Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
OMICS. 2021 Nov;25(11):681-692. doi: 10.1089/omi.2021.0160. Epub 2021 Oct 22.
Multiomics study designs have significantly increased understanding of complex biological systems. The multiomics literature is rapidly expanding and so is their heterogeneity. However, the intricacy and fragmentation of omics data are impeding further research. To examine current trends in multiomics field, we reviewed 52 articles from PubMed and Web of Science, which used an integrated omics approach, published between March 2006 and January 2021. From studies, data regarding investigated loci, species, omics type, and phenotype were extracted, curated, and streamlined according to standardized terminology, and summarized in a previously developed graphical summary. Evaluated studies included 21 omics types or applications of omics technology such as genomics, transcriptomics, metabolomics, epigenomics, environmental omics, and pharmacogenomics, species of various phyla including human, mouse, , , and various phenotypes, including cancer and COVID-19. In the analyzed studies, diverse methods, protocols, results, and terminology were used and accordingly, assessment of the studies was challenging. Adoption of standardized multiomics data presentation in the future will further buttress standardization of terminology and reporting of results in systems science. This shall catalyze, we suggest, innovation in both science communication and laboratory medicine by making available scientific knowledge that is easier to grasp, share, and harness toward medical breakthroughs.
多组学研究设计大大提高了对复杂生物系统的理解。多组学文献正在迅速扩展,其异质性也在增加。然而,组学数据的复杂性和碎片化阻碍了进一步的研究。为了研究多组学领域的当前趋势,我们回顾了 2006 年 3 月至 2021 年 1 月期间在 PubMed 和 Web of Science 上发表的 52 篇使用综合组学方法的文章。从这些研究中,提取了关于研究位点、物种、组学类型和表型的数据,并根据标准化术语进行了整理和简化,并总结在之前开发的图形摘要中。评估的研究包括 21 种组学类型或组学技术的应用,如基因组学、转录组学、代谢组学、表观基因组学、环境组学和药物基因组学,以及包括人类、小鼠、、、等在内的各个门的物种,以及各种表型,包括癌症和 COVID-19。在分析的研究中,使用了各种方法、方案、结果和术语,因此评估研究具有挑战性。未来采用标准化的多组学数据呈现方式将进一步支持系统科学中术语和结果报告的标准化。我们建议,这将促进科学传播和实验室医学的创新,使更容易理解、共享和利用的科学知识朝着医学突破的方向发展。