1. |
- Aguet, Francois, et al.
(author)
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Molecular quantitative trait loci
- 2023
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In: NATURE REVIEWS METHODS PRIMERS. - : Springer Nature. - 2662-8449. ; 3:1
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Journal article (peer-reviewed)abstract
- Understanding functional effects of genetic variants is one of the key challenges in human genetics, as much of disease-associated variation is located in non-coding regions with typically unknown putative gene regulatory effects. One of the most important approaches in this field has been molecular quantitative trait locus (molQTL) mapping, where genetic variation is associated with molecular traits that can be measured at scale, such as gene expression, splicing and chromatin accessibility. The maturity of the field and large-scale studies have produced a rich set of established methods for molQTL analysis, with novel technologies opening up new areas of discovery. In this Primer, we discuss the study design, input data and statistical methods for molQTL mapping and outline the properties of the resulting data as well as popular downstream applications. We review both the limitations and caveats of molQTL mapping as well as future potential approaches to tackle them. With technological development now providing many complementary methods for functional characterization of genetic variants, we anticipate that molQTLs will remain an important part of this toolkit as the only existing approach that can measure human variation in its native genomic, cellular and tissue context.
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2. |
- Brown, Brielin C., et al.
(author)
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Multiset correlation and factor analysis enables exploration of multi-omics data
- 2023
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In: Cell Genomics. - : Elsevier BV. - 2666-979X. ; 3:8, s. 100359-
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Journal article (peer-reviewed)abstract
- Multi-omics datasets are becoming more common, necessitating better integration methods to realize their revolutionary potential. Here, we introduce multi-set correlation and factor analysis (MCFA), an unsupervised integration method tailored to the unique challenges of high-dimensional genomics data that enables fast inference of shared and private factors. We used MCFA to integrate methylation markers, protein expression, RNA expression, and metabolite levels in 614 diverse samples from the Trans-Omics for Precision Medicine/Multi-Ethnic Study of Atherosclerosis multi-omics pilot. Samples cluster strongly by ancestry in the shared space, even in the absence of genetic information, while private spaces frequently capture dataset-specific technical variation. Finally, we integrated genetic data by conducting a genome-wide association study (GWAS) of our inferred factors, observing that several factors are enriched for GWAS hits and trans-expression quantitative trait loci. Two of these factors appear to be related to metabolic disease. Our study provides a foundation and framework for further integrative analysis of ever larger multi-modal genomic datasets.
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3. |
- Buschur, Kristina L., et al.
(author)
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Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis
- 2023
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In: Respiratory Research. - : Springer Nature. - 1465-9921 .- 1465-993X. ; 24:1
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Journal article (peer-reviewed)abstract
- BackgroundChronic obstructive pulmonary disease (COPD) varies significantly in symptomatic and physiologic presentation. Identifying disease subtypes from molecular data, collected from easily accessible blood samples, can help stratify patients and guide disease management and treatment.MethodsBlood gene expression measured by RNA-sequencing in the COPDGene Study was analyzed using a network perturbation analysis method. Each COPD sample was compared against a learned reference gene network to determine the part that is deregulated. Gene deregulation values were used to cluster the disease samples.ResultsThe discovery set included 617 former smokers from COPDGene. Four distinct gene network subtypes are identified with significant differences in symptoms, exercise capacity and mortality. These clusters do not necessarily correspond with the levels of lung function impairment and are independently validated in two external cohorts: 769 former smokers from COPDGene and 431 former smokers in the Multi-Ethnic Study of Atherosclerosis (MESA). Additionally, we identify several genes that are significantly deregulated across these subtypes, including DSP and GSTM1, which have been previously associated with COPD through genome-wide association study (GWAS).ConclusionsThe identified subtypes differ in mortality and in their clinical and functional characteristics, underlining the need for multi-dimensional assessment potentially supplemented by selected markers of gene expression. The subtypes were consistent across cohorts and could be used for new patient stratification and disease prognosis.
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4. |
- Buschur, Kristina L., et al.
(author)
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Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease
- 2024
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In: Annals of the American Thoracic Society. - : American Thoracic Society. - 2329-6933 .- 2325-6621. ; 21:6, s. 884-894
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Journal article (peer-reviewed)abstract
- Rationale: Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. The molecular mechanisms underlying these changes are poorly understood in patients, in part because of the inaccessibility of the pulmonary vasculature. Peripheral blood mononuclear cells (PBMCs) interact with the pulmonary endothelium. Objectives: To test the association between gene expression in PBMCs and pulmonary microvascular perfusion in COPD. Methods: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited two independent samples of COPD cases and controls with ⩾10 pack-years of smoking history. In both samples, pulmonary microvascular blood flow, pulmonary microvascular blood volume, and mean transit time were assessed on contrast-enhanced magnetic resonance imaging, and PBMC gene expression was assessed by microarray. Additional replication was performed in a third sample with pulmonary microvascular blood volume measures on contrast-enhanced dual-energy computed tomography. Differential expression analyses were adjusted for age, gender, race/ethnicity, educational attainment, height, weight, smoking status, and pack-years of smoking. Results: The 79 participants in the discovery sample had a mean age of 69 ± 6 years, 44% were female, 25% were non-White, 34% were current smokers, and 66% had COPD. There were large PBMC gene expression signatures associated with pulmonary microvascular perfusion traits, with several replicated in the replication sets with magnetic resonance imaging (n = 47) or dual-energy contrast-enhanced computed tomography (n = 157) measures. Many of the identified genes are involved in inflammatory processes, including nuclear factor-κB and chemokine signaling pathways. Conclusions: PBMC gene expression in nuclear factor-κB, inflammatory, and chemokine signaling pathways was associated with pulmonary microvascular perfusion in COPD, potentially offering new targetable candidates for novel therapies.
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5. |
- Einson, Jonah, et al.
(author)
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Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants
- 2023
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In: Genetics. - : Oxford University Press (OUP). - 0016-6731 .- 1943-2631. ; 224:4
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Journal article (peer-reviewed)abstract
- Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.
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6. |
- Einson, Jonah, et al.
(author)
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The impact of genetically controlled splicing on exon inclusion and protein structure
- 2024
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 19:3 March
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Journal article (peer-reviewed)abstract
- Common variants affecting mRNA splicing are typically identified though splicing quantitative trait locus (sQTL) mapping and have been shown to be enriched for GWAS signals by a similar degree to eQTLs. However, the specific splicing changes induced by these variants have been difficult to characterize, making it more complicated to analyze the effect size and direction of sQTLs, and to determine downstream splicing effects on protein structure. In this study, we catalogue sQTLs using exon percent spliced in (PSI) scores as a quantitative phenotype. PSI is an interpretable metric for identifying exon skipping events and has some advantages over other methods for quantifying splicing from short read RNA sequencing. In our set of sQTL variants, we find evidence of selective effects based on splicing effect size and effect direction, as well as exon symmetry. Additionally, we utilize AlphaFold2 to predict changes in protein structure associated with sQTLs overlapping GWAS traits, highlighting a potential new use-case for this technology for interpreting genetic effects on traits and disorders.
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7. |
- Ferreira, Pedro G., et al.
(author)
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Sequence variation between 462 human individuals fine-tunes functional sites of RNA processing
- 2016
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6
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Journal article (peer-reviewed)abstract
- Recent advances in the cost-efficiency of sequencing technologies enabled the combined DNA-and RNA-sequencing of human individuals at the population-scale, making genome-wide investigations of the inter-individual genetic impact on gene expression viable. Employing mRNA-sequencing data from the Geuvadis Project and genome sequencing data from the 1000 Genomes Project we show that the computational analysis of DNA sequences around splice sites and poly-A signals is able to explain several observations in the phenotype data. In contrast to widespread assessments of statistically significant associations between DNA polymorphisms and quantitative traits, we developed a computational tool to pinpoint the molecular mechanisms by which genetic markers drive variation in RNA-processing, cataloguing and classifying alleles that change the affinity of core RNA elements to their recognizing factors. The in silico models we employ further suggest RNA editing can moonlight as a splicing-modulator, albeit less frequently than genomic sequence diversity. Beyond existing annotations, we demonstrate that the ultra-high resolution of RNA-Seq combined from 462 individuals also provides evidence for thousands of bona fide novel elements of RNA processing-alternative splice sites, introns, and cleavage sites-which are often rare and lowly expressed but in other characteristics similar to their annotated counterparts.
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8. |
- Flynn, Elise D., et al.
(author)
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Functional Characterization of Genetic Variant Effects on Expression
- 2022
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In: Annual Review of Biomedical Data Science. - : Annual Reviews. - 2574-3414. ; 5, s. 119-139
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Journal article (peer-reviewed)abstract
- Thousands of common genetic variants in the human population have been associated with disease risk and phenotypic variation by genome-wide association studies (GWAS). However, the majority of GWAS variants fall into noncoding regions of the genome, complicating our understanding of their regulatory functions, and few molecular mechanisms of GWAS variant effects have been clearly elucidated. Here, we set out to review genetic variant effects, focusing on expression quantitative trait loci (eQTLs), including their utility in interpreting GWAS variant mechanisms. We discuss the interrelated challenges and opportunities for eQTL analysis, covering determining causal variants, elucidating molecular mechanisms of action, and understanding context variability. Addressing these questions can enable better functional characterization of disease-associated loci and provide insights into fundamental biological questions of the noncoding genetic regulatory code and its control of gene expression.
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9. |
- Flynn, E. D., et al.
(author)
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Transcription factor regulation of eQTL activity across individuals and tissues
- 2022
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In: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 18:1, s. e1009719-
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Journal article (peer-reviewed)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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10. |
- George, Sophia H.L., et al.
(author)
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Increasing diversity of functional genetics studies to advance biological discovery and human health
- 2023
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In: American Journal of Human Genetics. - : Cell Press. - 0002-9297 .- 1537-6605. ; 110:12, s. 1996-2002
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Research review (peer-reviewed)abstract
- In this perspective we discuss the current lack of genetic and environmental diversity in functional genomics datasets. There is a well-described Eurocentric bias in genetic and functional genomic research that has a clear impact on the benefit this research can bring to underrepresented populations. Current research focused on genetic variant-to-function experiments aims to identify molecular QTLs, but the lack of data from genetically diverse individuals has limited analyses to mostly populations of European ancestry. Although some efforts have been established to increase diversity in functional genomic studies, much remains to be done to consistently generate data for underrepresented populations from now on. We discuss the major barriers for this continuity and suggest actionable insights, aiming to empower research and researchers from underserved populations.
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11. |
- Glinos, Dafni A., et al.
(author)
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Transcriptome variation in human tissues revealed by long-read sequencing
- 2022
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In: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 608:7922, s. 353-359
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Journal article (peer-reviewed)abstract
- Regulation of transcript structure generates transcript diversity and plays an important role in human disease(1-7). The advent oflong-read sequencing technologies offers the opportunity to study the role of genetic variation in transcript structure(8-)(16). In this Article, we present a large human long-read RNA-seq dataset using the Oxford Nanopore Technologies platform from 88 samples from Genotype-Tissue Expression (GTEx) tissues and cell lines, complementing the GTEx resource. We identified just over 70,000 novel transcripts for annotated genes, and validated the protein expression of 10% of novel transcripts. We developed a new computational package, LORALS, to analyse the genetic effects of rare and common variants on the transcriptome by allele-specific analysis of long reads. We characterized allele-specific expression and transcript structure events, providing new insights into the specific transcript alterations caused by common and rare genetic variants and highlighting the resolution gained from long-read data. We were able to perturb the transcript structure upon knockdown of PTBP1, an RNA binding protein that mediates splicing, thereby finding genetic regulatory effects that are modified by the cellular environment. Finally, we used this dataset to enhance variant interpretation and study rare variants leading to aberrant splicing patterns.
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12. |
- Greger, Liliana, et al.
(author)
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Tandem RNA chimeras contribute to transcriptome diversity in human population and are associated with intronic genetic variants.
- 2014
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In: PloS one. - : Public Library of Science (PLoS). - 1932-6203. ; 9:8, s. e104567-
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Journal article (peer-reviewed)abstract
- Chimeric RNAs originating from two or more different genes are known to exist not only in cancer, but also in normal tissues, where they can play a role in human evolution. However, the exact mechanism of their formation is unknown. Here, we use RNA sequencing data from 462 healthy individuals representing 5 human populations to systematically identify and in depth characterize 81 RNA tandem chimeric transcripts, 13 of which are novel. We observe that 6 out of these 81 chimeras have been regarded as cancer-specific. Moreover, we show that a prevalence of long introns at the fusion breakpoint is associated with the chimeric transcripts formation. We also find that tandem RNA chimeras have lower abundances as compared to their partner genes. Finally, by combining our results with genomic data from the same individuals we uncover intronic genetic variants associated with the chimeric RNA formation. Taken together our findings provide an important insight into the chimeric transcripts formation and open new avenues of research into the role of intronic genetic variants in post-transcriptional processing events.
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13. |
- Kasela, Silva, et al.
(author)
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Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects
- 2024
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In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 111:1, s. 133-149
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Journal article (peer-reviewed)abstract
- Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.
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14. |
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15. |
- Lappalainen, Tuuli, et al.
(author)
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From variant to function in human disease genetics
- 2021
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In: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 373:6562, s. 1464-1468
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Research review (peer-reviewed)abstract
- Over the next decade, the primary challenge in human genetics will be to understand the biological mechanisms by which genetic variants influence phenotypes, including disease risk. Although the scale of this challenge is daunting, better methods for functional variant interpretation will have transformative consequences for disease diagnosis, risk prediction, and the development of new therapies. An array of new methods for characterizing variant impact at scale, using patient tissue samples as well as in vitro models, are already being applied to dissect variant mechanisms across a range of human cell types and environments. These approaches are also increasingly being deployed in clinical settings. We discuss the rationale, approaches, applications, and future outlook for characterizing the molecular and cellular effects of genetic variants.
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16. |
- Lappalainen, Tuuli, et al.
(author)
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Genetic and molecular architecture of complex traits
- 2024
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In: Cell. - : Elsevier BV. - 0092-8674 .- 1097-4172. ; 187:5, s. 1059-1075
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Research review (peer-reviewed)abstract
- Human genetics has emerged as one of the most dynamic areas of biology, with a broadening societal impact. In this review, we discuss recent achievements, ongoing efforts, and future challenges in the field. Advances in technology, statistical methods, and the growing scale of research efforts have all provided many insights into the processes that have given rise to the current patterns of genetic variation. Vast maps of genetic associations with human traits and diseases have allowed characterization of their genetic architecture. Finally, studies of molecular and cellular effects of genetic variants have provided insights into biological processes underlying disease. Many outstanding questions remain, but the field is well poised for groundbreaking discoveries as it increases the use of genetic data to understand both the history of our species and its applications to improve human health.
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17. |
- Lappalainen, Tuuli, et al.
(author)
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Genomic landscape of positive natural selection in Northern European populations.
- 2010
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In: European Journal of Human Genetics. - : Nature Publishing Group. - 1018-4813 .- 1476-5438. ; 18:4, s. 471-478
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Journal article (peer-reviewed)abstract
- Analyzing genetic variation of human populations for detecting loci that have been affected by positive natural selection is important for understanding adaptive history and phenotypic variation in humans. In this study, we analyzed recent positive selection in Northern Europe from genome-wide data sets of 250 000 and 500 000 single-nucleotide polymorphisms (SNPs) in a total of 999 individuals from Great Britain, Northern Germany, Eastern and Western Finland, and Sweden. Coalescent simulations were used for demonstrating that the integrated haplotype score (iHS) and long-range haplotype (LRH) statistics have sufficient power in genome-wide data sets of different sample sizes and SNP densities. Furthermore, the behavior of the F(ST) statistic in closely related populations was characterized by allele frequency simulations. In the analysis of the North European data set, 60 regions in the genome showed strong signs of recent positive selection. Out of these, 21 regions have not been discovered in previous scans, and many contain genes with interesting functions (eg, RAB38, INFG, NOS1AP, and APOE). In the putatively selected regions, we observed a statistically significant overrepresentation of genetic association with complex disease, which emphasizes the importance of the analysis of positive selection in understanding the evolution of human disease. Altogether, this study demonstrates the potential of genome-wide data sets to discover loci that lie behind evolutionary adaptation in different human populations.
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18. |
- Lappalainen, Tuuli, et al.
(author)
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Transcriptome and genome sequencing uncovers functional variation in humans
- 2013
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 501:7468, s. 506-511
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Journal article (peer-reviewed)abstract
- Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of messenger RNA and microRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project-the first uniformly processed high-throughput RNA-sequencing data from multiple human populations with high-quality genome sequences. We discover extremely widespread genetic variation affecting the regulation of most genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on the cellular mechanisms of regulatory and loss-of-function variation, and allows us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome.
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19. |
- Li, Xiaoting, et al.
(author)
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Identifying genetic regulatory variants that affect transcription factor activity
- 2023
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In: Cell Genomics. - : Elsevier BV. - 2666-979X. ; 3:9
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Journal article (peer-reviewed)abstract
- Genetic variants affecting gene expression levels in humans have been mapped in the Genotype-Tissue Expression (GTEx) project. Trans-acting variants impacting many genes simultaneously through a shared transcription factor (TF) are of particular interest. Here, we developed a generalized linear model (GLM) to estimate protein-level TF activity levels in an individual-specific manner from GTEx RNA sequencing (RNA-seq) profiles. It uses observed differential gene expression after TF perturbation as a predictor and, by analyzing differential expression within pairs of neighboring genes, controls for the confounding effect of variation in chromatin state along the genome. We inferred genotype-specific activities for 55 TFs across 49 tissues. Subsequently performing genome-wide association analysis on this virtual trait revealed TF activity quantitative trait loci (aQTLs) that, as a set, are enriched for functional features. Altogether, the set of tools we introduce here highlights the potential of genetic association studies for cellular endophenotypes based on a network-based multi-omics approach. The transparent peer review record is available.
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20. |
- Lim, Elaine T, et al.
(author)
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Distribution and Medical Impact of Loss-of-Function Variants in the Finnish Founder Population.
- 2014
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In: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 10:7
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Journal article (peer-reviewed)abstract
- Exome sequencing studies in complex diseases are challenged by the allelic heterogeneity, large number and modest effect sizes of associated variants on disease risk and the presence of large numbers of neutral variants, even in phenotypically relevant genes. Isolated populations with recent bottlenecks offer advantages for studying rare variants in complex diseases as they have deleterious variants that are present at higher frequencies as well as a substantial reduction in rare neutral variation. To explore the potential of the Finnish founder population for studying low-frequency (0.5-5%) variants in complex diseases, we compared exome sequence data on 3,000 Finns to the same number of non-Finnish Europeans and discovered that, despite having fewer variable sites overall, the average Finn has more low-frequency loss-of-function variants and complete gene knockouts. We then used several well-characterized Finnish population cohorts to study the phenotypic effects of 83 enriched loss-of-function variants across 60 phenotypes in 36,262 Finns. Using a deep set of quantitative traits collected on these cohorts, we show 5 associations (p<5×10-8) including splice variants in LPA that lowered plasma lipoprotein(a) levels (P = 1.5×10-117). Through accessing the national medical records of these participants, we evaluate the LPA finding via Mendelian randomization and confirm that these splice variants confer protection from cardiovascular disease (OR = 0.84, P = 3×10-4), demonstrating for the first time the correlation between very low levels of LPA in humans with potential therapeutic implications for cardiovascular diseases. More generally, this study articulates substantial advantages for studying the role of rare variation in complex phenotypes in founder populations like the Finns and by combining a unique population genetic history with data from large population cohorts and centralized research access to National Health Registers.
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21. |
- Martorella, Molly, et al.
(author)
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Evaluation of noninvasive biospecimens for transcriptome studies
- 2023
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In: BMC Genomics. - : Springer Nature. - 1471-2164. ; 24:1
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Journal article (peer-reviewed)abstract
- Transcriptome studies disentangle functional mechanisms of gene expression regulation and may elucidate the underlying biology of disease processes. However, the types of tissues currently collected typically assay a single post-mortem timepoint or are limited to investigating cell types found in blood. Noninvasive tissues may improve disease-relevant discovery by enabling more complex longitudinal study designs, by capturing different and potentially more applicable cell types, and by increasing sample sizes due to reduced collection costs and possible higher enrollment from vulnerable populations. Here, we develop methods for sampling noninvasive biospecimens, investigate their performance across commercial and in-house library preparations, characterize their biology, and assess the feasibility of using noninvasive tissues in a multitude of transcriptomic applications. We collected buccal swabs, hair follicles, saliva, and urine cell pellets from 19 individuals over three to four timepoints, for a total of 300 unique biological samples, which we then prepared with replicates across three library preparations, for a final tally of 472 transcriptomes. Of the four tissues we studied, we found hair follicles and urine cell pellets to be most promising due to the consistency of sample quality, the cell types and expression profiles we observed, and their performance in disease-relevant applications. This is the first study to thoroughly delineate biological and technical features of noninvasive samples and demonstrate their use in a wide array of transcriptomic and clinical analyses. We anticipate future use of these biospecimens will facilitate discovery and development of clinical applications.
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22. |
- Morris, John A., et al.
(author)
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Discovery of target genes and pathways at GWAS loci by pooled single-cell CRISPR screens
- 2023
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In: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 380:6646
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Journal article (peer-reviewed)abstract
- Most variants associated with complex traits and diseases identified by genome-wide association studies (GWAS) map to noncoding regions of the genome with unknown effects. Using ancestrally diverse, biobank-scale GWAS data, massively parallel CRISPR screens, and single-cell transcriptomic and proteomic sequencing, we discovered 124 cis-target genes of 91 noncoding blood trait GWAS loci. Using precise variant insertion through base editing, we connected specific variants with gene expression changes. We also identified trans-effect networks of noncoding loci when cis target genes encoded transcription factors or microRNAs. Networks were themselves enriched for GWAS variants and demonstrated polygenic contributions to complex traits. This platform enables massively parallel characterization of the target genes and mechanisms of human noncoding variants in both cis and trans.
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23. |
- Salmela, Elina, et al.
(author)
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Genome-wide analysis of single nucleotide polymorphisms uncovers population structure in Northern Europe
- 2008
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In: PLOS ONE. - San Fransisco : Public library of science. - 1932-6203. ; 3:10
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Journal article (peer-reviewed)abstract
- Background: Genome-wide data provide a powerful tool for inferring patterns of genetic variation and structure of human populations.Principal Findings: In this study, we analysed almost 250,000 SNPs from a total of 945 samples from Eastern and Western Finland, Sweden, Northern Germany and Great Britain complemented with HapMap data. Small but statistically significant differences were observed between the European populations (F(ST) = 0.0040, p < 10(-4)), also between Eastern and Western Finland (F(ST) = 0.0032, p < 10(-3)). The latter indicated the existence of a relatively strong autosomal substructure within the country, similar to that observed earlier with smaller numbers of markers. The Germans and British were less differentiated than the Swedes, Western Finns and especially the Eastern Finns who also showed other signs of genetic drift. This is likely caused by the later founding of the northern populations, together with subsequent founder and bottleneck effects, and a smaller population size. Furthermore, our data suggest a small eastern contribution among the Finns, consistent with the historical and linguistic background of the population.Significance: Our results warn against a priori assumptions of homogeneity among Finns and other seemingly isolated populations. Thus, in association studies in such populations, additional caution for population structure may be necessary. Our results illustrate that population history is often important for patterns of genetic variation, and that the analysis of hundreds of thousands of SNPs provides high resolution also for population genetics.
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24. |
- Salmela, Elina, et al.
(author)
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Swedish population substructure revealed by genome-wide single nucleotide polymorphism data
- 2011
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:2, s. e16747-
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Journal article (peer-reviewed)abstract
- The use of genome-wide single nucleotide polymorphism (SNP) data has recently proven useful in the study of human population structure. We have studied the internal genetic structure of the Swedish population using more than 350,000 SNPs from 1525 Swedes from all over the country genotyped on the Illumina HumanHap550 array. We have also compared them to 3212 worldwide reference samples, including Finns, northern Germans, British and Russians, based on the more than 29,000 SNPs that overlap between the Illumina and Affymetrix 250K Sty arrays. The Swedes--especially southern Swedes--were genetically close to the Germans and British, while their genetic distance to Finns was substantially longer. The overall structure within Sweden appeared clinal, and the substructure in the southern and middle parts was subtle. In contrast, the northern part of Sweden, Norrland, exhibited pronounced genetic differences both within the area and relative to the rest of the country. These distinctive genetic features of Norrland probably result mainly from isolation by distance and genetic drift caused by low population density. The internal structure within Sweden (F(ST) = 0.0005 between provinces) was stronger than that in many Central European populations, although smaller than what has been observed for instance in Finland; importantly, it is of the magnitude that may hamper association studies with a moderate number of markers if cases and controls are not properly matched geographically. Overall, our results underline the potential of genome-wide data in analyzing substructure in populations that might otherwise appear relatively homogeneous, such as the Swedes.
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25. |
- Schmitz, Daniel, 1995-
(author)
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Beyond GWAS : Novel Methods and Resources for Genetic Epidemiology
- 2024
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Doctoral thesis (other academic/artistic)abstract
- Since the first human genome assembly’s release, our knowledge of the genetic architecture of complex traits and diseases has grown steadily. Genome-wide association studies (GWAS) played a major role but are limited to common traits and single-nucleotide polymorphisms (SNPs). Technologies and resources like next-generation sequencing, Mendelian Randomization (MR), long-read sequencing and improved reference genomes enable the investigation of variants inaccessible to GWAS, such as copy number variations (CNVs), rare variants and variants in previously unresolved regions.In project I, we performed a GWAS of estradiol measurements using data from UK Biobank and quantified estradiol’s effect on bone mineral density (BMD) using MR. 14 loci were associated with estradiol levels in males, of which one was also significant in females and an additional female-specific locus. We found a significant effect of estradiol on BMD, confirming previous research of estrogen’s importance for skeletal health.In project II, we used the GWAS results from project I to investigate the effect of endogenous estradiol on breast, endometrial and ovarian cancer using MR. Estradiol was associated with ovarian cancer and nominally associated with estrogen receptor-positive breast cancer, demonstrating the effect of endogenous estrogen on cancer risk. In project III, we quantified the effect of 184,182 CNVs on 438 blood plasma proteins using whole-genome sequencing (WGS) data from a Northern Swedish cohort and validated our findings using long-read sequencing in a subcohort. 15 CNVs were associated with 16 proteins of which four could be validated using long reads and three more were more complex variation. Our findings show the effects of CNVs on the plasma proteome and highlight the application different sequencing technologies for CNV detection.In project IV, we evaluated the use of T2T-CHM13 as reference for the SweGen cohort. Compared to GRCh38, mapping quality improved and we identified 9.8 million more variants. Sensitivity for rare, singleton and functionally relevant variants was higher. These findings show how research and clinical applications benefit from T2T-CHM13 by improving detection of previously unknown functionally relevant variation.This thesis demonstrates the application of novel technologies and resources in genomics to detect variation and study its impact on quantitative traits. By using genotyping and WGS variants from short and long reads, I showed how we can leverage these technologies for research beyond GWAS.
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26. |
- Smolinska Garbulowska, Karolina
(author)
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Elucidation of complex diseases by machine learning
- 2021
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Doctoral thesis (other academic/artistic)abstract
- Uncovering the interpretability of models for complex health-related problems is a crucial task that is often neglected in machine learning (ML). The amount of available data makes the problem even more complicated. The focal point of my research was building and applying specialized tools that identify relevant descriptors (features and their values). These tools cover a spectrum of methods that originate in ML, statistics and network visualization.In the first part of the thesis, we predicted regulatory elements with potential regulatory impact on gene expression by incorporating several annotations tracks. Then, we created the funMotifs framework that enables the identification and analysis of functional transcription factor (TF) motifs in a tissue-specific manner (Paper I). The TF motifs were described by different chromatin signals from various genomics platforms. Afterwards, the data were merged into a functional score of the motif using logistic regression.Subsequently, funMotifs was used to characterize a map of regulatory mutations and regulatory elements in 37 cancer types from 2,515 samples (Paper II). We were able to identify 5,749 mutated regulatory elements containing 11,962 regulatory mutations. Additionally, we identified several dysregulated cancer-associated genes nearby the mutated elements. Finally, enrichment of cancer-related pathways was observed for the genes linked with the mutated elements.In the second part, we focused on interpretable ML modeling with rule-based classifiers. A rule-based model (RBM) consists of a set of IF-THEN rules, which are legible and allow to determine combinations of descriptors. To analyze RBMs, we created the R.ROSETTA R package that is a wrapper of ROSETTA (Paper III). As a result R.ROSETTA gained several additional functionalities that simplify validation and interpretation of RBMs.Visual inspection of RBMs is an essential step towards the identification of interesting descriptors of a classifier. In order to support the analysis of complex RBMs, we created the VisuNet R tool for rule network (RN) visualization (Paper IV). These networks are constructed from IF-THEN rules that constitute RBM; nodes are descriptors in rules, and an edge connects two nodes if the corresponding descriptors occur in the same rule. By creating RN for RBM, we are able to use network concepts to analyze complex health-related processes. We applied VisuNet on various datasets to illustrate the properties of the tool.In our studies, we showed the importance of identification of relevant descriptors for biological problems. Moreover, our methods may contribute to a better understanding of complex diseases.
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27. |
- 't Hoen, Peter A C, et al.
(author)
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Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories
- 2013
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In: Nature Biotechnology. - : Springer Science and Business Media LLC. - 1087-0156 .- 1546-1696. ; 31:11, s. 1015-1022
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Journal article (peer-reviewed)abstract
- RNA sequencing is an increasingly popular technology for genome-wide analysis of transcript sequence and abundance. However, understanding of the sources of technical and interlaboratory variation is still limited. To address this, the GEUVADIS consortium sequenced mRNAs and small RNAs of lymphoblastoid cell lines of 465 individuals in seven sequencing centers, with a large number of replicates. The variation between laboratories appeared to be considerably smaller than the already limited biological variation. Laboratory effects were mainly seen in differences in insert size and GC content and could be adequately corrected for. In small-RNA sequencing, the microRNA (miRNA) content differed widely between samples owing to competitive sequencing of rRNA fragments. This did not affect relative quantification of miRNAs. We conclude that distributing RNA sequencing among different laboratories is feasible, given proper standardization and randomization procedures. We provide a set of quality measures and guidelines for assessing technical biases in RNA-seq data.
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28. |
- Uffelmann, E., et al.
(author)
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Genome-wide association studies
- 2021
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In: Nature Reviews Methods Primers. - : Springer Nature. - 2662-8449. ; 1:1
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) test hundreds of thousands of genetic variants across many genomes to find those statistically associated with a specific trait or disease. This methodology has generated a myriad of robust associations for a range of traits and diseases, and the number of associated variants is expected to grow steadily as GWAS sample sizes increase. GWAS results have a range of applications, such as gaining insight into a phenotype’s underlying biology, estimating its heritability, calculating genetic correlations, making clinical risk predictions, informing drug development programmes and inferring potential causal relationships between risk factors and health outcomes. In this Primer, we provide the reader with an introduction to GWAS, explaining their statistical basis and how they are conducted, describe state-of-the art approaches and discuss limitations and challenges, concluding with an overview of the current and future applications for GWAS results.
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