Integrative Proteogenomics for Differential Expression and Splicing Variation in a DM1 Mouse Model.

Dysregulated mRNA splicing is involved in the pathogenesis of many diseases including cancer, neurodegenerative diseases, and muscular dystrophies such as myotonic dystrophy type 1 (DM1). Comprehensive assessment of dysregulated splicing on the transcriptome and proteome level has been methodologically challenging, and thus investigations have often been targeting only few genes. Here, we performed a large-scale coordinated transcriptomic and proteomic analysis to characterize a DM1 mouse model (HSALR) in comparison to wild type. Our integrative proteogenomics approach comprised gene- and splicing-level assessments for mRNAs and proteins. It recapitulated many known instances of aberrant mRNA splicing in DM1 and identified new ones. It enabled the design and targeting of splicing-specific peptides and confirmed the translation of known instances of aberrantly spliced disease-related genes (e.g., Atp2a1, Bin1, Ryr1), complemented by novel findings (Flnc and Ywhae). Comparative analysis of large-scale mRNA and protein expression data showed quantitative agreement of differentially expressed genes and splicing patterns between disease and wild type. We hence propose this work as a suitable blueprint for a robust and scalable integrative proteogenomic strategy geared toward advancing our understanding of splicing-based disorders. With such a strategy, splicing-based biomarker candidates emerge as an attractive and accessible option, as they can be efficiently asserted on the mRNA and protein level in coordinated fashion.

Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters.

Identifying DNA cis-regulatory modules (CRMs) that control the expression of specific genes is crucial for deciphering the logic of transcriptional control. Natural genetic variation can point to the possible gene regulatory function of specific sequences through their allelic associations with gene expression. However, comprehensive identification of causal regulatory sequences in brute-force association testing without incorporating prior knowledge is challenging due to limited statistical power and effects of linkage disequilibrium. Sequence variants affecting transcription factor (TF) binding at CRMs have a strong potential to influence gene regulatory function, which provides a motivation for prioritizing such variants in association testing. Here, we generate an atlas of CRMs showing predicted allelic variation in TF binding affinity in human lymphoblastoid cell lines and test their association with the expression of their putative target genes inferred from Promoter Capture Hi-C and immediate linear proximity. We reveal >1300 CRM TF-binding variants associated with target gene expression, the majority of them undetected with standard association testing. A large proportion of CRMs showing associations with the expression of genes they contact in 3D localize to the promoter regions of other genes, supporting the notion of 'epromoters': dual-action CRMs with promoter and distal enhancer activity.

Integrated genome-scale analysis of the transcriptional regulatory landscape in a blood stem/progenitor cell model.

Comprehensive study of transcriptional control processes will be required to enhance our understanding of both normal and malignant hematopoiesis. Modern sequencing technologies have revolutionized our ability to generate genome-scale expression and histone modification profiles, transcription factor (TF)-binding maps, and also comprehensive chromatin-looping information. Many of these technologies, however, require large numbers of cells, and therefore cannot be applied to rare hematopoietic stem/progenitor cell (HSPC) populations. The stem cell factor-dependent multipotent progenitor cell line HPC-7 represents a well-recognized cell line model for HSPCs. Here we report genome-wide maps for 17 TFs, 3 histone modifications, DNase I hypersensitive sites, and high-resolution promoter-enhancer interactomes in HPC-7 cells. Integrated analysis of these complementary data sets revealed TF occupancy patterns of genomic regions involved in promoter-anchored loops. Moreover, preferential associations between pairs of TFs bound at either ends of chromatin loops led to the identification of 4 previously unrecognized protein-protein interactions between key blood stem cell regulators. All HPC-7 data sets are freely available both through standard repositories and a user-friendly Web interface. Together with previously generated genome-wide data sets, this study integrates HPC-7 data into a genomic resource on par with ENCODE tier 1 cell lines and, importantly, is the only current model with comprehensive genome-scale data that is relevant to HSPC biology.