Keel Brittney N, Lindholm-Perry Amanda K
USDA-ARS, Roman L. Hruska U.S. Meat Animal Research Center, Clay Center, NE, United States.
Front Genet. 2022 Sep 19;13:983043. doi: 10.3389/fgene.2022.983043. eCollection 2022.
Decreases in the costs of high-throughput sequencing technologies have led to continually increasing numbers of livestock RNA-Seq studies in the last decade. Although the number of studies has increased dramatically, most livestock RNA-Seq experiments are limited by cost to a small number of biological replicates. Meta-analysis procedures can be used to integrate and jointly analyze data from multiple independent studies. Meta-analyses increase the sample size, which in turn increase both statistical power and robustness of the results. In this work, we discuss cutting edge approaches to combining results from multiple independent RNA-Seq studies to improve livestock transcriptomics research. We review currently published RNA-Seq meta-analyses in livestock, describe many of the key issues specific to RNA-Seq meta-analysis in livestock species, and discuss future perspectives.
在过去十年中，高通量测序技术成本的降低使得家畜RNA测序研究的数量持续增加。尽管研究数量大幅增长，但大多数家畜RNA测序实验因成本限制，只能进行少量生物学重复。荟萃分析程序可用于整合和联合分析来自多个独立研究的数据。荟萃分析增加了样本量，进而提高了统计效力和结果的稳健性。在这项工作中，我们讨论了结合多个独立RNA测序研究结果以改进家畜转录组学研究的前沿方法。我们回顾了目前已发表的家畜RNA测序荟萃分析，描述了家畜物种RNA测序荟萃分析特有的许多关键问题，并探讨了未来展望。
