Accelerating Biological Insight for Understudied Genes
Accelerating Biological Insight for Understudied Genes
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DOI：
10.1093/icb/icab029
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发表时间：
2022-02-05
影响因子：
2.6
通讯作者：
Settles，A. Mark
中科院分区：
文献类型：
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作者：
Reynolds，Kimberly A.;Rosa-Molinar，Eduardo;Settles，A. Mark
基因组序列数据的快速扩展增加了对所有生命领域的蛋白质编码基因的发现。用可靠的功能信息注释这些基因对于理解进化、定义自然界所能获得的完整生化空间以及确定生物技术改进的靶基因是必要的。大多数蛋白质是基于序列保守的注释，没有特定的生物、生化、遗传或细胞功能。整个生物科学领域的最新技术进步使得在更广泛的物种集合中对这些未被充分研究的蛋白质编码基因进行实验研究成为可能。然而，科学家们有动机和偏见继续关注他们首选的模式生物中有充分记录的基因。这一观点提出了一种研究模式，旨在通过使跨学科团队加速生物学功能注释来打破研究偏见的历史孤岛。我们提出一项倡议，发展合作的进化生物学家，细胞生物学家，遗传学家和生物化学家的协调项目，将重点放在多个模式生物的靶基因亚群上。对多种生物进行同步分析利用了进化分化和选择的优势，这使得单个物种更适合作为特定基因的实验模型。最重要的是，多系统方法将鼓励跨学科的批判性思维和假设检验，这在当前的生物学研究中是固有的缓慢。
The rapid expansion of genome sequence data is increasing the discovery of protein-coding genes across all domains of life. Annotating these genes with reliable functional information is necessary to understand evolution, to define the full biochemical space accessed by nature, and to identify target genes for biotechnology improvements. The majority of proteins are annotated based on sequence conservation with no specific biological, biochemical, genetic, or cellular function identified. Recent technical advances throughout the biological sciences enable experimental research on these understudied protein-coding genes in a broader collection of species. However, scientists have incentives and biases to continue focusing on well documented genes within their preferred model organism. This perspective suggests a research model that seeks to break historic silos of research bias by enabling interdisciplinary teams to accelerate biological functional annotation. We propose an initiative to develop coordinated projects of collaborating evolutionary biologists, cell biologists, geneticists, and biochemists that will focus on subsets of target genes in multiple model organisms. Concurrent analysis in multiple organisms takes advantage of evolutionary divergence and selection, which causes individual species to be better suited as experimental models for specific genes. Most importantly, multisystem approaches would encourage transdisciplinary critical thinking and hypothesis testing that is inherently slow in current biological research.