He Xiaoqing, Jin Yi, Ye Meixia, Chen Nan, Zhu Jing, Wang Jingqi, Jiang Libo, Wu Rongling
Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
College of Biological Sciences and Technology, Beijing Forestry University, Beijing, China.
Front Microbiol. 2017 Nov 27;8:2332. doi: 10.3389/fmicb.2017.02332. eCollection 2017.
How a species responds to such a biotic environment in the community, ultimately leading to its evolution, has been a topic of intense interest to ecological evolutionary biologists. Until recently, limited knowledge was available regarding the genotypic changes that underlie phenotypic changes. Our study implemented GWAS (Genome-Wide Association Studies) to illustrate the genetic architecture of ecological interactions that take place in microbial populations. By choosing 45 such interspecific pairs of and strains that were all genotyped throughout the entire genome, we employed Q-ROADTRIPS to analyze the association between single SNPs and microbial abundance measured at each time point for bacterial populations reared in monoculture and co-culture, respectively. We identified a large number of SNPs and indels across the genomes (35.69 G clean data of and 50.41 G of ). We reported 66 and 111 SNPs that were associated with interaction in and , respectively. 23 out of 66 polymorphic changes resulted in amino acid alterations.12 significant genes, such as , and , which were also identified in previous evolutionary studies. In , 111 SNPs detected in coding sequences could be divided into 35 non-synonymous and 76 synonymous SNPs. Our study illustrated the potential of genome-wide association methods for studying rapidly evolving traits in bacteria. Genetic association study methods will facilitate the identification of genetic elements likely to cause phenotypes of interest and provide targets for further laboratory investigation.
一个物种如何在群落中对这样的生物环境做出反应，最终导致其进化，一直是生态进化生物学家极为感兴趣的话题。直到最近，关于表型变化背后的基因型变化的知识还很有限。我们的研究实施了全基因组关联研究（GWAS），以阐明微生物种群中发生的生态相互作用的遗传结构。通过选择45对这样的种间菌株对，并对它们的整个基因组进行基因分型，我们采用Q-ROADTRIPS分别分析了单核苷酸多态性（SNP）与在单培养和共培养中培养的细菌种群在每个时间点测量的微生物丰度之间的关联。我们在基因组中鉴定出大量的SNP和插入缺失（分别为35.69G的 和50.41G的 清洁数据）。我们分别报告了66个和111个与 相互作用相关的SNP。66个多态性变化中有23个导致氨基酸改变。12个重要基因，如 、 和 ，这些基因也在先前的进化研究中被鉴定出来。在 中，在编码序列中检测到的111个SNP可分为35个非同义SNP和76个同义SNP。我们的研究说明了全基因组关联方法在研究细菌快速进化性状方面具有潜力。遗传关联研究方法将有助于识别可能导致感兴趣表型的遗传元件，并为进一步的实验室研究提供靶点。
