Multiple independent recombinations led to hermaphroditism in grapevine

Significance We studied the grape sex-determining region (SDR) in 12 Vitis genomes and demonstrated its conservation across 556 genotypes including 193 accessions from 47 world-wide wild grapevine species and 363 accessions of cultivated grapevine. Although the grape SDR is recombination free in all wild species, we found two distinct hermaphrodite (H) haplotypes (H1 and H2) among the cultivated grapevines, both chimeras of male (M) and female (f) haplotypes. The two independent recombinations carry different genetic signatures which long predate the domestication of grapevine, suggesting independent evolutions of this trait in wild European grapevine gene pools prior to human domestication.

In order to have a better understanding of the flower sex determination in the Vitis genus, we examined the grape SDR using the whole-genome assembly of 12 genotypes, including 4 genomes sequenced and assembled in this study, genome-wide shotgun resequencing of 556 individuals, targeted Amplicon sequencing of 167 individuals and transcriptome sequencing of 48 individuals which represents a large diversity of wild and cultivated germplasm resources.
To assemble the chromosome-and chromosome-arm level optical maps, uHMW DNA was labeled and stained using the Bionano Genomics Direct Label and Stain (DLS) method as previously described (5). Unlike previous mapping technologies, Bionano DLS enables non-destructive, single fluorophore labeling of DNA molecules at CTTAAG sites. Labeled and stained DNA molecules were separated, stretched, imaged and digitized using a Bionano Saphyr system. One subset of 515,727 molecules (174.765 Gb total length) with a minimum length of 250 Kb and N50 334 Kb was used for assembly into maps using the Bionano Solve software as previously described (6). The The current genetic model of sex determination in Vitis describes genetic dominance between alleles of male (M) > hermaphrodite (H) > female (f) (21,22). Male-flowering individuals are expected to carry one female haplotype and one male haplotype at the sex locus (M/f). Female individuals carry two female haplotypes (f/f). Using this framework, male-associated variants and female-associated variants are expected to have increased minor allele frequency and violate Hardy Weinberg equilibrium. The allele frequency spectrum for each population was calculated based on the genome-wide mean and standard deviation using a 10 kb sliding window and the z-score was calculated for each window. Deviation from Hardy Weinberg equilibrium was tested using a χ 2 goodness-offit test in R (v.3.5.0). SNPs that significantly deviate from HWE (p < 0.05) were summed for each 1kb window. The z-score for each window was calculated based on the genomewide mean and standard deviation and then the P-value was calculated using pnorm function in R (v.3.5.0). Linkage disequilibrium was estimated using all sites with MAF>0.05 and missing rate less than 0.5. Sites were randomly thinned to 30% and R 2 within 1Mb window were calculated using PLINK v.1.90 (19).

Estimating divergence at the SDR
Divergence time between H1 and H2 haplotypes was estimated based on conserved regions of the sex-determining locus using the program Mugsy (23). Samples included; four M haplotypes from V. cinerea, V. arizonica, and V. sylvestris; one female haplotype from V. rupestris 'B38'; H1 haplotypes from 'Chardonnay', 'Riesling', 'Carmé nè re' and 'Zinfandel'; two H2 haplotypes from 'Chardonnay', and 'Riesling'; and an unclassified haplotype from V. rotundifolia as the outgroup. A total of 15 conserved blocks that were larger than 1,000 bp (SI Appendix, Fig. S6) were identified across the SDR. Conserved blocks within the C region of the SDR were concatenated due to the lack of historical recombination observed for this region. After removing assembly gaps and poorly aligned positions using Gblocks (24), multiple sequence alignment was conducted using PRANK (25). The Akaike information criterion (AIC) indicated that a Hasegawa-Kishono-Yano (HKY) model +G+I was the best-fitted substitution model by jModelTest 2 v2.1. 10 (26). The maximum likelihood(ML) phylogeny of these haplotypes was further calculated using RAxML v8.2.4 with a GTRCTA site rate substitution model (27). Genetic divergence for the ML phylogeny was estimated by Bayesian analysis with the software BEAST v.2.5.2 with a relaxed molecular clock for 80 × 10 6 Markov chain Monte-Carlo cycles (28). The 95% credibility interval statistics for nodes and branches were summarized after a burn-in of 25% of the total generations that were sampled every 5,000 generations using TreeAnnotator v.1.8.3 implemented in BEAST. Divergence time was calculated by constraining the crown age of the Vitis genus with a normal prior distribution of 46.9 MYA (29).
LTRs were detected using the LTRharvest algorithm integrated with GenomeTools package (30). The target site sequences (TSD) of intact LTRs were extracted and aligned using MUSCLE (31). The genetic distance between the two TSDs was estimated using Kimura's two-parameter model (32). The insertion time of intact LTRs was calculated as T = K/2μ, where K is the genetic distance between the two TSDs and μ is the mutation rate. A mutation rate of 2.5 × 10 −9 mutations per nucleotide per year was assumed as has been shown in previous studies.

Pedigree relationships between accessions and tracking of hermaphroditic alleles
To clarify the historical relationship between grape cultivars with either the H1 or H2 hermaphroditic haplotypes, we accessed the Vitis International Variety Catalogue (http://www.vivc.de/) and queried parent-offspring relationship data for the 539 genebank accessions as well as 17 samples sequenced locally. A list of grandparent-parentoffspring relationships was summarized as a pedigree network of the sampled cultivars in this study using the igraph package in R (33) (Figure 4, SI Appendix, Dataset S3).

Genome-wide association studies and allele-specific read depth association for flower sex
There are three types of flower sex phenotype in the Vitis genus: female, male, and hermaphroditic. Flower sex was decomposed as the interaction of two factors, one determining male sterility/fertility, the other determining female-sterility/fertility. Hermaphroditic is a combination of male-fertility and female-fertility. We conducted a genome-wide association study (GWAS) using TASSEL 5 and alleles with MAF>0.05 and missing rate less than 0.5 (34). The association between the variance and the phenotype was detected using a mixed linear model (MLM) considering both population structure and the kinship matrix as covariance (34).
To measure the impact of gene expression in determining flower sex, flower buds were harvested from 29 accessions from 9 wild species (V. amurensis, V. cinerea, V. labrusca, V. acerifolia, V. palmata, V. riparia, V. rupestris, V. vulpina, and V. sylvestris) and 13 hermaphroditic V. vinifera (domesticated) accessions, and 6 bulked female and male samples from a bi-parental population (SI Appendix, Fig. S7, Table S3). RNA was extracted from the flower buds of each accession using a Sigma Spectrum RNA kit (Sigma) at stage H, which is around one week before anthesis. The concentration and purity of total RNA were tested with the Synergy HT Nanodrop system (Biotek, Germany). For each sample, 500ng of total RNA was used for library construction with Illumina Truseq kit. Over 20 million paired-end reads were generated for each sample with Hiseq2000. Clean reads were mapped to the CabSau_f reference genome using STAR (35), and then reads were split into exon segments and the mapping qualities were adjusted for variant detection. The downstream variant detection was identical to Senteion DNA Pipeline for Variant Detection, except that the soft clipped based were excluded and a lower minimum phred-scaled confidence was set as 20 (13). The number of uniquely mapped reads that supported each reference allele and alternative allele were summarized using pysam (https://github.com/pysam-developers/pysam). The association between the standardized number of reads supporting reference/alternative allele and the phenotypes were detected using a Kruskal-Wallis rank sum test by R (v.3.5.0).

Marker development for Amplicon sequencing-based genotyping
In order to make the primers work for diverse species in the Vitis genus, the primers were designed using a genus-wide approach similar to what we previously described 4 . We excluded all the variances with MAF >0.05 in the primer design to decrease possible mismatch between the primers and the template. The MAF is calculated based on variances called from 556 accessions of WGS in the previous section. The candidate region with sex-linked SNPs was searched for primer using Primer3 (36) with target size between 200bp-270bp (Optimum 250bp) and annealing temperatures (Tm) between 57-64 °C (Optimum 60 °C). The rhAmpseq markers were designed using the rhAmpSeq Design Tool developed by Integrated DNA Technologies, Inc. (IDT, Coralville, IA, USA). rhAmpSeq amplification, indexing, and pooling were conducted as described previously(1). In the Ampseq platform, two runs of PCR are performed, 1) amplify a multiplex of target-specific primers with linkers, and 2) amplify the sample-specific barcoding was performed (37). The amplicon from Ampseq or rhAmpSeq were pooled and sequenced with an Illumina MiSeq (Illumina, San Diego, CA, USA) with paired-end 2 x 150 bp mode. Reads were demultiplexed and genotyped using an in-house optimized pipeline (https://bitbucket.org/cornell_bioinformatics/amplicon).

Phenotype and Genotype prediction for the SDR
Because sex-linked sites violate Mendel's law of segregation, we first inferred the loglikelihood of genotype for each bi-allelic site for each sample independently without considering population genotype, which is an approach proposed by Li (38) and adopted in the estimation of PL (the phred-scaled genotype likelihoods) in the GATK HaplotypeCaller (14). For each sample, assuming the number of reads that covering one allele follows the binomial distribution with parameters n and p, abbreviated B(n,p), where n is the total number of reads that are uniquely aligned to this site, p is the probability that the reads supporting the alternative allele. Then we assume homologous reference genotype (denoted as 0) follows B(n,0.001), the heterozygous genotype (denoted as 1) follows B(n,0.5), and the homologous alternative genotype (denoted as 2) follows B(n,0.999). The log-likelihood of each genotype (0, 1, 2) given the read counts that we have observed is calculated by -log10 P(Data|genotype), then the genotype with highest likelihood is chosen for each site in the downstream analysis. To determine the genotype for the A, B, C, D region, we fit all the genotypes in one region into a linear regression with slope equals 0 and the intersect equals 0,1,2 respectively. The model with the smallest Least Squares Fitting were picked for each region. To determine the flower sex phenotype, we only need consider the genotype in A region and C region, when C region is homozygous reference genotype (f/f), the phenotype is male-sterile, when A region is not homozygous reference genotype (f/f), the phenotype is female-sterile. We used Bayes factor hypothesis testing comparing the null hypothesis that all sites are homozygous reference and the alternative hypothesis that all sites are heterozygous, = where, H0 B(n0,p0), H1 B(n1,p1). B(n,p) is another binomial distribution, in which the n denotes the total number of allelic sites considering all sites in this region, which is 2 fold of the total sites considered. And the p is the probability of the alternative allelic sites in this region. BF > 3 indicates substantial evidence supporting that the region examined is heterozygous, while BF<0.33 indicates substantial evidence supporting that the region is homozygous reference genotype. When using only one site to predict the flower sex, the BF ranges from 0.5 to 3 due to the small sample size. BF ranges from 0.5-1 to 1-3 only indicate anecdotal evidence supporting H0 or H1 in general, however in our prediction they are 100% consistent with the phenotype. Therefore, smaller BFs are still trustable when only using a few sites in the prediction. The package of Vitis_flower_sex_predictor is publicly available at (https://bitbucket.org/cornell_bioinformatics/flower_sex_predictor)  Genetic divergence between two SDR contigs in V.cinerea B9 and SDR in V. riparia 'Manitoba 37' are significantly different (unpaired t-test). c. Dot plot comparison indicating structure variance between two potential SDR contigs in V.cinerea 'B9' and SDR in V. riparia 'Manitoba 37'.    vDNArei049E01_E04_VcinereaB9_CAGGTTCA_TTGCTTGC  vDNArei049E01_F12_456057_TTCGGCTA_TTGCTTGC  vDNArei049E01_H10_456080_TCAGTAGG_TTGCTTGC  vDNArei049E01_C08_456019_GCCTTCTT_TTGCTTGC  vDNArei049E01_D12_456037_TTCCAGGT_TTGCTTGC  vDNArei049E01_C12_456024_TTACGTGC_TTGCTTGC  vDNArei049E01_B04_456002_CACCAGTT_TTGCTTGC  vDNArei049E01_E05_VcinereaB9_CCTTGGAA_TTGCTTGC  vDNArei049E01_H04_456074_CATTGACG_TTGCTTGC  vDNArei049E01_H02_456072_AGGTCAAC_TTGCTTGC  vDNArei049E01_G12_456070_TTGCAACG_TTGCTTGC  vDNArei049E01_H08_456078_GGCGAATA_TTGCTTGC  vDNArei049E01_G10_456068_TCACCTAG_TTGCTTGC  vDNArei049E01_G06_456063_CTCTCAGA_TTGCTTGC  vDNArei049E01_G08_456065_GGAATGTC_TTGCTTGC  vDNArei049E01_G09_456067_GTGGTATG_TTGCTTGC  vDNArei049E01_G03_456060_ATCTCCTG_TTGCTTGC  vDNArei049E01_F01_456045_ACCAAGCA_TTGCTTGC  vDNArei049E01_F04_456048_CATACGGA_TTGCTTGC  vDNArei049E01_F02_456046_AGGCAATG_TTGCTTGC  vDNArei049E01_E10_456042_TAGCTTCC_TTGCTTGC  vDNArei049E01_E09_456041_GTCAACAG_TTGCTTGC  vDNArei049E01_E07_456039_GAGCTCTA_TTGCTTGC  vDNArei049E01_F03_456047_ATCGTGGT_TTGCTTGC  vDNArei049E01_D11_456035_TCTGTCGT_TTGCTTGC  vDNArei049E01_D09_456033_GTATCGAG_TTGCTTGC  vDNArei049E01_D04_456028_CAGGATGT_TTGCTTGC  vDNArei049E01_D03_456027_AGTGGCAA_TTGCTTGC  vDNArei049E01_C01_456012_AAGTGCAG_TTGCTTGC  vDNArei049E01_B03_456001_AGTACACG_TTGCTTGC  vDNArei049E01_B11_456010_TCGTGCAT_TTGCTTGC  vDNArei049E01_B08_456007_GCCTATGT_TTGCTTGC  vDNArei049E01_A05_455100_CCAAGGTT_TTGCTTGC  vDNArei049E01_A12_455108_TGGCTCTT_TTGCTTGC  vDNArei049E01_A09_455105_GGTACGAA_TTGCTTGC  vDNArei049E01_A01_455096_AACCACTC_TTGCTTGC  vDNArei049E01_H03_456073_ATGCCTAG_TTGCTTGC  vDNArei049E01_H06_456076_CTGCCATA_TTGCTTGC  vDNArei049E01_G11_456069_TGCTCTAC_TTGCTTGC  vDNArei049E01_H05_456075_CGCAATGT_TTGCTTGC  vDNArei049E01_G05_456062_CGATTCTG_TTGCTTGC  vDNArei049E01_F09_456054_GTCGTTAC_TTGCTTGC  vDNArei049E01_F07_456052_GAGTGTGT_TTGCTTGC  vDNArei049E01_A04_455099_CACAGACT_TTGCTTGC  vDNArei049E01_D10_456034_TACTGCTC_TTGCTTGC  vDNArei049E01_D01_456025_ACACTACC_TTGCTTGC  vDNArei049E01_H12_456083_TTGGTGCA_TTGCTTGC  vDNArei049E01_H07_456077_GCAGAAGA_TTGCTTGC  vDNArei049E01_H01_456071_ACGGTACA_TTGCTTGC  vDNArei049E01_H11_456082_TGCTTGCT_TTGCTTGC  vDNArei049E01_G02_456059_AGGTAGGA_TTGCTTGC  vDNArei049E01_G01_456058_ACGAACGA_TTGCTTGC  vDNArei049E01_F11_456056_TGCCTCAA_TTGCTTGC  vDNArei049E01_G07_456064_GATCTTGC_TTGCTTGC  vDNArei049E01_G04_456061_CATGAGCA_TTGCTTGC  vDNArei049E01_F10_456055_TATGGCAC_TTGCTTGC  vDNArei049E01_E12_456044_TTCCTCCT_TTGCTTGC  vDNArei049E01_E11_456043_TCTTACGG_TTGCTTGC  vDNArei049E01_E08_456040_GCTGTAAG_TTGCTTGC  vDNArei049E01_F06_456050_CTCGACTT_TTGCTTGC  vDNArei049E01_F05_456049_CGAGAGAA_TTGCTTGC  vDNArei049E01_F08_456053_GGAACATG_TTGCTTGC  vDNArei049E01_E02_Horizon_AGGAACAC_TTGCTTGC  vDNArei049E01_D08_456032_GCTGAATC_TTGCTTGC  vDNArei049E01_E06_456038_CTCACCAA_TTGCTTGC  vDNArei049E01_D07_456031_GACTTGTG_TTGCTTGC  vDNArei049E01_D06_456030_CTAGCTCA_TTGCTTGC  vDNArei049E01_D05_456029_CCTTCCAT_TTGCTTGC  vDNArei049E01_E03_Horizon_ATAACGCC_TTGCTTGC  vDNArei049E01_C11_456023_TCTAGGAG_TTGCTTGC  vDNArei049E01_C10_456022_TACGGTCT_TTGCTTGC  vDNArei049E01_C09_456020_GTAACCGA_TTGCTTGC  vDNArei049E01_D02_456026_AGAAGTGG_TTGCTTGC  vDNArei049E01_C07_456018_GACCGATA_TTGCTTGC  vDNArei049E01_C06_456017_CTACATCC_TTGCTTGC  vDNArei049E01_C05_456016_CCTCGTTA_TTGCTTGC  vDNArei049E01_C04_456015_CAGAACTG_TTGCTTGC  vDNArei049E01_B10_456009_TACAGAGC_TTGCTTGC  vDNArei049E01_B12_456011_TGGTTCGA_TTGCTTGC  vDNArei049E01_B07_456005_GAACCTTC_TTGCTTGC  vDNArei049E01_B06_456004_CTAAGACC_TTGCTTGC  vDNArei049E01_B05_456003_CCAGTATC_TTGCTTGC  vDNArei049E01_B09_456008_GGTTAGCT_TTGCTTGC  vDNArei049E01_C02_456013_AGAAGCCT_TTGCTTGC  vDNArei049E01_B02_455110_ACTCTGAG_TTGCTTGC  vDNArei049E01_A06_455102_CGGAGTAT_TTGCTTGC  vDNArei049E01_A08_455104_GCATAGTC_TTGCTTGC  vDNArei049E01_A10_455106_GTTCCATG_TTGCTTGC  vDNArei049E01_A03_455098_AGGTGTTG_TTGCTTGC  vDNArei049E01_A02_455097_ACTCTCCA_TTGCTTGC  vDNArei049E01_A11_455107_TCCTGACT_TTGCTTGC  vDNArei049E01_A07_455103_CTTACAGC_TTGCTTGC  vDNArei049E01_B01_455109_AAGGCTCT_TTGCTTGC  vDNArei049E01_H09_456079_GTTAAGCG_TTGCTTGC  vDNArei049E01_C03_456014_AGTCAGGT_TTGCTTGC vDNAfen083G11_F09_F2_124_GTCGTTAC_TGTAGACC  vDNAfen083G11_G04_F2_064_CATGAGCA_TGTAGACC  vDNAfen083G11_G12_V_riparia37_TTGCAACG_TGTAGACC  vDNAfen083G11_E01_F2_016_ACAGTGAC_TGTAGACC  vDNAfen083G11_E12_F2_160_TTCCTCCT_TGTAGACC  vDNAfen083G11_F03_F2_048_ATCGTGGT_TGTAGACC  vDNAfen083G11_G01_F2_018_ACGAACGA_TGTAGACC  vDNAfen083G11_D01_F2_010_ACACTACC_TGTAGACC  vDNAfen083G11_H11_F2_096_TGCTTGCT_TGTAGACC  vDNAfen083G11_H01_V_riparia37_ACGGTACA_TGTAGACC  vDNAfen083G11_G02_F2_036_AGGTAGGA_TGTAGACC  vDNAfen083G11_G10_F2_142_TCACCTAG_TGTAGACC  vDNAfen083G11_E03_F2_046_ATAACGCC_TGTAGACC  vDNAfen083G11_D06_F2_088_CTAGCTCA_TGTAGACC  vDNAfen083G11_C06_F2_086_CTACATCC_TGTAGACC  vDNAfen083G11_A10_F2_133_GTTCCATG_TGTAGACC  vDNAfen083G11_B08_F2_110_GCCTATGT_TGTAGACC  vDNAfen083G11_C03_F2_044_AGTCAGGT_TGTAGACC  vDNAfen083G11_G05_F2_076_CGATTCTG_TGTAGACC  vDNAfen083G11_G11_BLANK_TGCTCTAC_TGTAGACC  vDNAfen083G11_H02_BLANK_AGGTCAAC_TGTAGACC  vDNAfen083G11_H03_BLANK_ATGCCTAG_TGTAGACC  vDNAfen083G11_G09_F2_127_GTGGTATG_TGTAGACC  vDNAfen083G11_H10_F2_077_TCAGTAGG_TGTAGACC  vDNAfen083G11_F11_F2_150_TGCCTCAA_TGTAGACC  vDNAfen083G11_D03_F2_045_AGTGGCAA_TGTAGACC  vDNAfen083G11_H08_F2_051_GGCGAATA_TGTAGACC  vDNAfen083G11_G03_F2_049_ATCTCCTG_TGTAGACC  vDNAfen083G11_F12_F2_161_TTCGGCTA_TGTAGACC  vDNAfen083G11_F04_F2_063_CATACGGA_TGTAGACC  vDNAfen083G11_E06_F2_093_CTCACCAA_TGTAGACC  vDNAfen083G11_D10_F2_138_TACTGCTC_TGTAGACC  vDNAfen083G11_C04_F2_057_CAGAACTG_TGTAGACC  vDNAfen083G11_D08_F2_113_GCTGAATC_TGTAGACC  vDNAfen083G11_H09_F2_065_GTTAAGCG_TGTAGACC  vDNAfen083G11_D12_F2_159_TTCCAGGT_TGTAGACC  vDNAfen083G11_D05_F2_072_CCTTCCAT_TGTAGACC  vDNAfen083G11_D02_F2_032_AGAAGTGG_TGTAGACC  vDNAfen083G11_C11_F2_146_TCTAGGAG_TGTAGACC  vDNAfen083G11_F10_F2_141_TATGGCAC_TGTAGACC  vDNAfen083G11_E10_F2_139_TAGCTTCC_TGTAGACC  vDNAfen083G11_B05_F2_067_CCAGTATC_TGTAGACC  vDNAfen083G11_F02_F2_034_AGGCAATG_TGTAGACC  vDNAfen083G11_H06_F2_019_CTGCCATA_TGTAGACC  vDNAfen083G11_B07_F2_101_GAACCTTC_TGTAGACC  vDNAfen083G11_E07_F2_104_GAGCTCTA_TGTAGACC  vDNAfen083G11_F05_F2_074_CGAGAGAA_TGTAGACC  vDNAfen083G11_C05_F2_068_CCTCGTTA_TGTAGACC  vDNAfen083G11_B02_F2_023_ACTCTGAG_TGTAGACC  vDNAfen083G11_C01_F2_008_AAGTGCAG_TGTAGACC  vDNAfen083G11_B03_F2_043_AGTACACG_TGTAGACC  vDNAfen083G11_C07_F2_102_GACCGATA_TGTAGACC  vDNAfen083G11_F07_F2_105_GAGTGTGT_TGTAGACC  vDNAfen083G11_A11_F2_144_TCCTGACT_TGTAGACC  vDNAfen083G11_A04_F2_052_CACAGACT_TGTAGACC  vDNAfen083G11_H04_F2_151_CATTGACG_TGTAGACC  vDNAfen083G11_H12_F2_108_TTGGTGCA_TGTAGACC  vDNAfen083G11_G06_F2_095_CTCTCAGA_TGTAGACC  vDNAfen083G11_F01_F2_017_ACCAAGCA_TGTAGACC  vDNAfen083G11_E09_F2_123_GTCAACAG_TGTAGACC  vDNAfen083G11_F06_F2_094_CTCGACTT_TGTAGACC  vDNAfen083G11_E02_F2_033_AGGAACAC_TGTAGACC  vDNAfen083G11_D07_F2_103_GACTTGTG_TGTAGACC  vDNAfen083G11_E04_F2_060_CAGGTTCA_TGTAGACC  vDNAfen083G11_C09_F2_121_GTAACCGA_TGTAGACC  vDNAfen083G11_C08_F2_111_GCCTTCTT_TGTAGACC  vDNAfen083G11_B06_F2_085_CTAAGACC_TGTAGACC  vDNAfen083G11_D04_F2_059_CAGGATGT_TGTAGACC  vDNAfen083G11_A05_F2_066_CCAAGGTT_TGTAGACC  vDNAfen083G11_A07_F2_099_CTTACAGC_TGTAGACC  vDNAfen083G11_A01_F2_003_AACCACTC_TGTAGACC  vDNAfen083G11_H05_F2_162_CGCAATGT_TGTAGACC  vDNAfen083G11_A02_F2_020_ACTCTCCA_TGTAGACC  vDNAfen083G11_H07_F2_037_GCAGAAGA_TGTAGACC  vDNAfen083G11_B10_F2_135_TACAGAGC_TGTAGACC  vDNAfen083G11_B12_F2_156_TGGTTCGA_TGTAGACC  vDNAfen083G11_A09_F2_118_GGTACGAA_TGTAGACC  vDNAfen083G11_A08_F2_109_GCATAGTC_TGTAGACC  vDNAfen083G11_E08_F2_114_GCTGTAAG_TGTAGACC  vDNAfen083G11_G07_F2_106_GATCTTGC_TGTAGACC  vDNAfen083G11_C12_F2_157_TTACGTGC_TGTAGACC  vDNAfen083G11_E05_F2_073_CCTTGGAA_TGTAGACC  vDNAfen083G11_G08_F2_116_GGAATGTC_TGTAGACC  vDNAfen083G11_C02_F2_028_AGAAGCCT_TGTAGACC  vDNAfen083G11_E11_F2_149_TCTTACGG_TGTAGACC  vDNAfen083G11_B11_F2_145_TCGTGCAT_TGTAGACC  vDNAfen083G11_B01_F2_004_AAGGCTCT_TGTAGACC  vDNAfen083G11_A12_F2_153_TGGCTCTT_TGTAGACC  vDNAfen083G11_F08_F2_115_GGAACATG_TGTAGACC  vDNAfen083G11_D11_F2_148_TCTGTCGT_TGTAGACC  vDNAfen083G11_D09_F2_122_GTATCGAG_TGTAGACC  vDNAfen083G11_C10_F2_137_TACGGTCT_TGTAGACC  vDNAfen083G11_B09_F2_119_GGTTAGCT_TGTAGACC  vDNAfen083G11_B04_F2_056_CACCAGTT_TGTAGACC  vDNAfen083G11_A03_F2_040_AGGTGTTG_TGTAGACC   Genetic Distance