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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
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Reference exome data for a Northern Brazilian population
Alexia L Weeks1, Richard W Francis1, Joao I C F Neri2
1Telethon Kids Institute, The University of Western Australia, Perth Children's Hospital, Western Australia, Perth, Australia.
Scientific Data
|October 22, 2020
Summary
This study catalogs genetic variants from 45 Brazilian babies, aiding rare disease diagnosis. The findings provide crucial population-specific data for clinical genetics in Brazil.
Area of Science:
- Genomics
- Clinical Genetics
- Population Genetics
Background:
- Exome sequencing is vital for diagnosing rare genetic disorders and analyzing complex diseases.
- A lack of population-specific reference data hinders accurate variant interpretation in clinical settings.
- This study addresses the need for localized genomic data in Brazil.
Purpose of the Study:
- To create a comprehensive catalog of exomic variants from a Brazilian cohort.
- To provide essential reference data for improving rare disease diagnosis in Brazil.
- To identify pathogenic variants using established clinical guidelines.
Main Methods:
- Whole exome sequencing was performed on 45 infants from Rio Grande do Nord, Brazil.
- Sequence data were processed using an intersect-then-combine (ITC) approach with GATK and SAMtools.
- Variant annotation and pathogenicity assessment followed American College of Medicine Genetics and Genomics (ACMG) guidelines.
Main Results:
- A total of 612,761 variants were identified across the cohort.
- This included 559,448 single nucleotide variants (SNVs) and 53,313 insertion/deletions.
- 185 variants (0.32%) were classified as pathogenic or likely pathogenic based on ACMG criteria.
Conclusions:
- The generated variant catalog serves as a valuable resource for rare disease diagnosis in Brazil.
- This population-specific data enhances the accuracy of variant interpretation for Brazilian patients.
- The study underscores the importance of localized genomic databases in clinical genetics.
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