The UCSC Genome Browser database: 2023 update

kmerDB: A database encompassing the set of genomic and proteomic sequence information for each species

The decrease in sequencing expenses has facilitated the creation of reference genomes and proteomes for an expanding array of organisms. Nevertheless, no established repository that details organism-specific genomic and proteomic sequences of specific lengths, referred to as kmers, exists to our knowledge. In this article, we present kmerDB, a database accessible through an interactive web interface that provides kmer-based information from genomic and proteomic sequences in a systematic way. kmerDB currently contains 202,340,859,107 base pairs and 19,304,903,356 amino acids, spanning 54,039 and 21,865 reference genomes and proteomes, respectively, as well as 6,905,362 and 149,305,183 genomic and proteomic species-specific sequences, termed quasi-primes. Additionally, we provide access to 5,186,757 nucleic and 214,904,089 peptide sequences absent from every genome and proteome, termed primes. kmerDB features a user-friendly interface offering various search options and filters for easy parsing and searching. The service is available at: www.kmerdb.com.

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Minimal phenotypes in transgenic mice with the human LOXL1/LOXL1-AS1 locus associated with exfoliation glaucoma

Exfoliation syndrome is a leading cause of secondary glaucoma worldwide. Among the risk-factors for exfoliation syndrome and exfoliation glaucoma that have been investigated, a genetic association with 15q24.1 is among the most striking. The leading candidates for the causal gene at this locus are LOXL1 and/or LOXL1-AS1, but studies have not yet coalesced in establishing, or ruling out, either candidate. Here, we contribute to studies of the 15q24.1 locus by making a partially humanized mouse model in which 166 kb of human genomic DNA from the 15q24.1 locus was introduced into the mouse genome via BAC transgenesis (B6-Tg(RP11-71M11)Andm). Transgenic expression of human genes in the BAC was only detectable for LOXL1-AS1. One cohort of 34 mice (21 experimental hemizygotes and 13 non-carrier control littermates) was assessed by slit-lamp exams and SD-OCT imaging at early (1-2 months) and mid (4-5 months) time points; fundus exams were performed at 5 months of age. A second smaller cohort (3 hemizygotes) were aged extensively (>12 months) to screen for overt abnormalities. Across all genotypes and ages, 136 slit-lamp exams, 128 SD-OCT exams, and 42 fundus exams detected no overt indices of exfoliation syndrome. Quantitatively, small, but statistically significant, age-related declines in ganglion cell complex thickness and total retinal thickness were detected in the hemizygotes at 4 months of age. Overall, this study demonstrates complexity in gene regulation from the 15q24.1 locus and suggests that LOXL1-AS1 is unlikely to be a monogenic cause of exfoliation syndrome but may contribute to glaucomatous retinal damage.

TIMP1 promotes thyroid cancer cell progression through macrophage phenotypic polarization via the PI3K/AKT signaling pathway

Increasing evidence suggests that tissue inhibitor of metalloproteinase 1 (TIMP1) played a pivotal role in immune regulation. Our study focused on examining the expression and function of TIMP1 in humans, particularly in its regulation of tumor-associated macrophages (TAMs) in papillary thyroid carcinoma (PTC). We observed an upregulation of TIMP1 in 16 different types of malignancies, including thyroid cancer. TIMP1 shaped the inflammatory TME in PTC. Inhibiting the expression of TIMP1 has been demonstrated to reduce the malignant biological traits of PTC cells. Furthermore, reducing TIMP1 expression impeded M2 macrophage polarization as well as facilitated M1 macrophage polarization in PTC. ELISA results demonstrated that downregulated TIMP1 expression correlated with decreased levels of IL10 and TGF-β in cell supernatants. Furthermore, the supernatant from polarized macrophages in the TIMP1-silenced group inhibited the motility of wild-type PTC cells. Therefore, TIMP1 may enhance the progression of PTC by stimulating the PI3K/AKT pathway via the secretion of IL10 and TGF-β, consequently influencing M2-type polarization in TAMs.

Quantitative comparison of single-cell RNA sequencing versus single-molecule RNA imaging for quantifying transcriptional noise

Stochastic fluctuations (noise) in transcription generate substantial cell-to-cell variability. However, how best to quantify genome-wide noise, remains unclear. Here we utilize a small-molecule perturbation (IdU) to amplify noise and assess noise quantification from numerous scRNA-seq algorithms on human and mouse datasets, and then compare to noise quantification from single-molecule RNA FISH (smFISH) for a panel of representative genes. We find that various scRNA-seq analyses report amplified noise, without altered mean-expression levels, for ∼90% of genes and that smFISH analysis verifies noise amplification for the vast majority of genes tested. Collectively, the analyses suggest that most scRNA-seq algorithms are appropriate for quantifying noise including a simple normalization approach, although all of these systematically underestimate noise compared to smFISH. From a practical standpoint, this analysis argues that IdU is a globally penetrant noise-enhancer molecule-amplifying noise without altering mean-expression levels-which could enable investigations of the physiological impacts of transcriptional noise.

MOTIVATION

Cell-to-cell variability in isogenic populations is predominantly attributed to the stochastic fluctuations (i.e., noise) in transcription. However, the quantification of this noise, particularly on a genome-wide scale, remains an open question. To address this general question, here we utilize a small-molecule perturbation reported to amplify transcriptional noise. Previous single-cell RNA-sequencing (scRNA-seq) analysis indicated that the pyrimidine nucleobase 5'-iodo-2'-deoxyuridine (IdU) amplifies noise but technical drawbacks of scRNA-seq may have obscured the penetrance and degree of noise amplification. Consequently, here we assess numerous scRNA-seq algorithms, on two different scRNA-seq datasets for a human and mouse cell type, for their ability to quantify noise amplification and then compare the results to noise quantification from single-molecule RNA FISH (smFISH) imaging for a panel of representative genes. The specific questions addressed are whether IdU amplifies noise in a globally or partially penetrant manner, and what scRNA-seq algorithm is most appropriate for quantifying transcriptional noise.

Pathogenic variants in KMT2C result in a neurodevelopmental disorder distinct from Kleefstra and Kabuki syndromes

Trithorax-related H3K4 methyltransferases, KMT2C and KMT2D, are critical epigenetic modifiers. Haploinsufficiency of KMT2C was only recently recognized as a cause of neurodevelopmental disorder (NDD), so the clinical and molecular spectrums of the KMT2C-related NDD (now designated as Kleefstra syndrome 2) are largely unknown. We ascertained 98 individuals with rare KMT2C variants, including 75 with protein-truncating variants (PTVs). Notably, ∼15% of KMT2C PTVs were inherited. Although the most highly expressed KMT2C transcript consists of only the last four exons, pathogenic PTVs were found in almost all the exons of this large gene. KMT2C variant interpretation can be challenging due to segmental duplications and clonal hematopoesis-induced artifacts. Using samples from 27 affected individuals, divided into discovery and validation cohorts, we generated a moderate strength disorder-specific KMT2C DNA methylation (DNAm) signature and demonstrate its utility in classifying non-truncating variants. Based on 81 individuals with pathogenic/likely pathogenic variants, we demonstrate that the KMT2C-related NDD is characterized by developmental delay, intellectual disability, behavioral and psychiatric problems, hypotonia, seizures, short stature, and other comorbidities. The facial module of PhenoScore, applied to photographs of 34 affected individuals, reveals that the KMT2C-related facial gestalt is significantly different from the general NDD population. Finally, using PhenoScore and DNAm signatures, we demonstrate that the KMT2C-related NDD is clinically and epigenetically distinct from Kleefstra and Kabuki syndromes. Overall, we define the clinical features, molecular spectrum, and DNAm signature of the KMT2C-related NDD and demonstrate they are distinct from Kleefstra and Kabuki syndromes highlighting the need to rename this condition.

Sleep and diurnal alternative polyadenylation sites associated with human APA-linked brain disorders

Disruption of sleep and circadian rhythms are a comorbid feature of many pathologies, and can negatively influence many health conditions, including neurodegenerative disease, metabolic illness, cancer, and various neurological disorders. Genetic association studies linking sleep and circadian disturbances with disease susceptibility have mainly focused on changes in gene expression due to mutations, such as single-nucleotide polymorphisms. The interaction between sleep and/or circadian rhythms with the use of Alternative Polyadenylation (APA) has been largely undescribed, particularly in the context of other disorders. APA is a process that generates various transcript isoforms of the same gene affecting its mRNA translation, stability, localization, and subsequent function. Here we identified unique APAs expressed in rat brain over time-of-day, immediately following sleep deprivation, and the subsequent recovery period. From these data, we performed a secondary analysis of these sleep- or time-of-day associated PASs with recently described APA-linked human brain disorder susceptibility genes.

FOSL1-mediated LINC01566 negatively regulates CD4+ T-cell activation in myasthenia gravis

BACKGROUND

Myasthenia gravis (MG) is an autoimmune disease characterized by pathogenic antibodies that target structures of the neuromuscular junction. The evidence suggests that the regulation of long noncoding RNAs (lncRNAs) that is mediated by transcription factors (TFs) plays a key role in the pathophysiology of MG. Nevertheless, the detailed molecular mechanisms of lncRNAs in MG remain largely undetermined.

METHODS

Using microarray analysis, we analyzed the lncRNA levels in MG. By bioinformatics analysis, LINC01566 was found to potentially play an important role in MG. First, qRT‒PCR was performed to verify the LINC1566 expressions in MG patients. Then, fluorescence in situ hybridization was conducted to determine the localization of LINC01566 in CD4 + T cells. Finally, the impact of LINC01566 knockdown or overexpression on CD4 + T-cell function was also analyzed using flow cytometry and CCK-8 assay. A dual-luciferase reporter assay was used to validate the binding of the TF FOSL1 to the LINC01566 promoter.

RESULTS

Based on the lncRNA microarray and differential expression analyses, we identified 563 differentially expressed (DE) lncRNAs, 450 DE mRNAs and 19 DE TFs in MG. We then constructed a lncRNA-TF-mRNA network. Through network analysis, we found that LINC01566 may play a crucial role in MG by regulating T-cell-related pathways. Further experiments indicated that LINC01566 is expressed at low levels in MG patients. Functionally, LINC01566 is primarily distributed in the nucleus and can facilitate CD4 + T-cell apoptosis and inhibit cell proliferation. Mechanistically, we hypothesized that LINC01566 may negatively regulate the expressions of DUSP3, CCR2, FADD, SIRPB1, LGALS3 and SIRPB1, which are involved in the T-cell activation pathway, to further influence the cellular proliferation and apoptosis in MG. Moreover, we found that the effect of LINC01566 on CD4 + T cells in MG was mediated by the TF FOSL1, and in vitro experiments indicated that FOSL1 can bind to the promoter region of LINC01566.

CONCLUSIONS

In summary, our research revealed the protective roles of LINC01566 in clinical samples and cellular experiments, illustrating the potential roles and mechanism by which FOSL1/LINC01566 negatively regulates CD4 + T-cell activation in MG.

Optimized rAAV8 targeting acinar KLF4 ameliorates fibrosis in chronic pancreatitis via exosomes-enriched let-7s suppressing pancreatic stellate cells activation

Chronic pancreatitis (CP) is marked by progressive fibrosis and the activation of pancreatic stellate cells (PSCs), accompanied by the destruction of pancreatic parenchyma, leading to the loss of acinar cells (ACs). Few research studies have explored the mechanism by which damaged ACs (DACs) contribute to PSCs activation and pancreatic fibrosis. Currently, there are no effective drugs for curing CP or limiting the progression of pancreatic fibrosis. In this research, co-culture with intact acinar cells (IACs) suppressed PSC activation, while co-culture with DACs did the opposite. Krüppel-like factor 4 (KLF4) was significantly upregulated in DACs and was established as the key molecule that switches ACs from PSCs-suppressor to PSCs-activator. We revealed the exosomes of IACs contributed to the anti-activated function of IACs-CS on PSCs. MiRNome profiling showed that let-7 family is significantly enriched in IAC-derived exosomes (>30% miRNome), which partially mediates IACs' suppressive impacts on PSCs. Furthermore, it has been observed that the enrichment of let-7 in exosomes was influenced by the expression level of KLF4. Mechanistic studies demonstrated that KLF4 in ACs upregulated Lin28A, thereby decreasing let-7 levels in AC-derived exosomes, and thus promoting PSCs activation. We utilized an adeno-associated virus specifically targeting KLF4 in ACs (shKLF4-pAAV) to suppress PSCs activation in CP, resulting in reduced pancreatic fibrosis. IAC-derived exosomes hold potential as potent weapons against PSCs activation via let-7s, while activated KLF4/Lin28A signaling in DACs diminished such functions. ShKLF4-pAAV holds promise as a novel therapeutic approach for CP.

Differential Conservation and Loss of Chicken Repeat 1 (CR1) Retrotransposons in Squamates Reveal Lineage-Specific Genome Dynamics Across Reptiles

Transposable elements (TEs) are repetitive DNA sequences which create mutations and generate genetic diversity across the tree of life. In amniote vertebrates, TEs have been mainly studied in mammals and birds, whose genomes generally display low TE diversity. Squamates (Order Squamata; including ∼11,000 extant species of lizards and snakes) show as much variation in TE abundance and activity as they do in species and phenotypes. Despite this high TE activity, squamate genomes are remarkably uniform in size. We hypothesize that novel, lineage-specific genome dynamics have evolved over the course of squamate evolution. To understand the interplay between TEs and host genomes, we analyzed the evolutionary history of the chicken repeat 1 (CR1) retrotransposon, a TE family found in most tetrapod genomes which is the dominant TE in most reptiles. We compared 113 squamate genomes to the genomes of turtles, crocodilians, and birds and used ancestral state reconstruction to identify shifts in the rate of CR1 copy number evolution across reptiles. We analyzed the repeat landscapes of CR1 in squamate genomes and determined that shifts in the rate of CR1 copy number evolution are associated with lineage-specific variation in CR1 activity. We then used phylogenetic reconstruction of CR1 subfamilies across amniotes to reveal both recent and ancient CR1 subclades across the squamate tree of life. The patterns of CR1 evolution in squamates contrast other amniotes, suggesting key differences in how TEs interact with different host genomes and at different points across evolutionary history.

BertSNR: an interpretable deep learning framework for single-nucleotide resolution identification of transcription factor binding sites based on DNA language model

MOTIVATION

Transcription factors are pivotal in the regulation of gene expression, and accurate identification of transcription factor binding sites (TFBSs) at high resolution is crucial for understanding the mechanisms underlying gene regulation. The task of identifying TFBSs from DNA sequences is a significant challenge in the field of computational biology today. To address this challenge, a variety of computational approaches have been developed. However, these methods face limitations in their ability to achieve high-resolution identification and often lack interpretability.

RESULTS

We propose BertSNR, an interpretable deep learning framework for identifying TFBSs at single-nucleotide resolution. BertSNR integrates sequence-level and token-level information by multi-task learning based on pre-trained DNA language models. Benchmarking comparisons show that our BertSNR outperforms the existing state-of-the-art methods in TFBS predictions. Importantly, we enhanced the interpretability of the model through attentional weight visualization and motif analysis, and discovered the subtle relationship between attention weight and motif. Moreover, BertSNR effectively identifies TFBSs in promoter regions, facilitating the study of intricate gene regulation.

AVAILABILITY AND IMPLEMENTATION

The BertSNR source code can be found at https://github.com/lhy0322/BertSNR.

N6-methyladenosine modified circPAK2 promotes lymph node metastasis via targeting IGF2BPs/VEGFA signaling in gastric cancer

Circular RNAs (circRNAs) have emerged as key regulators of cancer occurrence and progression, as well as promising biomarkers for cancer diagnosis and prognosis. However, the potential mechanisms of circRNAs implicated in lymph node (LN) metastasis of gastric cancer remain unclear. Herein, we identify a novel N6-methyladenosine (m6A) modified circRNA, circPAK2, which is significantly upregulated in gastric cancer tissues and metastatic LN tissues. Functionally, circPAK2 enhances the migration, invasion, lymphangiogenesis, angiogenesis, epithelial-mesenchymal transition (EMT), and metastasis of gastric cancer in vitro and in vivo. Mechanistically, circPAK2 is exported by YTH domain-containing protein 1 (YTHDC1) from the nucleus to the cytoplasm in an m6A methylation-dependent manner. Moreover, increased cytoplasmic circPAK2 interacts with Insulin-Like Growth Factor 2 mRNA-Binding Proteins (IGF2BPs) and forms a circPAK2/IGF2BPs/VEGFA complex to stabilize VEGFA mRNA, which contributes to gastric cancer vasculature formation and aggressiveness. Clinically, high circPAK2 expression is positively associated with LN metastasis and poor prognosis in gastric cancer. This study highlights m6A-modified circPAK2 as a key regulator of LN metastasis of gastric cancer, thus supporting circPAK2 as a promising therapeutic target and prognostic biomarker for gastric cancer.

A map of canine sequence variation relative to a Greenland wolf outgroup

For over 15 years, canine genetics research relied on a reference assembly from a Boxer breed dog named Tasha (i.e., canFam3.1). Recent advances in long-read sequencing and genome assembly have led to the development of numerous high-quality assemblies from diverse canines. These assemblies represent notable improvements in completeness, contiguity, and the representation of gene promoters and gene models. Although genome graph and pan-genome approaches have promise, most genetic analyses in canines rely upon the mapping of Illumina sequencing reads to a single reference. The Dog10K consortium, and others, have generated deep catalogs of genetic variation through an alignment of Illumina sequencing reads to a reference genome obtained from a German Shepherd Dog named Mischka (i.e., canFam4, UU_Cfam_GSD_1.0). However, alignment to a breed-derived genome may introduce bias in genotype calling across samples. Since the use of an outgroup reference genome may remove this effect, we have reprocessed 1929 samples analyzed by the Dog10K consortium using a Greenland wolf (mCanLor1.2) as the reference. We efficiently performed remapping and variant calling using a GPU-implementation of common analysis tools. The resulting call set removes the variability in genetic differences seen across samples and breed relationships revealed by principal component analysis are not affected by the choice of reference genome. Using this sequence data, we inferred the history of population sizes and found that village dog populations experienced a 9-13 fold reduction in historic effective population size relative to wolves.

Complete sequencing of ape genomes

We present haplotype-resolved reference genomes and comparative analyses of six ape species, namely: chimpanzee, bonobo, gorilla, Bornean orangutan, Sumatran orangutan, and siamang. We achieve chromosome-level contiguity with unparalleled sequence accuracy (<1 error in 500,000 base pairs), completely sequencing 215 gapless chromosomes telomere-to-telomere. We resolve challenging regions, such as the major histocompatibility complex and immunoglobulin loci, providing more in-depth evolutionary insights. Comparative analyses, including human, allow us to investigate the evolution and diversity of regions previously uncharacterized or incompletely studied without bias from mapping to the human reference. This includes newly minted gene families within lineage-specific segmental duplications, centromeric DNA, acrocentric chromosomes, and subterminal heterochromatin. This resource should serve as a definitive baseline for all future evolutionary studies of humans and our closest living ape relatives.

High expression of YEATS2 as a predictive factor of poor prognosis in patients with hepatocellular carcinoma

YEATS domain containing 2 (YEATS2), it may function as a proto-oncogene. This study aims to investigate if YEATS2 correlates with prognosis in hepatocellular carcinoma. The prognostic landscape of YEATS2 and its relationship with expression in hepatocellular carcinoma were deciphered with public databases, RT-qPCR and western-blot in tissue samples. The expression profiling and prognostic value of YEATS2 were explored using UALCAN, TIMER, OncoLnc database. Transcription and survival analyses of YEATS2 in hepatocellular carcinoma were investigated with cBioPortal database. The STRING database was explored to identify molecular functions and signaling pathways downstream of YEATS2. YEATS2 expression was significantly higher in hepatocellular carcinoma compared with adjacent non-malignant tissues. Promoter methylation of YEATS2 exhibited different patterns in hepatocellular carcinoma. High expression of YEATS2 was associated with poorer survival. Mechanistically, YEATS2 was involved in mediating multiple biological processes including morphogenesis and migration.

Impact of genome build on RNA-seq interpretation and diagnostics

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network and Genomics Research to Elucidate the Genetics of Rare Disease Consortium. Across six routinely collected biospecimens, 61% of quantified genes were not influenced by genome build. However, we identified 1,492 genes with build-dependent quantification, 3,377 genes with build-exclusive expression, and 9,077 genes with annotation-specific expression across six routinely collected biospecimens, including 566 clinically relevant and 512 known OMIM genes. Further, we demonstrate that between builds for a given gene, a larger difference in quantification is well correlated with a larger change in expression outlier calling. Combined, we provide a database of genes impacted by build choice and recommend that transcriptomics-guided analyses and diagnoses are cross referenced with these data for robustness.

Epigenetic Alteration of Smooth Muscle Cells Regulates Endothelin-Dependent Blood Pressure and Hypertensive Arterial Remodeling

Long-standing hypertension (HTN) affects multiple organ systems and leads to pathologic arterial remodeling, which is driven largely by smooth muscle cell (SMC) plasticity. Although genome wide association studies (GWAS) have identified numerous variants associated with changes in blood pressure in humans, only a small percentage of these variants actually cause HTN. In order to identify relevant genes important in SMC function in HTN, we screened three separate human GWAS and Mendelian randomization studies to identify SNPs located within non-coding gene regions, focusing on genes encoding epigenetic enzymes, as these have been recently identified to control SMC fate in cardiovascular disease. We identified SNPs rs62059712 and rs74480102 in the promoter of the human JMJD3 gene and show that the minor C allele increases JMJD3 transcription in SMCs via increased SP1 binding to the JMJD3 promoter. Using our novel SMC-specific Jmjd3-deficient murine model ( Jmjd3 flox/flox Myh11 CreERT ), we show that loss of Jmjd3 in SMCs results in HTN, mechanistically, due to decreased EDNRB expression and a compensatory increase in EDNRA expression. As a translational corollary, through single cell RNA-sequencing (scRNA-seq) of human arteries, we found strong correlation between JMJD3 and EDNRB expression in SMCs. Further, we identified that JMJD3 is required for SMC-specific gene expression, and loss of JMJD3 in SMCs in the setting of HTN results in increased arterial remodeling by promoting the SMC synthetic phenotype. Our findings link a HTN-associated human DNA variant with regulation of SMC plasticity, revealing therapeutic targets that may be used in the screening and/or personalized treatment of HTN.

IsoVis - a webserver for visualization and annotation of alternative RNA isoforms

Genes commonly express multiple RNA products (RNA isoforms), which differ in exonic content and can have different functions. Making sense of the plethora of known and novel RNA isoforms being identified by transcriptomic approaches requires a user-friendly way to visualize gene isoforms and how they differ in exonic content, expression levels and potential functions. Here we introduce IsoVis, a freely available webserver that accepts user-supplied transcriptomic data and visualizes the expressed isoforms in a clear, intuitive manner. IsoVis contains numerous features, including the ability to visualize all RNA isoforms of a gene and their expression levels; the annotation of known isoforms from external databases; mapping of protein domains and features to exons, allowing changes to protein sequence and function between isoforms to be established; and extensive species compatibility. Datasets visualised on IsoVis remain private to the user, allowing analysis of sensitive data. IsoVis visualisations can be downloaded to create publication-ready figures. The IsoVis webserver enables researchers to perform isoform analyses without requiring programming skills, is free to use, and available at https://isomix.org/isovis/.

MotifbreakR v2: extended capability and database integration

MotifbreakR is a software tool that scans genetic variants against position weight matrices of transcription factors (TF) to determine the potential for the disruption of TF binding at the site of the variant. It leverages the Bioconductor suite of software packages and annotations to operate across a diverse array of genomes and motif databases. Initially developed to interrogate the effect of single nucleotide variants (common and rare SNVs) on potential TF binding sites, in motifbreakR v2, we have updated the functionality. New features include the ability to query other types of more complex genetic variants, such as short insertions and deletions (indels). This function allows modeling a more extensive array of variants that may have more significant effects on TF binding. Additionally, while TF binding is based partly on sequence preference, predictions of TF binding based on sequence preference alone can indicate many more potential binding events than observed. Adding information from DNA-binding sequencing datasets lends confidence to motif disruption prediction by demonstrating TF binding in cell lines and tissue types. Therefore, motifbreakR implements querying the ReMap2022 database for evidence that a TF matching the disrupted motif binds over the disrupting variant. Finally, in motifbreakR, in addition to the existing interface, we have implemented an R/Shiny graphical user interface to simplify and enhance access to researchers with different skill sets.

Benchmarking Algorithms for Gene Set Scoring of Single-cell ATAC-seq Data

Gene set scoring (GSS) has been routinely conducted for gene expression analysis of bulk or single-cell RNA sequencing (RNA-seq) data, which helps to decipher single-cell heterogeneity and cell type-specific variability by incorporating prior knowledge from functional gene sets. Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a powerful technique for interrogating single-cell chromatin-based gene regulation, and genes or gene sets with dynamic regulatory potentials can be regarded as cell type-specific markers as if in single-cell RNA-seq (scRNA-seq). However, there are few GSS tools specifically designed for scATAC-seq, and the applicability and performance of RNA-seq GSS tools on scATAC-seq data remain to be investigated. Here, we systematically benchmarked ten GSS tools, including four bulk RNA-seq tools, five scRNA-seq tools, and one scATAC-seq method. First, using matched scATAC-seq and scRNA-seq datasets, we found that the performance of GSS tools on scATAC-seq data was comparable to that on scRNA-seq, suggesting their applicability to scATAC-seq. Then, the performance of different GSS tools was extensively evaluated using up to ten scATAC-seq datasets. Moreover, we evaluated the impact of gene activity conversion, dropout imputation, and gene set collections on the results of GSS. Results show that dropout imputation can significantly promote the performance of almost all GSS tools, while the impact of gene activity conversion methods or gene set collections on GSS performance is more dependent on GSS tools or datasets. Finally, we provided practical guidelines for choosing appropriate preprocessing methods and GSS tools in different application scenarios.

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Identification of Polymorphisms in EAAT1 Glutamate Transporter Gene SLC1A3 Associated with Reduced Migraine Risk

Dysfunction in ion channels or processes involved in maintaining ionic homeostasis is thought to lower the threshold for cortical spreading depression (CSD), and plays a role in susceptibility to associated neurological disorders, including pathogenesis of a migraine. Rare pathogenic variants in specific ion channels have been implicated in monogenic migraine subtypes. In this study, we further examined the channelopathic nature of a migraine through the analysis of common genetic variants in three selected ion channel or transporter genes: SLC4A4, SLC1A3, and CHRNA4. Using the Agena MassARRAY platform, 28 single-nucleotide polymorphisms (SNPs) across the three candidate genes were genotyped in a case-control cohort comprised of 182 migraine cases and 179 matched controls. Initial results identified significant associations between migraine and rs3776578 (p = 0.04) and rs16903247 (p = 0.05) genotypes within the SLC1A3 gene, which encodes the EAAT1 glutamate transporter. These SNPs were subsequently genotyped in an independent cohort of 258 migraine cases and 290 controls using a high-resolution melt assay, and association testing supported the replication of initial findings-rs3776578 (p = 0.0041) and rs16903247 (p = 0.0127). The polymorphisms are in linkage disequilibrium and localise within a putative intronic enhancer region of SLC1A3. The minor alleles of both SNPs show a protective effect on migraine risk, which may be conferred via influencing the expression of SLC1A3.

CpG island turnover events predict evolutionary changes in enhancer activity

BACKGROUND

Genetic changes that modify the function of transcriptional enhancers have been linked to the evolution of biological diversity across species. Multiple studies have focused on the role of nucleotide substitutions, transposition, and insertions and deletions in altering enhancer function. CpG islands (CGIs) have recently been shown to influence enhancer activity, and here we test how their turnover across species contributes to enhancer evolution.

RESULTS

We integrate maps of CGIs and enhancer activity-associated histone modifications obtained from multiple tissues in nine mammalian species and find that CGI content in enhancers is strongly associated with increased histone modification levels. CGIs show widespread turnover across species and species-specific CGIs are strongly enriched for enhancers exhibiting species-specific activity across all tissues and species. Genes associated with enhancers with species-specific CGIs show concordant biases in their expression, supporting that CGI turnover contributes to gene regulatory innovation. Our results also implicate CGI turnover in the evolution of Human Gain Enhancers (HGEs), which show increased activity in human embryonic development and may have contributed to the evolution of uniquely human traits. Using a humanized mouse model, we show that a highly conserved HGE with a large CGI absent from the mouse ortholog shows increased activity at the human CGI in the humanized mouse diencephalon.

CONCLUSIONS

Collectively, our results point to CGI turnover as a mechanism driving gene regulatory changes potentially underlying trait evolution in mammals.

A Transcriptomic Dataset of Embryonic Murine Telencephalon

Sex bias is known in the prevalence/pathology of neurodevelopmental disorders. Sex-dependent differences of the certain brain areas are known to emerge perinatally through the exposure to sex hormones, while gene expression patterns in the rodent embryonic brain does not seem to be completely the same between male and female. To investigate potential sex differences in gene expression and cortical organization during the embryonic period in mice, we conducted a comprehensive analysis of gene expression for the telencephalon at embryonic day (E) 11.5 (a peak of neural stem cell expansion) and E14.5 (a peak of neurogenesis) using bulk RNA-seq data. As a result, our data showed the existence of notable sex differences in gene expression patterns not obviously at E11.5, but clearly at E14.5 when neurogenesis has become its peak. These data can be useful for exploring potential contribution of genes exhibiting sex differences to the divergence in brain development. Additionally, our data underscore the significance of studying the embryonic period to gain a deeper understanding of sex differences in brain development.

The Maintenance of Deleterious Variation in Wild Chinese Rhesus Macaques

Understanding how deleterious variation is shaped and maintained in natural populations is important in conservation and evolutionary biology, as decreased fitness caused by these deleterious mutations can potentially lead to an increase in extinction risk. It is known that demographic processes can influence these patterns. For example, population bottlenecks and inbreeding increase the probability of inheriting identical-by-descent haplotypes from a recent common ancestor, creating long tracts of homozygous genotypes called runs of homozygosity (ROH), which have been associated with an accumulation of mildly deleterious homozygotes. Counterintuitively, positive selection can also maintain deleterious variants in a population through genetic hitchhiking. Here, we analyze the whole genomes of 79 wild Chinese rhesus macaques across five subspecies and characterize patterns of deleterious variation with respect to ROH and signals of recent positive selection. We show that the fraction of homozygotes occurring in long ROH is significantly higher for deleterious homozygotes than tolerated ones, whereas this trend is not observed for short and medium ROH. This confirms that inbreeding, by generating these long tracts of homozygosity, is the main driver of the high burden of homozygous deleterious alleles in wild macaque populations. Furthermore, we show evidence that homozygous LOF variants are being purged. Next, we identify seven deleterious variants at high frequency in regions putatively under selection near genes involved with olfaction and other processes. Our results shed light on how evolutionary processes can shape the distribution of deleterious variation in wild nonhuman primates.

Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT)

Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.

Analysis of the combined effect of rs699 and rs5051 on angiotensinogen expression and hypertension

Background

Hypertension (HTN) involves genetic variability in the renin-angiotensin system and influences antihypertensive response. We previously reported that angiotensinogen (AGT) messenger RNA (mRNA) is endogenously bound by miR-122-5p and rs699 A > G decreases reporter mRNA in the microRNA functional-assay PASSPORT-seq. The AGT promoter variant rs5051 C > T is in linkage disequilibrium (LD) with rs699 A > G and increases AGT transcription. The independent effect of these variants is understudied due to their LD therefore we aimed to test the hypothesis that increased AGT by rs5051 C > T counterbalances AGT decreased by rs699 A > G, and when these variants occur independently, it translates to HTN-related phenotypes.

Methods

We used in silico, in vitro, in vivo, and retrospective models to test this hypothesis.

Results

In silico, rs699 A > G is predicted to increase miR-122-5p binding affinity by 3%. Mir-eCLIP results show rs699 is 40-45 nucleotides from the strongest microRNA-binding site in the AGT mRNA. Unexpectedly, rs699 A > G increases AGT mRNA in an AGT-plasmid-cDNA HepG2 expression model. Genotype-Tissue Expression (GTEx) and UK Biobank analyses demonstrate liver AGT expression and HTN phenotypes are not different when rs699 A > G occurs independently from rs5051 C > T. However, GTEx and the in vitro experiments suggest rs699 A > G confers cell-type-specific effects on AGT mRNA abundance, and suggest paracrine renal renin-angiotensin-system perturbations could mediate the rs699 A > G associations with HTN.

Conclusions

We found that rs5051 C > T and rs699 A > G significantly associate with systolic blood pressure in Black participants in the UK Biobank, demonstrating a fourfold larger effect than in White participants. Further studies are warranted to determine if altered antihypertensive response in Black individuals might be due to rs5051 C > T or rs699 A > G. Studies like this will help clinicians move beyond the use of race as a surrogate for genotype.

Techniques, procedures, and applications in host genetic analysis

This chapter overviews genetic techniques' fundamentals and methodological features, including different approaches, analyses, and applications that have contributed to advancing health and disease. The aim is to describe laboratory methodologies and analyses employed to understand the genetic landscape of different biological contexts, from conventional techniques to cutting-edge technologies. Besides describing detailed aspects of the polymerase chain reaction (PCR) and derived types as one of the principles for many novel techniques, we also discuss microarray analysis, next-generation sequencing, and genome editing technologies such as transcription activator-like effector nucleases (TALENs) and the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems. These techniques study several phenotypes, ranging from autoimmune disorders to viral diseases. The significance of integrating diverse genetic methodologies and tools to understand host genetics comprehensively and addressing the ethical, legal, and social implications (ELSI) associated with using genetic information is highlighted. Overall, the methods, procedures, and applications in host genetic analysis provided in this chapter furnish researchers and practitioners with a roadmap for navigating the dynamic landscape of host-genome interactions.

The 18th International HLA & Immunogenetics workshop project report: Creating fully representative MHC reference haplotypes

A fundamental endeavor of the International Histocompatibility and Immunogenetics Workshop (IHIW) was assembling a collection of DNA samples homozygous through the MHC genomic region. This collection proved invaluable for assay development in the histocompatibility and immunogenetics field, for generating the human reference genome, and furthered our understanding of MHC diversity. Defined by their HLA-A, -B, -C and -DRB1 alleles, the combined frequency of the haplotypes from these individuals is ~20% in Europe. Thus, a significant proportion of MHC haplotypes, both common and rare throughout the world, and including many associated with disease, are not yet represented. In this workshop component, we are collecting the next generation of MHC -homozygous samples, to expand, diversify and modernize this critical community resource that has been foundational to the field. We asked laboratories worldwide to identify samples homozygous through all HLA class I and/or HLA class II genes, or through whole-genome SNP genotyping or sequencing, to have extensive homozygosity tracts within the MHC region. The focus is non-Europeans or those having HLA haplotypes less common in Europeans. Through this effort, we have obtained samples from 537 individuals representing 294 distinct haplotypes, as determined by their HLA class I and II alleles, and an additional 50 haplotypes distinct in HLA class I or II alleles. Although we have expanded the diversity, many populations remain underrepresented, particularly from Africa, and we encourage further participation. The data will serve as a resource for investigators seeking to characterize variation across the MHC genomic region for disease and population studies.

Coronary Artery Disease Risk Variant Dampens the Expression of CALCRL by Reducing HSF Binding to Shear Stress Responsive Enhancer in Endothelial Cells In Vitro

BACKGROUND

CALCRL (calcitonin receptor-like) protein is an important mediator of the endothelial fluid shear stress response, which is associated with the genetic risk of coronary artery disease. In this study, we functionally characterized the noncoding regulatory elements carrying coronary artery disease that risks single-nucleotide polymorphisms and studied their role in the regulation of CALCRL expression in endothelial cells.

METHODS

To functionally characterize the coronary artery disease single-nucleotide polymorphisms harbored around the gene CALCRL, we applied an integrative approach encompassing statistical, transcriptional (RNA-seq), and epigenetic (ATAC-seq [transposase-accessible chromatin with sequencing], chromatin immunoprecipitation assay-quantitative polymerase chain reaction, and electromobility shift assay) analyses, alongside luciferase reporter assays, and targeted gene and enhancer perturbations (siRNA and clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9) in human aortic endothelial cells.

RESULTS

We demonstrate that the regulatory element harboring rs880890 exhibits high enhancer activity and shows significant allelic bias. The A allele was favored over the G allele, particularly under shear stress conditions, mediated through alterations in the HSF1 (heat shock factor 1) motif and binding. CRISPR deletion of rs880890 enhancer resulted in downregulation of CALCRL expression, whereas HSF1 knockdown resulted in a significant decrease in rs880890-enhancer activity and CALCRL expression. A significant decrease in HSF1 binding to the enhancer region in endothelial cells was observed under disturbed flow compared with unidirectional flow. CALCRL knockdown and variant perturbation experiments indicated the role of CALCRL in mediating eNOS (endothelial nitric oxide synthase), APLN (apelin), angiopoietin, prostaglandins, and EDN1 (endothelin-1) signaling pathways leading to a decrease in cell proliferation, tube formation, and NO production.

CONCLUSIONS

Overall, our results demonstrate the existence of an endothelial-specific HSF (heat shock factor)-regulated transcriptional enhancer that mediates CALCRL expression. A better understanding of CALCRL gene regulation and the role of single-nucleotide polymorphisms in the modulation of CALCRL expression could provide important steps toward understanding the genetic regulation of shear stress signaling responses.

Interspecies regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we showed that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

Pathogenic SNPs Affect Both RNA and DNA G-Quadruplexes' Responses to Ligands

Single nucleotide polymorphisms (SNPs) are common genetic variations that are present in over 1% of the population and can significantly modify the structures of both DNA and RNA. G-quadruplex structures (G4) are formed by the superposition of tetrads of guanines. To date, the impact of SNPs on both G4 ligands' binding efficacies and specificities has not been investigated. Here, using a bioinformatically predicted G4 and SNPs found in the α-synuclein gene as a proof-of-concept, it was demonstrated that SNPs can modulate both DNA and RNA G4s' responses to ligands. Specifically, six widely recognized ligands (Phen-DC3, PDS, 360A, RHPS4, BRACO19, and TMPyP4) were shown to differentially affect both the structure and the polymerase stalling of the different SNPs. This work highlights the importance of choosing the appropriate G4 ligand when dealing with an SNP identified in a G-rich gene.

Npy transcription is regulated by noncanonical STAT3 signaling in hypothalamic neurons: Implication with lipotoxicity and obesity

Neuropeptide Y (Npy) is an abundant neuropeptide expressed in the central and peripheral nervous systems. NPY-secreting neurons in the hypothalamic arcuate nucleus regulate energy homeostasis, and Npy mRNA expression is regulated by peripheral nutrient and hormonal signals like leptin, interleukin-6 (IL-6), and fatty acids. This study demonstrates that IL-6, which phosphorylates tyrosine 705 (Y705) of STAT3, decreased Npy mRNA in arcuate immortalized hypothalamic neurons. In parallel, inhibitors of STAT3-Y705 phosphorylation, stattic and cucurbitacin I, robustly upregulated Npy mRNA. Chromatin-immunoprecipitation showed high baseline total STAT3 binding to multiple regulatory regions of the Npy gene, which are decreased by IL-6 exposure. The STAT3-Npy interaction was further examined in obesity-related pathologies. Notably, in four different hypothalamic neuronal models where palmitate potently stimulated Npy mRNA, Socs3, a specific STAT3 activity marker, was downregulated and was negatively correlated with Npy mRNA levels (R2 = 0.40, p < 0.001), suggesting that disrupted STAT3 signaling is involved in lipotoxicity-mediated dysregulation of Npy. Finally, human NPY SNPs that map to human obesity or body mass index were investigated for potential STAT3 binding sites. Although none of the SNPs were linked to direct STAT3 binding, analysis show that rs17149106 (-602 G > T) is located on an upstream enhancer element of NPY, where the variant is predicted to disrupt validated binding of KLF4, a known inhibitory cofactor of STAT3 and downstream effector of leptin signaling. Collectively, this study demonstrates that STAT3 signaling negatively regulates Npy transcription, and that disruption of this interaction may contribute to metabolic disorders.

Variant-to-function analysis of the childhood obesity chr12q13 locus implicates rs7132908 as a causal variant within the 3' UTR of FAIM2

The ch12q13 locus is among the most significant childhood obesity loci identified in genome-wide association studies. This locus resides in a non-coding region within FAIM2; thus, the underlying causal variant(s) presumably influence disease susceptibility via cis-regulation. We implicated rs7132908 as a putative causal variant by leveraging our in-house 3D genomic data and public domain datasets. Using a luciferase reporter assay, we observed allele-specific cis-regulatory activity of the immediate region harboring rs7132908. We generated isogenic human embryonic stem cell lines homozygous for either rs7132908 allele to assess changes in gene expression and chromatin accessibility throughout a differentiation to hypothalamic neurons, a key cell type known to regulate feeding behavior. The rs7132908 obesity risk allele influenced expression of FAIM2 and other genes and decreased the proportion of neurons produced by differentiation. We have functionally validated rs7132908 as a causal obesity variant that temporally regulates nearby effector genes and influences neurodevelopment and survival.

Disentangling associations between complex traits and cell types with seismic

Integrating single-cell RNA sequencing (scRNA-seq) with Genome-Wide Association Studies (GWAS) can help reveal GWAS-associated cell types, furthering our understanding of the cell-type-specific biological processes underlying complex traits and disease. However, current methods have technical limitations that hinder them from making systematic, scalable, interpretable disease-cell-type associations. In order to rapidly and accurately pinpoint associations, we develop a novel framework, seismic, which characterizes cell types using a new specificity score. We compare seismic with alternative methods across over 1,000 cell type characterizations at different granularities and 28 traits, demonstrating that seismic both corroborates findings and identifies trait-relevant cell groups which are not apparent through other methodologies. Furthermore, as part of the seismic framework, the specific genes driving cell type-trait associations can easily be accessed and analyzed, enabling further biological insights. The advantages of seismic are particularly salient in neurodegenerative diseases such as Parkinson's and Alzheimer's, where disease pathology has not only cell-specific manifestations, but also brain region-specific differences. Interestingly, a case study of Alzheimer's disease reveals the importance of considering GWAS endpoints, as studies relying on clinical diagnoses consistently identify microglial associations, while GWAS with a tau biomarker endpoint reveals neuronal associations. In general, seismic is a computationally efficient, powerful, and interpretable approach for identifying associations between complex traits and cell type-specific expression.

Diviner uncovers hundreds of novel human (and other) exons though comparative analysis of proteins

Background

Eukaryotic genes are often composed of multiple exons that are stitched together by splicing out the intervening introns. These exons may be conditionally joined in different combinations to produce a collection of related, but distinct, mRNA transcripts. For protein-coding genes, these products of alternative splicing lead to production of related protein variants (isoforms) of a gene. Complete labeling of the protein-coding content of a eukaryotic genome requires discovery of mRNA encoding all isoforms, but it is impractical to enumerate all possible combinations of tissue, developmental stage, and environmental context; as a result, many true exons go unlabeled in genome annotations.

Results

One way to address the combinatoric challenge of finding all isoforms in a single organism A is to leverage sequencing efforts for other organisms - each time a new organism is sequenced, it may be under a new combination of conditions, so that a previously unobserved isoform may be sequenced. We present Diviner, a software tool that identifies previously undocumented exons in organisms by comparing isoforms across species. We demonstrate Diviner's utility by locating hundreds of novel exons in the genomes of human, mouse, and rat, as well as in the ferret genome. Further, we provide analyses supporting the notion that most of the new exons reported by Diviner are likely to be part of a true (but unobserved) isoform of the containing species.

Population Genomic History of the Endangered Anatolian and Cyprian Mouflons in Relation to Worldwide Wild, Feral, and Domestic Sheep Lineages

Once widespread in their homelands, the Anatolian mouflon (Ovis gmelini anatolica) and the Cyprian mouflon (Ovis gmelini ophion) were driven to near extinction during the 20th century and are currently listed as endangered populations by the International Union for Conservation of Nature. While the exact origins of these lineages remain unclear, they have been suggested to be close relatives of domestic sheep or remnants of proto-domestic sheep. Here, we study whole genome sequences of n = 5 Anatolian mouflons and n = 10 Cyprian mouflons in terms of population history and diversity, comparing them with eight other extant sheep lineages. We find reciprocal genetic affinity between Anatolian and Cyprian mouflons and domestic sheep, higher than all other studied wild sheep genomes, including the Iranian mouflon (O. gmelini). Studying diversity indices, we detect a considerable load of short runs of homozygosity blocks (<2 Mb) in both Anatolian and Cyprian mouflons, reflecting small effective population size (Ne). Meanwhile, Ne and mutation load estimates are lower in Cyprian compared with Anatolian mouflons, suggesting the purging of recessive deleterious variants in Cyprian sheep under a small long-term Ne, possibly attributable to founder effects, island isolation, introgression from domestic lineages, or differences in their bottleneck dynamics. Expanding our analyses to worldwide wild and feral Ovis genomes, we observe varying viability metrics among different lineages and a limited consistency between viability metrics and International Union for Conservation of Nature conservation status. Factors such as recent inbreeding, introgression, and unique population dynamics may have contributed to the observed disparities.

Estimating the serological underrecognition of patients with weak or partial RHD variants

BACKGROUND

For patients with weak or discrepant RhD RBC phenotypes, RHD genotyping is employed to determine need for RhD-negative management. However, many RHD variants are type D-negative or D-positive. Serological recognition rates (RRs) of weak and partial RHD variants are poorly characterized.

STUDY DESIGN AND METHODS

Four US studies employing RHD genotyping for weak or discrepant RhD phenotypes provided data for race/ethnicity-specific serological recognition. Three studies used microplate, and 1 used gel and tube; 2 had anti-D data. We obtained White and Hispanic/Latino allele frequencies (AFs) of weak D types 1, 2, and 3 single-nucleotide variants (SNVs) from the Genome Aggregation Database (gnomAD, v4.0.0) and devised Hardy-Weinberg-based formulas to correct for gnomAD's overcount of hemizygous RHD SNVs as homozygous. We compiled common partial RHD AF from genotyped cohorts of US Black or sickle cell disease subjects. From variant AF, we calculated hemizygous-plus-homozygous genetic prevalences. Serological prevalence: genetic prevalence ratios yielded serological RRs.

RESULTS

Overall RRs of weak D types 1-3 were 17% (95% confidence interval 12%-24%) in Whites and 12% (5%-27%) in Hispanics/Latinos. For eight partial RHD variants in Blacks, overall RR was 11% (8%-14%). However, DAR RR was 80% (38%-156%). Compared to microplate, gel-tube recognition was higher for type 2 and DAU5 and lower for type 4.0. Anti-D was present in 6% of recognized partial RHD cases, but only in 0.7% of estimated total genetic cases.

DISCUSSION

Based on AF, >80% of patients with weak or partial RHD variants were unrecognized serologically. Although overall anti-D rates were low, better detection of partial RHD variants is desirable.

The NCBI Comparative Genome Viewer (CGV) is an interactive visualization tool for the analysis of whole-genome eukaryotic alignments

We report a new visualization tool for analysis of whole-genome assembly-assembly alignments, the Comparative Genome Viewer (CGV) (https://ncbi.nlm.nih.gov/genome/cgv/). CGV visualizes pairwise same-species and cross-species alignments provided by National Center for Biotechnology Information (NCBI) using assembly alignment algorithms developed by us and others. Researchers can examine large structural differences spanning chromosomes, such as inversions or translocations. Users can also navigate to regions of interest, where they can detect and analyze smaller-scale deletions and rearrangements within specific chromosome or gene regions. RefSeq or user-provided gene annotation is displayed where available. CGV currently provides approximately 800 alignments from over 350 animal, plant, and fungal species. CGV and related NCBI viewers are undergoing active development to further meet needs of the research community in comparative genome visualization.

Altered Rbfox1-Vamp1 pathway and prefrontal cortical dysfunction in schizophrenia

Deficient gamma oscillations in prefrontal cortex (PFC) of individuals with schizophrenia appear to involve impaired inhibitory drive from parvalbumin-expressing interneurons (PVIs). Inhibitory drive from PVIs is regulated, in part, by RNA binding fox-1 homolog 1 (Rbfox1). Rbfox1 is spliced into nuclear or cytoplasmic isoforms, which regulate alternative splicing or stability of their target transcripts, respectively. One major target of cytoplasmic Rbfox1 is vesicle associated membrane protein 1 (Vamp1). Vamp1 mediates GABA release probability from PVIs, and the loss of Rbfox1 reduces Vamp1 levels which in turn impairs cortical inhibition. In this study, we investigated if the Rbfox1-Vamp1 pathway is altered in PVIs in PFC of individuals with schizophrenia by utilizing a novel strategy that combines multi-label in situ hybridization and immunohistochemistry. In the PFC of 20 matched pairs of schizophrenia and comparison subjects, cytoplasmic Rbfox1 protein levels were significantly lower in PVIs in schizophrenia and this deficit was not attributable to potential methodological confounds or schizophrenia-associated co-occurring factors. In a subset of this cohort, Vamp1 mRNA levels in PVIs were also significantly lower in schizophrenia and were predicted by lower cytoplasmic Rbfox1 protein levels across individual PVIs. To investigate the functional impact of Rbfox1-Vamp1 alterations in schizophrenia, we simulated the effect of lower GABA release probability from PVIs on gamma power in a computational model network of pyramidal neurons and PVIs. Our simulations showed that lower GABA release probability reduces gamma power by disrupting network synchrony while minimally affecting network activity. Finally, lower GABA release probability synergistically interacted with lower strength of inhibition from PVIs in schizophrenia to reduce gamma power non-linearly. Together, our findings suggest that the Rbfox1-Vamp1 pathway in PVIs is impaired in schizophrenia and that this alteration likely contributes to deficient PFC gamma power in the illness.

Obesity during preclinical Alzheimer's disease development exacerbates brain metabolic decline

Alzheimer's disease (AD) is the most common form of dementia. Obesity in middle age increases AD risk and severity, which is alarming given that obesity prevalence peaks at middle age and obesity rates are accelerating worldwide. Midlife, but not late-life obesity increases AD risk, suggesting that this interaction is specific to preclinical AD. AD pathology begins in middle age, with accumulation of amyloid beta (Aβ), hyperphosphorylated tau, metabolic decline, and neuroinflammation occurring decades before cognitive symptoms appear. We used a transcriptomic discovery approach in young adult (6.5 months old) male and female TgF344-AD rats that overexpress mutant human amyloid precursor protein and presenilin-1 and wild-type (WT) controls to determine whether inducing obesity with a high-fat/high-sugar "Western" diet during preclinical AD increases brain metabolic dysfunction in dorsal hippocampus (dHC), a brain region vulnerable to the effects of obesity and early AD. Analyses of dHC gene expression data showed dysregulated mitochondrial and neurotransmission pathways, and up-regulated genes involved in cholesterol synthesis. Western diet amplified the number of genes that were different between AD and WT rats and added pathways involved in noradrenergic signaling, dysregulated inhibition of cholesterol synthesis, and decreased intracellular lipid transporters. Importantly, the Western diet impaired dHC-dependent spatial working memory in AD but not WT rats, confirming that the dietary intervention accelerated cognitive decline. To examine later consequences of early transcriptional dysregulation, we measured dHC monoamine levels in older (13 months old) AD and WT rats of both sexes after long-term chow or Western diet consumption. Norepinephrine (NE) abundance was significantly decreased in AD rats, NE turnover was increased, and the Western diet attenuated the AD-induced increases in turnover. Collectively, these findings indicate obesity during prodromal AD impairs memory, potentiates AD-induced metabolic decline likely leading to an overproduction of cholesterol, and interferes with compensatory increases in NE transmission.

The Maintenance of Deleterious Variation in Wild Chinese Rhesus Macaques

Understanding how deleterious variation is shaped and maintained in natural populations is important in conservation and evolutionary biology, as decreased fitness caused by these deleterious mutations can potentially lead to an increase in extinction risk. It is known that demographic processes can influence these patterns. For example, population bottlenecks and inbreeding increase the probability of inheriting identical-by-descent haplotypes from a recent common ancestor, creating long tracts of homozygous genotypes called runs of homozygosity (ROH), which have been associated with an accumulation of mildly deleterious homozygotes. Counter intuitively, positive selection can also maintain deleterious variants in a population through genetic hitchhiking. Here we analyze the whole genomes of 79 wild Chinese rhesus macaques across five subspecies and characterize patterns of deleterious variation with respect to ROH and signals of recent positive selection. We show that the fraction of homozygotes occurring in long ROH is significantly higher for deleterious homozygotes than tolerated ones, whereas this trend is not observed for short and medium ROH. This confirms that inbreeding, by generating these long tracts of homozygosity, is the main driver of the high burden of homozygous deleterious alleles in wild macaque populations. Furthermore, we show evidence that homozygous LOF variants are being purged. Next, we identify 7 deleterious variants at high frequency in regions putatively under selection near genes involved with olfaction and other processes. Our results shed light on how evolutionary processes can shape the distribution of deleterious variation in wild non-human primates.

Minimum information and guidelines for reporting a multiplexed assay of variant effect

Multiplexed assays of variant effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines have led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs.

Combined and differential roles of ADD domains of DNMT3A and DNMT3L on DNA methylation landscapes in mouse germ cells

DNA methyltransferase 3A (DNMT3A) and its catalytically inactive cofactor DNA methyltransferase 3-Like (DNMT3L) proteins form functional heterotetramers to deposit DNA methylation in mammalian germ cells. While both proteins have an ATRX-DNMT3-DNMT3L (ADD) domain that recognizes histone H3 tail unmethylated at lysine-4 (H3K4me0), the combined and differential roles of the domains in the two proteins have not been fully defined in vivo. Here we investigate DNA methylation landscapes in female and male germ cells derived from mice with loss-of-function amino acid substitutions in the ADD domains of DNMT3A and/or DNMT3L. Mutations in either the DNMT3A-ADD or the DNMT3L-ADD domain moderately decrease global CG methylation levels, but to different degrees, in both germ cells. Furthermore, when the ADD domains of both DNMT3A and DNMT3L lose their functions, the CG methylation levels are much more reduced, especially in oocytes, comparable to the impact of the Dnmt3a/3L knockout. In contrast, aberrant accumulation of non-CG methylation occurs at thousands of genomic regions in the double mutant oocytes and spermatozoa. These results highlight the critical role of the ADD-H3K4me0 binding in proper CG and non-CG methylation in germ cells and the various impacts of the ADD domains of the two proteins.

Genome-wide DNA methylation analysis in female veterans with military sexual trauma and comorbid PTSD/MDD

BACKGROUND

Military sexual trauma (MST) is a prevalent issue within the U.S. military. Victims are more likely to develop comorbid diseases such as posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). Nonetheless, not everyone who suffers from MST develops PTSD and/or MDD. DNA methylation, which can regulate gene expression, might give us insight into the molecular mechanisms behind this discrepancy. Therefore, we sought to identify genomic loci and enriched biological pathways that differ between patients with and without MST, PTSD, and MDD.

METHODS

Saliva samples were collected from 113 female veterans. Following DNA extraction and processing, DNA methylation levels were measured through the Infinium HumanMethylationEPIC BeadChip array. We used limma and bump hunting methods to generate the differentially methylated positions and differentially methylated regions (DMRs), respectively. Concurrently, we used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome to find enriched pathways.

RESULTS

A DMR close to the transcription start site of ZFP57 was differentially methylated between subjects with and without PTSD, replicating previous findings and emphasizing the potential role of ZFP57 in PTSD susceptibility. In the pathway analyses, none survived multiple correction, although top GO terms included some potentially relevant to MST, PTSD, and MDD etiology.

CONCLUSION

We conducted one of the first DNA methylation analyses investigating MST along with PTSD and MDD. In addition, we found one DMR near ZFP57 to be associated with PTSD. The replication of this finding indicates further investigation of ZFP57 in PTSD may be warranted.

scRNA-seq characterizing the heterogeneity of fibroblasts in breast cancer reveals a novel subtype SFRP4+ CAF that inhibits migration and predicts prognosis

Introduction

Cancer-associated fibroblasts (CAFs) are a diverse group of cells that significantly impact the tumor microenvironment and therapeutic responses in breast cancer (BC). Despite their importance, the comprehensive profile of CAFs in BC remains to be fully elucidated.

Methods

To address this gap, we utilized single-cell RNA sequencing (scRNA-seq) to delineate the CAF landscape within 14 BC normal-tumor paired samples. We further corroborated our findings by analyzing several public datasets, thereby validating the newly identified CAF subtype. Additionally, we conducted coculture experiments with BC cells to assess the functional implications of this CAF subtype.

Results

Our scRNA-seq analysis unveiled eight distinct CAF subtypes across five tumor and six adjacent normal tissue samples. Notably, we discovered a novel subtype, designated as SFRP4+ CAFs, which was predominantly observed in normal tissues. The presence of SFRP4+ CAFs was substantiated by two independent scRNA-seq datasets and a spatial transcriptomics dataset. Functionally, SFRP4+ CAFs were found to impede BC cell migration and the epithelial-mesenchymal transition (EMT) process by secreting SFRP4, thereby modulating the WNT signaling pathway. Furthermore, we established that elevated expression levels of SFRP4+ CAF markers correlate with improved survival outcomes in BC patients, yet paradoxically, they predict a diminished response to neoadjuvant chemotherapy in cases of triple-negative breast cancer.

Conclusion

This investigation sheds light on the heterogeneity of CAFs in BC and introduces a novel SFRP4+ CAF subtype that hinders BC cell migration. This discovery holds promise as a potential biomarker for refined prognostic assessment and therapeutic intervention in BC.

An efficient and robust ABC approach to infer the rate and strength of adaptation

Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in nonmodel species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to nonmodel genomes. We apply ABC-MK to the human proteome and a set of known virus interacting proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.

Accurate Bayesian inference of sex chromosome karyotypes and sex-linked scaffolds from low-depth sequencing data

The identification of sex-linked scaffolds and the genetic sex of individuals, i.e. their sex karyotype, is a fundamental step in population genomic studies. If sex-linked scaffolds are known, single individuals may be sexed based on read counts of next-generation sequencing data. If both sex-linked scaffolds as well as sex karyotypes are unknown, as is often the case for non-model organisms, they have to be jointly inferred. For both cases, current methods rely on arbitrary thresholds, which limits their power for low-depth data. In addition, most current methods are limited to euploid sex karyotypes (XX and XY). Here we develop BeXY, a fully Bayesian method to jointly infer the posterior probabilities for each scaffold to be autosomal, X- or Y-linked and for each individual to be any of the sex karyotypes XX, XY, X0, XXX, XXY, XYY and XXYY. If the sex-linked scaffolds are known, it also identifies autosomal trisomies and estimates the sex karyotype posterior probabilities for single individuals. As we show with downsampling experiments, BeXY has higher power than all existing methods. It accurately infers the sex karyotype of ancient human samples with as few as 20,000 reads and accurately infers sex-linked scaffolds from data sets of just a handful of samples or with highly imbalanced sex ratios, also in the case of low-quality reference assemblies. We illustrate the power of BeXY by applying it to both whole-genome shotgun and target enrichment sequencing data of ancient and modern humans, as well as several non-model organisms.

Genotype-phenotype associations in 1018 individuals with SCN1A-related epilepsies

OBJECTIVE

SCN1A variants are associated with epilepsy syndromes ranging from mild genetic epilepsy with febrile seizures plus (GEFS+) to severe Dravet syndrome (DS). Many variants are de novo, making early phenotype prediction difficult, and genotype-phenotype associations remain poorly understood.

METHODS

We assessed data from a retrospective cohort of 1018 individuals with SCN1A-related epilepsies. We explored relationships between variant characteristics (position, in silico prediction scores: Combined Annotation Dependent Depletion (CADD), Rare Exome Variant Ensemble Learner (REVEL), SCN1A genetic score), seizure characteristics, and epilepsy phenotype.

RESULTS

DS had earlier seizure onset than other GEFS+ phenotypes (5.3 vs. 12.0 months, p < .001). In silico variant scores were higher in DS versus GEFS+ (p < .001). Patients with missense variants in functionally important regions (conserved N-terminus, S4-S6) exhibited earlier seizure onset (6.0 vs. 7.0 months, p = .003) and were more likely to have DS (280/340); those with missense variants in nonconserved regions had later onset (10.0 vs. 7.0 months, p = .036) and were more likely to have GEFS+ (15/29, χ2 = 19.16, p < .001). A minority of protein-truncating variants were associated with GEFS+ (10/393) and more likely to be located in the proximal first and last exon coding regions than elsewhere in the gene (9.7% vs. 1.0%, p < .001). Carriers of the same missense variant exhibited less variability in age at seizure onset compared with carriers of different missense variants for both DS (1.9 vs. 2.9 months, p = .001) and GEFS+ (8.0 vs. 11.0 months, p = .043). Status epilepticus as presenting seizure type is a highly specific (95.2%) but nonsensitive (32.7%) feature of DS.

SIGNIFICANCE

Understanding genotype-phenotype associations in SCN1A-related epilepsies is critical for early diagnosis and management. We demonstrate an earlier disease onset in patients with missense variants in important functional regions, the occurrence of GEFS+ truncating variants, and the value of in silico prediction scores. Status epilepticus as initial seizure type is a highly specific, but not sensitive, early feature of DS.

Development of a rapid and comprehensive genomic profiling test supporting diagnosis and research for gliomas

A prompt and reliable molecular diagnosis for brain tumors has become crucial in precision medicine. While Comprehensive Genomic Profiling (CGP) has become feasible, there remains room for enhancement in brain tumor diagnosis due to the partial lack of essential genes and limitations in broad copy number analysis. In addition, the long turnaround time of commercially available CGPs poses an additional obstacle to the timely implementation of results in clinics. To address these challenges, we developed a CGP encompassing 113 genes, genome-wide copy number changes, and MGMT promoter methylation. Our CGP incorporates not only diagnostic genes but also supplementary genes valuable for research. Our CGP enables us to simultaneous identification of mutations, gene fusions, focal and broad copy number alterations, and MGMT promoter methylation status, with results delivered within a minimum of 4 days. Validation of our CGP, through comparisons with whole-genome sequencing, RNA sequencing, and pyrosequencing, has certified its accuracy and reliability. We applied our CGP for 23 consecutive cases of intracranial mass lesions, which demonstrated its efficacy in aiding diagnosis and prognostication. Our CGP offers a comprehensive and rapid molecular profiling for gliomas, which could potentially apply to clinical practices and research primarily in the field of brain tumors.