Shaping human brain development and vulnerability through alternative splicing.

Alternative splicing contributes to shaping lineage-specific gene expression and phenotypes. In this issue of Cell Genomics, Recinos, Bao, Wang, et al. report that the balance between splicing isoforms of the microtubule-associated protein Tau in the brain is differentially regulated among primates by the RNA-binding protein MBNL2, with consequences for protein aggregation and neurodegeneration in humans.

The relationship between nanoscale genome organization and gene expression in mouse embryonic stem cells during pluripotency transition.

During early development, gene expression is tightly regulated. However, how genome organization controls gene expression during the transition from naïve embryonic stem cells to epiblast stem cells is still poorly understood. Using single-molecule microscopy approaches to reach nanoscale resolution, we show that genome remodeling affects gene transcription during pluripotency transition.

Deconwolf enables high-performance deconvolution of widefield fluorescence microscopy images.

Microscopy-based spatially resolved omic methods are transforming the life sciences. However, these methods rely on high numerical aperture objectives and cannot resolve crowded molecular targets, limiting the amount of extractable biological information. To overcome these limitations, here we develop Deconwolf, an open-source, user-friendly software for high-performance deconvolution of widefield fluorescence microscopy images, which efficiently runs on laptop computers.

Predictive Biophysical Neural Network Modeling of a Compendium of Transcription Factor DNA Binding Profiles for .

The DNA binding of most Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of DNA binding for 139 TFs using ChIP-Seq. We used these data to train BoltzNet, a novel neural network that predicts TF binding energy from DNA sequence.

Targeting the autophagy-NAD axis protects against cell death in Niemann-Pick type C1 disease models.

Impairment of autophagy leads to an accumulation of misfolded proteins and damaged organelles and has been implicated in plethora of human diseases. Loss of autophagy in actively respiring cells has also been shown to trigger metabolic collapse mediated by the depletion of nicotinamide adenine dinucleotide (NAD) pools, resulting in cell death. Here we found that the deficit in the autophagy-NAD axis underpins the loss of viability in cell models of a neurodegenerative lysosomal storage disorder, Niemann-Pick type C1 (NPC1) disease.

Documenting the de-identification process of clinical and imaging data for AI for health imaging projects.

Artificial intelligence (AI) is revolutionizing the field of medical imaging, holding the potential to shift medicine from a reactive "sick-care" approach to a proactive focus on healthcare and prevention. The successful development of AI in this domain relies on access to large, comprehensive, and standardized real-world datasets that accurately represent diverse populations and diseases. However, images and data are sensitive, and as such, before using them in any way the data needs to be modified to protect the privacy of the patients.

Detection of differential bait proteoforms through immunoprecipitation-mass spectrometry data analysis.

Proteins are often referred to as the workhorses of cells, and their interactions are necessary to facilitate specific cellular functions. Despite the recognition that protein-protein interactions, and thus protein functions, are determined by proteoform states, such as mutations and post-translational modifications (PTMs), methods for determining the differential abundance of proteoforms across conditions are very limited. Classically, immunoprecipitation coupled with mass spectrometry (IP-MS) has been used to understand how the interactome (preys) of a given protein (bait) changes between conditions to elicit specific cellular functions.

An amphioxus neurula stage cell atlas supports a complex scenario for the emergence of vertebrate head mesoderm.

The emergence of new structures can often be linked to the evolution of novel cell types that follows the rewiring of developmental gene regulatory subnetworks. Vertebrates are characterized by a complex body plan compared to the other chordate clades and the question remains of whether and how the emergence of vertebrate morphological innovations can be related to the appearance of new embryonic cell populations. We previously proposed, by studying mesoderm development in the cephalochordate amphioxus, a scenario for the evolution of the vertebrate head mesoderm.

An extension of the Walsh-Hadamard transform to calculate and model epistasis in genetic landscapes of arbitrary shape and complexity.

Accurate models describing the relationship between genotype and phenotype are necessary in order to understand and predict how mutations to biological sequences affect the fitness and evolution of living organisms. The apparent abundance of epistasis (genetic interactions), both between and within genes, complicates this task and how to build mechanistic models that incorporate epistatic coefficients (genetic interaction terms) is an open question. The Walsh-Hadamard transform represents a rigorous computational framework for calculating and modeling epistatic interactions at the level of individual genotypic values (known as genetical, biological or physiological epistasis), and can therefore be used to address fundamental questions related to sequence-to-function encodings.

Germline NPAT inactivating variants as cause of hereditary colorectal cancer.

Two independent exome sequencing initiatives aimed to identify new genes involved in the predisposition to nonpolyposis colorectal cancer led to the identification of heterozygous loss-of-function variants in NPAT, a gene that encodes a cyclin E/CDK2 effector required for S phase entry and a coactivator of histone transcription, in two families with multiple members affected with colorectal cancer. Enrichment of loss-of-function and predicted deleterious NPAT variants was identified in familial/early-onset colorectal cancer patients compared to non-cancer gnomAD individuals, further supporting the association with the disease. Previous studies in Drosophila models showed that NPAT abrogation results in chromosomal instability, increase of double strand breaks, and induction of tumour formation.

Active transcription and epigenetic reactions synergistically regulate meso-scale genomic organization.

In interphase nuclei, chromatin forms dense domains of characteristic sizes, but the influence of transcription and histone modifications on domain size is not understood. We present a theoretical model exploring this relationship, considering chromatin-chromatin interactions, histone modifications, and chromatin extrusion. We predict that the size of heterochromatic domains is governed by a balance among the diffusive flux of methylated histones sustaining them and the acetylation reactions in the domains and the process of loop extrusion via supercoiling by RNAPII at their periphery, which contributes to size reduction.

TrxT and dhd are dispensable for Drosophila brain development but essential for l(3)mbt brain tumour growth.

Expression of the Drosophila cancer-germline (CG), X-linked, head-to-head gene pair TrxT and dhd is normally germline-specific but becomes upregulated in brain tumours caused by mutation in l(3)mbt. Here, we show that TrxT and dhd play a major synergistic role in the emergence of l(3)mbt tumour-linked transcriptomic signatures and tumour development, which is remarkable, taking into account that these two genes are never expressed together under normal conditions. We also show that TrxT, but not dhd, is crucial for the growth of l(3)mbt allografts, hence suggesting that the initial stages of tumour development and long-term tumour growth may depend on different molecular pathways.

Non-hypermutator cancers access driver mutations through reversals in germline mutational bias.

Cancer is an evolutionary disease driven by mutations in asexually-reproducing somatic cells. In asexual microbes, bias reversals in the mutation spectrum can speed adaptation by increasing access to previously undersampled beneficial mutations. By analyzing tumors from 20 tissues, along with normal tissue and the germline, we demonstrate this effect in cancer.

Proceedings of the 5th Meeting of Translational Hepatology, organized by the Spanish Association for the Study of the Liver (AEEH).

This is the summary report of the 5th Translational Hepatology Meeting, endorsed by the Spanish Association for the Study of the Liver (AEEH) and held in Seville, Spain, in October 2023. The meeting aimed to provide an update on the latest advances in the field of basic and translational hepatology, covering different molecular, cellular, and pathophysiological aspects of the most relevant clinical challenges in liver pathologies. This includes the identification of novel biomarkers and diagnostic tools, the understanding of the relevance of immune response and inflammation in liver diseases, the characterization of current medical approaches to reverse liver diseases, the incorporation of novel molecular insights through omics techniques, or the characterization of the impact of toxic and metabolic insults, as well as other organ crosstalk, in liver pathophysiology.

A complete map of specificity encoding for a partially fuzzy protein interaction.

Thousands of human proteins function by binding short linear motifs embedded in intrinsically disordered regions. How affinity and specificity are encoded in these binding domains and the motifs themselves is not well understood. The evolvability of binding specificity - how rapidly and extensively it can change upon mutation - is also largely unexplored, as is the contribution of 'fuzzy' dynamic residues to affinity and specificity in protein-protein interactions.

Guidelines for releasing a variant effect predictor.

Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released to date, and there is tremendous variability in their underlying algorithms and outputs, and in the ways in which the methodologies and predictions are shared. This leads to considerable challenges for end users in knowing which VEPs to use and how to use them.

The TP53-activated E3 ligase RNF144B is a tumour suppressor that prevents genomic instability.

Background: TP53, the most frequently mutated gene in human cancers, orchestrates a complex transcriptional program crucial for cancer prevention. While certain TP53-dependent genes have been extensively studied, others, like the recently identified RNF144B, remained poorly understood. This E3 ubiquitin ligase has shown potent tumor suppressor activity in murine Eμ Myc-driven lymphoma, emphasizing its significance in the TP53 network.