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Biology subjects

Boix, C. A.

Publications and source records attributed to Boix, C. A..

6 recordsLinked to original sources

Deep learning modeling of ribosome profiling reveals regulatory underpinnings of translatome and interprets disease variants

Gene expression involves transcription and translation. Despite large datasets and increasingly powerful methods devoted to calculating genetic variants effects on transcription, discrepancy between mRNA and protein levels hinders the systematic interpretation of the regulatory effects of disease-associated variants. Accurate models of the sequence determinants of translation are needed to close this gap and to interpret disease-associated variants that act on translation. Here, we present Translatomer, a multimodal transformer framework that predicts cell-type-specific translation from mRNA expression and gene sequence. We train Translatomer on 33 tissues and cell lines, and show that the inclusion of sequence substantially improves the prediction of ribosome profiling signal, indicating that Translatomer captures sequence-dependent translational regulatory information. Translatomer achieves accuracies of 0.72 to 0.80 for de novo prediction of cell-type-specific ribosome profiling. We develop an in silico mutagenesis tool to estimate mutational effects on translation and demonstrate that variants associated with translation regulation are evolutionarily constrained, both within the human population and across species. Notably, we identify cell-type-specific translational regulatory mechanisms independent of eQTLs for 3,041 non-coding and synonymous variants associated with complex diseases, including Alzheimers disease, schizophrenia, and congenital heart disease. Translatomer accurately models the genetic underpinnings of translation, bridging the gap between mRNA and protein levels, and providing valuable mechanistic insights toward mapping "missing regulation" in disease genetics.

genomics↗

A single-cell atlas of ABCA7 loss-of-function reveals lipid disruptions, mitochondrial dysfunction and DNA damage in neurons

Loss-of-function (LoF) variants in the lipid transporter ABCA7 significantly increase Alzheimers disease risk (odds ratio {approx} 2), yet the underlying pathogenic mechanisms and specific neural cell types affected remain unclear. To investigate this, we generated a single-nucleus RNA sequencing atlas of 36 human postmortem prefrontal cortex samples, including 12 carriers of ABCA7 LoF variants and 24 matched non-carriers. ABCA7 LoF variants were associated with transcriptional changes across all major neural cell types. Excitatory neurons, which expressed the highest levels of ABCA7, showed significant alterations in oxidative phosphorylation, lipid metabolism, DNA damage responses, and synaptic signaling pathways. ABCA7 LoF-associated transcriptional changes in neurons were similarly perturbed in carriers of the common AD missense variant ABCA7 p.Ala1527Gly (n = 240 controls, 135 carriers) predicted by molecular dynamic simulations to disrupt ABCA7 structure -, indicating that findings from our study may extend to large portions of the at-risk population. Human induced pluripotent stem cell (iPSC)-derived neurons carrying ABCA7 LoF variants closely recapitulated the transcriptional changes observed in human postmortem neurons. Biochemical experiments further demonstrated that ABCA7 LoF disrupts mitochondrial membrane potential via regulated uncoupling, increases oxidative stress, and alters phospholipid homeostasis in neurons, notably elevating saturated phosphatidylcholine levels. Supplementation with CDP-choline to enhance de novo phosphatidylcholine synthesis effectively reversed these transcriptional changes, restored mitochondrial uncoupling, and reduced oxidative stress. Additionally, CDP-choline normalized amyloid-{beta} secretion and alleviated neuronal hyperexcitability in ABCA7 LoF neurons. This study provides a detailed transcriptomic profile of ABCA7 LoF-induced changes and highlights phosphatidylcholine metabolism as a key driver in ABCA7-induced risk. Our findings suggest a promising therapeutic approach that may benefit a large proportion of individuals at increased risk for Alzheimers disease.

neuroscience↗

The ENCODE Imputation Challenge: A critical assessment of methods for cross-cell type imputation of epigenomic profiles

Functional genomics experiments are invaluable for understanding mechanisms of gene regulation. However, comprehensively performing all such experiments, even across a fixed set of sample and assay types, is often infeasible in practice. A promising alternative to performing experiments exhaustively is to, instead, perform a core set of experiments and subsequently use machine learning methods to impute the remaining experiments. However, questions remain as to the quality of the imputations, the best approaches for performing imputations, and even what performance measures meaningfully evaluate performance of such models. In this work, we address these questions by comprehensively analyzing imputations from 23 imputation models submitted to the ENCODE Imputation Challenge. We find that measuring the quality of imputations is significantly more challenging than reported in the literature, and is confounded by three factors: major distributional shifts that arise because of differences in data collection and processing over time, the amount of available data per cell type, and redundancy among performance measures. Our systematic analyses suggest several steps that are necessary, but also simple, for fairly evaluating the performance of such models, as well as promising directions for more robust research in this area.

bioinformatics↗

Single-cell mosaicism analysis reveals cell-type-specific somatic mutational burden in Alzheimer's Dementia

Despite significant advances in identifying genetic drivers of neurodegenerative disorders, the majority of affected individuals lack molecular genetic diagnosis, with somatic mutations proposed as one potential contributor to increased risk. Here, we report the first cell-type-specific map of somatic mosaicism in Alzheimers Dementia (AlzD), using 4,014 cells from prefrontal cortex samples of 19 AlzD and 17 non-AlzD individuals. We integrate full-transcript single-nucleus RNA-seq (SMART-Seq) with matched individual-level whole-genome sequencing to jointly infer mutational events and the cell-type in which they occurred. AlzD individuals show increased mutational burden, localized in excitatory neurons, oligodendrocytes, astrocytes and disease-associated "senescent" cells. High-mutational-burden cells showed mutational enrichment and similar single-cell expression profiles in AlzD cases versus non-AlzD individuals, indicating cellular-level genotype-to-phenotype correlation. Somatic mutations are specifically enriched for known AlzD genes, and implicate biologically meaningful cell-type specific processes, including: neuronal energy regulation, endocytic trafficking (NEFM), lipid metabolism (CNP, CRYAB), proteostasis (USP34), cytoskeleton, and microtubule dynamics (MACF1).

neuroscience↗

Neurons burdened by DNA double strand breaks incite microglia activation through antiviral-like signaling in neurodegeneration.

DNA double strand breaks (DSBs) are linked to aging, neurodegeneration, and senescence1,2. However, the role played by neurons burdened with DSBs in disease-associated neuroinflammation is not well understood. Here, we isolate neurons harboring DSBs from the CK-p25 mouse model of neurodegeneration through fluorescence-activated nuclei sorting (FANS), and characterize their transcriptomes using single-nucleus, bulk, and spatial sequencing techniques. We find that neurons harboring DSBs enter a late-stage DNA damage response marked by the activation of senescent and antiviral-like immune pathways. We identify the NFkB transcription factor as a master regulator of immune gene expression in DSB-bearing neurons, and find that the expression of cytokines like Cxcl10 and Ccl2 develop in DSB-bearing neurons before glial cell types. Alzheimers Disease pathology is significantly associated with immune activation in excitatory neurons, and direct purification of DSB-bearing neurons from Alzheimers Disease brain tissue further validates immune gene upregulation. Spatial transcriptomics reveal that regions of brain tissue dense with DSB-bearing neurons also harbor signatures of inflammatory microglia, which is ameliorated by NFkB knock down in neurons. Inhibition of NFkB or depletion of Ccl2 and Cxcl10 in DSB-bearing neurons also reduces microglial activation in organotypic brain slice culture. In conclusion, we find that in the context of age-associated neurodegenerative disease, DSBs activate immune pathways in neurons, which in turn adopt a senescence associated secretory phenotype to elicit microglia activation. These findings highlight a novel role for neurons in the mechanism of age-associated neuroinflammation. SummaryIt is unclear how age-associated DNA double strand break (DSB) accumulation in neurons influences the progression of cellular senescence and neurodegenerative disease. Here, we leverage mouse models of neurodegeneration, single-nucleus, bulk, and spatial transcriptomics from Alzheimers disease patients, mouse models, and primary neuron cultures to dissect the immune signaling pathways initiated by DSB-bearing neurons that trigger neuroinflammation.

neuroscience↗

Single-cell dissection of live human hearts in ischemic heart disease and heart failure reveals cell-type-specific driver genes and pathways

Ischemic heart disease is globally the leading cause of death. It plays a central role in the electrical and structural remodeling of the right atrium, predisposing to arrhythmias, heart failure, and sudden death. Here, we provide the first dissection of the gene expression changes in the live right atrial tissue, using single-nuclei RNA-seq and spatial transcriptomics. We investigate matched samples of the tissue and pericardial fluid and reveal substantial differences in disease- associated gene expression in all cell types, leading to inflammatory microvascular dysfunction and changes in the tissue composition. Our study demonstrates the importance of creating high- resolution cellular maps and partitioning disease signals beyond epicardial coronary arteries and ischemic left ventricle to identify candidate mechanisms leading to more severe types of human cardiovascular disease. One-Sentence SummarySingle-cell dissection of ex vivo heart biopsies and pericardial fluid in ischemic heart disease and heart failure

molecular biology↗