Functional characterization of open reading frames in nonmodel organisms, such as the common opportunistic fungal pathogen Candida albicans, can be labor-intensive. To meet this challenge, we built a comprehensive and unbiased coexpression network for C. albicans, which we call CalCEN, from data collected from 853 RNA sequencing runs from 18 large-scale studies deposited in the NCBI Sequence Read Archive. Retrospectively, CalCEN is highly predictive of known gene function annotations and can be synergistically combined with sequence similarity and interaction networks in Saccharomyces cerevisiae through orthology for additional accuracy in gene function prediction. To prospectively demonstrate the utility of the coexpression network in C. albicans, we predicted the function of underannotated open reading frames (ORFs) and identified CCJ1 as a novel cell cycle regulator in C. albicans. This study provides a tool for future systems biology analyses of gene function in C. albicans. We provide a computational pipeline for building and analyzing the coexpression network and CalCEN itself at http://github.com/momeara/CalCEN.

中文翻译：

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使用共表达对白色念珠菌基因进行 DeORFanizing

非模式生物（例如常见的机会性真菌病原体白色念珠菌）中开放阅读框的功能表征可能是劳动密集型的。为了应对这一挑战，我们从 NCBI 序列读取档案中保存的 18 项大规模研究的 853 次 RNA 测序运行中收集的数据为白色念珠菌建立了一个全面且无偏见的共表达网络，我们称之为 CalCEN。回顾过去，CalCEN 对已知基因功能注释具有高度预测性，并且可以通过正交学与酿酒酵母中的序列相似性和相互作用网络协同结合，以提高基因功能预测的准确性。前瞻性地证明共表达网络在在白色念珠菌中，我们预测了未充分注释的开放阅读框 (ORF) 的功能，并将 CCJ1 鉴定为白色念珠菌中的一种新型细胞周期调节剂。这项研究为未来对白色念珠菌基因功能进行系统生物学分析提供了一个工具。我们在 http://github.com/momeara/CalCEN 提供了用于构建和分析共表达网络和 CalCEN 本身的计算管道。