scholarly journals Genome‐wide linkage analysis and whole‐exome sequencing identifies anITGA2Bmutation in a family with thrombocytopenia

2019 ◽  
Vol 186 (4) ◽  
pp. 574-579
Author(s):  
Rami Khoriaty ◽  
Ayse B. Ozel ◽  
Shweta Ramdas ◽  
Charles Ross ◽  
Karl Desch ◽  
...  
2019 ◽  
Vol 40 (7) ◽  
pp. 819-827 ◽  
Author(s):  
Lan Xiao ◽  
Fang Wei ◽  
Fang Liang ◽  
Qiao Li ◽  
Hao Deng ◽  
...  

AbstractCancer is a complex disease, which may involve multiple tumor susceptibility genes that mediate the occurrence and development of tumor molecular events. This study aimed to identify new genetic loci using genome-wide linkage analysis and whole-exome sequencing in a rare, large multi-cancer pedigree recently found in China. We performed high-throughput single-nucleotide polymorphism (SNP) array and linkage analyses of 24 core members of this pedigree and found that the disease susceptibility locus in the multi-cancer pedigree was mapped to chromosome 3q24-26. We also used microsatellites to further validate the results of the SNP locus linkage analysis. Furthermore, we sequenced the whole exome of three members in this pedigree and identified a novel mutant of transforming growth factor β stimulated clone 22 domain family, member 2 (TSC22D2, c.-91T-C) cosegregated with the cancer phenotype. This change was at a highly conserved position, and the exome results were validated using linkage analysis. Moreover, we found the histone H4 transcription factor (HINFP) binds to the promoter region of TSC22D2 and may regulate its transcription. In conclusion, our findings are of great significance to the early pathogenesis of tumors and contribute to the search for molecular targets for the early prevention and treatment of tumors.


2017 ◽  
Vol 3 (5) ◽  
pp. e177 ◽  
Author(s):  
Javier Ruiz-Martínez ◽  
Luis J. Azcona ◽  
Alberto Bergareche ◽  
Jose F. Martí-Massó ◽  
Coro Paisán-Ruiz

Objective:Despite the enormous advancements made in deciphering the genetic architecture of Parkinson disease (PD), the majority of PD is idiopathic, with single gene mutations explaining only a small proportion of the cases.Methods:In this study, we clinically evaluated 2 unrelated Spanish families diagnosed with PD, in which known PD genes were previously excluded, and performed whole-exome sequencing analyses in affected individuals for disease gene identification.Results:Patients were diagnosed with typical PD without relevant distinctive symptoms. Two different novel mutations were identified in the CSMD1 gene. The CSMD1 gene, which encodes a complement control protein that is known to participate in the complement activation and inflammation in the developing CNS, was previously shown to be associated with the risk of PD in a genome-wide association study.Conclusions:We conclude that the CSMD1 mutations identified in this study might be responsible for the PD phenotype observed in our examined patients. This, along with previous reported studies, may suggest the complement pathway as an important therapeutic target for PD and other neurodegenerative diseases.


2017 ◽  
Vol 107 (2) ◽  
pp. 457-466.e9 ◽  
Author(s):  
Svetlana A. Yatsenko ◽  
Priya Mittal ◽  
Michelle A. Wood-Trageser ◽  
Mirka W. Jones ◽  
Urvashi Surti ◽  
...  

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Chiara Fabbri ◽  
Siegfried Kasper ◽  
Alexander Kautzky ◽  
Joseph Zohar ◽  
Daniel Souery ◽  
...  

2016 ◽  
Vol 15 ◽  
pp. CIN.S36612 ◽  
Author(s):  
Lun-Ching Chang ◽  
Biswajit Das ◽  
Chih-Jian Lih ◽  
Han Si ◽  
Corinne E. Camalier ◽  
...  

With rapid advances in DNA sequencing technologies, whole exome sequencing (WES) has become a popular approach for detecting somatic mutations in oncology studies. The initial intent of WES was to characterize single nucleotide variants, but it was observed that the number of sequencing reads that mapped to a genomic region correlated with the DNA copy number variants (CNVs). We propose a method RefCNV that uses a reference set to estimate the distribution of the coverage for each exon. The construction of the reference set includes an evaluation of the sources of variability in the coverage distribution. We observed that the processing steps had an impact on the coverage distribution. For each exon, we compared the observed coverage with the expected normal coverage. Thresholds for determining CNVs were selected to control the false-positive error rate. RefCNV prediction correlated significantly ( r = 0.96–0.86) with CNV measured by digital polymerase chain reaction for MET (7q31), EGFR (7p12), or ERBB2 (17q12) in 13 tumor cell lines. The genome-wide CNV analysis showed a good overall correlation (Spearman's coefficient = 0.82) between RefCNV estimation and publicly available CNV data in Cancer Cell Line Encyclopedia. RefCNV also showed better performance than three other CNV estimation methods in genome-wide CNV analysis.


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