Genetic Architecture of Natural Variation in Rice Chlorophyll Content Revealed by a Genome-Wide Association Study

Abstract

Chlorophyll content is one of the most important physiological traits as it is closely related to leaf photosynthesis and crop yield potential. So far, few genes have been reported to be involved in natural variation of chlorophyll content in rice (Oryza sativa) and the extent of variations explored is very limited. We conducted a genome-wide association study (GWAS) using a diverse worldwide collection of 529 O. sativa accessions. A total of 46 significant association loci were identified. Three F2 mapping populations with parents selected from the association panel were tested for validation of GWAS signals. We clearly demonstrated that Grain number, plant height, and heading date7 (Ghd7) was a major locus for natural variation of chlorophyll content at the heading stage by combining evidence from near-isogenic lines and transgenic plants. The enhanced expression of Ghd7 decreased the chlorophyll content, mainly through down-regulating the expression of genes involved in the biosynthesis of chlorophyll and chloroplast. In addition, Narrow leaf1 (NAL1) corresponded to one significant association region repeatedly detected over two years. We revealed a high degree of polymorphism in the 5' UTR and four non-synonymous SNPs in the coding region of NAL1, and observed diverse effects of the major haplotypes. The loci or candidate genes identified would help to fine-tune and optimize the antenna size of canopies in rice breeding.

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

“…A similar result was observed in wheat under rain-fed conditions (Lopes et al 2014) and in maize that was tolerant to low phosphorus (Zhang et al 2015b). CC in the flag leaf had a significant negative correlation with PH, as also reported in rice (Wang et al 2015). H10 was the taller, lower CC cultivar.…”

Genome-Wide Association Study for Plant Height and Grain Yield in Rice under Contrasting Moisture Regimes

“…144,995 SNPs, with less than 10% missing data in this natural population, were used for kinship calculation among individuals and principal component analysis (PCA) to adjust the population structure. The genome-wide threshold was set at p = 9.81E-07, calculated via the formula: 1/total number of SNPs, which was widely used in plant GWAS studies (Wen et al, 2014; Wang et al, 2015; Bai et al, 2016). We furthermore evaluated the extent of local LD (linkage disequilibrium) for each significant SNP.…”

“…Compared to QTL analysis, GWAS is based on natural populations, and can detect multiple alleles at the same site (Flint-Garcia et al, 2003). GWAS have widely been used in human genetic studies as well as in plants, such as Arabidopsis , maize, sorghum, and rice (Atwell et al, 2010; Huang et al, 2011; Tian et al, 2011; Li et al, 2012; Riedelsheimer et al, 2012; Morris et al, 2013; Chen et al, 2014; Wen et al, 2014; Yang et al, 2014, 2015; Wang et al, 2015; Yano et al, 2016). Identification of the allelic variation underpinning the phenotypic diversity in rice will result in enormous practical implications for rice breeding.…”

Fine mapping a major QTL qFCC7 L for chlorophyll content in rice (Oryza sativa L.) cv. PA64s

“…The Chl content of leaves might be affected by the variation of days-to-heading. Wang et al (2015a) reported that Ghd7 is a major locus for the natural variation of Chl content. We discovered that some genes related to heading time were on the corresponding regions of QTLs for Chl content.…”