Common polymorphic inversions at 17q21.31 and 8p23.1 associate with cancer prognosis.
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ABSTRACT:
SUBMITTER: Ruiz-Arenas C
PROVIDER: S-EPMC6873427 | biostudies-literature | 2019 Nov
REPOSITORIES: biostudies-literature
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Project description:Inversions are one type of structural variants linked to phenotypic differences and adaptation in multiple organisms. However, there is still very little information about polymorphic inversions in the human genome due to the difficulty of their detection. Here, we develop a new high-throughput genotyping method based on probe hybridization and amplification, and we perform a complete study of 45 common human inversions of 0.1-415 kb. Most inversions promoted by homologous recombination occur recurrently in humans and great apes and they are not tagged by SNPs. Furthermore, there is an enrichment of inversions showing signatures of positive or balancing selection, diverse functional effects, such as gene disruption and gene-expression changes, or association with phenotypic traits. Therefore, our results indicate that the genome is more dynamic than previously thought and that human inversions have important functional and evolutionary consequences, making possible to determine for the first time their contribution to complex traits.
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Project description:Polymorphic inversions are a source of genetic variability with a direct impact on recombination frequencies. Given the difficulty of their experimental study, computational methods have been developed to infer their existence in a large number of individuals using genome-wide data of nucleotide variation. Methods based on haplotype tagging of known inversions attempt to classify individuals as having a normal or inverted allele. Other methods that measure differences between linkage disequilibrium attempt to identify regions with inversions but unable to classify subjects accurately, an essential requirement for association studies.We present a novel method to both identify polymorphic inversions from genome-wide genotype data and classify individuals as containing a normal or inverted allele. Our method, a generalization of a published method for haplotype data 1, utilizes linkage between groups of SNPs to partition a set of individuals into normal and inverted subpopulations. We employ a sliding window scan to identify regions likely to have an inversion, and accumulation of evidence from neighboring SNPs is used to accurately determine the inversion status of each subject. Further, our approach detects inversions directly from genotype data, thus increasing its usability to current genome-wide association studies (GWAS).We demonstrate the accuracy of our method to detect inversions and classify individuals on principled-simulated genotypes, produced by the evolution of an inversion event within a coalescent model 2. We applied our method to real genotype data from HapMap Phase III to characterize the inversion status of two known inversions within the regions 17q21 and 8p23 across 1184 individuals. Finally, we scan the full genomes of the European Origin (CEU) and Yoruba (YRI) HapMap samples. We find population-based evidence for 9 out of 15 well-established autosomic inversions, and for 52 regions previously predicted by independent experimental methods in ten (9+1) individuals 34. We provide efficient implementations of both genotype and haplotype methods as a unified R package inveRsion.
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Project description:Inversion polymorphisms have occupied a privileged place in Drosophila genetic research since their discovery in the 1920s. Indeed, inversions seem to be nearly ubiquitous, and the majority of species that have been thoroughly surveyed have been found to be polymorphic for one or more chromosomal inversions. Despite enduring interest, however, inversions remain difficult to study because their effects are often cryptic, and few efficient assays have been developed. Even in Drosophila melanogaster, in which inversions can be reliably detected and have received considerable attention, the breakpoints of only three inversions have been characterized molecularly. Hence, inversion detection and assay design remain important unsolved problems. Here, we present a method for identification and local de novo assembly of inversion breakpoints using next-generation paired-end reads derived from D. melanogaster isofemale lines. PCR and cytological confirmations demonstrate that our method can reliably assemble inversion breakpoints, providing tools for future research on D. melanogaster inversions as well as a framework for detection and assay design of inversions and other chromosome aberrations in diverse taxa.
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Project description:Identifying genomic features that differ between individuals and cells can help uncover the functional variants that drive phenotypes and disease susceptibilities. For this, single-cell studies are paramount, as it becomes increasingly clear that the contribution of rare but functional cellular subpopulations is important for disease prognosis, management, and progression. Until now, studying these associations has been challenged by our inability to map structural rearrangements accurately and comprehensively. To overcome this, we coupled single-cell sequencing of DNA template strands (Strand-seq) with custom analysis software to rapidly discover, map, and genotype genomic rearrangements at high resolution. This allowed us to explore the distribution and frequency of inversions in a heterogeneous cell population, identify several polymorphic domains in complex regions of the genome, and locate rare alleles in the reference assembly. We then mapped the entire genomic complement of inversions within two unrelated individuals to characterize their distinct inversion profiles and built a nonredundant global reference of structural rearrangements in the human genome. The work described here provides a powerful new framework to study structural variation and genomic heterogeneity in single-cell samples, whether from individuals for population studies or tissue types for biomarker discovery.
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Project description:The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed an inversion association analysis including 21 inversions and 25 obesity-related traits on a total of 408,898 Europeans and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2, and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes for obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.
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Project description:Inversion polymorphisms have important phenotypic and evolutionary consequences in humans. Two different methodologies have been used to infer inversions from SNP dense data, enabling the use of large cohorts for their study. One approach relies on the differences in linkage disequilibrium across breakpoints; the other one captures the internal haplotype groups that tag the inversion status of chromosomes. In this article, we assessed the convergence of the two methods in the detection of 20 human inversions that have been reported in the literature. The methods converged in four inversions including inv-8p23, for which we studied its association with low-BMI in American children. Using a novel haplotype tagging method with control on inversion ancestry, we computed the frequency of inv-8p23 in two American cohorts and observed inversion haplotype admixture. Accounting for haplotype ancestry, we found that the European inverted allele in children carries a recessive risk of underweight, validated in an independent Spanish cohort (combined: OR= 2.00, P = 0.001). While the footprints of inversions on SNP data are complex, we show that systematic analyses, such as convergence of different methods and controlling for ancestry, can reveal the contribution of inversions to the ancestral composition of populations and to the heritability of human disease.
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Project description:Chromosome 17q21.31 contains a common inversion polymorphism of approximately 900?kb in populations with European ancestry. Two divergent MAPT haplotypes, H1 and H2 are described with distinct linkage disequilibrium patterns across the region reflecting the inversion status at this locus. The MAPT H1 haplotype has been associated with progressive supranuclear palsy, corticobasal degeneration, Parkinson's disease and Alzheimer's disease, while the H2 is linked to recurrent deletion events associated with the 17q21.31 microdeletion syndrome, a disease characterized by developmental delay and learning disability.In this study, we investigate the effect of the inversion on the expression of genes in the 17q21.31 region. We find the expression of several genes in and at the borders of the inversion to be affected; specific either to whole blood or different regions of the human brain. The H1 haplotype was found to be associated with an increased expression of LRRC37A4, PLEKH1M and MAPT. In contrast, a decreased expression of MGC57346, LRRC37A and CRHR1 was associated with H1.Studies thus far have focused on the expression of MAPT in the inversion region. However, our results show that the inversion status affects expression of other genes in the 17q21.31 region as well. Given the link between the inversion status and different neurological diseases, these genes may also be involved in disease pathology, possibly in a tissue-specific manner.
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