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Population- and genome-specific patterns of linkage disequilibrium and SNP variation in spring and winter wheat (Triticum aestivum L.)

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TLDR
This study demonstrated that the estimates of population structure between spring and winter wheat lines can identify genomic regions harboring candidate genes involved in the regulation of growth habit, and suggests that breeding and selection had a different impact on each wheat genome both within and among populations.
Abstract
Background: Single nucleotide polymorphisms (SNPs) are ideally suited for the construction of high-resolution genetic maps, studying population evolutionary history and performing genome-wide association mapping experiments. Here, we used a genome-wide set of 1536 SNPs to study linkage disequilibrium (LD) and population structure in a panel of 478 spring and winter wheat cultivars (Triticum aestivum) from 17 populations across the United States and Mexico. Results: Most of the wheat oligo pool assay (OPA) SNPs that were polymorphic within the complete set of 478 cultivars were also polymorphic in all subpopulations. Higher levels of genetic differentiation were observed among wheat lines within populations than among populations. A total of nine genetically distinct clusters were identified, suggesting that some of the pre-defined populations shared significant proportion of genetic ancestry. Estimates of population structure (FST) at individual loci showed a high level of heterogeneity across the genome. In addition, seven genomic regions with elevated FST were detected between the spring and winter wheat populations. Some of these regions overlapped with previously mapped flowering time QTL. Across all populations, the highest extent of significant LD was observed in the wheat D-genome, followed by lower LD in the A- and B-genomes. The differences in the extent of LD among populations and genomes were mostly driven by differences in long-range LD ( > 10 cM). Conclusions: Genome- and population-specific patterns of genetic differentiation and LD were discovered in the populations of wheat cultivars from different geographic regions. Our study demonstrated that the estimates of population structure between spring and winter wheat lines can identify genomic regions harboring candidate genes involved in the regulation of growth habit. Variation in LD suggests that breeding and selection had a different impact on each wheat genome both within and among populations. The higher extent of LD in the wheat D-genome versus the A- and B-genomes likely reflects the episodes of recent introgression and population bottleneck accompanying the origin of hexaploid wheat. The assessment of LD and population structure in this assembled panel of diverse lines provides critical information for the development of genetic resources for genome-wide association mapping of agronomically important traits in wheat.

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Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

TL;DR: The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.
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Genome-wide association study for grain yield and related traits in an elite spring wheat population grown in temperate irrigated environments

TL;DR: Through genome-wide association study, loci for grain yield and yield components were identified in chromosomes 5A and 6A in spring wheat (Triticum aestivum) and it was indicated that lines with 1B/1R translocation had higher YLD, grain weight, and taller plants than lines without the translocation.
Journal ArticleDOI

Domestication evolution, genetics and genomics in wheat

TL;DR: Research on wheat domestication is summarized and discussed, mainly focusing on recent findings in genetics and genomics studies, of greatly help in conservation and exploitation of wheat germplasm and genetic improvement of wheat cultivars.
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Abiotic stress and control of grain number in cereals.

TL;DR: A better understanding of the physiological and molecular processes that lead to stress-induced pollen abortion may provide the key to finding solutions for maintaining grain number under abiotic stress conditions.
References
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Controlling the false discovery rate: a practical and powerful approach to multiple testing

TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
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Inference of population structure using multilocus genotype data

TL;DR: Pritch et al. as discussed by the authors proposed a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations, which can be applied to most of the commonly used genetic markers, provided that they are not closely linked.
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Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

TL;DR: It is found that in most cases the estimated ‘log probability of data’ does not provide a correct estimation of the number of clusters, K, and using an ad hoc statistic ΔK based on the rate of change in the log probability between successive K values, structure accurately detects the uppermost hierarchical level of structure for the scenarios the authors tested.
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Estimating F-statistics for the analysis of population structure.

TL;DR: The purpose of this discussion is to offer some unity to various estimation formulae and to point out that correlations of genes in structured populations, with which F-statistics are concerned, are expressed very conveniently with a set of parameters treated by Cockerham (1 969, 1973).
Journal ArticleDOI

Haploview: analysis and visualization of LD and haplotype maps

TL;DR: Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.
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