A meta-analysis of RNA-Seq studies to identify novel genes that regulate aging.
A meta-analysis of RNA-Seq studies to identify novel genes that regulate aging.
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DOI：
10.1016/j.exger.2023.112107
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发表时间：
2023-03
影响因子：
3.9
通讯作者：
Truttmann, Matthias C.
中科院分区：
文献类型：
--
作者：
Bairakdar, Mohamad D.;Tewari, Ambuj;Truttmann, Matthias C.
衰老是一种普遍存在的生物过程，它限制了大多数生物体的最大寿命。许多研究小组作出了重大努力，确定了在受到自然或人工刺激时足以延长或缩短最大寿命的机制。先前使用秀丽隐杆线虫（C. elegans）进行的衰老研究产生了大量公开可用的转录组学数据集，这些数据集将基因表达的变化与寿命调节联系起来。然而，在衰老生物学的背景下，这些数据集在研究中的全面比较是缺失的。在这里，我们对从74篇同行评审的关于秀丽隐杆线虫衰老相关转录组变化的出版物中获得的1200多个大体积RNA测序（RNASeq）样本进行了系统的荟萃分析。使用差异表达分析和机器学习方法，我们挖掘了新的促长寿基因的汇总数据。我们发现这两种方法都能识别已知的长寿基因并提出新的长寿基因。此外，我们发现实验室间的实验差异使机器学习算法的应用复杂化，这是使用批量RNA-Seq批量校正和归一化技术无法解决的限制。总的来说，我们的研究结果表明，机器学习方法可能有助于识别调节衰老的基因，但需要更复杂的批量校正策略或标准化的输入数据来可靠地识别新的促长寿基因。
Aging is a ubiquitous biological process that limits the maximal lifespan of most organisms. Significant efforts by many groups have identified mechanisms that, when triggered by natural or artificial stimuli, are sufficient to either enhance or decrease maximal lifespan. Previous aging studies using the nematode Caenorhabditis elegans (C. elegans) generated a wealth of publicly available transcriptomics datasets linking changes in gene expression to lifespan regulation. However, a comprehensive comparison of these datasets across studies in the context of aging biology is missing. Here, we carry out a systematic meta-analysis of over 1200 bulk RNA sequencing (RNASeq) samples obtained from 74 peer-reviewed publications on aging-related transcriptomic changes in C. elegans. Using both differential expression analyses and machine learning approaches, we mine the pooled data for novel pro-longevity genes. We find that both approaches identify known and propose novel pro-longevity genes. Further, we find that inter-lab experimental variance complicates the application of machine learning algorithms, a limitation that was not solved using bulk RNA-Seq batch correction and normalization techniques. Taken as a whole, our results indicate that machine learning approaches may hold promise for the identification of genes that regulate aging but will require more sophisticated batch correction strategies or standardized input data to reliably identify novel pro-longevity genes.
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影响因子：
7.8
作者：
Kaeberlein, Tammi L.;Smith, Erica D.;Kaeberlein, Matt
通讯作者：
Kaeberlein, Matt
影响因子：
64.8
作者：
Jumper J;Evans R;Pritzel A;Green T;Figurnov M;Ronneberger O;Tunyasuvunakool K;Bates R;Žídek A;Potapenko A;Bridgland A;Meyer C;Kohl SAA;Ballard AJ;Cowie A;Romera-Paredes B;Nikolov S;Jain R;Adler J;Back T;Petersen S;Reiman D;Clancy E;Zielinski M;Steinegger M;Pacholska M;Berghammer T;Bodenstein S;Silver D;Vinyals O;Senior AW;Kavukcuoglu K;Kohli P;Hassabis D
通讯作者：
Hassabis D
影响因子：
8
作者：
Jaiswal AK;Yadav J;Makhija S;Mazumder S;Mitra AK;Suryawanshi A;Sandey M;Mishra A
通讯作者：
Mishra A
影响因子：
4.5
作者：
Fabris F;Magalhães JP;Freitas AA
通讯作者：
Freitas AA
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y