ArticleJournal of genetics2013
QTL mapping and correlation analysis for 1000-grain weight and percentage of grains with chalkiness in rice.
Article in Journal of genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification.Scientific reports · 2022Pooled it
- The effect of alternate wetting and drying (AWD) on spikelet fertility, grain traits and the biosynthesis of 2-acetyl-1-pyrroline (2-AP) in rice grown under high temperature.BMC plant biology · 2025Article
- An Integrative Analysis of the Transcriptome and Proteome of Rice Grain Chalkiness Formation Under High Temperature.Plants (Basel, Switzerland) · 2024Article
- Fantastic genes: where and how to find them? Exploiting rice genetic resources for the improvement of yield, tolerance, and resistance to a wide array of stresses in rice.Functional & integrative genomics · 2023Review
- Meta-QTL and haplo-pheno analysis reveal superior haplotype combinations associated with low grain chalkiness under high temperature in rice.Frontiers in plant science · 2023Article
- Screening and identification of genes affecting grain quality and spikelet fertility during high-temperature treatment in grain filling stage of rice.BMC plant biology · 2021Article
- Article
- Genetic Dissection ofFrontiers in plant science · 2018Article
- Mapping quantitative trait loci for heat tolerance at the booting stage using chromosomal segment substitution lines in rice.Physiology and molecular biology of plants : an international journal of functional plant biology · 2017Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study of 1000-grain weight (TGW) and percentage of grains with chalkiness (PGWC) is very important in rice. In this study, a set of introgression lines (ILs), derived from Sasanishiki/Habataki with Sasanishiki as the recurrent parent, were used to detect correlations and quantitative trait loci (QTL) on TGW and PGWC in two different environments. Phenotypic correlation analysis showed that there was no significant correlation between TGW and PGWC in both environments, which indicated that the linkage of TGW and PGWC traits could be broken via suitable population. A total of 20 QTL were detected in both environments, nine QTL for 1000-paddy-grain weight (PTGW), five QTL for 1000-brown-grain weight (BTGW) and six QTL for percentage of grains with chalkiness (PGWC). Moreover, five QTL, qPTGW3, qPTGW8.2, qPTGW11.1 for PTGW and qPGWC1.1, qPGWC1.2 for PGWC, were stably expressed in both environments. Phenotypic values were significantly different (P < 0.01) between the introgression lines carrying these five QTL alleles and the genetic background parent, Sasanishiki. The introgression lines carrying these QTL also represent a useful genetic resource in the context of rice yield and quality improvement via a design-breeding approach.
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