Ds-Seq: an integrated pipeline for in silico small RNA sequence analysis for host-pathogen interaction studies

Temitayo Adebanji Olagunju, Angela Uche Makolo, Andreas Gisel


Plant-pathogen interactions activate molecular activities wherein the host defends the pathogen while the pathogen tries to suppress the plant response. Small RNAs (sRNAs) mediate major mechanisms, including post-transcriptional gene silencing, histone modification and DNA methylation by which plants respond to the presence of pathogens. Genome-wide profiling of host and pathogen sRNAs is therefore pivotal to uncovering the mechanisms underlying the host-pathogen interaction and mechanisms for host resistance. sRNA high throughput sequencing (HTS) data analysis often involves multiple stages/tools. Most necessary tools are accessible only through the command line, making it challenging for those without a high level of Unix/Linux skills. Furthermore, installation of some of these tools may become difficult due to dependencies and software version compatibility. We have developed an integrated open-source pipeline, Ds-Seq, for end-to-end in silico analysis of sRNA HTS data with improved reproducibility. The pipeline combines in-house scripts and public tools in a shell script, which can be invoked with a single command. The pipeline's usefulness has been demonstrated with testing on publicly available and published data from independent sRNA-seq datasets of host-pathogen interaction studies. Ds-Seq is available on GitHub, while a Docker image can be obtained from the Docker hub.

Availability: Ds-Seq is freely available from the GitHub repository at https://github.com/CEPHAS-01/small-RNASeq.ngs and Docker hub with ID cephas/ds-seq (https://hub.docker.com/r/cephas/ds-seq).


Plant – pathogen interaction; Workflow; Next Generation Sequencing (NGS); small RNAs; Docker; RNA-Seq

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DOI: https://doi.org/10.14806/ej.29.0.1037


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