Analysis of QTLs on heading date based on single segment substitution lines in rice (Oryza Sativa L.)

Abstract

Single segment substitution lines (SSSLs) have been confirmed to be powerful tools to perform quantitative trait locus (QTL) analysis. This study illuminated the process and methods of QTL analysis with SSSLs on heading date (HD) in rice. QTL identification under two cropping seasons revealed 98 of 202 SSSLs associated with HD. A total of 22 QTLs were positioned in relative narrow regions on chromosomes by mrMLM.GUI software. QTL qHd3-1 was precisely positioned at 4.4 cM on chromosome 3 by a secondary F2 population. Through SSSL pyramiding, double segment substitution lines were constructed and used to analyze epistatic interactions of digenic loci. Epistatic effects for three pairs of QTLs were estimated, indicating the interactions of QTL qHd3-1 with other QTLs detected and the role to enhance the expression of early ripening or restraining of late flowering QTLs. Additionally, analysis of QTL in different environments provided information about the stability of HD QTLs. This type of research points out the way to excavate favorable genes for design breeding.

Unconditional and conditional analysis of epistasis between tillering QTLs based on single segment substitution lines in rice

“…It has been long to recognize the advantages of near isogenic lines or single segment substitution lines for QTL identification [16][17][18] . Based on single segment substitution lines numerous QTLs were identified [19][20][21][22][23][24][25][26][27][28][29][30][31][32] . However, the important genetic component of epistasis was often ignored or incomprehensive.…”

Breeding by design of CMS lines on the platform of SSSL library in rice

“…To date, more than 2000 SSSLs were developed, in which a rich of genes from AA genome of the Oryza genus was collected (He et al 2005;Xi et al 2006;He et al 2017;Zhao et al 2019). At the second step, we detected the genotypes on the chromosomal substituted segments in the SSSLs by mapping of genes or QTLs of important traits (He et al 2005;Zhao et al 2007;Liu et al 2010;Zhang et al 2012;Naeem et al 2013;Yang et al 2016;Zhou et al 2017;Zhu et al 2018), by assessing allelic variations at the loci of interest (Zeng et al 2006;Teng et al 2012;Cai et al 2013), by analyzing interaction of gene by gene and gene by environment (Liu et al 2008;Liu et al 2012;Chen et al 2014;Qin et al 2015;Zhao et al 2016;Yang et al 2018), and by cloning genes of agronomic important (Wang et al 2012;Wang et al 2015). A large gene information has been collected from the SSSL library.…”

“…The genes for agronomic importance on the substituted segments in the SSSLs were analyzed. The gene information was collected including gene location, allelic variation, interaction of gene by gene and gene by environment, molecular function, and so on (Zeng et al 2006;Zhao et al 2007;Liu et al 2008;Liu et al 2010;Liu et al 2012;Teng et al 2012;Wang et al 2012;Zhang et al 2012;Chen et al 2014;Qin et al 2015;Wang et al 2015;Yang et al 2016;Zhao et al 2016;Zhou et al 2017;Yang et al 2018;Zhu et al 2018). To assess allelic variations at the Rf3 and Rf4 loci, the SSSLs carrying one of the loci in the substituted segments were selected from the library.…”

Uniparental Inheritance of Salinity Tolerance and Beneficial Phytochemicals in Rice

“…A total of fifty SSR markers which were reported previously to be involved in growth parameters, yield, pest resistance, and the Saltol QTL (salinity tolerant) [7][8][9][10]12,[31][32][33][34][35][36][37][38][39][40][41][42][43][44][45] were selected to evaluate the differences among genotypes of the recurrent TBR1 and male KD18 cultivars (Supplementary Figure S3). These markers are distributed throughout 12 chromosomes of the rice genome (Supplementary Table S2).…”