scholarly journals The MIR137 VNTR rs58335419 Is Associated With Cognitive Impairment in Schizophrenia and Altered Cortical Morphology

2020 ◽  
Author(s):  
Ebrahim Mahmoudi ◽  
Joshua R Atkins ◽  
Yann Quidé ◽  
William R Reay ◽  
Heath M Cairns ◽  
...  
Keyword(s):  
Association Studies ◽  
Variable Number Tandem Repeat ◽  
Variable Number ◽  
Brain Morphology ◽  
Whole Genome Sequencing Data ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
Genome Wide ◽  
Cortical Morphology

Abstract Genome-wide association studies (GWAS) of schizophrenia have strongly implicated a risk locus in close proximity to the gene for miR-137. While there are candidate single-nucleotide polymorphisms (SNPs) with functional implications for the microRNA’s expression encompassed by the common haplotype tagged by rs1625579, there are likely to be others, such as the variable number tandem repeat (VNTR) variant rs58335419, that have no proxy on the SNP genotyping platforms used in GWAS to date. Using whole-genome sequencing data from schizophrenia patients (n = 299) and healthy controls (n = 131), we observed that the MIR137 4-repeats VNTR (VNTR4) variant was enriched in a cognitive deficit subtype of schizophrenia and associated with altered brain morphology, including thicker left inferior temporal gyrus and deeper right postcentral sulcus. These findings suggest that the MIR137 VNTR4 may impact neuroanatomical development that may, in turn, influence the expression of more severe cognitive symptoms in patients with schizophrenia.

scholarly journals A high-quality reference panel reveals the complexity and distribution of structural genome changes in a human population

2016 ◽  
Author(s):  
Jayne Y. Hehir-Kwa ◽  
Tobias Marschall ◽  
Wigard P. Kloosterman ◽  
Laurent C. Francioli ◽  
Jasmijn A. Baaijens ◽  
...  
Keyword(s):  
Association Studies ◽  
Whole Genome Sequencing Data ◽  
Strong Linkage Disequilibrium ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Full Spectrum ◽  
Disease Phenotypes ◽  
Human Genomes ◽  
Genome Wide ◽  
Genome Variants

AbstractStructural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation.Here, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals. Our findings are essential for genome-wide association studies.

scholarly journals The use of genomic data and imputation methods in dairy cattle breeding

2020 ◽  
Vol 65 (No. 12) ◽  
pp. 445-453
Author(s):  
Anita Klímová ◽  
Eva Kašná ◽  
Karolína Machová ◽  
Michaela Brzáková ◽  
Josef Přibyl ◽  
...  
Keyword(s):  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
Phenotypic Data ◽  
Single Nucleotide ◽  
Imputation Methods ◽  
Genome Wide ◽  
Dairy Cattle Breeding ◽  
Combine Information

The inclusion of animal genotype data has contributed to the development of genomic selection. Animals are selected not only based on pedigree and phenotypic data but also on the basis of information about their genotypes. Genomic information helps to increase the accuracy of selection of young animals and thus enables a reduction of the generation interval. Obtaining information about genotypes in the form of SNPs (single nucleotide polymorphisms) has led to the development of new chips for genotyping. Several methods of genomic comparison have been developed as a result. One of the methods is data imputation, which allows the missing SNPs to be calculated using low-density chips to high-density chips. Through imputations, it is possible to combine information from diverse sets of chips and thus obtain more information about genotypes at a lower cost. Increasing the amount of data helps increase the reliability of predicting genomic breeding values. Imputation methods are increasingly used in genome-wide association studies. When classical genotyping and genome-wide sequencing data are combined, this option helps to increase the chances of identifying loci that are associated with economically significant traits.

scholarly journals Genome-wide discovery of epistatic loci affecting antibiotic resistance using evolutionary couplings

2018 ◽  
Author(s):  
Benjamin Schubert ◽  
Rohan Maddamsetti ◽  
Jackson Nyman ◽  
Maha R. Farhat ◽  
Debora S. Marks
Keyword(s):  
Antibiotic Resistance ◽  
Statistical Power ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Whole Genome Sequencing Data ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Vast Number ◽  
Genome Wide

ABSTRACTThe analysis of whole genome sequencing data should, in theory, allow the discovery of interdependent loci that cause antibiotic resistance. In practice, however, identifying this epistasis remains a challenge as the vast number of possible interactions erodes statistical power. To solve this problem, we extend a method that has been successfully used to identify epistatic residues in proteins to infer genomic loci that are strongly coupled and associated with antibiotic resistance. Our method reduces the number of tests required for an epistatic genome-wide association study and increases the likelihood of identifying causal epistasis. We discovered 38 loci and 250 epistatic pairs that influence the dose needed to inhibit growth for five different antibiotics in 1,102 isolates of Neisseria gonorrhoeae that were confirmed in an independent dataset of 495 isolates. Many known resistance-affecting loci were recovered; however, the majority of loci occurred in unreported genes, including murE which was associated with cefixime. About half of the novel epistasis we report involved at least one locus previously associated with antibiotic resistance, including interactions between gyrA and parC associated with ciprofloxacin. Still, many combinations involved unreported loci and genes. Our work provides a systematic identification of epistasis pairs affecting antibiotic resistance in N. gonorrhoeae and a generalizable method for epistatic genome-wide association studies.

Reference SVA insertion polymorphisms are associated with dopaminergic degeneration in Parkinson’s Disease and differential gene expression in the PPMI cohort

2020 ◽  
Author(s):  
Abigail L Pfaff ◽  
Vivien J. Bubb ◽  
John P. Quinn ◽  
Sulev Koks
Keyword(s):  
Gene Expression ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Differential Gene Expression ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
Genome Wide ◽  
Differential Gene

Abstract Background: The development of Parkinson’s disease (PD) involves a complex interaction of genetic and environmental factors. The majority of studies investigating the genetic component of complex diseases, including PD, have focused on single nucleotide polymorphisms as this enables genome wide analysis of a large number of samples. Genome wide association studies have been crucial in identifying PD risk variants, however a large proportion of the heritability of PD remains to be identified. To investigate the component of PD that may involve complex genetic variants we characterised SINE-VNTR-Alus (SVAs), a retrotransposon known to affect gene expression, in the Parkinson’s Progression Markers Initiative (PPMI) cohort.Results: Utilising whole genome sequencing from the PPMI cohort that consisted of 179 healthy controls, 371 individuals with PD and 58 individuals classified as SWEDD (scans without evidence of dopaminergic deficit) we genotyped SVAs in the reference genome for their presence or absence identifying 81 such SVAs. Seven of these SVAs were associated with progression of the disease, including four whose specific genotypes were linked to an increase in the gradient of dopaminergic loss when comparing the caudate to putamen from DaTscan imaging analysis. These seven SVAs also demonstrated regulatory properties as they were associated with differential gene expression in whole blood RNA sequencing data.Conclusion: This study highlights the importance of addressing variation of SVAs and potentially other types of retrotransposons in PD genetics, furthermore these SVA elements should be considered as regulatory domains that could play a role in disease progression.

scholarly journals Finding genetic variants in plants without complete genomes

2019 ◽  
Author(s):  
Yoav Voichek ◽  
Detlef Weigel
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Structural Variants ◽  
Sequencing Data ◽  
New Associations ◽  
Maize Populations ◽  
Genome Wide ◽  
Genomic Regions

AbstractStructural variants and presence/absence polymorphisms are common in plant genomes, yet they are routinely overlooked in genome-wide association studies (GWAS). Here, we expand the genetic variants detected in GWAS to include major deletions, insertions, and rearrangements. We first use raw sequencing data directly to derive short sequences, k-mers, that mark a broad range of polymorphisms independently of a reference genome. We then link k-mers associated with phenotypes to specific genomic regions. Using this approach, we re-analyzed 2,000 traits measured in Arabidopsis thaliana, tomato, and maize populations. Associations identified with k-mers recapitulate those found with single-nucleotide polymorphisms (SNPs), however, with stronger statistical support. Moreover, we identified new associations with structural variants and with regions missing from reference genomes. Our results demonstrate the power of performing GWAS before linking sequence reads to specific genomic regions, which allow detection of a wider range of genetic variants responsible for phenotypic variation.

scholarly journals Elevated plasma levels of CXCL16 in severe COVID-19 patients

2021 ◽  
Author(s):  
Sandra P. Smieszek ◽  
Vasilios M. Polymeropoulos ◽  
Christos M. Polymeropoulos ◽  
Bartlomiej P. Przychodzen ◽  
Gunther Birznieks ◽  
...  
Keyword(s):  
Plasma Levels ◽  
Association Studies ◽  
Plasma Concentrations ◽  
Hospitalized Patients ◽  
Whole Genome Sequencing Data ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Genome Wide ◽  
Targeted Treatments ◽  
Severe Manifestation

AbstractGenome-wide association studies have recently identified 3p21.31, with lead variant pointing to the CXCR6 gene, as the strongest thus far reported susceptibility risk locus for severe manifestation of COVID-19. In order the determine its role, we measured plasma levels of Chemokine (C□X□C motif) ligand 16 (CXCL16) in the plasma of COVID-19 hospitalized patients. CXCL16 interacts with CXCR6 promoting chemotaxis or cell adhesion. The CXCR6/CXCL16 axis mediates homing of T cells to the lungs in disease and hyper-expression is associated with localised cellular injury. To characterize the CXCR6/CXCL16 axis in the pathogenesis of severe COVID-19, plasma concentrations of CXCL16 collected at baseline from 115 hospitalized COVID-19 patients participating in ODYSSEY COVID-19 clinical trial were assessed together with a set of controls. We report elevated levels of CXCL16 in a cohort of COVID-19 hospitalized patients. Specifically, we report significant elevation of CXCL16 plasma levels in association with severity of COVID-19 (as defined by WHO scale) (P-value<0.02). Our current study is the largest thus far study reporting CXCL16 levels in COVID-19 hospitalized patients (with whole-genome sequencing data available). The results further support the significant role of the CXCR6/CXCL16 axis in the immunopathogenesis of severe COVID-19 and warrants further studies to understand which patients would benefit most from targeted treatments.

scholarly journals Identification of deleterious and regulatory genomic variations in known asthma loci

2018 ◽  
Author(s):  
Matthew D. C. Neville ◽  
Jihoon Choi ◽  
Jonathan Lieberman ◽  
Qing Ling Duan
Keyword(s):  
Candidate Gene ◽  
Association Studies ◽  
Genome Wide Association ◽  
Whole Genome Sequencing Data ◽  
Sequence Variants ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Regulatory Variants ◽  
Genome Wide ◽  
Regulatory Effects

AbstractBackgroundCandidate gene and genome-wide association studies have identified hundreds of asthma risk loci. The majority of associated variants, however, are not known to have any biological function and are believed to represent markers rather than true causative mutations. We hypothesized that many of these associated markers are in linkage disequilibrium (LD) with the elusive causative variants.MethodsWe compiled a comprehensive list of 447 asthma-associated variants previously reported in candidate gene and genome-wide association studies. Next, we identified all sequence variants located within the 304 unique genes using whole-genome sequencing data from the 1000 Genomes Project. Then, we calculated the LD between known asthma variants and the sequence variants within each gene. LD variants identified were then annotated to determine those that are potentially deleterious and/or functional (i.e. coding or regulatory effects on the encoded transcript or protein).ResultsWe identified 10,048 variants in LD (r2 > 0.6) with known asthma variants. Annotations of these LD variants revealed that several have potentially deleterious effects including frameshift, alternate splice site, stop-lost, and missense. Moreover, 24 of the LD variants have been reported to regulate gene expression as expression quantitative trait loci (eQTLs).ConclusionsThis study is proof of concept that many of the genetic loci previously associated with complex diseases such as asthma are not causative but represent markers of disease, which are in LD with the elusive causative variants. We hereby report a number of potentially deleterious and regulatory variants that are in LD with the reported asthma loci. These reported LD variants could account for the original association signals with asthma and represent the true causative mutations at these loci.

scholarly journals Pharmacogenomics of Lithium Response in Bipolar Disorder

2021 ◽  
Vol 14 (4) ◽  
pp. 287
Author(s):  
Courtney M. Vecera ◽  
Gabriel R. Fries ◽  
Lokesh R. Shahani ◽  
Jair C. Soares ◽  
Rodrigo Machado-Vieira
Keyword(s):  
Bipolar Disorder ◽  
Association Studies ◽  
Mood Stabilizer ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Lithium Response ◽  
Genetic Loading ◽  
Long Non Coding Rna

Despite being the most widely studied mood stabilizer, researchers have not confirmed a mechanism for lithium’s therapeutic efficacy in Bipolar Disorder (BD). Pharmacogenomic applications may be clinically useful in the future for identifying lithium-responsive patients and facilitating personalized treatment. Six genome-wide association studies (GWAS) reviewed here present evidence of genetic variations related to lithium responsivity and side effect expression. Variants were found on genes regulating the glutamate system, including GAD-like gene 1 (GADL1) and GRIA2 gene, a mutually-regulated target of lithium. In addition, single nucleotide polymorphisms (SNPs) discovered on SESTD1 may account for lithium’s exceptional ability to permeate cell membranes and mediate autoimmune and renal effects. Studies also corroborated the importance of epigenetics and stress regulation on lithium response, finding variants on long, non-coding RNA genes and associations between response and genetic loading for psychiatric comorbidities. Overall, the precision medicine model of stratifying patients based on phenotype seems to derive genotypic support of a separate clinical subtype of lithium-responsive BD. Results have yet to be expounded upon and should therefore be interpreted with caution.

scholarly journals Transcriptional Regulation of RUNX1: An Informatics Analysis

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1175
Author(s):  
Amarni L. Thomas ◽  
Judith Marsman ◽  
Jisha Antony ◽  
William Schierding ◽  
Justin M. O’Sullivan ◽  
...  
Keyword(s):  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Runx1 Gene ◽  
Gene Regulatory Elements ◽  
Important Regulator ◽  
Aml1 Gene ◽  
Regulatory Landscape

The RUNX1/AML1 gene encodes a developmental transcription factor that is an important regulator of haematopoiesis in vertebrates. Genetic disruptions to the RUNX1 gene are frequently associated with acute myeloid leukaemia. Gene regulatory elements (REs), such as enhancers located in non-coding DNA, are likely to be important for Runx1 transcription. Non-coding elements that modulate Runx1 expression have been investigated over several decades, but how and when these REs function remains poorly understood. Here we used bioinformatic methods and functional data to characterise the regulatory landscape of vertebrate Runx1. We identified REs that are conserved between human and mouse, many of which produce enhancer RNAs in diverse tissues. Genome-wide association studies detected single nucleotide polymorphisms in REs, some of which correlate with gene expression quantitative trait loci in tissues in which the RE is active. Our analyses also suggest that REs can be variant in haematological malignancies. In summary, our analysis identifies features of the RUNX1 regulatory landscape that are likely to be important for the regulation of this gene in normal and malignant haematopoiesis.

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