| 1. |
- Bocher, Ozvan, et al.
(författare)
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Testing for association with rare variants in the coding and non-coding genome : RAVA-FIRST, a new approach based on CADD deleteriousness score
- 2022
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 18:9, s. e1009923-
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Tidskriftsartikel (refereegranskat)abstract
- Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: "RAVA-FIRST" (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the gnomAD populations, which are referred to as "CADD regions". (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.
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| 2. |
- Eisfeldt, J., et al.
(författare)
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Comprehensive structural variation genome map of individuals carrying complex chromosomal rearrangements
- 2019
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Ingår i: PLOS Genetics. - : NLM (Medline). - 1553-7390 .- 1553-7404. ; 15:2
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Tidskriftsartikel (refereegranskat)abstract
- Complex chromosomal rearrangements (CCRs) are rearrangements involving more than two chromosomes or more than two breakpoints. Whole genome sequencing (WGS) allows for outstanding high resolution characterization on the nucleotide level in unique sequences of such rearrangements, but problems remain for mapping breakpoints in repetitive regions of the genome, which are known to be prone to rearrangements. Hence, multiple complementary WGS experiments are sometimes needed to solve the structures of CCRs. We have studied three individuals with CCRs: Case 1 and Case 2 presented with de novo karyotypically balanced, complex interchromosomal rearrangements (46,XX,t(2;8;15)(q35;q24.1;q22) and 46,XY,t(1;10;5)(q32;p12;q31)), and Case 3 presented with a de novo, extremely complex intrachromosomal rearrangement on chromosome 1. Molecular cytogenetic investigation revealed cryptic deletions in the breakpoints of chromosome 2 and 8 in Case 1, and on chromosome 10 in Case 2, explaining their clinical symptoms. In Case 3, 26 breakpoints were identified using WGS, disrupting five known disease genes. All rearrangements were subsequently analyzed using optical maps, linked-read WGS, and short-read WGS. In conclusion, we present a case series of three unique de novo CCRs where we by combining the results from the different technologies fully solved the structure of each rearrangement. The power in combining short-read WGS with long-molecule sequencing or optical mapping in these unique de novo CCRs in a clinical setting is demonstrated.
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| 3. |
- Flynn, E. D., et al.
(författare)
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Transcription factor regulation of eQTL activity across individuals and tissues
- 2022
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 18:1, s. e1009719-
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Tidskriftsartikel (refereegranskat)abstract
- Tens of thousands of genetic variants associated with gene expression (cis-eQTLs) have been discovered in the human population. These eQTLs are active in various tissues and contexts, but the molecular mechanisms of eQTL variability are poorly understood, hindering our understanding of genetic regulation across biological contexts. Since many eQTLs are believed to act by altering transcription factor (TF) binding affinity, we hypothesized that analyzing eQTL effect size as a function of TF level may allow discovery of mechanisms of eQTL variability. Using GTEx Consortium eQTL data from 49 tissues, we analyzed the interaction between eQTL effect size and TF level across tissues and across individuals within specific tissues and generated a list of 10,098 TF-eQTL interactions across 2,136 genes that are supported by at least two lines of evidence. These TF-eQTLs were enriched for various TF binding measures, supporting with orthogonal evidence that these eQTLs are regulated by the implicated TFs. We also found that our TF-eQTLs tend to overlap genes with gene-by-environment regulatory effects and to colocalize with GWAS loci, implying that our approach can help to elucidate mechanisms of context-specificity and trait associations. Finally, we highlight an interesting example of IKZF1 TF regulation of an APBB1IP gene eQTL that colocalizes with a GWAS signal for blood cell traits. Together, our findings provide candidate TF mechanisms for a large number of eQTLs and offer a generalizable approach for researchers to discover TF regulators of genetic variant effects in additional QTL datasets.
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| 4. |
- Frånberg, Mattias, 1985-, et al.
(författare)
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Discovering Genetic Interactions in Large-Scale Association Studies by Stage-wise Likelihood Ratio Tests
- 2015
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 11:9
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Tidskriftsartikel (refereegranskat)abstract
- Despite the success of genome-wide association studies in medical genetics, the underlying genetics of many complex diseases remains enigmatic. One plausible reason for this could be the failure to account for the presence of genetic interactions in current analyses. Exhaustive investigations of interactions are typically infeasible because the vast number of possible interactions impose hard statistical and computational challenges. There is, therefore, a need for computationally efficient methods that build on models appropriately capturing interaction. We introduce a new methodology where we augment the interaction hypothesis with a set of simpler hypotheses that are tested, in order of their complexity, against a saturated alternative hypothesis representing interaction. This sequential testing provides an efficient way to reduce the number of non-interacting variant pairs before the final interaction test. We devise two different methods, one that relies on a priori estimated numbers of marginally associated variants to correct for multiple tests, and a second that does this adaptively. We show that our methodology in general has an improved statistical power in comparison to seven other methods, and, using the idea of closed testing, that it controls the family-wise error rate. We apply our methodology to genetic data from the PRO-CARDIS coronary artery disease case/control cohort and discover three distinct interactions. While analyses on simulated data suggest that the statistical power may suffice for an exhaustive search of all variant pairs in ideal cases, we explore strategies for a priori selecting subsets of variant pairs to test. Our new methodology facilitates identification of new disease-relevant interactions from existing and future genome-wide association data, which may involve genes with previously unknown association to the disease. Moreover, it enables construction of interaction networks that provide a systems biology view of complex diseases, serving as a basis for more comprehensive understanding of disease pathophysiology and its clinical consequences.
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| 5. |
- Gifford, Danna R., et al.
(författare)
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Mutators can drive the evolution of multi-resistance to antibiotics
- 2023
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 19:6
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Tidskriftsartikel (refereegranskat)abstract
- Antibiotic combination therapies are an approach used to counter the evolution of resistance; their purported benefit is they can stop the successive emergence of independent resistance mutations in the same genome. Here, we show that bacterial populations with ‘mutators’, organisms with defects in DNA repair, readily evolve resistance to combination antibiotic treatment when there is a delay in reaching inhibitory concentrations of antibiotic—under conditions where purely wild-type populations cannot. In populations of Escherichia coli subjected to combination treatment, we detected a diverse array of acquired mutations, including multiple alleles in the canonical targets of resistance for the two drugs, as well as mutations in multi-drug efflux pumps and genes involved in DNA replication and repair. Unexpectedly, mutators not only allowed multi-resistance to evolve under combination treatment where it was favoured, but also under single-drug treatments. Using simulations, we show that the increase in mutation rate of the two canonical resistance targets is sufficient to permit multi-resistance evolution in both single-drug and combination treatments. Under both conditions, the mutator allele swept to fixation through hitch-hiking with single-drug resistance, enabling subsequent resistance mutations to emerge. Ultimately, our results suggest that mutators may hinder the utility of combination therapy when mutators are present. Additionally, by raising the rates of genetic mutation, selection for multi-resistance may have the unwanted side-effect of increasing the potential to evolve resistance to future antibiotic treatments.
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| 6. |
- Jiang, Rays H. Y., et al.
(författare)
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Distinctive Expansion of Potential Virulence Genes in the Genome of the Oomycete Fish Pathogen Saprolegnia parasitica
- 2013
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Ingår i: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 9:6, s. e1003272-
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Tidskriftsartikel (refereegranskat)abstract
- Oomycetes in the class Saprolegniomycetidae of the Eukaryotic kingdom Stramenopila have evolved as severe pathogens of amphibians, crustaceans, fish and insects, resulting in major losses in aquaculture and damage to aquatic ecosystems. We have sequenced the 63 Mb genome of the fresh water fish pathogen, Saprolegnia parasitica. Approximately 1/3 of the assembled genome exhibits loss of heterozygosity, indicating an efficient mechanism for revealing new variation. Comparison of S. parasitica with plant pathogenic oomycetes suggests that during evolution the host cellular environment has driven distinct patterns of gene expansion and loss in the genomes of plant and animal pathogens. S. parasitica possesses one of the largest repertoires of proteases (270) among eukaryotes that are deployed in waves at different points during infection as determined from RNA-Seq data. In contrast, despite being capable of living saprotrophically, parasitism has led to loss of inorganic nitrogen and sulfur assimilation pathways, strikingly similar to losses in obligate plant pathogenic oomycetes and fungi. The large gene families that are hallmarks of plant pathogenic oomycetes such as Phytophthora appear to be lacking in S. parasitica, including those encoding RXLR effectors, Crinkler's, and Necrosis Inducing-Like Proteins (NLP). S. parasitica also has a very large kinome of 543 kinases, 10% of which is induced upon infection. Moreover, S. parasitica encodes several genes typical of animals or animal-pathogens and lacking from other oomycetes, including disintegrins and galactose-binding lectins, whose expression and evolutionary origins implicate horizontal gene transfer in the evolution of animal pathogenesis in S. parasitica.
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| 7. |
- Lindholm, Malene E., et al.
(författare)
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The Impact of Endurance Training on Human Skeletal Muscle Memory, Global Isoform Expression and Novel Transcripts
- 2016
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Ingår i: PLOS Genetics. - : Public Library of Science. - 1553-7390 .- 1553-7404. ; 12:9
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Tidskriftsartikel (refereegranskat)abstract
- Regularly performed endurance training has many beneficial effects on health and skeletal muscle function, and can be used to prevent and treat common diseases e.g. cardiovascular disease, type II diabetes and obesity. The molecular adaptation mechanisms regulating these effects are incompletely understood. To date, global transcriptome changes in skeletal muscles have been studied at the gene level only. Therefore, global isoform expression changes following exercise training in humans are unknown. Also, the effects of repeated interventions on transcriptional memory or training response have not been studied before. In this study, 23 individuals trained one leg for three months. Nine months later, 12 of the same subjects trained both legs in a second training period. Skeletal muscle biopsies were obtained from both legs before and after both training periods. RNA sequencing analysis of all 119 skeletal muscle biopsies showed that training altered the expression of 3,404 gene isoforms, mainly associated with oxidative ATP production. Fifty-four genes had isoforms that changed in opposite directions. Training altered expression of 34 novel transcripts, all with protein-coding potential. After nine months of detraining, no training-induced transcriptome differences were detected between the previously trained and untrained legs. Although there were several differences in the physiological and transcriptional responses to repeated training, no coherent evidence of an endurance training induced transcriptional skeletal muscle memory was found. This human lifestyle intervention induced differential expression of thousands of isoforms and several transcripts from unannotated regions of the genome. It is likely that the observed isoform expression changes reflect adaptational mechanisms and processes that provide the functional and health benefits of regular physical activity.
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| 8. |
- Nazaryan-Petersen, Lusine, et al.
(författare)
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Replicative and non-replicative mechanisms in the formation of clustered CNVs are indicated by whole genome characterization
- 2018
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Ingår i: PLOS Genetics. - : Public Library of Science. - 1553-7390 .- 1553-7404. ; 14:11
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Tidskriftsartikel (refereegranskat)abstract
- Clustered copy number variants (CNVs) as detected by chromosomal microarray analysis (CMA) are often reported as germline chromothripsis. However, such cases might need further investigations by massive parallel whole genome sequencing (WGS) in order to accurately define the underlying complex rearrangement, predict the occurrence mechanisms and identify additional complexities. Here, we utilized WGS to delineate the rearrangement structure of 21 clustered CNV carriers first investigated by CMA and identified a total of 83 breakpoint junctions (BPJs). The rearrangements were further sub-classified depending on the patterns observed: I) Cases with only deletions (n = 8) often had additional structural rearrangements, such as insertions and inversions typical to chromothripsis; II) cases with only duplications (n = 7) or III) combinations of deletions and duplications (n = 6) demonstrated mostly interspersed duplications and BPJs enriched with microhomology. In two cases the rearrangement mutational signatures indicated both a breakage-fusion-bridge cycle process and haltered formation of a ring chromosome. Finally, we observed two cases with Alu- and LINE-mediated rearrangements as well as two unrelated individuals with seemingly identical clustered CNVs on 2p25.3, possibly a rare European founder rearrangement. In conclusion, through detailed characterization of the derivative chromosomes we show that multiple mechanisms are likely involved in the formation of clustered CNVs and add further evidence for chromoanagenesis mechanisms in both "simple" and highly complex chromosomal rearrangements. Finally, WGS characterization adds positional information, important for a correct clinical interpretation and deciphering mechanisms involved in the formation of these rearrangements.
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| 9. |
- Skwark, Marcin J., et al.
(författare)
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Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis
- 2017
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Ingår i: PLOS Genetics. - : PUBLIC LIBRARY SCIENCE. - 1553-7390 .- 1553-7404. ; 13:2
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Tidskriftsartikel (refereegranskat)abstract
- Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein- protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work.
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