Dynamics of cardiomyocyte transcriptome and chromatin landscape demarcates key events of heart development.

Organogenesis involves dynamic regulation of gene transcription and complex multipathway interactions. Despite our knowledge of key factors regulating various steps of heart morphogenesis, considerable challenges in understanding its mechanism still exist because little is known about their downstream targets and interactive regulatory network. To better understand transcriptional regulatory mechanism driving heart development and the consequences of its disruption in vivo, we performed time-series analyses of the transcriptome and genome-wide chromatin accessibility in isolated cardiomyocytes (CMs) from wild-type zebrafish embryos at developmental stages corresponding to heart tube morphogenesis, looping, and maturation. We identified genetic regulatory modules driving crucial events of heart development that contained key cardiac TFs and are associated with open chromatin regions enriched for DNA sequence motifs belonging to the family of the corresponding TFs. Loss of function of cardiac TFs Gata5, Tbx5a, and Hand2 affected the cardiac regulatory networks and caused global changes in chromatin accessibility profile, indicating their role in heart development. Among regions with differential chromatin accessibility in mutants were highly conserved noncoding elements that represent putative enhancers driving heart development. The most prominent gene expression changes, which correlated with chromatin accessibility modifications within their proximal promoter regions, occurred between heart tube morphogenesis and looping, and were associated with metabolic shift and hematopoietic/cardiac fate switch during CM maturation. Our results revealed the dynamic regulatory landscape throughout heart development and identified interactive molecular networks driving key events of heart morphogenesis.

SONiCS: PCR stutter noise correction in genome-scale microsatellites.

Motivation: Massively parallel capture of short tandem repeats (STRs, or microsatellites) provides a strategy for population genomic and demographic analyses at high resolution with or without a reference genome. However, the high Polymerase Chain Reaction (PCR) cycle numbers needed for target capture experiments create genotyping noise through polymerase slippage known as PCR stutter. Results: We developed SONiCS-Stutter mONte Carlo Simulation-a solution for stutter correction based on dense forward simulations of PCR and capture experimental conditions. To test SONiCS, we genotyped a 2499-marker STR panel in 22 humpback dolphins (Sousa sahulensis) using target capture, and generated capillary-based genotypes to validate five of these markers. In these 110 comparisons, SONiCS showed a 99.1% accuracy rate and a 98.2% genotyping success rate, miscalling a single allele in a marker with low sequence coverage and rejecting another as un-callable. Availability and implementation: Source code and documentation for SONiCS is freely available at https://github.com/kzkedzierska/sonics. Raw read data used in experimental validation of SONiCS have been deposited in the Sequence Read Archive under accession number SRP135756. Supplementary information: Supplementary data are available at Bioinformatics online.

Genomic analysis of DNA repair genes and androgen signaling in prostate cancer.

BACKGROUND: The cellular effects of androgen are transduced through the androgen receptor, which controls the expression of genes that regulate biosynthetic processes, cell growth, and metabolism. Androgen signaling also impacts DNA damage signaling through mechanisms involving gene expression and transcription-associated DNA damaging events. Defining the contributions of androgen signaling to DNA repair is important for understanding androgen receptor function, and it also has translational implications. METHODS: We generated RNA-seq data from multiple prostate cancer lines and used bioinformatic analyses to characterize androgen-regulated gene expression. We compared the results from cell lines with gene expression data from prostate cancer xenografts, and patient samples, to query how androgen signaling and prostate cancer progression influences the expression of DNA repair genes. We performed whole genome sequencing to help characterize the status of the DNA repair machinery in widely used prostate cancer lines. Finally, we tested a DNA repair enzyme inhibitor for effects on androgen-dependent transcription. RESULTS: Our data indicates that androgen signaling regulates a subset of DNA repair genes that are largely specific to the respective model system and disease state. We identified deleterious mutations in the DNA repair genes RAD50 and CHEK2. We found that inhibition of the DNA repair enzyme MRE11 with the small molecule mirin inhibits androgen-dependent transcription and growth of prostate cancer cells. CONCLUSIONS: Our data supports the view that crosstalk between androgen signaling and DNA repair occurs at multiple levels, and that DNA repair enzymes in addition to PARPs, could be actionable targets in prostate cancer.