GWAS Hits for Bilateral Convergent Strabismus with Exophthalmos in Holstein Cattle Using Imputed Sequence Level Genotypes

Bilateral convergent strabismus with exophthalmos (BCSE) is a malformation of the eyes and is recognized as a mild but progressive disorder that affects cattle in the first two years of life. This most likely inherited disorder is rarely described in cattle resembling autosomal dominantly inherited forms of human progressive external ophthalmoplegia (PEO). In German Braunvieh cattle, two linked genome regions were found that could be responsible for the development and/or progression of BCSE. The goal of this study was to phenotypically characterize BCSE in Holstein cattle from Germany and Switzerland as well as to identify associated genome regions by GWAS. The clinicopathological phenotype of 52 BCSE-affected Holstein cattle was in accordance with the phenotype described in German Braunvieh cattle, but in addition, signs of degeneration and cellular infiltration in the eye muscles were found. By using imputed sequence level genotype data, three genome-wide significant GWAS hits were revealed on different chromosomes that were not detected by initial GWAS based on high density SNP array data highlighting the usefulness of this approach for mapping studies. The associated genome regions include the ABCC4 gene as well as markers adjacent to the NCOR2 and DNAJC3 genes all illustrating possible functional candidate genes. Our results challenge a monogenic mode of inheritance and indicate a more complex inheritance of BCSE in Holstein cattle. Furthermore, in comparison to previous results from German Braunvieh cattle, it illustrates an obvious genetic heterogeneity causing BSCE in cattle. Subsequent whole genome sequencing (WGS)-based analyses might elucidate pathogenic variants in the future.

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CADD-Splice—improving genome-wide variant effect prediction using deep learning-derived splice scores

Genome Medicine ◽

10.1186/s13073-021-00835-9 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Philipp Rentzsch ◽

Max Schubach ◽

Jay Shendure ◽

Martin Kircher

Keyword(s):

Prediction Models ◽

Splice Variants ◽

Superior Performance ◽

Data Set ◽

Pathogenic Variants ◽

Genome Wide ◽

Donor And Acceptor ◽

Human Proteins ◽

Variant Effect ◽

Variant Effect Prediction

Abstract Background Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate synthesis of human proteins. Genetic variants impacting splicing underlie a substantial proportion of genetic disease, but are challenging to identify beyond those occurring at donor and acceptor dinucleotides. To address this, various methods aim to predict variant effects on splicing. Recently, deep neural networks (DNNs) have been shown to achieve better results in predicting splice variants than other strategies. Methods It has been unclear how best to integrate such process-specific scores into genome-wide variant effect predictors. Here, we use a recently published experimental data set to compare several machine learning methods that score variant effects on splicing. We integrate the best of those approaches into general variant effect prediction models and observe the effect on classification of known pathogenic variants. Results We integrate two specialized splicing scores into CADD (Combined Annotation Dependent Depletion; cadd.gs.washington.edu), a widely used tool for genome-wide variant effect prediction that we previously developed to weight and integrate diverse collections of genomic annotations. With this new model, CADD-Splice, we show that inclusion of splicing DNN effect scores substantially improves predictions across multiple variant categories, without compromising overall performance. Conclusions While splice effect scores show superior performance on splice variants, specialized predictors cannot compete with other variant scores in general variant interpretation, as the latter account for nonsense and missense effects that do not alter splicing. Although only shown here for splice scores, we believe that the applied approach will generalize to other specific molecular processes, providing a path for the further improvement of genome-wide variant effect prediction.

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RMR-Related MAP2K6 Gene Variation on the Risk of Overweight/Obesity in Children: A 3-Year Panel Study

Journal of Personalized Medicine ◽

10.3390/jpm11020091 ◽

2021 ◽

Vol 11 (2) ◽

pp. 91

Author(s):

Myoungsook Lee ◽

Yunkyoung Lee ◽

Inhae Kang ◽

Jieun Shin ◽

Sungbin R. Sorn

Keyword(s):

Dietary Intake ◽

Resting Metabolic Rate ◽

Panel Study ◽

Snp Array ◽

Fat Intake ◽

Nucleotide Polymorphisms ◽

Korean Children ◽

Gene Variation ◽

Genome Wide ◽

Prevalence Of Obesity

From a pilot GWAS, seven MAP2K6 (MEK6) SNPs were significantly associated with resting metabolic rate (RMR) in obese children aged 8–9 years. The aim of this study was to investigate how RMR-linked MEK6 variation affected obesity in Korean children. With the follow-up students (77.9%) in the 3-year panel study, the changes of the variables associated with obesity (such as anthropometrics, blood biochemistry, and dietary intake) were collected. After the MEK6 SNPs were screened by Affymetrix Genome-Wide Human SNP array 6.0, the genotyping of the seven MEK6 SNPs was performed via SNaPshot assay. As the prevalence of obesity (≥85th percentile) increased from 19.4% to 25.5%, the rates of change of the variables RMR, body mass index (BMI), waist circumference (WC), systolic blood pressure (SBP), and dietary intake (energy and carbohydrate intakes) increased. The rate of overweight/obesity was higher in all mutant alleles of the seven MEK6 SNPs than it was in the matched children without mutant alleles. However, over the 3-year study period, RMRs were only significantly increased by the mutants of two single nucleotide polymorphisms (SNPs), rs996229 and rs756942, mainly related to male overweight/obesity as both WC and SBP levels increased. In the mutants of two of the SNPs, the odds ratio of overweight/obesity risk was six times higher in the highest tercile of fat intake and SBP than those of the lowest tercile. For personalized medicine to prevent pediatric obesity, SBP, WC, and dietary fat intake should be observed, particularly if boys have mutants of MEK6 SNPs, rs9916229, or rs756942.

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Genome-Wide Analyses Identifies Known and New Markers Responsible of Chicken Plumage Color

Animals ◽

10.3390/ani10030493 ◽

2020 ◽

Vol 10 (3) ◽

pp. 493

Author(s):

Salvatore Mastrangelo ◽

Filippo Cendron ◽

Gianluca Sottile ◽

Giovanni Niero ◽

Baldassare Portolano ◽

...

Keyword(s):

Genome Wide Association Study ◽

Snp Array ◽

Fixation Index ◽

Phenotypic Traits ◽

Plumage Color ◽

Phenotypic Marker ◽

Genome Wide ◽

A Genome ◽

The Difference ◽

Genomic Regions

Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these genes could explain the difference between the two Polverara breeds. Therefore, this study provides the basis for further investigation of the genetic mechanisms involved in plumage color in chicken.

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Development and Evaluation of a Genome-Wide 6K SNP Array for Diploid Sweet Cherry and Tetraploid Sour Cherry

PLoS ONE ◽

10.1371/journal.pone.0048305 ◽

2012 ◽

Vol 7 (12) ◽

pp. e48305 ◽

Cited By ~ 81

Author(s):

Cameron Peace ◽

Nahla Bassil ◽

Dorrie Main ◽

Stephen Ficklin ◽

Umesh R. Rosyara ◽

...

Keyword(s):

Sweet Cherry ◽

Snp Array ◽

Sour Cherry ◽

Genome Wide ◽

A Genome

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Fidelity of SNP Array Genotyping Using Epstein Barr Virus-Transformed B-Lymphocyte Cell Lines: Implications for Genome-Wide Association Studies

PLoS ONE ◽

10.1371/journal.pone.0006915 ◽

2009 ◽

Vol 4 (9) ◽

pp. e6915 ◽

Cited By ~ 25

Author(s):

Joshua T. Herbeck ◽

Geoffrey S. Gottlieb ◽

Kim Wong ◽

Roger Detels ◽

John P. Phair ◽

...

Keyword(s):

Epstein Barr Virus ◽

B Lymphocyte ◽

Association Studies ◽

Snp Array ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Barr Virus ◽

Genome Wide ◽

Epstein Barr ◽

Lymphocyte Cell

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A principal component regression based genome wide analysis approach reveals the presence of a novel QTL on BTA7 for MAP resistance in holstein cattle

Genomics ◽

10.1016/j.ygeno.2010.01.001 ◽

2010 ◽

Vol 95 (3) ◽

pp. 176-182 ◽

Cited By ~ 55

Author(s):

Sameer D. Pant ◽

Flavio S. Schenkel ◽

Chris P. Verschoor ◽

Qiumei You ◽

David F. Kelton ◽

...

Keyword(s):

Principal Component Regression ◽

Principal Component ◽

Analysis Approach ◽

Holstein Cattle ◽

Genome Wide Analysis ◽

Genome Wide

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Next generation genome-wide association tool: Design and coverage of a high-throughput European-optimized SNP array

Genomics ◽

10.1016/j.ygeno.2011.04.005 ◽

2011 ◽

Vol 98 (2) ◽

pp. 79-89 ◽

Cited By ~ 126

Author(s):

Thomas J. Hoffmann ◽

Mark N. Kvale ◽

Stephanie E. Hesselson ◽

Yiping Zhan ◽

Christine Aquino ◽

...

Keyword(s):

High Throughput ◽

Snp Array ◽

Tool Design ◽

Genome Wide Association ◽

Next Generation ◽

Genome Wide

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Whole-Exome Sequencing Identifies Novel Variants for Tooth Agenesis

Journal of Dental Research ◽

10.1177/0022034517724149 ◽

2017 ◽

Vol 97 (1) ◽

pp. 49-59 ◽

Cited By ~ 16

Author(s):

N. Dinckan ◽

R. Du ◽

L.E. Petty ◽

Z. Coban-Akdemir ◽

S.N. Jhangiani ◽

...

Keyword(s):

Exome Sequencing ◽

Whole Exome Sequencing ◽

Permanent Teeth ◽

Tooth Agenesis ◽

Disease Genes ◽

Nonsense Mediated Decay ◽

Pathogenic Variants ◽

Whole Exome ◽

Novel Variants ◽

Complex Inheritance

Tooth agenesis is a common craniofacial abnormality in humans and represents failure to develop 1 or more permanent teeth. Tooth agenesis is complex, and variations in about a dozen genes have been reported as contributing to the etiology. Here, we combined whole-exome sequencing, array-based genotyping, and linkage analysis to identify putative pathogenic variants in candidate disease genes for tooth agenesis in 10 multiplex Turkish families. Novel homozygous and heterozygous variants in LRP6, DKK1, LAMA3, and COL17A1 genes, as well as known variants in WNT10A, were identified as likely pathogenic in isolated tooth agenesis. Novel variants in KREMEN1 were identified as likely pathogenic in 2 families with suspected syndromic tooth agenesis. Variants in more than 1 gene were identified segregating with tooth agenesis in 2 families, suggesting oligogenic inheritance. Structural modeling of missense variants suggests deleterious effects to the encoded proteins. Functional analysis of an indel variant (c.3607+3_6del) in LRP6 suggested that the predicted resulting mRNA is subject to nonsense-mediated decay. Our results support a major role for WNT pathways genes in the etiology of tooth agenesis while revealing new candidate genes. Moreover, oligogenic cosegregation was suggestive for complex inheritance and potentially complex gene product interactions during development, contributing to improved understanding of the genetic etiology of familial tooth agenesis.

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