RNA sequencing reveals two major classes of gene expression levels in metazoan cells

The expression level of a gene is often used as a proxy for determining whether the protein or RNA product is functional in a cell or tissue. Therefore, it is of fundamental importance to understand the global distribution of gene expression levels, and to be able to interpret it mechanistically and functionally. Here we use RNA sequencing (RNA‐seq) of mouse Th2 cells, coupled with a range of other techniques, to show that all genes can be separated, based on their expression abundance, into two distinct groups: one group comprised of lowly expressed and putatively non‐functional mRNAs, and the other of highly expressed mRNAs with active chromatin marks at their promoters. These observations are confirmed in many other microarray and RNA‐seq data sets of metazoan cell types.     

Basic helix-loop-helix transcription factor gene family phylogenetics and nomenclature

A phylogenetic analysis of the basic helix-loop-helix (bHLH) gene superfamily was performed using seven different species (human, mouse, rat, worm, fly, yeast, and plant Arabidopsis) and involving over 600 bHLH genes ( Stevens et al., 2008). All bHLH genes were identified in the genomes of the various species, including expressed sequence tags, and the entire coding sequence was used in the analysis. Nearly 15% of the gene family has been updated or added since the original publication. A super-tree involving six clades and all structural relationships was established and is now presented for four of the species. The wealth of functional data available for members of the bHLH gene superfamily provides us with the opportunity to use this exhaustive phylogenetic tree to predict potential functions of uncharacterized members of the family. This phylogenetic and genomic analysis of the bHLH gene family has revealed unique elements of the evolution and functional relationships of the different genes in the bHLH gene family.     

Functional coordination between transcription factor clustering and gene activity

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