Genetic Analysis Of Rice(Oryza Sativa L.) Quantitative Traits With Different Heritabilities Under Four Environments In China And Zambia

Even though the importance of rice in the diet may vary among countries,its overall impact on global food security has led breeders to prioritize it as a solution to feeding the ever increasing global population.The sustainability of the rice industry,however,is directly tied to grain yield and quality.These quantitative traits have thus attracted a lot of attention in most breeding programmes,however,the genetic understanding of quantitative traits especially for those with relatively lower heritability,such as milling yield still remain limited.So,an experiment was conducted with the main aim of enhancing genetic and molecular breeding knowledge on the genetic factors that control various quantitative traits using three populations in multiple environments.Mapping populations used in the study were derived from an interspecific cross between MH63(indica)and 02428(japonica).These included two hundred and twenty six(226)MH63 background introgression lines(MH63_ILs),two hundred and twenty nine(229)02428 background introgression lines(02428_ILs)and two hundred and sixty one(261)recombinant inbred lines(RILs).An evaluation of these populations was conducted in replicated experiments at four locations including Beijing(Environment 1)and Hainan(Environment 2)in China,Mongu Namushakende Farm Institute(Environment 3)and Mount Makulu Research Station(Environment 4)in Zambia.Subsequent to this,a QTL analysis and investigation of the genetic interrelationship between low heritability traits such as milling yield traits and high heritability traits including days to 50% heading and grain dimension traits was conducted.The QTL analysis revealed genomic regions for grain dimension traits including grain length(GL),grain width(GW),length to width ratio(LWR)and grain volume(GV);milling quality traits including brown rice rate(BRR),milled rice rate(MRR)and head rice recovery(HRR),and agronomic traits including days to 50% heading(DTH),plant height(PH),grain yield(GY),thousand grain weight(TGW)and grain filling rate(GFR).A total of 103 QTL including 9 QTL for 3 milling quality traits,32 QTL for 4 grain dimension traits and 62 QTL for 5 agronomic traits were detected.Thirty QTL associated with various quantitative traits in this study were found to be novel and 27 QTL for grain dimension and agronomic traits were stably expressed.The stably expressed QTL included qGL3 c,qGL9a and qGL11 a for GL;qGW3a and qGW5 a for GW;qLWR3a and qLWR5 a for LWR;qGV1a,qGV3 a,qGV5a and qGV5 b for GV;qPH1e,qPH3 c,qPH5c and qPH6 a for PH;qTGW5a,qTGW5 c,TGW11a and qTGW11 b for TGW;and qGFR11 a for GFR in more than one environment.In addition,qDTH2 a and qDTH5 a for DTH;qGY3a for GY and qGFR3 c for GFR were detected in more than one population.Further,4 QTL were detected in more than 1 environment and more than 1 population and these included qGY3 a and qGY6 a for GY;qPH12a for PH and qTGW3 d for TGW.The analysis further revealed 17 major effect QTL for grain quality and agronomic traits including qHR8 a for head rice recovery on chromosome 8.The genetic background effect study exhibited a skew towards MH63_ILs population in terms of QTL detection with approximately 58.7%,28.6% and 12.7% of the QTL detected in MH63_ILs,RILs and in more than 1 population respectively.Seventeen QTL for both grain dimension and agronomic traits were found aligned with previously cloned genes and fine mapped QTL including sd.1,sdg,GS3,GS5,GS7,qGL7,GIF1,qHD5,qSS7,TGW6 and tgw11.In addition,25 QTL clusters of various quantitative traits were revealed with 5 harbouring at-least a milling quality trait.Two of these clusters exhibited some link between two milling quality traits and days to 50% heading.Chromosome 1 harboured a cluster flanked by markers M443 and M450 which included qDTH1 c and qMR1 a mapped just 2 cM apart.The second cluster which included qBR3 a,qMR3a and qDTH3 a was detected on chromosome 3 between markers M989 and M1028.This presents DTH a higher heritability trait as a primary target trait of selection for low heritable milling yield traits.Further,the results also revealed the effects of variation in heading dates on the QTL expression of milling yield traits in the different environments.Noteworthy,was also a skew of 73.5% of allele contribution to significant QTL towards the indica parent MH63.The genetic diversity study revealed highly significant variations among genotypes with some introgression lines exhibiting positive transgressive variation over the parents for all traits.Heritability in the broad sense ranged from low to high including 17 to 18% for milling quality traits,24 to 60% for agronomic traits and 69 to 83% for grain dimension traits in MH63_ILs.Generally,trait heritability among the 3 populations varied based on population confirming the effect of population on heritability.The study also established that grain width,grain length,thousand grain weight and days to heading could offer effective selection criteria for head rice recovery on the basis of their positive and significant correlations coupled with positive direct effects on head rice recovery under certain environments.This research would broaden our knowledge for quantitative traits under highly various environments and offer useful information for molecular breeders.