Transcriptome assembly and expression analysis in Colletotrichum gloeosporioides -tolerant Rubus glaucus Benth.

Abstract

Andean blackberry (Rubus glaucus Benth.) is an important crop of the Andean region affected by Colletotrichum gloeosporioides. In Colombia, tolerant plant material has been detected, but it has not been completely characterized. The objective of this research was oriented to analyze de novo transcriptome assembly of R. glaucus, and the comparison of the assembly with different reference genomes to further complete differential expression analysis of R. glaucus tolerant to C. gloespoiorides attack. To achieve this, three groups were used: infected tolerant material, infected susceptible material, and a susceptible group without inoculation. The RNA-seq sequencing was achieved through Illumina Hi-seq 2000. De novo assembly (Trinity, CD-HIT, TopHat) and functional annotation of sequences were carried out, additionally, mapping with reference genomes belonging to Rosaceae families was conducted (Bowtie2, TopHat). Subsequently, the differential expression was quantified (Cuffdiff) and analyzed through EdgeR. Variant analysis was made using MISA and SAMtools. After editing and assembly, 43579 consensus sequences were obtained (N50 = 489 bp; GC = 44.6%), annotation detected 35824 and 35602 sequences in Nt (partially non-redundant nucleotide sequences) and Nr (non-redundant protein sequences) databases, respectively. The 85% of Nr sequences was linked to members of Rosaceae family, mainly strawberry (67.6%). A total of 3570 simple sequence repeat (SSR) markers and 38791 single nucleotide polymorphisms (SNP) were found. The transcriptome of tolerant plants exhibited less SNPs. Finally, differentially expressed genes were found, including RPM1, MAPKBP1, CKX2. This research represents a contribution for future understanding of R. glaucus transcriptome, since there is little information available, and it would help further tolerance-related analysis.

A global analysis of the Rubus virome using public transcriptome data

“…This work confirms that virus discovery can be accelerated through the analysis and reinterpretation of public sequencing data (Maree, 2018;Villamor et al, 2019;Buddenhagen et al, 2021 andGhosh et al, 2022). In our case, datasets were derived from studies focused on basic genome and transcriptome characterization of Rubus species (Hyun et al, 2014;Garcia-Seco et al, 2015;Sharma et al, 2019;Chen et al, 2018;Yan et al, 2020;Li et al, 2021;Yang et al, 2021;Wu et al, 2022a,b;Brůna et al, 2023 andMcGavin et al, 2023); analysis of the transcriptional response to upon infection with pathogens (Arias et al, 2019 andGonzález et al, 2020); and the validation of virus detection pipelines (Baizan-Edge et al, 2019;Gauthier et al, 2022 andMcGavin et al, 2023). Our most interesting results involved the identification of a putative new member of the genus Brambyvirus in data from a transcriptomic analysis of flavonoid biosynthesis (Li et al, 2021); and a putative new member of the family Virgaviridae in data used to test a plant virus detection workflow (Baizan-Edge et al, 2019).…”

“…Given the lack of financial resources for basic research in developing countries, we have shown that data mining can become a powerful tool to provide additional epidemiological insights for crops of interests. In our case, a single RNA sequencing study from Colombia, generated to investigate the response of infection with the fungus Colletotrichum gloeosporioides (Arias et al, 2019), provided a valuable glimpse of viruses circulating in Colombia that might represent a potential threat in the productivity of R. glaucus such as: RBDV, PYV, RIV2-1, and RIV-2.…”