One of the most striking patterns of genome structure is the tight, typically negative, association between transposable elements (TEs) and meiotic recombination rates. While this is a highly ...recurring feature of eukaryotic genomes, the mechanisms driving correlations between TEs and recombination remain poorly understood, and distinguishing cause versus effect is challenging. Here, we review the evidence for a relation between TEs and recombination, and discuss the underlying evolutionary forces. Evidence to date suggests that overall TE densities correlate negatively with recombination, but the strength of this correlation varies across element types, and the pattern can be reversed. Results suggest that heterogeneity in the strength of selection against ectopic recombination and gene disruption can drive TE accumulation in regions of low recombination, but there is also strong evidence that the regulation of TEs can influence local recombination rates. We hypothesize that TE insertion polymorphism may be important in driving within-species variation in recombination rates in surrounding genomic regions. Furthermore, the interaction between TEs and recombination may create positive feedback, whereby TE accumulation in non-recombining regions contributes to the spread of recombination suppression. Further investigation of the coevolution between recombination and TEs has important implications for our understanding of the evolution of recombination rates and genome structure.
This article is part of the themed issue ‘Evolutionary causes and consequences of recombination rate variation in sexual organisms’.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Transposable elements (TEs) make up a significant portion of eukaryotic genomes and are important drivers of genome evolution. However, the extent to which TEs affect gene expression variation on a ...genome-wide scale in comparison with other types of variants is still unclear. We characterized TE insertion polymorphisms and their association with gene expression in 124 whole-genome sequences from a single population of Capsella grandiflora, and contrasted this with the effects of single nucleotide polymorphisms (SNPs). Population frequency of insertions was negatively correlated with distance to genes, as well as density of conserved noncoding elements, suggesting that the negative effects of TEs on gene regulation are important in limiting their abundance. Rare TE variants strongly influence gene expression variation, predominantly through downregulation. In contrast, rare SNPs contribute equally to up- and down-regulation, but have a weaker individual effect than TEs. An expression quantitative trait loci (eQTL) analysis shows that a greater proportion of common TEs are eQTLs as opposed to common SNPs, and a third of the genes with TE eQTLs do not have SNP eQTLs. In contrast with rare TE insertions, common insertions are more likely to increase expression, consistent with recent models of cis-regulatory evolution favoring enhancer alleles. Taken together, these results imply that TEs are a significant contributor to gene expression variation and are individually more likely than rare SNPs to cause extreme changes in gene expression.
Coevolution between transposable elements and recombination Kent, Tyler V.; Uzunović, Jasmina; Wright, Stephen I.
Philosophical transactions of the Royal Society of London. Series B. Biological sciences,
12/2017, Volume:
372, Issue:
1736
Journal Article
Peer reviewed
One of the most striking patterns of genome structure is the tight, typically negative, association between transposable elements (TEs) and meiotic recombination rates. While this is a highly ...recurring feature of eukaryotic genomes, the mechanisms driving correlations between TEs and recombination remain poorly understood, and distinguishing cause versus effect is challenging. Here, we review the evidence for a relation between TEs and recombination, and discuss the underlying evolutionary forces. Evidence to date suggests that overall TE densities correlate negatively with recombination, but the strength of this correlation varies across element types, and the pattern can be reversed. Results suggest that heterogeneity in the strength of selection against ectopic recombination and gene disruption can drive TE accumulation in regions of low recombination, but there is also strong evidence that the regulation of TEs can influence local recombination rates. We hypothesize that TE insertion polymorphism may be important in driving within-species variation in recombination rates in surrounding genomic regions. Furthermore, the interaction between TEs and recombination may create positive feedback, whereby accumulation in non-recombining regions contributes to the spread of recombination suppression. Further investigation of the coevolution between recombination and TEs has important implications for our understanding of the evolution of recombination rates and genome structure. This article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Co-lead authors: Habib Hamidi and Patrick Kimes Background: Standard induction therapy cures ~60% of patients (pts) with DLBCL; however, most remaining non-responders die from lymphoma, highlighting ...a need for improved first-line treatments. Biomarkers that can reliably assess the efficacy of new treatments are lacking in clinical practice. Mosunetuzumab (Mosun) is a CD20xCD3 T cell engaging bispecific antibody that redirects T cells to eliminate malignant B cells. In a Phase Ib/II trial (NCT03677141), Mosun combined with CHOP chemotherapy (M-CHOP) induced high response rates in pts with 1L DLBCL (ORR 87.5%, CR 85%; Phillips et al. ASH 2020). Here, we sought to identify biomarkers associated with M-CHOP response. Methods: Pts with 1L DLBCL receiving M-CHOP (six cycles) in NCT03677141 and with available biomarker data were included. Bulk RNASeq data from pre-treatment tumor biopsies were analyzed using gene set variation for tumor intrinsic pathways and xCell cell-type enrichment for immune and stromal cell types. High or low expression of each gene signature was determined by median cut-off. Cox regression examined associations between gene signatures and PFS. To assess specificity to M-CHOP, gene signatures were examined in pre-treatment biopsies from pts treated with rituximab + CHOP chemotherapy (R-CHOP) in GOYA (NCT01287741; Sehn et al. J Hematol Oncol 2020). Peripheral blood biomarkers were evaluated by whole blood flow cytometry and plasma cytokines by ELISA. Circulating tumor (ct) DNA levels were measured at baseline and on treatment using the AVENIO NHL CAPP-Seq assay (Stokowski et al. ASH 2022). Results: In M-CHOP-treated pts (n=33), gene expression analysis revealed two types of signatures associated with PFS: tumor immune microenvironment signature (TIMS) and tumor intrinsic proliferation signature (TIPS; Figure). High TIMS expression (e.g., CD4+ T cells) was associated with significantly longer PFS than low expression. Conversely, pts with high TIPS expression (e.g., MYC targets, DNA repair) had shorter PFS than those with low expression. These biological associations were specific to M-CHOP and were not observed in R-CHOP-treated pts. Consistent with the tumor-gene expression analysis, immune profiling of peripheral blood suggested that in pts treated with M-CHOP, a higher T cell baseline count was associated with a trend for prolonged PFS compared with pts with a lower baseline count. A higher count of circulating suppressive T cells was also associated with shortened PFS. Early on-treatment pharmacodynamic (PD) changes were observed following the first Mosun dose, including: induction of TNFα and IL-6, transient margination of CD4+ and CD8+ T cells, and activation of CD4+ and CD8+ T cells. The magnitude of the PD effects were similar to observations with Mosun monotherapy in pts with relapsed or refractory DLBCL (Hernandez et al. ASH 2019), confirming that Mosun maintains its immune activation effect when combined with CHOP in pts with 1L DLBCL. High baseline ctDNA levels were associated with high IPI score (n=32, Wilcoxon rank-sum p=0.007), ABC/non-GCB DLBCL subtype (n=30, p=0.033), and high lactate dehydrogenase (n=32, p=0.004). Pts with baseline ctDNA levels < median had a modest trend for improved PFS compared with pts > median (unadjusted hazard ratio HR=0.57 95% CI 0.16, 1.75; IPI-adjusted HR=0.72 95% CI 0.16, 3.20). The proportion of pts with undetectable ctDNA increased with each M-CHOP cycle (C) (C2 day D1, 25% 8/32; C3D1, 69% 20/29; C5D1, 88% 22/25). Pts with undetectable ctDNA at any on-treatment time point (C2D1, C3D1, C5D1) had superior PFS compared with pts with detectable ctDNA (unadjusted HR=0.12 95% CI 0.03, 0.52; IPI adjusted HR=0.14 95% CI 0.03, 0.61). Conclusions: Consistent with the Mosun mode of action, pts with high expression of TIMS and those with high levels of circulating T cells had improved PFS versus pts with low expression. In contrast, there was no association between immune cell signatures and PFS in pts treated with R-CHOP, suggesting that the different mode of action of rituximab versus Mosun may influence this. Future studies are warranted to confirm the potential clinical utility of immune cell signatures as biomarkers associated with CD20xCD3 bispecifics' activity.
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NUK, OILJ, SAZU, SBCE, UL, UM, UPCLJ, UPUK
Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals ...of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
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•GBMI is a collaborative network of 24 biobanks with >2.2 M individuals•GWASs in different biobanks worldwide can be successfully integrated•Biobank meta-analyses identified 317 known and 183 novel loci for 14 endpoints•GBMI publicly releases summary statistics of biobank meta-analyses
Zhou et al. present the flagship project of the Global Biobank Meta-analysis Initiative (GBMI). They demonstrate the substantial benefits of the collaborative efforts of 23 biobanks worldwide to advance genetic discoveries for human diseases with larger sample sizes and increased ancestry diversity and highlight issues and challenges in biobank meta-analyses.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Transposable elements (TEs) make up a significant portion of eukaryotic genomes, and thus are important drivers of genome evolution. The forces controlling TE copy number and the extent to which TEs ...affect phenotypic variation genome-wide are still unclear. I characterised TE insertion polymorphism in 124 whole genome sequences from a single population of Capsella grandiflora . The frequency of insertions is negatively correlated with distance to genes, as well as density of non-coding conserved elements, suggesting that the negative effects of TEs on gene regulation are important in limiting their spread throughout the population. Rare TE variants strongly influence gene expression variation, predominantly through downregulation. Contrarily, rare single nucleotide polymorphisms (SNPs) contribute equally to upregulation and downregulation, but have a weaker overall effect. Taken together, these results imply that TEs contribute significantly to gene expression variation and can be more likely than rare SNPs to cause extreme changes in gene expression.
The goal was to identify microbial drivers of IBD, by investigating mucosal-associated bacteria and their detrimental products in IBD patients.
We directly cultured bacterial communities from mucosal ...biopsies from pediatric gastrointestinal patients and examined for pathogenicity-associated traits. Upon identifying C. perfringens as toxigenic bacteria present in mucosal biopsies, we isolated strains and further characterized toxicity and prevalence.
Mucosal biopsy microbial composition differed from corresponding stool samples. C. perfringens was present in 8 of 9 patients' mucosal biopsies, correlating with hemolytic activity, while not in all corresponding stool samples. Large IBD datasets showed higher C. perfringens prevalence in stool samples of IBD adults (18.7-27.1%) versus healthy (5.1%). In vitro, C. perfringens supernatants were toxic to cell types beneath the intestinal epithelial barrier, including endothelial, neuroblasts, and neutrophils, while impact on epithelial cells was less pronounced, suggesting C. perfringens may be damaging particularly when barrier integrity is compromised. Further characterization using purified toxins and genetic insertion mutants confirmed PFO toxin was sufficient for toxicity. Toxin RNA signatures were found in the original patient biopsies by PCR, suggesting intestinal production. C. perfringens supernatants also induced activation of neuroblast and dorsal root ganglion neurons in vitro, suggesting C. perfringens in inflamed mucosal tissue may directly contribute to abdominal pain, a frequent IBD symptom.
Gastrointestinal carriage of certain toxigenic C. perfringens may have an important pathogenic impact on IBD patients. These findings support routine monitoring of C. perfringens and PFO toxins and potential treatment in patients.
Meta-analysis is pervasively used to combine multiple genome-wide association studies (GWASs). Fine-mapping of meta-analysis studies is typically performed as in a single-cohort study. Here, we first ...demonstrate that heterogeneity (e.g., of sample size, phenotyping, imputation) hurts calibration of meta-analysis fine-mapping. We propose a summary statistics-based quality-control (QC) method, suspicious loci analysis of meta-analysis summary statistics (SLALOM), that identifies suspicious loci for meta-analysis fine-mapping by detecting outliers in association statistics. We validate SLALOM in simulations and the GWAS Catalog. Applying SLALOM to 14 meta-analyses from the Global Biobank Meta-analysis Initiative (GBMI), we find that 67% of loci show suspicious patterns that call into question fine-mapping accuracy. These predicted suspicious loci are significantly depleted for having nonsynonymous variants as lead variant (2.7×; Fisher’s exact p = 7.3 × 10−4). We find limited evidence of fine-mapping improvement in the GBMI meta-analyses compared with individual biobanks. We urge extreme caution when interpreting fine-mapping results from meta-analysis of heterogeneous cohorts.
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•Extensive simulation of meta-analyses to show substantial fine-mapping miscalibration•SLALOM, a novel method that identifies suspicious loci for meta-analysis fine-mapping•Significant depletion of likely causal variants in SLALOM-predicted suspicious loci•Widespread suspicious loci for fine-mapping in current meta-analysis summary statistics
Genome-wide associations studies (GWASs), often performed as meta-analyses, have identified tens of thousands of disease-associated loci. Kanai et al. demonstrate via large-scale simulations and real data analysis that standard tools for pinpointing the causal variants underlying these associations can produce unreliable results when applied to GWAS meta-analyses.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Polygenic risk scores (PRSs) have been widely explored in precision medicine. However, few studies have thoroughly investigated their best practices in global populations across different diseases. ...We here utilized data from Global Biobank Meta-analysis Initiative (GBMI) to explore methodological considerations and PRS performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRSs using pruning and thresholding (P + T) and PRS-continuous shrinkage (CS). For both methods, using a European-based linkage disequilibrium (LD) reference panel resulted in comparable or higher prediction accuracy compared with several other non-European-based panels. PRS-CS overall outperformed the classic P + T method, especially for endpoints with higher SNP-based heritability. Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma, which has known variation in disease prevalence across populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using GBMI resources and highlight the importance of best practices for PRS in the biobank-scale genomics era.
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•PRS accuracy is heterogeneous across disease endpoints, ancestries, and biobanks•Larger sample sizes and greater diversity of GBMI improves PRS accuracy•Lessons and guidelines for developing PRS with multi-ancestry GWASs are provided
Wang et al. used the unique resource from Global Biobank Meta-analysis Initiative to develop and evaluate PRSs for 14 disease endpoints with varying genetic architectures and prevalences. They developed guidelines regarding the effects of multi-ancestry and heterogeneous GWASs, trait-specific genetic architecture, and PRS methods on prediction performance across diverse populations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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