How much should we sequence? An analysis of the Swiss SARS-CoV-2 surveillance effort.

During the SARS-CoV-2 pandemic, many countries directed substantial resources toward genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic data set from Switzerland, comprising more than 143k sequences. We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. The impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage-dependent-something that is unknown at the time of sequencing-and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.IMPORTANCESwitzerland had one of the most comprehensive genomic surveillance systems during the COVID-19 pandemic. Such programs need to strike a balance between societal benefits and program costs. Our study aims to answer the question: How would surveillance outcomes have changed had we sequenced less? We find that some outcomes but also certain viral lineages are more affected than others by sequencing less. However, sequencing to around a third of the original effort still captured many important outcomes for the variants of concern such as their first detection but affected more strongly other measures like the detection of first transmission clusters for some lineages. Our work highlights the importance of setting predefined targets for a national genomic surveillance program based on which sequencing effort should be determined. Additionally, the use of a centralized surveillance platform facilitates aggregating data on a national level for rapid public health responses as well as post-analyses.

Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Integrated multi-omics reveals anaplerotic rewiring in methylmalonyl-CoA mutase deficiency.

Methylmalonic aciduria (MMA) is an inborn error of metabolism with multiple monogenic causes and a poorly understood pathogenesis, leading to the absence of effective causal treatments. Here we employ multi-layered omics profiling combined with biochemical and clinical features of individuals with MMA to reveal a molecular diagnosis for 177 out of 210 (84%) cases, the majority (148) of whom display pathogenic variants in methylmalonyl-CoA mutase (MMUT). Stratification of these data layers by disease severity shows dysregulation of the tricarboxylic acid cycle and its replenishment (anaplerosis) by glutamine. The relevance of these disturbances is evidenced by multi-organ metabolomics of a hemizygous Mmut mouse model as well as through identification of physical interactions between MMUT and glutamine anaplerotic enzymes. Using stable-isotope tracing, we find that treatment with dimethyl-oxoglutarate restores deficient tricarboxylic acid cycling. Our work highlights glutamine anaplerosis as a potential therapeutic intervention point in MMA.

Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D.

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in the stretch enhancers most strongly implicated in GWAS signal location; (c) enrichment of islet cis-eQTL signals with T2D risk variants identified in genome-wide association studies; and (d) colocalization between 47 islet cis-eQTLs and variants influencing T2D or glycemic traits, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in disease relevant tissues.

Combined genetic and transcriptome analysis of patients with SLE: distinct, targetable signatures for susceptibility and severity.

OBJECTIVES: Systemic lupus erythematosus (SLE) diagnosis and treatment remain empirical and the molecular basis for its heterogeneity elusive. We explored the genomic basis for disease susceptibility and severity. METHODS: mRNA sequencing and genotyping in blood from 142 patients with SLE and 58 healthy volunteers. Abundances of cell types were assessed by CIBERSORT and cell-specific effects by interaction terms in linear models. Differentially expressed genes (DEGs) were used to train classifiers (linear discriminant analysis) of SLE versus healthy individuals in 80% of the dataset and were validated in the remaining 20% running 1000 iterations. Transcriptome/genotypes were integrated by expression-quantitative trail loci (eQTL) analysis; tissue-specific genetic causality was assessed by regulatory trait concordance (RTC). RESULTS: SLE has a 'susceptibility signature' present in patients in clinical remission, an 'activity signature' linked to genes that regulate immune cell metabolism, protein synthesis and proliferation, and a 'severity signature' best illustrated in active nephritis, enriched in druggable granulocyte and plasmablast/plasma-cell pathways. Patients with SLE have also perturbed mRNA splicing enriched in immune system and interferon signalling genes. A novel transcriptome index distinguished active versus inactive disease-but not low disease activity-and correlated with disease severity. DEGs discriminate SLE versus healthy individuals with median sensitivity 86% and specificity 92% suggesting a potential use in diagnostics. Combined eQTL analysis from the Genotype Tissue Expression (GTEx) project and SLE-associated genetic polymorphisms demonstrates that susceptibility variants may regulate gene expression in the blood but also in other tissues. CONCLUSION: Specific gene networks confer susceptibility to SLE, activity and severity, and may facilitate personalised care.

Cellular circadian period length inversely correlates with HbA1c levels in individuals with type 2 diabetes.

AIMS/HYPOTHESIS: The circadian system plays an essential role in regulating the timing of human metabolism. Indeed, circadian misalignment is strongly associated with high rates of metabolic disorders. The properties of the circadian oscillator can be measured in cells cultured in vitro and these cellular rhythms are highly informative of the physiological circadian rhythm in vivo. We aimed to discover whether molecular properties of the circadian oscillator are altered as a result of type 2 diabetes. METHODS: We assessed molecular clock properties in dermal fibroblasts established from skin biopsies taken from nine obese and eight non-obese individuals with type 2 diabetes and 11 non-diabetic control individuals. Following in vitro synchronisation, primary fibroblast cultures were subjected to continuous assessment of circadian bioluminescence profiles based on lentiviral luciferase reporters. RESULTS: We observed a significant inverse correlation (ρ = -0.592; p < 0.05) between HbA1c values and circadian period length within cells from the type 2 diabetes group. RNA sequencing analysis conducted on samples from this group revealed that ICAM1, encoding the endothelial adhesion protein, was differentially expressed in fibroblasts from individuals with poorly controlled vs well-controlled type 2 diabetes and its levels correlated with cellular period length. Consistent with this circadian link, the ICAM1 gene also displayed rhythmic binding of the circadian locomotor output cycles kaput (CLOCK) protein that correlated with gene expression. CONCLUSIONS/INTERPRETATION: We provide for the first time a potential molecular link between glycaemic control in individuals with type 2 diabetes and circadian clock machinery. This paves the way for further mechanistic understanding of circadian oscillator changes upon type 2 diabetes development in humans. DATA AVAILABILITY: RNA sequencing data and clinical phenotypic data have been deposited at the European Genome-phenome Archive (EGA), which is hosted by the European Bioinformatics Institute (EBI) and the Centre for Genomic Regulation (CRG), ega-box-1210, under accession no. EGAS00001003622.

High-fat diet impacts more changes in beta-cell compared to alpha-cell transcriptome.

Characterization of endocrine-cell functions and associated molecular signatures in diabetes is crucial to better understand why and by which mechanisms alpha and beta cells cause and perpetuate metabolic abnormalities. The now recognized role of glucagon in diabetes control is a major incentive to have a better understanding of dysfunctional alpha cells. To characterize molecular alterations of alpha cells in diabetes, we analyzed alpha-cell transcriptome from control and diabetic mice using diet-induced obesity model. To this aim, we quantified the expression levels of total mRNAs from sorted alpha and beta cells of low-fat and high-fat diet-treated mice through RNAseq experiments, using a transgenic mouse strain allowing collections of pancreatic alpha- and beta-cells after 16 weeks of diet. We now report that pancreatic alpha cells from obese hyperglycemic mice displayed minor variations of their transcriptome compared to controls. Depending on analyses, we identified 11 to 39 differentially expressed genes including non-alpha cell markers mainly due to minor cell contamination during purification process. From these analyses, we identified three new target genes altered in diabetic alpha cells and potently involved in cellular stress and exocytosis (Upk3a, Adcy1 and Dpp6). By contrast, analysis of the beta-cell transcriptome from control and diabetic mice revealed major alterations of specific genes coding for proteins involved in proliferation and secretion. We conclude that alpha cell transcriptome is less reactive to HFD diet compared to beta cells and display adaptations to cellular stress and exocytosis.

Angiogenin and Osteoprotegerin are type II muscle specific myokines protecting pancreatic beta-cells against proinflammatory cytokines.

Tissue cross-talk is emerging as a determinant way to coordinate the different organs implicated in glucose homeostasis. Among the inter-organ communication factors, muscle-secreted myokines can modulate the function and survival of pancreatic beta-cells. Using primary human myotubes from soleus, vastus lateralis and triceps brachii muscles, we report here that the impact of myokines on beta-cells depends on fiber types and their metabolic status. We show that Type I and type II primary myotubes present specific mRNA and myokine signatures as well as a different sensitivity to TNF-alpha induced insulin resistance. Finally, we show that angiogenin and osteoprotegerin are triceps specific myokines with beta-cell protective actions against proinflammatory cytokines. These results suggest that type I and type II muscles could impact insulin secretion and beta-cell mass differentially in type 2 diabetes through specific myokines secretion.

Transcriptomic analyses reveal rhythmic and CLOCK-driven pathways in human skeletal muscle.

Circadian regulation of transcriptional processes has a broad impact on cell metabolism. Here, we compared the diurnal transcriptome of human skeletal muscle conducted on serial muscle biopsies in vivo with profiles of human skeletal myotubes synchronized in vitro. More extensive rhythmic transcription was observed in human skeletal muscle compared to in vitro cell culture as a large part of the in vivo mRNA rhythmicity was lost in vitro. siRNA-mediated clock disruption in primary myotubes significantly affected the expression of ~8% of all genes, with impact on glucose homeostasis and lipid metabolism. Genes involved in GLUT4 expression, translocation and recycling were negatively affected, whereas lipid metabolic genes were altered to promote activation of lipid utilization. Moreover, basal and insulin-stimulated glucose uptake were significantly reduced upon CLOCK depletion. Our findings suggest an essential role for the circadian coordination of skeletal muscle glucose homeostasis and lipid metabolism in humans.

The genomic landscape of human cellular circadian variation points to a novel role for the signalosome.

The importance of natural gene expression variation for human behavior is undisputed, but its impact on circadian physiology remains mostly unexplored. Using umbilical cord fibroblasts, we have determined by genome-wide association how common genetic variation impacts upon cellular circadian function. Gene set enrichment points to differences in protein catabolism as one major source of clock variation in humans. The two most significant alleles regulated expression of COPS7B, a subunit of the COP9 signalosome. We further show that the signalosome complex is imported into the nucleus in timed fashion to stabilize the essential circadian protein BMAL1, a novel mechanism to oppose its proteasome-mediated degradation. Thus, circadian clock properties depend in part upon a genetically-encoded competition between stabilizing and destabilizing forces, and genetic alterations in these mechanisms provide one explanation for human chronotype.

Extension of human lncRNA transcripts by RACE coupled with long-read high-throughput sequencing (RACE-Seq).

Long non-coding RNAs (lncRNAs) constitute a large, yet mostly uncharacterized fraction of the mammalian transcriptome. Such characterization requires a comprehensive, high-quality annotation of their gene structure and boundaries, which is currently lacking. Here we describe RACE-Seq, an experimental workflow designed to address this based on RACE (rapid amplification of cDNA ends) and long-read RNA sequencing. We apply RACE-Seq to 398 human lncRNA genes in seven tissues, leading to the discovery of 2,556 on-target, novel transcripts. About 60% of the targeted loci are extended in either 5' or 3', often reaching genomic hallmarks of gene boundaries. Analysis of the novel transcripts suggests that lncRNAs are as long, have as many exons and undergo as much alternative splicing as protein-coding genes, contrary to current assumptions. Overall, we show that RACE-Seq is an effective tool to annotate an organism's deep transcriptome, and compares favourably to other targeted sequencing techniques.

IL-13 improves beta-cell survival and protects against IL-1beta-induced beta-cell death.

OBJECTIVES: IL-13 is a cytokine classically produced by anti-inflammatory T-helper-2 lymphocytes; it is decreased in the circulation of type 2 diabetic patients and impacts positively on liver and skeletal muscle. Although IL-13 can exert positive effects on beta-cell lines, its impact and mode of action on primary beta-cell function and survival remain largely unexplored. METHODS: Beta-cells were cultured for 48 h in the presence of IL-13 alone or in combination with IL-1ß or cytokine cocktail (IL-1ß, IFNγ, TNFα). RESULTS: IL-13 protected human and rat beta-cells against cytokine induced death. However, IL-13 was unable to protect from IL-1ß impaired glucose stimulated insulin secretion and did not influence NFκB nuclear relocalization induced by IL-1ß. IL-13 induced phosphorylation of Akt, increased IRS2 protein expression and counteracted the IL-1ß induced regulation of several beta-cell stress response genes. CONCLUSIONS: The prosurvival effects of IL-13 thus appear to be mediated through IRS2/Akt signaling with NFκB independent regulation of gene expression. In addition to previously documented beneficial effects on insulin target tissues, these data suggest that IL-13 may be useful for treatment of type 2 diabetes by preserving beta-cell mass or slowing its rate of decline.

Genome-wide association study identifies shared risk loci common to two malignancies in golden retrievers.

Dogs, with their breed-determined limited genetic background, are great models of human disease including cancer. Canine B-cell lymphoma and hemangiosarcoma are both malignancies of the hematologic system that are clinically and histologically similar to human B-cell non-Hodgkin lymphoma and angiosarcoma, respectively. Golden retrievers in the US show significantly elevated lifetime risk for both B-cell lymphoma (6%) and hemangiosarcoma (20%). We conducted genome-wide association studies for hemangiosarcoma and B-cell lymphoma, identifying two shared predisposing loci. The two associated loci are located on chromosome 5, and together contribute ~20% of the risk of developing these cancers. Genome-wide p-values for the top SNP of each locus are 4.6×10-7 and 2.7×10-6, respectively. Whole genome resequencing of nine cases and controls followed by genotyping and detailed analysis identified three shared and one B-cell lymphoma specific risk haplotypes within the two loci, but no coding changes were associated with the risk haplotypes. Gene expression analysis of B-cell lymphoma tumors revealed that carrying the risk haplotypes at the first locus is associated with down-regulation of several nearby genes including the proximal gene TRPC6, a transient receptor Ca2+-channel involved in T-cell activation, among other functions. The shared risk haplotype in the second locus overlaps the vesicle transport and release gene STX8. Carrying the shared risk haplotype is associated with gene expression changes of 100 genes enriched for pathways involved in immune cell activation. Thus, the predisposing germ-line mutations in B-cell lymphoma and hemangiosarcoma appear to be regulatory, and affect pathways involved in T-cell mediated immune response in the tumor. This suggests that the interaction between the immune system and malignant cells plays a common role in the tumorigenesis of these relatively different cancers.

Comparative analysis of the transcriptome across distant species.

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a 'universal model' based on a single set of organism-independent parameters.

Genome-wide analyses implicate 33 loci in heritable dog osteosarcoma, including regulatory variants near CDKN2A/B.

BACKGROUND: Canine osteosarcoma is clinically nearly identical to the human disease, but is common and highly heritable, making genetic dissection feasible. RESULTS: Through genome-wide association analyses in three breeds (greyhounds, Rottweilers, and Irish wolfhounds), we identify 33 inherited risk loci explaining 55% to 85% of phenotype variance in each breed. The greyhound locus exhibiting the strongest association, located 150 kilobases upstream of the genes CDKN2A/B, is also the most rearranged locus in canine osteosarcoma tumors. The top germline candidate variant is found at a >90% frequency in Rottweilers and Irish wolfhounds, and alters an evolutionarily constrained element that we show has strong enhancer activity in human osteosarcoma cells. In all three breeds, osteosarcoma-associated loci and regions of reduced heterozygosity are enriched for genes in pathways connected to bone differentiation and growth. Several pathways, including one of genes regulated by miR124, are also enriched for somatic copy-number changes in tumors. CONCLUSIONS: Mapping a complex cancer in multiple dog breeds reveals a polygenic spectrum of germline risk factors pointing to specific pathways as drivers of disease.

The GENCODE pseudogene resource.

BACKGROUND: Pseudogenes have long been considered as nonfunctional genomic sequences. However, recent evidence suggests that many of them might have some form of biological activity, and the possibility of functionality has increased interest in their accurate annotation and integration with functional genomics data. RESULTS: As part of the GENCODE annotation of the human genome, we present the first genome-wide pseudogene assignment for protein-coding genes, based on both large-scale manual annotation and in silico pipelines. A key aspect of this coupled approach is that it allows us to identify pseudogenes in an unbiased fashion as well as untangle complex events through manual evaluation. We integrate the pseudogene annotations with the extensive ENCODE functional genomics information. In particular, we determine the expression level, transcription-factor and RNA polymerase II binding, and chromatin marks associated with each pseudogene. Based on their distribution, we develop simple statistical models for each type of activity, which we validate with large-scale RT-PCR-Seq experiments. Finally, we compare our pseudogenes with conservation and variation data from primate alignments and the 1000 Genomes project, producing lists of pseudogenes potentially under selection. CONCLUSIONS: At one extreme, some pseudogenes possess conventional characteristics of functionality; these may represent genes that have recently died. On the other hand, we find interesting patterns of partial activity, which may suggest that dead genes are being resurrected as functioning non-coding RNAs. The activity data of each pseudogene are stored in an associated resource, psiDR, which will be useful for the initial identification of potentially functional pseudogenes.

Landscape of transcription in human cells.

Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.

Combining RT-PCR-seq and RNA-seq to catalog all genic elements encoded in the human genome.

Within the ENCODE Consortium, GENCODE aimed to accurately annotate all protein-coding genes, pseudogenes, and noncoding transcribed loci in the human genome through manual curation and computational methods. Annotated transcript structures were assessed, and less well-supported loci were systematically, experimentally validated. Predicted exon-exon junctions were evaluated by RT-PCR amplification followed by highly multiplexed sequencing readout, a method we called RT-PCR-seq. Seventy-nine percent of all assessed junctions are confirmed by this evaluation procedure, demonstrating the high quality of the GENCODE gene set. RT-PCR-seq was also efficient to screen gene models predicted using the Human Body Map (HBM) RNA-seq data. We validated 73% of these predictions, thus confirming 1168 novel genes, mostly noncoding, which will further complement the GENCODE annotation. Our novel experimental validation pipeline is extremely sensitive, far more than unbiased transcriptome profiling through RNA sequencing, which is becoming the norm. For example, exon-exon junctions unique to GENCODE annotated transcripts are five times more likely to be corroborated with our targeted approach than with extensive large human transcriptome profiling. Data sets such as the HBM and ENCODE RNA-seq data fail sampling of low-expressed transcripts. Our RT-PCR-seq targeted approach also has the advantage of identifying novel exons of known genes, as we discovered unannotated exons in ~11% of assessed introns. We thus estimate that at least 18% of known loci have yet-unannotated exons. Our work demonstrates that the cataloging of all of the genic elements encoded in the human genome will necessitate a coordinated effort between unbiased and targeted approaches, like RNA-seq and RT-PCR-seq.

GENCODE: the reference human genome annotation for The ENCODE Project.

The GENCODE Consortium aims to identify all gene features in the human genome using a combination of computational analysis, manual annotation, and experimental validation. Since the first public release of this annotation data set, few new protein-coding loci have been added, yet the number of alternative splicing transcripts annotated has steadily increased. The GENCODE 7 release contains 20,687 protein-coding and 9640 long noncoding RNA loci and has 33,977 coding transcripts not represented in UCSC genes and RefSeq. It also has the most comprehensive annotation of long noncoding RNA (lncRNA) loci publicly available with the predominant transcript form consisting of two exons. We have examined the completeness of the transcript annotation and found that 35% of transcriptional start sites are supported by CAGE clusters and 62% of protein-coding genes have annotated polyA sites. Over one-third of GENCODE protein-coding genes are supported by peptide hits derived from mass spectrometry spectra submitted to Peptide Atlas. New models derived from the Illumina Body Map 2.0 RNA-seq data identify 3689 new loci not currently in GENCODE, of which 3127 consist of two exon models indicating that they are possibly unannotated long noncoding loci. GENCODE 7 is publicly available from gencodegenes.org and via the Ensembl and UCSC Genome Browsers.

Evidence for transcript networks composed of chimeric RNAs in human cells.

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network.