New insights from Whole Genome Sequencing: BCLAF1 deletion as a structural variant that predisposes cells towards cellular transformation

AbstractBackgroundX - linked agammaglobulinemia (XLA, OMIM #300755) is a primary immunodeficiency disorder caused by pathogenic variations in the BTK gene, characterized by failure of development and maturation of B lymphocytes. The estimated prevalence worldwide is 1 in 190,000 male births. Recently, genome sequencing has been widely used in difficult to diagnose and familial cases. We report a large Indian family suffering from XLA with five affected individuals.MethodsWe performed complete blood count, immunoglobulin assay, and lymphocyte subset analysis for all patients and analyzed Btk expression for one patient and his mother. Whole exome sequencing (WES) for four patients, and whole genome sequencing (WGS) for two patients have been performed. Carrier screening was done for 17 family members using Multiplex Ligation-dependent Probe Amplification (MLPA) and haplotype ancestry mapping using fineSTRUCTURE was performed.ResultsAll patients had hypogammaglobulinemia and low CD19+ B cells. One patient who underwent Btk estimation had low expression and his mother showed a mosaic pattern. On structural variant analysis of WGS data, we found a novel large deletion of 5,296 bp at loci chrX:100,624,323-100,629,619 encompassing exons 3-5 of the BTK gene. Family screening revealed seven carriers for the deletion. Two patients had a successful HSCT. Haplotype mapping revealed mainly South Asian ancestry.ConclusionWhole genome sequencing led to identification of the accurate genetic mutation which could help in early diagnosis leading to improved outcomes, prevention of permanent organ damage and improved quality of life, as well as enabling prenatal diagnosis.

Download Full-text

A comprehensive benchmarking of WGS-based structural variant callers

10.1101/2020.04.16.045120 ◽

2020 ◽

Cited By ~ 1

Author(s):

Varuni Sarwal ◽

Sebastian Niehus ◽

Ram Ayyala ◽

Sei Chang ◽

Angela Lu ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Gold Standard ◽

Detection Methods ◽

Whole Genome ◽

Sequencing Data ◽

Structural Variant ◽

Gold Standard Dataset ◽

Low Pass ◽

Standard Set

AbstractAdvances in whole genome sequencing promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from whole genome sequencing (WGS) data presents a substantial number of challenges and a plethora of SV-detection methods have been developed. Currently, there is a paucity of evidence which investigators can use to select appropriate SV-detection tools. In this paper, we evaluated the performance of SV-detection tools using a comprehensive PCR-confirmed gold standard set of SVs. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of SV-detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance, as the SV-detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV-detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low and ultra-low pass sequencing data.

Download Full-text

Abstract 2176: Joint structural variant analysis of colorectal cancer whole genome sequencing data

10.1158/1538-7445.am2015-2176 ◽

2015 ◽

Author(s):

Esa Pitkänen ◽

Tatiana Cajuso ◽

Riku Katainen ◽

Sofie Lundgren ◽

Sari Tuupanen ◽

...

Keyword(s):

Colorectal Cancer ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Structural Variant ◽

Variant Analysis

Download Full-text

A deep learning approach for filtering structural variants in short read sequencing data

Briefings in Bioinformatics ◽

10.1093/bib/bbaa370 ◽

2020 ◽

Author(s):

Yongzhuang Liu ◽

Yalin Huang ◽

Guohua Wang ◽

Yadong Wang

Keyword(s):

Deep Learning ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome ◽

Structural Variants ◽

Sequencing Data ◽

Clinical Practices ◽

Short Read ◽

Structural Variant ◽

Variant Detection

Abstract Short read whole genome sequencing has become widely used to detect structural variants in human genetic studies and clinical practices. However, accurate detection of structural variants is a challenging task. Especially existing structural variant detection approaches produce a large proportion of incorrect calls, so effective structural variant filtering approaches are urgently needed. In this study, we propose a novel deep learning-based approach, DeepSVFilter, for filtering structural variants in short read whole genome sequencing data. DeepSVFilter encodes structural variant signals in the read alignments as images and adopts the transfer learning with pre-trained convolutional neural networks as the classification models, which are trained on the well-characterized samples with known high confidence structural variants. We use two well-characterized samples to demonstrate DeepSVFilter’s performance and its filtering effect coupled with commonly used structural variant detection approaches. The software DeepSVFilter is implemented using Python and freely available from the website at https://github.com/yongzhuang/DeepSVFilter.

Download Full-text

TBCK Encephaloneuropathy With Abnormal Lysosomal Storage: Use of a Structural Variant Bioinformatics Pipeline on Whole-Genome Sequencing Data Unravels a 20-Year-Old Clinical Mystery

Pediatric Neurology ◽

10.1016/j.pediatrneurol.2019.02.001 ◽

2019 ◽

Vol 96 ◽

pp. 74-75 ◽

Cited By ~ 2

Author(s):

Dulika Sumathipala ◽

Petter Strømme ◽

Christian Gilissen ◽

Jordi Corominas ◽

Eirik Frengen ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Lysosomal Storage ◽

Sequencing Data ◽

Bioinformatics Pipeline ◽

Structural Variant

Download Full-text

Whole genome sequencing identifies novel structural variant in a large Indian family affected with X-linked agammaglobulinemia

PLoS ONE ◽

10.1371/journal.pone.0254407 ◽

2021 ◽

Vol 16 (7) ◽

pp. e0254407

Author(s):

Abhinav Jain ◽

Geeta Madathil Govindaraj ◽

Athulya Edavazhippurath ◽

Nabeel Faisal ◽

Rahul C. Bhoyar ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Complete Blood Count ◽

Genetic Mutation ◽

Clinical Feature ◽

Whole Genome ◽

Single Nucleotide Variants ◽

Primary Immunodeficiency Disorder ◽

Structural Variant ◽

Indian Family

X—linked agammaglobulinemia (XLA, OMIM #300755) is a primary immunodeficiency disorder caused by pathogenic variations in the BTK gene, characterized by failure of development and maturation of B lymphocytes. The estimated prevalence worldwide is 1 in 190,000 male births. Recently, genome sequencing has been widely used in difficult to diagnose and familial cases. We report a large Indian family suffering from XLA with five affected individuals. We performed complete blood count, immunoglobulin assay, and lymphocyte subset analysis for all patients and analyzed Btk expression for one patient and his mother. Whole exome sequencing (WES) for four patients, and whole genome sequencing (WGS) for two patients have been performed. Carrier screening was done for 17 family members using Multiplex Ligation-dependent Probe Amplification (MLPA) and haplotype ancestry mapping using fineSTRUCTURE was performed. All patients had hypogammaglobulinemia and low CD19+ B cells. One patient who underwent Btk estimation had low expression and his mother showed a mosaic pattern. We could not identify any single nucleotide variants or small insertion/ deletions from the WES dataset that correlates with the clinical feature of the patient. Structural variant analysis through WGS data identifies a novel large deletion of 5,296 bp at loci chrX:100,624,323–100,629,619 encompassing exons 3–5 of the BTK gene. Family screening revealed seven carriers for the deletion. Two patients had a successful HSCT. Haplotype mapping revealed a South Asian ancestry. WGS led to identification of the accurate genetic mutation which could help in early diagnosis leading to improved outcomes, prevention of permanent organ damage and improved quality of life, as well as enabling genetic counselling and prenatal diagnosis in the family.

Download Full-text