Verticillium wilt (VW) and Fusarium wilt (FW), caused by the soil-borne fungi Verticillium dahliae and Fusarium oxysporum f. sp. vasinfectum, respectively, are two most destructive diseases in cotton production worldwide. Root-knot nematodes (Meloidogyne incognita, RKN) and reniform nematodes (Rotylenchulus reniformis, RN) cause the highest yield loss in the U.S. Planting disease resistant cultivars is the most cost effective control method. Numerous studies have reported mapping of quantitative trait loci (QTLs) for disease resistance in cotton; however, very few reliable QTLs were identified for use in genomic research and breeding. This study first performed a 4-year replicated test of a backcross inbred line (BIL) population for VW resistance, and 10 resistance QTLs were mapped based on a 2895 cM linkage map with 392 SSR markers. The 10 VW QTLs were then placed to a consensus linkage map with other 182 VW QTLs, 75 RKN QTLs, 27 FW QTLs, and 7 RN QTLs reported from 32 publications. A meta-analysis of QTLs identified 28 QTL clusters including 13, 8 and 3 QTL hotspots for resistance to VW, RKN and FW, respectively. The number of QTLs and QTL clusters on chromosomes especially in the A-subgenome was significantly correlated with the number of nucleotide-binding site (NBS) genes, and the distribution of QTLs between homeologous A- and D- subgenome chromosomes was also significantly correlated. Ten VW resistance QTL identified in a 4-year replicated study have added useful information to the understanding of the genetic basis of VW resistance in cotton. Twenty-eight disease resistance QTL clusters and 24 hotspots identified from a total of 306 QTLs and linked SSR markers provide important information for marker-assisted selection and high resolution mapping of resistance QTLs and genes. The non-overlapping of most resistance QTL hotspots for different diseases indicates that their resistances are controlled by different genes.

Background: Genetic male sterility (GMS) in cotton (Gossypium hirsutum) plays an important role in the utilization of hybrid vigor. However, the molecular mechanism of the GMS is still unclear. While numerous studies have demonstrated that microRNAs (miRNA) regulate flower and anther development, whether different small RNA regulations exist in GMS and its wild type is unclear. A deep sequencing approach was used to investigate the global expression and complexity of small RNAs during cotton anther development in this study. Results: Three small RNA libraries were constructed from the anthers of three development stages each from fertile wild type (WT) and its GMS mutant cotton, resulting in nearly 80 million sequence reads. The total number of miRNAs and short interfering RNAs in the three WT libraries was significantly greater than that in the corresponding three mutant libraries. Sixteen conserved miRNA families were identified, four of which comprised the vast majority of the expressed miRNAs during anther development. In addition, six conserved miRNA families were significantly differentially expressed during anther development between the GMS mutant and its WT. Conclusions: The present study is the first to deep sequence the small RNA population in G. hirsutum GMS mutant and its WT anthers. Our results reveal that the small RNA regulations in cotton GMS mutant anther development are distinct from those of the WT. Further results indicated that the differently expressed miRNAs regulated transcripts that were distinctly involved in anther development. Identification of a different set of miRNAs between the cotton GMS mutant and its WT will facilitate our understanding of the molecular mechanisms for male sterility.

Small auxin-up RNA (SAUR) gene family is the largest family of early auxin response genes in higher plants, which have been implicated in the regulation of multiple biological processes. However, no comprehensive analysis of SAUR genes has been reported in cotton (Gossypium spp.). In the study, we identified 145, 97, 214, and 176 SAUR homologous genes in the sequenced genomes of G. raimondii, G. arboreum, G. hirsutum, and G. barbadense, respectively. A phylogenetic analysis revealed that the SAUR genes can be classified into 10 groups. A further analysis of chromosomal locations and gene duplications showed that tandem duplication and segmental duplication events contributed to the expansion of the SAUR gene family in cotton. An exon-intron organization and motif analysis revealed the conservation of SAUR-specific domains, and the auxin responsive elements existed in most of the upstream sequences. The expression levels of 16 GhSAUR genes in response to an exogenous application of IAA were determined by a quantitative RT-PCR analysis. The genome-wide RNA-seq data and qRT-PCR analysis of selected SAUR genes in developing fibers revealed their differential expressions. The physical mapping showed that 20 SAUR genes were co-localized with fiber length quantitative trait locus (QTL) hotspots. Single nucleotide polymorphisms (SNPs) were detected for 12 of these 20 genes between G. hirsutum and G. barbadense, but no SNPs were identified between two backcross inbred lines with differing fiber lengths derived from a cross between the two cultivated tetraploids. This study provides an important piece of genomic information for the SAUR genes in cotton and lays a solid foundation for elucidating the functions of SAUR genes in auxin signaling pathways to regulate cotton growth.