基于RNA-Seq的小麦产量性状全基因组关联分析

发布时间：2018-10-09 19:20

【摘要】：小麦(Triticum aestivum)是世界上种植最广泛的谷物,它提供了大约20%的人类所消耗的热量。预计到2050年对小麦的需求可能会增加60%。因此,提高小麦产量尤为迫切。千粒重、单位面积穗数、穗粒数作为产量三要素是提高小麦产量的重要途径。除此之外,种质资源也在提高小麦产量上起重要作用。目前,小麦育种普遍存在种质资源匮乏等问题,迫切需要新种质的发现和创造。人工诱导产生突变体、构建突变体库,可以为小麦功能基因研究和小麦遗传改良提供基础材料。本研究以烟农15和经EMS诱变烟农15获得的农艺性状差异较大的110个株系为试验材料,以小麦12个主要产量性状为研究对象,利用RNA-Seq技术开发高通量单核苷酸多态性(SNP)和插入缺失(InDel)标记用于关联分析,为小麦遗传育种提供候选关联标记及基因。主要结果如下:1.本研究对烟农15开花后9天(DPA9)、18天(DPA18)、27天(DPA27)三个时期样本进行RNA-Seq技术测序,采用参考基因组拼接的方法对小麦转录组进行组装,得到较完整的转录组。共获得195601条转录本,平均长度1988bp。2.本研究对110个突变体株系开花后9天(DPA9)、18天(DPA18)、27天(DPA27)三个时期RNA等量等浓度混合后进行RNA-Seq测序,在已拼接好的转录组基础上,共在110个突变体株系中开发了126,980个标记,其中包括101,876个SNP标记,25,104个Indel标记。3.对突变体群体进行表型分析和相关性分析,结果表明突变体株系的12个产量性状均有较大的变异,变异系数在4.12~111.90%之间,变异最小的性状为粒长、变异最大性状为顶部不育小穗数。多数性状之间相关性显著。4.利用126,980个标记对产量相关性状进行关联分析,共检测到84个标记与9个产量性状在P7.87E-6水平存在显著关联,其中,与株高、小穗数、顶部不育小穗数、不育小穗数、可育小穗数、穗数、千粒重、粒长、粒宽显著关联的标记数分别为2、1、38、5、3、1、6、25、3个;检测到16个标记与穗粒数在P7.87E-8水平存在显著关联;检测到25个标记与穗长在P1E-6水平存在显著关联。单个标记位点的变异解释率范围在18.209%-52.993%。
[Abstract]:Wheat (Triticum aestivum) is the most widely grown grain in the world, providing about 20 percent of the calories consumed by humans. Demand for wheat is expected to increase by 60 percent by 2050. Therefore, increasing wheat yield is particularly urgent. 1000-grain weight, panicle number per unit area and grain number per panicle are three important factors to improve wheat yield. In addition, germplasm resources also play an important role in improving wheat yield. At present, wheat breeding is generally lack of germplasm resources, so the discovery and creation of new germplasm are urgently needed. Artificial induction of mutants and construction of mutants library can provide basic materials for wheat functional gene research and wheat genetic improvement. In this study, 110 lines obtained from Yannong 15 and Yannong 15 mutated by EMS were used as experimental materials, and 12 main yield characters of wheat were studied. High throughput single nucleotide polymorphisms (SNP) and insertion deletion (InDel) (InDel) markers were developed by RNA-Seq for association analysis to provide candidate association markers and genes for wheat genetics and breeding. The main results are as follows: 1. In this study, three samples of Yannong 15 were sequenced by RNA-Seq technique in three periods (DPA9, DPA18, 27 days (DPA27). The transcriptome of wheat was assembled by reference genome splicing method, and the complete transcriptome was obtained. A total of 195601 transcripts were obtained, with an average length of 1988bp.2. In this study, RNA-Seq sequencing was carried out on 110 mutants 9 days after anthesis (DPA9), 18 days after anthesis (DPA18) and 27 days after anthesis (DPA27). On the basis of spliced transcriptome, 126980 markers were developed in 110 mutants. These include 101876 SNP tags and 25104 Indel tags. Phenotypic analysis and correlation analysis of the mutant population showed that the 12 yield traits of the mutants had great variation, the coefficient of variation was between 4.12 and 111.90%, and the least variation was grain length. The maximum variation was the number of sterile spikelets at the top. The correlation between most traits was significant. 4. A total of 84 markers and 9 yield traits were found to be significantly correlated at P7.87E-6 level with 126980 markers, including plant height, spikelet number, number of sterile spikelets at the top, number of fertile spikelets, and number of fertile spikelets. The number of markers significantly correlated with panicle number, 1000-grain weight, grain length and grain width were 2 ~ (1) 1 ~ (38) ~ (35) ~ (35) ~ (3) ~ (1) ~ (1) ~ (1) ~ 625, 3, respectively, and 16 markers were significantly correlated with grain number per spike at P7.87E-8 level, and 25 markers were found to be significantly correlated with ear length at P1E-6 level. The interpretation rate of single marker loci ranged from 18.209 to 52.993.
【学位授予单位】：山东农业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：S512.1

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