Quest for Orthologs in the Era of Biodiversity Genomics.

IF 3.2 2区 生物学 Q2 EVOLUTIONARY BIOLOGY
Felix Langschied, Nicola Bordin, Salvatore Cosentino, Diego Fuentes-Palacios, Natasha Glover, Michael Hiller, Yanhui Hu, Jaime Huerta-Cepas, Luis Pedro Coelho, Wataru Iwasaki, Sina Majidian, Saioa Manzano-Morales, Emma Persson, Thomas A Richards, Toni Gabaldón, Erik Sonnhammer, Paul D Thomas, Christophe Dessimoz, Ingo Ebersberger
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Abstract

The era of biodiversity genomics is characterized by large-scale genome sequencing efforts that aim to represent each living taxon with an assembled genome. Generating knowledge from this wealth of data has not kept up with this pace. We here discuss major challenges to integrating these novel genomes into a comprehensive functional and evolutionary network spanning the tree of life. In summary, the expanding datasets create a need for scalable gene annotation methods. To trace gene function across species, new methods must seek to increase the resolution of ortholog analyses, e.g. by extending analyses to the protein domain level and by accounting for alternative splicing. Additionally, the scope of orthology prediction should be pushed beyond well-investigated proteomes. This demands the development of specialized methods for the identification of orthologs to short proteins and noncoding RNAs and for the functional characterization of novel gene families. Furthermore, protein structures predicted by machine learning are now readily available, but this new information is yet to be integrated with orthology-based analyses. Finally, an increasing focus should be placed on making orthology assignments adhere to the findable, accessible, interoperable, and reusable (FAIR) principles. This fosters green bioinformatics by avoiding redundant computations and helps integrating diverse scientific communities sharing the need for comparative genetics and genomics information. It should also help with communicating orthology-related concepts in a format that is accessible to the public, to counteract existing misinformation about evolution.

在生物多样性基因组时代寻找同源物。
生物多样性基因组学时代的特点是大规模的基因组测序工作,其目的是用组装好的基因组代表每个生物类群。从这些丰富的数据中获取知识的速度跟不上这一步伐。我们在此讨论将这些新基因组整合到横跨生命树的综合功能和进化网络中面临的主要挑战。总之,不断扩大的数据集需要可扩展的基因注释方法。为了追踪跨物种的基因功能,新方法必须设法提高同源物分析的分辨率,例如通过将分析扩展到蛋白质结构域水平和考虑替代剪接。此外,应将同源物预测的范围扩大到已深入研究的蛋白质组之外。这就要求开发专门的方法来识别短蛋白和非编码 RNA 的同源物,并对新基因家族进行功能表征。此外,通过机器学习预测的蛋白质结构现在很容易获得,但这些新信息还需要与基于同源物的分析相结合。最后,应越来越重视使选集分配遵循 FAIR 原则。这可以避免冗余计算,从而促进绿色生物信息学的发展,并有助于整合对比较遗传学和基因组学信息有共同需求的不同科学界。它还有助于以公众易于理解的形式传播与选集相关的概念,以抵消现有的关于进化的错误信息。
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来源期刊
Genome Biology and Evolution
Genome Biology and Evolution EVOLUTIONARY BIOLOGY-GENETICS & HEREDITY
CiteScore
5.80
自引率
6.10%
发文量
169
审稿时长
1 months
期刊介绍: About the journal Genome Biology and Evolution (GBE) publishes leading original research at the interface between evolutionary biology and genomics. Papers considered for publication report novel evolutionary findings that concern natural genome diversity, population genomics, the structure, function, organisation and expression of genomes, comparative genomics, proteomics, and environmental genomic interactions. Major evolutionary insights from the fields of computational biology, structural biology, developmental biology, and cell biology are also considered, as are theoretical advances in the field of genome evolution. GBE’s scope embraces genome-wide evolutionary investigations at all taxonomic levels and for all forms of life — within populations or across domains. Its aims are to further the understanding of genomes in their evolutionary context and further the understanding of evolution from a genome-wide perspective.
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