What is the right sequencing approach? Solo VS extended family analysis in consanguineous populations.
Type
ArticleAuthors
Alfares, Ahmed
Alsubaie, Lamia
Aloraini, Taghrid
Alaskar, Aljoharah
Althagafi, Azza Th.

Alahmad, Ahmed
Rashid, Mamoon
Alswaid, Abdulrahman
Alothaim, Ali
Eyaid, Wafaa
Ababneh, Faroug
Albalwi, Mohammed
Alotaibi, Raniah
Almutairi, Mashael
Altharawi, Nouf
Alsamer, Alhanouf
Abdelhakim, Marwa
Kafkas, Senay
Mineta, Katsuhiko

Cheung, Nicole
Abdallah, Abdallah
Büchmann-Møller, Stine
Fukasawa, Yoshinori
Zhao, Xiang
Rajan, Issaac
Hoehndorf, Robert

Al Mutairi, Fuad
Gojobori, Takashi

Alfadhel, Majid
KAUST Department
Bio-Ontology Research Group (BORG)Bioinformatics
Biological and Environmental Sciences and Engineering (BESE) Division
Bioscience Core Lab
Bioscience Program
Computational Bioscience Research Center (CBRC)
Computer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
NGS, qPCR and Single Cell Genomics
Sanger and Third Generation Sequencing
Date
2020-07-17Online Publication Date
2020-07-17Print Publication Date
2020-12Submitted Date
2019-05-08Permanent link to this record
http://hdl.handle.net/10754/664333
Metadata
Show full item recordAbstract
BACKGROUND:Testing strategies is crucial for genetics clinics and testing laboratories. In this study, we tried to compare the hit rate between solo and trio and trio plus testing and between trio and sibship testing. Finally, we studied the impact of extended family analysis, mainly in complex and unsolved cases. METHODS:Three cohorts were used for this analysis: one cohort to assess the hit rate between solo, trio and trio plus testing, another cohort to examine the impact of the testing strategy of sibship genome vs trio-based analysis, and a third cohort to test the impact of an extended family analysis of up to eight family members to lower the number of candidate variants. RESULTS:The hit rates in solo, trio and trio plus testing were 39, 40, and 41%, respectively. The total number of candidate variants in the sibship testing strategy was 117 variants compared to 59 variants in the trio-based analysis. We noticed that the average number of coding candidate variants in trio-based analysis was 1192 variants and 26,454 noncoding variants, and this number was lowered by 50-75% after adding additional family members, with up to two coding and 66 noncoding homozygous variants only, in families with eight family members. CONCLUSION:There was no difference in the hit rate between solo and extended family members. Trio-based analysis was a better approach than sibship testing, even in a consanguineous population. Finally, each additional family member helped to narrow down the number of variants by 50-75%. Our findings could help clinicians, researchers and testing laboratories select the most cost-effective and appropriate sequencing approach for their patients. Furthermore, using extended family analysis is a very useful tool for complex cases with novel genes.Citation
Alfares, A., Alsubaie, L., Aloraini, T., Alaskar, A., Althagafi, A., Alahmad, A., … Alfadhel, M. (2020). What is the right sequencing approach? Solo VS extended family analysis in consanguineous populations. BMC Medical Genomics, 13(1). doi:10.1186/s12920-020-00743-8Sponsors
This research used resources from the Core Labs of King Abdullah University of Science and Technology (KAUST).Publisher
Springer NatureJournal
BMC medical genomicsPubMed ID
32680510Additional Links
https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-020-00743-8https://bmcmedgenomics.biomedcentral.com/track/pdf/10.1186/s12920-020-00743-8
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Is Supplemented By:- [Dataset]
Alfares, A., Alsubaie, L., Aloraini, T., Aljoharah Alaskar, Azza Althagafi, Alahmad, A., Mamoon Rashid, Abdulrahman Alswaid, Alothaim, A., Eyaid, W., Faroug Ababneh, Albalwi, M., Raniah Alotaibi, Mashael Almutairi, Nouf Altharawi, Alhanouf Alsamer, Abdelhakim, M., Senay Kafkas, Mineta, K., … Alfadhel, M. (2020). What is the right sequencing approach? Solo VS extended family analysis in consanguineous populations. figshare. https://doi.org/10.6084/M9.FIGSHARE.C.5066525. DOI: 10.6084/m9.figshare.c.5066525 Handle: 10754/664972
ae974a485f413a2113503eed53cd6c53
10.1186/s12920-020-00743-8
Scopus Count
Collections
Articles; Bio-Ontology Research Group (BORG); Biological and Environmental Science and Engineering (BESE) Division; Bioscience Program; Computer Science Program; Computational Bioscience Research Center (CBRC); Bioscience Core Lab; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
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