Volume 55 Issue 12, December 2023

The preparedness of Africa for genomic medicine remains a matter of debate because this question is always evaluated from a technological standpoint. Yet the resilience of African researchers and the cultural values of equity and fairness are important assets to be considered in planning for the future of genomic medicine in Africa.

Deep learning shows promise for predicting gene expression levels from DNA sequences. However, recent studies show that current state-of-the-art models struggle to accurately characterize expression variation from personal genomes, limiting their usefulness in personalized medicine.

The pancreas is an essential organ present in all vertebrates, and human pancreatic agenesis is an extremely rare disorder of largely unknown genetic determinants. A study now demonstrates that a primate-specific regulatory network controlled by the KRAB zinc-finger protein ZNF808 is essential for pancreas development.

Variants in the HLA region on chromosome 6 are strongly associated with many immune-related diseases. A method to construct personalized HLA genomes from single-cell RNA sequencing data, coupled with single-cell HLA expression quantitative trait loci modeling, identifies how genetic variants influence HLA gene expression across cell states.

EasySci, a scalable single-cell profiling technique, uncovered over 300 mammalian brain cell states, revealing molecular features and dynamics of rare cell states linked to aging and Alzheimer’s disease. This work offers insights into cell states that expand (rare astrocytes and vascular leptomeningeal cells in the olfactory bulb, reactive microglia, and oligodendrocytes) or are depleted (neuronal progenitors, neuroblasts and committed oligodendrocyte precursors) during normal and pathological aging.

Whole-genome sequencing data of individuals from the UK Biobank and Iceland and a somatic mutation barcoding strategy enabled detection of clonal hematopoiesis at scale. This comprehensive study provides insights into the epidemiology, somatic and germline genetics, and disease associations of clonal hematopoiesis.

We present an analysis that shows that although nearly half of the human genome comprises repetitive sequences, recombination between homologous repeats has a minor role in cancer chromosomal evolution.

We present a model to predict the chance of each possible de novo mutation in the human genome informed by recent insights into determinants of mutagenesis. Predictions were applied to refine demographic models, identify constrained genes, and uncover mutagenic effects of polymerase III transcription and transcription factor binding in testis.

Combined analysis of genome-wide association studies and epigenetic data has identified certain immune cell types as drivers of autoimmune disease, but current methods have not been able to pinpoint key effector immune cell states. Using single-cell data from inflammatory tissues, we identified effector cell states embedded within inflammatory tissues — including T peripheral helper cells and tissue regulatory T cells — that capture disproportionate disease heritability.

Previous studies reported an effect of N⁶-methyladenosine (m⁶A) of super-enhancer RNAs (seRNAs) on chromatin accessibility and gene transcription. We investigated seRNA m⁶A levels in pancreatic ductal adenocarcinoma (PDAC) and found that aberrantly increased m⁶A methylation promoted local chromatin accessibility, resulting in increased transcription of oncogenes acting in PDAC progression.

This Perspective article explores complex synthetic lethal relationships in cancer, which can involve several partners. Understanding this complexity presents challenges and opportunities for the development of therapeutics that target these interactions.

A test of four genomic sequence-to-expression deep learning models (Enformer, Basenji2, ExPecto, Xpresso) finds that they often fail to predict the correct direction of effect of cis-regulatory genetic variation on gene expression.

Neural networks are a common machine learning architecture for predicting phenotype from genomic sequence. This analysis finds that they err in calling the variant direction of effect, with important implications for personalized predictions.

A multi-ancestry genome-wide association study of prostate cancer performed in 156,319 cases and 788,443 controls identifies 187 novel risk variants associated with the disease. Genetic risk scores associated with overall risk, and risk of aggressive disease in men of African ancestry.

Loss-of-function mutations in primate-specific ZNF808 cause pancreatic agenesis. Mechanistically, the loss of ZNF808 leads to the activation of the MER11 family of transposable elements in a regulatory capacity that ultimately induces a liver-specific program of gene expression during pancreatic differentiation.

Phenotype imputation increases the effective sample size of major depressive disorder cases in UK Biobank, enhancing study power and polygenic risk score (PRS) accuracy. A new pleiotropy metric enables assessment of PRS specificity and comparison among different PRS models.

Multi-ancestry genome-wide association meta-analyses identify risk loci for cannabis use disorder. Genomic structural equation modeling and genetic correlation analyses show overlap with several other traits, including impulsivity and psychopathology.

Single-cell transcriptomes and single-cell chromatin accessibility profiles generated using EasySci provide a global view of aging and Alzheimer’s pathogenesis-associated cell population dynamics in human and mouse brains.

A multivariate framework for isoform-resolution transcriptome-wide association studies enables modeling of a greater number of genes, with the benefit of identifying isoform-specific associations with psychiatric traits not observed at the gene level.

Cross-ancestry genome-wide association meta-analyses identify new risk loci for peptic ulcer diseases and provide evidence that gastrointestinal cell differentiation and hormone regulation contribute to their etiology.

JaBbA v1 pinpoints the ‘loose ends’ of large (>10-kb) unmapped structural variants in short-read DNA sequencing, suggesting that about 90% of cancer chromosomal alterations outside centromeres are resolvable with short reads and that long reads will primarily improve calling of smaller somatic variants.

A barcode-based approach applied to UK Biobank and an Icelandic cohort identifies drivers of clonal hematopoiesis (CH) and finds associations between CH and multiple diseases. Genome-wide association analyses identify 25 loci associated with CH susceptibility.

Whole-genome analysis of paired follicular lymphoma and double-hit lymphoma shows that lymphoma progression is accompanied by enhanced somatic mutations targeting super-enhancer-embedded promoters.

Multiomic analysis of cervical squamous cell carcinoma identifies distinct cellular ecosystems characterized by immune cell infiltration, heterotypic signaling and patient outcomes.

Circular extrachromosomal DNA in high-risk medulloblastoma contributes to tumor heterogeneity and associates with relapse and survival. Enhancer rewiring events involving known oncogenes are frequent events, affecting transcription and proliferation.

Analysis of single-nucleus RNA sequencing and single-nucleus assay for transposase-accessible chromatin with sequencing data derived from synovium of patients with rheumatoid arthritis identifies regions with dynamic accessibility that correlate with cell states. Dynamic peaks are more strongly enriched for autoimmune disease heritability.

CRISPR activation/interference screens identify transcriptional regulators of human CD8⁺ T cells, including BATF3. BATF3 overexpression counteracts T cell exhaustion and enhances cancer immunotherapy in in vivo models.

In pancreatic duct adenocarcinoma, super-enhancer RNAs (seRNAs) have higher N⁶-methyladenosine (m⁶A) levels than in adjacent normal tissue due to upregulation of the METTL3 cofactor CFL1. Aberrant m⁶A seRNAs promote oncogene expression via the YTHDC2–MLL1 complex.

Roulette enables the estimation of germline mutation rates at basepair resolution from humans. Genes encoding small nuclear RNA showed significant deviations from the mutation rate predicted by Roulette, highlighting RNA polymerase III (Pol III)-dependent transcription as a potent source of mutations in the human genome.

Population analysis of 516 wild and domesticated broomcorn millet genomes and a graph-based pangenome based on de novo assemblies of 32 representative accessions identify genomic variations associated with domestication traits.

scHLApers is an analysis pipeline that quantifies single-cell expression of HLA genes using a personalized genomic reference. Mapping of HLA expression quantitative trait loci at single-cell resolution identifies dynamic effects across cell states.

AutoComplete is a deep learning-based method that imputes missing phenotypes in population-scale biobank datasets, increasing effective sample sizes and improving power for genetic discoveries in genome-wide association studies.