在数据稀少的情况下,3'RNA-seq 优于标准 RNA-seq,但在确定模式生物的毒性通路方面,3'RNA-seq 则逊色于标准 RNA-seq。

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Frontiers in bioinformatics Pub Date : 2023-07-27 eCollection Date: 2023-01-01 DOI:10.3389/fbinf.2023.1234218
Ryan S McClure, Yvonne Rericha, Katrina M Waters, Robyn L Tanguay
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摘要

引言RNA 测序技术的应用为研究复杂生物系统中的基因表达水平带来了诸多突破。其中包括了解生物体(如脊椎动物模式生物斑马鱼(Danio rerio))如何对毒物暴露做出反应。最近,3'RNA-seq 的发展使得基因表达水平的测定只需要标准 RNA-seq 所需的一小部分读数。虽然 3' RNA-seq 有很多优点,但在整个生物体毒性和数据稀少的情况下,还没有与标准 RNA-seq 进行过比较。方法与结果在此,我们用 3' RNA-seq 或标准 RNA-seq 对暴露于全氟丁烷磺酰胺(FBSA)的斑马鱼样本进行了研究,以确定两者在识别功能富集通路方面的优势。我们发现,3'RNA-seq 和标准 RNA-seq 在关注基因组中已注释或未注释的区域时表现出特定的优势。我们还发现,标准 RNA-seq 能鉴定出更多的差异表达基因 (DEG),但在数据稀少的情况下,这种优势就会消失。我们还发现,通过分析 DEG 列表,标准 RNA-seq 在识别功能富集通路方面具有显著优势,但通过对所有基因进行基因组富集分析来识别通路时,这种优势则微乎其微。结论:这些结果表明,每种方法都有可能在某些实验条件下发挥优势。我们的观察结果有助于指导其他人选择 3' RNA-seq 与标准 RNA 测序来查询一系列生物系统中的基因表达水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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3' RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism.

Introduction: The application of RNA-sequencing has led to numerous breakthroughs related to investigating gene expression levels in complex biological systems. Among these are knowledge of how organisms, such as the vertebrate model organism zebrafish (Danio rerio), respond to toxicant exposure. Recently, the development of 3' RNA-seq has allowed for the determination of gene expression levels with a fraction of the required reads compared to standard RNA-seq. While 3' RNA-seq has many advantages, a comparison to standard RNA-seq has not been performed in the context of whole organism toxicity and sparse data. Methods and results: Here, we examined samples from zebrafish exposed to perfluorobutane sulfonamide (FBSA) with either 3' or standard RNA-seq to determine the advantages of each with regards to the identification of functionally enriched pathways. We found that 3' and standard RNA-seq showed specific advantages when focusing on annotated or unannotated regions of the genome. We also found that standard RNA-seq identified more differentially expressed genes (DEGs), but that this advantage disappeared under conditions of sparse data. We also found that standard RNA-seq had a significant advantage in identifying functionally enriched pathways via analysis of DEG lists but that this advantage was minimal when identifying pathways via gene set enrichment analysis of all genes. Conclusions: These results show that each approach has experimental conditions where they may be advantageous. Our observations can help guide others in the choice of 3' RNA-seq vs standard RNA sequencing to query gene expression levels in a range of biological systems.

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