Advanced backcross QTL analysis reveals complicated genetic control of rice grain shape in a <i>japonica</i> × <i>indica</i> cross

Abstract

Grain shape is an important trait for improving rice yield. A number of quantitative trait loci (QTLs) for this trait have been identified by using primary F2 mapping populations and recombinant inbred lines, in which QTLs with a small effect are harder to detect than they would be in advanced generations. In this study, we developed two advanced mapping populations (chromosome segment substitution lines [CSSLs] and BC4F2 lines consisting of more than 2000 individuals) in the genetic backgrounds of two improved cultivars: a japonica cultivar (Koshihikari) with short, round grains, and an indica cultivar (IR64) with long, slender grains. We compared the ability of these materials to reveal QTLs for grain shape with that of an F2 population. Only 8 QTLs for grain length or grain width were detected in the F2 population, versus 47 in the CSSL population and 65 in the BC4F2 population. These results strongly suggest that advanced mapping populations can reveal QTLs for agronomic traits under complicated genetic control, and that DNA markers linked with the QTLs are useful for choosing superior allelic combinations to enhance grain shape in the Koshihikari and IR64 genetic backgrounds.

Genetic analysis and fine mapping of the RK4 gene for round kernel in rice (Oryza sativa L.)

“…However, additional genes controlling grain shape remain to be identified in rice (Nagata et al 2015;Yin et al 2015;Feng et al 2016), few about the round kernel were detected. To date, 3 genes for the round kernel were reported: RK1, controlling short and round grain with slightly flattened shape, was located on chromosome 4; RK2 and RK3, controlling small and round grain, were located on chromosome 10 and 5, respectively (Iwata & Omura 1975, 1984doi: 10.17221/172/2016-CJGPB Sanchez & Khush 1998.…”

QTL for maize grain yield identified by QTL mapping in six environments and consensus loci for grain weight detected by meta‐analysis

“…c bin information from MaizeGDB (http://www.maizegdb.org). | 825 (Nagata et al, 2015). In addition, most of the QTLs that we detected had small effects but will nonetheless be useful for increasing grain yield.…”

“…However, 100 GW and KNPP showed a negative correlation and six QTLs for the two traits were found collocated in three common genomic loci. This result suggests that in practical breeding programmes, breeders should choose QTLs for target traits that lack negative correlation and remove tight links for undesirable traits (Nagata et al., ). In addition, most of the QTLs that we detected had small effects but will nonetheless be useful for increasing grain yield.…”

“…The 498 RIL lines were genotyped by a total of 151 SSR markers with the same method described by Zhang et al. (Nagata et al., ). The overall length of the linkage maps with 10 chromosomes was 1090.36 cM, with an average marker interval of 7.22 cM.…”

Development and Evaluation of Chromosome Segment Substitution Lines Carrying Overlapping Chromosome Segments of the Whole Wild Rice Genome

“…Specifically, CSSLs can be used for detecting and fine mapping of QTLs as a single Mendelian factor by blocking background genetic noise. So far, several CSSLs in rice have been developed and many QTLs for traits of biological and economic interest have been detected (Kubo et al, 2002; Ebitani et al, 2005; Mei et al, 2006; Takai et al, 2007; Zhu et al, 2009; Xu et al, 2010; Chen et al, 2014; Nagata et al, 2015; Subudhi et al, 2015). These achievements have undoubtedly enhanced the understanding of complex traits and promoted plant genomic studies.…”