Dataset Information

Assessment of Genetic Differentiation and Linkage Disequilibrium in Solanum pimpinellifolium Using Genome-Wide High-Density SNP Markers.

ABSTRACT: To mine new favorable alleles for tomato breeding, we investigated the feasibility of utilizing Solanum pimpinellifolium as a diverse panel of genome-wide association study through the restriction site-associated DNA sequencing technique. Previous attempts to conduct genome-wide association studies using S. pimpinellifolium were impeded by an inability to correct for population stratification and by lack of high-density markers to address the issue of rapid linkage disequilibrium decay. In the current study, a set of 24,330 SNPs was identified using 99 S. pimpinellifolium accessions from the Tomato Genetic Resource Center. Approximately 84% of PstI site-associated DNA sequencing regions were located in the euchromatic regions, resulting in the tagging of most SNPs on or near genes. Our genotypic data suggested that S. pimpinellifolium were divided into three single-ancestry subpopulations and four mixed-ancestry subpopulations. Additionally, our SNP genotypic data consistently confirmed the genetic differentiation, achieving a relatively reliable correction of population stratification. Previous studies utilized the 8K tomato SNP array, SolCAP, to investigate the genetic variation of S. pimpinellifolium and we performed a meta-analysis of these genotypes. The result suggested SolCAP array was less appropriate to profile the genetic differentiation of S. pimpinellifolium when more accessions were involved because the samples belonging to the same accession demonstrated different genome patterns. Moreover, as expected, rapid linkage disequilibrium decay was observed in S. pimpinellifolium, especially in euchromatic regions. Approximately two-thirds of the flanking SNP markers did not display linkage disequilibrium based on r2 = 0.1. However, the 18-Kb linkage disequilibrium decay indeed reveals the potential of single-gene resolution in GWAS when markers are saturated.

SUBMITTER: Lin YP

PROVIDER: S-EPMC6505160 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Assessment of Genetic Differentiation and Linkage Disequilibrium in Solanum pimpinellifolium Using Genome-Wide High-Density SNP Markers.

Lin Ya-Ping YP Liu Chu-Yin CY Chen Kai-Yi KY

G3 (Bethesda, Md.) 20190507 5

To mine new favorable alleles for tomato breeding, we investigated the feasibility of utilizing Solanum pimpinellifolium as a diverse panel of genome-wide association study through the restriction site-associated DNA sequencing technique. Previous attempts to conduct genome-wide association studies using S. pimpinellifolium were impeded by an inability to correct for population stratification and by lack of high-density markers to address the issue of rapid linkage disequilibrium d ...[more]

PMID: 30858236

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Project description:BackgroundThe extent of linkage disequilibrium (LD) within a population determines the number of markers that will be required for successful association mapping and marker-assisted selection. Most studies on LD in cattle reported to date are based on microsatellite markers or small numbers of single nucleotide polymorphisms (SNPs) covering one or only a few chromosomes. This is the first comprehensive study on the extent of LD in cattle by analyzing data on 1,546 Holstein-Friesian bulls genotyped for 15,036 SNP markers covering all regions of all autosomes. Furthermore, most studies in cattle have used relatively small sample sizes and, consequently, may have had biased estimates of measures commonly used to describe LD. We examine minimum sample sizes required to estimate LD without bias and loss in accuracy. Finally, relatively little information is available on comparative LD structures including other mammalian species such as human and mouse, and we compare LD structure in cattle with public-domain data from both human and mouse.ResultsWe computed three LD estimates, D', Dvol and r2, for 1,566,890 syntenic SNP pairs and a sample of 365,400 non-syntenic pairs. Mean D' is 0.189 among syntenic SNPs, and 0.105 among non-syntenic SNPs; mean r2 is 0.024 among syntenic SNPs and 0.0032 among non-syntenic SNPs. All three measures of LD for syntenic pairs decline with distance; the decline is much steeper for r2 than for D' and Dvol. The value of D' and Dvol are quite similar. Significant LD in cattle extends to 40 kb (when estimated as r2) and 8.2 Mb (when estimated as D'). The mean values for LD at large physical distances are close to those for non-syntenic SNPs. Minor allelic frequency threshold affects the distribution and extent of LD. For unbiased and accurate estimates of LD across marker intervals spanning < 1 kb to > 50 Mb, minimum sample sizes of 400 (for D') and 75 (for r2) are required. The bias due to small samples sizes increases with inter-marker interval. LD in cattle is much less extensive than in a mouse population created from crossing inbred lines, and more extensive than in humans.ConclusionFor association mapping in Holstein-Friesian cattle, for a given design, at least one SNP is required for each 40 kb, giving a total requirement of at least 75,000 SNPs for a low power whole-genome scan (median r2 > 0.19) and up to 300,000 markers at 10 kb intervals for a high power genome scan (median r2 > 0.62). For estimation of LD by D' and Dvol with sufficient precision, a sample size of at least 400 is required, whereas for r2 a minimum sample of 75 is adequate.

Project description:Characterization of genetic diversity, population structure, and linkage disequilibrium is a prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes, including advanced "Kabuli" breeding lines and Iranian landrace "Desi" chickpea genotypes, were genotyped using DArTseq-Based single nucleotide polymorphism (SNP) markers. Out of 3339 SNPs, 1152 markers with known chromosomal position were selected for genome diversity analysis. The number of mapped SNP markers varied from 52 (LG8) to 378 (LG4), with an average of 144 SNPs per linkage group. The chromosome size that was covered by SNPs varied from 16,236.36 kbp (LG8) to 67,923.99 kbp (LG5), while LG4 showed a higher number of SNPs, with an average of 6.56 SNPs per Mbp. Polymorphism information content (PIC) value of SNP markers ranged from 0.05 to 0.50, with an average of 0.32, while the markers on LG4, LG6, and LG8 showed higher mean PIC value than average. Unweighted neighbor joining cluster analysis and Bayesian-based model population structure grouped chickpea genotypes into four distinct clusters. Principal component analysis (PCoA) and discriminant analysis of principal component (DAPC) results were consistent with that of the cluster and population structure analysis. Linkage disequilibrium (LD) was extensive and LD decay in chickpea germplasm was relatively low. A few markers showed r2 ≥ 0.8, while 2961 pairs of markers showed complete LD (r2 = 1), and a huge LD block was observed on LG4. High genetic diversity and low kinship value between pairs of genotypes suggest the presence of a high genetic diversity among the studied chickpea genotypes. This study also demonstrates the efficiency of DArTseq-based SNP genotyping for large-scale genome analysis in chickpea. The genotypic markers provided in this study are useful for various association mapping studies when combined with phenotypic data of different traits, such as seed yield, abiotic, and biotic stresses, and therefore can be efficiently used in breeding programs to improve chickpea.

Project description:BackgroundHuman genome contains millions of common single nucleotide polymorphisms (SNPs) and these SNPs play an important role in understanding the association between genetic variations and human diseases. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), thus it is not necessary to genotype all SNPs for association study. Many algorithms have been developed to find a small subset of SNPs called tag SNPs that are sufficient to infer all the other SNPs. Algorithms based on the r2 LD statistic have gained popularity because r2 is directly related to statistical power to detect disease associations. Most of existing r2 based algorithms use pairwise LD. Recent studies show that multi-marker LD can help further reduce the number of tag SNPs. However, existing tag SNP selection algorithms based on multi-marker LD are both time-consuming and memory-consuming. They cannot work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.ResultsWe propose an efficient algorithm called FastTagger to calculate multi-marker tagging rules and select tag SNPs based on multi-marker LD. FastTagger uses several techniques to reduce running time and memory consumption. Our experiment results show that FastTagger is several times faster than existing multi-marker based tag SNP selection algorithms, and it consumes much less memory at the same time. As a result, FastTagger can work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.FastTagger also produces smaller sets of tag SNPs than existing multi-marker based algorithms, and the reduction ratio ranges from 3%-9% when length-3 tagging rules are used. The generated tagging rules can also be used for genotype imputation. We studied the prediction accuracy of individual rules, and the average accuracy is above 96% when r2 >/= 0.9.ConclusionsGenerating multi-marker tagging rules is a computation intensive task, and it is the bottleneck of existing multi-marker based tag SNP selection methods. FastTagger is a practical and scalable algorithm to solve this problem.

Dataset Information

Assessment of Genetic Differentiation and Linkage Disequilibrium in Solanum pimpinellifolium Using Genome-Wide High-Density SNP Markers.

Publications

Assessment of Genetic Differentiation and Linkage Disequilibrium in <i>Solanum pimpinellifolium</i> Using Genome-Wide High-Density SNP Markers.

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