A mapping framework of competition–cooperation QTLs that drive community dynamics

Abstract

Genes have been thought to affect community ecology and evolution, but their identification at the whole-genome level is challenging. Here, we develop a conceptual framework for the genome-wide mapping of quantitative trait loci (QTLs) that govern interspecific competition and cooperation. This framework integrates the community ecology theory into systems mapping, a statistical model for mapping complex traits as a dynamic system. It can characterize not only how QTLs of one species affect its own phenotype directly, but also how QTLs from this species affect the phenotype of its interacting species indirectly and how QTLs from different species interact epistatically to shape community behavior. We validated the utility of the new mapping framework experimentally by culturing and comparing two bacterial species, Escherichia coli and Staphylococcus aureus, in socialized and socially isolated environments, identifying several QTLs from each species that may act as key drivers of microbial community structure and function.

Gut microbiota in ulcerative colitis: insights on pathogenesis and treatment

“…Studying interrelationships within a microbiome requires an analysis of inter‐individual or inter‐species interactions, but the manner and intensity of the interaction is unclear . Therefore, a suitable research strategy and model for studying the interaction of intestinal flora is required to facilitate a clarification of the characteristics of the intestinal flora ecology . A study of Drosophila melanogaster shows that interactions between bacterial species can affect host life and microbial abundance .…”

“…114,115 Therefore, a suitable research strategy and model for studying the interaction of intestinal flora is required to facilitate a clarification of the characteristics of the intestinal flora ecology. [116][117][118] A study of Drosophila melanogaster shows that interactions between bacterial species can affect host life and microbial abundance. 119 It is possible that multi-omic microbiome interactions may underlie UC disease activity.…”

Progress in next generation sequencing (NGS) combined with genetic statistical model in microbial molecular ecology

“…或系统来定位数量性状位点(quantitative trait loci, QTLs), 具有更高的生物学内涵 [16,17] [18] ; 同时 基因表达调控网络的重构是功能基因组中最具挑战性 的课题之一, 贝叶斯网络模型已成为构建基因调控网 络的有力工具 [19] . 本文围绕NGS并结合以上遗传统计 模型对微生物互作、表型可塑性、微生物与植物互作 等方面的应用研究进行了概述和展望.…”

“…He等人 [7] 将45对大肠杆菌 ( [32,33] . 最近, 博弈 论被引入该理论框架, 用于解析共培养细菌之间相互 竞争与合作的方式与强度, 基于此, 研究人员提出了 竞争合作定位模型 [17] . Jiang等人 [17] 发现, 两个不同细 [41] .…”

“…最近, 博弈 论被引入该理论框架, 用于解析共培养细菌之间相互 竞争与合作的方式与强度, 基于此, 研究人员提出了 竞争合作定位模型 [17] . Jiang等人 [17] 发现, 两个不同细 [41] . 对海洋微生物的研究发现, 表型可塑性影 响微生物群落功能变化 [18] , 较强的表型可塑性加强了 微生物的环境适应能力 [42] .…”