Comparative quantitative trait loci analysis framework reveals relationships between salt stress responsive phenotypes and pathways
Issued Date
2024-01-01
Resource Type
eISSN
1664462X
Scopus ID
2-s2.0-85186881881
Journal Title
Frontiers in Plant Science
Volume
15
Rights Holder(s)
SCOPUS
Bibliographic Citation
Frontiers in Plant Science Vol.15 (2024)
Suggested Citation
Phosuwan S., Nounjan N., Theerakulpisut P., Siangliw M., Charoensawan V. Comparative quantitative trait loci analysis framework reveals relationships between salt stress responsive phenotypes and pathways. Frontiers in Plant Science Vol.15 (2024). doi:10.3389/fpls.2024.1264909 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/97593
Title
Comparative quantitative trait loci analysis framework reveals relationships between salt stress responsive phenotypes and pathways
Corresponding Author(s)
Other Contributor(s)
Abstract
Soil salinity is a complex abiotic stress that involves several biological pathways. Hence, focusing on a specific or a few salt-tolerant phenotypes is unlikely to provide comprehensive insights into the intricate and interwinding mechanisms that regulate salt responsiveness. In this study, we develop a heuristic framework for systematically integrating and comprehensively evaluating quantitative trait loci (QTL) analyses from multiple stress-related traits obtained by different studies. Making use of a combined set of 46 salinity-related traits from three independent studies that were based on the same chromosome segment substitution line (CSSL) population of rice (Oryza sativa), we demonstrate how our approach can address technical biases and limitations from different QTL studies and calling methods. This allows us to compile a comprehensive list of trait-specific and multi-trait QTLs, as well as salinity-related candidate genes. In doing so, we discover several novel relationships between traits that demonstrate similar trends of phenotype scores across the CSSLs, as well as the similarities between genomic locations that the traits were mapped to. Finally, we experimentally validate our findings by expression analyses and functional validations of several selected candidate genes from multiple pathways in rice and Arabidopsis orthologous genes, including OsKS7 (ENT-KAURENE SYNTHASE 7), OsNUC1 (NUCLEOLIN 1) and OsFRO1 (FERRIC REDUCTASE OXIDASE 1) to name a few. This work not only introduces a novel approach for conducting comparative analyses of multiple QTLs, but also provides a list of candidate genes and testable hypotheses for salinity-related mechanisms across several biological pathways.
