scholarly journals Defining the diverse spectrum of inversions, complex structural variation, and chromothripsis in the morbid human genome

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Ryan L. Collins ◽  
Harrison Brand ◽  
Claire E. Redin ◽  
Carrie Hanscom ◽  
Caroline Antolik ◽  
...  
PLoS Genetics ◽  
2016 ◽  
Vol 12 (6) ◽  
pp. e1006071 ◽  
Author(s):  
Ying Guo ◽  
Xiaorong Gu ◽  
Zheya Sheng ◽  
Yanqiang Wang ◽  
Chenglong Luo ◽  
...  

2019 ◽  
Author(s):  
Kevin Hadi ◽  
Xiaotong Yao ◽  
Julie M. Behr ◽  
Aditya Deshpande ◽  
Charalampos Xanthopoulakis ◽  
...  

SummaryCancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g. deletion, translocation) or complex (e.g. chromothripsis, chromoplexy) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,833 tumor whole genome sequences (WGS), we introduce three complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are “towers” of low-JCN duplications associated with early replicating regions and superenhancers, and are enriched in breast and ovarian cancers. Rigma comprise “chasms” of low-JCN deletions at late-replicating fragile sites in esophageal and other gastrointestinal (GI) adenocarcinomas. Tyfonas are “typhoons” of high-JCN junctions and fold back inversions that are enriched in acral but not cutaneous melanoma and associated with a previously uncharacterized mutational process of non-APOBEC kataegis. Clustering of tumors according to genome graph-derived features identifies subgroups associated with DNA repair defects and poor prognosis.


Cell ◽  
2020 ◽  
Vol 183 (1) ◽  
pp. 197-210.e32 ◽  
Author(s):  
Kevin Hadi ◽  
Xiaotong Yao ◽  
Julie M. Behr ◽  
Aditya Deshpande ◽  
Charalampos Xanthopoulakis ◽  
...  

2012 ◽  
Vol 554 ◽  
pp. 96-101 ◽  
Author(s):  
B. Christopher Rinderspacher ◽  
Jan W. Andzelm ◽  
Robert H. Lambeth

2015 ◽  
Vol 97 (1) ◽  
pp. 170-176 ◽  
Author(s):  
Harrison Brand ◽  
Ryan L. Collins ◽  
Carrie Hanscom ◽  
Jill A. Rosenfeld ◽  
Vamsee Pillalamarri ◽  
...  

2019 ◽  
Author(s):  
Walid Algady ◽  
Eleanor Weyell ◽  
Daria Mateja ◽  
André Garcia ◽  
David Courtin ◽  
...  

AbstractStructural variation in the human genome can affect risk of disease. An example is a complex structural variant of the human glycophorin gene cluster, called DUP4, which is associated with a clinically-significant level of protection against severe malaria. The human glycophorin gene cluster harbours at least 23 distinct structural variants and accurate genotyping of this complex structural variation remains a challenge. Here, we use a PCR-based strategy to genotype structural variation at the human glycophorin gene cluster. We validate our approach, based on a triplex paralogue ratio test (PRT) combined with junction-fragment specific PCR, on publically-available samples from the 1000 Genomes project. We then genotype a longitudinal birth cohort using small amounts of DNA at low cost. Our approach readily identifies known deletions and duplications, and can potentially identify novel variants for further analysis. It will allow exploration of genetic variation at the glycophorin locus, and investigation of its relationship with malaria, in large sample sets at minimal cost, using standard molecular biology equipment.


2020 ◽  
Vol 85 (1) ◽  
pp. 7-17
Author(s):  
Walid Algady ◽  
Eleanor Weyell ◽  
Daria Mateja ◽  
André Garcia ◽  
David Courtin ◽  
...  

2017 ◽  
Author(s):  
Joseph G. Arthur ◽  
Xi Chen ◽  
Bo Zhou ◽  
Alexander E. Urban ◽  
Wing Hung Wong

AbstractDetecting structural variants (SVs) from sequencing data is key to genome analysis, but methods using standard whole-genome sequencing (WGS) data are typically incapable of resolving complex SVs with multiple co-located breakpoints. We introduce the ARC-SV method, which uses a probabilistic model to detect arbitrary local rearrangements from WGS data. Our method performs well on simple SVs while surpassing state-of-the-art methods in complex SV detection.


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