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Updated: Jan 19, 2026

Next-Gen Transcriptomics Using RNA-Seq
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Assessment of kinship detection using RNA-seq data.

Natalia Blay1,2,3, Eduard Casas1,2,4, Iván Galván-Femenía1,5

  • 1Program for Predictive and Personalized Medicine of Cancer, Germans Trias i Pujol Research Institute (PMPPC-IGTP), Badalona 08916, Spain.

Nucleic Acids Research
|September 11, 2019
PubMed
Summary

RNA sequencing (RNA-seq) data can predict kinship up to second-degree relatives. This method uses pairwise identity by descent (IBD) estimates from high-quality single nucleotide polymorphisms (SNPs) derived from RNA-seq data.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Genomics

Background:

  • RNA sequencing (RNA-seq) is crucial for clinical and molecular genetics.
  • Predicting kinship from RNA-seq aids family-based studies and identifies related individuals in population studies.
  • Current kinship reconstruction relies on SNPs or microsatellites from genotyping or sequencing.

Purpose of the Study:

  • To assess the utility of RNA-seq data for detecting kinship between individuals.
  • To evaluate the effectiveness of pairwise identity by descent (IBD) estimates for kinship detection using RNA-seq.

Main Methods:

  • High-quality single nucleotide polymorphisms (SNPs) were identified and filtered to minimize biases.
  • Pairwise IBD estimates were calculated using the selected SNPs.
  • Both real and simulated RNA-seq datasets were analyzed.

Main Results:

  • RNA-seq data can be used to detect kinship relationships.
  • Up to second-degree relationships were identifiable using RNA-seq data.
  • The method is effective even with low to moderate sequencing depth.

Conclusions:

  • RNA-seq data is a viable source for kinship prediction.
  • Pairwise IBD estimation from RNA-seq derived SNPs is a reliable method for relationship inference.
  • This approach offers a valuable tool for genetic studies involving related individuals.