Evaluating and improving heritability models using summary statistics | Nature Genetics
There is currently much debate regarding the best model for how heritability varies across the genome. Here researchers provide a statistical framework for assessing heritability models using summary statistics from genome-wide association studies.
Obstacles to detecting isoforms using full-length scRNA-seq data | Genome Biology
Early single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched bulk RNA-seq samples. However, these studies generally did not consider the impact of dropouts or isoform quantification errors, potentially confounding the results of these analyses. In this study, researchers take a simulation based approach in which they explicitly account for dropouts and isoform quantification errors. They find that the high rate of dropouts associated with scRNA-seq is a major obstacle to studying alternative splicing.
Modeling the complex genetic architectures of brain disease | Nature Genetics
The genetic architecture of each individual comprises common and rare variants that, acting alone and in combination, confer risk of disease. The cell-type-specific and/or context-dependent functional consequences of the risk variants linked to brain disease must be resolved. The authors discuss advances at the intersection of genomics, human induced pluripotent stem cells (hiPSC) and CRISPR. A better understanding of the molecular mechanisms underlying disease risk will improve genetic diagnosis, drive phenotypic drug discovery and pave the way toward precision medicine.