Construction Of Genetic Linkage Maps And QTL Mapping For Yield Related Traits Using Two Associated RIL Populations Of Wheat

Two associated RIL populations comprising 229 (Weimai8/Yannong19-derived, WY) and 485 (Weimai8/Jimai20-derived, WJ) lines were used in the present study to construct two genetic linkage maps using SSR, EST-SSR, RAPD, SRAP, STS and ISSR markers. Then the inclusive interval mapping method was utilized to map QTLs with additive effect by software Icimapping v3.0 for grain yield per plant (GY) and yield components (YC), such as spikelet number per spike (SN), spike number per plant (PN), grain number per main spike (GN) and 1,000-grain weight (GW). What's more, conditional values of GY without the influences of YC were also used to map conditional QTLs for GY. The results were as follows:(1). Three thousand one handred and twenty three pairs of genomic primers were used to genotype the two RIL populations and their parents, and in total 256 and 237 pairs of markers amplified clear and discrepant sites between Weimai8 and Yannong19 and between Weimai8 and Jimai20, respectively. The separation ratio of most sites fit the 1:1, suggesting that the two RIL populations could be utilized in QTL mapping analysis.(2). Two high density genetic linage maps, both with 27 linkage groups, were constructed using the software MAPMAKER/EXP3.0 and Joinmap v3.0, one of which was the WY map, comprising 358 sites, with the whole genome length of 3010.70 cM and an average distance of 8.41 cM between markers, and the number of markers being 3 on chromosomes 4D and 7D to 45 on 4A, and the other, WJ map, comprising 344 sites, with the whole genome length of 2855.50 cM and an average distance of 8.30 cM between markers, and the number of markers being 3 on chromosome 3D to 40 on 1B, showing that the mapping populations were suitable for QTL mapping. In addition, the associated mapping populations shared 69 common markers, facilitating the comparison of results between populations and the construction of integrated map.(3). Based on the genetic linkage maps, the software IciMapping v3.0 (with inclusive interval mapping method) was used to conduct QTL mapping of the five important yield traits (SN, PN, GN, GW and GY), in four environments. In WY population, totally 29 QTLs with additive effect for the five traits were mapped on all wheat chromosomes except 3A, 3D, 4A, 5A, 5B and 7A, with the explanation of phenotypic variation (PVE) from 4.9% to 18.6% of a single QTL. There were 16 QTLs explaining >10% of the PVE which could be regard as major QTLs, 5 QTLs could be detected among environments and 4 marker intervals harboured pleiotropy or closely linked QTLs. In WJ population, a total of 45 QTLs with additive effect for the five traits were mapped on all wheat chromosomes except 4B, with a single QTL explaning of PVE from 1.7 % to 14.7%. There were only 3 QTLs explaining >10% of the PVE which could be regard as major QTLs, 17 QTLs could be detected among environments and 20 marker intervals harboured pleiotropy or closely linked QTLs. All of the QTLs detected in the two RILs distributed on all the 21 wheat chromosomes, with 9 pairs of QTLs linked with common markers between populations, which might be genes co-expressed in both WY and WJ.(4). For the first time, conditional QTL mapping was conducted for GY and YC in wheat. Excluding the variance of GN, PN and GW, 2+2/5+3, 1+11/3+11 and 3+2/5+3 QTLs were detected of the total 8 and 6 unconditional QTLs and 15 and 17 additional conditional QTLs in WY and WJ, respectively. The first digit is the number of unconditional QTLs also discovered as conditional QTLs with no change or minor changes in their additive effects. The second digit represents QTLs only detected in conditional mapping when GY was conditioned on each contributing trait. Additionally, there were 4 unconditional QTLs in WY that failed to be identified in conditional mapping. These results showed that all of the QTLs identified were associated with at least one of the three yield components, and the number of QTLs detected that significantly affected grain yield was different with respect to component-special influences with the biggest contribution from PN, which can be applied in breeding programs. In addition, 19 QTLs located on chromosomes 1B, 1D, 2A, 2D, 4A and 5A were common between populations for their linkage with the same markers in both RILs.