Evidence for exon shuffling is sensitive to model choice.

IF 0.9 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Xiaoyue Cui, Maureen Stolzer, Dannie Durand
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引用次数: 0

Abstract

The exon shuffling theory posits that intronic recombination creates new domain combinations, facilitating the evolution of novel protein function. This theory predicts that introns will be preferentially situated near domain boundaries. Many studies have sought evidence for exon shuffling by testing the correspondence between introns and domain boundaries against chance intron positioning. Here, we present an empirical investigation of how the choice of null model influences significance. Although genome-wide studies have used a uniform null model, exclusively, more realistic null models have been proposed for single gene studies. We extended these models for genome-wide analyses and applied them to 21 metazoan and fungal genomes. Our results show that compared with the other two models, the uniform model does not recapitulate genuine exon lengths, dramatically underestimates the probability of chance agreement, and overestimates the significance of intron-domain correspondence by as much as 100 orders of magnitude. Model choice had much greater impact on the assessment of exon shuffling in fungal genomes than in metazoa, leading to different evolutionary conclusions in seven of the 16 fungal genomes tested. Genome-wide studies that use this overly permissive null model may exaggerate the importance of exon shuffling as a general mechanism of multidomain evolution.

外显子洗牌的证据对模型选择很敏感。
外显子改组理论认为内含子重组创造了新的结构域组合,促进了新的蛋白质功能的进化。该理论预测内含子将优先位于区域边界附近。许多研究通过测试内含子和结构域边界之间的对应关系来寻找外显子洗牌的证据,以防止内含子偶然定位。在这里,我们提出了零模型的选择如何影响显著性的实证调查。虽然全基因组研究使用了统一的零模型,但对于单基因研究,已经提出了更现实的零模型。我们将这些模型扩展到全基因组分析,并将其应用于21个后生动物和真菌基因组。我们的研究结果表明,与其他两种模型相比,统一模型没有概括出真实的外显子长度,严重低估了偶然一致的概率,并且高估了内含子域对应的重要性,高达100个数量级。与后生动物相比,模型选择对真菌基因组外显子洗选的影响要大得多,这导致16个真菌基因组中有7个得出了不同的进化结论。使用这种过于宽松的零模型的全基因组研究可能夸大了外显子洗牌作为多域进化的一般机制的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Bioinformatics and Computational Biology
Journal of Bioinformatics and Computational Biology MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
2.10
自引率
0.00%
发文量
57
期刊介绍: The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information. The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.
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