TY - JOUR T1 - The Detection of Covariation of mRNA Levels of Large Sets of Genes across Multiple Human Populations JF - bioRxiv DO - 10.1101/082842 SP - 082842 AU - Yu Quan AU - Chao Xie AU - Rohan B. H. Williams AU - Peter Little Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/12/08/082842.abstract N2 - In this study we report that, measured in human lymphoblastoid cell lines (LCLs), different individuals exhibit correlated changes in the mRNA levels of multiple groups of genes; the largest group of genes such variation contains 2168 members and over 52% of all genes expressed in these cell lines are members of one or more groups. We show that these gene groups are replicable across different human populations and across different methods of analysis, supporting the view that the covariation is caused by biological and not experimental batch effects. This view is also supported by enrichment in the covarying genes of single and combinations of transcription factors (TFs) binding to cognate promoter regions, enrichment of genes shown to be sensitive to the knockdown of individual TFs and by enrichment of functional pathways and finally of protein-protein interactions. The properties of the groups of genes are therefore most readily explained by the influence of cumulative variations in the effectors of gene expression that act in trans on cognate genes. We suggest that covariation has functional outcomes by showing that covariation of 83 genes involved in the spliceosome pathway accounts for 21–43% of the variation in the alternative splicing patterns of genes expressed in human LCLs.Author Summary Enormous effort has gone into understanding the changes in gene expressions that underpin human disease and welfare and the research has been largely focused on the local genetic variations near and within genes that influence when and how much mRNA is made by the adjacent gene. In our study we focus on how variations in the many different proteins (and other molecules) that are involved in controlling genes might result in changes in a gene’s mRNA output. Because controlling proteins control multiple genes, we predict we should be able to observe the influence by looking for groups of, rather than single, genes that co-ordinately exhibit changes in amount of mRNA. Using a novel approach to detect co-ordinated changes of mRNA levels we identify large groups of genes that are apparently affected by the shared effect of changes in control. Some groups can contain thousands of genes and importantly many of these genes encode proteins that operate together to perform specific functions in cells. The simultaneous change of control of many genes involved in a given cell function is likely to have a more dramatic effect than changes of just a single gene. We report evidence that supports this view and defines for the first time sets of genes whose simultaneous change in control might explain some major differences between humans, including their health. ER -