scholarly journals Genotyping complex structural variation at the malaria‐associated human glycophorin locus using a PCR‐based strategy

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


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

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Ryan L. Collins ◽  
Harrison Brand ◽  
Claire E. Redin ◽  
Carrie Hanscom ◽  
Caroline Antolik ◽  
...  

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

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.


2021 ◽  
Vol 12 ◽  
Author(s):  
Junfu Guo ◽  
Chang Shi ◽  
Xi Chen ◽  
Ou Wang ◽  
Ping Liu ◽  
...  

Co-barcoded reads originating from long DNA fragments (mean length >30 kbp) maintain both single base level accuracy and long-range genomic information. We propose a pipeline, stLFRsv, to detect structural variation using co-barcoded reads. stLFRsv identifies abnormal large gaps between co-barcoded reads to detect potential breakpoints and reconstruct complex structural variants (SVs). Haplotype phasing by co-barcoded reads increases the signal to noise ratio, and barcode sharing profiles are used to filter out false positives. We integrate the short read SV caller smoove for smaller variants with stLFRsv. The integrated pipeline was evaluated on the well-characterized genome HG002/NA24385, and 74.5% precision and a 22.4% recall rate were obtained for deletions. stLFRsv revealed some large variants not included in the benchmark set that were verified by long reads or assembly. For the HG001/NA12878 genome, stLFRsv also achieved the best performance for both resource usage and the detection of large variants. Our work indicates that co-barcoded read technology has the potential to improve genome completeness.


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