Search

Nature Biotechnology asks a selection of researchers about the most exciting frontier in their field and the most needed technologies for advancing knowledge and applications.

Genome interpretation and analysis of allelic activity requires appropriate haplotype phasing. Here the authors present phASER, a fast and accurate method for variant phrasing from RNA-seq and genome sequencing data.

RNA sequencing of 465 human lymphoblastoid cell lines across seven European laboratories shows the feasibility of transcriptome sequencing for population-wide and cross-biobank studies.

Multiple transcriptome approaches, including single-cell sequencing, demonstrate that escape from X chromosome inactivation is widespread and occasionally variable between cells, chromosomes, and tissues, resulting in sex-biased expression of at least 60 genes and potentially contributing to sex-specific differences in health and disease.

To understand the contribution of variants to transcript expression regulation, long-read transcriptome data are generated from the GTEx resource, and a new software package to perform allele-specific analysis is developed.

Chronic obstructive pulmonary disease is a leading cause of morbidity and mortality. Here, the authors analyse whole genome sequence data and find new loci associated with lung function and COPD.

Epigenome-wide association studies (EWAS) are potentially powerful approaches for identifying transcriptional regulatory perturbations (particularly DNA methylation) that associate with phenotypes of interest. In this Opinion article, Lappalainen and Greally provide their views on how to maximize the interpretability and biological insights from these associations, such as by hypothesis-driven consideration of cellular phenotypes, characterizing the roles of transcription factors, dissecting directions of causality and moving towards multi-omics profiling.

Insight into the genetic influence on the immune response is important for the understanding of interindividual variability in human pathologies. Here, the authors generate transcriptome data from human blood monocytes stimulated with various immune stimuli and provide a time-resolved response eQTL map.

Sequencing and deep analysis of mRNA and miRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project reveal widespread genetic variation affecting the regulation of most genes, with transcript structure and expression level variation being equally common but genetically largely independent, and the analyses point to putative causal variants for dozens of disease-associated loci.

Samples of different body regions from hundreds of human donors are used to study how genetic variation influences gene expression levels in 44 disease-relevant tissues.

This report from the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations; hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites, can be found in each individual.

The genome of a western lowland gorilla has been sequenced and analysed, completing the genome sequences of all great ape genera, and providing evidence for parallel accelerated evolution in chimpanzee, gorilla and human lineages at a number of loci.

Molecular quantitative trait locus (molQTL) mapping associates genetic variation with molecular traits that can be measured as gene expression, splicing and chromatin accessibility. In this Primer, Aguet et al. discuss the study design and implementation of molQTL mapping in various applications, with a focus on technical developments for functional characterization.

Analysis of GTEx, cancer and autism data sets shows that cis-regulatory variation can modify the penetrance of coding variants. Deleterious coding variants on regulatory haplotypes resulting in high expression are enriched in disease cohorts and selected against in general populations.

Using the GTEx data and others, a comprehensive analysis of adenosine-to-inosine RNA editing in mammals is presented; targets of the various ADAR enzymes are identified, as are several potential regulators of editing, such as AIMP2.

The authors show that rare genetic variants contribute to large gene expression changes across diverse human tissues and provide an integrative method for interpretation of rare variants in individual genomes.

Structural variants in more than 17,000 human genomes are mapped and characterized using whole-genome sequencing, showing how this type of variation contributes to rare deleterious coding and noncoding alleles.

Phenotypic variation and diseases are influenced by factors such as genetic variants and gene expression. Here, Barbeira et al. develop S-PrediXcan to compute PrediXcan results using summary data, and investigate the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes.

Emmanouil Dermitzakis, Alfonso Buil and colleagues measure transcriptome-wide expression in a sample of twins to measure the relative contribution of genetic and environmental effects on allele-specific expression and find substantial effects of gene × gene and gene × environment interactions.

1000 Genomes imputation can increase the power of genome-wide association studies to detect genetic variants associated with human traits and diseases. Here, the authors develop a method to integrate and analyse low-coverage sequence data and SNP array data, and show that it improves imputation performance.

Results for the final phase of the 1000 Genomes Project are presented including whole-genome sequencing, targeted exome sequencing, and genotyping on high-density SNP arrays for 2,504 individuals across 26 populations, providing a global reference data set to support biomedical genetics.

The developmental Genotype-Tissue Expression (dGTEx) projects will catalogue and integrate gene expression, regulation and genetics data across 120 human donors from birth to adulthood with developmentally matched non-human primates, including 126 rhesus macaques and 72 common marmosets.

Uffelmann et al. describe the key considerations and best practices for conducting genome-wide association studies (GWAS), techniques for deriving functional inferences from the results and applications of GWAS in understanding disease risk and trait architecture. The Primer also provides information on the best practices for data sharing and discusses important ethical considerations when considering GWAS populations and data.