Upland cotton is the most important natural-fiber crop. The genomic variation of diverse germplasms and alleles underpinning fiber quality and yield should be extensively explored. Here, we resequenced a core collection comprising 419 accessions with 6.55-fold coverage depth and identified approximately 3.66 million SNPs for evaluating the genomic variation. We performed phenotyping across 12 environments and conducted genome-wide association study of 13 fiber-related traits. 7,383 unique SNPs were significantly associated with these traits and were located within or near 4,820 genes; more associated loci were detected for fiber quality than fiber yield, and more fiber genes were detected in the D than the A subgenome. Several previously undescribed causal genes for days to flowering, fiber length, and fiber strength were identified. Phenotypic selection for these traits increased the frequency of elite alleles during domestication and breeding. These results provide targets for molecular selection and genetic manipulation in cotton improvement.
less than 100 words)GetOrganelle is a state-of-the-art toolkit to assemble accurate organelle genomes from NGS data. This toolkit recruit organelle-associated reads using a modified "baiting and iterative mapping" approach, conducts de novo assembly, filters and disentangles assembly graph, and produces all possible configurations of circular organelle genomes. For 50 published samples, we reassembled the circular plastome in 47 samples using GetOrganelle, but only in 12 samples using NOVOPlasty. In comparison with published/NOVOPlasty plastomes, we demonstrated that GetOrganelle assemblies are more accurate.Moreover, we assembled complete mitogenomes of fungi and animals using GetOrganelle. GetOrganelle is freely released under a GPL-3 license (https://github.com/Kinggerm/GetOrganelle).
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