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SUMMARYThe early limb bud consists of mesenchymal progenitors (limb progenitors) derived from the lateral plate mesoderm (LPM) that produce most of the tissues of the mature limb bud. The LPM also gives rise to the mesodermal components of the trunk, flank and neck. However, the mesenchymal cells generated at these other axial levels cannot produce the variety of cell types found in the limb bud, nor can they be directed to form a patterned appendage-like structure, even when placed in the context of the signals responsible for organizing the limb bud. Here, by taking advantage of a direct reprogramming approach, we find a set of factors (Prdm16, Zbtb16, and Lin28) normally expressed in the early limb bud, that are capable of imparting limb progenitor-like properties to non-limb fibroblasts. Cells reprogrammed by these factors show similar gene expression profiles, and can differentiate into similar cell types, as endogenous limb progenitors. The further addition of Lin41 potentiates proliferation of the reprogrammed cells while suppressing differentiation. These results suggest that these same four key factors may play pivotal roles in the specification of endogenous limb progenitors.

MotivationDe novo variant (DNV) calling typically relies on heuristic filters intrinsic to specific platforms and variant calling algorithms. FreeBayes and neural network approaches have overcome this limitation for variant calling, and we implemented a similar approach for DNV identification.ResultsWe developed a DNV calling framework that uses Genome Analysis Toolkit (GATK), FreeBayes and a neural network trained on Integrative Genomics Viewer pile-up plots (IGV-bot). We identified DNVs in 2,390 WGS trios and benchmarked results against heuristics based on GATK parameters. Results were validated in silico and with Sanger sequencing, with the latter showing true positive rates of 98.4% and 97.3% for SNVs and indels, respectively. Taken together we describe a scalable framework for DNV identification based on both FreeBayes and neural network methods.AvailabilitySource code and documentation are available at https://github.com/ShenLab/igv-classifier and https://github.com/frichter/dnv_pipeline under the MIT license.Contactys2411@cumc.columbia.edu

BackgroundThe contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined.ResultsWe developed a computational method, Expectation-Maximization-based detection of Mosaicism (EM-mosaic), to analyze mosaicism in exome sequences of 2530 CHD proband-parent trios. EM-mosaic detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The frequency of mosaic variants above 10% mosaicism was 0.13/person in blood and 0.14/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction.ConclusionsWe estimate that ~1% of CHD probands have a mosaic variant detectable in blood that could contribute to cardiac malformations, particularly those damaging variants expressed at higher allele fraction compared to benign variants. Although blood is a readily-available DNA source, cardiac tissues analyzed contributed ~5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses.

and KeywordsBackgroundSex differences exist in the prevalence, presentation, and outcomes of ischemic heart disease. Females have higher risk of heart failure post myocardial infarction relative to males and the female sex is an independent risk factor for hospital and operative mortality after cardiac surgery. However, the mechanisms underlying this sexual dimorphism remain unclear. We examined sex differences in human myocardial gene expression in response to ischemia.MethodsLeft ventricular biopsies from 68 male and 46 female patients undergoing aortic valve replacement surgery were obtained at baseline and after a median 74 minutes of cold cardioplegic arrest/ischemia and respective transcriptomes were quantified by RNA-Seq. Sex-specific responses to ischemia were quantified by differential gene expression, expression quantitative trait loci (eQTL) and pathway and functional analysis. Cell-type enrichment analysis. was used to obtain an estimate of the identity and relative proportions of different cell types present in each sample.ResultsA sex-specific response to ischemia was observed for 271 genes. Functional annotation analysis revealed sex-specific modulation of the oxytocin signaling pathway and common pathway of fibrin clot formation. The eQTL analysis identified variant-by-sex interaction eQTLs at baseline and post-ischemia, indicative of sex differences in the genotypic effects on gene expression, and cell-type enrichment analysis showed sex-bias in proportion of specific cell types.ConclusionIn response to myocardial ischemia, the human left ventricle demonstrates changes in gene expression that differ between the sexes. These differences provide insight into the sexual dimorphism of ischemic heart disease and may aid in the development of sex-specific therapies that reduce myocardial injury.