207: Semantic Design of de novo Genes with Evo

Semantic Design of de novo Genes with Evo Music:Enjoy the music based on this article at the end of the episode. DOI:10.1038/s41586-025-09749-7 License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 Official website https://basebybase.com On PaperCast Base by Base you’ll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/semantic-design-of-de-novo-genes-with-evo ️ Episode:207: Semantic Design of de novo Genes with Evo ️ Season:1 Article title:Semantic design of functional de novo genes from a genomic language model Journal:Nature QC:This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-11-24. QC Scope:- article metadata and core scientific claims from the narration- excludes analogies, intro/outro, and music- transcript coverage: Audited transcript sections describing Evo 1.5 semantic design, contextual autocompletion, toxin–antitoxin designs (T2TA/T3TA), anti-CRISPR designs, and SynGenome, plus limitations and licensing statements.- transcript topics: Semantic design and genomic context; In-context design and autoregression; Toxin–antitoxin (T2TA) design and validation; Toxin–antitoxin (T3TA) design and validation; Anti-CRISPR (Acr) design and validation; SynGenome database and analyses QC Summary:- factual score: 10/10- metadata score: 10/10- supported core claims: 6- claims flagged for review: 0- metadata checks passed: 4- metadata issues found: 0 Metadata Audited:- article_doi- article_title- article_journal- license Factual Items Audited:- Semantic design uses genomic context to enable function-guided design of de novo genes (Evo 1.5).- Autocomplete test: Evo 1.5 achieved 85% amino acid recovery for rpoS with 30% input.- Toxin–antitoxin (T2TA) design yielded functional toxins and antitoxins; EvoRelE1 toxin; EvoAT1–4 antitoxins; EvoAT2 and EvoAT4 show multitoxin neutralization; EvoT3TA design produc- Anti-CRISPR (Acr) designs produced functional Acrs; 17% of tested Acrs exhibited activity against SpCas9; EvoAcr1–5 validated.- SynGenome database contains over 120 billion base pairs of AI-generated DNA; ~3.7 million predicted protein structures; Pfam-domain frequencies in SynGenome closely mirror natural- Limitations include autoregressive generation risks (repetitive/hallucinated sequences) and reliance on genomic context; lab validation remains essential; applicability to human ge QC result: Pass. Chapters (00:00:00) - A New Way to Design New Genomes(00:05:45) - Artificial Intelligence's challenge to protein design(00:11:08) - Uncovering the genome's hidden secrets(00:11:53) - The Secret Life of Genes