Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
BMC Genomics. 2013 Jan 16;14:33. doi: 10.1186/1471-2164-14-33.
Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository.
In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony) demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences.
Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.
比较基因组学为序列进化提供了深入的了解,但通过将序列分析与基因功能和调控的实验测试相结合,可能会学到更多。然而,这种比较的可靠性通常受到表达条件的偏置采样和跨物种基因功能知识不完整的限制。为了解决这些挑战,我们之前曾系统地在酿酒酵母中生成表达谱,以最大限度地提高与现有酿酒酵母数据存储库相比的功能覆盖度。
在本文中,我们利用这两个数据存储库来比较各种条件下同源基因表达模式。首先,我们开发了一种可扩展的表达差异度量标准,使我们能够在全局水平上检测到序列和表达保守性之间的显著相关性,而之前较小规模的表达研究未能检测到这种相关性。尽管存在这种全局保守趋势,但种间基因表达邻域的保守程度不如不同环境扰动下的种内比较,并且约有 4%的同源基因表现出共表达伙伴的显著变化。此外,我们对两种物种中收集的匹配扰动(如双相转变和细胞周期同步)进行的分析表明,约四分之一的同源基因表现出特定条件下表达模式的差异。
总之,这些分析提供了两种物种之间基因表达模式的全局视图,包括基因表达的条件和时间以及共表达伙伴。我们的结果提供了可测试的假设,这些假设将指导未来的实验确定这些变化如何在基因组中指定。