On Design of Oligonucleotide SNP Arrays and Methods for Genotype Calling

Author(s):  
Wenjiang J. Fu ◽  
Ming Li ◽  
Lin Wan ◽  
Minghua Deng ◽  
Minping Qian
Keyword(s):  
2006 ◽  
Vol 23 (1) ◽  
pp. 57-63 ◽  
Author(s):  
J. Hua ◽  
D. W. Craig ◽  
M. Brun ◽  
J. Webster ◽  
V. Zismann ◽  
...  

2005 ◽  
Vol 22 (1) ◽  
pp. 7-12 ◽  
Author(s):  
N. Rabbee ◽  
T. P. Speed

2021 ◽  
Vol 22 (7) ◽  
pp. 3786
Author(s):  
Andreas Brodehl ◽  
Alexey Meshkov ◽  
Roman Myasnikov ◽  
Anna Kiseleva ◽  
Olga Kulikova ◽  
...  

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.


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

PLoS ONE ◽  
2010 ◽  
Vol 5 (6) ◽  
pp. e10909 ◽  
Author(s):  
Zongzhi Liu ◽  
Ao Li ◽  
Vincent Schulz ◽  
Min Chen ◽  
David Tuck

2009 ◽  
Vol 3 (Suppl 7) ◽  
pp. S59 ◽  
Author(s):  
Maren Vens ◽  
Arne Schillert ◽  
Inke R König ◽  
Andreas Ziegler
Keyword(s):  

2013 ◽  
Vol 98 (6) ◽  
pp. E1131-E1136 ◽  
Author(s):  
Erica S. Rinella ◽  
Christopher Still ◽  
Yongzhao Shao ◽  
G. Craig Wood ◽  
Xin Chu ◽  
...  

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.


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