Jacob González Isa

🇪🇸 Postgraduate Fellow 'la Caixa' @BecariosFLC at @Cambridge_uni \ MSc CompBio @La_UPM \ BSc Biochemistry @unisevilla \ 🌱💻🧬 #FirstGenUni

[Jacob González Isa @JacobGIsa]

I am so grateful. This has been an incredible first year of PhD.
Looking for more and better!

Las raíces lo son todos, es lo único que tengo💚🤍💚
🇪🇸
https://t.co/Kl4dZa9Jo6 via @CSurNoticias

[Xiao Dong @justdx0713]

Very happy to see our work on the mutational dynamics of Arabidopsis centromeres officially out in @Nature! 🎉🌱

Huge thanks to everyone in @LabSchneeberger , our collaborators, and everyone who helped along the way!

📄 https://t.co/zBzB4wANgd
📰 https://t.co/l0EdtRAkOZ

[André Marques @marques_et_al]

Out today in Nature: sex without crossovers.

Rhynchospora tenuis makes pollen, fertilises and sets seed, yet 0 crossovers in 10,997 pollen nuclei. Chromosome drive and ~87% seed abortion rebuild the mother's genotype, so the offspring are clones.

https://t.co/t9f5eMmaeu

[Jaime Huerta-Cepas @jhcepas]

The CGMLab is seeking an experienced postdoctoral researcher to work on an EU project focusing on the bioprospecting of novel microbial enzymes and pathways through metagenomics. Further information and application form can be found at: https://t.co/tWIhiCBg31

[Jaime Huerta-Cepas @jhcepas]

The CGMLab is seeking an experienced postdoctoral researcher to work on an international project focusing on the clinical associations of the microbiome of the female reproductive tract and heavy menstrual bleeding disorder. Applications and info at https://t.co/eFJ9tVVIOr.

[Ian Henderson @hendersi]

CRISPR-mediated centromere fission generates neochromosomes with distorted meiotic inheritance in Arabidopsis https://t.co/8lHyxOZxic new preprint from us - includes changing the Arabidopsis karyotype from 5 -> 6 chromosomes using Cas9 & outcomes of 5/6 chromosome hybrid meiosis

[Crisanto Gutierrez @CG_ath]

Muy agradecido por este reconocimiento por parte del @MICIU extensivo a los miembros del equipo, actuales y pasados, y a las personas e instituciones que apoyaron la candidatura @CBM_CSIC_UAM @CSIC @SEBBM @LluisMontoliu @Molina_CBGP @jfxdiffley @CarolineDeanLab #EvaKondorosi

[Department of Plant Sciences Cambridge @camplantsci]

Job opportunity!

Research Assistant / Research Associate

An opportunity to be a part of a pioneering new effort to generate fully synthetic plant chromosomes.

Apply by Sunday 19 July 2026: https://t.co/pKrnJAtMfH

[Nature Methods @naturemethods]

A model-agnostic empirical framework measures the uncertainty associated with protein embeddings and assesses their biological relevance to improve model reliability. @y_bromberg @rpkarans

https://t.co/nISAGtc8IV

[Jaime Huerta-Cepas @jhcepas]

📢 We are hiring!
PhD Position in Metagenomics at the CGMLab

We are looking for a motivated researcher to join our newly launched project exploring the Unknown Microbial Biosphere, focusing on uncultivated eukaryotic microbes and novel functions.

https://t.co/2qVgEMpp3c

[Evolutionary Genomics @evol_genomics]

RECUR: Identifying recurrent amino acid substitutions from multiple sequence alignments https://t.co/EiZcgIdOtf @MolBioEvol

[Genetics Society of America @GeneticsGSA]

A new study in #GENETICS from @hendersi’s group explores how natural variation in #Arabidopsis influences centromere-proximal crossover frequency and segregation distortion when #centromeres are heterozygous. https://t.co/DGPq6BMB1a

[Alexandros Bousios @abousios]

Come join our lab in Sussex, UK for a PhD on TEs, on centromeres, on the genome ecosystem! Exciting times for TE:genome dynamics given the rate of T2T sequencing. Please circulate! https://t.co/X5w3Bir8Ti

[bioRxiv Genomics @biorxiv_genomic]

A holocentric pangenome links karyotype evolution to meiotic recombination https://t.co/cMb6Vn4qC8 #biorxiv_genomic

[Jacob González Isa @JacobGIsa]

I believe we should understand how to train these without masking and excluding repetitive sequences (rDNA, centromeres, etc.). They are crucial in long-range genomic organization and in the k-mer spectra of genomes…

That might help to mitigate these concerns.

[Biology+AI Daily @BiologyAIDaily]

Fundamental limitations of genomic language models for realistic sequence generation

1. A new study evaluates the capabilities of genomic language models (gLMs) in generating realistic genomic sequences, revealing significant limitations in capturing essential genomic features. The research highlights the need for specialized architectures to better model biological constraints.

2. The study focuses on Evo 2, a state-of-the-art gLM with 40 billion parameters, and tests its performance on diverse prokaryotic, eukaryotic, and viral genomes. Results show that while synthetic sequences capture local statistics, they fail to preserve long-range genomic organization and other key biological features.

3. Synthetic genomes generated by Evo 2 consistently fail to replicate natural k-mer spectra, showing systematic distortions in frequency chaos game representations (FCGRs). This indicates a lack of species-specific higher-order k-mer organization in the generated sequences.

4. The research also finds that synthetic genomes exhibit significant deviations in nullomer content, with eukaryotic genomes showing depletion of nullomers, while viral and prokaryotic genomes show enrichment. This highlights Evo 2's inability to capture domain-specific evolutionary constraints.

5. Non-B DNA motifs, which are crucial for genomic processes, are systematically distorted in synthetic genomes. Eukaryotic sequences show depletion of these motifs, while viral genomes show enrichment, indicating a failure to replicate the density and distribution of non-B DNA structures.

6. Transcription factor binding sites (TFBS) are found to be systematically enriched in synthetic human sequences, with a loss of native clustering and hotspot organization. This suggests that gLMs like Evo 2 reshape the regulatory motif landscape in a way that diverges from natural genomic patterns.

📜Paper: https://t.co/wUdrF6ZGpg
#Genomics #LanguageModels #ComputationalBiology #SyntheticGenomes #Bioinformatics

[bioRxiv Genomics @biorxiv_genomic]

Pangenome analysis reveals the evolutionary dynamics of repeat-based holocentromeres https://t.co/PlMWrJj6zX #biorxiv_genomic

[Biology+AI Daily @BiologyAIDaily]

Rewriting Protein Alphabets with Language Models

1. A groundbreaking study introduces TEA (The Embedded Alphabet), a novel 20-letter alphabet derived from protein language models, enabling highly efficient large-scale protein homology searches. This method achieves sensitivity comparable to structure-based approaches without requiring structural information, bridging the gap between deep learning representations and traditional sequence bioinformatics tools.

2. The core innovation lies in using contrastive learning to convert high-dimensional protein language model embeddings into a discrete alphabet. This allows for rapid sequence comparisons using optimized tools like MMseqs2, while retaining the ability to detect remote homologs with structural similarity, offering a powerful alternative to existing methods.

3. TEA demonstrates remarkable performance in benchmarks, achieving high sensitivity in detecting homologs within the SCOPe40 database and multi-domain proteins from the AlphaFold Database. It outperforms traditional sequence alignment methods and matches the accuracy of structure-based searches, all while maintaining low computational costs.

4. An intriguing aspect is the use of entropy as a confidence metric, providing a measure of prediction reliability. This allows researchers to filter results based on confidence levels, enhancing the accuracy of functional annotations and structural predictions, especially in challenging cases like disordered regions or poorly modeled structures.

5. The study highlights TEA’s potential to improve functional annotation by connecting structural singletons in the AlphaFold Database to cluster representatives. This approach identifies over 14 million new connections with high accuracy, suggesting TEA could revolutionize clustering efforts and reveal novel functional relationships.

6. Looking ahead, TEA offers a versatile framework for creating specialized alphabets tailored to specific biological goals, such as function prediction or interface description. This could extend its applications to RNA sequences and other areas, further integrating deep learning into bioinformatics workflows.

7. The TEA model and training scripts are available on GitHub, along with converted TEA sequences for popular databases like AFDB Clusters and UniRef50, making it accessible for researchers to integrate into their workflows.

📜Paper: https://t.co/19sozB2H57
#ProteinLanguageModels #Bioinformatics #ContrastiveLearning #HomologySearch #StructuralBiology #ComputationalBiology

[Jaime Huerta-Cepas @jhcepas]

tx! This is of course the outcome of a long-term team effort!
Kudos to all current and former lab members and collaborators!!
(...yes we need to update our group photo :)

[🧬Jacob L Steenwyk @jlsteenwyk]

NEW pub in @ScienceMagazine🥳

Is it sponges (panels A & B) or comb jellies (C & D) that root the animal tree of life?

For over 15 years, #phylogenomic studies have been divided.

We provide new evidence suggesting that...

[ISCB SC RSG-Spain @RSGSpain]

@eduardoarandac @franjrm_711 @JacobGIsa Jacob González Isa
- "Detection of meiotic recombination in centromeres"

#RSGSpain #XStudentSymposium

[Cell @CellCellPress]

Now online! The genomic footprints of wild Saccharum species trace domestication, diversification, and modern breeding of sugarcane https://t.co/lsJSFsvm9k