An atlas of alternative polyadenylation quantitative trait loci contributing to complex trait and disease heritability

Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis

The function of some genetic variants associated with brain-relevant traits has been explained through colocalization with expression quantitative trait loci (eQTL) conducted in bulk postmortem adult brain tissue. However, many brain-trait associated loci have unknown cellular or molecular function. These genetic variants may exert context-specific function on different molecular phenotypes including post-transcriptional changes. Here, we identified genetic regulation of RNA editing and alternative polyadenylation (APA) within a cell-type-specific population of human neural progenitors and neurons. More RNA editing and isoforms utilizing longer polyadenylation sequences were observed in neurons, likely due to higher expression of genes encoding the proteins mediating these post-transcriptional events. We also detected hundreds of cell-type-specific editing quantitative trait loci (edQTLs) and alternative polyadenylation QTLs (apaQTLs). We found colocalizations of a neuron edQTL in CCDC88A with educational attainment and a progenitor apaQTL in EP300 with schizophrenia, suggesting that genetically mediated post-transcriptional regulation during brain development leads to differences in brain function.

A multi-modal framework improves prediction of tissue-specific gene expression from a surrogate tissue

BACKGROUND

Tissue-specific analysis of the transcriptome is critical to elucidating the molecular basis of complex traits, but central tissues are often not accessible. We propose a methodology, Multi-mOdal-based framework to bridge the Transcriptome between PEripheral and Central tissues (MOTPEC).

METHODS

Multi-modal regulatory elements in peripheral blood are incorporated as features for gene expression prediction in 48 central tissues. To demonstrate the utility, we apply it to the identification of BMI-associated genes and compare the tissue-specific results with those derived directly from surrogate blood.

FINDINGS

MOTPEC models demonstrate superior performance compared with both baseline models in blood and existing models across the 48 central tissues. We identify a set of BMI-associated genes using the central tissue MOTPEC-predicted transcriptome data. The MOTPEC-based differential gene expression (DGE) analysis of BMI in the central tissues (including brain caudate basal ganglia and visceral omentum adipose tissue) identifies 378 genes overlapping the results from a TWAS of BMI, while only 162 overlapping genes are identified using gene expression in blood. Cellular perturbation analysis further supports the utility of MOTPEC for identifying trait-associated gene sets and narrowing the effect size divergence between peripheral blood and central tissues.

INTERPRETATION

The MOTPEC framework improves the gene expression prediction accuracy for central tissues and enhances the identification of tissue-specific trait-associated genes.

FUNDING

This research is supported by the National Natural Science Foundation of China 82204118 (D.Z.), the seed funding of the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province (2020E10004), the National Institutes of Health (NIH) Genomic Innovator Award R35HG010718 (E.R.G.), NIH/NHGRI R01HG011138 (E.R.G.), NIH/NIA R56AG068026 (E.R.G.), NIH Office of the Director U24OD035523 (E.R.G.), and NIH/NIGMS R01GM140287 (E.R.G.).

Transcriptomic analysis of the spatiotemporal axis of oogenesis and fertilization in C. elegans

Caenorhabditis elegans hermaphrodite presents a unique model to study the formation of oocytes. However, the size of the model animal and difficulties in retrieval of specific stages of the germline have obviated closer systematic studies of this process throughout the years. Here, we present a transcriptomic level analysis into the oogenesis of C. elegans hermaphrodites. We dissected a hermaphrodite gonad into seven sections corresponding to the mitotic distal region, the pachytene region, the diplotene region, the early diakinesis region and the 3 most proximal oocytes, and deeply sequenced the transcriptome of each of them along with that of the fertilized egg using a single-cell RNA-seq (scRNA-seq) protocol. We identified specific gene expression events as well as gene splicing events in finer detail along the gonad and provided novel insights into underlying mechanisms of the oogenesis process. Furthermore, through careful review of relevant research literature coupled with patterns observed in our analysis, we delineate transcripts that may serve functions in the interactions between the germline and cells of the somatic gonad. These results expand our knowledge of the transcriptomic space of the C. elegans germline and lay a foundation on which future studies of the germline can be based upon.

Large-Scale Alternative Polyadenylation-Wide Association Studies to Identify Putative Cancer Susceptibility Genes

Alternative polyadenylation (APA) modulates mRNA processing in the 3'-untranslated regions (3' UTR), affecting mRNA stability and translation efficiency. Research into genetically regulated APA has the potential to provide insights into cancer risk. In this study, we conducted large APA-wide association studies to investigate associations between APA levels and cancer risk. Genetic models were built to predict APA levels in multiple tissues using genotype and RNA sequencing data from 1,337 samples from the Genotype-Tissue Expression project. Associations of genetically predicted APA levels with cancer risk were assessed by applying the prediction models to data from large genome-wide association studies of six common cancers among European ancestry populations: breast, ovarian, prostate, colorectal, lung, and pancreatic cancers. A total of 58 risk genes (corresponding to 76 APA sites) were associated with at least one type of cancer, including 25 genes previously not linked to cancer susceptibility. Of the identified risk APAs, 97.4% and 26.3% were supported by 3'-UTR APA quantitative trait loci and colocalization analyses, respectively. Luciferase reporter assays for four selected putative regulatory 3'-UTR variants demonstrated that the risk alleles of 3'-UTR variants, rs324015 (STAT6), rs2280503 (DIP2B), rs1128450 (FBXO38), and rs145220637 (LDHA), significantly increased the posttranscriptional activities of their target genes compared with reference alleles. Furthermore, knockdown of the target genes confirmed their ability to promote proliferation and migration. Overall, this study provides insights into the role of APA in the genetic susceptibility to common cancers. Significance: Systematic evaluation of associations of alternative polyadenylation with cancer risk reveals 58 putative susceptibility genes, highlighting the contribution of genetically regulated alternative polyadenylation of 3'UTRs to genetic susceptibility to cancer.

Human genetic variation determines 24-hour rhythmic gene expression and disease risk

24-hour biological rhythms are essential to maintain physiological homeostasis. Disruption of these rhythms increases the risks of multiple diseases. The biological rhythms are known to have a genetic basis formed by core clock genes, but how individual genetic variation shapes the oscillating transcriptome and contributes to human chronophysiology and disease risk is largely unknown. Here, we mapped interactions between temporal gene expression and genotype to identify quantitative trait loci (QTLs) contributing to rhythmic gene expression. These newly identified QTLs were termed as rhythmic QTLs (rhyQTLs), which determine previously unappreciated rhythmic genes in human subpopulations with specific genotypes. Functionally, rhyQTLs and their associated rhythmic genes contribute extensively to essential chronophysiological processes, including bile acid and lipid metabolism. The identification of rhyQTLs sheds light on the genetic mechanisms of gene rhythmicity, offers mechanistic insights into variations in human disease risk, and enables precision chronotherapeutic approaches for patients.

Population Diversity at the Single-Cell Level

Population-scale single-cell genomics is a transformative approach for unraveling the intricate links between genetic and cellular variation. This approach is facilitated by cutting-edge experimental methodologies, including the development of high-throughput single-cell multiomics and advances in multiplexed environmental and genetic perturbations. Examining the effects of natural or synthetic genetic variants across cellular contexts provides insights into the mutual influence of genetics and the environment in shaping cellular heterogeneity. The development of computational methodologies further enables detailed quantitative analysis of molecular variation, offering an opportunity to examine the respective roles of stochastic, intercellular, and interindividual variation. Future opportunities lie in leveraging long-read sequencing, refining disease-relevant cellular models, and embracing predictive and generative machine learning models. These advancements hold the potential for a deeper understanding of the genetic architecture of human molecular traits, which in turn has important implications for understanding the genetic causes of human disease.

RNA Sequencing in Disease Diagnosis

RNA sequencing (RNA-seq) enables the accurate measurement of multiple transcriptomic phenotypes for modeling the impacts of disease variants. Advances in technologies, experimental protocols, and analysis strategies are rapidly expanding the application of RNA-seq to identify disease biomarkers, tissue- and cell-type-specific impacts, and the spatial localization of disease-associated mechanisms. Ongoing international efforts to construct biobank-scale transcriptomic repositories with matched genomic data across diverse population groups are further increasing the utility of RNA-seq approaches by providing large-scale normative reference resources. The availability of these resources, combined with improved computational analysis pipelines, has enabled the detection of aberrant transcriptomic phenotypes underlying rare diseases. Further expansion of these resources, across both somatic and developmental tissues, is expected to soon provide unprecedented insights to resolve disease origin, mechanism of action, and causal gene contributions, suggesting the continued high utility of RNA-seq in disease diagnosis.

Single-cell total-RNA profiling unveils regulatory hubs of transcription factors

Recent development of RNA velocity uses master equations to establish the kinetics of the life cycle of RNAs from unspliced RNA to spliced RNA (i.e., mature RNA) to degradation. To feed this kinetic analysis, simultaneous measurement of unspliced RNA and spliced RNA in single cells is greatly desired. However, the majority of single-cell RNA-seq chemistry primarily captures mature RNA species to measure gene expressions. Here, we develop a one-step total-RNA chemistry-based single-cell RNA-seq method: snapTotal-seq. We benchmark this method with multiple single-cell RNA-seq assays in their performance in kinetic analysis of cell cycle by RNA velocity. Next, with LASSO regression between transcription factors, we identify the critical regulatory hubs mediating the cell cycle dynamics. We also apply snapTotal-seq to profile the oncogene-induced senescence and identify the key regulatory hubs governing the entry of senescence. Furthermore, from the comparative analysis of unspliced RNA and spliced RNA, we identify a significant portion of genes whose expression changes occur in spliced RNA but not to the same degree in unspliced RNA, indicating these gene expression changes are mainly controlled by post-transcriptional regulation. Overall, we demonstrate that snapTotal-seq can provide enriched information about gene regulation, especially during the transition between cell states.

Integration of apaQTL and eQTL analysis reveals novel SNPs associated with occupational pulmonary fibrosis risk

To explore the association between apaQTL/eQTL-SNPs and the susceptibility to silicosis. A silicosis-related GWAS was initially conducted to screen for single nucleotide polymorphisms (SNPs) associated with the risk of silicosis. Candidate SNPs with apaQTL and eQTL functions were then obtained from the 3'aQTL-atlas and GTEx databases. Subsequently, additional case-control studies were performed to validate the relationship between the candidate apaQTL/eQTL-SNPs and the risk of silicosis. Finally, experiments were conducted to illustrate APA events occurring at different alleles of the identified apaQTL/eQTL-SNPs. The combined results of the GWAS and iMLDR validations indicate that the variant T allele of the rs2974341 located on SMIM19 (additive model: OR = 0.66, the 95% CI = 0.53-0.84, P = 0.001) and the variant T allele of the rs2390488 located on TMTC4 (additive model: OR = 0.72, 95% CI = 0.57-0.90, P = 0.005) were significantly associated with decreased risk of developing silicosis susceptibility. Furthermore, 3'RACE experiments verified the presence of two poly (A) sites (proximal and distal) in SMIM19, rs2974341 may remotely regulate the binding between miRNA-3646 and SMIM19 with its high LD locus rs2974353 to affect the expression level of SMIM19. The rs2974341 variant T allele may contribute to the generation of the shorter 3'UTR transcript of SMIM19 and affect the binding of miRNA-3646 to the target gene SMIM19. The apaQTL/eQTL-SNPs may provide new perspectives for evaluating the regulatory function of SNPs in the development of silicosis.

Colocalization analysis of 3' UTR alternative polyadenylation quantitative trait loci reveals novel mechanisms underlying associations with lung function

While many disease-associated single nucleotide polymorphisms (SNPs) are expression quantitative trait loci (eQTLs), a large proportion of genome-wide association study (GWAS) variants are of unknown function. Alternative polyadenylation (APA) plays an important role in posttranscriptional regulation by allowing genes to shorten or extend 3' untranslated regions (UTRs). We hypothesized that genetic variants that affect APA in lung tissue may lend insight into the function of respiratory associated GWAS loci. We generated alternative polyadenylation (apa) QTLs using RNA sequencing and whole genome sequencing on 1241 subjects from the Lung Tissue Research Consortium (LTRC) as part of the NHLBI TOPMed project. We identified 56 179 APA sites corresponding to 13 582 unique genes after filtering out APA sites with low usage. We found that a total of 8831 APA sites were associated with at least one SNP with q-value < 0.05. The genomic distribution of lead APA SNPs indicated that the majority are intronic variants (33%), followed by downstream gene variants (26%), 3' UTR variants (17%), and upstream gene variants (within 1 kb region upstream of transcriptional start site, 10%). APA sites in 193 genes colocalized with GWAS data for at least one phenotype. Genes containing the top APA sites associated with GWAS variants include membrane associated ring-CH-type finger 2 (MARCHF2), nectin cell adhesion molecule 2 (NECTIN2), and butyrophilin subfamily 3 member A2 (BTN3A2). Overall, these findings suggest that APA may be an important mechanism for genetic variants in lung function and chronic obstructive pulmonary disease (COPD).

2'-O-methylation at internal sites on mRNA promotes mRNA stability

2'-O-methylation (Nm) is a prominent RNA modification well known in noncoding RNAs and more recently also found at many mRNA internal sites. However, their function and base-resolution stoichiometry remain underexplored. Here, we investigate the transcriptome-wide effect of internal site Nm on mRNA stability. Combining nanopore sequencing with our developed machine learning method, NanoNm, we identify thousands of Nm sites on mRNAs with a single-base resolution. We observe a positive effect of FBL-mediated Nm modification on mRNA stability and expression level. Elevated FBL expression in cancer cells is associated with increased expression levels for 2'-O-methylated mRNAs of cancer pathways, implying the role of FBL in post-transcriptional regulation. Lastly, we find that FBL-mediated 2'-O-methylation connects to widespread 3' UTR shortening, a mechanism that globally increases RNA stability. Collectively, we demonstrate that FBL-mediated Nm modifications at mRNA internal sites regulate gene expression by enhancing mRNA stability.

FUS reads histone H3K36me3 to regulate alternative polyadenylation

Complex organisms generate differential gene expression through the same set of DNA sequences in distinct cells. The communication between chromatin and RNA regulates cellular behavior in tissues. However, little is known about how chromatin, especially histone modifications, regulates RNA polyadenylation. In this study, we found that FUS was recruited to chromatin by H3K36me3 at gene bodies. The H3K36me3 recognition of FUS was mediated by the proline residues in the ZNF domain. After these proline residues were mutated or H3K36me3 was abolished, FUS dissociated from chromatin and bound more to RNA, resulting in an increase in polyadenylation sites far from stop codons genome-wide. A proline mutation corresponding to a mutation in amyotrophic lateral sclerosis contributed to the hyperactivation of mitochondria and hyperdifferentiation in mouse embryonic stem cells. These findings reveal that FUS is an H3K36me3 reader protein that links chromatin-mediated alternative polyadenylation to human disease.

Transcriptomic Analysis of the Spatiotemporal Axis of Oogenesis and Fertilization in C. elegans

The oocyte germline of the C. elegans hermaphrodite presents a unique model to study the formation of oocytes. However, the size of the model animal and difficulties in retrieval of specific stages of the germline have obviated closer systematic studies of this process throughout the years. Here, we present a transcriptomic level analysis into the oogenesis of C. elegans hermaphrodites. We dissected a hermaphrodite gonad into seven sections corresponding to the mitotic distal region, the pachytene, the diplotene, the early diakinesis region and the 3 most proximal oocytes, and deeply sequenced the transcriptome of each of them along with that of the fertilized egg using a single-cell RNA-seq protocol. We identified specific gene expression events as well as gene splicing events in finer detail along the oocyte germline and provided novel insights into underlying mechanisms of the oogenesis process. Furthermore, through careful review of relevant research literature coupled with patterns observed in our analysis, we attempt to delineate transcripts that may serve functions in the interaction between the germline and cells of the somatic gonad. These results expand our knowledge of the transcriptomic space of the C. elegans germline and lay a foundation on which future studies of the germline can be based upon.

Alternative polyadenylation quantitative trait loci contribute to acute myeloid leukemia risk genes regulation

Acute myeloid leukemia (AML) is a hematopoietic malignancy with a high relapse rate and progressive drug resistance. Alternative polyadenylation (APA) contributes to post-transcriptional dysregulation, but little is known about the association between APA and AML. The APA quantitative trait locus (apaQTL) is a powerful method to investigate the relationship between APA and single nucleotide polymorphisms (SNPs). We quantified APA usage in 195 Chinese AML patients and identified 4922 cis-apaQTLs related to 1875 genes, most of which were newly reported. Cis-apaQTLs may modulate the APA selection of 115 genes through poly(A) signals. Colocalization analysis revealed that cis-apaQTLs colocalized with cis-eQTLs may regulate gene expression by affecting miRNA binding sites or RNA secondary structures. We discovered 207 cis-apaQTLs related to AML risk by comparing genotype frequency with the East Asian healthy controls from the 1000 Genomes Project. Genes with cis-apaQTLs were associated with hematological phenotypes and tumor incidence according to the PHARMGKB and MGI databases. Collectively, we profiled an atlas of cis-apaQTLs in Asian AML patients and found their association with APA selection, gene expression, AML risk, and complex traits. Cis-apaQTLs may provide insights into the regulatory mechanisms related to APA in AML occurrence, progression, and prognosis.

Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention and intervention

Identifying risk protein targets and their therapeutic drugs is crucial for effective cancer prevention. Here, we conduct integrative and fine-mapping analyses of large genome-wide association studies data for breast, colorectal, lung, ovarian, pancreatic, and prostate cancers, and characterize 710 lead variants independently associated with cancer risk. Through mapping protein quantitative trait loci (pQTL) for these variants using plasma proteomics data from over 75,000 participants, we identify 365 proteins associated with cancer risk. Subsequent colocalization analysis identifies 101 proteins, including 74 not reported in previous studies. We further characterize 36 potential druggable proteins for cancers or other disease indications. Analyzing >3.5 million electronic health records, we uncover five drugs (Haloperidol, Trazodone, Tranexamic Acid, Haloperidol, and Captopril) associated with increased cancer risk and two drugs (Caffeine and Acetazolamide) linked to reduced colorectal cancer risk. This study offers novel insights into therapeutic drugs targeting risk proteins for cancer prevention and intervention.

Long-read sequencing for 29 immune cell subsets reveals disease-linked isoforms

Alternative splicing events are a major causal mechanism for complex traits, but they have been understudied due to the limitation of short-read sequencing. Here, we generate a full-length isoform annotation of human immune cells from an individual by long-read sequencing for 29 cell subsets. This contains a number of unannotated transcripts and isoforms such as a read-through transcript of TOMM40-APOE in the Alzheimer's disease locus. We profile characteristics of isoforms and show that repetitive elements significantly explain the diversity of unannotated isoforms, providing insight into the human genome evolution. In addition, some of the isoforms are expressed in a cell-type specific manner, whose alternative 3'-UTRs usage contributes to their specificity. Further, we identify disease-associated isoforms by isoform switch analysis and by integration of several quantitative trait loci analyses with genome-wide association study data. Our findings will promote the elucidation of the mechanism of complex diseases via alternative splicing.

Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms

RNA splicing is highly prevalent in the brain and has strong links to neuropsychiatric disorders; yet, the role of cell type-specific splicing and transcript-isoform diversity during human brain development has not been systematically investigated. In this work, we leveraged single-molecule long-read sequencing to deeply profile the full-length transcriptome of the germinal zone and cortical plate regions of the developing human neocortex at tissue and single-cell resolution. We identified 214,516 distinct isoforms, of which 72.6% were novel (not previously annotated in Gencode version 33), and uncovered a substantial contribution of transcript-isoform diversity-regulated by RNA binding proteins-in defining cellular identity in the developing neocortex. We leveraged this comprehensive isoform-centric gene annotation to reprioritize thousands of rare de novo risk variants and elucidate genetic risk mechanisms for neuropsychiatric disorders.

Predicting functional UTR variants by integrating region-specific features

The untranslated region (UTR) of messenger ribonucleic acid (mRNA), including the 5'UTR and 3'UTR, plays a critical role in regulating gene expression and translation. Variants within the UTR can lead to changes associated with human traits and diseases; however, computational prediction of UTR variant effect is challenging. Current noncoding variant prediction mainly focuses on the promoters and enhancers, neglecting the unique sequence of the UTR and thereby limiting their predictive accuracy. In this study, using consolidated datasets of UTR variants from disease databases and large-scale experimental data, we systematically analyzed more than 50 region-specific features of UTR, including functional elements, secondary structure, sequence composition and site conservation. Our analysis reveals that certain features, such as C/G-related sequence composition in 5'UTR and A/T-related sequence composition in 3'UTR, effectively differentiate between nonfunctional and functional variant sets, unveiling potential sequence determinants of functional UTR variants. Leveraging these insights, we developed two classification models to predict functional UTR variants using machine learning, achieving an area under the curve (AUC) value of 0.94 for 5'UTR and 0.85 for 3'UTR, outperforming all existing methods. Our models will be valuable for enhancing clinical interpretation of genetic variants, facilitating the prediction and management of disease risk.

Quantifying 3'UTR length from scRNA-seq data reveals changes independent of gene expression

Although more than half of all genes generate transcripts that differ in 3'UTR length, current analysis pipelines only quantify the amount but not the length of mRNA transcripts. 3'UTR length is determined by 3' end cleavage sites (CS). We map CS in more than 200 primary human and mouse cell types and increase CS annotations relative to the GENCODE database by 40%. Approximately half of all CS are used in few cell types, revealing that most genes only have one or two major 3' ends. We incorporate the CS annotations into a computational pipeline, called scUTRquant, for rapid, accurate, and simultaneous quantification of gene and 3'UTR isoform expression from single-cell RNA sequencing (scRNA-seq) data. When applying scUTRquant to data from 474 cell types and 2134 perturbations, we discover extensive 3'UTR length changes across cell types that are as widespread and coordinately regulated as gene expression changes but affect mostly different genes. Our data indicate that mRNA abundance and mRNA length are two largely independent axes of gene regulation that together determine the amount and spatial organization of protein synthesis.

Disentangling genetic effects on transcriptional and post-transcriptional gene regulation through integrating exon and intron expression QTLs

Expression quantitative trait loci (eQTL) studies typically consider exon expression of genes and discard intronic RNA sequencing reads despite their information on RNA metabolism. Here, we quantify genetic effects on exon and intron levels of genes and their ratio in lymphoblastoid cell lines, revealing thousands of cis-QTLs of each type. While genetic effects are often shared between cis-QTL types, 7814 (47%) are not detected as top cis-QTLs at exon levels. We show that exon levels preferentially capture genetic effects on transcriptional regulation, while exon-intron-ratios better detect those on co- and post-transcriptional processes. Considering all cis-QTL types substantially increases (by 71%) the number of colocalizing variants identified by genome-wide association studies (GWAS). It further allows dissecting the potential gene regulatory processes underlying GWAS associations, suggesting comparable contributions by transcriptional (50%) and co- and post-transcriptional regulation (46%) to complex traits. Overall, integrating intronic RNA sequencing reads in eQTL studies expands our understanding of genetic effects on gene regulatory processes.

Identification and characterization of whole blood gene expression and splicing quantitative trait loci during early to mid-lactation of dairy cattle

BACKGROUND

Characterization of regulatory variants (e.g., gene expression quantitative trait loci, eQTL; gene splicing QTL, sQTL) is crucial for biologically interpreting molecular mechanisms underlying loci associated with complex traits. However, regulatory variants in dairy cattle, particularly in specific biological contexts (e.g., distinct lactation stages), remain largely unknown. In this study, we explored regulatory variants in whole blood samples collected during early to mid-lactation (22-150 days after calving) of 101 Holstein cows and analyzed them to decipher the regulatory mechanisms underlying complex traits in dairy cattle.

RESULTS

We identified 14,303 genes and 227,705 intron clusters expressed in the white blood cells of 101 cattle. The average heritability of gene expression and intron excision ratio explained by cis-SNPs is 0.28 ± 0.13 and 0.25 ± 0.13, respectively. We identified 23,485 SNP-gene expression pairs and 18,166 SNP-intron cluster pairs in dairy cattle during early to mid-lactation. Compared with the 2,380,457 cis-eQTLs reported to be present in blood in the Cattle Genotype-Tissue Expression atlas (CattleGTEx), only 6,114 cis-eQTLs (P < 0.05) were detected in the present study. By conducting colocalization analysis between cis-e/sQTL and the results of genome-wide association studies (GWAS) from four traits, we identified a cis-e/sQTL (rs109421300) of the DGAT1 gene that might be a key marker in early to mid-lactation for milk yield, fat yield, protein yield, and somatic cell score (PP4 > 0.6). Finally, transcriptome-wide association studies (TWAS) revealed certain genes (e.g., FAM83H and TBC1D17) whose expression in white blood cells was significantly (P < 0.05) associated with complex traits.

CONCLUSIONS

This study investigated the genetic regulation of gene expression and alternative splicing in dairy cows during early to mid-lactation and provided new insights into the regulatory mechanisms underlying complex traits of economic importance.

Circulating tumor cell clustering modulates RNA splicing and polyadenylation to facilitate metastasis

Circulating tumor cell (CTC) clusters exhibit significantly higher metastatic potential compared to single CTCs. However, the underlying mechanism behind this phenomenon remains unclear, and the role of posttranscriptional RNA regulation in CTC clusters has not been explored. Here, we conducted a comparative analysis of alternative splicing (AS) and alternative polyadenylation (APA) profiles between single CTCs and CTC clusters. We identified 994 and 836 AS events in single CTCs and CTC clusters, respectively, with ∼20% of AS events showing differential regulation between the two cell types. A key event in this differential splicing was observed in SRSF6, which disrupted AS profiles and contributed to the increased malignancy of CTC clusters. Regarding APA, we found a global lengthening of 3' UTRs in CTC clusters compared to single CTCs. This alteration was primarily governed by 14 core APA factors, particularly PPP1CA. The modified APA profiles facilitated the cell cycle progression of CTC clusters and indicated their reduced susceptibility to oxidative stress. Further investigation revealed that the proportion of H2AFY mRNA with long 3' UTR instead of short 3' UTR was higher in CTC clusters than single CTCs. The AU-rich elements (AREs) within the long 3' UTR of H2AFY mRNA enhance mRNA stability and translation activity, resulting in promoting cell proliferation and invasion, which potentially facilitate the establishment and rapid formation of metastatic tumors mediated by CTC clusters. These findings provide new insights into the mechanisms driving CTC cluster metastasis.

Proteasome hyperactivation rewires the proteome enhancing stress resistance, proteostasis, lipid metabolism and ERAD in C. elegans

Proteasome dysfunction is implicated in the pathogenesis of neurodegenerative diseases and age-related proteinopathies. Using a C. elegans model, we demonstrate that 20S proteasome hyperactivation, facilitated by 20S gate-opening, accelerates the targeting of intrinsically disordered proteins. This leads to increased protein synthesis, extensive rewiring of the proteome and transcriptome, enhanced oxidative stress defense, accelerated lipid metabolism, and peroxisome proliferation. It also promotes ER-associated degradation (ERAD) of aggregation-prone proteins, such as alpha-1 antitrypsin (ATZ) and various lipoproteins. Notably, our results reveal that 20S proteasome hyperactivation suggests a novel role in ERAD with broad implications for proteostasis-related disorders, simultaneously affecting lipid homeostasis and peroxisome proliferation. Furthermore, the enhanced cellular capacity to mitigate proteostasis challenges, alongside unanticipated acceleration of lipid metabolism is expected to contribute to the longevity phenotype of this mutant. Remarkably, the mechanism of longevity induced by 20S gate opening appears unique, independent of known longevity and stress-resistance pathways. These results support the therapeutic potential of 20S proteasome activation in mitigating proteostasis-related disorders broadly and provide new insights into the complex interplay between proteasome activity, cellular health, and aging.

Alternative polyadenylation quantitative trait methylation mapping in human cancers provides clues into the molecular mechanisms of APA

Genetic variants are involved in the orchestration of alternative polyadenylation (APA) events, while the role of DNA methylation in regulating APA remains unclear. We generated a comprehensive atlas of APA quantitative trait methylation sites (apaQTMs) across 21 different types of cancer (1,612 to 60,219 acting in cis and 4,448 to 142,349 in trans). Potential causal apaQTMs in non-cancer samples were also identified. Mechanistically, we observed a strong enrichment of cis-apaQTMs near polyadenylation sites (PASs) and both cis- and trans-apaQTMs in proximity to transcription factor (TF) binding regions. Through the integration of ChIP-signals and RNA-seq data from cell lines, we have identified several regulators of APA events, acting either directly or indirectly, implicating novel functions of some important genes, such as TCF7L2, which is known for its involvement in type 2 diabetes and cancers. Furthermore, we have identified a vast number of QTMs that share the same putative causal CpG sites with five different cancer types, underscoring the roles of QTMs, including apaQTMs, in the process of tumorigenesis. DNA methylation is extensively involved in the regulation of APA events in human cancers. In an attempt to elucidate the potential underlying molecular mechanisms of APA by DNA methylation, our study paves the way for subsequent experimental validations into the intricate biological functions of DNA methylation in APA regulation and the pathogenesis of human cancers. To present a comprehensive catalog of apaQTM patterns, we introduce the Pancan-apaQTM database, available at https://pancan-apaqtm-zju.shinyapps.io/pancanaQTM/.

The Transcriptional Landscape of Immune-Response 3'-UTR Alternative Polyadenylation in Melanoma

The prognosis of patients with malignant melanoma has been improved in recent decades due to advancements in immunotherapy. However, a considerable proportion of patients are refractory to treatment, particularly at advanced stages. This underscores the necessity of developing a new strategy to improve it. Alternative polyadenylation (APA), as a marker of crucial posttranscriptional regulation, has emerged as a major new type of epigenetic marker involved in tumorigenesis. However, the potential roles of APA in shaping the tumor microenvironment (TME) are largely unexplored. Herein, we collected two cohorts comprising melanoma patients who received immune checkpoint inhibitor (ICI) immunotherapy to quantify transcriptome-wide discrepancies in APA. We observed a global change in 3'-UTRs between responders and non-responders, which might involve DNA damage response, angiogenesis, PI3K-AKT signaling pathways, etc. Ten putative master APA regulatory factors for those APA events were detected via a network analysis. Notably, we established an immune response-related APA scoring system (IRAPAss), which exhibited a great performance of predicting immunotherapy response in multiple cohorts. Furthermore, we examined the correlation of APA with TME at the single-cell level using four single-cell immune profiles of tumor-infiltrating lymphocytes (TILs), which revealed an overall discrepancy in 3'-UTR length across diverse T cell populations, probably contributing to immunoregulation in melanoma. In conclusion, our study provides a transcriptional landscape of APA implicated in immunoregulation, which might lay the foundation for developing a new strategy for improving immunotherapy response for melanoma patients by targeting APA.

A distinct class of pan-cancer susceptibility genes revealed by an alternative polyadenylation transcriptome-wide association study

Alternative polyadenylation plays an important role in cancer initiation and progression; however, current transcriptome-wide association studies mostly ignore alternative polyadenylation when identifying putative cancer susceptibility genes. Here, we perform a pan-cancer 3' untranslated region alternative polyadenylation transcriptome-wide association analysis by integrating 55 well-powered (n > 50,000) genome-wide association studies datasets across 22 major cancer types with alternative polyadenylation quantification from 23,955 RNA sequencing samples across 7,574 individuals. We find that genetic variants associated with alternative polyadenylation are co-localized with 28.57% of cancer loci and contribute a significant portion of cancer heritability. We further identify 642 significant cancer susceptibility genes predicted to modulate cancer risk via alternative polyadenylation, 62.46% of which have been overlooked by traditional expression- and splicing- studies. As proof of principle validation, we show that alternative alleles facilitate 3' untranslated region lengthening of CRLS1 gene leading to increased protein abundance and promoted proliferation of breast cancer cells. Together, our study highlights the significant role of alternative polyadenylation in discovering new cancer susceptibility genes and provides a strong foundational framework for enhancing our understanding of the etiology underlying human cancers.

Structured 3' UTRs destabilize mRNAs in plants

BACKGROUND

RNA secondary structure (RSS) can influence the regulation of transcription, RNA processing, and protein synthesis, among other processes. 3' untranslated regions (3' UTRs) of mRNA also hold the key for many aspects of gene regulation. However, there are often contradictory results regarding the roles of RSS in 3' UTRs in gene expression in different organisms and/or contexts.

RESULTS

Here, we incidentally observe that the primary substrate of miR159a (pri-miR159a), when embedded in a 3' UTR, could promote mRNA accumulation. The enhanced expression is attributed to the earlier polyadenylation of the transcript within the hybrid pri-miR159a-3' UTR and, resultantly, a poorly structured 3' UTR. RNA decay assays indicate that poorly structured 3' UTRs could promote mRNA stability, whereas highly structured 3' UTRs destabilize mRNA in vivo. Genome-wide DMS-MaPseq also reveals the prevailing inverse relationship between 3' UTRs' RSS and transcript accumulation in the transcriptomes of Arabidopsis, rice, and even human. Mechanistically, transcripts with highly structured 3' UTRs are preferentially degraded by 3'-5' exoribonuclease SOV and 5'-3' exoribonuclease XRN4, leading to decreased expression in Arabidopsis. Finally, we engineer different structured 3' UTRs to an endogenous FT gene and alter the FT-regulated flowering time in Arabidopsis.

CONCLUSIONS

We conclude that highly structured 3' UTRs typically cause reduced accumulation of the harbored transcripts in Arabidopsis. This pattern extends to rice and even mammals. Furthermore, our study provides a new strategy of engineering the 3' UTRs' RSS to modify plant traits in agricultural production and mRNA stability in biotechnology.

Comparative alternative polyadenylation profiles in differentiated adipocytes of subcutaneous and intramuscular fat tissue in cattle

Alternative polyadenylation (APA) is a key molecular mechanism involved in the post-transcriptional regulation of gene expression, which has been proven to play a critical role in cell differentiation. In the present study, we performed IVT-SAPAS sequencing to profile the dynamic changes of APA sites in bovine subcutaneous preadipocytes and intramuscular preadipocytes during adipogenesis. A total of 52621 high quality APA sites were identified in preadipocytes and adipocytes. Compared with preadipocytes, the increased usage of canonical AATAAA was observed in the cell-biased APA sites of adipocytes. Furthermore, 1933 and 2140 differentially expressed APA (DE-APA) sites, as well as 341 and 337 untranslated region-APA (UTR-APA) switching genes were identified in subcutaneous preadipocytes and intramuscular preadipocytes during adipogenesis, respectively. The UTR-APA switching genes showed divergent trends in preadipocytes, among which UTR-APA switching genes in intramuscular preadipocytes tended to use shorter 3'UTR for differentiation into mature adipocytes. APA events mediated by UTR-APA switching in intramuscular adipocytes were enriched in lipid synthesis and adipocyte differentiation. TRIB3, WWTR1, and INSIG1 played important roles in the differentiation of intramuscular preadipocytes. Briefly, our results provided new insights into understanding the mechanisms of bovine adipocyte differentiation.

Identifying novel chemical-related susceptibility genes for five psychiatric disorders through integrating genome-wide association study and tissue-specific 3'aQTL annotation datasets

The establishment of 3'aQTLs comprehensive database provides an opportunity to help explore the functional interpretation from the genome-wide association study (GWAS) data of psychiatric disorders. In this study, we aim to search novel susceptibility genes, pathways, and related chemicals of five psychiatric disorders via GWAS and 3'aQTLs datasets. The GWAS datasets of five psychiatric disorders were collected from the open platform of Psychiatric Genomics Consortium (PGC, https://www.med.unc.edu/pgc/ ) and iPSYCH ( https://ipsych.dk/ ) (Demontis et al. in Nat Genet 51(1):63-75, 2019; Grove et al. in Nat Genet 51:431-444, 2019; Genomic Dissection of Bipolar Disorder and Schizophrenia in Cell 173: 1705-1715.e1716, 2018; Mullins et al. in Nat Genet 53: 817-829; Howard et al. in Nat Neurosci 22: 343-352, 2019). The 3'untranslated region (3'UTR) alternative polyadenylation (APA) quantitative trait loci (3'aQTLs) summary datasets of 12 brain regions were obtained from another public platform ( https://wlcb.oit.uci.edu/3aQTLatlas/ ) (Cui et al. in Nucleic Acids Res 50: D39-D45, 2022). First, we aligned the GWAS-associated SNPs of psychiatric disorders and datasets of 3'aQTLs, and then, the GWAS-associated 3'aQTLs were identified from the overlap. Second, gene ontology (GO) and pathway analysis was applied to investigate the potential biological functions of matching genes based on the methods provided by MAGMA. Finally, chemical-related gene-set analysis (GSA) was also conducted by MAGMA to explore the potential interaction of GWAS-associated 3'aQTLs and multiple chemicals in the mechanism of psychiatric disorders. A number of susceptibility genes with 3'aQTLs were found to be associated with psychiatric disorders and some of them had brain-region specificity. For schizophrenia (SCZ), HLA-A showed associated with psychiatric disorders in all 12 brain regions, such as cerebellar hemisphere (P = 1.58 × 10-36) and cortex (P = 1.58 × 10-36). GO and pathway analysis identified several associated pathways, such as Phenylpropanoid Metabolic Process (GO:0009698, P = 6.24 × 10-7 for SCZ). Chemical-related GSA detected several chemical-related gene sets associated with psychiatric disorders. For example, gene sets of Ferulic Acid (P = 6.24 × 10-7), Morin (P = 4.47 × 10-2) and Vanillic Acid (P = 6.24 × 10-7) were found to be associated with SCZ. By integrating the functional information from 3'aQTLs, we identified several susceptibility genes and associated pathways especially chemical-related gene sets for five psychiatric disorders. Our results provided new insights to understand the etiology and mechanism of psychiatric disorders.

TDP-43 dysregulation of polyadenylation site selection is a defining feature of RNA misprocessing in ALS/FTD and related disorders

Nuclear clearance and cytoplasmic aggregation of the RNA-binding protein TDP-43 are observed in many neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS) and fronto- temporal dementia (FTD). Although TDP-43 dysregulation of splicing has emerged as a key event in these diseases, TDP-43 can also regulate polyadenylation; yet, this has not been adequately studied. Here, we applied the dynamic analysis of polyadenylation from RNA-seq (DaPars) tool to ALS/FTD transcriptome datasets, and report extensive alternative polyadenylation (APA) upon TDP-43 alteration in ALS/FTD cell models and postmortem ALS/FTD neuronal nuclei. Importantly, many identified APA genes highlight pathways implicated in ALS/FTD pathogenesis. To determine the functional significance of APA elicited by TDP-43 nuclear depletion, we examined microtubule affinity regulating kinase 3 (MARK3). Nuclear loss of TDP-43 yielded increased expression of MARK3 transcripts with longer 3'UTRs, resulting in greater transcript stability and elevated MARK3 protein levels, which promotes increased neuronal tau S262 phosphorylation. Our findings define changes in polyadenylation site selection as a previously unrecognized feature of TDP-43-driven disease pathology in ALS/FTD and highlight a potentially novel mechanistic link between TDP-43 dysfunction and tau regulation.

Polygenic risk for schizophrenia converges on alternative polyadenylation as molecular mechanism underlying synaptic impairment

Schizophrenia (SCZ) is a genetically heterogenous psychiatric disorder of highly polygenic nature. Correlative evidence from genetic studies indicate that the aggregated effects of distinct genetic risk factor combinations found in each patient converge onto common molecular mechanisms. To prove this on a functional level, we employed a reductionistic cellular model system for polygenic risk by differentiating induced pluripotent stem cells (iPSCs) from 104 individuals with high polygenic risk load and controls into cortical glutamatergic neurons (iNs). Multi-omics profiling identified widespread differences in alternative polyadenylation (APA) in the 3' untranslated region of many synaptic transcripts between iNs from SCZ patients and healthy donors. On the cellular level, 3'APA was associated with a reduction in synaptic density of iNs. Importantly, differential APA was largely conserved between postmortem human prefrontal cortex from SCZ patients and healthy donors, and strongly enriched for transcripts related to synapse biology. 3'APA was highly correlated with SCZ polygenic risk and affected genes were significantly enriched for SCZ associated common genetic variation. Integrative functional genomic analysis identified the RNA binding protein and SCZ GWAS risk gene PTBP2 as a critical trans-acting factor mediating 3'APA of synaptic genes in SCZ subjects. Functional characterization of PTBP2 in iNs confirmed its key role in 3'APA of synaptic transcripts and regulation of synapse density. Jointly, our findings show that the aggregated effects of polygenic risk converge on 3'APA as one common molecular mechanism that underlies synaptic impairments in SCZ.

PRMD: an integrated database for plant RNA modifications

The scope and function of RNA modifications in model plant systems have been extensively studied, resulting in the identification of an increasing number of novel RNA modifications in recent years. Researchers have gradually revealed that RNA modifications, especially N6-methyladenosine (m6A), which is one of the most abundant and commonly studied RNA modifications in plants, have important roles in physiological and pathological processes. These modifications alter the structure of RNA, which affects its molecular complementarity and binding to specific proteins, thereby resulting in various of physiological effects. The increasing interest in plant RNA modifications has necessitated research into RNA modifications and associated datasets. However, there is a lack of a convenient and integrated database with comprehensive annotations and intuitive visualization of plant RNA modifications. Here, we developed the Plant RNA Modification Database (PRMD; http://bioinformatics.sc.cn/PRMD and http://rnainformatics.org.cn/PRMD) to facilitate RNA modification research. This database contains information regarding 20 plant species and provides an intuitive interface for displaying information. Moreover, PRMD offers multiple tools, including RMlevelDiff, RMplantVar, RNAmodNet and Blast (for functional analyses), and mRNAbrowse, RNAlollipop, JBrowse and Integrative Genomics Viewer (for displaying data). Furthermore, PRMD is freely available, making it useful for the rapid development and promotion of research on plant RNA modifications.

Immune-response 3'UTR alternative polyadenylation quantitative trait loci contribute to variation in human complex traits and diseases

Genome-wide association studies (GWASs) have identified thousands of non-coding variants that are associated with human complex traits and diseases. The analysis of such GWAS variants in different contexts and physiological states is essential for deciphering the regulatory mechanisms underlying human disease. Alternative polyadenylation (APA) is a key post-transcriptional modification for most human genes that substantially impacts upon cell behavior. Here, we mapped 9,493 3'-untranslated region APA quantitative trait loci in 18 human immune baseline cell types and 8 stimulation conditions (immune 3'aQTLs). Through the comparison between baseline and stimulation data, we observed the high responsiveness of 3'aQTLs to immune stimulation (response 3'aQTLs). Co-localization and mendelian randomization analyses of immune 3'aQTLs identified 678 genes where 3'aQTL are associated with variation in complex traits, 27.3% of which were derived from response 3'aQTLs. Overall, these analyses reveal the role of immune 3'aQTLs in the determination of complex traits, providing new insights into the regulatory mechanisms underlying disease etiologies.

Therapeutic targeting of CPSF3-dependent transcriptional termination in ovarian cancer

Transcriptional dysregulation is a recurring pathogenic hallmark and an emerging therapeutic vulnerability in ovarian cancer. Here, we demonstrated that ovarian cancer exhibited a unique dependency on the regulatory machinery of transcriptional termination, particularly, cleavage and polyadenylation specificity factor (CPSF) complex. Genetic abrogation of multiple CPSF subunits substantially hampered neoplastic cell viability, and we presented evidence that their indispensable roles converged on the endonuclease CPSF3. Mechanistically, CPSF perturbation resulted in lengthened 3'-untranslated regions, diminished intronic polyadenylation and widespread transcriptional readthrough, and consequently suppressed oncogenic pathways. Furthermore, we reported the development of specific CPSF3 inhibitors building upon the benzoxaborole scaffold, which exerted potent antitumor activity. Notably, CPSF3 blockade effectively exacerbated genomic instability by down-regulating DNA damage repair genes and thus acted in synergy with poly(adenosine 5'-diphosphate-ribose) polymerase inhibition. These findings establish CPSF3-dependent transcriptional termination as an exploitable driving mechanism of ovarian cancer and provide a promising class of boron-containing compounds for targeting transcription-addicted human malignancies.

xQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs

Genome-wide association studies (GWAS) have identified thousands of disease-associated non-coding variants, posing urgent needs for functional interpretation. Molecular Quantitative Trait Loci (xQTLs) such as eQTLs serve as an essential intermediate link between these non-coding variants and disease phenotypes and have been widely used to discover disease-risk genes from many population-scale studies. However, mining and analyzing the xQTLs data presents several significant bioinformatics challenges, particularly when it comes to integration with GWAS data. Here, we developed xQTLbiolinks as the first comprehensive and scalable tool for bulk and single-cell xQTLs data retrieval, quality control and pre-processing from public repositories and our integrated resource. In addition, xQTLbiolinks provided a robust colocalization module through integration with GWAS summary statistics. The result generated by xQTLbiolinks can be flexibly visualized or stored in standard R objects that can easily be integrated with other R packages and custom pipelines. We applied xQTLbiolinks to cancer GWAS summary statistics as case studies and demonstrated its robust utility and reproducibility. xQTLbiolinks will profoundly accelerate the interpretation of disease-associated variants, thus promoting a better understanding of disease etiologies. xQTLbiolinks is available at https://github.com/lilab-bioinfo/xQTLbiolinks.

A novel APA-based prognostic signature may predict the prognosis of lung adenocarcinoma in an East Asian population

The role of alternative polyadenylation (APA) in tumor development is becoming increasingly evident, but the impact of APA events on the prognosis of LUAD patients is unclear. Therefore, in the present study, we aimed to analyze specific APA events in LUAD to identify novel prognostic biomarkers for LUAD. We first identified prognostic candidate genes for LUAD associated with APA events and validated them in both the East Asian and the USA cohorts, finding that five genes (DCUN1D5, PSMC4, TFAM, THRA, and TMEM100) were of prognostic significance in both populations. Based on this, an APA-based prognostic signature was constructed for the East Asian population. The predictive accuracy of the prognostic signature was further evaluated by the time-dependent ROC, with 1-, 2-, and 3-year AUCs of 0.86, 0.81, and 0.71, respectively. This study may provide new markers for individualized diagnosis and prognostic assessment of LUAD and potential targets for precision treatment.

Alternative polyadenylation-related genetic variants contribute to bladder cancer risk

Aberrant alternative polyadenylation (APA) events play an important role in cancers, but little is known about whether APA-related genetic variants contribute to the susceptibility to bladder cancer. Previous genome-wide association study performed APA quantitative trait loci (apaQTL) analyses in bladder cancer, and identified 17 955 single nucleotide polymorphisms (SNPs). We found that gene symbols of APA affected by apaQTL-associated SNPs were closely correlated with cancer signaling pathways, high mutational burden, and immune infiltration. Association analysis showed that apaQTL-associated SNPs rs34402449 C>A, rs2683524 C>T, and rs11540872 C>G were significantly associated with susceptibility to bladder cancer (rs34402449: OR = 1.355, 95% confidence interval [CI]: 1.159-1.583, P = 1.33 × 10 -4; rs2683524: OR = 1.378, 95% CI: 1.164-1.632, P = 2.03 × 10 -4; rs11540872: OR = 1.472, 95% CI: 1.193-1.815, P = 3.06 × 10 -4). Cumulative effect analysis showed that the number of risk genotypes and smoking status were significantly associated with an increased risk of bladder cancer ( P trend = 2.87 × 10 -12). We found that PRR13, being demonstrated the most significant effect on cell proliferation in bladder cancer cell lines, was more highly expressed in bladder cancer tissues than in adjacent normal tissues. Moreover, the rs2683524 T allele was correlated with shorter 3' untranslated regions of PRR13 and increased PRR13 expression levels. Collectively, our findings have provided informative apaQTL resources and insights into the regulatory mechanisms linking apaQTL-associated variants to bladder cancer risk.

Deep learning of human polyadenylation sites at nucleotide resolution reveals molecular determinants of site usage and relevance in disease

The genomic distribution of cleavage and polyadenylation (polyA) sites should be co-evolutionally optimized with the local gene structure. Otherwise, spurious polyadenylation can cause premature transcription termination and generate aberrant proteins. To obtain mechanistic insights into polyA site optimization across the human genome, we develop deep/machine learning models to identify genome-wide putative polyA sites at unprecedented nucleotide-level resolution and calculate their strength and usage in the genomic context. Our models quantitatively measure position-specific motif importance and their crosstalk in polyA site formation and cleavage heterogeneity. The intronic site expression is governed by the surrounding splicing landscape. The usage of alternative polyA sites in terminal exons is modulated by their relative locations and distance to downstream genes. Finally, we apply our models to reveal thousands of disease- and trait-associated genetic variants altering polyadenylation activity. Altogether, our models represent a valuable resource to dissect molecular mechanisms mediating genome-wide polyA site expression and characterize their functional roles in human diseases.

Large-scale alternative polyadenylation (APA)-wide association studies to identify putative susceptibility genes in human common cancers

Alternative polyadenylation (APA) modulates mRNA processing in the 3' untranslated regions (3'UTR), which affect mRNA stability and translation efficiency. Here, we build genetic models to predict APA levels in multiple tissues using sequencing data of 1,337 samples from the Genotype-Tissue Expression, and apply these models to assess associations between genetically predicted APA levels and cancer risk with data from large genome-wide association studies of six common cancers, including breast, ovary, prostate, colorectum, lung, and pancreas among European-ancestry populations. At a Bonferroni-corrected P □<□0.05, we identify 58 risk genes, including seven in newly identified loci. Using luciferase reporter assays, we demonstrate that risk alleles of 3'UTR variants, rs324015 ( STAT6 ), rs2280503 ( DIP2B ), rs1128450 ( FBXO38 ) and rs145220637 ( LDAH ), could significantly increase post-transcriptional activities of their target genes compared to reference alleles. Further gene knockdown experiments confirm their oncogenic roles. Our study provides additional insight into the genetic susceptibility of these common cancers.

Functional filter for whole-genome sequencing data identifies HHT and stress-associated non-coding SMAD4 polyadenylation site variants >5 kb from coding DNA

Despite whole-genome sequencing (WGS), many cases of single-gene disorders remain unsolved, impeding diagnosis and preventative care for people whose disease-causing variants escape detection. Since early WGS data analytic steps prioritize protein-coding sequences, to simultaneously prioritize variants in non-coding regions rich in transcribed and critical regulatory sequences, we developed GROFFFY, an analytic tool that integrates coordinates for regions with experimental evidence of functionality. Applied to WGS data from solved and unsolved hereditary hemorrhagic telangiectasia (HHT) recruits to the 100,000 Genomes Project, GROFFFY-based filtration reduced the mean number of variants/DNA from 4,867,167 to 21,486, without deleting disease-causal variants. In three unsolved cases (two related), GROFFFY identified ultra-rare deletions within the 3' untranslated region (UTR) of the tumor suppressor SMAD4, where germline loss-of-function alleles cause combined HHT and colonic polyposis (MIM: 175050). Sited >5.4 kb distal to coding DNA, the deletions did not modify or generate microRNA binding sites, but instead disrupted the sequence context of the final cleavage and polyadenylation site necessary for protein production: By iFoldRNA, an AAUAAA-adjacent 16-nucleotide deletion brought the cleavage site into inaccessible neighboring secondary structures, while a 4-nucleotide deletion unfolded the downstream RNA polymerase II roadblock. SMAD4 RNA expression differed to control-derived RNA from resting and cycloheximide-stressed peripheral blood mononuclear cells. Patterns predicted the mutational site for an unrelated HHT/polyposis-affected individual, where a complex insertion was subsequently identified. In conclusion, we describe a functional rare variant type that impacts regulatory systems based on RNA polyadenylation. Extension of coding sequence-focused gene panels is required to capture these variants.

Genetic Variants That Impact Alternative Polyadenylation in Cancer Represent Candidate Causal Risk Loci

Alternative polyadenylation (APA) is emerging as a major mechanism of posttranscriptional regulation. APA can impact the development and progression of cancer, suggesting that the genetic determinants of APA might play an important role in regulating cancer risk. Here, we depicted a pan-cancer atlas of human APA quantitative trait loci (apaQTL), containing approximately 0.7 million apaQTLs across 32 cancer types. Systematic multiomics analyses indicated that cancer apaQTLs could contribute to APA regulation by altering poly(A) motifs, RNA-binding proteins (RBP), and chromatin regulatory elements and were preferentially enriched in genome-wide association studies (GWAS)-identified cancer susceptibility loci. Moreover, apaQTL-related genes (aGene) were broadly related to cancer signaling pathways, high mutational burden, immune infiltration, and drug response, implicating their potential as therapeutic targets. Furthermore, apaQTLs were mapped in Chinese colorectal cancer tumor tissues and then screened for functional apaQTLs associated with colorectal cancer risk in 17,789 cases and 19,951 controls using GWAS-ChIP data, with independent validation in a large-scale population consisting of 6,024 cases and 10,022 controls. A multi-ancestry-associated apaQTL variant rs1020670 with a C>G change in DNM1L was identified, and the G allele contributed to an increased risk of colorectal cancer. Mechanistically, the risk variant promoted aberrant APA and facilitated higher usage of DNM1L proximal poly(A) sites mediated by the RBP CSTF2T, which led to higher expression of DNM1L with a short 3'UTR. This stabilized DNM1L to upregulate its expression, provoking colorectal cancer cell proliferation. Collectively, these findings generate a resource for understanding APA regulation and the genetic basis of human cancers, providing insights into cancer etiology.

SIGNIFICANCE

Cancer risk is mediated by alternative polyadenylation quantitative trait loci, including the rs1020670-G variant that promotes alternative polyadenylation of DNM1L and increases colorectal cancer risk.

Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective

Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.

Systematic differences in discovery of genetic effects on gene expression and complex traits

Most signals in genome-wide association studies (GWAS) of complex traits implicate noncoding genetic variants with putative gene regulatory effects. However, currently identified regulatory variants, notably expression quantitative trait loci (eQTLs), explain only a small fraction of GWAS signals. Here, we show that GWAS and cis-eQTL hits are systematically different: eQTLs cluster strongly near transcription start sites, whereas GWAS hits do not. Genes near GWAS hits are enriched in key functional annotations, are under strong selective constraint and have complex regulatory landscapes across different tissue/cell types, whereas genes near eQTLs are depleted of most functional annotations, show relaxed constraint, and have simpler regulatory landscapes. We describe a model to understand these observations, including how natural selection on complex traits hinders discovery of functionally relevant eQTLs. Our results imply that GWAS and eQTL studies are systematically biased toward different types of variant, and support the use of complementary functional approaches alongside the next generation of eQTL studies.

Long 3'UTRs predispose neurons to inflammation by promoting immunostimulatory double-stranded RNA formation

Loss of RNA homeostasis underlies numerous neurodegenerative and neuroinflammatory diseases. However, the molecular mechanisms that trigger neuroinflammation are poorly understood. Viral double-stranded RNA (dsRNA) triggers innate immune responses when sensed by host pattern recognition receptors (PRRs) present in all cell types. Here, we report that human neurons intrinsically carry exceptionally high levels of immunostimulatory dsRNAs and identify long 3'UTRs as giving rise to neuronal dsRNA structures. We found that the neuron-enriched ELAVL family of genes (ELAVL2, ELAVL3, and ELAVL4) can increase (i) 3'UTR length, (ii) dsRNA load, and (iii) activation of dsRNA-sensing PRRs such as MDA5, PKR, and TLR3. In wild-type neurons, neuronal dsRNAs signaled through PRRs to induce tonic production of the antiviral type I interferon. Depleting ELAVL2 in WT neurons led to global shortening of 3'UTR length, reduced immunostimulatory dsRNA levels, and rendered WT neurons susceptible to herpes simplex virus and Zika virus infection. Neurons deficient in ADAR1, a dsRNA-editing enzyme mutated in the neuroinflammatory disorder Aicardi-Goutières syndrome, exhibited intolerably high levels of dsRNA that triggered PRR-mediated toxic inflammation and neuronal death. Depleting ELAVL2 in ADAR1 knockout neurons led to prolonged neuron survival by reducing immunostimulatory dsRNA levels. In summary, neurons are specialized cells where PRRs constantly sense "self" dsRNAs to preemptively induce protective antiviral immunity, but maintaining RNA homeostasis is paramount to prevent pathological neuroinflammation.

Alternative polyadenylation regulates acetyl-CoA carboxylase function in peanut

BACKGROUND

Polyadenylation is a crucial process that terminates mRNA molecules at their 3'-ends. It has been observed that alternative polyadenylation (APA) can generate multiple transcripts from a single gene locus, each with different polyadenylation sites (PASs). This leads to the formation of several 3' untranslated regions (UTRs) that vary in length and composition. APA has a significant impact on approximately 60-70% of eukaryotic genes and has far-reaching implications for cell proliferation, differentiation, and tumorigenesis.

RESULTS

In this study, we conducted long-read, single-molecule sequencing of mRNA from peanut seeds. Our findings revealed that over half of all peanut genes possess over two PASs, with older developing seeds containing more PASs. This suggesting that the PAS exhibits high tissue specificity and plays a crucial role in peanut seed maturation. For the peanut acetyl-CoA carboxylase A1 (AhACCA1) gene, we discovered four 3' UTRs referred to UTR1-4. RT-PCR analysis showed that UTR1-containing transcripts are predominantly expressed in roots, leaves, and early developing seeds. Transcripts containing UTR2/3 accumulated mainly in roots, flowers, and seeds, while those carrying UTR4 were constitutively expressed. In Nicotiana benthamiana leaves, we transiently expressed all four UTRs, revealing that each UTR impacted protein abundance but not subcellular location. For functional validation, we introduced each UTR into yeast cells and found UTR2 enhanced AhACCA1 expression compared to a yeast transcription terminator, whereas UTR3 did not. Furthermore, we determined ACC gene structures in seven plant species and identified 51 PASs for 15 ACC genes across four plant species, confirming that APA of the ACC gene family is universal phenomenon in plants.

CONCLUSION

Our data demonstrate that APA is widespread in peanut seeds and plays vital roles in peanut seed maturation. We have identified four 3' UTRs for AhACCA1 gene, each showing distinct tissue-specific expression patterns. Through subcellular location experiment and yeast transformation test, we have determined that UTR2 has a stronger impact on gene expression regulation compared to the other three UTRs.

Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms

RNA splicing is highly prevalent in the brain and has strong links to neuropsychiatric disorders, yet the role of cell-type-specific splicing or transcript-isoform diversity during human brain development has not been systematically investigated. Here, we leveraged single-molecule long-read sequencing to deeply profile the full-length transcriptome of the germinal zone (GZ) and cortical plate (CP) regions of the developing human neocortex at tissue and single-cell resolution. We identified 214,516 unique isoforms, of which 72.6% are novel (unannotated in Gencode-v33), and uncovered a substantial contribution of transcript-isoform diversity, regulated by RNA binding proteins, in defining cellular identity in the developing neocortex. We leveraged this comprehensive isoform-centric gene annotation to re-prioritize thousands of rare de novo risk variants and elucidate genetic risk mechanisms for neuropsychiatric disorders.

One-Sentence Summary

A cell-specific atlas of gene isoform expression helps shape our understanding of brain development and disease.

Structured Abstract

INTRODUCTION: The development of the human brain is regulated by precise molecular and genetic mechanisms driving spatio-temporal and cell-type-specific transcript expression programs. Alternative splicing, a major mechanism increasing transcript diversity, is highly prevalent in the human brain, influences many aspects of brain development, and has strong links to neuropsychiatric disorders. Despite this, the cell-type-specific transcript-isoform diversity of the developing human brain has not been systematically investigated.RATIONALE: Understanding splicing patterns and isoform diversity across the developing neocortex has translational relevance and can elucidate genetic risk mechanisms in neurodevelopmental disorders. However, short-read sequencing, the prevalent technology for transcriptome profiling, is not well suited to capturing alternative splicing and isoform diversity. To address this, we employed third-generation long-read sequencing, which enables capture and sequencing of complete individual RNA molecules, to deeply profile the full-length transcriptome of the germinal zone (GZ) and cortical plate (CP) regions of the developing human neocortex at tissue and single-cell resolution.RESULTS: We profiled microdissected GZ and CP regions of post-conception week (PCW) 15-17 human neocortex in bulk and at single-cell resolution across six subjects using high-fidelity long-read sequencing (PacBio IsoSeq). We identified 214,516 unique isoforms, of which 72.6% were novel (unannotated in Gencode), and >7,000 novel exons, expanding the proteome by 92,422 putative proteoforms. We uncovered thousands of isoform switches during cortical neurogenesis predicted to impact RNA regulatory domains or protein structure and implicating previously uncharacterized RNA-binding proteins in cellular identity and neuropsychiatric disease. At the single-cell level, early-stage excitatory neurons exhibited the greatest isoform diversity, and isoform-centric single-cell clustering led to the identification of previously uncharacterized cell states. We systematically assessed the contribution of transcriptomic features, and localized cell and spatio-temporal transcript expression signatures across neuropsychiatric disorders, revealing predominant enrichments in dynamic isoform expression and utilization patterns and that the number and complexity of isoforms per gene is strongly predictive of disease. Leveraging this resource, we re-prioritized thousands of rare de novo risk variants associated with autism spectrum disorders (ASD), intellectual disability (ID), and neurodevelopmental disorders (NDDs), more broadly, to potentially more severe consequences and revealed a larger proportion of cryptic splice variants with the expanded transcriptome annotation provided in this study.CONCLUSION: Our study offers a comprehensive landscape of isoform diversity in the human neocortex during development. This extensive cataloging of novel isoforms and splicing events sheds light on the underlying mechanisms of neurodevelopmental disorders and presents an opportunity to explore rare genetic variants linked to these conditions. The implications of our findings extend beyond fundamental neuroscience, as they provide crucial insights into the molecular basis of developmental brain disorders and pave the way for targeted therapeutic interventions. To facilitate exploration of this dataset we developed an online portal ( https://sciso.gandallab.org/ ).

Infernape uncovers cell type-specific and spatially resolved alternative polyadenylation in the brain

Differential polyadenylation sites (PAs) critically regulate gene expression, but their cell type-specific usage and spatial distribution in the brain have not been systematically characterized. Here, we present Infernape, which infers and quantifies PA usage from single-cell and spatial transcriptomic data and show its application in the mouse brain. Infernape uncovers alternative intronic PAs and 3'-UTR lengthening during cortical neurogenesis. Progenitor-neuron comparisons in the excitatory and inhibitory neuron lineages show overlapping PA changes in embryonic brains, suggesting that the neural proliferation-differentiation axis plays a prominent role. In the adult mouse brain, we uncover cell type-specific PAs and visualize such events using spatial transcriptomic data. Over two dozen neurodevelopmental disorder-associated genes such as Csnk2a1 and Mecp2 show differential PAs during brain development. This study presents Infernape to identify PAs from scRNA-seq and spatial data, and highlights the role of alternative PAs in neuronal gene regulation.

Evaluating the interaction between 3'aQTL and alcohol consumption/smoking on anxiety and depression: 3'aQTL-by-environment interaction study in UK Biobank cohort

BACKGROUND

Smoking and alcohol consumption were associated with the development of depression and anxiety. 3'UTR APA quantitative trait loci (3'aQTLs) have been associated with multiple health states and conditions. Our aim is to evaluate the interactive effects of 3'aQTLs-alcohol consumption/tobacco smoking on the risk of anxiety and depression.

METHODS

The 3'aQTL data of 13 brain regions were extracted from the large-scale 3'aQTL atlas. The phenotype data (frequency of cigarette smoking and alcohol drinking, anxiety score, self-reported anxiety, depression score and self-reported depression) of 90,399-103,011 adults aged 40-69 years living in the UK and contributing to the UK Biobank during 2006-2010, were obtained from the UK Biobank cohort. The frequency of cigarette smoking and alcohol drinking of each subject were defined by the amount of smoking and alcohol drinking of self-reported, respectively. The continuous alcohol consumption/smoking terms were further categorized in tertiles. 3'aQTL-by-environmental interaction analysis was then performed to evaluate the associations of gene-smoking/alcohol consumption interactions with anxiety and depression using generalized linear model (GLM) of PLINK 2.0 with an additive mode of inheritance. Furthermore, GLM was also used to explore the relationship between alcohol consumption/smoking with hazard of anxiety/depression stratified by allele for the significant genotyped SNPs that modified the alcohol consumption/smoking-anxiety/depression association.

RESULTS

The interaction analysis identified several candidate 3'aQTLs-alcohol consumption interactions, such as rs7602638 located in PPP3R1 (β = 0.08, P = 6.50 × 10-6) for anxiety score; rs10925518 located in RYR2 (OR = 0.95, P = 3.06 × 10-5) for self-reported depression. Interestingly, we also observed that the interactions between TMOD1 (β = 0.18, P = 3.30 × 10-8 for anxiety score; β = 0.17, P = 1.42 × 10-6 for depression score), ZNF407 (β = 0.17, P = 2.11 × 10-6 for anxiety score; β = 0.15, P = 4.26 × 10-5 for depression score) and alcohol consumption was not only associated with anxiety, but related to depression. Besides, we found that relationship between alcohol consumption and hazard of anxiety/depression was significantly different for different SNPs genotypes, such as rs34505550 in TMOD1 (AA: OR = 1.03, P = 1.79 × 10-6; AG: OR = 1.00, P = 0.94; GG: OR = 1.00, P = 0.21) for self-reported anxiety.

LIMITATIONS

The identified 3'aQTLs-alcohol consumption/smoking interactions were associated with depression and anxiety, and its potential biological mechanisms need to be further revealed.

CONCLUSIONS

Our study identified important interactions between candidate 3'aQTL and alcohol consumption/smoking on depression and anxiety, and found that the 3'aQTL may modify the associations between consumption/smoking with depression and anxiety. These findings may help to further explore the pathogenesis of depression and anxiety.

Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis

The function of some genetic variants associated with brain-relevant traits has been explained through colocalization with expression quantitative trait loci (eQTL) conducted in bulk post-mortem adult brain tissue. However, many brain-trait associated loci have unknown cellular or molecular function. These genetic variants may exert context-specific function on different molecular phenotypes including post-transcriptional changes. Here, we identified genetic regulation of RNA-editing and alternative polyadenylation (APA), within a cell-type-specific population of human neural progenitors and neurons. More RNA-editing and isoforms utilizing longer polyadenylation sequences were observed in neurons, likely due to higher expression of genes encoding the proteins mediating these post-transcriptional events. We also detected hundreds of cell-type-specific editing quantitative trait loci (edQTLs) and alternative polyadenylation QTLs (apaQTLs). We found colocalizations of a neuron edQTL in CCDC88A with educational attainment and a progenitor apaQTL in EP300 with schizophrenia, suggesting genetically mediated post-transcriptional regulation during brain development lead to differences in brain function.

ClipperQTL: ultrafast and powerful eGene identification method

A central task in expression quantitative trait locus (eQTL) analysis is to identify cis-eGenes (henceforth "eGenes"), i.e., genes whose expression levels are regulated by at least one local genetic variant. Among the existing eGene identification methods, FastQTL is considered the gold standard but is computationally expensive as it requires thousands of permutations for each gene. Alternative methods such as eigenMT and TreeQTL have lower power than FastQTL. In this work, we propose ClipperQTL, which reduces the number of permutations needed from thousands to 20 for data sets with large sample sizes (> 450) by using the contrastive strategy developed in Clipper; for data sets with smaller sample sizes, it uses the same permutation-based approach as FastQTL. We show that ClipperQTL performs as well as FastQTL and runs about 500 times faster if the contrastive strategy is used and 50 times faster if the conventional permutation-based approach is used. The R package ClipperQTL is available at https://github.com/heatherjzhou/ClipperQTL.