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Unmmaped RNA-Seq reads from inoculated sugarcane reveals long non-coding RNAs related to retrotransposons and suggest microbiome modulation

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ABSTRACT Background Transcriptome studies have contributed to the understanding of protein coding and non-coding gene expression of several organisms. They also provide knowledge into host responses to pathogen infections. Not common yet is to detect transcripts from multiple interacting organisms present in a given sample. In addition, transcriptome studies with complex polyploid hybrid genomes and not completely sequenced, such as the one of sugarcane, remains a challenge. In such studies, a considerable set of reads may not align on any reference genome but still hold significant relevance to the study, allowing to gather information beyond the complex organism itself. Results A complete transcriptome analysis of sugarcane inoculated with a pathogen, with and without the addition of a beneficial bacteria, generated a subset of reads that did not map to their respective genome references. Here, we report a pipeline based on the assembly of a collection of unmapped reads that potentially interfere with the gene expression of the associated microbiome, as well as the identification of long non-coding RNAs related to transposable elements present in a host-pathogen interaction. In addition, the detection of transcripts of naturally occurring microorganisms in sugarcane allowed the identification of its microbiome at the species level. Further studies support changes in microorganism transcription levels according to the biotic stress the plant was conditioned. Conclusion A quick and practical pipeline is proposed to study unmapped reads to infer relevant information that would remain otherwise unnoticed. New sequences from hybrid sugarcane transcriptome, such as long non-coding genes related to known retrotransposons are described. Also, changes in microbiome gene expression provides insights to the microbiome alterations and bring knowledge to the sugarcane “pathobiome”.
Title: Unmmaped RNA-Seq reads from inoculated sugarcane reveals long non-coding RNAs related to retrotransposons and suggest microbiome modulation
Description:
ABSTRACT Background Transcriptome studies have contributed to the understanding of protein coding and non-coding gene expression of several organisms.
They also provide knowledge into host responses to pathogen infections.
Not common yet is to detect transcripts from multiple interacting organisms present in a given sample.
In addition, transcriptome studies with complex polyploid hybrid genomes and not completely sequenced, such as the one of sugarcane, remains a challenge.
In such studies, a considerable set of reads may not align on any reference genome but still hold significant relevance to the study, allowing to gather information beyond the complex organism itself.
Results A complete transcriptome analysis of sugarcane inoculated with a pathogen, with and without the addition of a beneficial bacteria, generated a subset of reads that did not map to their respective genome references.
Here, we report a pipeline based on the assembly of a collection of unmapped reads that potentially interfere with the gene expression of the associated microbiome, as well as the identification of long non-coding RNAs related to transposable elements present in a host-pathogen interaction.
In addition, the detection of transcripts of naturally occurring microorganisms in sugarcane allowed the identification of its microbiome at the species level.
Further studies support changes in microorganism transcription levels according to the biotic stress the plant was conditioned.
Conclusion A quick and practical pipeline is proposed to study unmapped reads to infer relevant information that would remain otherwise unnoticed.
New sequences from hybrid sugarcane transcriptome, such as long non-coding genes related to known retrotransposons are described.
Also, changes in microbiome gene expression provides insights to the microbiome alterations and bring knowledge to the sugarcane “pathobiome”.

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