Allele-specific expression reveals genetic drivers of tissue regeneration in mice.

In adult mammals, skin wounds typically heal by scarring rather than through regeneration. In contrast, "super-healer" Murphy Roths Large (MRL) mice have the unusual ability to regenerate ear punch wounds; however, the molecular basis for this regeneration remains elusive. Here, in hybrid crosses between MRL and non-regenerating mice, we used allele-specific gene expression to identify cis-regulatory variation associated with ear regeneration.

Color Data v2: a user-friendly, open-access database with hereditary cancer and hereditary cardiovascular conditions datasets.

Publicly available genetic databases promote data sharing and fuel scientific discoveries for the prevention, treatment and management of disease. In 2018, we built Color Data, a user-friendly, open access database containing genotypic and self-reported phenotypic information from 50 000 individuals who were sequenced for 30 genes associated with hereditary cancer. In a continued effort to promote access to these types of data, we launched Color Data v2, an updated version of the Color Data database.

Single-cell transcriptional diversity is a hallmark of developmental potential.

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation is challenging. Here, we demonstrate a simple, yet robust, determinant of developmental potential-the number of expressed genes per cell-and leverage this measure of transcriptional diversity to develop a computational framework (CytoTRACE) for predicting differentiation states from scRNA-seq data.

Independent erosion of conserved transcription factor binding sites points to shared hindlimb, vision and external testes loss in different mammals.

Genetic variation in cis-regulatory elements is thought to be a major driving force in morphological and physiological changes. However, identifying transcription factor binding events that code for complex traits remains a challenge, motivating novel means of detecting putatively important binding events. Using a curated set of 1154 high-quality transcription factor motifs, we demonstrate that independently eroded binding sites are enriched for independently lost traits in three distinct pairs of placental mammals.

M-CAP eliminates a majority of variants of uncertain significance in clinical exomes at high sensitivity.

Variant pathogenicity classifiers such as SIFT, PolyPhen-2, CADD, and MetaLR assist in interpretation of the hundreds of rare, missense variants in the typical patient genome by deprioritizing some variants as likely benign. These widely used methods misclassify 26 to 38% of known pathogenic mutations, which could lead to missed diagnoses if the classifiers are trusted as definitive in a clinical setting. We developed M-CAP, a clinical pathogenicity classifier that outperforms existing methods at all thresholds and correctly dismisses 60% of rare, missense variants of uncertain significance in a typical genome at 95% sensitivity.