Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

Understanding the genetic regulatory code that governs gene expression is a primary, yet challenging aspiration in molecular biology that opens up possibilities to cure human diseases and solve biotechnology problems. However, the fundamental question of how each of the individual coding and non-coding regions of the gene regulatory structure interact and contribute to the mRNA expression levels remains unanswered. Considering that all the information for gene expression regulation is already present in living cells, here we applied deep learning on over 20,000 mRNA datasets in 7 model organisms ranging from bacteria to Human. We show that in all organisms, mRNA abundance can be predicted directly from the DNA sequence with high accuracy, demonstrating that up to 82% of the variation of gene expression levels is encoded in the gene regulatory structure. Coding and non-coding regions carry both overlapping and orthogonal information and additively contribute to gene expression levels. By searching for DNA regulatory motifs present across the whole gene regulatory structure, we discover that motif interactions can regulate gene expression levels in a range of over three orders of magnitude. The uncovered co-evolution of coding and non-coding regions challenges the current paradigm that single motifs or regions are solely responsible for gene expression levels. Instead, we show that the correct combination of all regulatory regions must be established in order to accurately control gene expression levels. Therefore, the holistic system that spans the entire gene regulatory structure is required to analyse, understand, and design any future gene expression systems.

Human accelerated region 1 noncoding RNA is repressed by REST in Huntington's disease

In the neurons of Huntington's disease (HD) patients, gene regulatory networks are disrupted by aberrant nuclear localization of the master transcriptional repressor REST. Emerging evidence suggests that, in addition to protein-coding genes, noncoding RNAs (ncRNAs) may also contribute to neurodegenerative processes. To discover ncRNAs that are involved in HD, we screened genome-wide data for novel, noncoding targets of REST. This identified human accelerated region 1 (HAR1), a rapidly evolving cis-antisense locus that is specifically transcribed in the nervous system. We show that REST is targeted to the HAR1 locus by specific DNA regulatory motifs, resulting in potent transcriptional repression. Consistent with other REST target genes, HAR1 levels are significantly lower in the striatum of HD patients compared with unaffected individuals. These data represent further evidence that noncoding gene expression changes accompany neurodegeneration in Huntington's disease.