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

Content Provider	Springer Nature : BioMed Central
Author	Tapia, Andrew C. Jaromczyk, Jerzy W. Moore, Neil Schardl, Christopher L.
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 ( $2n = 14\text { Gb}$ ), 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.
Related Links	https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-024-05811-9.pdf
Ending Page	33
Page Count	33
Starting Page	1
File Format	HTM / HTML
ISSN	14712105
DOI	10.1186/s12859-024-05811-9
Journal	BMC Bioinformatics
Issue Number	1
Volume Number	25
Language	English
Publisher	BioMed Central
Publisher Date	2024-06-04
Access Restriction	Open
Subject Keyword	Bioinformatics Microarrays Computational Biology Computer Appl. in Life Sciences Algorithms RNA-seq Genetic distance Graph algorithms Phylogenetics Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Molecular Biology Biochemistry Computer Science Applications Applied Mathematics Structural Biology
Journal Impact Factor	2.9/2023
5-Year Journal Impact Factor	3.6/2023

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

ASGAL: aligning RNA-Seq data to a splicing graph to detect novel alternative splicing events

The maximum clique enumeration problem: algorithms, applications, and implementations

FastqPuri: high-performance preprocessing of RNA-seq data

An integrative method to normalize RNA-Seq data

Matataki: an ultrafast mRNA quantification method for large-scale reanalysis of RNA-Seq data

Fused inverse-normal method for integrated differential expression analysis of RNA-seq data

Algorithmic tools for tripartite data analysis

NURD: an implementation of a new method to estimate isoform expression from non-uniform RNA-seq data

An efficient scRNA-seq dropout imputation method using graph attention network

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

Similar Documents

ASGAL: aligning RNA-Seq data to a splicing graph to detect novel alternative splicing events

The maximum clique enumeration problem: algorithms, applications, and implementations

FastqPuri: high-performance preprocessing of RNA-seq data

An integrative method to normalize RNA-Seq data

Matataki: an ultrafast mRNA quantification method for large-scale reanalysis of RNA-Seq data

Fused inverse-normal method for integrated differential expression analysis of RNA-seq data

Algorithmic tools for tripartite data analysis

NURD: an implementation of a new method to estimate isoform expression from non-uniform RNA-seq data

An efficient scRNA-seq dropout imputation method using graph attention network

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