Su Chengfu, Wang Wei, Gong Shunliang, Zuo Jinghui, Li Shujiang, Xu Shizhong
Department of Life Sciences, Liupanshui Normal UniversityLiupanshui, China.
Department of Botany and Plant Sciences, University of California, RiversideRiverside, CA, USA.
Front Plant Sci. 2017 May 8;8:706. doi: 10.3389/fpls.2017.00706. eCollection 2017.
Increasing grain yield is the ultimate goal for maize breeding. High resolution quantitative trait loci (QTL) mapping can help us understand the molecular basis of phenotypic variation of yield and thus facilitate marker assisted breeding. The aim of this study is to use genotyping-by-sequencing (GBS) for large-scale SNP discovery and simultaneous genotyping of all F individuals from a cross between two varieties of maize that are in clear contrast in yield and related traits. A set of 199 F progeny derived from the cross of varieties SG-5 and SG-7 were generated and genotyped by GBS. A total of 1,046,524,604 reads with an average of 5,258,918 reads per F individual were generated. This number of reads represents an approximately 0.36-fold coverage of the maize reference genome Zea_mays.AGPv3.29 for each F individual. A total of 68,882 raw SNPs were discovered in the F population, which, after stringent filtering, led to a total of 29,927 high quality SNPs. Comparative analysis using these physically mapped marker loci revealed a higher degree of synteny with the reference genome. The SNP genotype data were utilized to construct an intra-specific genetic linkage map of maize consisting of 3,305 bins on 10 linkage groups spanning 2,236.66 cM at an average distance of 0.68 cM between consecutive markers. From this map, we identified 28 QTLs associated with yield traits (100-kernel weight, ear length, ear diameter, cob diameter, kernel row number, corn grains per row, ear weight, and grain weight per plant) using the composite interval mapping (CIM) method and 29 QTLs using the least absolute shrinkage selection operator (LASSO) method. QTLs identified by the CIM method account for 6.4% to 19.7% of the phenotypic variation. Small intervals of three QTLs (, and ) contain several genes, including one gene (GRMZM2G139872) encoding the F-box protein, three genes (GRMZM2G180811, GRMZM5G828139, and GRMZM5G873194) encoding the WD40-repeat protein, and one gene (GRMZM2G019183) encoding the UDP-Glycosyltransferase. The work will not only help to understand the mechanisms that control yield traits of maize, but also provide a basis for marker-assisted selection and map-based cloning in further studies.
提高谷物产量是玉米育种的最终目标。高分辨率数量性状位点(QTL)定位有助于我们了解产量表型变异的分子基础,从而促进分子标记辅助育种。本研究的目的是利用简化基因组测序(GBS)进行大规模单核苷酸多态性(SNP)发现,并对两个玉米品种杂交产生的所有F个体进行同步基因分型,这两个玉米品种在产量及相关性状上有明显差异。通过GBS对SG-5和SG-7两个品种杂交产生的199个F子代进行基因分型。共产生了1,046,524,604条 reads,每个F个体平均有5,258,918条 reads。这个 reads 数量代表了每个F个体对玉米参考基因组Zea_mays.AGPv3.29约0.36倍的覆盖度。在F群体中总共发现了68,882个原始SNP,经过严格筛选后,得到了总共29,927个高质量SNP。使用这些物理定位的标记位点进行比较分析,发现与参考基因组具有更高程度的共线性。利用SNP基因型数据构建了一个玉米种内遗传连锁图谱,该图谱由10个连锁群上的3,305个bin组成,跨度为2,236.66 cM,相邻标记之间的平均距离为0.68 cM。通过该图谱,我们使用复合区间作图(CIM)方法鉴定了28个与产量性状(百粒重、穗长、穗直径、穗轴直径、行数、每行玉米粒数、穗重和单株粒重)相关的QTL,使用最小绝对收缩选择算子(LASSO)方法鉴定了29个QTL。CIM方法鉴定的QTL解释了6.4%至19.7%的表型变异。三个QTL(、和)的小区间包含几个基因,包括一个编码F-box蛋白的基因(GRMZM2G139872)、三个编码WD40重复蛋白的基因(GRMZM2G180811、GRMZM5G828139和GRMZM5G873194)以及一个编码UDP-糖基转移酶的基因(GRMZM2G019183)。这项工作不仅有助于理解控制玉米产量性状的机制,也为进一步研究中的分子标记辅助选择和图位克隆提供了基础。