2017
DOI: 10.1038/ng.3887
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Genomic analyses in cotton identify signatures of selection and loci associated with fiber quality and yield traits

Abstract: Upland cotton (Gossypium hirsutum) is the most important natural fiber crop in the world. The overall genetic diversity among cultivated species of cotton and the genetic changes that occurred during their improvement are poorly understood. Here we report a comprehensive genomic assessment of modern improved upland cotton based on the genome-wide resequencing of 318 landraces and modern improved cultivars or lines. We detected more associated loci for lint yield than for fiber quality, which suggests that lint… Show more

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Cited by 317 publications
(354 citation statements)
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References 51 publications
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“…Recent studies in rice (Caicedo et al, 2007;Li, Li, Jia, Caicedo, & Olsen, 2017), tomato (Lin et al, 2014), and maize have shown that high genetic differentiation among populations reflects adaptation to specific agroclimatic zones. Population genomic approaches for identifying signatures of selection include decreased pairwise nucleotide diversity, composite likelihood ratio (CLR) analysis for selective sweeps, and genome-environment associations (GEA) (Fang et al, 2017;Fournier-Level et al, 2011;Lasky et al, 2015;Li et al, 2017;Lin et al, 2014). The CLR analysis in SweeD is relatively robust to demographic events because the method conservatively estimates the neutral site frequency spectrum (SFS) based on the observed data (Nielsen et al, 2005;Pavlidis, Živković, Stamatakis, & Alachiotis, 2013).…”
Section: Introductionmentioning
confidence: 99%
“…Recent studies in rice (Caicedo et al, 2007;Li, Li, Jia, Caicedo, & Olsen, 2017), tomato (Lin et al, 2014), and maize have shown that high genetic differentiation among populations reflects adaptation to specific agroclimatic zones. Population genomic approaches for identifying signatures of selection include decreased pairwise nucleotide diversity, composite likelihood ratio (CLR) analysis for selective sweeps, and genome-environment associations (GEA) (Fang et al, 2017;Fournier-Level et al, 2011;Lasky et al, 2015;Li et al, 2017;Lin et al, 2014). The CLR analysis in SweeD is relatively robust to demographic events because the method conservatively estimates the neutral site frequency spectrum (SFS) based on the observed data (Nielsen et al, 2005;Pavlidis, Živković, Stamatakis, & Alachiotis, 2013).…”
Section: Introductionmentioning
confidence: 99%
“…Most prior genetic diversity studies have suggested that no obvious genetic structure exists in Chinese upland cotton populations (Fang et al ; Sun et al ; Wang et al ). In our study, we present strong evidence that CUCSG has highly divergent genomic signatures for the different lineages.…”
Section: Discussionmentioning
confidence: 99%
“…However, the number of markers and genome coverage was limited, leading to uncertainty about the population structure and, thus, hampering the identification of favorable alleles. Recent single‐nucleotide polymorphism (SNP)‐based studies were also unable to clearly illuminate the population structure of upland cotton (Fang et al ; Sun et al ; Wang et al ).…”
Section: Introductionmentioning
confidence: 99%
“…In addition, re‐sequencing the genome for which there is a reference genome available permits exploration of the association between sequence variations. Recent comprehensive genome assessment by genome‐wide re‐sequencing of 34 (Page et al ., ), 318 (Fang et al ., ), 147 (Fang et al ., ) and 352 (Wang et al ., ) cotton accessions represented extensive collections in order to identify genome regions that are signature of selection. These studies provide new genomic resources that significantly advance molecular breeding in cotton.…”
Section: Cotton Genome Sequencing: Progress and Implicationsmentioning
confidence: 99%