368 papers
Genomics is the study of an organism's complete set of DNA, offering a deep dive into the biological instructions that shape life. This field explores how genetic information influences traits, health, and evolution, moving beyond single genes to understand the complex interplay within entire genomes. From uncovering the roots of disease to mapping biodiversity, genomics provides the foundational data for many modern medical breakthroughs.
At Gist.Science, we process every new preprint in this category as it appears on bioRxiv, ensuring you stay ahead of the curve. Each paper is accompanied by both a clear, plain-language overview and a detailed technical summary, making cutting-edge research accessible to everyone regardless of their background. Below are the latest papers in genomics, freshly summarized and ready for you to explore.
This study establishes a comprehensive resource and novel sequence modeling strategies by integrating multi-omics data from 190 human donors to map cell type-specific cis-regulatory variants in the brain, enabling the functional interpretation of non-coding Parkinson's disease risk loci.
OxBreaker is an automated, species-agnostic, and user-friendly open-source pipeline that leverages Oxford Nanopore sequencing to enable non-specialists to perform high-resolution, real-time genomic surveillance of bacterial outbreaks with accuracy comparable to short-read platforms.
This paper evaluates nine statistical and machine learning methods for handling high-dimensional ecological and evolutionary data, finding that while overfitting is common and accurate variable selection often unattainable under realistic sampling schemes, sparse models can still achieve predictive accuracy and mitigate overfitting when data attributes such as sample size, effect strength, and variable count are favorable.
This study demonstrates that PacBio HiFi long-read sequencing enables the accurate de novo assembly of complete Plasmodium falciparum genomes, including complex Variant Surface Antigen families, from 43 natural isolates in The Gambia, providing a high-quality genomic resource for studying parasite evolution and antigenic diversity.
The paper introduces ARGformer, a transformer-based model that learns context-dependent embeddings from ancestral recombination graphs to effectively capture population structure and infer ancestry without relying on genotype matrices.
BioWorldModel is a unified, multi-kingdom architecture that leverages evolutionary curriculum learning to predict phenotypic distributions across fungi, plants, and animals with a single set of parameters, significantly outperforming traditional species-specific genomic prediction methods by capturing shared genotype-to-phenotype principles.
The authors present ExTRaCT, an efficient and user-friendly automated pipeline designed to identify and classify conserved gene exons, such as APOBEC3 Z-domains, in novel species genomes without relying on whole-genome annotations or closely related reference species.
This study presents a genome-scale functional atlas of the mouse brain by using an enhanced in vivo Perturb-seq platform to profile transcriptome-wide responses to the loss of 1,947 disease-associated genes across 7.7 million cells, revealing cell-type-specific essentiality and opposing transcriptional programs that advance our understanding of neurodevelopmental, psychiatric, and neurodegenerative diseases.
This study presents genomic evidence that Norwegian farmhouse "kveik" yeasts represent an early-diverging, distinct lineage of *Saccharomyces cerevisiae* domestication dating back 4,000–8,000 years, preserving a relic of ancient human brewing practices with minimal admixture from other domesticated strains.
This study analyzes nearly 4,700 eukaryotic genomes to reveal that genes encoding secreted proteins are consistently enriched in genomic regions characterized by long flanking intergenic sequences and a high density of truncated, fragmented repeats, suggesting an ancient, conserved genomic architecture that drives evolutionary innovation in secreted protein function.