191 research outputs found

    A Variant of GJD2, Encoding for Connexin 36, Alters the Function of Insulin Producing β-Cells.

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    Signalling through gap junctions contributes to control insulin secretion and, thus, blood glucose levels. Gap junctions of the insulin-producing β-cells are made of connexin 36 (Cx36), which is encoded by the GJD2 gene. Cx36-null mice feature alterations mimicking those observed in type 2 diabetes (T2D). GJD2 is also expressed in neurons, which share a number of common features with pancreatic β-cells. Given that a synonymous exonic single nucleotide polymorphism of human Cx36 (SNP rs3743123) associates with altered function of central neurons in a subset of epileptic patients, we investigated whether this SNP also caused alterations of β-cell function. Transfection of rs3743123 cDNA in connexin-lacking HeLa cells resulted in altered formation of gap junction plaques and cell coupling, as compared to those induced by wild type (WT) GJD2 cDNA. Transgenic mice expressing the very same cDNAs under an insulin promoter revealed that SNP rs3743123 expression consistently lead to a post-natal reduction of islet Cx36 levels and β-cell survival, resulting in hyperglycemia in selected lines. These changes were not observed in sex- and age-matched controls expressing WT hCx36. The variant GJD2 only marginally associated to heterogeneous populations of diabetic patients. The data document that a silent polymorphism of GJD2 is associated with altered β-cell function, presumably contributing to T2D pathogenesis

    Shared genetic etiology between idiopathic pulmonary fibrosis and COVID-19 severity

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    Background: Idiopathic pulmonary fibrosis (IPF) is a complex lung disease, characterized by progressive lung scarring. Severe COVID-19 is associated with substantial pneumonitis and has a number of shared major risk factors with IPF. This study aimed to determine the genetic correlation between IPF and severe COVID-19 and assess a potential causal role of genetically increased risk of IPF on COVID-19 severity. Methods: The genetic correlation between IPF and COVID-19 severity was estimated with linkage disequilib-rium (LD) score regression. We performed a Mendelian randomization (MR) study for IPF causality in COVID-19. Genetic variants associated with IPF susceptibility (P Findings: We detected a positive genetic correlation of IPF with COVID-19 severity (rg=0.31 [95% CI 0.04-0.57], P = 0.023). The MR estimates for severe COVID-19 did not reveal any genetic association (OR 1.05, [95% CI 0.92-1.20], P = 0.43). However, outlier analysis revealed that the IPF risk allele rs35705950 at MUC5B had a dif-ferent effect compared with the other variants. When rs35705950 was excluded, MR results provided evidence that genetically increased risk of IPF has a causal effect on COVID-19 severity (OR 1.21, [95% CI 1.06-1.38], P = 4.24 x 10(-3)). Furthermore, the IPF risk-allele at MUC5B showed an apparent protective effect against COVID-19 hospitalization only in older adults (OR 0.86, [95% CI 0.73-1.00], P = 2.99 x 10(-2)) . Interpretation: The strongest genetic determinant of IPF, rs35705950 at MUC5B, seems to confer protection against COVID-19, whereas the combined effect of all other IPF risk loci seem to confer risk of COVID-19 severity. The observed effect of rs35705950 could either be due to protective effects of mucin over-produc-tion on the airways or a consequence of selection bias due to (1) a patient group that is heavily enriched for the rs35705950 T undertaking strict self-isolation and/or (2) due to survival bias of the rs35705950 non-IPF risk allele carriers. Due to the diverse impact of IPF causal variants on SARS-CoV-2 infection, with a possible selection bias as an explanation, further investigation is needed to address this apparent paradox between variance at MUC5B and other IPF genetic risk factors. (C) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Peer reviewe

    Global assessment of genomic variation in cattle by genome resequencing and high-throughput genotyping

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    <p>Abstract</p> <p>Background</p> <p>Integration of genomic variation with phenotypic information is an effective approach for uncovering genotype-phenotype associations. This requires an accurate identification of the different types of variation in individual genomes.</p> <p>Results</p> <p>We report the integration of the whole genome sequence of a single Holstein Friesian bull with data from single nucleotide polymorphism (SNP) and comparative genomic hybridization (CGH) array technologies to determine a comprehensive spectrum of genomic variation. The performance of resequencing SNP detection was assessed by combining SNPs that were identified to be either in identity by descent (IBD) or in copy number variation (CNV) with results from SNP array genotyping. Coding insertions and deletions (indels) were found to be enriched for size in multiples of 3 and were located near the N- and C-termini of proteins. For larger indels, a combination of split-read and read-pair approaches proved to be complementary in finding different signatures. CNVs were identified on the basis of the depth of sequenced reads, and by using SNP and CGH arrays.</p> <p>Conclusions</p> <p>Our results provide high resolution mapping of diverse classes of genomic variation in an individual bovine genome and demonstrate that structural variation surpasses sequence variation as the main component of genomic variability. Better accuracy of SNP detection was achieved with little loss of sensitivity when algorithms that implemented mapping quality were used. IBD regions were found to be instrumental for calculating resequencing SNP accuracy, while SNP detection within CNVs tended to be less reliable. CNV discovery was affected dramatically by platform resolution and coverage biases. The combined data for this study showed that at a moderate level of sequencing coverage, an ensemble of platforms and tools can be applied together to maximize the accurate detection of sequence and structural variants.</p

    A high-resolution integrated map of copy number polymorphisms within and between breeds of the modern domesticated dog

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    <p>Abstract</p> <p>Background</p> <p>Structural variation contributes to the rich genetic and phenotypic diversity of the modern domestic dog, <it>Canis lupus familiaris</it>, although compared to other organisms, catalogs of canine copy number variants (CNVs) are poorly defined. To this end, we developed a customized high-density tiling array across the canine genome and used it to discover CNVs in nine genetically diverse dogs and a gray wolf.</p> <p>Results</p> <p>In total, we identified 403 CNVs that overlap 401 genes, which are enriched for defense/immunity, oxidoreductase, protease, receptor, signaling molecule and transporter genes. Furthermore, we performed detailed comparisons between CNVs located within versus outside of segmental duplications (SDs) and find that CNVs in SDs are enriched for gene content and complexity. Finally, we compiled all known dog CNV regions and genotyped them with a custom aCGH chip in 61 dogs from 12 diverse breeds. These data allowed us to perform the first population genetics analysis of canine structural variation and identify CNVs that potentially contribute to breed specific traits.</p> <p>Conclusions</p> <p>Our comprehensive analysis of canine CNVs will be an important resource in genetically dissecting canine phenotypic and behavioral variation.</p

    The landscape of inherited and de novo copy number variants in a plasmodium falciparum genetic cross

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    <p>Abstract</p> <p>Background</p> <p>Copy number is a major source of genome variation with important evolutionary implications. Consequently, it is essential to determine copy number variant (CNV) behavior, distributions and frequencies across genomes to understand their origins in both evolutionary and generational time frames. We use comparative genomic hybridization (CGH) microarray and the resolution provided by a segregating population of cloned progeny lines of the malaria parasite, <it>Plasmodium falciparum</it>, to identify and analyze the inheritance of 170 genome-wide CNVs.</p> <p>Results</p> <p>We describe CNVs in progeny clones derived from both Mendelian (i.e. inherited) and non-Mendelian mechanisms. Forty-five CNVs were present in the parent lines and segregated in the progeny population. Furthermore, extensive variation that did not conform to strict Mendelian inheritance patterns was observed. 124 CNVs were called in one or more progeny but in neither parent: we observed CNVs in more than one progeny clone that were not identified in either parent, located more frequently in the telomeric-subtelomeric regions of chromosomes and singleton <it>de novo </it>CNVs distributed evenly throughout the genome. Linkage analysis of CNVs revealed dynamic copy number fluctuations and suggested mechanisms that could have generated them. Five of 12 previously identified expression quantitative trait loci (eQTL) hotspots coincide with CNVs, demonstrating the potential for broad influence of CNV on the transcriptional program and phenotypic variation.</p> <p>Conclusions</p> <p>CNVs are a significant source of segregating and <it>de novo </it>genome variation involving hundreds of genes. Examination of progeny genome segments provides a framework to assess the extent and possible origins of CNVs. This segregating genetic system reveals the breadth, distribution and dynamics of CNVs in a surprisingly plastic parasite genome, providing a new perspective on the sources of diversity in parasite populations.</p

    A Snapshot of CNVs in the Pig Genome

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    Recent studies of mammalian genomes have uncovered the extent of copy number variation (CNV) that contributes to phenotypic diversity, including health and disease status. Here we report a first account of CNVs in the pig genome covering part of the chromosomes 4, 7, 14, and 17 already sequenced and assembled. A custom tiling oligonucleotide array was used with a median probe spacing of 409 bp for screening 12 unrelated Duroc boars that are founders of a large family material. After a strict CNV calling pipeline, 37 copy number variable regions (CNVRs) across all four chromosomes were identified, with five CNVRs overlapping segmental duplications, three overlapping pig unigenes and one overlapping a RefSeq pig mRNA. This CNV snapshot analysis is the first of its kind in the porcine genome and constitutes the basis for a better understanding of porcine phenotypes and genotypes with the prospect of identifying important economic traits
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