Recognition of the polycistronic nature of human genes is critical to understanding the genotype-phenotype relationship.
Recognition of the polycistronic nature of human genes is critical to understanding the genotype-phenotype relationship.
复制标题
DOI:
10.1101/gr.230938.117
复制
发表时间:
2018-05
期刊:
影响因子:
7
通讯作者:
Roucou X
中科院分区:
文献类型:
--
作者:
Brunet MA;Levesque SA;Hunting DJ;Cohen AA;Roucou X
Technological advances promise unprecedented opportunities for whole exome sequencing and proteomic analyses of populations. Currently, data from genome and exome sequencing or proteomic studies are searched against reference genome annotations. This provides the foundation for research and clinical screening for genetic causes of pathologies. However, current genome annotations substantially underestimate the proteomic information encoded within a gene. Numerous studies have now demonstrated the expression and function of alternative (mainly small, sometimes overlapping) ORFs within mature gene transcripts. This has important consequences for the correlation of phenotypes and genotypes. Most alternative ORFs are not yet annotated because of a lack of evidence, and this absence from databases precludes their detection by standard proteomic methods, such as mass spectrometry. Here, we demonstrate how current approaches tend to overlook alternative ORFs, hindering the discovery of new genetic drivers and fundamental research. We discuss available tools and techniques to improve identification of proteins from alternative ORFs and finally suggest a novel annotation system to permit a more complete representation of the transcriptomic and proteomic information contained within a gene. Given the crucial challenge of distinguishing functional ORFs from random ones, the suggested pipeline emphasizes both experimental data and conservation signatures. The addition of alternative ORFs in databases will render identification less serendipitous and advance the pace of research and genomic knowledge. This review highlights the urgent medical and research need to incorporate alternative ORFs in current genome annotations and thus permit their inclusion in hypotheses and models, which relate phenotypes and genotypes.
登录
查看更多内容
影响因子:
7.7
作者:
Andreev DE;O'Connor PB;Fahey C;Kenny EM;Terenin IM;Dmitriev SE;Cormican P;Morris DW;Shatsky IN;Baranov PV
通讯作者:
Baranov PV
DOI:
10.1038/nrm4069
发表时间:
2015-11
期刊:
Nature reviews. Molecular cell biology
影响因子:
--
作者:
Brar GA;Weissman JS
通讯作者:
Weissman JS
影响因子:
4
作者:
Bertrand C;Valet P;Castan-Laurell I
通讯作者:
Castan-Laurell I
影响因子:
3
作者:
Shihab HA;Rogers MF;Ferlaino M;Campbell C;Gaunt TR
通讯作者:
Gaunt TR
DOI:
10.1073/pnas.0308758101
发表时间:
2004-06-01
影响因子:
11.1
作者:
Abramowitz, J;Grenet, D;Birnbaumer, L
通讯作者:
Birnbaumer, L