ArticlePloS one2020
Unraveling candidate genomic regions responsible for delayed leaf senescence in rice.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It carries an expression of concern. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Expression of Concern: Unraveling candidate genomic regions responsible for delayed leaf senescence in rice.PloS one · 2026Article
- Insights into the Genomic Regions and Candidate Genes of Senescence-Related Traits in Upland Cotton via GWAS.International journal of molecular sciences · 2022Article
- Current Understanding of Leaf Senescence in Rice.International journal of molecular sciences · 2021Review
Corrections and comments
- Expression of concern
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Photosynthates generated after heading contributes to 60% - 80% of grain yield in rice. Delay in leaf senescence can contribute to a long grain-filling period and thereby increased yield. The objective of this study was to identify genomic region(s) responsible for delayed leaf senescence (DLS) and validate the role of underlying candidate genes in controlling target traits. 302 BC2F4 backcross-derived lines (BILs) developed from a cross between Swarna and Moroberekan were phenotyped for two seasons (DS2016 and WS2017) for chlorophyll content and yield parameters. KASPar-SNP assays based genotyping data with 193 SNPs of mapping population was used to identify the targeted genomic region(s). Significant positive correlation was observed between the two most important determinants of DLS traits viz., RDCF (reduced decline degree of chlorophyll content of flag leaf) and RDCS (reduced decline degree of chlorophyll content of second leaf) with plant height (PH), grain number per panicle (GPN), panicle length (PL), number of tiller (NT) and grain yield (GY). A total of 41 and 29 QTLs with phenotypic variance (PVE) ranging from 8.2 to 25.1% were detected for six DLS traits during DS2016 and WS2017, respectively. Out of these identified QTLs, 19 were considered as stable QTLs detected across seasons. 17 of the identified stable QTLs were found to be novel. In-silico analysis revealed five key genes regulating chlorophyll metabolism. Expression analysis of these genes confirmed their strong association with the senescence pattern in leaf tissue of parents as well as selected phenotypically extreme lines. The identified stable QTLs regulating DLS traits and validation of potential candidate genes provides insight into genetic basis of delayed senescence and is expected to contribute in enhancing grain yield through genomics-assisted breeding (GAB).
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