Making use of the markers linked closely to QTL for early-maturing traits for MAS (Marker-assisted selection) is an effective method for the simultaneous improvement of early maturity and other properties in cotton. In this study, two F2 populations and their F2:3 families were generated from the two upland cotton (Gossypium hirsutum L.) crosses, Baimian2 × TM-1 and Baimian2 × CIR12. QTL for early-maturing traits were analyzed using F2:3 families. A total of 54 QTL (31 suggestive and 23 significant) were detected. Fourteen significant QTL had the LOD scores not only > 3 but also exceeding permutation threshold. At least four common QTL, qBP-17 for bud period (BP), qGP-17a/qGP-17b (qGP-17) for growth period (GP), qYPBF-17a/qYPBF-17b (qYPBF-17) for yield percentage before frost (YPBF) and qHFFBN-17 for height of first fruiting branch node (HFFBN), were found in both populations. These common QTL should be reliable and could be used for MAS to facilitate early maturity. The common QTL, qBP-17, had a LOD score not only > 3 but also exceeding permutation threshold, explaining 12.6% of the phenotypic variation. This QTL should be considered preferentially in MAS. Early-maturing traits of cotton are primarily controlled by dominant and over-dominant effects.

A major breeding target in Upland cotton (Gossypium hirsutum L.) is to improve the fiber quality. To address this issue, 169 diverse accessions, genotyped by 53,848 high-quality single-nucleotide polymorphisms (SNPs) and phenotyped in four environments, were used to conduct genome-wide association studies (GWASs) for fiber quality traits using three single-locus and three multi-locus models. As a result, 342 quantitative trait nucleotides (QTNs) controlling fiber quality traits were detected. Of the 342 QTNs, 84 were simultaneously detected in at least two environments or by at least two models, which include 29 for fiber length, 22 for fiber strength, 11 for fiber micronaire, 12 for fiber uniformity, and 10 for fiber elongation. Meanwhile, nine QTNs with 10% greater sizes (R2) were simultaneously detected in at least two environments and between single- and multi-locus models, which include TM80185 (D13) for fiber length, TM1386 (A1) and TM14462 (A6) for fiber strength, TM18616 (A7), TM54735 (D3), and TM79518 (D12) for fiber micronaire, TM77489 (D12) and TM81448 (D13) for fiber uniformity, and TM47772 (D1) for fiber elongation. This indicates the possibility of marker-assisted selection in future breeding programs. Among 455 genes within the linkage disequilibrium regions of the nine QTNs, 113 are potential candidate genes and four are promising candidate genes. These findings reveal the genetic control underlying fiber quality traits and provide insights into possible genetic improvements in Upland cotton fiber quality.

Cotton is one of the most important textile crops but little is known how microRNAs regulate cotton fiber development. Using a well-studied cotton fiberless mutant Xu-142-fl, we compared 54 miRNAs for their expression between fiberless mutant and its wildtype. In wildtype Xu-142, 26 miRNAs are involved in cotton fiber initiation and 48 miRNAs are related to primary wall synthesis and secondary wall thickening. Thirty three miRNAs showed different expression in fiber initiation between Xu-142 and Xu-142-fl. These miRNAs potentially target 723 protein-coding genes, including transcription factors, such as MYB, ARF, and LRR. ARF18 was newly predicted targets of miR160a, and miR160a was expressed at higher level in −2DPA of Xu-142-fl compared with Xu-142. Furthermore, the result of Gene Ontology-based term classification (GO), EuKaryotic Orthologous Groups (KOG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis shows that miRNA targets were classified to 222 biological processes, 64 cellular component and 42 molecular functions, enriched in 22 KOG groups, and classified into 28 pathways. Together, our study provides evidence for better understanding of miRNA regulatory roles in the process of fiber development, which is helpful to increase fiber yield and improve fiber quality.

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