Background Cell state-specific gene expression programs emerge from the interplay between cis-regulatory elements (CREs), such as enhancers, and transcription factors (TFs). Massively parallel reporte...

In this Review, Rodriguez-Fraticelli and Parreno discuss advances in single-cell lineage-tracing methods and how their application to diverse biological processes, such as development, ageing and canc...

Feng et al. present the first genome-scale CRISPR interference perturbation map with scRNA-seq readout across many genetic backgrounds in human pluripotent cells, pioneering population-scale CRISPR pe...

As people read less they think less clearly, scholars fear

This study introduces SDR-seq, a droplet-based single-cell DNA–RNA sequencing platform, enabling the study of gene expression profiles linked to both noncoding and coding variants.

Yin et al. demonstrate the use of iteratively retrained deep learning models to design synthetic enhancers for progressively higher cell-type specificity. They show the feasibility of model training f...

Un estudio liderado por dos centros de investigación de Barcelona ha descubierto que, a partir de esa edad, cada vez tenemos menos células madre sanguíneas y las que hay se replican cada vez con más e...

This work presents SUM-seq, an ultra-high-throughput method for co-profiling chromatin accessibility and gene expression in single nuclei across multiplexed samples, advancing the study of gene regula...

The discovery that DNA methylation of different CpG sites can serve as digital barcodes of clonal identity led to the development of EPI-Clone, an algorithm that enables single-cell lineage tracing th...

Much remains to be learned about the clonal fate of mammalian epiblast cells. Here, we develop high-diversity Cre recombinase-driven LoxCode barcoding…

This study presents a large-scale enhancer screening approach to optimize gene therapy vectors. A compact, potent, erythroid-specific enhancer used in a therapeutic vector, improved viral titers, tran...

A team from the Centre for Genomic Regulation (CRG) and Pompeu Fabra University (UPF) in Barcelona has developed an artificial intelligence tool capable of designing regulatory sequences for genes that do not exist in nature. When introduced into cells, these enhancers can increase or decrease gene activity in a specific way depending on the type of cell targeted. According to the authors, ‘the potential applications are enormous. It's like writing software, but for biology.’ The results are published in the journal Cell.

Screen of minimalistic enhancers in blood progenitor cells demonstrates widespread dual activator-repressor function of transcription factors (TFs) and enables the model-guided design of cell-state-specific enhancers.

Screen of minimalistic enhancers in blood progenitor cells demonstrates widespread dual activator-repressor function of transcription factors (TFs) and enables the model-guided design of cell-state-sp...

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