Linda Koch

Review: AI to advance CRISPR-based genome editing technologies www.nature.com/articles/s41... (read free: rdcu.be/eQKtm)

I highly recommend this fantastic review by Jennifer A. Korchak, S. Stephen Yi, @nlkproteomics.bsky.social, Nidhi Sahni and Gloria M. Sheynkman!

And it's a whopper of an issue!

Walking around the office looking for a print copy yesterday... "Oh yeah, I saw your Stranger Things cover over there..." 😁

Preprint site arXiv is banning computer-science reviews: here’s why The repository is taking steps to tackle a surge in low quality, AI-generated content.

Preprint site arXiv is banning computer-science reviews: here’s why www.nature.com/articles/d41...

It was a fun one!

New commentary from @katholt.bsky.social just dropped 😊

This is figure 1, which shows mutational burden and signature analysis in sperm and matched blood.

The findings of a study in Nature shed light on germline selection dynamics and highlight a broader increased disease risk for children born to fathers of advanced age than previously appreciated. go.nature.com/4h5BglX 🧬 🧪

A reminder that you can follow all of our journals with one click by using our starter pack!

a boy and a girl are sitting at a desk and the girl says " it 's october 3rd " ALT: a boy and a girl are sitting at a desk and the girl says " it 's october 3rd "

@heykatray.bsky.social 🫶

Donate to Support Rick's Battle with Cancer, organized by Melanie Tiffen Help Rick fight! My brother-in-law 

Rick has been diagnosed with metastatic … Melanie Tiffen needs your support for Support Rick's Battle with Cancer

gofund.me/a6fca9629

A genomic view of Earth’s biomes - Nature Reviews Genetics Genome-wide approaches have uncovered the vast microbial and viral diversity across ecosystems. This Review explores advances in metagenomics, single-cell sequencing and functional profiling to elucid...

This was a really nice review to work on:
A genomic view of Earth’s biomes go.nature.com/3VTLImU by Gitta Szabó, Emiley A. Eloe-Fadrosh, Jennifer Pett-Ridge & Tanja Woyke

Thanks, Ursula! X

🎉 25 years of NRG! Feels a bit bonkers to think I’ve been at the helm for almost 12 years 🤯 Where did the time go???

hey bluesky 👋 visa hurdles mean I’m looking for opportunities outside the US. I’m a computational biologist (bacterial + phage genomics, postdoc in Koonin’s group @ NIH). I am interested in teaming up on funding apps. reach out if this resonates!

Non-CG DNA methylation in animal genomes Nature Genetics - This Review discusses noncanonical DNA methylation (mCH) in animal genomes and highlights the remaining need to clarify whether mCH represents a conserved regulatory layer or a...

Very happy to have contributed to this review on "non-CG" #methylation in animals now out in @natgenet.nature.com. Working again with @obog.bsky.social and Tirsa is always a pleasure. We think this not so well studied form of methylation should be more widely considered, please read: rdcu.be/eFAEk

Review: Transcriptomics in the era of long-read sequencing www.nature.com/articles/s41... (read free: rdcu.be/efBjP) 🧬🖥️🧪

Translon: a single term for translated regions - Nature Methods Nature Methods - Translon: a single term for translated regions

There is a lack of general terminology for translated regions that does not depend on the properties of their products or their sequence.

Spearheaded by Pavel (Pasha) Baranov, this primer provides a unifying nomenclature for translation units: *Translon*

www.nature.com/articles/s41...

I'm not giving up my M-dash!!!

This is figure 1, which shows a summary of genomic findings for schizophrenia, bipolar disorder and depression.

A Review in Nature Reviews Genetics discusses how genomic advances have enhanced our understanding of schizophrenia, bipolar disorder and major depressive disorder, which could address limitations in diagnostic frameworks and future treatment strategies. go.nature.com/44bKTuy 🧬 🧪

Autophagy genes in biology and disease - Nature Reviews Genetics Macroautophagy and microautophagy involve characteristic membrane dynamics regulated by autophagy-related proteins to degrade cytoplasmic material in lysosomes. In this Review, the authors summarize r...

Autophagy genes in biology and disease go.nature.com/4lnHiiT #Review by Hayashi Yamamoto, Sidi Zhang & Noboru Mizushima

Methods and applications for single-cell and spatial multi-omics Nature Reviews Genetics - In this Review, the authors discuss the latest advances in profiling multiple molecular modalities from single cells, including genomic, transcriptomic, epigenomic and...

Methods and applications for single-cell and spatial multi-omics go.nature.com/3GkzmzZ #Review by Katy Vandereyken, Alejandro Sifrim, @bernthie.bsky.social & Thierry Voet
Free to read here: rdcu.be/c6JjL

Targeted genome-modification tools and their advanced applications in crop breeding Nature Reviews Genetics - Targeted genome modification using CRISPR–Cas genome editing, base editing or prime editing is driving base research in plants and precise molecular breeding. The...

Targeted genome-modification tools and their advanced applications in crop breeding go.nature.com/3T8J8bs #Review by Boshu Li, Chao Sun, Jiayang Li & Caixia Gao
Free to read here: rdcu.be/dFHti

If you enjoyed our RNA splicing collection, this @natrevdrugdiscov.nature.com Review may be of interest:
Protein isoform-centric therapeutics: expanding targets and increasing specificity go.nature.com/44HDClo

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

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)

What gif pops up when you type your name

Our August 2025 issue is now live: go.nature.com/4kIXzOI
Topics include: systems biology in the single-cell era; ADAR1-mediated RNA editing; retrotransposable element reactivation and its biological impact; transcriptional condensates as temporal signal integrators; X-linked competition

Multiplexed assays of variant effect for clinical variant interpretation Nature Reviews Genetics - Multiplexed assays of variant effect (MAVEs) are highly scalable experimental approaches used to generate functional data for genetic variants. In this Review, McEwen et...

Interested in using functional data to understand clinical variants? Been hunting for a good review of the topic? We just wrote one! rdcu.be/exaEU

We (with Clement Coclet, not on Bsky) had the chance to work on a broad "state of viromics" review. We tried to use this to give an overview of how the field changed over the last ~ 15 years, and also what we think are some of the major remaining challenges. Full-text access at -> rdcu.be/excHt

New review article with @mmdesai.bsky.social is out today! Grateful for the opportunity to contribute something we hope will serve the community well