194 papers
Genetics is the fascinating study of how traits are passed down and how our DNA shapes everything from eye color to disease risk. At Gist.Science, we bring you the very latest discoveries in this dynamic field directly from bioRxiv, the leading preprint server for biology. Because these findings appear months before formal publication, staying updated requires sifting through complex data that often feels inaccessible to non-specialists.
To bridge that gap, our team processes every new genetics preprint uploaded to bioRxiv, transforming dense scientific reports into clear, plain-language explanations alongside detailed technical summaries. This dual approach ensures that whether you are a seasoned researcher or simply curious about how genes work, you can grasp the core insights without getting lost in jargon. Below are the latest papers in genetics, curated and simplified for your reading.
Genomic analysis of 430 individuals from an Early Classic Maya kingdom in Belize reveals that elite lineages intentionally dispersed the remains of the same 24 ancestors between elite tombs and distant ritual caves, demonstrating a geographically expansive strategy of ancestor veneration that underscores the spiritual significance of caves in Maya belief systems.
The eQTM Atlas is a comprehensive, freely accessible web-based resource that curates over 11 million DNA methylation-gene expression associations across 11 tissues and 4 diseases to facilitate the functional interpretation of epigenome-wide association study findings by linking CpG sites to statistically associated genes rather than relying solely on genomic proximity.
This study demonstrates that redox stress agents significantly enhance mutagenesis in single-stranded DNA during bacterial conjugation, producing distinct mutational and metabolic footprints that may accelerate the evolution of antibiotic resistance.
This study establishes that heterozygous MED13L variants consistently cause mitochondrial dysfunction and aberrant cytoplasmic mislocalization of Cyclin C across multiple patient-derived fibroblast lines, revealing a molecular link between transcriptional control and metabolic decline that correlates with disease severity and offers a framework for biomarker-driven therapeutic development.
In a large twin study, researchers found that while extinction learning rates robustly predict anxiety severity, neither extinction nor safety learning rates are heritable or genetically linked to anxiety, suggesting they are not endophenotypes despite the confirmed heritability of safety learning parameters.
This study developed statistical methods to identify genomic regions with excess reciprocal recombination in autism spectrum disorder families, revealing specific loci near candidate genes where recombination likely disrupts co-adapted haplotypes to contribute to disease etiology, independent of copy number variations.
This study psychometrically validates the Education and Assessment of Genetic Literacy (EAGL) measure in a large US sample, confirming its multi-domain structure and revealing significant interactions between education, personal connection to autism, and knowledge comprehension while finding no geographic disparities.
This study reveals that the pathogenicity of C-terminal frameshift deletions in MeCP2 is determined by a specific +2 reading frame shift that creates a destabilizing proline-proline-stop motif, and demonstrates that correcting this motif via base editing can rescue MeCP2 levels and Rett syndrome phenotypes.
This paper establishes the theoretical foundations of HaloGen, an open-source hierarchical Bayesian framework that evaluates trace DNA evidence under activity-level propositions by explicitly modeling transfer, persistence, and detection probabilities to provide transparent and robust likelihood ratios across diverse evidentiary scenarios.
This paper presents the practical implementation and simulation validation of the open-source HaloGen framework for calculating activity-level likelihood ratios from DNA transfer evidence, demonstrating how inter-laboratory variability and case-specific contextual assumptions critically influence evidential strength while proposing a minimum-effort calibration pathway for forensic laboratories.