Human genomics. The human transcriptome across tissues and individuals

Exploring the latent space of transcriptomic data with topic modeling

The availability of high-dimensional transcriptomic datasets is increasing at a tremendous pace, together with the need for suitable computational tools. Clustering and dimensionality reduction methods are popular go-to methods to identify basic structures in these datasets. At the same time, different topic modeling techniques have been developed to organize the deluge of available data of natural language using their latent topical structure. This paper leverages the statistical analogies between text and transcriptomic datasets to compare different topic modeling methods when applied to gene expression data. Specifically, we test their accuracy in the specific task of discovering and reconstructing the tissue structure of the human transcriptome and distinguishing healthy from cancerous tissues. We examine the properties of the latent space recovered by different methods, highlight their differences, and their pros and cons across different tasks. We focus in particular on how different statistical priors can affect the results and their interpretability. Finally, we show that the latent topic space can be a useful low-dimensional embedding space, where a basic neural network classifier can annotate transcriptomic profiles with high accuracy.

A CRISPR/Cas9-based enhancement of high-throughput single-cell transcriptomics

Single-cell RNA-seq (scRNAseq) struggles to capture the cellular heterogeneity of transcripts within individual cells due to the prevalence of highly abundant and ubiquitous transcripts, which can obscure the detection of biologically distinct transcripts expressed up to several orders of magnitude lower levels. To address this challenge, here we introduce single-cell CRISPRclean (scCLEAN), a molecular method that globally recomposes scRNAseq libraries, providing a benefit that cannot be recapitulated with deeper sequencing. scCLEAN utilizes the programmability of CRISPR/Cas9 to target and remove less than 1% of the transcriptome while redistributing approximately half of reads, shifting the focus toward less abundant transcripts. We experimentally apply scCLEAN to both heterogeneous immune cells and homogenous vascular smooth muscle cells to demonstrate its ability to uncover biological signatures in different biological contexts. We further emphasize scCLEAN's versatility by applying it to a third-generation sequencing method, single-cell MAS-Seq, to increase transcript-level detection and discovery. Here we show the possible utility of scCLEAN across a wide array of human tissues and cell types, indicating which contexts this technology proves beneficial and those in which its application is not advisable.

Advancing forensic body fluid identification: A comparative analysis of RT-LAMP+CRISPR-Cas12a and established mRNA-based methods

In forensic science, the analysis of body fluid evidence determines the cellular origin of a sample, aiding in the reconstruction of a potential crime. Messenger ribonucleic acid (mRNA) based confirmatory tests address limitations of current conventional methods, providing increased specificity and sensitivity, minimal sample consumption, and the detection of a broader range of body fluids. However, they require expensive instrumentation, longer reaction times, and lack portability. Reverse-transcription loop-mediated isothermal amplification (RT-LAMP) coupled with clustered regular interspaced short palindromic repeats (CRISPR) with CRISPR-associated protein 12a (Cas12a) has the potential to overcome these challenges. This approach offers reduced testing time and cost, while potentially providing equivalent sensitivity and specificity, as observed in the field of viral diagnostics. Visual detection capabilities enable the development of rapid, portable screening tests suitable for testing at the crime scene. In the context of a sexual assault investigation, RT-LAMP+CRISPR-Cas12a could potentially increase the efficiency and detection rate. This study compares this novel method to two other mRNA-based methods, endpoint reverse transcription polymerase chain reaction (RT-PCR) multiplex assay CellTyper 2, and a real-time reverse transcription quantitative PCR (RT-qPCR) multiplex assay. The tests' sensitivity and specificity were evaluated on single-source and mixed body fluid samples, including rectal mucosa, a fluid which is minimally explored in forensic literature. The RT-qPCR assay demonstrated the highest sensitivity, specificity, and precision in mixed samples. In addition, RT-qPCR offers a greater linear dynamic range, faster processing time and easier methodology compared to CellTyper 2, only limited by its expensive nature. Notably, rectal mucosa samples exhibited non-specific marker expression of CellTyper 2 markers and expression of CYP2B7P (vaginal fluid) for all methods. This emphasises the need for a dedicated rectal mucosa marker. RT-LAMP+CRISPR-Cas12a exhibited a high specificity, displaying off-target expression of CYP2B7P in two fluid types. However, the method lacked sensitivity and precision for most markers except MMP3 (menstrual blood), demonstrating detection down to 1:10,000 with 100 % specificity. RT-LAMP+CRISPR requires further development, but its quick, inexpensive nature and high specificity suggest it has potential as a confirmatory test that could reduce the limitations of existing methods.

An ultrasensitive method for detection of cell-free RNA

Sensitive methods for detection of cell-free RNA (cfRNA) could facilitate non-invasive gene expression profiling and monitoring of diseases1-6. Here we describe RARE-seq (random priming and affinity capture of cfRNA fragments for enrichment analysis by sequencing), a method optimized for cfRNA analysis. We demonstrate that platelet contamination can substantially confound cfRNA analyses and develop an approach to overcome it. In analytical validations, we find RARE-seq to be approximately 50-fold more sensitive for detecting tumour-derived cfRNA than whole-transcriptome RNA sequencing (RNA-seq), with a limit of detection of 0.05%. To explore clinical utility, we profiled 437 plasma samples from 369 individuals with cancer or non-malignant conditions and controls. Detection of non-small-cell lung cancer expression signatures in cfRNA increased with stage (6 out of 20 (30%) in stage I; 5 out of 8 (63%) in stage II; 10 out of 15 (67%) in stage III; 80 out of 96 (83% sensitivity) in stage IV at 95% specificity) and RARE-seq was more sensitive than tumour-naive circulating tumour DNA (ctDNA) analysis. In patients with EGFR-mutant non-small-cell lung cancer who developed resistance to tyrosine kinase inhibitors, we detected both histological transformation and mutation-based resistance mechanisms. Finally, we demonstrate the potential utility of RARE-seq for determination of tissue of origin, assessing benign pulmonary conditions and tracking response to mRNA vaccines. These results highlight the potential value of ultrasensitive cfRNA analysis and provide proof of concept for diverse clinical applications.

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.

Defects in mRNA splicing and implications for infertility: a comprehensive review and in silico analysis

BACKGROUND

mRNA splicing is a fundamental process in the reproductive system, playing a pivotal role in reproductive development and endocrine function, and ensuring the proper execution of meiosis, mitosis, and gamete function. Trans-acting factors and cis-acting elements are key players in mRNA splicing whose dysfunction can potentially lead to male and female infertility. Although hundreds of trans-acting factors have been implicated in mRNA splicing, the mechanisms by which these factors influence reproductive processes are fully understood for only a subset. Furthermore, the clinical impact of variations in cis-acting elements on human infertility has not been comprehensively characterized, leading to probable omissions of pathogenic variants in standard genetic analyses.

OBJECTIVE AND RATIONALE

This review aimed to summarize our current understanding of the factors involved in mRNA splicing regulation and their association with infertility disorders. We introduced methods for prioritizing and functionally validating splicing variants associated with human infertility. Additionally, we explored corresponding abnormal splicing therapies that could potentially provide insight into treating human infertility.

SEARCH METHODS

Systematic literature searches of human and model organisms were performed in the PubMed database between May 1977 and July 2024. To identify mRNA splicing-related genes and pathogenic variants in infertility, the search terms 'splice', 'splicing', 'variant', and 'mutation' were combined with azoospermia, oligozoospermia, asthenozoospermia, multiple morphological abnormalities of the sperm flagella, acephalic spermatozoa, disorders of sex development, early embryonic arrest, reproductive endocrine disorders, oocyte maturation arrest, premature ovarian failure, primary ovarian insufficiency, zona pellucida, fertilization defects, infertile, fertile, infertility, fertility, reproduction, and reproductive.

OUTCOMES

Our search identified 5014 publications, of which 291 were included in the final analysis. This review provided a comprehensive overview of the biological mechanisms of mRNA splicing, with a focus on the roles of trans-acting factors and cis-acting elements. We highlighted the disruption of 52 trans-acting proteins involved in spliceosome assembly and catalytic activity and recognized splicing regulatory regions and epigenetic regulation associated with infertility. The 73 functionally validated splicing variants in the cis-acting elements of 54 genes have been reported in 20 types of human infertility; 27 of them were located outside the canonical splice sites and potentially overlooked in standard genetic analysis due to likely benign or of uncertain significance. The in silico prediction of splicing can prioritize potential splicing abnormalities that may be true pathogenic mechanisms. We also summarize the methods for prioritizing splicing variants and strategies for functional validation and review splicing therapy approaches for other diseases, providing a reference for abnormal reproduction treatment.

WIDER IMPLICATIONS

Our comprehensive review of trans-acting factors and cis-acting elements in mRNA splicing will further promote a more thorough understanding of reproductive regulatory processes, leading to improved pathogenic variant identification and potential treatments for human infertility.

REGISTRATION NUMBER

N/A.

The network response to Egf is tissue-specific

Epidermal growth factor receptor (Egfr)-driven signaling regulates fundamental homeostatic processes. Dysregulated signaling via Egfr is implicated in numerous disease pathologies and distinct Egfr-associated disease etiologies are known to be tissue-specific. The molecular basis of this tissue-specificity remains poorly understood. Most studies of Egfr signaling to date have been performed in vitro or in tissue-specific mouse models of disease, which has limited insight into Egfr signaling patterns in healthy tissues. Here, we carried out integrated phosphoproteomic, proteomic, and transcriptomic analyses of signaling changes across various mouse tissues in response to short-term stimulation with the Egfr ligand Egf. We show how both baseline and Egf-stimulated signaling dynamics differ between tissues. Moreover, we propose how baseline phosphorylation and total protein levels may be associated with clinically relevant tissue-specific Egfr-associated phenotypes. Altogether, our analyses illustrate tissue-specific effects of Egf stimulation and highlight potential links between underlying tissue biology and Egfr signaling output.

High tissue specificity of lncRNAs maximises the prediction of tissue of origin of circulating DNA

Several studies have made it possible to envision a translational application of plasma DNA sequencing in cancer diagnosis and monitoring. However, the extremely low concentration of circulating tumour DNA (ctDNA) fragments among the total cell-free DNA (cfDNA) remains a formidable challenge to overcome and statistical models have yet to be improved enough to become of practical use. In this study, we set about appraising the predictive value of a variety of binary classification models based on cfDNA sequencing using fragmentation features extracted around transcription start sites (TSSs). We investigated (1) features summarising mapped fragment density around each TSS, (2) long non-coding RNA (lncRNA) genes versus coding genes and (3) selection criteria to generate gene classes to be assigned by the model. Given that, in healthy samples, most of the cfDNA comes from lymphomyeloid lineages, we could identify the model parametrisation with the best accuracy in those lineages using publicly available datasets of healthy patients' cfDNA. Our results show that (1) the way tissue-specific gene classes are defined matters more than what fragmentation features are included, and (2) in particular, lncRNAs are more tissue specific than coding genes and stand out in terms of both sensitivity and specificity in our results.

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.

Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms

Most human transcription factor (TF) genes encode multiple protein isoforms differing in DNA-binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators," both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.

Are pre-analytical factors fully considered in forensic FFPE molecular analyses? A systematic review reveals the need for standardised procedures

The need for molecular analyses has become increasingly common in the forensic sciences, particularly in forensic pathology, to better shape the causes of death. This approach is called the "molecular autopsy," where conventional medico-legal findings are often enhanced with specific molecular tests to provide reliable clinical and forensic diagnoses. In this context, FFPE (Formalin-Fixed Paraffin-Embedded) tissue samples collected during forensic autopsies are the only available specimens in retrospective studies for molecular DNA and/or RNA analyses. It is well known that pre-analytical parameters such as the agonal time, the PMI (Post-Mortem Interval), the fixation procedures, and the FFPE ageing and storage conditions can deeply impact the quality and quantity of the recovered nucleic acids, thus influencing the reliability of the downstream molecular tests. In the present study, we reviewed the recent forensic literature to establish whether these parameters are reported. Our survey showed that up to 34.9% and 40.5% of the 50 selected studies on DNA and RNA, respectively, reported the pre-analytical parameters mentioned above. Many publications did not report the length of agony (if any), which is an important parameter in RNA-based studies and estimations of the PMI; in addition, even relevant information on formalin tissue fixation procedures was often missing, thus impairing any critical evaluation of the PCR-based results. To address these issues, we propose the use of a simple form we set up to be filled out by Forensic Pathologists, where each pre-analytical step concerning the tissue samples collected during autopsy is accurately described and reported. In our opinion, this standardization will help the forensic community compare and evaluate the results of different molecular tests, thus increasing the reliability of the molecular results in forensics.

A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines

The human genome contains instructions to transcribe more than 200,000 RNAs. However, many RNA transcripts are generated from the same gene, resulting in alternative isoforms that are highly similar and that remain difficult to quantify. To evaluate the ability to study RNA transcript expression, we profiled seven human cell lines with five different RNA-sequencing protocols, including short-read cDNA, Nanopore long-read direct RNA, amplification-free direct cDNA and PCR-amplified cDNA sequencing, and PacBio IsoSeq, with multiple spike-in controls, and additional transcriptome-wide N6-methyladenosine profiling data. We describe differences in read length, coverage, throughput and transcript expression, reporting that long-read RNA sequencing more robustly identifies major isoforms. We illustrate the value of the SG-NEx data to identify alternative isoforms, novel transcripts, fusion transcripts and N6-methyladenosine RNA modifications. Together, the SG-NEx data provide a comprehensive resource enabling the development and benchmarking of computational methods for profiling complex transcriptional events at isoform-level resolution.

Gene expression differences associated with alcohol use disorder in human brain

Excessive alcohol consumption is a leading cause of preventable death worldwide. To improve understanding of neurobiological mechanisms associated with alcohol use disorder (AUD) in humans, we compared gene expression data from deceased individuals with and without AUD across two addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC). Bulk RNA-seq data from NAc and DLPFC (N ≥50 with AUD, ≥46 non-AUD) were analyzed for differential gene expression using modified negative binomial regression adjusting for technical and biological covariates. The region-level results were meta-analyzed with those from an independent dataset (NNAc = 28 AUD, 29 non-AUD; NPFC = 66 AUD, 77 non-AUD). We further tested for heritability enrichment of AUD-related phenotypes, gene co-expression networks, gene ontology enrichment, and drug repurposing. We identified 176 differentially expressed genes (DEGs; 12 in both regions, 78 in NAc only, 86 in DLPFC only) for AUD in our new dataset. After meta-analyzing with published data, we identified 476 AUD DEGs (25 in both regions, 29 in NAc only, 422 in PFC only). Of these DEGs, 17 were significant when looked up in GWAS of problematic alcohol use or drinks per week. Gene co-expression analysis showed both concordant and unique gene networks across brain regions. We also identified 29 and 436 drug compounds that target DEGs from our meta-analysis in NAc and PFC, respectively. This study identified robust AUD-associated DEGs, contributing novel neurobiological insights into AUD and highlighting genes targeted by known drug compounds, generating opportunity for drug repurposing to treat AUD.

Computational Comparison of Differential Splicing Tools for Targeted RNA Long-Amplicon Sequencing (rLAS)

RNA sequencing (RNA-Seq) is a powerful technique for the quantification of transcripts and the analysis of alternative splicing. Previously, our laboratory developed the targeted RNA long-amplicon sequencing (rLAS) method, which has the advantage of allowing deep analysis of targeted specific transcripts. The computational tools for analyzing RNA-Seq data have boosted alternative splicing research by detecting and quantifying splicing events. However, the performance of these splicing tools has not yet been investigated for rLAS. Here, we evaluated the performance of four splicing tools (MAJIQ, rMATS, MISO, and SplAdder) using samples with different types of known splicing events (exon-skipping, multiple-exon-skipping, alternative 5' splicing, and alternative 3' splicing). MAJIQ was able to detect all of the types of events, but it was unable to detect one of the exon-skipping events. On the other hand, rMATS was able to detect all of the exon-skipping events. However, rMATS failed to detect other types of events besides exon-skipping events. Both MISO and SplAdder were unable to detect any of the events. These results indicate that MAJIQ presents better performance for the different types of splicing events in rLAS and that rMATS shows better performance for exon-skipping splicing events.

Novel biallelic COL25A1 variants broaden the clinical spectrum from congenital cranial dysinnervation disorders to fetal lethal phenotypes

Biallelic variants in COL25A1 have been associated with isolated congenital cranial dysinnervation disorders (CCDDs) and arthrogryposis multiplex congenital (AMC) with or without CCDD. COL25A1 encodes collagen XXV that belongs to the subfamily of membrane-associated collagens with interrupted triple helices. COL25A1 contains four non-collagenous and three collagenous domains. Three alternatively spliced COL25A1 transcript variants are known. In mice, Col25a1 is required for intramuscular motor innervation and cranial motor neuron development. We report seven subjects with novel biallelic COL25A1 pathogenic variants, including three AMC-affected individuals, one of whom died in infancy, and four unrelated fetuses. We expand the associated phenotypic spectrum as fetuses showed lethal phenotypes including reduced or no movement, contractures, and hydrops in three and growth retardation and skeletal abnormalities in one. The molecular spectrum includes two microdeletions encompassing several 5' or 3' exons, two missense, one nonsense, one frameshift, and one variant affecting splicing. In fibroblasts of the subject who was compound heterozygous for the c.367G > C and c.1198G > T variants, we identified skipping of exon 3 in COL25A1 mRNAs due to the G-to-C change. These aberrantly spliced transcripts were subject to nonsense-mediated mRNA decay. Analysis of transcriptome sequencing data from primary human fibroblasts without COL25A1 pathogenic variants revealed novel COL25A1 exon-exon junctions and 13 not previously annotated alternatively spliced in-frame exons. We hypothesized that interindividual variation in the splicing of COL25A1 exons in different tissues may underlie the variable phenotypes in the affected individuals.

Evaluating genetic-ancestry inference from single-cell RNA-seq data

Characterizing the ancestry of donors in single-cell RNA sequencing (scRNA-seq) studies is critical to ensure the genetic homogeneity of the dataset and reduce biases in analyses, to identify ancestry-specific regulatory mechanisms and understand their downstream role in diseases, and to ensure that existing datasets are representative of human genetic diversity. While scRNA-seq is now widely available, the information on the ancestry of the donors is often missing, hindering further analysis. Here we propose a framework to evaluate methods for inferring genetic-ancestry from genetic polymorphisms detected from scRNA-seq reads. We demonstrate that widely used tools (e.g., ADMIXTURE) provide accurate inference of genetic-ancestry and admixture proportions despite the limited number of genetic polymorphisms identified and imperfect variant calling from scRNA-seq reads. We inferred genetic-ancestry for 196 donors from four scRNA-seq datasets from the Human Cell Atlas and highlighted an extremely large proportion of donors of European ancestry. For researchers generating single-cell datasets, we recommend reporting genetic-ancestry inference for all donors and generating datasets that represent diverse ancestries.

PRMT7-Mediated PTEN Activation Enhances Bone Regeneration in Female Mice

Epigenetic regulation provides new insights into the mechanisms of osteogenic differentiation and identifies potential targets for treating bone-related diseases. However, the specific regulatory networks and mechanisms involved still need further investigation. In this study, we identify PRMT7 as a novel epigenetic regulator of mesenchymal stem cells (MSCs) osteogenic commitment. Conditional knockout of Prmt7 in mice reveals a significant impairment in osteogenesis and bone regeneration, specifically in females, affecting both femurs and mandibles, with no noticeable effect in males. Mechanistically, PRMT7 modulates MSCs osteogenic differentiation by activating PTEN. Specifically, PRMT7 enhances PTEN transcription by increasing H3R2me1 levels at the PTEN promoter. Additionally, PRMT7 interacts with the PTEN protein and stabilizes nuclear PTEN, revealing an unprecedented pathway. Notably, overexpression of PTEN alleviates the osteogenic deficits observed in Prmt7-deficient mice. This research establishes PRMT7 as a potential therapeutic target for promoting bone formation/regeneration and offers novel molecular insights into the PRMT7-PTEN regulatory axis, underscoring its significance in bone biology and regenerative medicine.

Regulation of LEAP2 by insulin and glucagon in mice and humans

Liver-expressed antimicrobial peptide 2 (LEAP2) is an endogenous antagonist and inverse agonist of the ghrelin receptor, countering ghrelin's effects on cell signaling and feeding. However, despite an emerging interest in LEAP2's physiology and pharmacology, its endocrine regulation remains unclear. Here, we report that plasma LEAP2 levels decrease significantly upon glucagon infusions during somatostatin clamps in humans. This effect is preserved in patients with obesity and type 2 diabetes while diminished following a hypercaloric diet and a sedentary lifestyle for 2 weeks. Additionally, insulin receptor antagonism offsets the upregulation of LEAP2 during the postprandial state in mice. Finally, insulin and glucagon receptor-expressing hepatocytes are the primary source of hepatic LEAP2 expression, coinciding with a putative enhancer-like signature bound by insulin- and glucagon-regulated transcription factors at the LEAP2 locus. Collectively, our findings implicate insulin and glucagon in regulating LEAP2 and warrant further investigations into the exact mechanisms orchestrating this endocrine axis.

Comparative analysis of genotype imputation strategies for SNPs calling from RNA-seq

BACKGROUND

RNA sequencing (RNA-seq) is a powerful tool for transcriptome profiling, enabling integrative studies of expression quantitative trait loci (eQTL). As it identifies fewer genetic variants than DNA sequencing (DNA-seq), reference panel-based genotype imputation is often required to enhance its utility.

RESULTS

This study evaluated the accuracy of genotype imputation using SNPs called from RNA-seq data (RNA-SNPs). SNP features from 6,567 RNA-seq samples across 28 pig tissues were used to mask whole genome sequencing (WGS) data, with the Pig Genomic Reference Panel (PGRP) serving as the reference panel. Three imputation software tools (i.e., Beagle, Minimac4, and Impute5) were employed to perform the imputation. The result showed that RNA-SNPs achieved higher imputation accuracy (CR: 0.895 ~ 0.933; r²: 0.745 ~ 0.817) than SNPs from GeneSeek Genomic Profiler Porcine SNP50 BeadChip (Chip-SNPs) (CR: 0.873 ~ 0.909; r²: 0.629 ~ 0.698), and lower accuracy in "intergenic" regions. After imputation, quality control (QC) by minor allele frequency (MAF) and imputation quality (DR²) could improve r² but reduce SNP retention. Among software, Minimac4 takes the least runtime in single-thread setting, while Beagle performed best in multi-thread setting and phasing. Impute5 takes up minimal memory usage but requires the maximum runtime. All tools demonstrated comparable global accuracy (CR: 0.906 ~ 0.917; r²: 0.780 ~ 0.787).

CONCLUSIONS

This study offers practical guidance for conducting RNA-SNP imputation strategies in genome and transcriptome research.

Transcriptome Complexity Disentangled: A Regulatory Molecules Approach

Transcription factors (TFs) and microRNAs (miRNAs) are fundamental regulators of gene expression, cell state, and biological processes. This study investigated whether a small subset of TFs and miRNAs could accurately predict genome-wide gene expression. We analyzed 8895 samples across 31 cancer types from The Cancer Genome Atlas and identified 28 miRNA and 28 TF clusters using unsupervised learning. Medoids of these clusters could differentiate tissues of origin with 92.8% accuracy, demonstrating their biological relevance. We developed Tissue-Agnostic and Tissue-Aware models to predict 20,000 gene expressions using the 56 selected medoid miRNAs and TFs. The Tissue-Aware model attained an R2 of 0.70 by incorporating tissue-specific information. Despite measuring only 1/400th of the transcriptome, the prediction accuracy was comparable to that achieved by the 1000 landmark genes. This suggests the transcriptome has an intrinsically low-dimensional structure that can be captured by a few regulatory molecules. Our approach could enable cheaper transcriptome assays and analysis of low-quality samples. It also provides insights into genes that are heavily regulated by miRNAs/TFs versus alternative mechanisms. However, model transportability was impacted by dataset discrepancies, especially in miRNA distribution. Overall, this study demonstrates the potential of a biology-guided approach for robust transcriptome representation.

Transcriptome Complexity Disentangled: A Regulatory Molecules Approach

Transcription factors (TFs) and microRNAs (miRNAs) are fundamental regulators of gene expression, cell state, and biological processes. This study investigated whether a small subset of TFs and miRNAs could accurately predict genome-wide gene expression. We analyzed 8895 samples across 31 cancer types from The Cancer Genome Atlas and identified 28 miRNA and 28 TF clusters using unsupervised learning. Medoids of these clusters could differentiate tissues of origin with 92.8% accuracy, demonstrating their biological relevance. We developed Tissue-Agnostic and Tissue-Aware models to predict 20,000 gene expressions using the 56 selected medoid miRNAs and TFs. The Tissue-Aware model attained anR 2 of 0.70 by incorporating tissue-specific information. Despite measuring only 1/400th of the transcriptome, the prediction accuracy was comparable to that achieved by the 1000 landmark genes. This suggests the transcriptome has an intrinsically low-dimensional structure that can be captured by a few regulatory molecules. Our approach could enable cheaper transcriptome assays and analysis of low-quality samples. It also provides insights into genes that are heavily regulated by miRNAs/TFs versus alternative mechanisms. However, model transportability was impacted by dataset discrepancies, especially in miRNA distribution. Overall, this study demonstrates the potential of a biology-guided approach for robust transcriptome representation.

An Ocular Gene-Set Expression Library for Heritability Partition and Cell Line Enrichment Analyses

Purpose

Use of genome-wide association studies (GWASs) in combination with transcriptomic arrays of different tissues or cell lines can reveal relevant cellular profiles and significantly improve understanding of the mechanisms of diseases. However, due to difficulty of access, few ocular transcriptomics datasets are available. This work aimed to create and make available an expression library platform that can be used with popular and versatile tools such as the linkage disequilibrium score (LDSC) regression techniques to identify specific cell lines enriched in ocular diseases.

Methods

We used transcriptome information from six publicly available single-cell and single-nucleus RNA sequence datasets to obtain matrices of normalized gene expression and estimated enrichment of the 10% most expressed transcripts in each cell line. We tested for type 1 error using simulated GWAS datasets and then used LDSC regression analyses to study the enrichment in different eye diseases.

Results

Gene expression databases for over 197 ocular cell lines were generated. Simulations of 1000 random GWASs of varying sample sizes showed no genomic inflation. Cell line-specific analyses of GWAS results found that genes near single nucleotide polymorphisms (SNPs) associated with refractive error were significantly enriched in cones (P = 0.008), rods (P = 0.002) and peripheral retina Müller cells (P = 0.002), juxtacanalicular cribriform cells (P = 0.0017), stromal keratocytes (P = 0.0018), and one beam-cell subpopulation (P = 0.0028) in primary open-angle glaucoma, emphasizing the importance of intraocular pressure in its etiology.

Conclusions

We have built a structured ocular transcriptomics library to estimate cell line enrichment among association signals from genome-wide association studies that may be extended by incorporating other datasets. We identified cells that appear important in the genetics of common eye diseases.

Mapping naturally presented T cell antigens in medulloblastoma based on integrative multi-omics

Medulloblastoma is the most frequent malignant primary brain tumor in children. Despite recent advances in integrated genomics, the prognosis in children with high-risk medulloblastoma remains devastating, and new tumor-specific therapeutic approaches are needed. Here, we present an atlas of naturally presented T cell antigens in medulloblastoma. We map the human leukocyte antigen (HLA)-presented peptidomes of 28 tumors and perform comparative immunopeptidome profiling against an in-house benign database. Medulloblastoma is shown to be a rich source of tumor-associated antigens, naturally presented on HLA class I and II molecules. Remarkably, most tumor-associated peptides and proteins are subgroup-specific, whereas shared presentation among all subgroups of medulloblastoma (WNT, SHH, Group 3 and Group 4) is rare. Functional testing of top-ranking novel candidate antigens demonstrates the induction of peptide-specific T cell responses, supporting their potential for T cell immunotherapy. This study is an in-depth mapping of naturally presented T cell antigens in medulloblastoma. Integration of immunopeptidomics, transcriptomics, and epigenetic data leads to the identification of a large set of actionable targets that can be further used for the translation into the clinical setting by facilitating the informed design of immunotherapeutic approaches to children with medulloblastoma.

A multi-class support vector machine classification model based on 14 microRNAs for forensic body fluid identification

MicroRNAs (miRNAs) are promising biomarkers for forensic body fluid identification owing to their small size, stability against degradation, and differential expression patterns. However, the expression of most body fluid-miRNAs is relative (differentially expressed in certain body fluids) rather than absolute (exclusively expressed in a specific body fluid). Moreover, different body fluids contain heterogeneous cell types, complicating their identification. Therefore, appropriate normalization strategies to eliminate non-biological variations and robust models to interpret expression levels accurately are necessary prerequisites for applying miRNAs in body fluid identification. In this study, the expression stability of six candidate reference genes (RGs) across five body fluids was validated using geNorm, NormFinder, BestKeeper and RankAggreg, and the most suitable combination of RGs (hsa-miR-484 and hsa-miR-191-5p) was identified under our experimental conditions. Subsequently, we systematically evaluated the expression patterns of the 28 most promising body fluid-specific miRNA markers using TaqMan RT-qPCR and selected the optimal combination of markers (12 miRNAs) to establish a multi-class support vector machine (MSVM) classification model. An independent test set (60 samples) was used to validate the accuracy of the proposed classification model, while an additional 30 casework samples were used to assess its robustness. The MSVM model accurately predicted the body fluid origin for almost all (59/60) single-source samples. Moreover, this model demonstrated the capability to identify aged forensic samples and to predict the primary components of mixed stains to a certain extent. In summary, this study presented a miRNA-based MSVM classification model for forensic body fluid identification using the qPCR platform. However, extensive validation, especially inter-laboratory collaborative exercises, is necessary before miRNA can be routinely applied in forensic identification practice.

Sex, Gender, and COPD

Sex and gender have emerged as critical considerations relevant to chronic obstructive pulmonary disease (COPD). Sex differences in lung development and physiologic response to hormones and environmental exposures influence COPD susceptibility, progression, severity, morbidity, and mortality. Gender has been poorly measured in the context of COPD, and gendered exposures further impact biology. The hormonal milieu is critical to study across the life course. Differences in immunity and inflammation likely impact sex- and gender-related features of COPD. Emerging evidence from multiple types of omics data is revealing new genes and pathways to consider as relevant to sex- and gender-divergent features of COPD. Much research to date has focused on autosomes, but the growing awareness of a role for allosomes is highlighting knowledge gaps. Reproductive aging impacts lung function and requires more investigation. Network medicine holds promise as an approach to sex and gender omics to uncover drivers of COPD in men and women.

Coordinated neuron-specific splicing events restrict nucleosome engagement of the LSD1 histone demethylase complex

Chromatin regulatory proteins are expressed broadly and assumed to exert the same intrinsic function across cell types. Here, we report that 14 chromatin regulators undergo evolutionary-conserved neuron-specific splicing events involving microexons. Among them are two components of a histone demethylase complex: LSD1 H3K4 demethylase and the H3K4me0-reader PHF21A. We found that neuronal LSD1 splicing reduces the enzymes' affinity to the nucleosome. Meanwhile, neuronal PHF21A splicing significantly attenuates histone H3 binding and further ablates the DNA-binding function exerted by an AT-hook motif. Furthermore, in vitro reconstitution of the canonical and neuronal PHF21A-LSD1 complexes, combined with in vivo methylation mapping, identified the neuronal complex as a hypomorphic H3K4 demethylating machinery. The neuronal PHF21A, albeit with its weaker nucleosome binding, is necessary for normal gene expression and the H3K4 landscape in the developing brain. Thus, ubiquitously expressed chromatin regulatory complexes can exert neuron-specific functions via alternative splicing of their subunits.

Regulation of protein abundance in normal human tissues

We report a systematic quantification of 10,841 unique proteins from over 700 GTEx samples, representing five human tissues. Sex, age and genetic factors are associated with variation in protein abundance. In total, 1981 cis-protein quantitative trait loci (cis-pQTL) are identified, of which a majority of protein targets have not been assayed in the recent plasma-based proteogenomic studies. Integrating transcriptomic information from matching tissues delineates concordant as well as discordant expression patterns at RNA and protein levels. Juxtaposition of data from different tissues indicates both shared and tissue-specific genetic architecture that underlie protein abundance. Complementing genomic annotation, RNA-based eQTL studies, as well as the recent establishment of plasma-based proteogenomic characterization, tissue-pQTLs shed light on biology underlying genotype-phenotype association of complex traits and diseases.

Rapid and accurate multi-phenotype imputation for millions of individuals

Deep phenotyping can enhance the power of genetic analysis, including genome-wide association studies (GWAS), but the occurrence of missing phenotypes compromises the potential of such resources. Although many phenotypic imputation methods have been developed, the accurate imputation of millions of individuals remains challenging. In the present study, we have developed a multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms. We demonstrate by extensive simulations that PIXANT is reliable, robust and highly resource-efficient. We then apply PIXANT to the UKB data of 277,301 unrelated White British citizens and 425 traits, and GWAS is subsequently performed on the imputed phenotypes, 18.4% more GWAS loci are identified than before imputation (8710 vs 7355). The increased statistical power of GWAS identified some additional candidate genes affecting heart rate, such as RNF220, SCN10A, and RGS6, suggesting that the use of imputed phenotype data from a large cohort may lead to the discovery of additional candidate genes for complex traits.

An Evolutionary Framework Exploiting Virologs and Their Host Origins to Inform Poxvirus Protein Functions

Poxviruses represent evolutionary successful infectious agents. As a family, poxviruses can infect a wide variety of species including humans, fish, and insects. While many other viruses are species-specific, an individual poxvirus species is often capable of infecting diverse hosts and cell types. For example, the prototypical poxvirus, vaccinia, is well known to infect numerous human cell types but can also infect cells from divergent hosts like frog neurons. Notably, poxvirus infections result in both detrimental human and animal diseases. The most infamous disease linked to a poxvirus is smallpox caused by variola virus. Poxviruses are large double-stranded DNA viruses, which uniquely replicate in the cytoplasm of cells. The model poxvirus genome encodes ~200 nonoverlapping protein-coding open reading frames (ORFs). Poxvirus gene products impact various biological processes like the production of virus particles, the host range of infectivity, and disease pathogenesis. In addition, poxviruses and their gene products have biomedical application with several species commonly engineered for use as vaccines and oncolytic virotherapy. Nevertheless, we still have an incomplete understanding of the functions associated with many poxvirus genes. In this chapter, we outline evolutionary insights that can complement ongoing studies of poxvirus gene functions and biology, which may serve to elucidate new molecular activities linked to this biomedically relevant class of viruses.

mRNA for Body Fluid and Individual Identification

Biological stains are one of the most important pieces of evidence, playing a multifaceted role in forensic investigations. An integral facet of forensic practice involves the identification of body fluids, typically achieved through chemical and enzymatic reactions. In recent decades, the introduction of mRNA markers has been posited as a pivotal advancement to augment the capabilities of body fluid identification (BFID). The mRNA coding region single-nucleotide polymorphisms (cSNPs) also present notable advantages, particularly in the task of individual identification. Here, we review the specificity and stability of mRNA markers in the context of BFID and the prowess of mRNA polymorphism in individual identification. Additionally, innovative methods for mRNA detection are discussed.

Intermittent fasting shifts the diurnal transcriptome atlas of transcription factors

Intermittent fasting remains a safe and effective strategy to ameliorate various age-related diseases, but its specific mechanisms are not fully understood. Considering that transcription factors (TFs) determine the response to environmental signals, here, we profiled the diurnal expression of 600 samples across four metabolic tissues sampled every 4 over 24 h from mice placed on five different feeding regimens to provide an atlas of TFs in biological space, time, and feeding regimen. Results showed that 1218 TFs exhibited tissue-specific and temporal expression profiles in ad libitum mice, of which 974 displayed significant oscillations at least in one tissue. Intermittent fasting triggered more than 90% (1161 in 1234) of TFs to oscillate somewhere in the body and repartitioned their tissue-specific expression. A single round of fasting generally promoted TF expression, especially in skeletal muscle and adipose tissues, while intermittent fasting mainly suppressed TF expression. Intermittent fasting down-regulated aging pathway and upregulated the pathway responsible for the inhibition of mammalian target of rapamycin (mTOR). Intermittent fasting shifts the diurnal transcriptome atlas of TFs, and mTOR inhibition may orchestrate intermittent fasting-induced health improvements. This atlas offers a reference and resource to understand how TFs and intermittent fasting may contribute to diurnal rhythm oscillation and bring about specific health benefits.

Global identification of mammalian host and nested gene pairs reveal tissue-specific transcriptional interplay

Nucleotide sequences along a gene provide instructions to transcriptional and cotranscriptional machinery allowing genome expansion into the transcriptome. Nucleotide sequence can often be shared between two genes and in some occurrences, a gene is located completely within a different gene; these are known as host/nested gene pairs. In these instances, if both genes are transcribed, overlap can result in a transcriptional crosstalk where genes regulate each other. Despite this, a comprehensive annotation of where such genes are located and their expression patterns is lacking. To address this, we provide an up-to-date catalog of host/nested gene pairs in mouse and human, showing that over a tenth of all genes contain a nested gene. We discovered that transcriptional co-occurrence is often tissue specific. This coexpression was especially prevalent within the transcriptionally permissive tissue, testis. We use this developmental system and scRNA-seq analysis to demonstrate that the coexpression of pairs can occur in single cells and transcription in the same place at the same time can enhance the transcript diversity of the host gene. In agreement, host genes are more transcript-diverse than the rest of the transcriptome. Host/nested gene configurations are common in both human and mouse, suggesting that interplay between gene pairs is a feature of the mammalian genome. This highlights the relevance of transcriptional crosstalk between genes which share nucleic acid sequence. The results and analysis are available on an Rshiny application (https://hngeneviewer.sites.er.kcl.ac.uk/hn_viewer/).

An integrated transcriptomic analysis of brain aging and strategies for healthy aging

Background

It is been noted that the expression levels of numerous genes undergo changes as individuals age, and aging stands as a primary factor contributing to age-related diseases. Nevertheless, it remains uncertain whether there are common aging genes across organs or tissues, and whether these aging genes play a pivotal role in the development of age-related diseases.

Methods

In this study, we screened for aging genes using RNAseq data of 32 human tissues from GTEx. RNAseq datasets from GEO were used to study whether aging genes drives age-related diseases, or whether anti-aging solutions could reverse aging gene expression.

Results

Aging transcriptome alterations showed that brain aging differ significantly from the rest of the body, furthermore, brain tissues were divided into four group according to their aging transcriptome alterations. Numerous genes were downregulated during brain aging, with functions enriched in synaptic function, ubiquitination, mitochondrial translation and autophagy. Transcriptome analysis of age-related diseases and retarding aging solutions showed that downregulated aging genes in the hippocampus further downregulation in Alzheimer's disease but were effectively reversed by high physical activity. Furthermore, the neuron loss observed during aging was reversed by high physical activity.

Conclusion

The downregulation of many genes is a major contributor to brain aging and neurodegeneration. High levels of physical activity have been shown to effectively reactivate these genes, making it a promising strategy to slow brain aging.

Interactomic Analyses and a Reverse Engineering Study Identify Specific Functional Activities of One-to-One Interactions of the S1 Subunit of the SARS-CoV-2 Spike Protein with the Human Proteome

The S1 subunit of SARS-CoV-2 Spike is crucial for ACE2 recognition and viral entry into human cells. It has been found in the blood of COVID-19 patients and vaccinated individuals. Using BioGRID, I identified 146 significant human proteins that interact with S1. I then created an interactome model that made it easier to study functional activities. Through a reverse engineering approach, 27 specific one-to-one interactions of S1 with the human proteome were selected. S1 interacts in this manner independently from the biological context in which it operates, be it infection or vaccination. Instead, when it works together with viral proteins, they carry out multiple attacks on single human proteins, showing a different functional engagement. The functional implications and tropism of the virus for human organs/tissues were studied using Cytoscape. The nervous system, liver, blood, and lungs are among the most affected. As a single protein, S1 operates in a complex metabolic landscape which includes 2557 Biological Processes (GO), much more than the 1430 terms controlled when operating in a group. A Data Merging approach shows that the total proteins involved by S1 in the cell are over 60,000 with an average involvement per single biological process of 26.19. However, many human proteins become entangled in over 100 different biological activities each. Clustering analysis showed significant activations of many molecular mechanisms, like those related to hepatitis B infections. This suggests a potential involvement in carcinogenesis, based on a viral strategy that uses the ubiquitin system to impair the tumor suppressor and antiviral functions of TP53, as well as the role of RPS27A in protein turnover and cellular stress responses.

Human introns contain conserved tissue-specific cryptic poison exons

Eukaryotic cells express a large number of transcripts from a single gene due to alternative splicing. Despite hundreds of thousands of splice isoforms being annotated in databases, it has been reported that the current exon catalogs remain incomplete. At the same time, introns of human protein-coding (PC) genes contain a large number of evolutionarily conserved elements with unknown function. Here, we explore the possibility that some of them represent cryptic exons that are expressed in rare conditions. We identified a group of cryptic exons that are similar to the annotated exons in terms of evolutionary conservation and RNA-seq read coverage in the Genotype-Tissue Expression dataset. Most of them were poison, i.e. generated an nonsense-mediated decay (NMD) isoform upon inclusion, and many showed signs of tissue-specific and cancer-specific expression and regulation. We performed RNA-seq in A549 cell line treated with cycloheximide to inactivate NMD and confirmed using quantitative polymerase chain reaction that seven of eight exons tested are, indeed, expressed. This study shows that introns of human PC genes contain cryptic poison exons, which reside in conserved intronic regions and remain not fully annotated due to insufficient representation in RNA-seq libraries.

Novel insights into the circadian modulation of lipid metabolism in chicken livers revealed by RNA sequencing and weighted gene co-expression network analysis

The circadian clock is crucial for maintaining lipid metabolism homeostasis in mammals. Despite the economic importance of fat content in poultry, research on the regulatory effects and molecular mechanisms of the circadian clock on avian hepatic lipid metabolism has been limited. In this study, we observed significant diurnal variations (P<0.05) in triglyceride (TG), free fatty acids (FFA), fatty acid synthase (FAS), and total cholesterol (TC) levels in the chicken embryonic liver under 12-h light/12-h dark incubation conditions, with TG, FFA, and TC concentrations showing significant cosine rhythmic oscillations (P<0.05). However, such rhythmic variations were not observed under complete darkness incubation conditions. Using transcriptome sequencing technology, we identified 157 genes significantly upregulated at night and 313 genes significantly upregulated during the 12-h light/12-h dark cycle. These circadian differential genes are involved in processes and pathways such as lipid catabolic process regulation, meiotic cell cycle, circadian rhythm regulation, positive regulation of the MAPK cascade, and glycerolipid metabolism. Weighted gene co-expression network analysis (WGCNA) revealed 3 modules-green, blue, and red-that significantly correlate with FFA, FAS, and TG, respectively. Genes within these modules were enriched in processes and pathways including the cell cycle, light stimulus response, circadian rhythm regulation, phosphorylation, positive regulation of the MAPK cascade, and lipid biosynthesis. Notably, we identified ten hub genes, including protein kinase C delta (PRKCD), polo like kinase 4 (PLK4), clock circadian regulator (CLOCK), steroid 5 alpha-reductase 3 (SRD5A3), BUB1 mitotic checkpoint serine/threonine kinase (BUB1B), shugoshin 1 (SGO1), NDC80 kinetochore complex component (NDC80), NIMA related kinase 2 (NEK2), minichromosome maintenance complex component 4 (MCM4), polo like kinase 1 (PLK1), potentially link circadian regulation with lipid metabolic homeostasis. These findings demonstrate the regulatory role of the circadian clock in chicken liver lipid metabolism homeostasis and provide a theoretical basis and molecular targets for optimizing the circadian clock to reduce excessive fat deposition in chickens, which is significant for the healthy development of the poultry industry.

Multiomic Network Analysis Identifies Dysregulated Neurobiological Pathways in Opioid Addiction

BACKGROUND

Opioid addiction is a worldwide public health crisis. In the United States, for example, opioids cause more drug overdose deaths than any other substance. However, opioid addiction treatments have limited efficacy, meaning that additional treatments are needed.

METHODS

To help address this problem, we used network-based machine learning techniques to integrate results from genome-wide association studies of opioid use disorder and problematic prescription opioid misuse with transcriptomic, proteomic, and epigenetic data from the dorsolateral prefrontal cortex of people who died of opioid overdose and control individuals.

RESULTS

We identified 211 highly interrelated genes identified by genome-wide association studies or dysregulation in the dorsolateral prefrontal cortex of people who died of opioid overdose that implicated the Akt, BDNF (brain-derived neurotrophic factor), and ERK (extracellular signal-regulated kinase) pathways, identifying 414 drugs targeting 48 of these opioid addiction-associated genes. Some of the identified drugs are approved to treat other substance use disorders or depression.

CONCLUSIONS

Our synthesis of multiomics using a systems biology approach revealed key gene targets that could contribute to drug repurposing, genetics-informed addiction treatment, and future discovery.

Mechanism of NACHO-mediated assembly of pentameric ligand-gated ion channels

Pentameric ligand-gated ion channels (pLGICs) are cell surface receptors of crucial importance for animal physiology1-4. This diverse protein family mediates the ionotropic signals triggered by major neurotransmitters and includes γ-aminobutyric acid receptors (GABAARs) and acetylcholine receptors (nAChRs). Receptor function is fine-tuned by a myriad of endogenous and pharmacological modulators3. A functional pLGIC is built from five homologous, sometimes identical, subunits, each containing a β-scaffold extracellular domain (ECD), a four-helix transmembrane domain (TMD) and intracellular loops of variable length. Although considerable progress has been made in understanding pLGICs in structural and functional terms, the molecular mechanisms that enable their assembly at the endoplasmic reticulum (ER)5 in a vast range of potential subunit configurations6 remain unknown. Here, we identified candidate pLGICs assembly factors selectively associated with an unassembled GABAAR subunit. Focusing on one of the candidates, we determined the cryo-EM structure of an assembly intermediate containing two α1 subunits of GABAAR each bound to an ER-resident membrane protein NACHO. The structure showed how NACHO shields the principal (+) transmembrane interface of α1 subunits containing an immature extracellular conformation. Crosslinking and structure-prediction revealed an adjacent surface on NACHO for β2 subunit interactions to guide stepwise oligimerisation. Mutations of either subunit-interacting surface on NACHO also impaired the formation of homopentameric α7 nAChRs, pointing to a generic framework for pLGIC assembly. Our work provides the foundation for understanding the regulatory principles underlying pLGIC structural diversity.

Germ cell progression through zebrafish spermatogenesis declines with age

Vertebrate spermatogonial stem cells maintain sperm production over the lifetime of an animal, but fertility declines with age. Although morphological studies have informed our understanding of typical spermatogenesis, the molecular and cellular mechanisms underlying the maintenance and decline of spermatogenesis are not yet understood. We used single-cell RNA sequencing to generate a developmental atlas of the aging zebrafish testis. All testes contained spermatogonia, but we observed a progressive decline in spermatogenesis that correlated with age. Testes from some older males only contained spermatogonia and a reduced population of spermatocytes. Spermatogonia in older males were transcriptionally distinct from spermatogonia in testes capable of robust spermatogenesis. Immune cells including macrophages and lymphocytes drastically increased in abundance in testes that could not complete spermatogenesis. Our developmental atlas reveals the cellular changes as the testis ages and defines a molecular roadmap for the regulation of spermatogenesis.

PCPE2: Expression of multifunctional extracellular glycoprotein associated with diverse cellular functions

Procollagen C-endopeptidase enhancer 2, known as PCPE2 or PCOC2 (gene name, PCOLCE2) is a glycoprotein that resides in the extracellular matrix, and is similar in domain organization to PCPE1/PCPE, PCOC1 (PCOLCE1/PCOLCE). Due to the many similarities between the two related proteins, PCPE2 has been assumed to have biological functions similar to PCPE. PCPE is a well-established enhancer of procollagen processing activating the enzyme, BMP-1. However, reports show that PCPE2 has a strikingly different tissue expression profile compared to PCPE. With that in mind and given the paucity of published studies on PCPE2, this review examines the current literature citing PCPE2 and its association with specific cell types and signaling pathways. Additionally, this review will present a brief history of PCPE2's discovery, highlighting structural and functional similarities and differences compared to PCPE. Considering the widespread use of RNA sequencing techniques to examine associations between cell-specific gene expression and disease states, we will show that PCPE2 is repeatedly found as a differentially regulated gene (DEG) significantly associated with a number of cellular processes, well beyond the scope of procollagen fibril processing.

Gene expression landscape of cutaneous squamous cell carcinoma progression

BACKGROUND

Cutaneous squamous cell carcinomas (cSCCs) are the second most common human cancer and have been characterized by RNA sequencing (RNA-Seq); however, the transferability of findings from individual studies may be limited by small sample sizes and diverse analysis protocols.

OBJECTIVES

To define the transcriptome landscape at different stages in the progression of normal skin to cSCC via a meta-analysis of publicly available RNA-Seq samples.

METHODS

Whole-transcriptome data from 73 clinically normal skin samples, 46 actinic keratoses (AK) samples, 16 in situ SCC samples, 13 keratoacanthoma (KA) samples and 147 cSCC samples [including 30 samples from immunocompromised patients and 8 from individuals with recessive dystrophic epidermolysis bullosa (RDEB)] were uniformly processed to harmonize gene expression. Differential expression, fusion detection and cell-type deconvolution analyses were performed.

RESULTS

Individual RNA-Seq studies of cSCC demonstrated study-specific clustering and varied widely in their differential gene expression detection. Following batch correction, we defined a consensus set of differentially expressed genes (DEGs), including those altered in the preinvasive stages of cSCC development, and used single-cell RNA-Seq data to demonstrate that DEGs are often - but not always - expressed by tumour-specific keratinocytes (TSKs). Analysis of the cellular composition of cSCC, KA and RDEB-cSCC identified an increase in differentiated keratinocytes in KA, while RDEB-cSCC contained the most TSKs. Compared with cSCC arising in immunocompetent individuals, cSCC samples from immunosuppressed patients demonstrated fewer memory B cells and CD8+ T cells. A comprehensive and unbiased search for fusion transcripts in cSCC and intermediate disease stages identified few candidates that recurred in >1% of all specimens, suggesting that most cSCC are not driven by oncogenic gene fusions. Finally, using Genotype-Tissue Expression (GTEx) data, we distilled a novel 300-gene signature of chronic sun exposure that affirms greater cumulative ultraviolet (UV) exposure in later stages of cSCC development.

CONCLUSIONS

Our results define the gene expression landscape of cSCC progression, characterize cell subpopulation heterogeneity in cSCC subtypes that contribute to their distinct clinical phenotypes, demonstrate that gene fusions are not a common cause of cSCC and identify UV-responsive genes associated with cSCC development.

Metabolic reprogramming tips vaccinia virus infection outcomes by stabilizing interferon-γ induced IRF1

Interferon (IFN) induced activities are critical, early determinants of immune responses and infection outcomes. A key facet of IFN responses is the upregulation of hundreds of mRNAs termed interferon-stimulated genes (ISGs) that activate intrinsic and cell-mediated defenses. While primary interferon signaling is well-delineated, other layers of regulation are less explored but implied by aberrant ISG expression signatures in many diseases in the absence of infection. Consistently, our examination of tonic ISG levels across uninfected human tissues and individuals revealed three ISG subclasses. As tissue identity and many comorbidities with increased virus susceptibility are characterized by differences in metabolism, we characterized ISG responses in cells grown in media known to favor either aerobic glycolysis (glucose) or oxidative phosphorylation (galactose supplementation). While these conditions over time had a varying impact on the expression of ISG RNAs, the differences were typically greater between treatments than between glucose/galactose. Interestingly, extended interferon-priming led to divergent expression of two ISG proteins: upregulation of IRF1 in IFN-γ/glucose and increased IFITM3 in galactose by IFN-α and IFN-γ. In agreement with a hardwired response, glucose/galactose regulation of interferon-γ induced IRF1 is conserved in unrelated mouse and cat cell types. In galactose conditions, proteasome inhibition restored interferon-γ induced IRF1 levels to that of glucose/interferon-γ. Glucose/interferon-γ decreased replication of the model poxvirus vaccinia at low MOI and high MOIs. Vaccinia replication was restored by IRF1 KO. In contrast, but consistent with differential regulation of IRF1 protein by glucose/galactose, WT and IRF1 KO cells in galactose media supported similar levels of vaccinia replication regardless of IFN-γ priming. Also associated with glucose/galactose is a seemingly second block at a very late stage in viral replication which results in reductions in herpes- and poxvirus titers but not viral protein expression. Collectively, these data illustrate a novel layer of regulation for the key ISG protein, IRF1, mediated by glucose/galactose and imply unappreciated subprograms embedded in the interferon response. In principle, such cellular circuitry could rapidly adapt immune responses by sensing changing metabolite levels consumed during viral replication and cell proliferation.

CRISPR tiling deletion screens reveal functional enhancers of neuropsychiatric risk genes and allelic compensation effects (ACE) on transcription

Precise transcriptional regulation is critical for cellular function and development, yet the mechanism of this process remains poorly understood for many genes. To gain a deeper understanding of the regulation of neuropsychiatric disease risk genes, we identified a total of 39 functional enhancers for four dosage-sensitive genes, APP, FMR1, MECP2, and SIN3A, using CRISPR tiling deletion screening in human induced pluripotent stem cell (iPSC)-induced excitatory neurons. We found that enhancer annotation provides potential pathological insights into disease-associated copy number variants. More importantly, we discovered that allelic enhancer deletions at SIN3A could be compensated by increased transcriptional activities from the other intact allele. Such allelic compensation effects (ACE) on transcription is stably maintained during differentiation and, once established, cannot be reversed by ectopic SIN3A expression. Further, ACE at SIN3A occurs through dosage sensing by the promoter. Together, our findings unravel a regulatory compensation mechanism that ensures stable and precise transcriptional output for SIN3A, and potentially other dosage-sensitive genes.

Functional Optimization in Distinct Tissues and Conditions Constrains the Rate of Protein Evolution

Understanding the main determinants of protein evolution is a fundamental challenge in biology. Despite many decades of active research, the molecular and cellular mechanisms underlying the substantial variability of evolutionary rates across cellular proteins are not currently well understood. It also remains unclear how protein molecular function is optimized in the context of multicellular species and why many proteins, such as enzymes, are only moderately efficient on average. Our analysis of genomics and functional datasets reveals in multiple organisms a strong inverse relationship between the optimality of protein molecular function and the rate of protein evolution. Furthermore, we find that highly expressed proteins tend to be substantially more functionally optimized. These results suggest that cellular expression costs lead to more pronounced functional optimization of abundant proteins and that the purifying selection to maintain high levels of functional optimality significantly slows protein evolution. We observe that in multicellular species both the rate of protein evolution and the degree of protein functional efficiency are primarily affected by expression in several distinct cell types and tissues, specifically, in developed neurons with upregulated synaptic processes in animals and in young and fast-growing tissues in plants. Overall, our analysis reveals how various constraints from the molecular, cellular, and species' levels of biological organization jointly affect the rate of protein evolution and the level of protein functional adaptation.

CoGTEx: Unscaled system-level coexpression estimation from GTEx data forecast novel functional gene partners

MOTIVATION

Coexpression estimations are helpful for analysis of pathways, cofactors, regulators, targets, and human health and disease. Ideally, coexpression estimations should consider as many diverse cell types as possible and consider that available data is not uniform across tissues. Importantly, the coexpression estimations accessible today are performed on a "tissue level", which is based on cell type standardized formulations. Little or no attention is paid to overall gene expression levels. The tissue-level estimation assumes that variance expression levels are more important than mean expression levels. Here, we challenge this assumption by estimating a coexpression calculation at the "system level", which is estimated without standardization by tissue, and show that it provides valuable information. We made available a resource to view, download, and analyze both, tissue- and system-level coexpression estimations from GTEx human data.

METHODS

GTEx v8 expression data was globally normalized, batch-processed, and filtered. Then, PCA, clustering, and tSNE stringent procedures were applied to generate 42 distinct and curated tissue clusters. Coexpression was estimated from these 42 tissue clusters computing the correlation of 33,445 genes by sampling 70 samples per tissue cluster to avoid tissue overrepresentation. This process was repeated 20 times, extracting the minimum value provided as a robust estimation. Three metrics were calculated (Pearson, Spearman, and G-statistic) in two data processing modes, at the system-level (TPM scale) and tissue levels (z-score scale).

RESULTS

We first validate our tissue-level estimations compared with other databases. Then, by specific analyses in several examples and literature validations of predictions, we show that system-level coexpression estimation differs from tissue-level estimations and that both contain valuable information reflected in biological pathways. We also show that coexpression estimations are associated to transcriptional regulation. Finally, we present CoGTEx, a valuable resource for viewing and analyzing coexpressed genes in human adult tissues from GTEx v8 data. We introduce our web resource to list, view and explore the coexpressed genes from GTEx data.

CONCLUSION

We conclude that system-level coexpression is a novel and interesting coexpression metric capable of generating plausible predictions and biological hypotheses; and that CoGTEx is a valuable resource to view, compare, and download system- and tissue- level coexpression estimations from GTEx data.

AVAILABILITY

The web resource is available at http://bioinformatics.mx/cogtex.

Generation of human region-specific brain organoids with medullary spinal trigeminal nuclei

Brain organoids with nucleus-specific identities provide unique platforms for studying human brain development and diseases at a finer resolution. Despite its essential role in vital body functions, the medulla of the hindbrain has seen a lack of in vitro models, let alone models resembling specific medullary nuclei, including the crucial spinal trigeminal nucleus (SpV) that relays peripheral sensory signals to the thalamus. Here, we report a method to differentiate human pluripotent stem cells into region-specific brain organoids resembling the dorsal domain of the medullary hindbrain. Importantly, organoids specifically recapitulated the development of the SpV derived from the dorsal medulla. We also developed an organoid system to create the trigeminothalamic projections between the SpV and the thalamus by fusing these organoids, namely human medullary SpV-like organoids (hmSpVOs), with organoids representing the thalamus (hThOs). Our study provides a platform for understanding SpV development, nucleus-based circuit organization, and related disorders in the human brain.

Genes with differential expression across ancestries are enriched in ancestry-specific disease effects likely due to gene-by-environment interactions

Multi-ancestry genome-wide association studies (GWASs) have highlighted the existence of variants with ancestry-specific effect sizes. Understanding where and why these ancestry-specific effects occur is fundamental to understanding the genetic basis of human diseases and complex traits. Here, we characterized genes differentially expressed across ancestries (ancDE genes) at the cell-type level by leveraging single-cell RNA-sequencing data in peripheral blood mononuclear cells for 21 individuals with East Asian (EAS) ancestry and 23 individuals with European (EUR) ancestry (172,385 cells); then, we tested whether variants surrounding those genes were enriched in disease variants with ancestry-specific effect sizes by leveraging ancestry-matched GWASs of 31 diseases and complex traits (average n ∼ 90,000 and ∼ 267,000 in EAS and EUR, respectively). We observed that ancDE genes tended to be cell-type specific and enriched in genes interacting with the environment and in variants with ancestry-specific disease effect sizes, which suggests cell-type-specific, gene-by-environment interactions shared between regulatory and disease architectures. Finally, we illustrated how different environments might have led to ancestry-specific myeloid cell leukemia 1 (MCL1) expression in B cells and ancestry-specific allele effect sizes in lymphocyte count GWASs for variants surrounding MCL1. Our results imply that large single-cell and GWAS datasets from diverse ancestries are required to improve our understanding of human diseases.

Metabolic reprogramming tips vaccinia virus infection outcomes by stabilizing interferon-γ induced IRF1

Interferon (IFN) induced activities are critical, early determinants of immune responses and infection outcomes. A key facet of IFN responses is the upregulation of hundreds of mRNAs termed interferon-stimulated genes (ISGs) that activate intrinsic and cell-mediated defenses. While primary interferon signaling is well-delineated, other layers of regulation are less explored but implied by aberrant ISG expression signatures in many diseases in the absence of infection. Consistently, our examination of tonic ISG levels across uninfected human tissues and individuals revealed three ISG subclasses. As tissue identity and many comorbidities with increased virus susceptibility are characterized by differences in metabolism, we characterized ISG responses in cells grown in media known to favor either aerobic glycolysis (glucose) or oxidative phosphorylation (galactose supplementation). While these conditions over time had a varying impact on the expression of ISG RNAs, the differences were typically greater between treatments than between glucose/galactose. Interestingly, extended interferon-priming led to divergent expression of two ISG proteins: upregulation of IRF1 in IFN-γ/glucose and increased IFITM3 in galactose by IFN-α and IFN-γ. In agreement with a hardwired response, glucose/galactose regulation of interferon-γ induced IRF1 is conserved in unrelated mouse and cat cell types. In galactose conditions, proteasome inhibition restored interferon-γ induced IRF1 levels to that of glucose/interferon-γ. Glucose/interferon-γ decreased replication of the model poxvirus vaccinia at low MOI and high MOIs. Vaccinia replication was restored by IRF1 KO. In contrast, but consistent with differential regulation of IRF1 protein by glucose/galactose, WT and IRF1 KO cells in galactose media supported similar levels of vaccinia replication regardless of IFN-γ priming. Also associated with glucose/galactose is a seemingly second block at a very late stage in viral replication which results in reductions in herpes- and poxvirus titers but not viral protein expression. Collectively, these data illustrate a novel layer of regulation for the key ISG protein, IRF1, mediated by glucose/galactose and imply unappreciated subprograms embedded in the interferon response. In principle, such cellular circuitry could rapidly adapt immune responses by sensing changing metabolite levels consumed during viral replication and cell proliferation.

Radiotherapy and breast cancer: finally, an lncRNA perspective on radiosensitivity and radioresistance

Radiotherapy (RT) serves as one of the key adjuvant treatments in management of breast cancer. Nevertheless, RT has two major problems: side effects and radioresistance. Given that patients respond differently to RT, it is imperative to understand the molecular mechanisms underlying these differences. Two-thirds of human genes do not encode proteins, as we have realized from genome-scale studies conducted after the advent of the genomic era; nevertheless, molecular understanding of breast cancer to date has been attained almost entirely based on protein-coding genes and their pathways. Long non-coding RNAs (lncRNAs) are a poorly understood but abundant class of human genes that yield functional non-protein-coding RNA transcripts. Here, we canvass the field to seek evidence for the hypothesis that lncRNAs contribute to radioresistance in breast cancer. RT-responsive lncRNAs ranging from "classical" lncRNAs discovered at the dawn of the post-genomic era (such as HOTAIR, NEAT1, and CCAT), to long intergenic lncRNAs such as LINC00511 and LINC02582, antisense lncRNAs such as AFAP-AS1 and FGD5-AS1, and pseudogene transcripts such as DUXAP8 were found during our screen of the literature. Radiation-related pathways modulated by these lncRNAs include DNA damage repair, cell cycle, cancer stem cells phenotype and apoptosis. Thus, providing a clear picture of these lncRNAs' underlying RT-relevant molecular mechanisms should help improve overall survival and optimize the best radiation dose for each individual patient. Moreover, in healthy humans, lncRNAs show greater natural expression variation than protein-coding genes, even across individuals, alluding to their exceptional potential for targeting in truly personalized, precision medicine.

Targeted partial reprogramming of age-associated cell states improves markers of health in mouse models of aging

Aging is a complex multifactorial process associated with epigenome dysregulation, increased cellular senescence, and decreased rejuvenation capacity. Short-term cyclic expression of octamer-binding transcription factor 4 (Oct4), sex-determining region Y-box 2 (Sox2), Kruppel-like factor 4 (Klf4), and cellular myelocytomatosis oncogene (cMyc) (OSKM) in wild-type mice improves health but fails to distinguish cell states, posing risks to healthy cells. Here, we delivered a single dose of adeno-associated viruses (AAVs) harboring OSK under the control of the cyclin-dependent kinase inhibitor 2a (Cdkn2a) promoter to specifically partially reprogram aged and stressed cells in a mouse model of Hutchinson-Gilford progeria syndrome (HGPS). Mice showed reduced expression of proinflammatory cytokines and extended life spans upon aged cell-specific OSK expression. The bone marrow and spleen, in particular, showed pronounced gene expression changes, and partial reprogramming in aged HGPS mice led to a shift in the cellular composition of the hematopoietic stem cell compartment toward that of young mice. Administration of AAVs carrying Cdkn2a-OSK to naturally aged wild-type mice also delayed aging phenotypes and extended life spans without altering the incidence of tumor development. Furthermore, intradermal injection of AAVs carrying Cdkn2a-OSK led to improved wound healing in aged wild-type mice. Expression of CDKN2A-OSK in aging or stressed human primary fibroblasts led to reduced expression of inflammation-related genes but did not alter the expression of cell cycle-related genes. This targeted partial reprogramming approach may therefore facilitate the development of strategies to improve health and life span and enhance resilience in the elderly.