SNP calling from RNA-seq data without a reference genome: identification, quantification, differential analysis and impact on the protein sequence

Hélène Lopez-Maestre; Lilia Brinza; Camille Marchet; Janice Kielbassa; Sylvère Bastien; Mathilde Boutigny; David Monnin; Adil El Filali; Claudia Marcia Carareto; Cristina Vieira; Franck Picard; Natacha Kremer; Fabrice Vavre; Marie-France Sagot; Vincent Lacroix

doi:10.1093/nar/gkw655

SNP calling from RNA-seq data without a reference genome: identification, quantification, differential analysis and impact on the protein sequence

Hélène Lopez-Maestre ^{1, 2} Lilia Brinza ³ Camille Marchet ⁴ Janice Kielbassa ⁵ Sylvère Bastien ^{1, 2} Mathilde Boutigny ^{1, 2} David Monnin ¹ Adil El Filali ¹ Claudia Marcia Carareto ⁶ Cristina Vieira ^{1, 2, 7} Franck Picard ¹ Natacha Kremer ¹ Fabrice Vavre ^{1, 2} Marie-France Sagot ^{1, 2} Vincent Lacroix ^{2, 1}

1 LBBE - Laboratoire de Biométrie et Biologie Evolutive

2 ERABLE - Equipe de recherche européenne en algorithmique et biologie formelle et expérimentale

Inria Grenoble - Rhône-Alpes

3 PT Génomique et Transcriptomique, BIOASTER, Lyon

4 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics

Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE

5 Centre Léon Bérard [Lyon]

6 UNESP - Universidade Estadual Paulista Júlio de Mesquita

7 IUF - Institut Universitaire de France

Abstract : SNPs (Single Nucleotide Polymorphisms) are genetic markers whose precise identification is a prerequisite for association studies. Methods to identify them are currently well developed for model species, but rely on the availability of a (good) reference genome, and therefore cannot be applied to non-model species. They are also mostly tailored for whole genome (re-)sequencing experiments , whereas in many cases, transcriptome se-quencing can be used as a cheaper alternative which already enables to identify SNPs located in transcribed regions. In this paper, we propose a method that identifies, quantifies and annotates SNPs without any reference genome, using RNA-seq data only. Individuals can be pooled prior to sequencing, if not enough material is available from one individual. Using pooled human RNA-seq data, we clarify the precision and recall of our method and discuss them with respect to other methods which use a reference genome or an assembled transcriptome. We then validate experimentally the predictions of our method using RNA-seq data from two non-model species. The method can be used for any species to annotate SNPs and predict their impact on the protein sequence. We further enable to test for the association of the identified SNPs with a phenotype of interest.

Type de document :

Article dans une revue

Nucleic Acids Research, Oxford University Press, 2016, 〈10.1093/nar/gkw655〉

Domaine :

Informatique [cs] / Bio-informatique [q-bio.QM]

Informatique [cs] / Algorithme et structure de données [cs.DS]

Sciences du Vivant [q-bio]

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https://hal.inria.fr/hal-01352586
Contributeur : Marie-France Sagot <>
Soumis le : lundi 8 août 2016 - 15:35:24
Dernière modification le : vendredi 18 mai 2018 - 13:54:02

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SNP calling from RNA-seq data without a reference genome: identification, quantification, differential analysis and impact on the protein sequence

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SNP calling from RNA-seq data without a reference genome: identification, quantification, differential analysis and impact on the protein sequence

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