Assessment of single-nucleotide variant discovery protocols in RNA-seq data from human cells exposed to mycotoxins

Abstract

Food and feed contamination by nonlegislated mycotoxins beauvericin (BEA) and enniatin B (ENB) is a worldwide health concern in the present. The principal objective of this work is to assess some of the existing protocols to discover the single nucleotide variants (SNVs) in transcriptomic data obtained by RNA-seq from Jurkat cells in vitro samples individually exposed to BEA and ENB at three concentration levels (1.5, 3 and 5 µM). Moreover, previous transcriptomic results will be compared with new findings obtained using a different protocol. SNVs rs201003509 in BEA exposed cells and the rs36045790 in ENB were found in the differentially expressed genes in all doses compared to controls by means of the Genome Analysis Toolkit (GATK) Best Practices workflow. SNV-RNA-seq complementary pipeline did not show any SNV. Concerning gene expression, discrepant results were found for 1.5 µM BEA exposed cells compared with previous findings. However, 354 overlapped differentially expressed genes (DEGs) were identified in the three ENB concentrations used, with 147 matches with respect to the 245 DEGs found in the previous results. In conclusion, the two discovery SNVs protocols based on variant calling from RNA-seq used in this work displayed very different results and there were SNVs found manually not identified by any pipeline. Additionally, the new gene expression analysis reported comparable but non identical DEGs to the previous transcriptomic results obtained from these RNA-seq data.

Graphical Abstract

• Single-nucleotide variants discovery protocols in transcriptomic data by RNA-seq from Jurkat cells exposed to mycotoxins for the first time

Keywords:

• Beauvericin
• enniatin B
• single-nucleotide variants
• Jurkat cells
• transcriptomic data

Compliance with ethical standards

The article contains no research in which animals were used.

Author contributions

M. Alonso-Garrido: writing original draft, review & editing. M. Lozano: visualization, conceptualization, writing original draft, data curation, statistical analysis. A.L. Riffo-Campos: visualization, conceptualization, review & editing. G. Font: funding acquisition, project administration, supervision, review & editing. P. Vila-Donat: writing final draft, review & editing. L. Manyes: conceptualization, funding acquisition, project administration, supervision, review & editing.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research study was supported by the Ministry of Science and Innovation (PID2019-108070RB-100) and the Ministry of Universities under the grant CAS21/00008 and grant for the requalification of the Spanish University, financed by the European Union, NextGeneration EU.