Curtin Shaun J, Tiffin Peter, Guhlin Joseph, Trujillo Diana I, Burghart Liana T, Atkins Paul, Baltes Nicholas J, Denny Roxanne, Voytas Daniel F, Stupar Robert M, Young Nevin D
Department of Plant Pathology (S.J.C., R.D., N.D.Y.) and Department of Plant Biology (P.T., J.G., D.T., L.B., N.D.Y.), University of Minnesota, St. Paul, Minnesota 55108.
Department of Genetics, Cell Biology, and Development and Center for Genome Engineering, University of Minnesota, Minneapolis, Minnesota 55455 (P.A., N.J.B., D.F.V.); and.
Plant Physiol. 2017 Feb;173(2):921-931. doi: 10.1104/pp.16.01923. Epub 2017 Jan 5.
Genome-wide association (GWA) studies offer the opportunity to identify genes that contribute to naturally occurring variation in quantitative traits. However, GWA relies exclusively on statistical association, so functional validation is necessary to make strong claims about gene function. We used a combination of gene-disruption platforms (Tnt1 retrotransposons, hairpin RNA-interference constructs, and CRISPR/Cas9 nucleases) together with randomized, well-replicated experiments to evaluate the function of genes that an earlier GWA study in Medicago truncatula had identified as candidates contributing to variation in the symbiosis between legumes and rhizobia. We evaluated ten candidate genes found in six clusters of strongly associated single nucleotide polymorphisms, selected on the basis of their strength of statistical association, proximity to annotated gene models, and root or nodule expression. We found statistically significant effects on nodule production for three candidate genes, each validated in two independent mutants. Annotated functions of these three genes suggest their contributions to quantitative variation in nodule production occur through processes not previously connected to nodulation, including phosphorous supply and salicylic acid-related defense response. These results demonstrate the utility of GWA combined with reverse mutagenesis technologies to discover and validate genes contributing to naturally occurring variation in quantitative traits. The results highlight the potential for GWA to complement forward genetics in identifying the genetic basis of ecologically and economically important traits.
全基因组关联(GWA)研究为识别影响数量性状自然变异的基因提供了机会。然而,GWA完全依赖于统计关联,因此需要进行功能验证才能有力地阐明基因功能。我们结合了基因破坏平台(Tnt1逆转座子、发夹RNA干扰构建体和CRISPR/Cas9核酸酶)以及随机且重复良好的实验,来评估在较早的一项蒺藜苜蓿GWA研究中被鉴定为影响豆科植物与根瘤菌共生变异的候选基因的功能。我们评估了在六个紧密关联的单核苷酸多态性簇中发现的十个候选基因,这些基因是根据它们的统计关联强度、与注释基因模型的接近程度以及根或根瘤表达情况来选择的。我们发现三个候选基因对根瘤形成有统计学上的显著影响,每个基因都在两个独立的突变体中得到了验证。这三个基因的注释功能表明,它们对根瘤形成数量变异的贡献是通过以前与结瘤无关的过程实现的,包括磷供应和水杨酸相关的防御反应。这些结果证明了GWA与反向诱变技术相结合在发现和验证影响数量性状自然变异的基因方面的实用性。结果突出了GWA在补充正向遗传学以确定生态和经济重要性状的遗传基础方面的潜力。