Cell genomics最新文献

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.

Drug resistance is a major hurdle prohibiting effective treatment of many diseases, including cancer. Using model-guided designs, Leighow et al.¹ engineered a dual-switch selection gene drive system custom designed to combat drug-resistant tumors. By demonstrating remarkable killing efficacies in preclinical models using human non-small lung cancer cells in vitro and in mice, this work describes an attractive mindset to develop next-generation anticancer therapies.

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.

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.

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.

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.

Chondrichthyes is an important lineage to reconstruct the evolutionary history of vertebrates. Here, we analyzed genome synteny for six chondrichthyan chromosome-level genomes. Our comparative analysis reveals a slow evolutionary rate of chromosomal changes, with infrequent but independent fusions observed in sharks, skates, and chimaeras. The chondrichthyan common ancestor had a proto-vertebrate-like karyotype, including the presence of 18 microchromosome pairs. The X chromosome is a conversed microchromosome shared by all sharks, suggesting a likely common origin of the sex chromosome at least 181 million years ago. We characterized the Y chromosomes of two sharks that are highly differentiated from the X except for a small young evolutionary stratum and a small pseudoautosomal region. We found that shark sex chromosomes lack global dosage compensation but that dosage-sensitive genes are locally compensated. Our study on shark chromosome evolution enhances our understanding of shark sex chromosomes and vertebrate chromosome evolution.

Several X-linked genes escape from X chromosome inactivation (XCI), while differences in escape across cell types and tissues are still poorly characterized. Here, we developed scLinaX for directly quantifying relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA sequencing (scRNA-seq) data. The scLinaX and differentially expressed gene analyses with large-scale blood scRNA-seq datasets consistently identified the stronger escape in lymphocytes than in myeloid cells. An extension of scLinaX to a 10x multiome dataset (scLinaX-multi) suggested a stronger escape in lymphocytes than in myeloid cells at the chromatin-accessibility level. The scLinaX analysis of human multiple-organ scRNA-seq datasets also identified the relatively strong degree of escape from XCI in lymphoid tissues and lymphocytes. Finally, effect size comparisons of genome-wide association studies between sexes suggested the underlying impact of escape on the genotype-phenotype association. Overall, scLinaX and the quantified escape catalog identified the heterogeneity of escape across cell types and tissues.