GoKawiil
Tech News
A study published in Nature by Morales and colleagues presents assembled genomes for 103 bat species, including 42 newly generated for the project, covering representatives of every known bat taxonomic family. The dataset gives scientists a broad genomic view of bat diversity and evolutionary history across the order Chiroptera.
Google has released AlphaGenome Atlas, a tool that predicts the functional impact of swapping in any of the three alternative bases at every position across the roughly 3-billion-base human genome, amounting to 9 billion base substitutions analyzed. The system focuses heavily on non-coding DNA, which makes up over 97% of the genome and includes regulatory elements that control gene activity alongside leftover viral sequences with no clear function.
Two independent research teams, led by Bower and colleagues and by Jerabek and colleagues, applied base editing—a precise form of genome editing—directly to human embryos to study how a specific gene shapes the earliest stages of development. Their experiments, published in Nature, show how embryos respond when particular DNA letters are altered, offering a clearer picture of this critical developmental window.
Researchers analyzed whole-genome sequencing data from 1,001 prostate cancer patients (1,172 tumour samples) collected through the PPCG consortium, applying computational tools to classify structural variants, including simple, complex, and chromothripsis-related genomic rearrangements. The team combined breakpoint detection, copy number segmentation, and statistical tests to build a detailed picture of mutational processes driving the disease.
Researchers analyzed genome-wide data from over 140,000 participants in the Mexico City Prospective Study, combining it with reference panels from the 1000 Genomes Project and Human Genome Diversity Project to estimate individual ancestry proportions across Indigenous American, European, African and East Asian populations. Using an ADMIXTURE model with four ancestral groups, they examined how differences in ancestry proportions among siblings within the same family relate to complex traits, isolating genetic ancestry effects from shared environmental and socioeconomic factors.
Google DeepMind has launched AlphaGenome Atlas, a publicly available database that uses its AlphaGenome AI model to predict the likely effects of every possible single-letter mutation across the human genome, covering both protein-coding and regulatory regions. The tool is free for non-commercial research use starting immediately, with a paid licensing option for commercial users, including DeepMind's own drug-discovery affiliate Isomorphic Labs, expected to follow via Google Cloud.
Google DeepMind has released AlphaGenome Atlas, a 1-petabyte database that uses its AlphaGenome AI model to predict the regulatory impact of all roughly 9 billion possible single-letter mutations across the human genome. The Atlas also introduces a scoring system called AVI, which condenses complex coding and non-coding predictions into one number researchers can use to quickly identify which genetic variants deserve closer study.
Google DeepMind has launched AlphaGenome Atlas, a database that predicts the molecular effects of every one of the roughly nine billion possible single-letter changes across the human genome. The tool is accessible via a web portal, the Antigravity development platform, and the AlphaGenome interface, and comes bundled with a new Variant Impact Score to help researchers prioritize which mutations are most likely to matter.
Google DeepMind has launched the AlphaGenome Atlas, a free, non-commercial database that uses its AlphaGenome AI model to predict the biological impact of every possible single-letter change across the human genome—about 9 billion mutations in total. The tool also incorporates predictions for over 100 million short insertions and deletions found in human DNA, and is designed to be accessible without requiring users to write code, unlike the original API-based release.
Researchers pooled data from 46 cohorts through the ReGPC consortium to run genome-wide association analyses on personality traits among participants with European-like and African-like ancestry. They applied strict quality controls—filtering low-frequency variants, poor imputation quality, and problematic samples—before analyzing how genetic variants relate to standardized Big Five personality measures.
Scientists led by Ben Lehner at the Wellcome Sanger Institute created over 44,000 genetic variants of the well-studied bacteriophage ΦX174 by systematically altering nearly every nucleotide and amino acid in its genome. They measured how each change affected the virus's ability to survive and replicate in bacterial cultures, finding that most mutations were harmful but that the reasons behind roughly a quarter of these lethal effects remain unexplained.
Researchers have devised a method to operate two separate genetic codes at once without needing to re-engineer an organism's entire genome to accommodate the change. The approach was tested outside living cells, so it avoids the laborious process of altering every gene, as previous efforts required when adding new amino acids to bacterial proteins.