The UCSC Genome Browser database: 2024 update

Identification of Transdiagnostic Childhood Externalizing Pathology Within an Electronic Medical Records Database and Application to the Analysis of Rare Copy Number Variation

Externalizing traits and behaviors are broadly defined by impairments in self-regulation and impulse control that typically begin in childhood and adolescence. Externalizing behaviors, traits, and symptoms span a range of traditional psychiatric diagnostic categories. In this study, we sought to generate an algorithm that could reliably identify transdiagnostic childhood-onset externalizing cases and controls within a university hospital electronic health record (EHR) database. Within the Vanderbilt University Medical Center (VUMC) EHR, our algorithm identified cases with a clinician-validated positive predictive value of 90% and controls with a negative predictive value of 88%. In individuals of genetically defined European ancestry (CEU-clustered; Ncase = 487, Ncontrol = 5638), case status was significantly associated with psychiatric comorbidity and with elevated externalizing polygenic scores (OR: 1.20; 95% CI: 1.09-1.33; p = 1.14 × 10-3; based on published genome-wide association data). To test whether our cohort definitions could be applied to generate novel genetic insights, we examined rare (allele frequency < 0.5%) copy number variation. An association (OR: 9.70; CI: 3.24-29.0) was identified in the CEU-clustered cohort on chromosome 2 (chr2: 45,408,678-45,551,530; duplication), although the statistical strength of this association was modest (p = 0.052). We also examined the role of an externalizing burden score based on the number of externalizing diagnoses present in cases and found similar results to our case-control analysis. This analysis identified several other statistically significant CNV region associations. This study provides a framework for identifying childhood externalizing case-control cohorts within an EHR. Future work should validate this framework within other health systems. A broadly applicable algorithm, like this one, may allow for detection of rare outcomes or outcomes in populations historically excluded from genomic research through meta-analysis of data across health care systems.

A multi-tissue atlas of allelic-specific expression reveals the characteristics, mechanisms, and relationship with dominant effects in cattle

BACKGROUND

Allele-specific expression (ASE) analysis is a crucial tool for validating expression quantitative trait loci (eQTLs), identifying causal variants associated with complex traits, and investigating the genetic mechanisms underlying heterosis. In this study, we characterized ASE variants across 35 tissues using 7532 publicly available RNA-seq datasets. Additionally, we explored the mechanisms driving ASE through integration with epigenomic data and examined the relationship between ASE and dominance effects on gene expression and milk-related traits in Holstein cattle.

RESULTS

ASE variants exhibited stronger tissue specificity and lower reproducibility compared to eQTLs. Interestingly, variants with opposite directional effects demonstrated greater resilience across diverse environments. Functional annotation revealed that ASE variants were enriched in both enhancer and promoter regions during transcription and implicated in post-transcriptional and translational processes, including mutations that affect mRNA splicing and trigger nonsense-mediated decay. Analysis of eQTLs, splicing QTLs (sQTLs), and validated QTLs associated with milk-related traits in Holstein cattle, coupled with enrichment analysis in QTL databases and effect size evaluation, indicated that ASE variants were more closely aligned with dominant effects than additive effects, particularly in reproductive and immune-related tissues/traits, which exhibited higher levels of heterosis.

CONCLUSIONS

Our findings not only enhance our understanding of the genetic mechanisms underlying heterosis and ASE formation but also provide a valuable resource of regulatory variants that can be leveraged to improve economic traits through molecular breeding or the strategic exploitation of heterosis.

Specific targeting of brain endothelial cells using enhancer AAV vectors

Brain endothelial cells (BECs) in brain vasculature are critical structural and functional components of the blood brain barrier (BBB). Adeno-associated virus (AAV) capsids have previously been genetically engineered to confer specificity to endothelial cells, but these capsids show limited endothelial cell specificity that varies by delivery conditions. We developed a set of new BEC-enhancer AAV vectors that specifically target BECs based on the cis-regulatory elements identified from single-cell epigenetic datasets. Ex vivo and in vivo characterization of BEC-enhancer AAVs in wild-type, Ai9 reporter, and Alzheimer's disease model mouse brains show their utility for high transduction selectivity of the BECs with little off-target transduction in the liver. Our BEC-enhancer AAVs target the brain vasculature by systemic administration and can be minimally invasive in terms of the route of administration. They are useful new tools for delivering genetic payloads specifically to BECs for normal and diseased brain studies.

Global DNA methylation differences involving germline structural variation impact gene expression in pediatric brain tumors

The extent of genetic variation and its influence on gene expression across multiple tissue and cellular contexts is still being characterized, with germline Structural Variants (SVs) being historically understudied. DNA methylation also represents a component of normal germline variation across individuals. Here, we combine germline SVs (by short-read sequencing) with tumor DNA methylation across 1292 pediatric brain tumor patients. For thousands of methylation probes for CpG Islands (CGIs) or enhancers, rare and common SV breakpoints upstream or downstream associate with differential methylation in tumors spanning various histologic types, a significant subset involving genes with SV-associated differential expression. Cancer predisposition genes involving SV-associated differential methylation and expression include MSH2, RSPA, and PALB2. SV breakpoints falling within CGIs or histone marks H3K36me3 or H3K9me3 associate with differential CGI methylation. Genes with SVs and CGI methylation associated with patient survival include POLD4. Our results capture a class of normal phenotypic variation having disease implications.

Elucidating the Genetic Underpinnings of Human Musculoskeletal System Aging Through Genomic Structural Equation Modeling

The genetic architecture underlying traits related to Human Musculoskeletal System Aging (MSA) remains largely unexplored. In this study, we conducted a large-scale multivariate genome-wide association study (GWAS) of MSA utilizing Genomic Structural Equation Modeling (Genomic SEM). We estimated causal single nucleotide polymorphisms (SNPs) associated with independent variation and identified 14 genome-wide significant loci (mean.PP > 0.95). We employed multiple transcriptome-wide association methods to analyze tissue, cellular levels, and genomic elements, identifying loci with high relevance to MSA susceptibility, along with associated element information. Our research represents the first comprehensive delineation of the genetic architecture of Musculoskeletal System Aging through a GWAS of unmeasured phenotype.

Human-specific genomic evolution of a regulatory network enables fine-tuning of N-cadherin gene expression

Androgen receptor (AR), a member of the nuclear receptor superfamily controls prostate epithelial cell plasticity by repressing a panel of genes involved in epithelial-mesenchymal transition (EMT), including the human CDH2 gene encoding N-cadherin. At the opposite, pathological AR variants such as AR-V7 associated with prostate tumor progression upregulate those EMT genes. Here, focusing on the human CDH2 gene, we show that this duality between AR and AR-V7 relies on a potential human accelerated region present in the intron 1. This fastest-evolving region of the human genome is actually a variable number tandem repeat (VNTR) comprising 24 repetitions of a DNA sequence that englobes binding sites for steroid hormone receptors, recombination signal binding protein for immunoglobulin kappa j region (RBPJ) an effector of the Notch pathway, and zinc finger e-box binding homeobox 1 (ZEB1). Genomic DNA sequencing, multiple sequence alignment, data mining, as well as protein-DNA interaction and gene expression analyses indicate that this VNTR constitutes a potential transcriptional hub for different transcription factors to control human CDH2 expression. Also, our data suggest that prostate tumor cells may unlock an up to now unknown molecular mechanism associated with a fine-tuned control of human CDH2 gene expression.

Most human DNA replication initiation is dispersed throughout the genome with only a minority within previously identified initiation zones

BACKGROUND

The identification of sites of DNA replication initiation in mammalian cells has been challenging. Here, we present unbiased detection of replication initiation events in human cells using BrdU incorporation and single-molecule nanopore sequencing.

RESULTS

Increases in BrdU incorporation allow us to measure DNA replication dynamics, including identification of replication initiation, fork direction, and termination on individual nanopore sequencing reads. Importantly, initiation and termination events are identified on single molecules with high resolution, throughout S-phase, genome-wide, and at high coverage at specific loci using targeted enrichment. We find a significant enrichment of initiation sites within the broad initiation zones identified by population-level studies. However, these focused initiation sites only account for ~ 20% of all identified replication initiation events. Most initiation events are dispersed throughout the genome and are missed by cell population approaches. This indicates that most initiation occurs at sites that, individually, are rarely used. These dispersed initiation sites contrast with the focused sites identified by population studies, in that they do not show a strong relationship to transcription or a particular epigenetic signature.

CONCLUSIONS

We show here that single-molecule sequencing enables unbiased detection and characterization of DNA replication initiation events, including the numerous dispersed initiation events that replicate most of the human genome.

scCompass: An Integrated Multi-Species scRNA-seq Database for AI-Ready

Emerging single-cell sequencing technology has generated large amounts of data, allowing analysis of cellular dynamics and gene regulation at the single-cell resolution. Advances in artificial intelligence enhance life sciences research by delivering critical insights and optimizing data analysis processes. However, inconsistent data processing quality and standards remain to be a major challenge. Here scCompass is proposed, which provides a comprehensive resource designed to build large-scale, multi-species, and model-friendly single-cell data collection. By applying standardized data pre-processing, scCompass integrates and curates transcriptomic data from nearly 105 million single cells across 13 species. Using this extensive dataset, it is able to identify stable expression genes (SEGs) and organ-specific expression genes (OSGs) in humans and mice. Different scalable datasets are provided that can be easily adapted for AI model training and the pretrained checkpoints with state-of-the-art single-cell foundation models. In summary, scCompass is highly efficient and scalable database for AI-ready, which combined with user-friendly data sharing, visualization, and online analysis, greatly simplifies data access and exploitation for researchers in single-cell biology (http://www.bdbe.cn/kun).

Sex-differentiated placental methylation and gene expression regulation has implications for neonatal traits and adult diseases

Sex differences in physiological and disease traits are pervasive and begin during early development, but the genetic architecture of these differences is largely unknown. Here, we leverage the human placenta, a transient organ during pregnancy critical to fetal development, to investigate the impact of sex in the regulatory landscape of placental autosomal methylome and transcriptome, and its relevance to health and disease. We find that placental methylation and its genetic regulation are extensively impacted by fetal sex, whereas sex differences in placental gene expression and its genetic regulation are limited. We identify molecular processes and regulatory targets that are enriched in a sex-specific manner, and find enrichment of imprinted genes in sex-differentiated placental methylation, including female-biased methylation within the well-known KCNQ1OT1/CDKN1C imprinting cluster of genes expressed in a parent-of-origin dependent manner. We establish that several sex-differentiated genetic effects on placental methylation and gene expression colocalize with birthweight and adult disease genetic associations, facilitating mechanistic insights on early life origins of health and disease outcomes shaped by sex.

Two rodent suborders have evolved missing amino acids in the lipid-binding region of apolipoprotein E

The order Rodentia comprises nearly 45% of all extant taxa, currently organized into 31 living families, some 450 genera, and roughly 2010 species (Kelt & Patton, 2020). Considering that rodents began evolving at least 66 million years ago, it is not surprising that they have diversified into five distinct suborders. With the advent of molecular biology, this difference can often be seen at the molecular level as well. Previous studies have indicated that the apolipoprotein E (APOE) of guinea pigs, belonging to the suborder Hystricomorpha, have fewer amino acids than have been reported for other suborders of Rodentia. Searching the genomic database for hystricomorph APOE genes, it was found that hystricomorphs were missing residues both in the vicinity of the hinge region and in the lipid-binding region of the apolipoprotein. In the hinge region, missing residues varied between 5 and 3, and in the latter region, seven residues were missing. The search also revealed that castorimorphs, although lacking the smaller of the two deletions, were also missing the same seven residue deletion as found in APOE of the hystricomorphs.

Mitochondrial membrane hyperpolarization modulates nuclear DNA methylation and gene expression through phospholipid remodeling

Maintenance of the mitochondrial inner membrane potential (ΔΨm) is critical for many aspects of mitochondrial function. While ΔΨm loss and its consequences are well studied, little is known about the effects of mitochondrial hyperpolarization. In this study, we used cells deleted of ATP5IF1 (IF1), a natural inhibitor of the hydrolytic activity of the ATP synthase, as a genetic model of increased resting ΔΨm. We found that the nuclear DNA hypermethylates when the ΔΨm is chronically high, regulating the transcription of mitochondrial, carbohydrate and lipid genes. These effects can be reversed by decreasing the ΔΨm and recapitulated in wild-type (WT) cells exposed to environmental chemicals that cause hyperpolarization. Surprisingly, phospholipid changes, but not redox or metabolic alterations, linked the ΔΨm to the epigenome. Sorted hyperpolarized WT and ovarian cancer cells naturally depleted of IF1 also showed phospholipid remodeling, indicating this as an adaptation to mitochondrial hyperpolarization. These data provide a new framework for how mitochondria can impact epigenetics and cellular biology to influence health outcomes, including through chemical exposures and in disease states.

Distinct adipose progenitor cells emerging with age drive active adipogenesis

Starting at middle age, adults often suffer from visceral adiposity and associated adverse metabolic disorders. Lineage tracing in mice revealed that adipose progenitor cells (APCs) in visceral fat undergo extensive adipogenesis during middle age. Thus, despite the low turnover rate of adipocytes in young adults, adipogenesis is unlocked during middle age. Transplantations quantitatively showed that APCs in middle-aged mice exhibited high adipogenic capacity cell-autonomously. Single-cell RNA sequencing identified a distinct APC population, the committed preadipocyte, age-enriched (CP-A), emerging at this age. CP-As demonstrated elevated proliferation and adipogenesis activity. Pharmacological and genetic manipulations indicated that leukemia inhibitory factor receptor signaling was indispensable for CP-A adipogenesis and visceral fat expansion. These findings uncover a fundamental mechanism of age-dependent adipose remodeling, offering critical insights into age-related metabolic diseases.

ReLume: Enhancing DNA storage data reconstruction with flow network and graph partitioning

DNA storage is an ideal alternative to silicon-based storage, but focusing on data writing alone cannot address the inevitable errors and durability issues. Therefore, we propose ReLume, a DNA storage data reconstruction method based on flow networks and graph partitioning technology, which can accomplish the data reconstruction task of millions of reads on a laptop with 24 GB RAM. The results show that ReLume copes well with many types of errors, more than doubles sequence recovery rates, and reduces memory usage by about 60 %. ReLume is 10 times more durable than other representative methods, meaning that data can be read without loss after 100 years. Results from the wet lab DNA storage dataset show that ReLume's sequence recovery rates of 73 % and 93.2 %, respectively, significantly outperform existing methods. In summary, ReLume effectively overcomes the accuracy and hardware limitations and provides a feasible idea for the portability of DNA storage.

A modular, Galaxy-based immunopeptidogenomic (iPepGen) analysis pipeline for discovery, verification, and prioritization of candidate cancer neoantigen peptides

Background

Characterizing peptide antigens, processed from tumor-specific proteoforms, and bound to the major histocompatibility complex, is critical for immuno-oncology research. Next-generation sequencing predicts candidate neoantigen peptides derived from DNA mutations and/or RNA transcripts coding proteoform sequences that differ from the reference proteome. Mass spectrometry (MS)-based immunopeptidomics identifies predicted, MHC-bound neoantigen peptides and other tumor antigens. This "immunopeptidogenomic" approach requires multi-omic software integration, challenging researchers with limited bioinformatics expertise and resources. As a solution, we developed the immunopeptidogenomic (iPepGen) pipeline in the Galaxy ecosystem. iPepGen is composed of five core workflow modules, available via publicly accessible, scalable Galaxy instances, accompanied by training resources to empower community adoption.

Findings

Using representative multi-omic data from malignant peripheral nerve sheath tumors, we demonstrate the operation of iPepGen modules with these functions: 1) Predict neoantigen candidates from sequencing data and generate customized protein sequence databases, including reference and non-reference neoantigen candidate sequences; 2) Discover neoantigen peptide candidates by sequence database searching of tandem mass spectrometry (MS/MS) immunopeptidomics data; 3) Verify discovered peptide candidates through a secondary peptide-centric evaluation method against the MS/MS dataset; 4) Visualize and classify the nature of verified neoantigen peptides encoded by the genome and/or transcriptome; 5) Prioritize neoantigens for further exploration and empirical validation.

Conclusions

We demonstrate the effectiveness of the iPepGen pipeline for candidate neoantigen discovery and characterization. With tools, workflows, and training resources available in the open Galaxy ecosystem, iPepGen should provide cancer researchers with a flexible and accessible informatics resource tailored to accelerating immuno-oncology studies.

Actionable genetic variants in 4,198 Scottish participants from the Orkney and Shetland founder populations and implementation of return of results

The benefits of returning clinically actionable genetic results to participants in research cohorts are accruing, yet such a genome-first approach is challenging. Here, we describe the implementation of return of such results in two founder populations from Scotland. Between 2005 and 2015, we recruited >4,000 adults with grandparents from Orkney and Shetland into the Viking Genes research cohort. The return of genetic data was not offered at baseline, but in 2023, we sent invitations to participants for consent to return of actionable genetic findings. We generated exome sequence data from 4,198 participants and used the American College of Medical Genetics and Genomics (ACMG) v.3.2 list of 81 genes, ClinVar review, and pathogenicity status, plus manual curation, to develop a pipeline to identify potentially actionable variants. We identified 104 individuals (2.5%) with 108 actionable genotypes at 39 variants in 23 genes and validated these. Working with the NHS Clinical Genetics service, which provided genetic counseling and clinical verification of the research results, and after expert clinical review, we notified 64 consenting participants (or their next of kin) of their actionable genotypes. Ten actionable variants across seven genes (BRCA1, BRCA2, ATP7B, TTN, KCNH2, MUTYH, and GAA) have risen 50- to >3,000-fold in frequency through genetic drift in ancestral island localities. Viking Genes is one of the first UK research cohorts to return actionable findings, providing an ethical and logistical exemplar of return of results. The genetic structure in the Northern Isles of Scotland with multiple founder effects provides a unique opportunity for a tailored approach to disease prevention through genetic screening.

The sweet and the bitter sides of galectin-1 in immunity: its role in immune cell functions, apoptosis, and immunotherapies for cancer with a focus on T cells

Galectin-1 (Gal-1), a member of the β-galactoside-binding soluble lectin family, is a double-edged sword in immunity. On one hand, it plays a crucial role in regulating diverse immune cell functions, including the apoptosis of activated T cells. These processes are key in resolving inflammation and preventing autoimmune diseases. On the other hand, Gal-1 has significant implications in cancer, where tumor cells and the tumor microenvironment (TME) (e.g., tumor-associated fibroblasts, myeloid-derived suppressor cells) secrete Gal-1 to evade immune surveillance and promote cancer cell growth. Within the TME, Gal-1 enhances the differentiation of tolerogenic dendritic cells, induces the apoptosis of effector T cells, and enhances the proliferation of regulatory T cells, collectively facilitating tumor immune escape. Therefore, targeting Gal-1 holds the potential to boost anti-tumor immunity and improve the efficacy of cancer immunotherapy. This review provides insights into the intricate role of Gal-1 in immune cell regulation, with an emphasis on T cells, and elucidates how tumors exploit Gal-1 for immune evasion and growth. Furthermore, we discuss the potential of Gal-1 as a therapeutic target to augment current immunotherapies across various cancer types.

Inhibition of PRC2 enables self-renewal of blastoid-competent naive pluripotent stem cells from chimpanzee

Naive pluripotent stem cells (PSCs) are counterparts of early epiblast in the mammalian embryo. Mouse and human naive PSCs differ in self-renewal requirements and extraembryonic lineage potency. Here, we investigated the generation of chimpanzee naive PSCs. Colonies generated by resetting or reprogramming failed to propagate. We discovered that self-renewal is enabled by inhibition of Polycomb repressive complex 2 (PRC2). Expanded cells show global transcriptome proximity to human naive PSCs and embryo pre-implantation epiblast, with shared expression of a subset of pluripotency transcription factors. Chimpanzee naive PSCs can transition to multilineage competence or can differentiate into trophectoderm and hypoblast, forming tri-lineage blastoids. They thus provide a higher primate comparative model for studying pluripotency and early embryogenesis. Genetic deletions confirm that PRC2 mediates growth arrest. Further, inhibition of PRC2 overcomes a roadblock to feeder-free propagation of human naive PSCs. Therefore, excess deposition of chromatin modification H3K27me3 is an unexpected barrier to naive PSC self-renewal.

Vitamin D-related genetic variants and prostate cancer risk in Black men

BACKGROUND

The relationship between vitamin D and prostate cancer has primarily been characterized among White men. Black men, however, have higher prostate cancer incidence and mortality rates, chronically low circulating vitamin D levels, and ancestry-specific genetic variants in vitamin D-related genes. Here, we examine critical genes in the vitamin D pathway and prostate cancer risk in Black men.

METHODS

We assessed a total of 73 candidate variants in genes (namely GC, CYP27A1, CYP27B1, CYP24A1, VDR, and RXRA) including functional variants previously associated with prostate cancer and circulating 25(OHD) in White men. Associations with prostate cancer risk were examined using genome-wide association study data for approximately 10,000 prostate cancer cases and 10,000 controls among Black men and over 85,000 cases and 91,000 controls among White men for comparison. A statistical significance threshold of 0.000685 was used to account for the 73 variants tested.

RESULTS

None of the variants examined were significantly associated with prostate cancer risk among Black men after multiple comparison adjustment. Suggestive associations (P < 0.05) for four variants were found in Black men, including two in RXRA (rs41400444 OR=1.09, 95 % CI: 1.01-1.17, P = 0.024 and rs10881574 OR = 0.93, 0.87-1.00, P = 0.046) and two in VDR (rs2853563 OR = 1.07, 1.01-1.13, P = 0.017 and rs1156882 OR = 1.06, 1.00-1.12, P = 0.045). Two variants in VDR were also positively associated with risk in White men (rs11568820 OR = 1.04, 1.02-1.06, P = 0.00024 and rs4516035 OR = 1.03, 1.01-1.04, P = 0.00055).

CONCLUSION

We observed suggestive associations between genetic variants in RXRA and VDR and prostate cancer risk in Black men. Future research exploring the relationship of vitamin D with cancer risk in Black men will need larger sample sizes to identify ancestry-specific variants relevant to risk in this population.

Caloric restriction prevents inheritance of polycystic ovary syndrome through oocyte-mediated DNA methylation reprogramming

Polycystic ovary syndrome (PCOS) is a prevalent metabolic and reproductive endocrine disorder with strong heritability. However, the independent role of oocytes in mediating this heritability remains unclear. Utilizing in vitro fertilization-embryo transfer and surrogacy, we demonstrated that oocytes from androgen-exposed mice (F1) transmitted PCOS-like traits to F2 and F3 generations. Notably, caloric restriction (CR) in F1 or F2 effectively prevented this transmission by restoring disrupted DNA methylation in oocyte genes related to insulin secretion and AMPK signaling pathways. Further detection in adult tissues of offspring revealed dysregulated DNA methylation and expression of those genes (e.g., Adcy3, Gnas, and Srebf1) were reversed by maternal CR. Moreover, similar benefits of CR were observed in aberrant embryonic methylome of women with PCOS. These findings elucidate the essential role of CR in preventing PCOS transmission via methylation reprogramming, emphasizing the importance of preconception metabolic management for women with PCOS.

Epigenome-Wide Association Study of Asthma Exacerbations in Europeans

BACKGROUND

Asthma exacerbations (AEs) represent the major contributor to the global asthma burden. Although genetic and environmental factors have been associated with AEs, the role of epigenetics remains uncovered.

OBJECTIVE

This study aimed to identify whole blood DNA methylation (DNAm) markers associated with AEs in Europeans.

METHODS

DNAm was assessed in 406 blood samples from Spanish individuals using the Infinium MethylationEPIC microarray (Illumina). An epigenome-wide association study was conducted to test the association of DNAm with AEs at differentially methylated positions, regions, and epigenetic modules. CpGs suggestively associated with AEs (false discovery rate [FDR] < 0.1) were followed up for replication in 222 European individuals, and the genome-wide significance (p < 9 × 10-8) was declared after meta-analyzing the discovery and replication samples. Additional assessment was performed using nasal tissue DNAm data from 155 Spanish individuals. The effects of genetic variation on DNAm were assessed through cis-methylation quantitative trait loci (meQTL) analysis. Enrichment analyses of previous EWAS signals were conducted.

RESULTS

Four CpGs were associated with AEs, and two were replicated and reached genomic significance in the meta-analysis (annotated to ZBTB16 and BAIAP2). Of those, CpG cg25345365 (ZBTB16) was cross-tissue validated in nasal epithelium (p= 0.003) and associated with five independent meQTLs (FDR < 0.05). Additionally, four differentially methylated regions and one module were significantly associated with AEs. Enrichment analyses revealed an overrepresentation of prior epigenetic associations with prenatal and environmental exposures, immune-mediated diseases, and mortality.

CONCLUSIONS

DNAm in whole blood and nasal samples may contribute to AEs in Europeans, capturing genetic and environmental risk factors.

MAFin: motif detection in multiple alignment files

MOTIVATION

Whole Genome and Proteome Alignments, represented by the multiple alignment file format, have become a standard approach in comparative genomics and proteomics. These often require identifying conserved motifs, which is crucial for understanding functional and evolutionary relationships. However, current approaches lack a direct method for motif detection within MAF files. We present MAFin, a novel tool that enables efficient motif detection and conservation analysis in MAF files to address this gap, streamlining genomic and proteomic research.

RESULTS

We developed MAFin, the first motif detection tool for Multiple Alignment Format files. MAFin enables the multithreaded search of conserved motifs using three approaches: (i) using user-specified k-mers to search the sequences. (ii) with regular expressions, in which case one or more patterns are searched, and (iii) with predefined Position Weight Matrices. Once the motif has been found, MAFin detects the motif instances and calculates the conservation across the aligned sequences. MAFin also calculates a conservation percentage, which provides information about the conservation levels of each motif across the aligned sequences, based on the number of matches relative to the length of the motif. A set of statistics enables the interpretation of each motif's conservation level, and the detected motifs are exported in JSON and CSV files for downstream analyses.

AVAILABILITY AND IMPLEMENTATION

MAFin is offered as a Python package under the GPL license as a multi-platform application and is available at: https://github.com/Georgakopoulos-Soares-lab/MAFin.

CellBouncer, A Unified Toolkit for Single-Cell Demultiplexing and Ambient RNA Analysis, Reveals Hominid Mitochondrial Incompatibilities

Pooled processing, in which cells from multiple sources are cultured or captured together, is an increasingly popular strategy for droplet-based single cell sequencing studies. This design allows efficient scaling of experiments, isolation of cell-intrinsic differences, and mitigation of batch effects. We present CellBouncer, a computational toolkit for demultiplexing and analyzing single-cell sequencing data from pooled experiments. We demonstrate that CellBouncer can separate and quantify multi-species and multi-individual cell mixtures, identify unknown mitochondrial haplotypes in cells, assign treatments from lipid-conjugated barcodes or CRISPR sgRNAs, and infer pool composition, outperforming existing methods. We also introduce methods to quantify ambient RNA contamination per cell, infer individual donors' contributions to the ambient RNA pool, and determine a consensus doublet rate harmonized across data types. Applying these tools to tetraploid composite cells, we identify a competitive advantage of human over chimpanzee mitochondria across 10 cell fusion lines and provide evidence for inter-mitochondrial incompatibility and mito-nuclear incompatibility between species.

Conservation assessment of human splice site annotation based on a 470-genome alignment

Despite many improvements over the years, the annotation of the human genome remains imperfect. The use of evolutionarily conserved sequences provides a strategy for selecting a high-confidence subset of the annotation. Using the latest whole-genome alignment, we found that splice sites from protein-coding genes in the high-quality MANE annotation are consistently conserved across >350 species. We also studied splice sites from the RefSeq, GENCODE, and CHESS databases not present in MANE. In addition, we analyzed the completeness of the alignment with respect to the human genome annotations and described a method that would allow us to fix up to 60% of the missing alignments of the protein-coding exons. We trained a logistic regression classifier to distinguish between the conservation exhibited by sites from MANE versus sites chosen randomly from neutrally evolving sequences. We found that splice sites classified by our model as well-supported have lower single nucleotide polymorphism rates and better transcriptomic evidence. We then computed a subset of transcripts using only "well-supported" splice sites or ones from MANE. This subset is enriched in high-confidence transcripts of the major gene catalogs that appear to be under purifying selection and are more likely to be correct and functionally relevant.

True length of diverse capped RNA sequencing (TLDR-seq): 5'-3'-end sequencing of capped RNAs regardless of 3'-end status

Analysis of transcript function is greatly aided by knowledge of the full-length RNA sequence. New long-read sequencing enabled by Oxford Nanopore and PacBio devices have the potential to provide full-length transcript information; however, standard methods still lack the ability to capture true RNA 5' ends and select for polyadenylated (pA+) transcripts only. Here, we present a method that, by utilizing cap trapping and 3'-end adapter ligation, sequences transcripts between their exact 5' and 3' ends regardless of polyadenylation status and without the need for ribosomal RNA depletion, with the ability to characterize polyadenylation length of RNAs, if any. The method shows high reproducibility, can faithfully detect 5' ends, 3' ends and splice junctions, and produces gene-expression estimates that are highly correlated to those of short-read sequencing techniques. We also demonstrate that the method can detect and sequence full-length nonadenylated (pA-) RNAs, including long noncoding RNAs, promoter upstream transcripts, and enhancer RNAs, and present cases where pA+ and pA- RNAs show preferences for different but closely located transcription start sites. Our method is therefore useful for the characterization of diverse capped RNA species and analysis of relationships between transcription initiation, termination, and RNA processing.

Nucleosome binding by TP53, TP63, and TP73 is determined by the composition, accessibility, and helical orientation of their binding sites

The TP53 family of transcription factors plays key roles in driving development and combating cancer by regulating gene expression. TP53, TP63, and TP73-the three members of the TP53 family-regulate gene expression by binding to their DNA binding sites, many of which are situated within nucleosomes. To thoroughly examine the nucleosome-binding abilities of the TP53 family, we used Pioneer-seq, a technique that assesses a transcription factor's binding affinity to its DNA-binding sites at all possible positions within the nucleosome core particle. Using Pioneer-seq, we analyzed the binding affinities of TP53, TP63, and TP73 to 10 TP53 family binding sites across the nucleosome core particle. We find that the affinities of TP53, TP63, and TP73 for nucleosomes are primarily determined by the positioning of TP53 family binding sites within nucleosomes; TP53 family members bind strongly to the more accessible edges of nucleosomes but weakly to the less accessible centers of nucleosomes. Our results further show that the DNA-helical orientation of TP53 family binding sites within nucleosomal DNA impacts the nucleosome-binding affinities of TP53 family members, with binding-site composition impacting the affinity of each TP53 family member only when the binding-site location is accessible. Taken together, our results show that the accessibility, composition, and helical orientation of TP53 family binding sites collectively determine the nucleosome-binding affinities of TP53, TP63, and TP73. These findings help explain the rules underlying TP53 family-nucleosome binding and thus provide requisite insight into how we may better control gene expression changes involved in development and tumor suppression.

High-recombining genomic regions affect demography inference based on ancestral recombination graphs

Multiple methods of demography inference are based on the ancestral recombination graph. This powerful approach uses observed mutations to model local genealogies changing along chromosomes by historical recombination events. However, inference of underlying genealogies is difficult in regions with high recombination rate relative to mutation rate due to the lack of mutations representing genealogies. Despite the prevalence of high-recombining genomic regions in some organisms, such as birds, its impact on demography inference based on ancestral recombination graphs has not been well studied. Here, we use population genomic simulations to investigate the impact of high-recombining regions on demography inference based on ancestral recombination graphs. We demonstrate that inference of effective population size and the time of population split events is systematically affected when high-recombining regions cover wide breadths of the chromosomes. Excluding high-recombining genomic regions can practically mitigate this impact, and population genomic inference of recombination maps is informative in defining such regions although the estimated values of local recombination rate can be biased. Finally, we confirm the relevance of our findings in empirical analysis by contrasting demography inferences applied for a bird species, the Eurasian blackcap (Sylvia atricapilla), using different parts of the genome with high and low recombination rates. Our results suggest that demography inference methods based on ancestral recombination graphs should be carried out with caution when applied in species whose genomes contain long stretches of high-recombining regions.

SNPeBoT: a tool for predicting transcription factor allele specific binding

BACKGROUND

Mutations in non-coding regulatory regions of DNA may lead to disease through the disruption of transcription factor binding. However, our understanding of binding patterns of transcription factors and the effects that changes to their binding sites have on their action remains limited. To address this issue we trained a Deep learning model to predict the effects of Single Nucleotide Polymorphisms (SNP) on transcription factor binding. Allele specific binding (ASB) data from Chromatin Immunoprecipitation sequencing (ChIP-seq) experiments were paired with high sequence-identity DNA binding Domains assessed in Protein Binding Microarray (PBM) experiments. For each transcription factor a paired DNA binding Domain was selected from which we derived E-score profiles for reference and alternate DNA sequences of ASB events. A Convolutional Neural Network (CNN) was trained to predict whether these profiles were indicative of ASB gain/loss or no change in binding. 18211 E-score profiles from 113 transcription factors were split into train, validation and test data. We compared the performance of the trained model with other available platforms for predicting the effect of SNP on transcription factor binding. Our model demonstrated increased accuracy and ASB recall in comparison to the best scoring benchmark tools.

CONCLUSION

In this paper we present our model SNPeBoT (Single Nucleotide Polymorphism effect on Binding of Transcription Factors) in its standalone and web server form. The increased recovery and prediction accuracy of allele specific binding events could prove useful in discovering non-coding mutations relevant to disease.

Assessing genome conservation on pangenome graphs with PanSel

Motivation

With more and more telomere-to-telomere genomes assembled, pangenomes make it possible to capture the genomic diversity of a species. Because they introduce less biases, pangenomes, represented as graphs, tend to supplant the usual linear representation of a reference genome, augmented with variations. However, this major change requires new tools adapted to this data structure. Among the numerous questions that can be addressed to a pangenome graph is the search for conserved or divergent genes.

Results

In this article, we present a new tool, named PanSel, which computes a conservation score for each segment of the genome, and finds genomic regions that are significantly conserved, or divergent. PanSel can be used on prokaryotes and eukaryotes, with a sequence identity not less than 98%.

Availability and implementation

PanSel, written in C++11 with no dependency, is available at https://github.com/mzytnicki/pansel.

Regulatory Plasticity of the Human Genome

Evolutionary turnover in noncoding regions has driven phenotypic divergence during past speciation events and continues to facilitate environmental adaptation through variants. We used a deep learning model to identify the substrates of regulatory turnover using genome-wide mutations mimicking three evolutionary pathways: recent history (human-chimp substitutions), modern population (human population variation), and mutational susceptibility (random mutations). We observed enhancer turnover in approximately 6% of the whole genome, with more than 80% of the novel activity arising from repurposing of enhancers between cell types. Frequency of turnover in a cell type is remarkably similar across the three pathways, despite only ∼19% overlap in the source regions. The majority of turnover loci were found to be localized within 100 kb of a gene, with the highest turnover occurring near neurodevelopmental genes including CNTNAP2, NPAS3, and AUTS2. Flanking enhancers of these genes undergo high turnover irrespective of the mutational model pathway, suggesting a high plasticity in neurocognitive evolution. Based on susceptibility to random mutations, these enhancers were identified as vulnerable by nature and feature a higher abundance of cell type-specific transcription factor binding sites. Our findings suggest that enhancer repurposing within vulnerable loci drives regulatory innovation while keeping the core regulatory networks intact.

RIBOSS detects novel translational events by combining long- and short-read transcriptome and translatome profiling

Ribosome profiling is a high-throughput sequencing technique that captures the positions of translating ribosomes on RNAs. Recent advancements in ribosome profiling include achieving highly phased ribosome footprints for plant translatomes and more recently for bacterial translatomes. This substantially increases the specificity of detecting open reading frames (ORFs) that can be translated, such as small ORFs located upstream and downstream of the annotated ORFs. However, most genomes (e.g. bacterial genomes) lack the annotations for the transcription start and termination sites. This hinders the systematic discovery of novel ORFs in the 'untranslated' regions in ribosome profiling data. Here, we develop a new computational pipeline called RIBOSS to discover noncanonical ORFs and assess their translational potential against annotated ORFs. The RIBOSS Python modules are versatile, and we use them to analyse both prokaryotic and eukaryotic data. We present a resulting list of noncanonical ORFs with high translational potential in Homo sapiens, Arabidopsis thaliana, and Salmonella enterica. We further illustrate RIBOSS utility when studying organisms with incomplete transcriptome annotations. We leverage long-read and short-read data for reference-guided transcriptome assembly and highly phased ribosome profiling data for detecting novel translational events in the assembled transcriptome for S. enterica. In sum, RIBOSS is the first integrated computational pipeline for noncanonical ORF detection and translational potential assessment that incorporates long- and short-read sequencing technologies to investigate translation. RIBOSS is freely available at https://github.com/lcscs12345/riboss.

Machine learning-based prediction reveals kinase MAP4K4 regulates neutrophil differentiation through phosphorylating apoptosis-related proteins

Neutrophils, an essential innate immune cell type with a short lifespan, rely on continuous replenishment from bone marrow (BM) precursors. Although it is established that neutrophils are derived from the granulocyte-macrophage progenitor (GMP), the molecular regulators involved in the differentiation process remain poorly understood. Here we developed a random forest-based machine-learning pipeline, NeuRGI (Neutrophil Regulatory Gene Identifier), which utilized Positive-Unlabeled Learning (PU-learning) and neural network-based in silico gene knockout to identify neutrophil regulators. We interrogated features including gene expression dynamics, physiological characteristics, pathological relatedness, and gene conservation for the model training. Our identified pipeline leads to identifying Mitogen-Activated Protein Kinase-4 (MAP4K4) as a novel neutrophil differentiation regulator. The loss of MAP4K4 in hematopoietic stem cells and progenitors in mice induced neutropenia and impeded the differentiation of neutrophils in the bone marrow. By modulating the phosphorylation level of proteins involved in cell apoptosis, such as STAT5A, MAP4K4 delicately regulates cell apoptosis during the process of neutrophil differentiation. Our work presents a novel regulatory mechanism in neutrophil differentiation and provides a robust prediction model that can be applied to other cellular differentiation processes.

Soluble Factors and Mechanisms Regulated by Sialylated IgG Signaling

Inflammation is a complex biological response that can be both induced and actively suppressed by IgG-Fc gamma receptor (FcγR) interactions. This review explores the role of IgG sialylation in reducing or blocking inflammatory responses. We first revisit foundational studies that established the anti-inflammatory properties of sialylated IgG1 Fc. These early investigations revealed that the sialylated fraction is crucial for intravenous immunoglobulin's (IVIg's) ability to reduce inflammation in many autoinflammatory diseases and defined a paracrine signaling mechanism underlying this activity. Next, we discuss a recently identified mechanism whereby sialylated IgG directly induces RE1-Silencing Transcription Factor (REST) which functions as a transcriptional repressor of NF-κB1. This mechanism suggests a very broad role for sialylated IgG signaling in inflammation control since NF-κB is a central mediator of responses downstream of diverse activating receptors on both adaptive and innate immune cells. Finally, we review a set of soluble factors that are suppressed by sialylated IgG signaling in the murine airway and in purified human macrophages, providing additional insight into mechanisms by which sialylated IgG contributes to broad inflammatory control.

Brassica Panache: A multi-species graph pangenome representing presence absence variation across forty-one Brassica genomes

Brassicas are an economically important crop species that provide a source of healthy oil and vegetables. With the rising population and the impact of climate change on agriculture, there is an increasing need to improve agronomically important traits of crops such as Brassica. The genomes of plant species have significant sequence presence absence variation (PAV), which is a source of genetic variation that can be used for crop improvement, and this species variation can be captured through the construction of pangenomes. Graph pangenomes are a recent reference format that represent the genomic variation with a species or population as alternate paths in a sequence graph. Graph pangenomes contain information on alignment, PAV, and annotation. Here we present the first multi-species graph pangenome for Brassica visualized with pangenome analyzer with chromosomal exploration (Panache).

Single-cell assay for transposase-accessible chromatin sequencing of human clear cell renal cell carcinoma

Regulating the occurrence and progression of tumor cells at the epigenetic level is a new insight of clear cell renal cell carcinoma (ccRCC). Chromatin accessibility is an important pathway of epigenetic regulation, which may explain the mystery of tumor occurrence. Assay for transposase-accessible chromatin sequencing (ATAC-seq) provides insight into the epigenetic regulatory features of ccRCC, especially at the single-cell level. In this study, we performed scATAC-seq of 3 ccRCC samples and captured a total of 18,703 high-quality cell nuclei and 104,818 unique peaks. Our protocol for nuclear extraction was reliable and stable, which can be used to deal with fresh and frozen single-cell suspensions. We presented basic methods for scATAC-seq data analysis, such as cell clustering, gene activity scoring, cell subtype specific peaks, transcription factors, motif and motif footprinting analysis. Taken together, our data indicated the valuable epigenetic features of ccRCC, which will provide more references for the study of ccRCC.

Interactive visualization and interpretation of pangenome graphs by linear reference-based coordinate projection and annotation integration

With the increasing availability of high-quality genome assemblies, pangenome graphs emerged as a new paradigm in the genomic field for identifying, encoding, and presenting genomic variation at both the population and species level. However, it remains challenging to truly dissect and interpret pangenome graphs via biologically informative visualization. To facilitate better exploration and understanding of pangenome graphs toward novel biological insights, here we present a web-based interactive visualization and interpretation framework for linear reference-projected pangenome graphs (VRPG). VRPG provides efficient and intuitive support for exploring and annotating pangenome graphs along a linear-genome-based coordinate system (e.g., that of a primary linear reference genome). Moreover, VRPG offers many unique features such as in-graph path highlighting for graph-constituent input assemblies, copy number characterization for graph-embedding nodes, and graph-based mapping for query sequences, all of which are highly valuable for researchers working with pangenome graphs. Additionally, VRPG enables side-by-side visualization between the graph-based pangenome representation and the conventional primary linear reference genome-based feature annotations, therefore seamlessly bridging the graph and linear genomic contexts. To further demonstrate its functionality and scalability, we applied VRPG to the cutting-edge yeast and human reference pangenome graphs derived from hundreds of high-quality genome assemblies via a dedicated web portal and examined their local genome diversity in the graph contexts.

Advancing long-read nanopore genome assembly and accurate variant calling for rare disease detection

More than 50% of families with suspected rare monogenic diseases remain unsolved after whole-genome analysis by short-read sequencing (SRS). Long-read sequencing (LRS) could help bridge this diagnostic gap by capturing variants inaccessible to SRS, facilitating long-range mapping and phasing and providing haplotype-resolved methylation profiling. To evaluate LRS's additional diagnostic yield, we sequenced a rare-disease cohort of 98 samples from 41 families, using nanopore sequencing, achieving per sample ∼36× average coverage and 32-kb read N50 from a single flow cell. Our Napu pipeline generated assemblies, phased variants, and methylation calls. LRS covered, on average, coding exons in ∼280 genes and ∼5 known Mendelian disease-associated genes that were not covered by SRS. In comparison to SRS, LRS detected additional rare, functionally annotated variants, including structural variants (SVs) and tandem repeats, and completely phased 87% of protein-coding genes. LRS detected additional de novo variants and could be used to distinguish postzygotic mosaic variants from prezygotic de novos. Diagnostic variants were established by LRS in 11 probands, with diverse underlying genetic causes including de novo and compound heterozygous variants, large-scale SVs, and epigenetic modifications. Our study demonstrates LRS's potential to enhance diagnostic yield for rare monogenic diseases, implying utility in future clinical genomics workflows.

Comparative Genomics Reveals LINE-1 Recombination with Diverse RNAs

Long interspersed element-1 (LINE-1, L1) retrotransposons are the most abundant protein-coding transposable elements (TE) in mammalian genomes, and have shaped genome content over 170 million years of evolution. LINE-1 is self-propagating and mobilizes other sequences, including Alu elements. Occasionally, LINE-1 forms chimeric insertions with non-coding RNAs and mRNAs. U6 spliceosomal small nuclear RNA/LINE-1 chimeras are best known, though there are no comprehensive catalogs of LINE-1 chimeras. To address this, we developed TiMEstamp, a computational pipeline that leverages multiple sequence alignments (MSA) to estimate the age of LINE-1 insertions and identify candidate chimeric insertions where an adjacent sequence arrives contemporaneously. Candidates were refined by detecting hallmark features of L1 retrotransposition, such as target site duplication (TSD). Applying this pipeline to the human genome, we recovered all known species of LINE-1 chimeras and discovered new chimeric insertions involving small RNAs, Alu elements, and mRNA fragments. Some insertions are compatible with known mechanisms, such as RNA ligation. Other structures nominate novel mechanisms, such as trans-splicing. We also see evidence that LINE-1 loci with defunct promoters can acquire regulatory elements from nearby genes to restore retrotransposition activity. These discoveries highlight the recombinatory potential of LINE-1 RNA with implications for genome evolution and TE domestication.

A novel smoking cessation behavior based on quit attempts may identify new genes associated with long-term abstinence

BACKGROUND

Smoking cessation at any age has been shown to improve quality of life, decrease illness, and reduce mortality. About half of smokers attempt to quit each year, but only ∼ 7 % maintain long-term abstinence unaided. Few genetic factors have been consistently associated with smoking cessation, possibly due to poor phenotype definition.

METHODS

We performed a genome-wide association study (GWAS) with an alternative phenotype based on the difficulty of quitting smoking (DQS) in the Cancer Prevention Study-3 cohort. Difficult quitters were defined as having made at least ten quit attempts, whether successful or not, and easy quitters as having quit after only one attempt. Only individuals of European ancestry were selected for the study. Among 10,004 smokers (5,071 difficult quitters, 4,933 easy quitters), we assessed the genetic heritability of DQS and evaluated associations between DQS and each genome-wide variant using logistic regression while adjusting for confounders, including smoking intensity (cigarettes per day).

RESULTS

The genetic heritability of the DQS phenotype was 13 %, comparable to, or higher than, the reported heritability of other smoking behaviors (e.g., smoking intensity, cessation). Although no variants were genome-wide significant, several genes were identified at a subthreshold level (p < 10-4). A variant in MEGF9 (rs149760032), a transmembrane protein largely expressed in the central nervous system, showed the strongest association with DQS (OR = 0.60, p = 1.3x10-7). Additional variants associated with DQS independently by smoking intensity were also detected in GLRA3 (rs73006492, OR = 0.77, p = 5.6x10-7) and FOCAD (rs112251973, OR = 1.96, p = 1.8x10-6) and are plausibly related to smoking cessation through pathways in the brain and respiratory system.

CONCLUSIONS

The use of an alternative cessation phenotype based on difficulty quitting smoking facilitated the identification of new pathways that could lead to unique smoking treatments.

Feedback regulation of retinaldehyde reductase DHRS3, a critical determinant of retinoic acid homeostasis

Retinoic acid is crucial for vertebrate embryogenesis, influencing anterior-posterior patterning and organogenesis through its interaction with nuclear hormone receptors comprising heterodimers of retinoic acid receptors (RARα, β, or γ) and retinoid X receptors (RXRα, β, or γ). Tissue retinoic acid levels are tightly regulated since both its excess and deficiency are deleterious. Dehydrogenase/reductase 3 (DHRS3) plays a critical role in this regulation by converting retinaldehyde to retinol, preventing excessive retinoic acid formation. Mutations in DHRS3 can result in embryonic lethality and congenital defects. This study shows that mouse Dhrs3 expression is responsive to vitamin A status and is directly regulated by the RAR/RXR complex through cis-regulatory elements. This highlights a negative feedback mechanism that ensures retinoic acid homeostasis.

INSTINCT: Multi-sample integration of spatial chromatin accessibility sequencing data via stochastic domain translation

Recent advances in spatial epigenomic techniques have given rise to spatial assay for transposase-accessible chromatin using sequencing (spATAC-seq) data, enabling the characterization of epigenomic heterogeneity and spatial information simultaneously. Integrative analysis of multiple spATAC-seq samples, for which no method has been developed, allows for effective identification and elimination of unwanted non-biological factors within the data, enabling comprehensive exploration of tissue structures and providing a holistic epigenomic landscape, thereby facilitating the discovery of biological implications and the study of regulatory processes. In this article, we present INSTINCT, a method for multi-sample INtegration of Spatial chromaTIN accessibility sequencing data via stochastiC domain Translation. INSTINCT can efficiently handle the high dimensionality of spATAC-seq data and eliminate the complex noise and batch effects of samples through a stochastic domain translation procedure. We demonstrate the superiority and robustness of INSTINCT in integrating spATAC-seq data across multiple simulated scenarios and real datasets. Additionally, we highlight the advantages of INSTINCT in spatial domain identification, visualization, spot-type annotation, and various downstream analyses, including motif enrichment analysis, expression enrichment analysis, and partitioned heritability analysis.

Analyzing, visualizing, and annotating tRNA-derived RNAs using tRAX and tDRnamer

tRNA-derived RNAs (tDRs) are known for their diverse regulatory roles in many organisms. These small RNA transcripts have been identified mainly by high-throughput RNA sequencing, numbering hundreds to thousands of unique molecules in any given biological sample. As such, bioinformatic analysis is essential in understanding the features, complexity, and unexplored biological patterns of tDRs. This chapter describes use of tRAX: tRNA Analysis of eXpression, a specially designed comprehensive end-to-end software pipeline for tDR abundance estimation, differential expression comparison, and inference of RNA modifications from raw small RNA sequencing data. We also demonstrate tDRnamer, a web- and command-line-based companion tool that provides automated, standardized tDR naming and annotations based on source tRNAs and related tDRs.

A de novo, mosaic and complex chromosome 21 rearrangement causes APP triplication and familial autosomal dominant early onset Alzheimer disease

Copy number variation (CNV) of the amyloid-β precursor protein gene (APP) is a known cause of autosomal dominant Alzheimer disease (ADAD), but de novo genetic variants causing ADAD are rare. We report a mother and daughter with neuropathologically confirmed definite Alzheimer disease (AD) and extensive cerebral amyloid angiopathy (CAA). Copy number analysis identified an increased number of APP copies and genome sequencing (GS) revealed the underlying complex genomic rearrangement (CGR) including a triplication of APP with two unique breakpoint junctions (BPJs). The mosaic state in the mother had likely occurred de novo. Digital droplet PCR (ddPCR) on 42 different tissues, including 17 different brain regions, showed the derivative chromosome at varying mosaic levels (20-96%) in the mother who had symptom onset at age 58 years. In contrast, the derivative chromosome was present in all analyzed cells in the daughter whose symptom onset was at 34 years. This study reveals the architecture of a de novo CGR causing APP triplication and ADAD with a striking difference in age at onset between the fully heterozygous daughter compared to the mosaic mother. The GS analysis identified the complexity of the CGR illustrating its usefulness in identifying structural variants (SVs) in neurodegenerative disorders.

Standardized pipelines support and facilitate integration of diverse datasets at the Rat Genome Database

The Rat Genome Database (RGD) is a multispecies knowledgebase which integrates genetic, multiomic, phenotypic, and disease data across 10 mammalian species. To support cross-species, multiomics studies and to enhance and expand on data manually extracted from the biomedical literature by the RGD team of expert curators, RGD imports and integrates data from multiple sources. These include major databases and a substantial number of domain-specific resources, as well as direct submissions by individual researchers. The incorporation of these diverse datatypes is handled by a growing list of automated import, export, data processing, and quality control pipelines. This article outlines the development over time of a standardized infrastructure for automated RGD pipelines with a summary of key design decisions and a focus on lessons learned.

From Soil to Surface: Exploring the Impact of Green Infrastructure on Microbial Communities in the Built Environment

High microbial diversity offers extensive benefits to both the environment and human health, contributing to ecosystem stability, nutrient cycling, and pathogen suppression. In built environments, factors such as building design, human activity, and cleaning protocols influence microbial communities. This study investigates the impact of landscape design on microbial diversity and function within the "Visionary Lab" exhibition in Tokyo, Japan, using 16S rRNA gene amplicon sequencing and shallow shotgun sequencing. Despite the limited sample size, the study suggests that the Visionary Lab samples may exhibit higher microbial diversity compared to other museum areas. Potential distinct microbial community structures may be correlated with sampling locations. However, despite this, no consistent patterns were observed in virulence factors or antimicrobial resistance genes across the samples. Metabolic function analysis showed varied profiles, suggesting diverse ecological interactions influenced that may be by the curated landscape. This suggest that the curated landscape design may have the potential to enhance microbial diversity, highlighting a possible avenue to create healthier and more sustainable built environments. However, the lack of consistent patterns in virulence factors and antimicrobial resistance genes underscores the complexity of microbial community dynamics.

Genome-wide absolute quantification of chromatin looping

3D genomics methods such as Hi-C and Micro-C have uncovered chromatin loops across the genome and linked these loops to gene regulation. However, these methods only measure 3D interaction probabilities on a relative scale. Here, we overcome this limitation by using live imaging data to calibrate Micro-C in mouse embryonic stem cells, thus obtaining absolute looping probabilities for 36,804 chromatin loops across the genome. We find that the looped state is generally rare, with a mean probability of 2.3% and a maximum of 26% across the quantified loops. On average, CTCF-CTCF loops are stronger than loops between cis-regulatory elements (3.2% vs. 1.1%). Our findings can be extended to human stem cells and differentiated cells under certain assumptions. Overall, we establish an approach for genome-wide absolute loop quantification and report that loops generally occur with low probabilities, generalizing recent live imaging results to the whole genome.

Single-nucleotide-resolution genomic maps of O6-methylguanine from the glioblastoma drug temozolomide

Temozolomide kills cancer cells by forming O6-methylguanine (O6-MeG), which leads to cell cycle arrest and apoptosis. However, O6-MeG repair by O6-methylguanine-DNA methyltransferase (MGMT) contributes to drug resistance. Characterizing genomic profiles of O6-MeG could elucidate how O6-MeG accumulation is influenced by repair, but there are no methods to map genomic locations of O6-MeG. Here, we developed an immunoprecipitation- and polymerase-stalling-based method, termed O6-MeG-seq, to locate O6-MeG across the whole genome at single-nucleotide resolution. We analyzed O6-MeG formation and repair across sequence contexts and functional genomic regions in relation to MGMT expression in a glioblastoma-derived cell line. O6-MeG signatures were highly similar to mutational signatures from patients previously treated with temozolomide. Furthermore, MGMT did not preferentially repair O6-MeG with respect to sequence context, chromatin state or gene expression level, however, may protect oncogenes from mutations. Finally, we found an MGMT-independent strand bias in O6-MeG accumulation in highly expressed genes. These data provide high resolution insight on how O6-MeG formation and repair are impacted by genome structure and nucleotide sequence. Further, O6-MeG-seq is expected to enable future studies of DNA modification signatures as diagnostic markers for addressing drug resistance and preventing secondary cancers.

Update of the FANTOM web resource: enhancement for studying noncoding genomes

The FANTOM web resource (https://fantom.gsc.riken.jp/) has been a unique resource for studying mammalian genomes, which is built on the research activities conducted in the international collaborative project FANTOM (Functional ANnoTation Of the Mammalian genome). In recent updates, we expanded annotations for long non-coding RNAs (lncRNAs) and transcribed cis-regulatory elements (CREs). The former was derived from the large-scale lncRNA perturbations in induced pluripotent stem cells (iPSCs) and integrative analysis of Hi-C data conducted in the sixth iteration of the project (FANTOM6). The resulting annotations of lncRNAs, according to the impact on cellular and molecular phenotypes and the potential RNA-chromatin interactions, are accessible via the interactive ZENBU-Reports framework. The latter involves a new platform, fanta.bio (https://fanta.bio/), which collects transcribed CREs identified via use of an extended dataset of CAGE profiles. The CREs, with their annotations including genetic and epigenetic information, are accessible via a dedicated interface as well as the UCSC Genome Browser Database. These updates offer enhanced opportunities to investigate the functions of non-coding regions within mammalian genomes.

Mechanisms underlying dilated cardiomyopathy associated with FKBP12 deficiency

Dilated cardiomyopathy (DCM) is a highly prevalent and genetically heterogeneous condition that results in decreased contractility and impaired cardiac function. The FK506-binding protein FKBP12 has been implicated in regulating the ryanodine receptor in skeletal muscle, but its role in cardiac muscle remains unclear. To define the effect of FKBP12 in cardiac function, we generated conditional mouse models of FKBP12 deficiency. We used Cre recombinase driven by either the α-myosin heavy chain, (αMHC) or muscle creatine kinase (MCK) promoter, which are expressed at embryonic day 9 (E9) and E13, respectively. Both conditional models showed an almost total loss of FKBP12 in adult hearts compared with control animals. However, only the early embryonic deletion of FKBP12 (αMHC-Cre) resulted in an early-onset and progressive DCM, increased cardiac oxidative stress, altered expression of proteins associated with cardiac remodeling and disease, and sarcoplasmic reticulum Ca2+ leak. Our findings indicate that FKBP12 deficiency during early development results in cardiac remodeling and altered expression of DCM-associated proteins that lead to progressive DCM in adult hearts, thus suggesting a major role for FKBP12 in embryonic cardiac muscle.

miRStart 2.0: enhancing miRNA regulatory insights through deep learning-based TSS identification

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by binding to the 3'-untranslated regions of target mRNAs, influencing various biological processes at the post-transcriptional level. Identifying miRNA transcription start sites (TSSs) and transcription factors' (TFs) regulatory roles is crucial for elucidating miRNA function and transcriptional regulation. miRStart 2.0 integrates over 4500 high-throughput datasets across five data types, utilizing a multi-modal approach to annotate 28 828 putative TSSs for 1745 human and 1181 mouse miRNAs, supported by sequencing-based signals. Over 6 million tissue-specific TF-miRNA interactions, integrated from ChIP-seq data, are supplemented by DNase hypersensitivity and UCSC conservation data, with network visualizations. Our deep learning-based model outperforms existing tools in miRNA TSS prediction, achieving the most overlaps with both cell-specific and non-cell-specific validated TSSs. The user-friendly web interface and visualization tools make miRStart 2.0 easily accessible to researchers, enabling efficient identification of miRNA upstream regulatory elements in relation to their TSSs. This updated database provides systems-level insights into gene regulation and disease mechanisms, offering a valuable resource for translational research, facilitating the discovery of novel therapeutic targets and precision medicine strategies. miRStart 2.0 is now accessible at https://awi.cuhk.edu.cn/∼miRStart2.

RPS 2.0: an updated database of RNAs involved in liquid-liquid phase separation

Liquid-liquid phase separation (LLPS) is a crucial process for the formation of biomolecular condensates such as coacervate droplets, P-bodies and stress granules, which play critical roles in many physiological and pathological processes. Increasing studies have shown that not only proteins but also RNAs play a critical role in LLPS. To host LLPS-associated RNAs, we previously developed a database named 'RPS' in 2021. In this study, we present an updated version RPS 2.0 (https://rps.renlab.cn/) to incorporate the newly generated data and to host new LLPS-associated RNAs driven by post-transcriptional regulatory mechanisms. Currently, RPS 2.0 hosts 171 301 entries of LLPS-associated RNAs in 24 different biomolecular condensates with four evidence types, including 'Reviewed', 'High-throughput (LLPS enrichment)', 'High-throughput (LLPS perturbation)' and 'Predicted', and five event types, including 'Expression', 'APA', 'AS', 'A-to-I' and 'Modification'. Additionally, extensive annotations of LLPS-associated RNAs are provided in RPS 2.0, including RNA sequence and structure features, RNA-protein/RNA-RNA interactions, RNA modifications, as well as diseases related annotations. We expect that RPS 2.0 will further promote research of LLPS-associated RNAs and deepen our understanding of the biological functions and regulatory mechanisms of LLPS.