The Polygenic and Monogenic Basis of Blood Traits and Diseases.

Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation.

Misexpression of inactive genes in whole blood is associated with nearby rare structural variants.

Gene misexpression is the aberrant transcription of a gene in a context where it is usually inactive. Despite its known pathological consequences in specific rare diseases, we have a limited understanding of its wider prevalence and mechanisms in humans. To address this, we analyzed gene misexpression in 4,568 whole-blood bulk RNA sequencing samples from INTERVAL study blood donors. We found that while individual misexpression events occur rarely, in aggregate they were found in almost all samples and a third of inactive protein-coding genes. Using 2,821 paired whole-genome and RNA sequencing samples, we identified that misexpression events are enriched in cis for rare structural variants. We established putative mechanisms through which a subset of SVs lead to gene misexpression, including transcriptional readthrough, transcript fusions, and gene inversion. Overall, we develop misexpression as a type of transcriptomic outlier analysis and extend our understanding of the variety of mechanisms by which genetic variants can influence gene expression.

GWAS of genetic factors affecting white blood cell morphological parameters in Sardinians uncovers influence of chromosome 11 innate immunity gene cluster on eosinophil morphology.

Few genome-wide association studies (GWAS) analyzing genetic regulation of morphological traits of white blood cells have been reported. We carried out a GWAS of 12 morphological traits in 869 individuals from the general population of Sardinia, Italy. These traits, included measures of cell volume, conductivity and light scatter in four white-cell populations (eosinophils, lymphocytes, monocytes, neutrophils). This analysis yielded seven statistically significant signals, four of which were novel (four novel, PRG2, P2RX3, two of CDK6). Five signals were replicated in the independent INTERVAL cohort of 11 822 individuals. The most interesting signal with large effect size on eosinophil scatter (P-value = 8.33 x 10-32, beta = -1.651, se = 0.1351) falls within the innate immunity cluster on chromosome 11, and is located in the PRG2 gene. Computational analyses revealed that a rare, Sardinian-specific PRG2:p.Ser148Pro mutation modifies PRG2 amino acid contacts and protein dynamics in a manner that could possibly explain the changes observed in eosinophil morphology. Our discoveries shed light on genetics of morphological traits. For the first time, we describe such large effect size on eosinophils morphology that is relatively frequent in Sardinian population.

Transcriptome-wide association study in UK Biobank Europeans identifies associations with blood cell traits.

Previous genome-wide association studies (GWAS) of hematological traits have identified over 10 000 distinct trait-specific risk loci. However, at these loci, the underlying causal mechanisms remain incompletely characterized. To elucidate novel biology and better understand causal mechanisms at known loci, we performed a transcriptome-wide association study (TWAS) of 29 hematological traits in 399 835 UK Biobank (UKB) participants of European ancestry using gene expression prediction models trained from whole blood RNA-seq data in 922 individuals. We discovered 557 gene-trait associations for hematological traits distinct from previously reported GWAS variants in European populations. Among the 557 associations, 301 were available for replication in a cohort of 141 286 participants of European ancestry from the Million Veteran Program. Of these 301 associations, 108 replicated at a strict Bonferroni adjusted threshold ($\alpha$= 0.05/301). Using our TWAS results, we systematically assigned 4261 out of 16 900 previously identified hematological trait GWAS variants to putative target genes. Compared to coloc, our TWAS results show reduced specificity and increased sensitivity in external datasets to assign variants to target genes.

SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification.

High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in well-annotated mammalian species. The advances in sequencing technology have created a need for studies and tools that can characterize these novel variants. Here, we present SQANTI, an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse transcriptome using Pacific Biosciences (PacBio) long reads and illustrate how the tool is effective in characterizing and describing the composition of the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, resulting more frequently in novel ORFs than novel UTRs, and are enriched in both general metabolic and neural-specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read-based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases, we find that alternative isoforms are elusive to proteogenomics detection. SQANTI allows the user to maximize the analytical outcome of long-read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes.

The Characteristics of Heterozygous Protein Truncating Variants in the Human Genome.

Sequencing projects have identified large numbers of rare stop-gain and frameshift variants in the human genome. As most of these are observed in the heterozygous state, they test a gene's tolerance to haploinsufficiency and dominant loss of function. We analyzed the distribution of truncating variants across 16,260 autosomal protein coding genes in 11,546 individuals. We observed 39,893 truncating variants affecting 12,062 genes, which significantly differed from an expectation of 12,916 genes under a model of neutral de novo mutation (p<10-4). Extrapolating this to increasing numbers of sequenced individuals, we estimate that 10.8% of human genes do not tolerate heterozygous truncating variants. An additional 10 to 15% of truncated genes may be rescued by incomplete penetrance or compensatory mutations, or because the truncating variants are of limited functional impact. The study of protein truncating variants delineates the essential genome and, more generally, identifies rare heterozygous variants as an unexplored source of diversity of phenotypic traits and diseases.

Genetic associations at regulatory phenotypes improve fine-mapping of causal variants for 12 immune-mediated diseases.

The resolution of causal genetic variants informs understanding of disease biology. We used regulatory quantitative trait loci (QTLs) from the BLUEPRINT, GTEx and eQTLGen projects to fine-map putative causal variants for 12 immune-mediated diseases. We identify 340 unique loci that colocalize with high posterior probability (≥98%) with regulatory QTLs and apply Bayesian frameworks to fine-map associations at each locus. We show that fine-mapping credible sets derived from regulatory QTLs are smaller compared to disease summary statistics. Further, they are enriched for more functionally interpretable candidate causal variants and for putatively causal insertion/deletion (INDEL) polymorphisms. Finally, we use massively parallel reporter assays to evaluate candidate causal variants at the ITGA4 locus associated with inflammatory bowel disease. Overall, our findings suggest that fine-mapping applied to disease-colocalizing regulatory QTLs can enhance the discovery of putative causal disease variants and enhance insights into the underlying causal genes and molecular mechanisms.

Genetic perturbation of PU.1 binding and chromatin looping at neutrophil enhancers associates with autoimmune disease.

Neutrophils play fundamental roles in innate immune response, shape adaptive immunity, and are a potentially causal cell type underpinning genetic associations with immune system traits and diseases. Here, we profile the binding of myeloid master regulator PU.1 in primary neutrophils across nearly a hundred volunteers. We show that variants associated with differential PU.1 binding underlie genetically-driven differences in cell count and susceptibility to autoimmune and inflammatory diseases. We integrate these results with other multi-individual genomic readouts, revealing coordinated effects of PU.1 binding variants on the local chromatin state, enhancer-promoter contacts and downstream gene expression, and providing a functional interpretation for 27 genes underlying immune traits. Collectively, these results demonstrate the functional role of PU.1 and its target enhancers in neutrophil transcriptional control and immune disease susceptibility.

tappAS: a comprehensive computational framework for the analysis of the functional impact of differential splicing.

Recent advances in long-read sequencing solve inaccuracies in alternative transcript identification of full-length transcripts in short-read RNA-Seq data, which encourages the development of methods for isoform-centered functional analysis. Here, we present tappAS, the first framework to enable a comprehensive Functional Iso-Transcriptomics (FIT) analysis, which is effective at revealing the functional impact of context-specific post-transcriptional regulation. tappAS uses isoform-resolved annotation of coding and non-coding functional domains, motifs, and sites, in combination with novel analysis methods to interrogate different aspects of the functional readout of transcript variants and isoform regulation. tappAS software and documentation are available at https://app.tappas.org.

Event Analysis: Using Transcript Events To Improve Estimates of Abundance in RNA-seq Data.

Alternative splicing leverages genomic content by allowing the synthesis of multiple transcripts and, by implication, protein isoforms, from a single gene. However, estimating the abundance of transcripts produced in a given tissue from short sequencing reads is difficult and can result in both the construction of transcripts that do not exist, and the failure to identify true transcripts. An alternative approach is to catalog the events that make up isoforms (splice junctions and exons). We present here the Event Analysis (EA) approach, where we project transcripts onto the genome and identify overlapping/unique regions and junctions. In addition, all possible logical junctions are assembled into a catalog. Transcripts are filtered before quantitation based on simple measures: the proportion of the events detected, and the coverage. We find that mapping to a junction catalog is more efficient at detecting novel junctions than mapping in a splice aware manner. We identify 99.8% of true transcripts while iReckon identifies 82% of the true transcripts and creates more transcripts not included in the simulation than were initially used in the simulation. Using PacBio Iso-seq data from a mouse neural progenitor cell model, EA detects 60% of the novel junctions that are combinations of existing exons while only 43% are detected by STAR. EA further detects ∼5,000 annotated junctions missed by STAR. Filtering transcripts based on the proportion of the transcript detected and the number of reads on average supporting that transcript captures 95% of the PacBio transcriptome. Filtering the reference transcriptome before quantitation, results in is a more stable estimate of isoform abundance, with improved correlation between replicates. This was particularly evident when EA is applied to an RNA-seq study of type 1 diabetes (T1D), where the coefficient of variation among subjects (n = 81) in the transcript abundance estimates was substantially reduced compared to the estimation using the full reference. EA focuses on individual transcriptional events. These events can be quantitate and analyzed directly or used to identify the probable set of expressed transcripts. Simple rules based on detected events and coverage used in filtering result in a dramatic improvement in isoform estimation without the use of ancillary data (e.g., ChIP, long reads) that may not be available for many studies.

SOD3 improves the tumor response to chemotherapy by stabilizing endothelial HIF-2α.

One drawback of chemotherapy is poor drug delivery to tumor cells, due in part to hyperpermeability of the tumor vasculature. Extracellular superoxide dismutase (SOD3) is an antioxidant enzyme usually repressed in the tumor milieu. Here we show that specific SOD3 re-expression in tumor-associated endothelial cells (ECs) increases doxorubicin (Doxo) delivery into and chemotherapeutic effect on tumors. Enhanced SOD3 activity fostered perivascular nitric oxide accumulation and reduced vessel leakage by inducing vascular endothelial cadherin (VEC) transcription. SOD3 reduced HIF prolyl hydroxylase domain protein activity, which increased hypoxia-inducible factor-2α (HIF-2α) stability and enhanced its binding to a specific VEC promoter region. EC-specific HIF-2α ablation prevented both the SOD3-mediated increase in VEC transcription and the enhanced Doxo effect. SOD3, VEC, and HIF-2α levels correlated positively in primary colorectal cancers, which suggests a similar interconnection of these proteins in human malignancy.

Notch-regulated miR-223 targets the aryl hydrocarbon receptor pathway and increases cytokine production in macrophages from rheumatoid arthritis patients.

Evidence links aryl hydrocarbon receptor (AHR) activation to rheumatoid arthritis (RA) pathogenesis, although results are inconsistent. AHR agonists inhibit pro-inflammatory cytokine expression in macrophages, pivotal cells in RA aetiopathogenesis, which hints at specific circuits that regulate the AHR pathway in RA macrophages. We compared microRNA (miR) expression in CD14(+) cells from patients with active RA or with osteoarthritis (OA). Seven miR were downregulated and one (miR-223) upregulated in RA compared to OA cells. miR-223 upregulation correlated with reduced Notch3 and Notch effector expression in RA patients. Overexpression of the Notch-induced repressor HEY-1 and co-culture of healthy donor monocytes with Notch ligand-expressing cells showed direct Notch-mediated downregulation of miR-223. Bioinformatics predicted the AHR regulator ARNT (AHR nuclear translocator) as a miR-223 target. Pre-miR-223 overexpression silenced ARNT 3'UTR-driven reporter expression, reduced ARNT (but not AHR) protein levels and prevented AHR/ARNT-mediated inhibition of pro-inflammatory cytokine expression. miR-223 counteracted AHR/ARNT-induced Notch3 upregulation in monocytes. Levels of ARNT and of CYP1B1, an AHR/ARNT signalling effector, were reduced in RA compared to OA synovial tissue, which correlated with miR-223 levels. Our results associate Notch signalling to miR-223 downregulation in RA macrophages, and identify miR-223 as a negative regulator of the AHR/ARNT pathway through ARNT targeting.

CX3CL1 at the crossroad of EGF signals: Relevance for the progression of ERBB2+ breast carcinoma.

Inflammatory mediators can play a dual role in oncogenesis and tumor progression. CX3CL1, a chemokine previously implicated in natural killer cell- and CD8+ T cell-mediated antitumor immune responses, has now been identified as a promoter of ERBB2-expressing breast carcinomas as it cross-activates members of the epidermal growth factor receptor family.

A lovastatin-elicited genetic program inhibits M2 macrophage polarization and enhances T cell infiltration into spontaneous mouse mammary tumors.

Beyond their ability to inhibit cholesterol biosynthesis, the statins have pleiotropic effects that include anti-inflammatory and immunomodulatory activities. Statins could have clinical utility, alone or in combination with other chemotherapeutics, in the treatment of cancer. The mechanisms that underlie the anti-tumor activity of the statins are nonetheless poorly defined. No studies have analyzed how they alter the tumor-associated leukocyte infiltrate, a central factor that influences tumor stroma and cancer evolution. Here we used HER2/neu transgenic (Tg-neu) mice to analyze the effect of lovastatin (Lov) on the inflammatory reaction of spontaneous mammary tumors. Lov treatment of tumor-bearing Tg-neu mice did not alter growth of established tumors, but significantly reduced the number of new oncogenic lesions in these mice. Moreover, Lov inhibited the growth of newly implanted Tg-neu tumors in immunocompetent but not in immunodeficient mice. We found that Lov enhanced tumor infiltration by effector T cells, and reduced the number of immunosuppressive and pro-angiogenic M2-like tumor-associated macrophages (TAM). Concomitantly, the drug improved the structure and function of the tumor vasculature, measured as enhanced tumor oxygenation and penetration of cytotoxic drugs. Microarray analysis identified a Lov-elicited genetic program in Tg-neu tumors that might explain these effects; we observed Lov-induced downregulation of placental growth factor, which triggers aberrant angiogenesis and M2-like TAM polarization. Our results identify a role for lovastatin in the shaping and re-education of the inflammatory infiltrate in tumors, with functional consequences in angiogenesis and antitumor immunity.

CX3CL1 promotes breast cancer via transactivation of the EGF pathway.

Chemokines are relevant molecules in shaping the tumor microenvironment, although their contributions to tumorigenesis are not fully understood. We studied the influence of the chemokine CX3CL1/fractalkine in de novo breast cancer formation using HER2/neu transgenic mice. CX3CL1 expression was downmodulated in HER2/neu tumors, yet, paradoxically, adenovirus-mediated CX3CL1 expression in the tumor milieu enhanced mammary tumor numbers in a dose-dependent manner. Increased tumor multiplicity was not a consequence of CX3CL1-induced metastatic dissemination of the primary tumor, although CX3CL1 induced epithelial-to-mesenchymal transition in breast cancer cells in vitro. Instead, CX3CL1 triggered cell proliferation by induction of ErbB receptors through the proteolytic shedding of an ErbB ligand. This effect was important insofar as mammary tumorigenesis was delayed and tumor multiplicity was reduced by genetic deletion of CX3CL1 in HER2/neu mice, but not in polyoma middle T-antigen oncomice. Our findings support the conclusion that CX3CL1 acts as a positive modifier of breast cancer in concert with ErbB receptors.

Aurora kinase B activity is modulated by thyroid hormone during transcriptional activation of pituitary genes.

Covalent histone modifications clearly play an essential role in ligand-dependent transcriptional regulation by nuclear receptors. One of the predominant mechanisms used by nuclear receptors to activate or repress target-gene transcription is the recruitment of coregulatory factors capable of covalently modify the amino terminal ends of histones. Here we show that the thyroid hormone (T3) produces a rapid increase in histone H3Ser10 phosphorylation (H3Ser10ph) concomitant to the rapid displacement of the heterochromatin protein 1ß (HP1ß) to the nuclear periphery. Moreover, we found that T3-mediated pituitary gene transcription is associated with an increase in H3Ser10ph. Interestingly, the Aurora kinase B inhibitor ZM443979 abolishes the effect of T3 on H3Ser10ph, blocks HP1ß delocalization, and significantly reduces ligand-dependent transactivation. Similar effects were shown when Aurora kinase B expression was abrogated in small interfering RNA assays. In an effort to understand the underlying mechanism by which T3 increases H3Ser10ph, we demonstrate that liganded thyroid hormone receptor directly interacts with Aurora kinase B, increasing its kinase activity. Moreover, using chromatin immunoprecipitation assays, we have shown that Aurora kinase B participates of a mechanism that displaces HP1ß from promoter region, thus preparing the chromatin for the transcriptional activation of T3 regulated genes. Our findings reveal a novel role for Aurora kinase B during transcriptional initiation in GO/G1, apart from its well-known mitotic activity.