CelEst:用于估算秀丽隐杆线虫转录因子活性的统一基因调控网络。

IF 3.3 3区 生物学 Q2 GENETICS & HEREDITY Genetics Pub Date : 2024-12-20 DOI:10.1093/genetics/iyae189
Marcos Francisco Perez
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引用次数: 0

摘要

转录因子(TFs)在协调基因调控的关键复杂模式中起着关键作用。虽然基因表达是复杂的,但数百个基因的差异表达通常是由少数tf调节的。尽管在阐明秀丽隐杆线虫中tf靶调控关系方面做了大量的工作,但现有的实验数据集涵盖了tf的不同子集,这给数据整合带来了挑战。在这里,我介绍CelEst,这是一个统一的基因调控网络,旨在从基因表达数据中估计487种不同秀丽隐杆线虫tf的活性-约占总数的58%。为了整合来自ChIP-seq、dna结合基序和eY1H筛选的数据,针对一组TF扰动RNA-seq实验对每种数据类型的最佳处理进行了基准测试。此外,我还展示了如何利用相关物种基因组中靶启动子中的TF基序保护来区分高信息量的相互作用,这一策略可以应用于许多模式生物。对包括热休克、细菌感染和性别差异在内的常见研究条件的数据进行综合分析,验证了CelEst的表现,并强调了可能在协调这些条件下的转录反应中发挥主要作用的被忽视的tf。CelEst可以在几分钟内推断出一台标准笔记本电脑上的TF活动。此外,还为社区提供了一个带有分步指南的R Shiny应用程序,以最少的编码要求执行快速分析。我预计CelEsT的广泛采用将大大提高转录组学实验的解释力,无论是现在的还是回顾性的,从而提高我们对秀丽隐杆线虫及其他物种基因调控的理解。
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CelEst: a unified gene regulatory network for estimating transcription factor activities in C. elegans.

Transcription factors (TFs) play a pivotal role in orchestrating critical intricate patterns of gene regulation. Although gene expression is complex, differential expression of hundreds of genes is often due to regulation by just a handful of TFs. Despite extensive efforts to elucidate TF-target regulatory relationships in Caenorhabditis elegans, existing experimental datasets cover distinct subsets of TFs and leave data integration challenging. Here, I introduce CelEst, a unified gene regulatory network designed to estimate the activity of 487 distinct C. elegans TFs-∼58% of the total-from gene expression data. To integrate data from ChIP-seq, DNA-binding motifs, and eY1H screens, optimal processing of each data type was benchmarked against a set of TF perturbation RNA-seq experiments. Moreover, I showcase how leveraging TF motif conservation in target promoters across genomes of related species can distinguish highly informative interactions, a strategy which can be applied to many model organisms. Integrated analyses of data from commonly studied conditions including heat shock, bacterial infection, and sex differences validates CelEst's performance and highlights overlooked TFs that likely play major roles in coordinating the transcriptional response to these conditions. CelEst can infer TF activity on a standard laptop computer within minutes. Furthermore, an R Shiny app with a step-by-step guide is provided for the community to perform rapid analysis with minimal coding required. I anticipate that widespread adoption of CelEsT will significantly enhance the interpretive power of transcriptomic experiments, both present and retrospective, thereby advancing our understanding of gene regulation in C. elegans and beyond.

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来源期刊
Genetics
Genetics GENETICS & HEREDITY-
CiteScore
6.90
自引率
6.10%
发文量
177
审稿时长
1.5 months
期刊介绍: GENETICS is published by the Genetics Society of America, a scholarly society that seeks to deepen our understanding of the living world by advancing our understanding of genetics. Since 1916, GENETICS has published high-quality, original research presenting novel findings bearing on genetics and genomics. The journal publishes empirical studies of organisms ranging from microbes to humans, as well as theoretical work. While it has an illustrious history, GENETICS has changed along with the communities it serves: it is not your mentor''s journal. The editors make decisions quickly – in around 30 days – without sacrificing the excellence and scholarship for which the journal has long been known. GENETICS is a peer reviewed, peer-edited journal, with an international reach and increasing visibility and impact. All editorial decisions are made through collaboration of at least two editors who are practicing scientists. GENETICS is constantly innovating: expanded types of content include Reviews, Commentary (current issues of interest to geneticists), Perspectives (historical), Primers (to introduce primary literature into the classroom), Toolbox Reviews, plus YeastBook, FlyBook, and WormBook (coming spring 2016). For particularly time-sensitive results, we publish Communications. As part of our mission to serve our communities, we''ve published thematic collections, including Genomic Selection, Multiparental Populations, Mouse Collaborative Cross, and the Genetics of Sex.
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