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Published on: June 24, 2021
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Ancestry patterns inferred from massive RNA-seq data
Ruth Barral-Arca1,2, Jacobo Pardo-Seco1,2, Xabi Bello1,2
1Unidade de Xenética, Instituto de Ciencias Forenses (INCIFOR), Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, of the Instituto de Investigación Sanitaria de Santiago (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), 15706 Galicia, Spain.
RNA (New York, N.Y.)
|April 24, 2019
Summary
Ancestral background significantly impacts human gene expression patterns. Standardized methods are needed to infer genetic ancestry from RNA-seq data, especially for quality-controlled studies, to avoid confounding disease research.
Area of Science:
- Genomics
- Population Genetics
- Bioinformatics
Background:
- Gene expression patterns exhibit significant variation within and between human populations.
- The influence of this variation on human diseases remains underexplored due to a lack of standardized protocols for estimating biogeographical ancestry from gene expression data.
Purpose of the Study:
- To investigate the impact of ancestral background on gene expression patterns.
- To test a standardized procedure for inferring genetic ancestry from RNA-seq data.
Main Methods:
- Examined multiple studies providing evidence for ancestral impact on gene expression.
- Tested an RNA-seq based ancestry inference procedure on 25 datasets with reported ethnicity.
- Utilized reference genome data from The 1000 Genomes Project for comparison.
Main Results:
- Only 8 out of 25 datasets met standard quality filters (FastQC).
- Genetic ancestry was efficiently inferred from quality-controlled datasets, including admixed populations.
- Suboptimal data quality often led to inaccurate ancestry inference patterns.
Conclusions:
- Ancestral genetic background is a crucial factor to consider in gene expression studies.
- Controlling for ancestral background is essential to prevent confounding effects in human disease research.
- Highlights the importance of data quality control in RNA-seq studies for reliable ancestry inference.
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