In-depth genome diversity, population structure and linkage disequilibrium analysis of worldwide diverse safflower (Carthamus tinctorius L.) accessions using NGS data generated by DArTseq technology

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.

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Whole Genome Diversity, Population Structure and Linkage Disequilibrium Analysis of Chickpea (Cicer arietinum L.) Genotypes Using Genome-Wide DArTseq-Based SNP Markers

10.20944/preprints201904.0321.v1 ◽

2019 ◽

Author(s):

Somayeh Farahani ◽

Mojdeh Maleki ◽

Rahim Mehrabi ◽

Homayoun Kanouni ◽

Reza Talebi

Keyword(s):

Genetic Diversity ◽

Population Structure ◽

Linkage Disequilibrium ◽

Large Scale ◽

Principal Component ◽

Snp Markers ◽

Genome Diversity ◽

High Genetic Diversity ◽

Breeding Programs ◽

Population Structure Analysis

Characterization of genetic diversity, population structure and linkage disequilibrium is 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 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 covered by SNPs varied from 16236.36 kbp (LG8) to 67923.99 kbp (LG5), while LG4 showed 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. Un-weighted 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 suggesting the presence of a high genetic diversity among studied chickpea genotypes. This study also demonstrated 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.

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A Genealogical Interpretation of Linkage Disequilibrium

Genetics ◽

10.1093/genetics/162.2.987 ◽

2002 ◽

Vol 162 (2) ◽

pp. 987-991 ◽

Cited By ~ 14

Author(s):

Gilean A T McVean

Keyword(s):

Monte Carlo Simulation ◽

Population Structure ◽

Linkage Disequilibrium ◽

Population Bottlenecks ◽

Neutral Model ◽

Demographic Models ◽

Degree Of Association ◽

Different Parts ◽

Direct Correspondence ◽

Coalescence Times

Abstract The degree of association between alleles at different loci, or linkage disequilibrium, is widely used to infer details of evolutionary processes. Here I explore how associations between alleles relate to properties of the underlying genealogy of sequences. Under the neutral, infinite-sites assumption I show that there is a direct correspondence between the covariance in coalescence times at different parts of the genome and the degree of linkage disequilibrium. These covariances can be calculated exactly under the standard neutral model and by Monte Carlo simulation under different demographic models. I show that the effects of population growth, population bottlenecks, and population structure on linkage disequilibrium can be described through their effects on the covariance in coalescence times.

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Linkage and linkage disequilibrium analysis of the lipoprotein lipase gene with lipid profiles in Chinese hypertensive families

Clinical Science ◽

10.1042/cs20040101 ◽

2005 ◽

Vol 108 (2) ◽

pp. 137-142 ◽

Cited By ~ 5

Author(s):

Wenjie YANG ◽

Jianfeng HUANG ◽

Cailiang YAO ◽

Shaoyong SU ◽

Donghai LIU ◽

...

Keyword(s):

Linkage Disequilibrium ◽

Lipoprotein Lipase ◽

Lipid Profiles ◽

Strong Linkage Disequilibrium ◽

Nucleotide Polymorphisms ◽

Linkage Disequilibrium Analysis ◽

Lipid Levels ◽

Lipase Gene ◽

Significant Independent Risk Factor ◽

Lpl Gene

Elevated TG [triacylglycerol (triglyceride)] is a significant independent risk factor for cardiovascular disease. LPL (lipoprotein lipase) is one of the key enzymes in the metabolism of the TG-rich lipoproteins which hydrolyses TG from the chylomicrons and very-LDL (low-density lipoprotein). To investigate the relationship between the LPL gene and lipid profiles, especially TG, in 148 hypertensive families, we have chosen seven flanking microsatellite markers and four internal markers of the LPL gene and conducted linkage analysis by SOLAR and S.A.G.E. (statistical analysis for genetic epidemiology)/SIBPAL 2 programs, and linkage disequilibrium analysis by QTDT (quantitative transmission/disequilibrium test) and GOLD (graphical overview of linkage disequilibrium). There were statistically significant differences in lipid levels between subjects without and with hypertension within families. A maximum LOD score of 1.3 with TG at the marker D8S261 was observed by SOLAR. Using S.A.G.E./SIBPAL 2, we identified a linkage with TG at the marker ‘ATTT’ located within intron 6 of the LPL gene (P=0.0095). Two SNPs (single nucleotide polymorphisms), HindIII and HinfI, were found in linkage disequilibrium with LDL-cholesterol levels (P=0.0178 and P=0.0088 respectively). A strong linkage disequilibrium was observed between the HindIII in intron 8 and HinfI in the exon 9 (P<0.00001, D′=0.895). Linkage disequilibrium was also found between the ‘ATTT’ polymorphism in intron 6 and two SNPs (P=0.0021 and D′=0.611 for HindIII; and P=0.00004, D′=0.459 for HinfI). The present study in the Chinese families with hypertension suggested that the LPL gene might influence lipid levels, especially TG metabolism. Replication studies both in Chinese and other populations are warranted to confirm these results.

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