基于两个相关群体的玉米7个主要农艺性状遗传分析和QTL定位

株高、穗位高、穗位比、叶面积、叶形系数、散粉-吐丝时间间隔(ASI)和雄穗分枝数等是影响玉米生态适应性、抗倒性、耐密植能力及生产潜力的重要农艺性状。因此, 以TS141为共同亲本, 分别与廊黄、昌7-2杂交, 构建2套F₂群体(LTpop、CTpop)为试材, 分析了7个农艺性状的杂种优势, 探讨了其与单穗重间的相互关系, 并进行相关性状QTLs的检测及效应分析。结果表明: 1)2个F₁杂交种的穗位比和ASI表现为明显的中亲优势, 其余5个性状均呈明显的正向超亲优势;F₁杂种优势指数和相对杂种优势均表现为株高>穗位高>雄穗分枝数>叶面积>叶形系数>ASI>穗位比, 而F₂优势降低率表现为叶面积>株高>穗位高>雄穗分枝数>ASI>叶形系数>穗位比。2)单穗重与ASI呈显著负相关, 与其余性状间均呈显著正相关;除雄穗分枝数外, 利用逐步回归分析成功构建了单穗重与其余6个农艺性状间的最优多元线性回归方程。3)利用CIM法在2套F₂群体间总共检测到56个QTLs位点, 单个QTL的表型贡献率介于4.22%~15.74%。其中株高、穗位比、ASI和雄穗分枝数均受加性和非加性效应的调控, 而其余性状均受非加性效应的调控;进一步分析, 在2套F₂群体中总共检测到12个稳定表达的sQTLs位点, 分别位于Bin1.07(umc1278~bnlg1025)调控株高、Bin1.08~1.10(mmc0041~phi308707)调控叶面积、Bin2.02(umc1823~umc2363)调控ASI、Bin4.06(bnlg1621a~umc2027)同时调控穗位高和穗位比、Bin4.09(umc2287~umc2360)同时调控ASI和雄穗分枝数、Bin6.05(umc2040~bnlg1174a)调控ASI、Bin7.00(umc2177~umc1378)调控雄穗分枝数、Bin8.08(umc1005~umc2218)调控穗位比、 Bin10.01~10.02(bnlg451~umc1337)同时调控株高和穗位比。为玉米相关性状的育种应用、精细定位及基因克隆提供有益参考。

Genetic analysis and QTL mapping for seven agronomic traits in maize (Zea mays) using two connected populations

Seven important agronomic traits that influence the ecological adaptability, lodging resistance, dense planting ability and the production potential of maize are plant height (PH), ear height (EH), panicle aspect ratio (PAR), leaf area (LA), leaf shape coefficient (LSC), anthesis-silking interval (ASI) and tassel branch number (TBN). In order to analyze the heterosis of these seven traits, two F₂ populations were derived from crosses of Langhuang×TS141 (LTpop) and Chang7-2×TS141(CTpop). Analysis was also undertaken to reveal the relationship between these traits and ear weight (EW), and to detect QTLs and their corresponding QTL effects. The results showed that: 1) The PAR and ASI of the two F₁ hybrids showed significant mid-parent heterosis, while the other traits showed significant positive over-parent heterosis. The F₁ heterosis index and relative heterosis results were consistently PH>EH>TBN>LA>LSC>ASI>PAR. However, the F₂ advantage reduction rate results were LA>PH>EH>TBN>ASI>LSC>PAR. 2) EW was significantly negatively correlated with ASI and was significantly positively correlated with the other six traits. Moreover, except for TBN, optimal regression equations between EW and the other six traits were successfully constructed via stepwise regression analysis. 3)56 QTLs were detected in the two F₂ populations using composite interval mapping (CIM), with the results explaining 4.22%-15.74% of phenotypic variation per QTL. For these QTLs, PH, PAR, ASI and TBN showed both additive and non-additive effects, while the other traits showed non-additive effects. Further analysis identified 12 stable QTLs (sQTLs) in the two F₂ populations. These sQTLs were for PH (Bin1.07; umc1278-bnlg1025), LA (Bin1.08-1.10; mmc0041-phi308707), ASI (Bin2.02; umc1823-umc2363), EH and PAR (Bin4.06; bnlg1621a-umc2027), ASI and TBN (Bin4.09; umc2287-umc2360), ASI(Bin6.05; umc2040-bnlg1174a),TBN (Bin7.00; umc2177-umc1378), PAR (Bin8.08; umc1005-umc2218), and for PH and PAR (Bin10.01-10.02; bnlg451-umc1337). This study has provided valuable information for application in the breeding, precision mapping and positional gene cloning for desired agronomic traits in maize.