Walhout Albertha J M, Reboul Jérôme, Shtanko Olena, Bertin Nicolas, Vaglio Philippe, Ge Hui, Lee Hongmei, Doucette-Stamm Lynn, Gunsalus Kristin C, Schetter Aaron J, Morton Diane G, Kemphues Kenneth J, Reinke Valerie, Kim Stuart K, Piano Fabio, Vidal Marc
Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
Curr Biol. 2002 Nov 19;12(22):1952-8. doi: 10.1016/s0960-9822(02)01279-4.
By integrating functional genomic and proteomic mapping approaches, biological hypotheses should be formulated with increasing levels of confidence. For example, yeast interactome and transcriptome data can be correlated in biologically meaningful ways. Here, we combine interactome mapping data generated for a multicellular organism with data from both large-scale phenotypic analysis ("phenome mapping") and transcriptome profiling. First, we generated a two-hybrid interactome map of the Caenorhabditis elegans germline by using 600 transcripts enriched in this tissue. We compared this map to a phenome map of the germline obtained by RNA interference (RNAi) and to a transcriptome map obtained by clustering worm genes across 553 expression profiling experiments. In this dataset, we find that essential proteins have a tendency to interact with each other, that pairs of genes encoding interacting proteins tend to exhibit similar expression profiles, and that, for approximately 24% of germline interactions, both partners show overlapping embryonic lethal or high incidence of males RNAi phenotypes and similar expression profiles. We propose that these interactions are most likely to be relevant to germline biology. Similar integration of interactome, phenome, and transcriptome data should be possible for other biological processes in the nematode and for other organisms, including humans.
通过整合功能基因组学和蛋白质组学图谱绘制方法，生物学假设应以越来越高的可信度来构建。例如，酵母相互作用组和转录组数据可以通过具有生物学意义的方式进行关联。在此，我们将为多细胞生物生成的相互作用组图谱数据与来自大规模表型分析（“表型组图谱绘制”）和转录组分析的数据相结合。首先，我们利用在该组织中富集 的600个转录本生成了秀丽隐杆线虫生殖系的双杂交相互作用组图谱。我们将此图谱与通过RNA干扰（RNAi）获得 的生殖系表型组图谱以及通过对553个表达谱实验中的线虫基因进行聚类获得的转录组图谱进行了比较。在这个数据集中，我们发现必需蛋白倾向于相互作用，编码相互作用蛋白的基因对倾向于表现出相似的表达谱 ；并且对于大约24%的生殖系相互作用，双方都表现出重叠的胚胎致死或雄性RNAi表型的高发生率以及相似的表达谱 。我们提出这些相互作用最有可能与生殖系生物学相关 。线虫中其他生物学过程以及包括人类在内的其他生物类似地整合相互作用组、表型组和转录组数据应该也是可行的。
