Intraspecies Transcriptional Profiling Reveals Key Regulators of Candida albicans Pathogenic Traits.
Intraspecies Transcriptional Profiling Reveals Key Regulators of Candida albicans Pathogenic Traits.
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DOI：
10.1128/mbio.00586-21
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发表时间：
2021-04-20
期刊：
影响因子：
6.4
通讯作者：
Anderson MZ
中科院分区：
文献类型：
--
作者：
Wang JM;Woodruff AL;Dunn MJ;Fillinger RJ;Bennett RJ;Anderson MZ
感染性真菌物种通常被统一处理，尽管有明确的证据表明基因型和表型异质性在菌株间广泛存在。确定这种表型多样性的遗传基础极具挑战性，因为可能有数万或数十万个变体可以区分两种菌株。人类真菌和机会致病真菌白念珠菌在临床分离株中显示出广泛的遗传和表型变异。在这里，我们对21个特征良好的分离株进行了RNA测序，以研究遗传变异如何导致基因表达差异，并将这些差异与表型性状联系起来。C.白念珠菌适应主要通过克隆进化，但在这组分离株的基因表达谱的层次聚类没有再现其系统发育关系。引人注目的是，菌株特异性基因表达在某些菌株背景中普遍存在。基因表达与表型数据的关联，通过差异分析、线性相关和基因网络的组装将先前表征的和新的基因与23 C连接起来。白色念珠菌特征构建的从头基因模块产生的基因图谱纳入67%的C。白念珠菌基因，并揭示了表达模块和重要的表型，如系统毒力之间的相关性。此外，有针对性的调查，有新的作用，在生长和发育的两个模块支持我们的生物信息学预测。总之，这些研究揭示了C中广泛的转录变异。白念珠菌分离，并确定遗传和表观遗传联系的表型变异的基础上共表达网络分析。
Infectious fungal species are often treated uniformly despite clear evidence of genotypic and phenotypic heterogeneity being widespread across strains. Identifying the genetic basis for this phenotypic diversity is extremely challenging because of the tens or hundreds of thousands of variants that may distinguish two strains. The human commensal and opportunistic fungal pathogen Candida albicans displays extensive genetic and phenotypic variation across clinical isolates. Here, we performed RNA sequencing on 21 well-characterized isolates to examine how genetic variation contributes to gene expression differences and to link these differences to phenotypic traits. C. albicans adapts primarily through clonal evolution, and yet hierarchical clustering of gene expression profiles in this set of isolates did not reproduce their phylogenetic relationship. Strikingly, strain-specific gene expression was prevalent in some strain backgrounds. Association of gene expression with phenotypic data by differential analysis, linear correlation, and assembly of gene networks connected both previously characterized and novel genes with 23 C. albicans traits. Construction of de novo gene modules produced a gene atlas incorporating 67% of C. albicans genes and revealed correlations between expression modules and important phenotypes such as systemic virulence. Furthermore, targeted investigation of two modules that have novel roles in growth and filamentation supported our bioinformatic predictions. Together, these studies reveal widespread transcriptional variation across C. albicans isolates and identify genetic and epigenetic links to phenotypic variation based on coexpression network analysis.