Volume 54 Issue 3, March 2022

Would genetics research be a priority for Rwanda while the country was rebuilding just after the 1994 genocide against Tutsi? This was a question that I needed to consider. Sometimes, it is very hard to make the best choice for your career in a new scientific discipline when you have no role models and the only way forward is to start from scratch. Later, however, you can look back on what you have accomplished with surprise, and pride, when you see all your efforts paying off. Here I tell the story of my journey in genetics research, from rebuilding a country after trauma to facing our current COVID-19 pandemic challenges.

To build a more efficient, equitable and sustainable approach to rare disease research in the United States, we must prioritize integrated research infrastructure and approaches that focus on understanding connections across rare diseases.

A new study demonstrates that profiles of nascent RNA accurately predict genomic patterns of histone modifications and chromatin state. Consistent with that, active histone marks are revealed to reflect transcription activity, rather than preceding or directing gene output.

The gap between heritability estimates from twin studies and those from genotyping array data has puzzled researchers for over a decade. New research suggests that much of the ‘missing’ heritability is due to rare variants that can only be captured by whole-genome sequencing (WGS) data.

Chromosome-scale genome assembly of the South African bread wheat (Triticum aestivum) cultivar Kariega facilitates the cloning of the stripe rust resistance gene Yr27.

Genome-wide association analyses identify new susceptibility loci for Brugada syndrome. Functional studies implicate microtubule-related trafficking effects on sodium channel expression as an underlying molecular mechanism.

Analysis of whole-exome sequencing data from over 200,000 individuals in the UK Biobank provides new insights into the contribution of rare variants to cardiometabolic diseases and traits.

Colocalization of regulatory quantitative trait loci from the BLUEPRINT project with genetic association data aids fine-mapping of putative causal variants for 12 immune-mediated diseases.

Analysis of whole-genome sequences of 25,465 individuals of European ancestry shows that rare variants contribute substantially to the heritability of height and body mass index.

LAVA estimates multivariate local genetic relations, which enables conditional genetic analyses. Application to behavioral and health traits identifies local genetic heterogeneity and provides insights into genetic mediation and confounding.

Analysis of massively parallel reporter assays measuring the transcriptional activity of DNA sequences indicates that most transcription factor (TF) activity is additive and does not rely on specific TF–TF interactions. Individual TFs can have different gene regulatory activities.

A machine-learning tool can predict the distribution of histone post-translational modifications using nascent transcription data. Inhibiting transcription impacts H3K4me3, H3K27ac and H3K27me3 dynamics.

Allele-sensitive single-cell RNA sequencing analysis of long noncoding RNA (lncRNA) transcriptional kinetics shows that their lower expression compared to mRNA is due to lower burst frequencies and highlights cell-state-specific functions for several lncRNAs.

Totipotent cells in mouse embryos and 2-cell-like cells have slow DNA replication fork speed. Perturbations that slow replication fork speed promote 2-cell-like cell emergence and improve somatic cell nuclear transfer reprogramming and formation of induced pluripotent stem cell colonies.

Integrative analysis of single-cell RNA-sequencing datasets across mouse gastrulation and organogenesis identifies cell states and trajectories at successive developmental stages, along with transcription factors that could potentially mediate lineage choices.

Haplotype-resolved genome assembly of the tetraploid potato cultivar ‘Otava’ sheds light on functional organization of the tetraploid genome and provides the potential for genomics-assisted breeding.

GestaltMatcher uses a deep convolutional neural network to improve recognition of rare disorders based on facial morphology. The framework detects similarities among patients with previously unseen syndromes, aiding discovery of new disease genes.