Cell genomics最新文献

Genetic variants in ABCA7, an Alzheimer's disease (AD)-associated gene, elevate AD risk, yet its functional relevance to the etiology is unclear. We generated a CRISPR-Cas9-mediated abca7 knockout zebrafish to explore ABCA7's role in AD. Single-cell transcriptomics in heterozygous abca7^+/- knockout combined with Aβ42 toxicity revealed that ABCA7 is crucial for neuropeptide Y (NPY), brain-derived neurotrophic factor (BDNF), and nerve growth factor receptor (NGFR) expressions, which are crucial for synaptic integrity, astroglial proliferation, and microglial prevalence. Impaired NPY induction decreased BDNF and synaptic density, which are rescuable with ectopic NPY. In induced pluripotent stem cell-derived human neurons exposed to Aβ42, ABCA7^-/- suppresses NPY. Clinical data showed reduced NPY in AD correlated with elevated Braak stages, genetic variants in NPY associated with AD, and epigenetic changes in NPY, NGFR, and BDNF promoters linked to ABCA7 variants. Therefore, ABCA7-dependent NPY signaling via BDNF-NGFR maintains synaptic integrity, implicating its impairment in increased AD risk through reduced brain resilience.

Colorectal cancer (CRC) ranks as the second leading cause of cancer deaths globally. In recent years, short-read single-cell RNA sequencing (scRNA-seq) has been instrumental in deciphering tumor heterogeneities. However, these studies only enable gene-level quantification but neglect alterations in transcript structures arising from alternative end processing or splicing. In this study, we integrated short- and long-read scRNA-seq of CRC samples to build an isoform-resolution CRC transcriptomic atlas. We identified 394 dysregulated transcript structures in tumor epithelial cells, including 299 resulting from various combinations of splicing events. Second, we characterized genes and isoforms associated with epithelial lineages and subpopulations exhibiting distinct prognoses. Among 31,935 isoforms with novel junctions, 330 were supported by The Cancer Genome Atlas RNA-seq and mass spectrometry data. Finally, we built an algorithm that integrated novel peptides derived from open reading frames of recurrent tumor-specific transcripts with mass spectrometry data and identified recurring neoepitopes that may aid the development of cancer vaccines.

Single-cell RNA sequencing (scRNA-seq) enables comprehensive characterization of the micro-evolutionary processes of B cells during an adaptive immune response, capturing features of somatic hypermutation (SHM) and class switch recombination (CSR). Existing phylogenetic approaches for reconstructing B cell evolution have primarily focused on the SHM process alone. Here, we present tree inference of B cell clonal lineages (TRIBAL), an algorithm designed to optimally reconstruct the evolutionary history of B cell clonal lineages undergoing both SHM and CSR from scRNA-seq data. Through simulations, we demonstrate that TRIBAL produces more comprehensive and accurate B cell lineage trees compared to existing methods. Using real-world datasets, TRIBAL successfully recapitulates expected biological trends in a model affinity maturation system while reconstructing evolutionary histories with more parsimonious class switching than state-of-the-art methods. Thus, TRIBAL significantly improves B cell lineage tracing, useful for modeling vaccine responses, disease progression, and the identification of therapeutic antibodies.

The characterization of somatic genomic variation associated with the biology of tumors is fundamental for cancer research and personalized medicine, as it guides the reliability and impact of cancer studies and genomic-based decisions in clinical oncology. However, the quality and scope of tumor genome analysis across cancer research centers and hospitals are currently highly heterogeneous, limiting the consistency of tumor diagnoses across hospitals and the possibilities of data sharing and data integration across studies. With the aim of providing users with actionable and personalized recommendations for the overall enhancement and harmonization of somatic variant identification across research and clinical environments, we have developed ONCOLINER. Using specifically designed mosaic and tumorized genomes for the analysis of recall and precision across somatic SNVs, insertions or deletions (indels), and structural variants (SVs), we demonstrate that ONCOLINER is capable of improving and harmonizing genome analysis across three state-of-the-art variant discovery pipelines in genomic oncology.

Asthma is a complex disease caused by genetic and environmental factors. Studies show that wheezing during rhinovirus infection correlates with childhood asthma development. Over 150 non-coding risk variants for asthma have been identified, many affecting gene regulation in T cells, but the effects of most risk variants remain unknown. We hypothesized that airway epithelial cells could also mediate genetic susceptibility to asthma given they are the first line of defense against respiratory viruses and allergens. We integrated genetic data with transcriptomics of airway epithelial cells subject to different stimuli. We demonstrate that rhinovirus infection significantly upregulates childhood-onset asthma-associated genes, particularly in non-ciliated cells. This enrichment is also observed with influenza infection but not with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or cytokine activation. Overall, our results suggest that rhinovirus infection is an environmental factor that interacts with genetic risk factors through non-ciliated airway epithelial cells to drive childhood-onset asthma.

The mutational landscape of an individual's cancer can inform on its molecular state and be used as prognostic and therapeutic markers. The study by Barbour et al.¹ analyzes mutational patterns in bladder cancer samples to uncover new biological insights into the ERCC2 gene function and develop new predictive prognostic tools.

DNA is folded into higher-order structures that shape and are shaped by genome function. The role of long-range loops in the establishment of new gene expression patterns during cell fate transitions remains poorly understood. Here, we investigate the link between cell-specific loops and RNA polymerase II (RNA Pol II) during neural lineage commitment. We find thousands of loops decommissioned or gained de novo upon differentiation of human induced pluripotent stem cells (hiPSCs) to neural progenitor cells (NPCs) and post-mitotic neurons. During hiPSC-to-NPC and NPC-to-neuron transitions, genes changing from RNA Pol II initiation to elongation are >4-fold more likely to anchor cell-specific loops than repressed genes. Elongated genes exhibit significant mRNA upregulation when connected in cell-specific promoter-enhancer loops but not invariant promoter-enhancer loops or promoter-promoter loops or when unlooped. Genes transitioning from repression to RNA Pol II initiation exhibit a slight mRNA increase independent of loop status. Our data link cell-specific loops and robust RNA Pol II-mediated elongation during neural cell fate transitions.

Crosstalk between N⁶-methyladenosine (m⁶A) and epigenomes is crucial for gene regulation, but its regulatory directionality and disease significance remain unclear. Here, we utilize quantitative trait loci (QTLs) as genetic instruments to delineate directional maps of crosstalk between m⁶A and two epigenomic traits, DNA methylation (DNAme) and H3K27ac. We identify 47 m⁶A-to-H3K27ac and 4,733 m⁶A-to-DNAme and, in the reverse direction, 106 H3K27ac-to-m⁶A and 61,775 DNAme-to-m⁶A regulatory loci, with differential genomic location preference observed for different regulatory directions. Integrating these maps with complex diseases, we prioritize 20 genome-wide association study (GWAS) loci for neuroticism, depression, and narcolepsy in brain; 1,767 variants for asthma and expiratory flow traits in lung; and 249 for coronary artery disease, blood pressure, and pulse rate in muscle. This study establishes disease regulatory paths, such as rs3768410-DNAme-m⁶A-asthma and rs56104944-m⁶A-DNAme-hypertension, uncovering locus-specific crosstalk between m⁶A and epigenomic layers and offering insights into regulatory circuits underlying human diseases.

Understanding the roles played by centromeres in chromosome evolution and speciation is complicated by the fact that centromeres comprise large arrays of tandemly repeated satellite DNA, which hinders high-quality assembly. Here, we used long-read sequencing to generate nearly complete genome assemblies for four karyotypically diverse Papaver species, P. setigerum (2n = 44), P. somniferum (2n = 22), P. rhoeas (2n = 14), and P. bracteatum (2n = 14), collectively representing 45 gapless centromeres. We identified four centromere satellite (cenSat) families and experimentally validated two representatives. For the two allopolyploid genomes (P. somniferum and P. setigerum), we characterized the subgenomic distribution of each satellite and identified a "homogenizing" phase of centromere evolution in the aftermath of hybridization. An interspecies comparison of the peri-centromeric regions further revealed extensive centromere-mediated chromosome rearrangements. Taking these results together, we propose a model for studying cenSat competition after hybridization and shed further light on the complex role of the centromere in speciation.