iiinova — where your digital self keeps evolving

Zoe Ward (She/Her) @zoe-ward.bsky.social · 17/08/2025

If you're at #hgsa2025 swing by poster 130 to see how we delivered a diagnosis for a family who had been on a 20 year unsolved genetic journey with @polona.bsky.social #raredisease #inheritedcardiac #humangenetics

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Reposted by Zoe Ward (She/Her)

Ewan Birney @ewanbirney.bsky.social · 29/07/2025

Another set of uORF impact mutations very likely to be causal in this set (uORFs - changes in UTR sequences which make or destroy an upstream ORF - uORF - often key for regulation)

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Reposted by Zoe Ward (She/Her)

Pacific Northwest Research Institute @pnrigenetics.bsky.social · 21/07/2025

Scientific advances are making it possible to detect #DNA changes that once went unnoticed. The Carvalho Lab @claucarvalho.bsky.social‬ is studying structural variants—like inversions—that may may disrupt genes and contribute to #rarediseases. Explore the latest research highlights: bit.ly/454JDZF

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Reposted by Zoe Ward (She/Her)

Samarendra Pani @samarendra-pani.bsky.social · 24/07/2025

[1/8] *New Open-Access Long Read Resource*. We sequenced 1,019 genomes from the 1000 Genomes Project sample cohort using @nanoporetech.com long-read sequencing (LRS) to median 17x coverage. Publication at go.nature.com/4ffPb8f. @hhu.de @crg.eu @embl.org @impvienna.bsky.social

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Reposted by Zoe Ward (She/Her)

Nature Reviews Genetics @natrevgenet.nature.com · 02/07/2025

Evolution of splicing model architectures go.nature.com/4eweliE Figure from our recent Review: From computational models of the splicing code to regulatory mechanisms and therapeutic implications (free to read here: rdcu.be/dVNV4)

a, Early models built sequence motifs to describe the consensus sequences of individual core splicing elements, such as splice sites (SSs) and intronic and/or exonic enhancers and silencers. Statistical and machine-learning models were built to output the probability of a novel sequence acting as a core splicing element. The sequence logos shown for 5′SS and 3′SS were generated from Human hg38 RefSeq annotations (code available at https://www.github.com/ulelab/splicelogos). b, As our understanding of splicing mechanisms progressed, expert-selected features were extracted from sequences and used to train integrative models to predict splicing outcomes. c, With the advent of deep-learning, models could jointly learn features directly from raw sequence input. Although theoretically, sequence context could be as large as shown in part d, in practice smaller windows of up to 30 kb have been used. d, Supervised models with convolutional and transformer layers produce multimodal genome-wide data. These models use a much larger sequence context and can predict genome-wide data including RNA sequencing coverage, which can be further processed to evaluate splicing. e, By learning how to reconstruct partially masked genomic sequences across multiple species, self-supervised masked language models capture evolutionarily conserved sequence elements and their functional context in a very generic and flexible fashion. The informative numerical representations obtained by large language models can be used for splicing prediction tasks. Here 3′SS within different sequence contexts from multiple species are shown aligned for easier interpretation, but in practice sequences do not have to be aligned. Current masked language models with application to splicing use variable context windows from 1,000 to 1 million base pairs; however, it is currently unclear whether larger context windows confer better performance

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Reposted by Zoe Ward (She/Her)

Human Genetics and Genomics Advances @hggadvances.bsky.social · 20/06/2025

📣New research from @gregor-research.bsky.social! 📄 Long-Read Sequencing is Required for Precision Diagnosis of Incontinentia Pigmenti 👉http://bit.ly/4kQLRCo

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Reposted by Zoe Ward (She/Her)

Human Genetics and Genomics Advances @hggadvances.bsky.social · 20/06/2025

📣New from Ng et al! 📄Identification of technically challenging variants – whole genome sequencing improves diagnostic yield in patients with high clinical suspicion of rare diseases 👉http://bit.ly/4lkXEci

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Reposted by Zoe Ward (She/Her)

Ming Tommy Tang @tommytang.bsky.social · 06/07/2025

DiffMethylTools: a toolbox of the detection, annotation and visualization of differential DNA methylation www.biorxiv.org/content/10.... the github link is dead, though..

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