Center for Comparative Genomics and Bioinformatics, Pennsylvania State University, University Park, PA 16802 USA.
BMC Evol Biol. 2011 Jul 28;11:226. doi: 10.1186/1471-2148-11-226.
Gene clusters containing multiple similar genomic regions in close proximity are of great interest for biomedical studies because of their associations with inherited diseases. However, such regions are difficult to analyze due to their structural complexity and their complicated evolutionary histories, reflecting a variety of large-scale mutational events. In particular, conversion events can mislead inferences about the relationships among these regions, as traced by traditional methods such as construction of phylogenetic trees or multi-species alignments.
To correct the distorted information generated by such methods, we have developed an automated pipeline called CHAP (Cluster History Analysis Package) for detecting conversion events. We used this pipeline to analyze the conversion events that affected two well-studied gene clusters (α-globin and β-globin) and three gene clusters for which comparative sequence data were generated from seven primate species: CCL (chemokine ligand), IFN (interferon), and CYP2abf (part of cytochrome P450 family 2). CHAP is freely available at http://www.bx.psu.edu/miller_lab.
These studies reveal the value of characterizing conversion events in the context of studying gene clusters in complex genomes.
由于与遗传性疾病有关,包含多个相似基因组区域的基因簇,引起了生物医学研究的极大兴趣。然而,由于其结构复杂性和复杂的进化历史,反映了各种大规模突变事件,这些区域很难进行分析。特别是,转换事件可能会误导通过构建系统发育树或多物种比对等传统方法追踪这些区域之间关系的推断。
为了纠正此类方法产生的扭曲信息,我们开发了一种名为 CHAP(Cluster History Analysis Package)的自动分析流水线,用于检测转换事件。我们使用该流水线分析了影响两个研究良好的基因簇(α-球蛋白和β-球蛋白)以及三个基因簇的转换事件,这些基因簇的比较序列数据来自七个灵长类物种:CCL(趋化因子配体)、IFN(干扰素)和 CYP2abf(细胞色素 P450 家族 2 的一部分)。CHAP 可在 http://www.bx.psu.edu/miller_lab 上免费获得。
这些研究揭示了在复杂基因组中研究基因簇时,描述转换事件的价值。