不同磷、钾处理小麦苗期氮营养性状的QTL分析

QTL mapping of nitrogen related traits under different concentrations of P and K at wheat seedling stage

【目的】对不同浓度磷、钾处理下小麦苗期氮养分效率相关性状进行QTL分析,以深入理解磷、钾与氮养分效率的相互关系,为氮营养相关性状的图位克隆及分子标记辅助选择育种奠定基础。【方法】采用苗期液培试验,以"川35050×山农483"组合衍生的小麦重组自交系群体(131个株系)为研究材料,设置了中磷中钾(MPMK)、高磷(HP)、低磷1(LP1)、低磷2(LP2)、低磷3(LP3),高钾(HK)、低钾1(LK1)、低钾2(LK2)、低钾3(LK3)共9个处理,对不同磷、钾处理下的氮养分效率相关性状进行研究,并结合分子标记遗传图谱,从整个基因组水平对与小麦苗期氮养分效率相关的10个性状进行QTL定位及遗传分析。【结果】不同处理下的10个性状共检测到137个QTL,位于除3D外的20条染色体上,大部分QTL(89.05%)仅在单一处理下被定位到,有3个QTL(QRnue-1A.2、QSnue-1A.1和QTnue-1A.1)可在至少4个处理中被检测到,有5个QTL(QRnue-1A.1、QTnue-1A.1、QSnc-4A、QRnc-6A.3和QSnue-6B)可同时在低磷和低钾环境中被检测到。本研究还检测到至少包含3个以上QTL的QTL簇17个,分别位于1A、1B、2B、2D、3A、3B、4A、4B、5D、6A、6 B、6 D和7 A染色体上,共涉及6 6个Q T L,占Q T L总数的4 8.1 8%。其中,有5个Q T L簇仅与特定磷、钾处理有关,大多数QTL簇均同时定位了不同磷、钾处理的不同性状,许多QTL簇位点还与前人定位的生物量、产量及其他养分有关。【结论】磷、钾的供应能够显著影响小麦苗期对氮素的吸收利用及其相关QTL的表达。影响苗期小麦氮养分效率相关性状的QTL大多数仅在特定处理下被检测到,但大多数QTL会形成QTL簇,构成了控制氮养分效率的QTL热点,许多热点区域也与前人定位的许多成株期性状如生物量、产量及其他养分效率有关,这些QTL/基因密集区域及其特点的发现,为我们深入理解小麦氮养分效率的遗传控制特点及其与磷、钾养分供应的关系提供了新的视角,也为这些重要位点的克隆及其应用提供数据支持。

【Objectives】The objective of this study was to detect quantitative trait locus（QTL） for N use efficiency related traits at the seedling stage of wheat under different levels of phosphorus（P） and potassium（K）treatments. The results will deepen our understanding of the relationship between N and P/K, and this knowledge could be applied for map-based cloning and marker assisted selection（MAS） in wheat breeding. 【Methods】Population employed for QTL analysis was a set of 131 RILs derived from a Chuan 35050 × Shannong 483 cross.The 131 RILs and their parental lines were grown under hydroponic culture in greenhouse. Nine treatments were designed. The concentrations of the applied P and K treatments were as follows： moderate P and K（MPMK）, high P（HP）, low P1（LP1）, low P2（LP2）, low P3（LP3）, high K（HK）, low K1（LK1）, low K2（LK2） and low K3（LK3）. Combined with an enriched genetic map, we conducted research on the N use efficiency traits under different P and K treatments in order to map the QTLs（quantitative trait loci） related to N use efficiency of 10 traits at the wheat seedling stage and to conduct genetic analysis at the whole genome level. 【Results】 A total of 137 QTLs for the 10 seedling traits were detected on 20 chromosomes, with the exception of 3D. Of these QTLs, 122（89.05%） were detected in only one treatment. Three relatively high-frequency QTLs（QRnue-1A.2,QSnue-1A.1 and QTnue-1A.1） were detected in four treatments at least. Five QTLs（QRnue-1A.1, QTnue-1A.1, QSnc-4A, QRnc-6A.3 and QSnue-6B） were detected in both the low P and low K treatments. Seventeen important QTL clusters（C1-C17） containing at least three or more traits which involved 66 out of 137 QTLs（48.18%） were mapped on chromosomes 1A, 1B, 2B, 2D, 3A, 3B, 4A, 4B, 5D, 6A, 6B, 6D and 7A. Most QTL clusters were detected in both P and K treatments, while five QTL clusters only associated with specific phosphorus or potassium treatments. Many QTL cluster sites in this study were also related to the biomass,yield and other nutrients in the predecessors＇ investigation. 【Conclusions】 The supply of P and K significantly affects N efficiency of wheat at the seedling stage and the expression of related QTLs. Most N efficiency related QTLs were only detected in certain treatments, but many QTLs were located at the same hot sites and composed clusters（hot sites）. Many of these sites were also co-located QTLs for biomass, yield and other nutrient traits in the previous study. The detection of these QTL/gene hot sites is valuable for further understanding about the genetic control of N efficiency related traits of wheat and their relationship with P and K environment.