# RNA-clique: a method for computing genetic distances from RNA-seq data

## TL;DR

RNA-clique is a new method that computes genetic distances from RNA-seq data, integrating functional and genetic diversity studies.

## Contribution

RNA-clique introduces a novel computational approach using reciprocal BLASTn and graph-based filtering to compute reliable genetic distances from RNA-seq data.

## Key findings

- RNA-clique reliably distinguishes tall fescue and bluehead wrasse RNA-seq samples by genotype or individual.
- Simulated data tests show RNA-clique accurately recovers ground truth phylogeny from computed distances.
- RNA-clique results are at least as reliable as alternative methods, especially for bluehead wrasse data.

## Abstract

Although RNA-seq data are traditionally used for quantifying gene expression levels, the same data could be useful in an integrated approach to compute genetic distances as well. Challenges to using mRNA sequences for computing genetic distances include the relatively high conservation of coding sequences and the presence of paralogous and, in some species, homeologous genes.

We developed a new computational method, RNA-clique, for calculating genetic distances using assembled RNA-seq data and assessed the efficacy of the method using biological and simulated data. The method employs reciprocal BLASTn followed by graph-based filtering to ensure that only orthologous genes are compared. Each vertex in the graph constructed for filtering represents a gene in a specific sample under comparison, and an edge connects a pair of vertices if the genes they represent are best matches for each other in their respective samples. The distance computation is a function of the BLAST alignment statistics and the constructed graph and incorporates only those genes that are present in some complete connected component of this graph. As a biological testbed we used RNA-seq data of tall fescue (Lolium arundinaceum), an allohexaploid plant (\documentclass[12pt]{minimal}
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\begin{document}$$2n = 14\text { Gb}$$\end{document}2n=14Gb), and bluehead wrasse (Thalassoma bifasciatum), a teleost fish. RNA-clique reliably distinguished individual tall fescue plants by genotype and distinguished bluehead wrasse RNA-seq samples by individual. In tests with simulated RNA-seq data, the ground truth phylogeny was accurately recovered from the computed distances. Moreover, tests of the algorithm parameters indicated that, even with stringent filtering for orthologs, sufficient sequence data were retained for the distance computations. Although comparisons with an alternative method revealed that RNA-clique has relatively high time and memory requirements, the comparisons also showed that RNA-clique’s results were at least as reliable as the alternative’s for tall fescue data and were much more reliable for the bluehead wrasse data.

Results of this work indicate that RNA-clique works well as a way of deriving genetic distances from RNA-seq data, thus providing a methodological integration of functional and genetic diversity studies.

The online version contains supplementary material available at 10.1186/s12859-024-05811-9.