Utility of SNP arrays in detecting, quantifying, and determining meiotic origin of tetrasomy 12p in blood from individuals with Pallister-Killian syndrome

2012 ◽  
Vol 158A (12) ◽  
pp. 3046-3053 ◽  
Author(s):  
Laura K. Conlin ◽  
Maninder Kaur ◽  
Kosuke Izumi ◽  
Lindsey Campbell ◽  
Alisha Wilkens ◽  
...  
Keyword(s):  
Snp Arrays

scholarly journals Hemi- and Homozygous Loss-of-Function Mutations in DSG2 (Desmoglein-2) Cause Recessive Arrhythmogenic Cardiomyopathy with an Early Onset

2021 ◽  
Vol 22 (7) ◽  
pp. 3786
Author(s):  
Andreas Brodehl ◽  
Alexey Meshkov ◽  
Roman Myasnikov ◽  
Anna Kiseleva ◽  
Olga Kulikova ◽  
...  
Keyword(s):  
Medical History ◽  
Splice Site Mutation ◽  
Pathogenic Mutation ◽  
Large Deletion ◽  
Loss Of Function ◽  
Arrhythmogenic Cardiomyopathy ◽  
Site Mutation ◽  
Snp Arrays ◽  
Number Of Patients ◽  
History Of

About 50% of patients with arrhythmogenic cardiomyopathy (ACM) carry a pathogenic or likely pathogenic mutation in the desmosomal genes. However, there is a significant number of patients without positive familial anamnesis. Therefore, the molecular reasons for ACM in these patients are frequently unknown and a genetic contribution might be underestimated. Here, we used a next-generation sequencing (NGS) approach and in addition single nucleotide polymor-phism (SNP) arrays for the genetic analysis of two independent index patients without familial medical history. Of note, this genetic strategy revealed a homozygous splice site mutation (DSG2–c.378+1G>T) in the first patient and a nonsense mutation (DSG2–p.L772X) in combination with a large deletion in DSG2 in the second one. In conclusion, a recessive inheritance pattern is likely for both cases, which might contribute to the hidden medical history in both families. This is the first report about these novel loss-of-function mutations in DSG2 that have not been previously identi-fied. Therefore, we suggest performing deep genetic analyses using NGS in combination with SNP arrays also for ACM index patients without obvious familial medical history. In the future, this finding might has relevance for the genetic counseling of similar cases.

scholarly journals MixHMM: Inferring Copy Number Variation and Allelic Imbalance Using SNP Arrays and Tumor Samples Mixed with Stromal Cells

PLoS ONE ◽  
2010 ◽  
Vol 5 (6) ◽  
pp. e10909 ◽  
Author(s):  
Zongzhi Liu ◽  
Ao Li ◽  
Vincent Schulz ◽  
Min Chen ◽  
David Tuck
Keyword(s):  
Copy Number Variation ◽  
Stromal Cells ◽  
Copy Number ◽  
Allelic Imbalance ◽  
Snp Arrays ◽  
Number Variation

scholarly journals Genome-wide Association of Single-Nucleotide Polymorphisms With Weight Loss Outcomes After Roux-en-Y Gastric Bypass Surgery

2013 ◽  
Vol 98 (6) ◽  
pp. E1131-E1136 ◽  
Author(s):  
Erica S. Rinella ◽  
Christopher Still ◽  
Yongzhao Shao ◽  
G. Craig Wood ◽  
Xin Chu ◽  
...  
Keyword(s):  
Weight Loss ◽  
Gastric Bypass ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Single Nucleotide ◽  
Snp Arrays ◽  
Genome Wide ◽  
Common Genetic Variants ◽  
Weight Loss Outcomes

Context: Roux-en-Y gastric bypass (RYGB) is among the most effective treatments for extreme obesity and obesity-related complications. However, despite its potential efficacy, many patients do not achieve and/or maintain sufficient weight loss. Objective: Our objective was to identify genetic factors underlying the variability in weight loss outcomes after RYGB surgery. Design: We conducted a genome-wide association study using a 2-stage phenotypic extreme study design. Setting: Patients were recruited from a comprehensive weight loss program at an integrated health system. Patients: Eighty-six obese (body mass index >35 kg/m2) patients who had the least percent excess body weight loss (%EBWL) and 89 patients who had the most %EBWL at 2 years after surgery were genotyped using Affymetrix version 6.0 single-nucleotide polymorphism (SNP) arrays. A second group from the same cohort consisting of 164 patients in the lower quartile of %EBWL and 169 from the upper quartile were selected for evaluation of candidate regions using custom SNP arrays. Intervention: We performed RYGB surgery. Main Outcome Measures: We assessed %EBWL at 2 years after RYGB and SNPs. Results: We identified 111 SNPs in the first-stage analysis whose frequencies were significantly different between 2 phenotypic extremes of weight loss (allelic χ2 test P < .0001). Linear regression of %EBWL at 2 years after surgery revealed 17 SNPs that approach P < .05 in the validation stage and cluster in or near several genes with potential biological relevance including PKHD1, HTR1A, NMBR, and IGF1R. Conclusions: This is the first genome-wide association study of weight loss response to RYGB. Variation in weight loss outcomes after RYGB may be influenced by several common genetic variants.

scholarly journals Efficient phasing and imputation of low-coverage sequencing data using large reference panels

2020 ◽  
Author(s):  
S. Rubinacci ◽  
D.M. Ribeiro ◽  
R. Hofmeister ◽  
O. Delaneau
Keyword(s):  
Paradigm Shift ◽  
Rare Variants ◽  
Association Studies ◽  
Cost Effective ◽  
Human Populations ◽  
Sequencing Data ◽  
Snp Arrays ◽  
Genomic Studies ◽  
Low Coverage ◽  
The Impact

AbstractLow-coverage whole genome sequencing followed by imputation has been proposed as a cost-effective genotyping approach for disease and population genetics studies. However, its competitiveness against SNP arrays is undermined as current imputation methods are computationally expensive and unable to leverage large reference panels.Here, we describe a method, GLIMPSE, for phasing and imputation of low-coverage sequencing datasets from modern reference panels. We demonstrate its remarkable performance across different coverages and human populations. It achieves imputation of a full genome for less than $1, outperforming existing methods by orders of magnitude, with an increased accuracy of more than 20% at rare variants. We also show that 1x coverage enables effective association studies and is better suited than dense SNP arrays to access the impact of rare variations. Overall, this study demonstrates the promising potential of low-coverage imputation and suggests a paradigm shift in the design of future genomic studies.

Whole genome SNP arrays using DNA derived from formalin-fixed, paraffin-embedded ovarian tumor tissue

2005 ◽  
Vol 26 (4) ◽  
pp. 384-389 ◽  
Author(s):  
Ella R. Thompson ◽  
Shane C. Herbert ◽  
Susan M. Forrest ◽  
Ian G. Campbell
Keyword(s):  
Ovarian Tumor ◽  
Tumor Tissue ◽  
Whole Genome ◽  
Snp Arrays ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Formalin Fixed

Using SNP arrays to leverage historical data sets for improved prediction accuracy and study of G×E×M in peach

2021 ◽  
pp. 133-140
Author(s):  
C. Hardner ◽  
K. Gasic ◽  
C. da Silva Linge ◽  
M. Worthington ◽  
D. Byrne ◽  
...  
Keyword(s):  
Prediction Accuracy ◽  
Historical Data ◽  
Data Sets ◽  
Snp Arrays

scholarly journals 34 Present and future of genomic test reporting in the cattle industry

2019 ◽  
Vol 97 (Supplement_2) ◽  
pp. 19-20
Author(s):  
Rich Tait ◽  
Ryan Ferretti ◽  
Barry Simpson ◽  
Jeremy Walker ◽  
Jamie Parham ◽  
...  
Keyword(s):  
Evaluation System ◽  
Imputation Accuracy ◽  
Snp Array ◽  
Cattle Industry ◽  
Maximum Information ◽  
Snp Arrays ◽  
Target Populations ◽  
Genomic Test ◽  
Routine Basis ◽  
Genetic Evaluations

Abstract A series of custom low density (LD) SNP genotyping platforms have been created over the years. Recognized by the GeneSeek Genomic Profiler (GGP) nomenclature, these SNP arrays have increased in size as new versions were created, such as: GGP-LD-v1 (n = 8,762), GGP-LD-v2 (n = 20,057), GGP-LD-v3 (n = 26,151), GGP-LD-v4 (n = 30,108), and GGP Bovine 50K (n = 47,843), all of which contained a base of the Illumina Bovine LD array (n = 7,931) and then added SNPs to provide maximum information content (Shannon Entropy) and optimal genomic coverage into target populations without specific restrictions on overlap to historical commercial arrays such as the Illumina Bovine 50K (n = 54,001). Our approach has been to select SNP content which originated on the Illumina Bovine HD array (n = 777,962) or the GGP F250 functional SNP array (n = 221,115). This approach produced GGPs which: 1) have a larger number of SNPs that meet quality control metrics for minor allele frequency and Hardy-Weinberg segregation testing; 2) have superior imputation accuracy to the Illumina HD array in target populations; and 3) have causative SNPs or SNPs in closer LD with causative mutations for functional genomics studies and increased utility across populations. These design features have not always been utilized by users of the GGP portfolio. In some cases, users have imputed from GGP content back to the Illumina Bovine 50K SNP content within their population because that was the earliest process they developed in their evaluation system. This approach ignores the innovation and potential utility designed into the GGP chips for breeders within those organizations. We do not look back to prior SNP arrays for content definition for the purpose of bridging content from current arrays to the past. Instead, our vision is to continue to innovate, on a routine basis, which SNPs we provide to customers, so that their genetic evaluations can continue to evolve and improve into the future.

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