Atias Nir, Kupiec Martin, Sharan Roded
Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.
Department of Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv 69978, Israel
Nucleic Acids Res. 2016 Mar 18;44(5):e50. doi: 10.1093/nar/gkv1284. Epub 2015 Nov 23.
The yeast mutant collections are a fundamental tool in deciphering genomic organization and function. Over the last decade, they have been used for the systematic exploration of ∼6 000 000 double gene mutants, identifying and cataloging genetic interactions among them. Here we studied the extent to which these data are prone to neighboring gene effects (NGEs), a phenomenon by which the deletion of a gene affects the expression of adjacent genes along the genome. Analyzing ∼90,000 negative genetic interactions observed to date, we found that more than 10% of them are incorrectly annotated due to NGEs. We developed a novel algorithm, GINGER, to identify and correct erroneous interaction annotations. We validated the algorithm using a comparative analysis of interactions from Schizosaccharomyces pombe. We further showed that our predictions are significantly more concordant with diverse biological data compared to their mis-annotated counterparts. Our work uncovered about 9500 new genetic interactions in yeast.
酵母突变体库是解读基因组组织和功能的一项基本工具。在过去十年中,它们被用于对约600万个双基因突变体进行系统探索,识别并编目其中的基因相互作用。在此,我们研究了这些数据在多大程度上容易受到邻近基因效应(NGEs)的影响,这是一种基因缺失会影响基因组中相邻基因表达的现象。分析迄今观察到的约90000个负向基因相互作用,我们发现其中超过10%因邻近基因效应而被错误注释。我们开发了一种新算法GINGER,以识别并纠正错误的相互作用注释。我们通过对粟酒裂殖酵母相互作用的比较分析验证了该算法。我们进一步表明,与错误注释的结果相比,我们的预测与多种生物学数据的一致性显著更高。我们的研究在酵母中发现了约9500个新的基因相互作用。