| Wheat (Triticum aestivum L.) is a major food crop worldwide. As an allohexaploid carrying the genomes AABBDD (2n = 6x = 42), common wheat owns large genome size, 80% of which is repetitive DNA . Hence, molecular markers show lower level polymorphism in wheat, which makes the genetic research in wheat fall behind other crops such as maize, rice, etc. Knowing the precise position and effect of QTL for yield-related traits will be of great value for genetic improvement in yiled in wheat breeding programs. Thus, it is of importance to construct a high-density wheat molecular map. In present study, high-density wheat molecular genetic maps were constructed based on three related mapping populations. Based on the novel molecular genetic maps above, multivariate conditional and unconditional QTL mapping analysis were conducted to specify the genetic characteristics of yield and yield-related traits at the QTL level. The main results were as follows:⑴Two molecular genetic maps comprising 344 and 358 PCR-based marker loci were constructed based on 485 WJ-derived and 229 WY-derived recombinant inbred line (RIL) populations. The two genetic maps spaned 2855.5 cM and 3010.72 cM, respectively, with an average density of one marker per 8.30 cM and 8.41 cM. Due to the linkage distance > 50 cM between the adjacent loci, there were six linkage gaps each in the two genetic maps. Sixty-nine pairwise molecular marker loci were common to the two genetic maps.⑵To saturate the two genetic maps above, 175 and 172 progenies were randomly selected from 485 WJ-derived and 229 WY-derived RIL populations, respectively, for developing diversity arrays technology (DArT) markers. Combining the novel DArT markers and PCR-based markers, two high-density genetic maps were established, including 629 and 681 loci on the wheat chromosomes, 373 and 406 of which, respectively, were novel DArT marker loci. The two high-density genetic maps covered total lengths of 2777.54 cM and 3004.62 cM, with average densities of one marker per of 4.42 cM and 4.41 cM, respectively. The linkage distances > 50 cM between the adjacent loci resluted in eight and 13 linakage gaps in WJ and WY-derived high-density genetic maps, respectively. The two high-density genetic maps shared 270 common loci.⑶A high-density integrative genetic map was developed by combining the two WJ and WY-derived high-density genetic maps and the third high-density genetic map, which was constructed based on a 179 F8:9 RIL population derived from the cross between Weimai 8 and Luohan 2. It comprised 1113 loci, 536 and 575 of which, respectively, were PCR-based marker loci and novel DArT marker loci, covering a total length of 2946.98 cM, with an average density of one marker per of 2.65 cM. Of the 1113 loci, 494 loci were common among the three individual genetic maps, covering a total length of 1607.21 cM. The common loci were used for joint QTL mapping analysis based on the nested association mapping (NAM) population.⑷In total, up to 533 putative additive QTL for the 21 yield and yield-related traits were detected in the 485/229 WJ/WY RIL populations. Of these, 117 QTL showed significance in at least two different environments of E1, E2, E3 and E4, 36 of which accounted for no less than 10% of the phenotypic variation, being major stable QTL. Of these, 19 QTL showed pleiotropic effects and were co-located on chromosomal regions of 1B, 1D, 2A, 2B, 2D, 5A, 5D or 6D, referring to seven major stable QTL clusters. QTL analysis based on 175/172 WJ/WY RIL populations identified 480 QTL for the 21 yield and yield-related traits. Of these, 75 QTL were verified in at least two different environments of E1, E2, E3 and E4, 61 of which were major stable QTL explaining more than 10% of the phenotypic variation. Of these, 32 QTL showed pleiotropic effects and were co-located on chromosomal regions of 1A, 1D, 2A, 2B, 2D, 3A, 4A, 5A, 5B, 6A, 6B, 7B or 7D, referring to 13 major stable QTL clusters. In the WJ and WY population, 22.22% and 32.62% QTL detected based on large RIL populations have been verified in the QTL analysis based on 175/172 WJ/WY RIL populations, respectively. Joint QTL mapping analysis based on the nested association mapping (NAM) population detected 185 congruent QTL among the three RIL populations.⑸Possible genetic relationships between kernel dimensions (KD) and thousand-kernel weight (TKW), TKW, spike-related traits (SRT) and kernel weight per spike (KWPS), and plant height components (PHC) and plant height (PH) were detected using both multivariate conditional and unconditional QTL analysis based on 485/229 WJ/WY RIL populations. The results were as follows: at the QTL level,①kernel width (KW) has the strongest influence on TKW, next to kernel length (KL), but kernel diameter ratio (KDR) has the least level contribution to TKW;②kernel number per spike (KNPS) contributes the most to KWPS, next to TKW, both spikelet numbe per spike (SPN) and SL have lower level contribution to KWPS;③spike length (SL) contributes the least to PH, followed by the first internode length from the top (FIITL); the third internode length from the top (TITL) has the strongest influence on PH, followed by the second internode length from the top (SITL) and the fourth internode length from the top (FOITL).⑹Based on comparison of the QTL detected based on large/small populations using moderate/high-density genetic maps, we concluded that:①both density of the genetic map and population size have great influence on the estimation of QTL number; and②the limited population sizes can lead to overestimation of QTL effects... |
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