Data from: Gene coexpression networks reveal key drivers of phenotypic divergence in lake whitefish

BACKGROUND: A functional understanding of processes involved in adaptive divergence is one of the awaiting opportunities afforded by high throughput transcriptomic technologies. Functional analysis of co-expressed genes has succeeded in the biomedical field in identifying key drivers of disease pathways. However, in ecology and evolutionary biology, functional interpretation of transcriptomic data is still limited. RESULTS: Here we used Weighted Gene Co-Expression Network Analysis (WGCNA) to identify modules of co-expressed genes in muscle and brain tissue of a lake whitefish backcross progeny. Modules were connected to gradients of known adaptive traits involved in the ecological speciation process between benthic and limnetic ecotypes. Key drivers, i.e. hub genes of functional modules related to reproduction, growth, and behavior were identified, and module preservation was assessed in natural populations. Using this approach, we identified modules of co-expressed genes involved in phenotypic divergence and their key drivers, and further identified a module part specifically rewired in the backcross progeny. CONCLUSIONS: Functional analysis of transcriptomic data can significantly contribute to the understanding of the mechanisms underlying ecological speciation. Our findings point to BMP and Calcium signaling as common pathways involved in coordinated evolution of trophic behavior, trophic morphology (gill rakers), and reproduction. Results also point to pathways implicating hemoglobins and constitutive stress response (HSP70) governing growth in lake whitefish.

研究背景：对适应性分化相关过程的功能解析，是高通量转录组技术（high throughput transcriptomic technologies）所带来的待探索机遇之一。共表达基因功能分析已在生物医学领域成功识别出疾病通路的关键调控因子。然而在生态学与进化生物学领域，转录组数据的功能阐释仍较为有限。
研究结果：本研究采用加权基因共表达网络分析（Weighted Gene Co-Expression Network Analysis, WGCNA），在湖白鲑回交后代的肌肉与脑组织中鉴定出共表达基因模块。将该基因模块与底栖生态型与浮游生态型间生态物种形成过程所涉及的已知适应性性状梯度进行关联分析。本研究识别出与繁殖、生长及行为相关的功能模块的枢纽基因（hub genes），并在自然种群中评估了模块的保守性。通过该分析策略，我们鉴定出参与表型分化的共表达基因模块及其关键调控因子，并进一步发现了一个仅在回交后代中发生特异性重连的基因模块。
研究结论：转录组数据的功能分析可显著推动对生态物种形成潜在机制的解析。本研究结果显示，骨形态发生蛋白（Bone Morphogenetic Protein, BMP）与钙信号通路（Calcium signaling）是参与摄食行为、摄食形态（鳃耙）及繁殖协同演化的共同通路。此外，本研究还发现，调控湖白鲑生长的通路涉及血红蛋白与组成型应激反应（HSP70）。