QTL analysis and candidate gene identification for plant height in cotton based on an interspecific backcross inbred line population of Gossypium hirsutum × Gossypium barbadense.

KEY MESSAGE: We constructed the first high-quality and high-density genetic linkage map for an interspecific BIL population in cotton by specific-locus amplified fragment sequencing for QTL mapping. A novel gene GhPIN3 for plant height was identified in cotton. Ideal plant height (PH) is important for improving lint yield and mechanized harvesting in cotton. Most published genetic studies on cotton have focused on fibre yield and quality traits rather than PH. To facilitate the understanding of the genetic basis in PH, an interspecific backcross inbred line (BIL) population of 250 lines derived from upland cotton (Gossypium hirsutum L.) CRI36 and Egyptian cotton (G. barbadense L.) Hai7124 was used to construct a high-density genetic linkage map for quantitative trait locus (QTL) mapping. The high-density genetic map harboured 7,709 genotyping-by-sequencing (GBS)-based single nucleotide polymorphism (SNP) markers that covered 3,433.24 cM with a mean marker interval of 0.67 cM. In total, ten PH QTLs were identified and each explained 4.27-14.92% of the phenotypic variation, four of which were stable as they were mapped in at least two tests or based on best linear unbiased prediction in seven field tests. Based on functional annotation of orthologues in Arabidopsis and transcriptome data for the genes within the stable QTL regions, GhPIN3 encoding for the hormone auxin efflux carrier protein was identified as a candidate gene located in the stable QTL qPH-Dt1-1 region. A qRT-PCR analysis showed that the expression level of GhPIN3 in apical tissues was significantly higher in four short-statured cotton genotypes than that in four tall-statured cotton genotypes. Virus-induced gene silencing cotton has significantly increased PH when the expression of the GhPIN3 gene was suppressed.

Genetic variation of dynamic fiber elongation and developmental quantitative trait locus mapping of fiber length in upland cotton (Gossypium hirsutum L.).

BACKGROUND: In upland cotton (Gossypium hirsutum L.), genotypes with the same mature fiber length (FL) might possess different genes and exhibit differential expression of genes related to fiber elongation at different fiber developmental stages. However, there is a lack of information on the genetic variation influencing fiber length and its quantitative trait loci (QTLs) during the fiber elongation stage. In this study, a subset of upland cotton accessions was selected based on a previous GWAS conducted in China and grown in multiple environments to determine the dynamic fiber length at 10, 15, 20, and 25 days post-anthesis (DPA) and maturity. The germplasm lines were genotyped with the Cotton 63 K Illumina single-nucleotide polymorphism (SNP) array for GWAS. RESULTS: A total of 25, 38, 57, 89 and 88 SNPs showed significant correlations with fiber length at 10, 15, 20 and 25 DPA and maturity, respectively. In addition, 60 more promising SNPs were detected in at least two tests and two FL developmental time points, and 20 SNPs were located within the confidence intervals of QTLs identified in previous studies. The fastest fiber-length growth rates were obtained at 10 to 15 DPA in 69 upland cotton lines and at 15 to 20 DPA in 14 upland cotton accessions, and 10 SNPs showed significant correlations with the fiber-length growth rate. A combined transcriptome and qRT-PCR analysis revealed that two genes (D10G1008 and D13G2037) showed differential expression between two long-fiber genotypes and two short-fiber genotypes. CONCLUSIONS: This study provides important new insights into the genetic basis of the time-dependent fiber-length trait and reveals candidate SNPs and genes for improving fiber length in upland cotton.

A genome-wide analysis of the small auxin-up RNA (SAUR) gene family in cotton.

BACKGROUND: 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.). RESULTS: 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. CONCLUSIONS: 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.

Sparse Personalized Federated Learning.

Federated learning (FL) is a collaborative machine learning technique to train a global model (GM) without obtaining clients' private data. The main challenges in FL are statistical diversity among clients, limited computing capability among clients' equipment, and the excessive communication overhead between the server and clients. To address these challenges, we propose a novel sparse personalized FL scheme via maximizing correlation (FedMac). By incorporating an approximated l1 -norm and the correlation between client models and GM into standard FL loss function, the performance on statistical diversity data is improved and the communicational and computational loads required in the network are reduced compared with nonsparse FL. Convergence analysis shows that the sparse constraints in FedMac do not affect the convergence rate of the GM, and theoretical results show that FedMac can achieve good sparse personalization, which is better than the personalized methods based on the l2 -norm. Experimentally, we demonstrate the benefits of this sparse personalization architecture compared with the state-of-the-art personalization methods (e.g., FedMac, respectively, achieves 98.95%, 99.37%, 90.90%, 89.06%, and 73.52% accuracy on the MNIST, FMNIST, CIFAR-100, Synthetic, and CINIC-10 datasets under non-independent and identically distributed (i.i.d.) variants).

Genome-Scale Analysis of the WRI-Like Family in Gossypium and Functional Characterization of GhWRI1a Controlling Triacylglycerol Content.

Cotton (Gossypium spp.) is the most important natural fiber crop and the source of cottonseed oil, a basic by-product after ginning. AtWRI1 and its orthologs in several other crop species have been previously used to increase triacylglycerols in seeds and vegetative tissues. In the present study, we identified 22, 17, 9, and 11 WRI-like genes in G. hirsutum, G. barbadense, G. arboreum, and G. raimondii, respectively. This gene family was divided into four subgroups, and a more WRI2-like subfamily was identified compared with dicotyledonous Arabidopsis. An analysis of chromosomal distributions revealed that the 22 GhWRI genes were distributed on eight At and eight Dt subgenome chromosomes. Moreover, GhWRI1a was highly expressed in ovules 20-35 days after anthesis and was selected for further functional analysis. Ectopic expression of GhWRI1a rescued the seed phenotype of a wri1-7 mutant and increased the oil content of Arabidopsis seeds. Our comprehensive genome-wide analysis of the cotton WRI-like gene family lays a solid foundation for further studies.