetic types 44 4 B B and Aj A B B are considered as being completely different even though they share 3 of the 4 genes The next option LIST OF LOCI is preset to All n loci where n is the number of loci in the input file If not all loci are to be chosen change the preset text to a list of the desired loci separated by blanks or commas e g 2 3 4 or 2 3 4 see next window The next option LIST OF DEMES is preset to All m demes where m is the number of demes in the input file If not all demes are to be chosen change the pres
44. allele if its presence can be determined All integers are of type INTEGER 4 and range between 2147483647 and 2147483647 Real numbers are of single precision type REAL with approximately 7 digit accuracy and range from 10738 to 10 5 The output formats accomodate 5 digit integers up to 99999 and floating point numbers with up to 5 digits in front of the decimal point Floating point calculations are printed with 3 decimal places The one exception is the expected absolute frequencies in tests which have two decimal places GSED currently allows a maximum of MXALL 250 different allele designations or names across loci For example if alleles 200 201 and 202 are found at locus 1 over all demes and if 200 210 and 220 occur at locus 2 in all demes then there are five designations namely 200 201 202 210 and 220 Statistical tests can be performed for a maximum of 100 degrees of freedom An encounter of more degrees of freedom does not cause termination of the program If the expected value in any cell is less than 5 a warning is printed Smaller expected values can inflate the X and G test statistics resulting in the erroneous indication of significant deviation from the hypothesis as compared to an exact test 95 B The example input file example txt The following sample input file is used throughout the manual The genotypes at all 4 loci are unorde
45. at line All data in the deme specification line and the genotype lines are integers In particular the allele designations or names must be non negative integers No non numeric letters are permitted The allele designation 0 is meant to denote a null allele if its presence can be determined The READ format line of an input file specifies how the integers in the deme specification line and the genotype lines are to be read see 2 3 It can have one of two forms 2 2 1 Unformatted input If each integer in the genotype lines is followed by a field separator blank comma or tab character as in CSV files the READ format line can simply be specified by placing the word unformatted anywhere within the first 70 columns of the line Advantages and disadvantages of unformatted input e Advantage The integers can appear anywhere on the data line as long as they are in the correct order and separated by a blank comma or tab character e Disadvantage No additional information can be included on the data lines such as non numeric text This line can be followed by one or more empty lines 2 2 2 Formatted input The READ format line for formatted input specifies in which columns each integer of the data is to be found It has the following form e Columns 1 2 right justified The number of loci specified on each line of data e Beginning in column 5 A FORTRAN READ format defining which columns in each of the s
46. ata to the alleles at gene loci e Specification of whether each genotype refers to a single individual see Sec 2 3 2 or to a given number of individuals see Sec 2 3 3 e Indication of whether or not the gametic sex of the alleles at each of the loci is specified see 5 The deme specification line specifies the positions on the data line of the following integers for n gene loci DemeNo 0 z LocusNoz GamSex LocusNoy GamSezo LocusNon Gamsern where DemeNo Deme number referring to the list of demes in header 0 Indication that this line is a deme specification line LocusNo Number of the first locus in the genotype referring to list of gene loci in the header If LocusNo gt 0 each genotype refers to a single individual see 2 3 2 If LocusNoy 0 the second field on each genotype line gives the number of individuals that possess this genotype see 2 3 3 Gamser Gametic sex specification of the first locus GamSez 1 if gametic sex is specified 0 otherwise LocusNoj Number of the ith locus in the genotype referring to the list of loci i 235325 in the header LocusNo gt 0 Gamez Gametic sex specification of ith locus Bein GamSex 1 if gametic sex is specified 0 otherwise Examples of deme specification lines for formatted input using the FORTRAN READ format 10 214 1X 10 212 T Example 1 Deme specification line for deme 2 specifying that multilo
47. cal and 6 1 when all subpopulations are genetically disjoint i e share no types do is useful to quantify variation not only between demes but also within demes In the spe cial case in which each individual is considered to form a subpopulation of its own reduces to the measure of total population differentiation r Gregorius 1987 1988 Measures of evenness specify the minimum genetic distance to a uniform distribution Gregorius 1990 Only the diversity measure v2 does not rely on do The variation within individual genotypes in a deme at singe loci is measured as the propor tion of heterozygous individuals both observed and conditional on the allele frequencies For multiple loci the distribution of the number of heterozygous loci per individual is given In addition to the calculation of genetic structures and variation measures that are not to be found in other software GSED includes several statistical tests 1 A test of homogeneity among demes at any level of genetic integration provides an additional measure of between deme variation 2 Tests of the correspondence of the manner in which alleles are associated in genotypes to special mating systems a A test of Hardy Weinberg proportions examines the hypothesis of random mating within a deme b A test of product structure examines the hypothesis of random fusion between asymmetric gametic distributions in cases where the gametic sex of the alleles is known Curr
48. cus genotypes com prise loci 1 10 that the second integer in the subsequent genotype lines contains the name of the single individual whose genotype is listed and that gametic sex is not specified for any locus 2 031020 30 40 50 60 70 80 90100 11 Example 2 Deme specification line for deme 5 specifying that multilocus genotypes com prise loci 1 10 that the second integer in the subsequent genotype lines denotes the fre quency of the respective genotype in the deme and that gametic sex is specified for all loci 5 0 11 21 31 41 51 61 71 81 91101 2 3 2 Genotypes of single individuals If the sign of LocusNo in the deme specification line of a deme equals or is blank see 2 3 1 then each genotype is interpreted to be that of a single individual In this case each genotype line specifies the following integers DemeNo IndivNo Locus Allele Locus Alleleg LocusnAllelez Locusn Alleleo where DemeNo Deme number referring to the list of demes in header IndivNo Number designating the individual whose genotype is listed Locus Alleley The first allele at locus i as an integer gt 1 If gametic sex is specified for this locus then Locus Allele is the allele contributed by the maternal parent Locus Alleleo The second allele at locus 2 as an integer gt 1 Dei tt If gametic sex is specified for this locus then Locus Alleleg is the allele contributed by the paternal parent
49. dual s haplotype or genotype refers to a single allele or pair of alleles respectively that is are present at a single gene locus single locus haplotype genotype or at each of two or more gene loci multilocus haplotype genotype In diploid organisms the gametic sex of an allele at a locus can sometimes be determined as the contribution of the female or the male gametophyte to the nuclear or organelle genome see legend of Table 1 If the gametic sex of each allele at each locus that is the sex of the contributing parent is specifiable the genotype can be designated as an ordered genotype with the maternal allele in the first position and the paternal in the second When using GSED to analyze genetic types it is essential that the alleles at each locus be known ln other words the phenotype produced by the genes at each locus must be a gene marker in that the phenotype enables identification of all involved alleles Microsatellite and isoenzyme phenotypes that result from gene loci showing a codominant mode of inheritance are gene markers For a dominant mode of inheritance such as is caused by the presence of a recessive null allele at a locus the phenotypes do not define a gene marker loci showing dominance cannot be used for the analysis of genetic types unless additional inheritance analysis has revealed the true genotype of each individual at the locus Data that is simply missing denoted as the allele 1 in an individual s
50. e The observed allele frequencies are given to the right of the table 33 The lower table in App F entitled Test statistics contains the results of the likeli hood ratio test G Pearson s x test X and in tables such as this with one degree of freedom DF 1 the x test with continuity correction of 0 5 X 2 c 5 The symbol here directly to the right of each statistic indicates its level of significance which can be inferred from the two rightmost columns of the table The abbreviation C V of CHI 2 stands for critical value of the x distribution for the given degrees of freedom DF and Level of significance The symbol n s found to the right of a statistic in other tables means not significant Self explanatory messages are printed on the screen if difficulties of the following types are encountered Files cannot be opened read or closed an erroneous answer is given during the interactive sequence limitations on data are exceeded see A 2 Messages are printed in the output in the following cases A requested frequency distribution measure or test cannot be calculated differences in definition of genetic types between demes prohibit comparison of the demes special situations arise during a test Some messages are followed by cause and a number the latter referring to a compiler specific list of I O status values 34 4 2 The output file prefix tab txt
51. e is revealed Inheritance analysis of the phenotypes of the endosperm produced by single trees allows inference of the haploid genotype haplotype of each endosperm and thus the diploid genotype of each tree Bergmann 1971 Inference of the genotype of a diploid embryo and subtraction of the haplotype of the corresponding endosperm then reveals the haplotype of the paternal gamete for codominant alleles of enzyme loci Miiller Starck 1977a M ller Starck 1977b Miiller Starck If the gametic sex of the alleles i e the sex of the parent contributing each allele at all involved loci is specified a number of additional frequency distributions can be calculated For a single locus e Allele frequencies among maternal contributions The set of alleles contributed by the maternal parents of the sampled individuals represents a deme of the alleles in the population of successful maternal gametes 37 e Allele frequencies among paternal contributions In like manner the set of alleles contributed by the paternal parents of the sampled individuals represents a deme of the alleles in the population of successful paternal gametes e Ordered genotype frequencies maternal x paternal alleles The set of ordered geno types represents a deme out of the population of successful fusions between female and male gametes Ordered genotypes take into account the gametic sex specification of the alleles at the loc
52. e A in the population equals p N 2N the genotypic frequencies expected under the null hypothesis of Hardy Weinberg structure equal E Nu N 2 AN and E N N N 2N i j 1 k The N and E N for i lt j are the observed and expected deme frequencies respectively entering the test statistics described above The number of degrees of freedom equals k k 1 2 The observed numbers of homozygotes and heterozygotes in a deme of N individuals from a large population equal gt gt Ni and gt Nij respectively The numbers of homozygotes and heterozygotes expected under the assumption of a Hardy Weinberg structure equal E Y N Y ve AN and E v N E gt N i lt j respectively Again the expected frequencies are conditioned on the allele frequencies in the deme One degree of freedom remains By definition a genotypic structure shows an excess of homozygotes heterozygotes if its proportion of homozygotes heterozygotes exceeds the proportion of homozygotes het erozygotes in the corresponding Hardy Weinberg structure If the genotypic structure is a Hardy Weinberg structure then such an excess will not be statistically significant if the test for Hardy Weinberg structure is not significant an excess still may or may not be significant Tests for homozygote excess frequently form the first step in an analysis of so called inbreeding structures Detailed tests for realization of inbreedin
53. eld of each genotype line contains the number of individuals that were found to have the respective genotype in the deme Note that it is possible to include several deme specification lines within the same deme Data adapted from Kim 1985 2 2 SAP A LAP A DEUTSCHLAND ECKERN DEUTSCHLAND KEIMLINGE GEWAECHSHAUS 1 2I4 1X 1 212 1X 0 2 151 111 107 6 51 83 5 68 OQ KM KM KA HE KA PS CON KA PPWPRPWNHPWNF O 999 o I ONNNNNNNNNNNNNNNNNNNNORPRPRPRPRPRPRP p p pb BE w co N LG KM KM G K KA E LO KM K KM MKM G G A L KM K G GQ GKM GM GO E LQ GKM GKM G O 999 59 Example 4 Here the number of loci is large necessitating continuation of the genotypes on additional lines The usage of the formatted input saves space on the line by allowing the alleles designation to be written with separators Lack of gametic sex specification is indicated by the 0 following each locus number in the deme specification line 1 30 Locus 1 Locus 2 Locus 30 Beech forest 30 2i4 20 i2 i1 8x 10 i2 i1 1 O 10 20 30 40 50 60 70 80 90100110120130140150160170180180200 210220230240250260270280290300 1 1 11 22 31 11 21 12 44 34 35 43 31 32 33 22 13 13 22 11 11 22 43 23 22 33 11 22 31 12 11 00 1 2 22 33 33 22 44 11 22 11 31 11 22 31 12 14 34 42 13 23 21 22 35 43 21 12 11 23 21 11 22 12 9999 Example 5 This example of formatted input shows the input for a deme of successful maternal haplotypes such as could be found by sampling
54. en that the average degree of heterozygosity equals the mean proportion of heterozygotes at the single loci Reference Gregorius 1978 43 7 2 Tests of single locus structure The following goodness of fit tests are performed for two models of single locus genotypic structure Pearson s x goodness of fit test with statistic N E N y E N ee AD types Likelihood ratio test with statistic G 2 y N In N n E N types For one degree of freedom x goodness of fit test with continuity correction c i with statistic 7 IW EQ 3 E N X yo types NI N and E N represent observed and expected deme frequencies respectively of the dif ferent types These statistics are asymptotically x distributed the number of degrees of freedom de pending on the model Thus it must be kept in mind that these tests are accurate only for large deme sizes A warning is printed in the output if a type is found to have expected frequency less than 5 Exact tests have recently been devised in some cases but these seemed too time consuming in terms of computing time to allow their inclusion in the larger framework of GSED In borderline cases i e statistic near critical value of x of small deme size it may be advisable to retest structures using special statistics programs that perform exact hypothesis testing References Louis amp Dempster 1987 Weir 1990 pp 71 f 7 2 1 Test of Hardy Weinbe
55. ent research in the field of population genetics underlines the importance of this alter native system of data analysis The realization is spreading that the most commonly used measure For Gsr Wright 1978 does not measure differentiation among populations when differentiation is understood in the sense of differences Gregorius 1987 Jost 2008 A new conceptual analysis of the distribution of variation over populations shows that whereas Fsr is not a measure of differentiation among populations but rather a measure of the apportionment of variation to populations 0 is indeed a measure of differentiation Many of the measures of variation calculated by GSED can be applied not only to genetic types but also to any system of classification by which each individual of a population can be assigned one of a finite set of discrete types e g phenotypes ecotypes Although the assumption that data input to GSED concerns genetic types is reflected in its commentaries one or higher dimensional non genetic classifications can be disguised as maternal alleles or haplotypes at loci for which gametic sex is specified and paternal type unknown An input file would be analogous to that of Example 4 in App C Output headings would have to be reinterpreted accordingly 1 2 Requirements on the data Input to GSED consists of a list of genotypes or haplotypes scored in individuals belonging to one or more collections or demes An indivi
56. equency distributions of the types in deme j and in the re mainder of the population respectively and dy is the genetic distance defined above The subpopulation differentiation is then defined by deco j 41 where the weights c express the proportion of genetic elements present in the jth deme References Gregorius 1984b 1988 1996 Gregorius amp Roberds 1986 6 2 3 Test of homogeneity Let m collections of individuals each be characterized by a frequency distribution defined by the number of individuals of each of n types in the collection A test of homogeneity of the m frequency distributions tests the hypothesis that these m collections all originated from a single large collection of individuals conditioned on the marginal distributions given by the m deme sizes as proportions of the sum of deme sizes and the mean relative frequencies of the n types over the demes Goodness of fit tests see 7 2 are performed for m 1 n 1 degrees of freedom References Elandt Johnson 1971 pp 365 f Weber 1978 pp 96 7 42 7 Analysis of genotypic structure The following measures and tests aid in the characterization of genotypic structures In contrast to other measures quantifying variation within and between demes see 6 8 het erozygosity measures genetic variation within individuals Tests of single locus structure investigate the association of gametes in observed zygotic genotypic structures by compar ing the
57. erg proportions Sampling variances and use in estimation of inbreeding coefficients Genetics 107 703 718 http www genetics org cgi content abstract 107 4 703 Weber E 1978 Mathematische Grundlagen der Genetik VEB Gustav Fischer Verlag Jena Weir B S 1990 Genetic Data Analysis Sinauer Associates Inc Publ Sunderland Mass 93 Wright S 1978 Evolution and the Genetics of Populations Vol 4 The University of Chicago Press Chicago 54 A Technical specifications A 1 Compiler information GSED is written in the programming language FORTRAN as a mixture of FORTRAN 77 and FORTRAN 90 subroutines Compilations by the GNU FORTRAN compiler gfortran on the operating systems WinXP and openSUSE Linux can be downloaded from http www uni goettingen de de 95607 html The compiler version appears in the program header During execution GSED stores intermediate results in direct access files Depending on the compiler they receive names such as FORnnn DAT or a seemingly arbitrary sequence of letters and numbers They are stored on the default directory or drive see A 1 and are deleted automatically upon successful completion of the program If the program is interrupted in mid run the files may remain and can be deleted by hand A 2 Limitations on data Allele designations or names must be non negative integers No non numeric letters are permitted The allele designation 0 is meant to denote a null
58. erlying genes from the lowest level of the alleles at a single locus to the level of the gene pool over loci to the level of multilocus genotypes to the level of multilocus haplotypes Infer ence of multilocus haplotypes requires specification of the gametic sex of each allele for example as the cytotypes of uniparentally inherited haploid organelles or as the multilo cus haploid gametic contribution of the maternal seed parent or the paternal pollen parent of conifer seeds where the gametic sex of each allele is determinable by means of megagametophyte embryo analysis GSED calculates genetic structures as the frequency distributions of the genetic types at any chosen level of integration from lists of multilocus genotypes multilocus haplotypes require specification of the gametic sex of the alleles For each genetic structure GSED calculates measures of variation within and between demes most of which are based on dy For example matrices of pairwise distances dy are calculated that can be imported into programs that construct dendrograms For demes that can be considered as subpopulations of a large population dy forms the basis of the measure of subpopulation differentiation measures the mean genetic distance D of each subpopulation j to its complement that is formed by pooling all other subpopulations Gregorius amp Roberds 1986 As a true measure of differentiation 6 0 when all subpop ulations are identi
59. es in App F I If calculations are requested only for single loci results for the gene pool and hypothetical gametic output defined by these loci are included at the end of the file see Sec 8 Each locus combination single or multilocus is in turn divided into the output for each of the chosen frequency distributions measures of variation within demes between demes fol lowed by the analysis of genotypic structure heterozygosity tests of single locus structure The demes are listed in columns as opposed to the file example txt tab txt Results for measures of variation and heterozygosity appear in tables each column con taining the results for one of the chosen demes If the chosen width of output see 3 2 Width of output is not sufficient to allow inclusion of all demes onto one line each table is truncated vertically and continued on the next lines If the current locus combination consists only of a single locus the output for this combination closes with the results of the chosen tests of single locus structure for each deme 3l The legend printed at the beginning of the output explains notational conventions 0 or E Observed or Expected absolute frequency in a test i Denotes multilocus haplotype or genotype NA Denotes undefinable parameter value Gam sex spec Abbreviation of Gametic sex specification yes if maternal paternal alleles distinguishable no otherwise alpha All alleles haplotypes
60. et text to a list of the desired demes separated by blanks or commas e g 1 2 or 1 2 see next window A single deme can also be chosen Part 2 SELECT CALCULATIONS When GSED is run with a new input file all checkboxes are empty For subsequent runs with an input file of the same name the calculations that were checked in the previous run are shown see 3 3 18 Under FREQUENCY DISTRIBUTIONS one or more of the distributions described in in 5 can be chosen by clicking on the checkboxes Checking Ignore gametic sex if specified in data causes GSED to treat the genotypes at the locus as unordered genotypes and to suppress calculation of maternal paternal allele haplotype frequencies Under VARIATION WITHIN DEMES VARIATION BETWEEN DEMES and GENO TYPIC STRUCTURE parameters are chosen for calculation see 6 The selections are submitted by clicking on the OK button The selected calculations are saved in a configuration file the name of which consists of the name of the input file followed by cfg here example txt cfg In all subsequent runs using the same input file the checkboxes in the GSED Interactive input window will be preset according to the settings stored in the configuration file If no calculations were selected in the GSED Interactive input window the following message window appears GSED must be restarted GSED Interactive input x No calculations chosen
61. fication line 25 Loci Loc2 Loc3 Loc4 Loc5 Popi Pop2 unformatted 1 0 1 0 2 0 3 0 4 0 5 0 1 1 213 223 244 244 154 168 155 155 191 193 1 2 213 217 244 244 166 168 155 155 187 193 1 3 213 215 243 248 166 168 155 155 187 187 1 4 211 211 240 242 166 168 151 155 187 201 1 5 213 217 243 248 166 168 155 155 187 193 1 6 211 223 243 243 168 168 151 155 187 193 1 7 211 215 243 245 168 168 155 173 187 203 1 8 Eq c 248 251 154 168 155 173 197 197 1 9 215 217 243 243 154 168 155 159 191 191 1 10 211 213 255 255 166 168 155 155 187 201 2 0 1 0 2 0 3 0 4 0 5 0 2 65 213 223 244 246 166 168 155 155 187 197 2 66 213 215 243 243 168 168 155 155 187 187 2 67 215 225 242 246 168 168 155 159 201 201 2 68 213 225 242 245 168 168 155 173 189 201 2 69 217 229 246 252 168 168 155 157 187 187 2 70 203 215 242 246 168 168 155 155 187 197 2 71 213 219 243 246 168 168 155 165 191 197 2 72 213 235 240 244 168 168 155 161 191 197 2 73 209 209 244 244 168 168 155 155 187 205 2 74 203 229 242 242 166 168 155 161 187 193 2 75 213 213 242 244 168 168 153 155 187 197 58 Example 3 This example of formatted input see 2 2 2 demonstrates that it is still possible to input single locus genotypes at more than one locus even if they refer to the same population but not necessarily the same individuals T he disadvantage of this type of input is that all individual multilocus information is lost The 1 in the deme specification lines indicates that the second fi
62. fied Since sorting of multilocus types can take an extreme amount of computing time it is advisable not to choose these calculations for multilocus combinations only the first two questions apply unless they themselves are of interest A test of homogeneity for a large number of multilocus types may well exceed the capacity of the program anyway see A 2 Often heterozygosity is the only calculation desired for multilocus genotypes it is performed quickly if it alone is selected 30 4 Output GSED produces four kinds of output the names of which begin with the chosen prefix see Sec 3 1 denoted prefix The output is named e The file prefix out txt Complete output of all selected calculations including fre quency distributions variation parameters and statistical tests e The file prefix tab txt Tabular output of all frequency distributions and all calcu lated variation parameters This file can be imported into any spreadsheet program by indicating the separation of columns by one tab character e The directory prefix Snails containing the snail graphs if subpopulation differenti ation was calculated e The file name of input file cfg Stores the selected calculations to be shown in the checkboxes or configuration of the next run see Sec 3 3 4 1 The output file prefix out txt This file is organized by locus combination t e by single locus or by multilocus combination see Secs 6 7 See the exampl
63. fined as j E v p E it k 1 va p measures the differentiation effective number of types it is less than or equal to the actual number of types and equals this number only for a uniform distribution References Gregorius 1978 1987 6 1 2 Total population differentiation r Let a collection of size N be characterized by a frequency vector p pi pos Pn of its genetic types where n IN and for k 1 n p gt 0 and gt pk 1 The total population differentiation r of the collection is defined as N r 1 TT Wo SH or letting N N p be the absolute frequency of the kth type T NL N Nk NL k 1 It holds that 0 lt r lt 1 with r 0 for monomorphy and r 1 if no two deme members are of the same genetic type References Gregorius 1987 1988 6 1 3 Evenness e Given a distribution of types of individuals in a collection the evenness of the distri bution is considered to measure the degree to which these types are equally represented Gregorius 1990 40 The evenness e is defined to equal one minus the minimal distance of the frequency distribution to all plateaus each consisting of equally frequent types in effectively infinite collections In small collections the plateaus are defined by the respective distributions closest to uniformity If din equals this minimal distance the absolute evenness is given by e 1 din for the definiti
64. g structures require consideration of various cases as specified e g in Robertson amp Hill 1984 References Elandt Johnson 1971 Gregorius 1989 pp 20 f 68ff Hattemer Bergmann amp Ziehe 1993 pp 175ff Ledwina amp Gnot 1980 Pamilo amp Varvio Aho 1984 Robertson amp Hill 1984 and references therein Weir 1990 pp 71ff 7 2 2 Test of product structure for ordered genotypes In a large population random fusion of gametes from the set of maternal and the set of paternal gametes gives rise to a zygotic genotypic structure at a locus with k alleles that 45 fulfills the properties of a product structure Pepi ij 1 k where P is the relative frequency of the ordered genotype A A i e A is the maternal contribution and A the paternal so that gt gt Pi 1 D is the relative frequency of 3 allele A among maternal gametic contributions and p is the relative frequency of allele A among paternal gametic contributions Given a random deme of N individuals from a large population the test of a product struc ture is performed as a test of independence of association between maternal and paternal allelic contributions conditioned on marginal distributions given by the frequencies of these contributions in the deme For absolute frequencies N i j 1 k of the ordered genotypes in the deme the absolute frequency N of the allele A in the deme of N ma ternal alleles equals N Nj
65. genotypes of relative frequency not less than alpha in deme appear in sample with replacement with probability 0 95 alpha HWP As above if genotypes in deme are in Hardy Weinberg Proportions HWP The output for each frequency distribution begins with a heading which provides the fol lowing information about each deme Deme No Number of the deme in accordance with the list of demes in the input file Gam sex spec Abbreviation of Gametic sex specification yes if the sex of the parent contributing each allele is known in the entire deme no otherwise Deme_size Total number of individuals whose genotypes are included in the input file regardless of whether they contain unknown alleles or not No _identified Number of individuals whose genetic types with respect to the cur rent frequency distribution are completely identified no unknown alleles see 5 Relative frequencies refer to this number alpha see below alpha HWP see below No unknown Number of individuals whose genetic types with respect to the cur rent frequency distribution are unknown and thus are not counted see 5 Deme size equals the sum of No identified and No unknown alpha In loose terms alpha tells how frequent a type allele haplotype genotype must be in the base population in order for it to have a probability of 0 95 or greater of being represented
66. ified at any locus then the answer to this question is meaningless If gametic sex is specified at some or all loci then an answer of N will cause this spec ification to be ignored at all of them For example in such a case both of the genotypes AA and As A where the first allele is that contributed by the maternal parent would be counted as the genotype 414 26 Choice of calculations Answer Y yes or N no Frequency distributions 7 Y An answer of Y causes the calculated frequency distributions to be included in the output If the answer is N they will be omitted Measures of variation within demes Measures of variation between demes Analysis of genotypic structure If selected the measures and tests offered in the subsequent questions and described in 6 7 8 are calculated for each of the chosen frequency distributions Note that if Subpopulation differentiation Dj deltais chosen both methods of calculating relative subpopulation sizes c and both of the snail formats WMF and EPS are automatically selected see 3 1 The above choices of frequency distributions measures and tests are saved in a configura tion file The name of the configuration file consists of the name of the input file followed by cfg for example example txt cfg All subsequent runs using the same input file will first print the stored configuration table and then ask whether it should be adopted If the answer
67. iles Enter new prefix for output files Select one of the options Overwrite existing output files or Enter new prefix for output files Again the option is submitted by clicking on the OK button If the latter option is chosen as in this window Wil GSED Check existence of output files using prefix Exit OUTPUT FILE ALREADY EXISTS example txt out txt SELECT OPTION Overwrite existing outp Enter new prefix for output files the window entitled GSED Prefix for output files is reopened and a new prefix can be entered such as xxx If output files with this new prefix also exist the window entitled GSED Check existence of output files using prefix reappears This loop continues until either a prefix is entered that has not been used before or until the option Overwrite existing output files is selected in the GSED Check existence of output files using prefix window 17 The configuration and calculations are selected in the next window entitled GSED Inter active input El GSED Interactive input FEER Exit Help SELECT CONFIGURATION SINGLE LOCI OR MULTILOCUS Single locus genetic types Multilocus genetic types LIST OF LOCI g 4 loci LIST OF DEMES jan 3 demes SELECT CALCULATIONS FREQUENCY DISTRIBUTIONS Maternal allele haplotype frequencies if gametic sexis specified in data Paternal allelefhaplotype frequencies if gametic sex is specified in dat
68. in a deme of the given size No _identified More precisely the probability of having sampled and identified all types occurring with relative frequency greater than or equal to alpha is 0 95 or greater Obviously the larger the deme size the smaller alpha becomes see Gregorius 1980 for derivation of alpha Alleles and multilocus haplotypes occur in pairs in the form of genotypes If the only way to deme haplotypes is by sampling genotypes it must be remembered that the manner 32 of association between the different haplotypes making up the genotypes homozygosity heterozygosity has a great influence on the probability of finding the rarer haplotypes alpha describes the worst case situation for finding the rarer haplotypes namely pure homozygosity in that only one allele or haplotype can be sampled per individual see Gregorius 1980 for proof alpha HWP In the case of alleles and haplotypes with arbitrary frequencies this rela tive frequency characterizes an analogous alpha for the best case situation for sampling haplotypes when only genotypes can be sampled Gregorius 1980 gives proof that this sit uation occurs when the genotypes arose by random fertilization between alleles haplotypes which are then independently associated in the genotypes The resulting Hardy Weinberg Proportions HWP thus represent the optimal relationships between homozygosity and het erozygosity for sam
69. is N new choices can be made An example for the case in which a configuration file already exists is given in App E The sequence of questions continues as follows Demes for output O all demes 1 some demes Option 7 The two options are explained as follows Option 0 The output contains the results for all of the demes in the input file Measures of variation between demes see 6 2 are calculated using ALL of the demes Option 1 The output contains the results for only those demes given in reply to the following question This option allows measures of variation between demes see 6 2 to be calculated for differing sets of demes As an example demes 1 and 3 are chosen in reply to the following questions How many demes 7 2 Which demes separated by commas and using as many lines as necessary 7 1 3 Output unit S screen F file Option 7 27 Output can be directed to one of two units as follows Option S All results are typed on the screen They are not saved elsewhere and thus are lost as soon as they disappear off the screen Option 7 F Results are output as ASCII text to the designated file A maximum of 60 characters are allowed for the file name and any necessary specification of path Since the output is in ASCII code it is possible to alter its format later using any text editor The finished file can then be printed on any printer Output file already exists
70. istance dg between gene pools Let one collection be characterized by the frequency vectors of the different genes alleles at L gene loci that is by the L frequency vectors pi pu par Hail 1 L where n IN is the number of alleles at locus and py gt 0 and Y Hw 1 holds for all k 1 ny Let a second collection be characterized by the L frequency vectors pi pui Pou ux aes l 1 L at the same L loci and for the same numbering of alleles at each locus The gene pool genetic distance dy between the two collections was proven to be the arithmetic mean of the single locus distances i e L dy Y do pi pi Eb ll m ni Me Bx ls POS Dr Hl ll m k 1 Reference Gregorius amp Roberds 1986 8 2 2 Differentiation of subdivided gene pools Let a collection of subpopulations have the subpopulation differentiation q at locus I l 1 L Then the unweighted subpopulation differentiation of the gene 48 pool was proven to be the arithmetic mean of the subpopulation differentiation at each locus that is L 0 1 ra Reference Gregorius amp Roberds 1986 49 9 Acknowledgements and disclaimer I am still grateful to the many colleagues who helped with the original version of GSED and its manual Matthias K hle did some of the programming of the interactive sequence especially the saving of the configuration Fritz Bergmann Bernd Degen Rei
71. ited from the paternal parent paternal allele second requires specification of the gametic sex of the alleles Single locus maternal haplotype The allele contributed by the maternal parent listed in the first position of an ordered genotype Single locus paternal haplotype The allele contributed by the paternal parent listed in the second position of an ordered genotype Single locus cytotype The genetic variant at an organelle locus represented as one of the alleles of an ordered single locus genotype the other allele being unknown Multilocus genotype List specifying the single locus genotype at each of a given set of loci Ordered multilocus genotype List specifying the ordered single locus genotypes at each of a given set of loci Multilocus maternal haplotype List specifying the maternally contributed allele at each of the loci in an ordered multilocus genotype given in the first position of every single locus genotype Multilocus paternal haplotype List specifying the paternally contributed allele at each of the loci in an ordered multilocus genotype given in the second position of every single locus genotype Multilocus organelle cytotype List specifying the genetic variant at each of the loci in an ordered multilocus genotype given in the first position of every single locus genotype the allele at the second position being unknown or vice versa 10 e The assignment of fields or blocks of columns in a line of d
72. ity 7 2 2 Test of product structure for ordered genotypes 8 Analysis of the gene pool 8 1 Measures of variation within demes 8 1 1 Diversity vo of the gene pool 8 1 2 Diversity vgam of the hypothetical gametic output 8 1 3 Total population differentiation r of the gene pool 8 2 Measures of variation between demes 8 2 1 Distance do between gene pools 8 2 2 Differentiation 6 of subdivided gene pools 9 Acknowledgements and disclaimer 10 Copyright information on the GSED software il 40 40 40 40 40 41 41 41 42 43 43 43 43 43 44 44 45 47 47 AT 47 48 48 48 48 50 51 Technical specifications Al Compiler information a exe Ia UR Bee aa A 2 Limitations on data The example input file example txt More examples of input files Keyboard driven execution for first run Keyboard driven execution for subsequent runs Output file example txt out txt Output file example txt tab txt Output file example txt multi out txt Output file example txt multi tab txt 111 55 95 95 56 57 61 63 65 70 72 79 List of Tables Genetic structures calculated by GSED Characterization of genetic structures by GSED o Genetic types that can be represented in GSED input data Ee
73. lleles Locus 1 eps 9KB PostScript S example txt snal EquPopSiz Aleles Locus 1i wmf 11KB WMF Bild e i example txt Snall EquPopSiz Alleles__Locus_2 eps 7 KB PostScript Detalis Dexample txt Snai EquPopSiz Alleles_Locus_2 wmf 9KB WMF Bid S example txt snal EquPopSiz Alleles Locus 3 eps BKB PostScript IS example txt snal EquPopSiz Alleles Locus 3 wmf 10KB VVMF Bid 3 example txt snal EquPopSiz Alldles Locus 4 eps BRB PostScript Mexample txt Snai EquPopSiz Alleles_Locus_4 wmf 10KB WMF Bild example txt Snal EquPopSiz Genotypes Locus 1 eps 10KB PostScript IS example txt snal EquPopSiz Genotypes Locus 1 wmf 12KB WMF Bild example bxt Snall EquPopSiz Genotypes__Locus_2 eps 9KB PostScript Bann txt Snall EquPopSiz Genotypes__Locus_2 wmf 11KB WMF Bid A example txt Snal EquPopSiz Genotypes__Locus_3 eps 10KB PostScript M example txt Snall EquPopSiz Genotypes__Locus_3 wmf 12KB WMF Bild 3 example txt snal EquPopSiz Genotypes Locus 4 eps 10KB Postscript Dexample txt Snai EquPopSiz Genotypes__Locus_4 wmf 12KB WMF Bild Bilexample txt Snail SmpPopSiz Alleles__Gene_Pool eps BKB PostScript example txt Snail SmpPopSiz Alleles___Gene_Pool wmf 12KB WMF Bild J example bxt Snai SmpPopSiz Alleles__Locus_1 eps 9KB PostScript Mexample txt Snail SmpPopSiz Alleles_Locus_1 wmf 12KB VVMF Bild Rexample txt Snai SmpPopSiz Alleles_Locus_2 eps BKB Postscript Mexample txt Snai SmpPopSiz Alleles_Locus_2 wnf 11KB WVMF Bild S example txt snal SmpPopSiz Allles Locus
74. n 0 0 1 DISTRIBUTION OF DEGREE OF HETEROZYGOSITY OF PROBES WITH COMPLETELY IDENTIFIED 4 LOCUS GENOTYPES Deme 1 2 3 hloc 0 0 0 1 0 000 00 000 0 111 hloc 1 0 2 2 0 000 0 200 0 222 hloc 2 3 2 3 0 300 0 200 0 333 TT hloc 3 5 3 2 0 500 0 300 0 222 2 3 1 0 200 0 300 0 111 AVERAGE DEGREE OF HETEROZYGOSITY OF PROBES WITH COMPLETELY IDENTIFIED 4 LOCUS GENOTYPES Deme 1 2 3 0 725 0 675 0 500 xx Combination 1 is not a single locus Test of Hardy Weinberg structure is not possible Test of product structure is not possible 78 I Output file example txt multi tab txt Example of output file named example txt multi tab txt for the multilocus geno type frequencies at all loci in the sample input file example txt The long lines under Measures of genetic variation are wrapped in order to fit the table on the page GSED INPUT FILE path example txt GSED OUTPUT FILE path example txt multi out txt Date 19 Apr 2010 15 52 46 MULTILOCUS COMBINATION OF LOCT LOCUS NO 1 Locusi LOCUS_NO 2 Locus2 LOCUS_NO 3 Locus3 LOCUS_NO 4 Locus4 GENOTYPE_FREQUENCIES Absolute_frequency_distribution Deme_No 1 2 3 Type 1 0 1 0 101 101 76 76 121 193 36 48 Type 2 0 1 0 101 101 76 83 89 106 36 48 Type 3 0 0 1 101 101 76 83 106 106 42 42 Type_4 0 0 1 101 101 TG 102 106 106 48 48 Ln Type 5 0 1 0 101 101 83 83 106 106 36 48 Type 6 1 0 0 1
75. ne 3 22223 ae pd pa RC SU 13 ZA End RIU a R Ta a ra Sel qe Da ren erste dre aod 18 3 Running GSED 14 3 1 Menu driven execution tere aa Gs Re pac e 8S Bo Rd AO eg 14 3 2 Keyboard driven execution 2 49x a be be eR an EG 25 3 3 Configuration DIES 34 eb IS AS A Da SS LE aes t 29 3 4 Sorting of haplotypes and genotypes a 30 4 Output 31 4 1 The output file prefix out txt aa sia wleie ege ES 31 4 2 The output file prefix tab txt ute cae d cte en A 35 4 3 The output directory prefix Snails aa a sa HL EEE Ae ESE SE GS 36 4 4 The configuration file name of input file cfg 36 5 Frequency distributions 37 6 Measures of variation 6 1 Measures of variation within demes 6 1 1 Diversity 2 2 Ne Roe S 6 1 2 Total population differentiation r 6 1 3 Evenness uo ae aa SR EE 6 2 Measures of variation between demes 6 2 1 Genetic distance dg 6 2 2 Subpopulation differentiation D and 6 2 8 Test of homogeneity 7 Analysis of genotypic structure 7 1 Heterozygosity xov exe X6 eR mus 7 1 1 Proportion of heterozygosity of single locus genotypes 7 1 2 Conditional heterozygosity of single locus genotypes 7 1 3 Degree of heterozygosity of multilocus genotypes 7 2 Tests of single locus structure 7 2 1 Test of Hardy Weinberg structure and heterozygos
76. ne loci the so called multilocus combinations As an example one multilocus combination comprising the gene loci 1 and 2 and a second comprising only the single locus 1 are specified in reply to the following questions as in the second case a multi locus combination can refer to the genotypes at a single locus Number of different multilocus combinations 2 Combination 1 How many gene loci 7 2 Which loci separated by commas and using as many lines as necessary 7 1 2 Combination 2 How many gene loci 1 Which loci separated by commas and using as many lines as necessary 7 3 It is important to note here that measures characterizing the gene pool see 8 are calculated if and only if the Locus configuration 77 comprises only single loci i e if either option 0 or 1 is chosen Since the gene pool measures are formulated as means of the respective single locus measures at all loci contributing to the gene pool the single locus measures must already be available Option 3 Calculations will be performed for multilocus genotypes defined by the genotypes at all of the single loci in example txt for all four loci Choice of frequency distributions Answer Y yes or N no Choices can be made among the four types of frequency distribution offered by the subse quent questions and described below see 5 Should gametic sex specification if given be retained 7 Y If no gametic sex is spec
77. ner Finkeldey Hans Rolf Gregorius Hans H Hattemer Sven Herzog Bernhard Hosius Gerhard M ller Starck Aristotelis Papageorgiou Rommy Starke Jozef Turok Martin Ziehe and too many master s students to list here tested the various versions of GSED on their data and sug gested improvements Martin Ziehe recalculated many of the computed results thereby discovering several bugs Hans Rolf Gregorius provided valuable instruction over the years on the meaning of genetic variation and mating systems in general and on the implemented measures and tests in particular and suggested improvements for the output Hans Rolf Gregorius Hans H Hattemer Bernhard Hosius and Martin Ziehe suggested improvements on this manual Generous financial support of earlier versions was obtained by Florian Scholz and Bernd Degen of the Bundesforschungsanstalt f r Forst und Holzwirtschaft now the Institut f r Forstgenetik in the Johann Heinrich von Th nen Institut in Grofhansdorf and Alwin Jan en of the Hessische Forstliche Versuchsanstalt now the Nordwestdeutsche Forstliche Versuchsanstalt in Hann M nden I am also grateful to Helmut Michels author of the scientific data plot software DISLIN http www dislin de for advice on programming the menu driven execution and on plotting the subpopulation differentiation snails in the new version of GSED As before I have tried my best to find all programming errors Nevertheless the user is advised to check
78. ntaries in the output Another is that the maximal number of columns of the contingency tables in the tests of genotypic structure that can be printed onto one line is also set to the chosen number of demes per line A reply of 0 zero causes the results of all demes to be printed onto one line Additional calculations using the same input file and locus configuration 7 Option 7 When this line appears the chosen calculations have been completed and either typed on the screen or stored in the output file Its purpose becomes apparent in the description of the options Option Y Type Y if additional frequency distributions measures or tests for the same or a different set of demes are desired for the same input file and locus configuration Since the frequency data is already stored the input file is not reread and results are obtained quickly This option provides a means of ordering the output differently from that reflected by the in teractive sequence It also allows calculation of measures of variation between demes for different sets of demes Option N An answer of N terminates the program 3 3 Configuration file In subsequent runs of GSED for an input file a configuration file may exist This will be the case if the question Should these choices be stored in a file for later use was answered with Y in an earlier run for the same input file The configuration file contains the previo
79. omogeneity e ANALYSIS OF GENOTYPIC STRUCTURE Heterozygosity single locus and multilocus observed and conditional Test of Hardy Weinberg structure and heterozygosity Test of product structure e ANALYSIS OF THE GENE POOL Measures of variation within demes x Diversity va of the gene pool Diversity Ugam of the hypothetical gametic output x Total population differentiation r of the gene pool Measures of variation between demes Distance do between gene pools Differentiation of subdivided gene pools measure of absolute distance do P P Y pi p i l ND m between two demes e g populations P and P where p and p denote the relative fre quency of individuals of type i in deme P and P respectively with respect to a trait that is expressed in each individual as one of n types trait states Gregorius 1974a b 1978 1984a do ranges from dg 0 for demes with identical frequency distributions to do 1 for disjoint demes i e demes that share no types The metric distance dy quantifies the proportion of individuals in one of the demes whose type must be changed in order to make this deme match the other dy can be applied to genetic traits and to phenotypic traits whose genotypes have yet to be determined For genetic traits the p refer to genetic types that can be of arbitrary complexity Thus do enables comparison of demes at any level of genetic integration of the und
80. omogeneity y Heterozygosity y Test of Hardy Weinberg structure heterozygosity single locus y Test of product structure single locus y Locus 1 Locus Locus 2 Locus2 Deme 1 Popi Locus 3 Locus3 Deme 2 Pop2 Locus 4 Locus4 Deme 3 Pop3 Locus configuration 0 all single loci 2 multilocus some loci 1 some single loci 3 multilocus all loci Option 0 Ignore gametic sex if specified in data n Options saved in file example txt cfg Demes for output 7 O all demes 1 some demes Option 0 Output unit S screen F file 63 Option f File already exists A append new output 0 overwrite old output Option Width of output min of 75 characters line as number of demes per line No demes line 1 10 No characters line 15 For example 0 for ALL 3 demes 75 chars line 6 for 6 demes 75 chars line as for DIN A4 paper upright 10 for 10 demes 115 chars line as for DIN A4 paper crosswise 11 for 11 demes 125 chars line as in condensed mode Option 0 Reading input file example txt 1 3 4 2 Locusi 3 Locus2 4 Locus3 5 Locus4 6 Popi T Pop2 8 Pop3 9 unformatted 10 1 0 1 0 2 0 3 0 4 0 11 1 1 121 121 83 295 118 193 42 42 44 3 10 132 136 83 8 89106 48 48 45 End of input file Sorting haplotypes Sorting genotypes Calculating and outputting results for Locus 1 Locusi for Locus 2 Locus2 for Locus
81. on of d see genetic distance below e 1 holds only for uniform distribu tions As e approaches a lower bound of 0 5 the unevenness increases As a transformation of evenness which varies between 0 and 1 the relative evenness of the population is defined as e 1 2 d min Reference Gregorius 1990 6 2 Measures of variation between demes 6 2 1 Genetic distance do Let two collections be characterized by frequency vectors p pi po p and p pi p ph of their genetic types where n IN and for k 1 n py p gt 0 and Dz Pk 1 SX py The genetic distance do p p is defined as I pr phl k 1 The genetic distance between two collections is specified as the proportion of genetic ele ments alleles genes at multiple loci gametes genotypes which the two collections do not share Thus dy 1 if and only if the two collections have no types in common References Gregorius 1974a b 1978 1984a do p p DI m 6 2 2 Subpopulation differentiation D and Let a population be divided into demes subpopulations collections The amount of ge netic differentiation of one subpopulation to the remainder of the population is specified as the proportion of genetic elements alleles genes at multiple loci gametes genotypes by which a deme differs from the remainder of the population in type Gregorius 1984b This proportion is defined as Dj do p P3 where p and p are the fr
82. one gametic parent is unknown If more than one locus is scored in the same individual its multilocus genotype is specified by a line of data listing its single locus genotypes If gametic sex is specified at all of the loci the multilocus maternal haplotypes and paternal haplotypes can be inferred Multilocus organelle cytotypes are represented as ordered multilocus genotypes with one parental allele unknown at all loci The data for each deme consists of three parts each of which is explained in detail in the following subsections e A deme specification line defining the order and the gametic sex specification of the loci e Lines containing each of the genotypes found in the deme and if indicated in the deme specification line the number of individuals possessing this genotype e The end of deme line Demes can appear in any order since the deme number is included on each line of data 2 3 1 Deme specification line The data for each deme begins with the deme specification line This line contains the following information as integers about each deme e The deme number in accordance with the ordering of the deme names in the header Table 3 Genetic types that can be represented in GSED input data Single locus genotype The pair of alleles at a single gene locus Ordered single locus genotype Single locus genotype in which the allele inherited from the maternal parent maternal allele is listed first and the allele inher
83. opulation GSED treats unknown alleles denoted 1 in input and haplotypes and genotypes containing them as follows for each frequency distribution e Maternal allele haplotype frequencies Unknown maternal alleles are assumed to be a random deme of all maternal alleles and are thus left out of the calculation In the same manner incomplete maternal multilocus haplotypes containing an unknown allele at one or more loci are also treated as a random deme of haplotypes and are ignored e Paternal allele haplotype frequencies Unknown paternal alleles and haplotypes are treated in the same way as maternal ones e Allele haplotype frequencies Only those alleles are taken into account that are part of a completely known genotype Thus if one allele is known and the other is unknown e g because the primary endosperm of a conifer seed was analyzed but the embryo lost the known allele will not be counted in the allele frequency distribution e Genotype frequencies Unknown genotypes are assumed to be a random deme and are not counted 39 6 Measures of variation The following measures of variation can be calculated for any of the types of frequency distributions listed in 5 6 1 Measures of variation within demes 6 1 1 Diversity vs Let a collection be characterized by a frequency vector p p1 P2 Pn of its genetic types where n IN and for k 1 n py gt 0 and Xg px 1 The diversity va p of the collection is de
84. pling different alleles or haplotypes in genotypes In Gregorius 1980 it is shown that alpha HWP is equal to the value of alpha for a deme twice the size of the given deme Thus sampling haplotypes in a Hardy Weinberg population of genotypes is equivalent to drawing a deme of haplotypes singly as opposed to pairwise that is twice the size of the given deme of genotypes The designation of the different alleles haplotypes and genotypes in the output is demon strated in Tab 4 Table 4 Examples demonstrating designation of alleles haplotypes and genotypes in the output Genetic type Designation Consists of Allele 1 allele 1 Single locus genotype 1x3 alleles 1 and 3 Ordered single locus genotype 3x1 maternal allele 3 x paternal al lele 1 Haplotype 241 allele 2 at first locus allele 4 at second locus 4 allele 1 at third locus Multilocus genotype 14 23 13 singlelocus genotypes 1 x 4 at first locus 2 x 3 at second lo cus 1 x 3 at third locus Ordered multilocus genotype 12 40 32 maternal haplotype 1 4 3 paternal haplotype 2 0 2 x The output for the various measures and tests is described in Secs 6 7 8 The output of the statistical tests is similar to the example in App F The upper table contains the observed frequencies of the genotypes 44 44 4143 and 4343 and beneath each in square brackets the frequencies expected under the null hypothesis of Hardy Weinberg structur
85. putting results for locus No 1 Locust for locus No 2 Locus2 for locus No 3 Locus3 for locus No 4 Locus4 Additional calculations using the same input file and locus configuration Option N 62 E Keyboard driven execution for subsequent runs Start of the interactive sequence for a subsequent run using the input file example txt The choices made during the first run were stored in the configuration file example txt cfg shown below This configuration can be adopted by replying with a Y in which case the interactive sequence will be skipped A reply of N allows a new choice of frequency distributions and calculations Enter name of input file max 256 characters example txt Enter prefix for names of output files default example txt Return Option file exists example txt cfg p ANALYSIS OF GENOTYPIC STRUCTURE ooooooo o o o Frequency distributions y Maternal frequencies n A MEASURES OF VARIATION WITHIN DEMES Paternal frequencies n Diversity y Allele haplotype frequencies yl Total population differentiation deltaT y Genotype frequencies yl Evenness y finite population size y infinite population size y MEASURES OF VARIATION BETWEEN DEMES Genetic distance y Subpopulation differentiation Dj delta y weights proportional to sample size y weights all equal to 1 No subpops y Test of h
86. r more gene loci in a deme of diploid individuals It is also possible to input haplotypes observed in a deme of gametophytes of one sex by listing the second allele at each locus as unknown t e 1 and gametic sex as specified see 2 2 From genotype data it is possible to construct the following frequency distributions For a single locus e Allele frequencies At a diploid locus each sampled individual contributes two alleles to the overall deme so that heterozygotes reveal more allelic types than homozy gotes The association between alleles in genotypes genotypic structure therefore determines the degree to which a deme detects the allelic types in a population see 4 alpha alpha HWP e Genotype frequencies The genotype of each sampled individual is counted without regard to gametic sex specification Over a set of loci e Multilocus genotype frequencies The multilocus genotype of each sampled individual is counted without regard to gametic sex specification Gametic sex specification In some organisms it is possible to determine which allele at a nuclear gene locus was contributed by the maternal parent For example the seed of most coniferous species contains not only the diploid embryo but also nutritive tissue genetically identical to the maternal gametophyte the primary endosperm or megagametophyte If the endosperm of a seed is subjected to isoenzyme electrophoresis the maternal phenotyp
87. red t e lacking gametic specification Note that individual 9 at Locus 3 in Deme 3 is of unknown genotype 1 1 The last line of the file is an empty line 3 4 Locusi Locus2 Locus3 Locus4 Popi Pop2 Pop3 unformatted 1 0 1 0 2 0 3 0 4 0 1 1 121 121 83 95 118 193 42 42 1 2 121 136 83 102 106 193 36 36 1 3 136 136 76 95 118 121 42 48 1 4 101 136 95 102 106 121 42 48 1 5 121 136 83 102 106 118 36 42 1 6 101 101 83 102 106 193 36 36 1 7 101 136 83 83 106 193 42 48 1 8 101 121 95 95 89 106 42 48 1 9 121 121 76 83 89 193 36 36 1 10 101 121 76 95 118 121 42 42 2 0 1 0 2 0 3 0 4 0 2 1 101 101 76 83 89 106 36 48 2 2 101 101 83 83 106 106 36 48 2 3 101 101 76 76 121 193 36 48 2 4 121 121 83 83 89 89 36 42 2 5 121 121 76 76 121 193 36 42 2 6 101 121 83 95 106 193 36 48 2 7 101 121 83 102 89 193 36 48 2 8 101 121 76 95 89 89 36 48 2 9 101 121 76 102 89 193 36 48 2 10 101 121 76 102 121 121 36 48 3 0 1 0 2 0 3 0 4 0 3 1 132 136 76 83 89 106 36 42 3 2 101 101 76 83 106 106 42 42 3 3 132 136 95 95 121 121 36 48 3 4 101 136 83 95 121 121 36 42 3 5 101 136 83 102 89 89 36 42 3 6 132 132 76 76 89 89 42 42 3 7 101 101 76 102 106 106 48 48 3 8 132 132 95 95 89 121 42 48 3 9 101 136 76 102 1 1 36 36 3 10 132 136 83 83 89 106 48 48 56 C More examples of input files Example 1 The file example txt was already introduced see Sec 2 3 The first deme Population 1 consists of the 4 locus genotypes of 5 individuals
88. rg structure and heterozygosity To each unordered genotypic structure with relative frequencies P of genotypes A A Pj Pj Di lt Pij 1 there corresponds a Hardy Weinberg structure with genotypic frequencies P7 defined by P p and Pi 2pip forifjandij 1 k In this definition p is the relative frequency of allele A from the original genotypic struc ture t e pi Ps I 374i Pig Hardy Weinberg structures result from special mating sys tems such as are specified e g in Gregorius 1989 pp 20 f 68 ff and Hattemer Bergmann amp Ziehe 1993 pp 175ff 44 The purpose here is to detect deviations of 1 an actual genotypic structure P from its corresponding Hardy Weinberg structure PZ and 2 actual heterozygosity from the corresponding Hardy Weinberg heterozygosity Actual heterozygosity is defined by Phet 1 Y Pj and its corresponding Hardy Weinberg heterozygosity by D 1 X pi Assume that a deme of N individuals was randomly drawn from a large population and consider their genotypes at a locus with k alleles Gametic sex if specified is disregarded i e genotypes A A and A A are not distinguished For unordered absolute genotype frequencies Ni i j 1 k Ng Nj Dic Ni N in the deme the absolute frequency N of allele A in the deme of 2N alleles equals N 2N jz Nij Conditioning on the allele frequencies in the deme i e assuming that the true frequency p of allel
89. s containing the snail files are now listed in the file manager EE 25ed30 X Datei Bearbeiten Ansicht Favoriten Extras qe Q Zur ck Y py Suchen i Ordner HRM Adresse 3 C Dokumente und Einstellungen All Users Dokumente gsed30 Wechseln zu Name Gr e Typ Datei und Ordneraufgaben Y a Dateiordner E example txt 2KB Textdokument dere Orte y E example txt cfg 1KB CFG Datei El example txt out txt 31KB Textdokument example txt tab txt 17KB Textdokument lt Elgsed exe 1 902 KB Anwendung 23 The output files contain the following information e The file example txt out txt contains the complete output including the results of all statistical tests but excepting the graphical snail files e The file example txt tab txt contains all of the frequency distributions and all variation parameters in a compact tabular form The separation of columns by a single tab character makes this file easily importable into a spreadsheet program e The directory example txt Snails contains the snail files BW example txt Snails Datei Bearbeiten Ansicht Favoriten Extras 2 Q ari FB suchen gt orde Ev Adresse C Dokumente und Einstellungen All Users Dokumente gsed30 example tx lt t Snails v Es Wechseln zu Name Gr e Typ Jexample txt Snall EquPopsSiz Alleles___ Gene_Pool eps BKB PostScript Mexample txt Snai EquPopSiz Alleles__Gene_Pool wmf 10KB VVMF Bild Andere Orte Rj example txt snai EquPopSiz A
90. sets prefix Snail DemPopSiz EquPopSiz Alleles Genotypes Locus z Gene Pool Combination 1 Loci r y 2 wmf eps Examples of snail file names are example txt Snail DemPopSiz Alleles Gene Pool eps example txt Snail DemPopSiz Alleles Gene Pool wmf example txt Snail DemPopSiz Alleles Locus 1 eps example txt Snail DemPopSiz Alleles Locus 1 wmf example txt Snail DemPopSiz Genotypes Combination 1 Loci example txt Snail DemPopSiz Genotypes Combination 1 Loci example txt Snail DemPopSiz Genotypes Locus 1 eps example txt Snail DemPopSiz Genotypes Locus 1 wmf example txt Snail EquPopSiz Alleles Gene Pool eps example txt Snail EquPopSiz Alleles Gene Pool wmf example txt Snail EquPopSiz Alleles Locus 1 eps example txt Snail EquPopSiz Alleles Locus 1 wmf example txt Snail EquPopSiz Genotypes Combination 1 Loci 1 2 3 4 eps example txt Snail EquPopSiz Genotypes Combination 1 Loci 1 2 3 4 wmf example txt Snail EquPopSiz Genotypes Locus 1 eps example txt Snail EquPopSiz Genotypes Locus 1 wmf eps 1 2 3 4 1 2 3 A4 wmf 4 4 The configuration file name of input file cfg This file contains the selected calculations for use in the next run see Sec 3 3 It is not necessary to understand this automatically created text file see Sec 3 3 which has a form such as 3 YY YY YY Y yy yy nnyy 0 yyy 36 5 Frequency distributions The input to GSED usually consists of the genotypes observed at one o
91. the correctness of the results as I can assume no liability for any errors I would be very grateful for news of any bugs that remain in the program or errors in this manual 50 10 Copyright information on the GSED software GSED 1985 2010 Elizabeth M Gillet Author s address Abt Forstgenetik und Forstpflanzenz chtung Universit t G ttingen B sgenweg 2 37077 G ttingen Germany Email egillet gwdg de GSED website http www uni goettingen de de 67064 html License GSED is free software you can redistribute it under the terms of the GNU Gen eral Public License GPL v 3 as published by the Free Software Foundation GSED is distributed in the hope that it will be useful but WITHOUT ANY WARRANTY without even the implied warranty of merchantability or fitness for a particular purpose Reassem bling is not permitted See the GNU General Public License a copy of which is contained in the file COPYING included in the download file or see http www gnu org licenses GSED implements the scientific data plotting software DISLIN Copyright 2009 Helmut Michels http www dislin de 51 References Bergmann F 1971 Genetische Untersuchungen bei Picea abies mit Hilfe der Isoenzym Identifizierung II M glichkeiten f r genetische Zertifizierung von Forstsaatgut Allge meine Forst und Jagdzeitung 142 278 280 Elandt Johnson R C 1971 Probability Models and Statistical Methods in Genetics John Wiley amp
92. the data in the normal spreadsheet format to enable later revision the GSED input file is made by saving the input as a CSV text file with the extension csv or if available directly as a text only file with extension txt The field separator can be chosen to be a blank a comma or a tab character After saving changing the extension of an input file to dat or inp for example may help to distinguish it from GSED output files which have the extension txt Each input file consists of three parts e The header that defines the numbers and names of the gene loci and demes see 2 1 e The READ format line that specifies how the lines of data are to be interpreted see 2 2 e The deme data containing the genotypes in each deme Examples of input files are given in App C 2 1 Header The header which occupies the first lines of an input file defines the number and names of demes and gene loci It consists of e One line containing the number of demes and the number of gene loci separated by a blank comma or tab character e One line per gene locus containing the name of the locus 12 characters The first named locus is referred to as Locus 1 in the remainder of the data the second named locus as Locus 2 etc e One line per deme containing the name of the deme lt 40 characters The first named deme is referred to as Deme 1 in the remainder of the data the second named deme as Deme 2 etc 2 2 READ form
93. ubsequent data lines contain each of 2 2x n integers where n is the number of gene loci see 2 2 Advantages and disadvantages of formatted input e Advantages Shorter data lines since separators blanks commas tab characters between integers are not needed Inclusion of non numeric text in specified columns of the data lines since the FORTRAN READ format can be constructed to skip over these columns e Disadvantage The integers must appear in the same columns in every data line as specified by the FORTRAN READ format Examples of FORTRAN READ formats are shown in 2 3 The following box gives a short description of each of the elements of FORTRAN READ format that are of relevance here for further information consult any FORTRAN language reference manual nlw The I field descriptor indicates that an integer is to be read in a field of width w i e w columns The n specifies the number of integers that are to be read in consecutive fields of width w nX The X field descriptor indicates that n columns are to be skipped r The repeat count r indicates that the contents of the parentheses are to be repeated r times Separates field descriptors Separates field descriptors and causes reading to continue on a new line Parentheses enclose the entire FORTRAN READ format Examples of FORTRAN READ formats Example 1 10 214 1X 10 212 reads 22 integers including a 10 locus genotype from the
94. us distinguishing for example between the genotypes 1 x 3 and 3 x 1 see Tab 4 Over a set of loci e Haplotype frequencies among maternal contributions The set of maternal haplotypes represents a deme of the haplotypes in the population of successful maternal ga metes e Haplotype frequencies among paternal contributions The set of paternal haplotypes represents a deme of the haplotypes in the population of successful paternal ga metes e Haplotype frequencies A deme of the haplotypes of successful gametes is constructed by counting both the maternal and the paternal haplotypes of the sampled individuals Since each sampled individual contributes two haplotypes the association between haplotypes in genotypes genotypic structure determines the degree to which a deme detects the haplotypes present in a population see Allele frequencies above and see 4 alpha alpha HWP e Ordered multilocus genotype frequencies maternal x paternal haplotypes The set of ordered genotypes represents a deme of the genotypes in the population of success ful fusions between female and male gametes Ordered multilocus genotype frequen cies distinguish between maternal and paternal haplotypes For example whereas the ordered genotype 1 2 1 2 results from fusion of the maternal haplotype 1 1 and the paternal haplotype 2 2 the ordered genotype 21 1 2 is the product of maternal haplotype 2 1
95. us answers to the questions listed under the headings of Choice of frequency distributions and Choice of calculations see App D The name of the configuration file consists of the name of the input file followed by the extension cfg for example example txt cfg If a configuration file exists then a configuration table such as that presented in App E is typed on the screen after the Locus configuration has been specified 29 If the answer to the subsequent question Do you want to adopt this configuration is answered by Y then Choice of frequency distributions and Choice of calculations are skipped The question Should gametic sex specification if given be retained 77 is still posed since in the case of gametic sex specification one may want to perform the same calculations with and without regard of gametic sex see Sec 5 If the answer to Do you want to adopt this configuration is N then Choice of frequency distributions and Choice of calculations must be made anew as in App E 3 4 Sorting of haplotypes and genotypes An answer of Y to any of the following questions causes the lists of encountered haplotypes and genotypes to be printed in lexicographic order Frequency distributions 7 Test of homogeneity of the deme distributions 7 Test of Hardy Weinberg structure and heterozygosity 7 Test of product structure only if gametic sex is speci

GSED 3.0 User's Manual (April 2010)

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