Wei Li

Immune-cold tumours such as prostate cancer often resist immune checkpoint therapies (ICT) due to impaired antigen presentation via major histocompatibility complex class I (MHC-I). While MHC-I downregulation is a common immune evasion mechanism, no approved therapies selectively restore MHC-I expression in tumours. We developed a programmable RNA engineering platform, termed the 3'UTR CRISPR/dCas13 Engineering System (3'UTRCES), to precisely manipulate mRNA alternative polyadenylation (APA) in vivo. We identified tumour-specific 3'UTR shortening of the E3 ligase adaptor SPSB1 as a driver of MHC-I degradation via SPSB1-mediated ubiquitination, without affecting PD-L1. Lipid nanoparticle (LNP)-delivered 3'UTRCES reversed SPSB1 3'UTR shortening, restored MHC-I expression and sensitized tumours to ICT in syngeneic mice. These effects were elicited by MHC-I-dependent increases in CD8 T cell infiltration and antitumour cytotoxic activity. Our findings reveal APA-driven MHC-I suppression as a previously unrecognized mechanism of immune escape and establish LNP-3'UTRCES as a versatile platform for post-transcriptional RNA engineering in cancer.

The role of the epigenome in age-related neurodegenerative disorders remains understudied. Here, we analyzed circulating cell-free DNA (cfDNA) from blood to detect methylation changes as a liquid-biopsy for Amyotrophic Lateral Sclerosis (ALS). Our study included 20 patients with sporadic ALS, 10 patients with C9orf72-associated ALS, 10 asymptomatic carriers of the C9orf72 repeat expansion mutation, and 21 non-disease controls. Following targeted enzymatic methyl-sequencing (EM-seq) of ~4 million CpG sites, we detected numerous differentially methylated genes, including several implicated in ALS disease risk and pathogenesis. By integrating multiple epigenetic features, we delineated a distinct epigenetic signature, which achieved an average area under the curve (AUC) of 0.91 plus/minus 0.10 upon receiver operator characteristic (ROC) analysis, which enabled detection of ~70% of ALS patients with close to 100% specificity. Furthermore, we also identified a set of genes whose methylation status significantly correlated with clinical disease progression and cerebrospinal fluid (CSF) neurofilament levels. Our results reveal the potential of cfDNA-based biomarkers to accurately diagnose ALS and potentially predict disease progression.

Aims: Missense variants in the CALM1, CALM2, and CALM3 genes cause calmodulinopathy, which is characterised by ventricular arrhythmias and sudden cardiac death. Although the three genes encode an identical protein, their individual roles and gene-specific clinical implications remain poorly understood. We aimed to determine the relative contribution from each of the genes to the total calmodulin amount and assess the consequence of missense mutations on the severity of calmodulinopathy. Methods and results: Using data from the Genotype-Tissue Expression (GTEx) project, we show that CALM2 constituted a higher percentage of the calmodulin-coding mRNA (41.9%) compared to CALM1 (36.8%) and CALM3 (21.3%) (p < 2×10-16). Paired RNA sequencing and ribosome profiling data from the left ventricle was used to demonstrate that the translation into calmodulin protein was significantly different among CALM1 (44.8%) and CALM2 (44.2%), and CALM3 (11.0%) (p < 2×10-16). The observed-to-expected ratio for the number of missense variants in the Genome Aggregation Database (gnomAD) was 0.29 (90% CI, 0.23-0.36) in CALM3, 0.20 (90% CI, 0.15-0.27) in CALM2, and 0.11 in CALM1 (90% CI, 0.07-0.17). In the International Calmodulinopathy Registry, a different percentage of carriers experiencing cardiac events was observed among those with missense variants in CALM1 (46/52, 89%), CALM2 (37/53, 70%), and CALM3 (20/35, 57%) (p = 0.004). Conclusions: Compared to CALM1 and CALM2, CALM3 is under less negative selection and missense variant carriers are less prone to cardiac events. We suggest this is partially due to CALM3 accounting for only 11% of the calmodulin protein produced in the ventricles.

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

Background: Missense variants in the CALM1, CALM2, and CALM3 genes cause calmodulinopathy, an ultra-rare spectrum of clinical manifestations, including ventricular arrhythmias and sudden cardiac death. The three genes encode an identical calmodulin protein. However, little is known about the potential different clinical consequences of protein-altering variants in each of the three genes. Methods: We compared variants from the International Calmodulinopathy Registry with population data from the Genome Aggregation Database (gnomAD). RNA sequencing data from the Genotype-Tissue Expression (GTEx) project was used to investigate the relative expression of CALM1, CALM2, and CALM3 among 49 different human tissues. We used ribosome profiling data of left ventricle tissue to estimate the percentage of calmodulin that could be attributed to each of CALM1 , CALM2 , and CALM3 . Results: The percentage of carriers with cardiac events was different among carriers with missense variants in CALM1, CALM2, and CALM3 ( p = 0.004). Observed-to-expected ratios in population data were higher in CALM3 (0.29) in comparison to CALM2 (0.20) and especially, CALM1 (0.11) suggesting differential selection against missense variants in the three genes. RNA sequencing data revealed that CALM3 was less expressed than CALM1 and CALM2 in 39 of the 49 investigated tissues. Finally, the contribution to the total calmodulin amount in the left ventricle differed significantly among CALM1 , CALM2 , and CALM3 ( p < 2×10 ^-16 ), with estimated contributions of 45%, 44%, and 11%, respectively. Conclusions: Our findings reveal a four-fold greater contribution of CALM1 and CALM2 to the total calmodulin levels in the human heart compared to CALM3 , suggesting why missense variants in CALM3 are associated with a less severe cardiac phenotype than those in CALM1 and CALM2 .

Genetic mutation and drift, coupled with natural and human-mediated selection and migration, have produced a wide variety of genotypes and phenotypes in farmed animals. We here introduce the Farm Animal Genotype–Tissue Expression (FarmGTEx) Project, which aims to elucidate the genetic determinants of gene expression across 16 terrestrial and aquatic domestic species under diverse biological and environmental contexts. For each species, we aim to collect multiomics data, particularly genomics and transcriptomics, from 50 tissues of 1,000 healthy adults and 200 additional animals representing a specific context. This Perspective provides an overview of the priorities of FarmGTEx and advocates for coordinated strategies of data analysis and resource-sharing initiatives. FarmGTEx aims to serve as a platform for investigating context-specific regulatory effects, which will deepen our understanding of molecular mechanisms underlying complex phenotypes. The knowledge and insights provided by FarmGTEx will contribute to improving sustainable agriculture-based food systems, comparative biology and eventual human biomedicine.

Background: The incidence of early-onset colorectal cancer (EOCRC) has been rising at an alarming rate in the USA, and EOCRC disproportionately affects racial/ethnic minorities. Here, we construct comprehensive profiles of EOCRC DNA methylomes at base-pair resolution for a cohort of Hispanic and African American patients. Results: We show the epigenetic landscape of these EOCRC patients differs from that of late-onset colorectal cancer patients, and methylation canyons in EOCRC tumor tissue preferentially overlapped genes in cancer-related pathways. Furthermore, we identify epigenetic alterations in metabolic genes that are specific to our racial/ethnic minority EOCRC cohort but not Caucasian patients from TCGA. Top genes differentially methylated between these cohorts included the obesity-protective MFAP2 gene as well as cancer risk susceptibility genes APOL3 and RNASEL. Conclusions: In this study, we provide to the scientific community high-resolution DNA methylomes for a cohort of EOCRC patients from underrepresented populations. Our exploratory findings in this cohort highlight epigenetic mechanisms underlying the pathogenesis of EOCRC and nominate novel biomarkers for EOCRC in underrepresented populations.

Although rare non-coding variants (RVs) play crucial roles in complex traits and diseases, understanding their mechanisms and identifying disease-associated RVs continue to be major challenges. Here we constructed a comprehensive atlas of alternative polyadenylation (APA) outliers (aOutliers), including 1334 3′ UTR and 200 intronic aOutliers, from 15,201 samples across 49 human tissues. These aOutliers exhibit unique characteristics from transcription or splicing outliers, with a pronounced RV enrichment. Mechanistically, aOutlier-RVs alter poly(A) signals and splicing sites, and perturbation indeed triggers APA events. Furthermore, we developed a Bayesian-based APA RV prediction model, which successfully pinpointed a specific set of 1799 RVs impacting 278 genes with significantly large disease effect sizes. Notably, we observed a convergence effect between rare and common cancer variants, exemplified by regulation in the DDX18 gene. Together, this study introduced an APA-enhanced framework for genome annotation, underscoring APA’s role in uncovering functional RVs linked to complex traits and diseases.

Tandem repeat (TR) size variation is implicated in ~50 neurological disorders, yet its impact on gene regulation in the human brain remains largely unknown. In the present study, we quantified the impact of TR size variation on brain gene regulation across distinct molecular phenotypes, based on 4,412 multi-omics samples from 1,597 donors, including 1,586 newly sequenced ones. We identified ~2.2 million TR molecular quantitative trait loci (TR-xQTLs), linking ~139,000 unique TRs to nearby molecular phenotypes, including many known disease-risk TRs, such as the G₂C₄ expansion in C9orf72 associated with amyotrophic lateral sclerosis. Fine-mapping revealed ~18,700 TRs as potential causal variants. Our in vitro experiments further confirmed the causal and independent regulatory effects of three TRs. Additional colocalization analysis indicated the potential causal role of TR variation in brain-related phenotypes, highlighted by a 3ʹ-UTR TR in NUDT14 linked to cortical surface area and a TG repeat in PLEKHA1, associated with Alzheimer’s disease.