Uncovering Novel Genomic Regions and Candidate Genes for Senescence-Related Traits by Genome-Wide Association Studies in Upland Cotton (Gossypium hirsutum L.)

Abstract

Senescence in plants is a complex trait, which is controlled by both genetic and environmental factors and can affect the yield and quality of cotton. However, the genetic basis of cotton senescence remains relatively unknown. In this study, we reported genome-wide association studies (GWAS) based on 185 accessions of upland cotton and 26,999 high-quality single-nucleotide polymorphisms (SNPs) to reveal the genetic basis of cotton senescence. To determine cotton senescence, we evaluated eight traits/indices. Our results revealed a high positive correlation (r>0.5) among SPAD value 20 days after topping (SPAD20d), relative difference of SPAD (RSPAD), nodes above white flower on topping day (NAWF0d), nodes above white flower 7 days after topping (NAWF7d), and number of open bolls on the upper four branches (NB), and genetic analysis revealed that all traits had medium or high heritability ranging from 0.53 to 0.86. Based on a multi-locus method (FASTmrMLM), a total of 63 stable and significant quantitative trait nucleotides (QTNs) were detected, which represented 50 genomic regions (GWAS risk loci) associated with cotton senescence. We observed three reliable loci located on chromosomes A02 (A02_105891088_107196428), D03 (D03_37952328_38393621) and D13 (D13_59408561_60730103) because of their high repeatability. One candidate gene (Ghir_D03G011060) was found in the locus D03_37952328_38393621, and its Arabidopsis thaliana homologous gene (AT5G23040) encodes a cell growth defect factor-like protein (CDF1), which might be involved in chlorophyll synthesis and cell death. Moreover, qRT-PCR showed that the transcript level of Ghir_D03G011060 was down-regulated in old cotton leaves, and virus-induced gene silencing (VIGS) indicated that silencing of Ghir_D03G011060 resulted in leaf chlorosis and promoted leaf senescence. In addition, two candidate genes (Ghir_A02G017660 and Ghir_D13G021720) were identified in loci A02_105891088_107196428 and D13_59408561_60730103, respectively. These results provide new insights into the genetic basis of cotton senescence and will serve as an important reference for the development and implementation of strategies to prevent premature senescence in cotton breeding programs.

Insights into the Genomic Regions and Candidate Genes of Senescence-Related Traits in Upland Cotton via GWAS

“…The SPAD value in the BOP period had a larger range of variation than that in the FBP period. Moreover, the SPAD value in the FBP period showed higher heritability than that in the BOP period (0.65 and 0.41, respectively), which is similar to the results of the previous study [ 37 ]. These results indicate that environmental factors have a more significant impact on later cotton development.…”

“…Given that functional variations are usually rare in GWAS [ 49 ], significant SNPs were integrated into genomic regions (GWAS loci). In the previous study, 50 genomic regions associated with cotton senescence were revealed based on SLAF-seq data of 185 accessions, which spanned a total of 51.50 Mb [ 37 ]. In the present study, 55 senescence-related genomic regions (SGRs) spanning approximately 18.09 Mb were identified.…”

“…In another GWAS study, 64 candidate genes associated with maize senescence were identified using the maize diversity panel, of which 14 genes were involved in senescence-related processes, such as proteolysis and sink activity, and eight candidate genes were supported by a regulatory network [ 36 ]. Furthermore, our previous study revealed 50 genomic regions associated with cotton senescence via a multi-locus GWAS based on 185 upland cotton accessions and SLAF-seq data [ 37 ]. The candidate gene, GhCDF1 , was identified as a negative regulator of cotton senescence.…”

A Nimble Cloning-compatible vector system for high-throughput gene functional analysis in plants

“…We demonstrate that this vector system is effective for gene functional analysis in plants, including the study of gene ectopic expression, gene silencing, protein subcellular localization, protein–protein interaction, promoter activity, and CRISPR–Cas9-mediated gene editing. Some of the vectors constructed in this study have been successfully used in several laboratories ( Jiang et al., 2022a , 2022b ; Liu et al., 2022a , 2022b , 2022c ; Han et al., 2022b ). These vectors will further facilitate application of the Nimble Cloning system in plant science and provide a high-throughput toolkit for large-scale analysis of plant functional genomics.…”

Genome-wide identification and mining elite allele variation of the Monoacylglycerol lipase (MAGL) gene family in upland cotton (Gossypium hirsutum L.)

“…Additionally, haplotypes of the GhMAGL genes were determined using Haploview software [55] and identified within 355 cotton germplasm accessions. These haplotypes were analyzed for their distribution across domestic cotton cultivation regions, aligning with classifications of breeding stages and geographical distributions previously characterized by our laboratory [56]. The visualization of these comprehensive analyses was performed using the 'ggplot2' package within R software (version: 4.3.2) [57].…”