Growth-regulating factors-interacting factors (GIFs) are a type of transcription co-activators in plants, playing crucial roles in plants’ growth, development, and stress adaptation. Here, a total of 35 GIF genes were identified and clustered into two groups by phylogenetic analysis in four cotton genus. The gene structure and conserved domain analysis proved the conservative characteristics of GIF genes in cotton. The function of GIF genes was evaluated in two cotton accessions, Ji A-1-7 (33xi) and King, which have larger and smaller lateral root numbers, respectively. The results showed that the expression of GhGIF4 in Ji A-1-7 (33xi) was higher than that in King. The enzyme activity and microstructure assay showed a higher POD activity, lower MDA content, and more giant cells of the lateral root emergence part phenotype in Ji A-1-7 (33xi) than in King. A mild waterlogging assay showed the GIF genes were down-regulated in the waterlogged seedling. Further confirmation of the suppression of GhGIF4 in cotton plants further confirmed that GhGIF4 could reduce the lateral root numbers in cotton. This study could provide a basis for future studies of the role of GIF genes in upland cotton.
Background Seedling stage plant biomass is usually used as an auxiliary trait to study plant growth and development or stress adversities. However, few molecular markers and candidate genes of seedling biomass-related traits were found in cotton. Result Here, we collected 215 Gossypium arboreum accessions, and investigated 11 seedling biomass-related traits including the fresh weight, dry weight, water content, and root shoot ratio. A genome-wide association study (GWAS) utilizing 142,5003 high-quality SNPs identified 83 significant associations and 69 putative candidate genes. Furthermore, the transcriptome profile of the candidate genes emphasized higher expression of Ga03G1298, Ga09G2054, Ga10G1342, Ga11G0096, and Ga11G2490 in four representative cotton accessions. The relative expression levels of those five genes were further verified by qRT-PCR. Conclusions The significant SNPs, candidate genes identified in this study are expected to lay a foundation for studying the molecular mechanism for early biomass development and related traits in Asian cotton.
Background The lateral root is one of the most important organs that constitute the root architecture system in plants. It can directly affect the contact area between plants and soil and plays an important role in plant structural support and nutrient absorption. Optimizing root architecture systems can greatly increase crop yields. This study was designed to identify the molecular markers and candidate genes associated with lateral root development in cotton and to evaluate correlations with yield and disease traits. Result The number of lateral roots for 14-day old seedlings was recorded for 215 Gossypium arboreum accessions. A correlation analysis showed that the number of lateral roots positively correlates with the sympodial branch node and seed index traits, but negatively correlates with lint percentage. A Genome-wide association study (GWAS) identified 18 significant SNPs with 19 candidate genes associated with the lateral root number. Expression analysis identified three genes (FLA12, WRKY29, and RBOHA) associated with lateral root development. Conclusion GWAS analysis identified key SNPs and candidate genes for lateral root number, and genes of FLA12, WRKY29, and RBOHA may play a pivotal role in lateral root development in Asian cotton.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.