Metatranscriptomic Sequencing

Partial results are shown below:

The taxonomy distribution of all sample in Phylum classification level.

Species abundance Heatmap.

Rarefaction curve of the sequenced reads for all samples.

Boxplot analysis based on bray Curtis (A), binary jaccard (B), unweighted unifrac (C), and weighted unifrac (D).

PCoA analysis based on bray Curtis (A), binary jaccard (B), unweighted unifrac (C), and weighted unifrac (D).

UPGMA clustering tree based on unweighted unifrac (A), and weighted unifrac (B).

Boxplot of TPM for each sample.

Correlation graph of gene number.

Statistics results of GO annotation for CLC_vs_SLC.

CLC_vs_SLC KEGG_classification.

Statistical of specific function database common and unique annotation.

CAZy function classification.

1. What are the noteworthy issues of RNA samples?

The contamination should be rigorously excluded when sampling. In detail, sampling-related instruments and consumables should be sterilized and RNase-free. The freshly obtained samples should be immediately frozen by putting into liquid nitrogen, or directly submitting original environmental or clinical samples to us. The recommended total RNA amount for submission is 6 µg or more with a concentration of greater than 50 ng/µl.

2. What kind of QC methods do you adopt for the customer's samples?

We will perform QC on your total RNA samples prior to sequencing them. We use the Agilent Bioanalyzer to determine the RNA Integrity Number (RIN). If the RIN is lower than 8, the samples will not pass QC. The library QC will also be performed using the Agilent Bioanalyzer to determine library size and purity. Also, prior to loading the libraries on the sequencer, we perform qPCR quantification. The cost for this is included in the sequencing service. The raw data will pass our Q30 filter, which means more than 80% of bases with a greater than Q30 quality score.

3. What are the advantages of metatranscriptomics?

Metatranscriptomics is the genomic analysis of complete microbial transcriptomes, providing a particularly rich source of data on the global diversity of RNA viruses and their evolutionary history. Metatranscriptomics has several advantages over traditional methods such as cell culture, consensus PCR, and metagenomics approaches based on viral particle purification.

Metatranscriptomics has proven successful in characterizing the RNA viromes of diverse invertebrates. Specifically: (i) it uncovers the entire RNA virome, with sufficient coverage to assembly complete viral genomes, including those from co-infecting parasites; (ii) it offers a reliable quantification and assessment of both viral and host RNAs; (iii) it is comparatively simple, requiring minimal sample processing; and (iv) it provides more information than the genome sequence alone, allowing a characterization of viral diversity and ecology.

References

1. Shi M, Neville P, Nicholson J, et al. High-Resolution Metatranscriptomics Reveals the Ecological Dynamics of Mosquito-Associated RNA Viruses in Western Australia. Journal of Virology, 2017, 91(17): e00680-17.
2. Shi M, Zhang Y Z, Holmes E C. Meta-transcriptomics and The Evolutionary Biology of RNA Viruses. Virus research, https://doi.org/10.1016/j.virusres.2017.10.01

High-Resolution Metatranscriptomics Reveals the Ecological Dynamics of Mosquito-Associated RNA Viruses in Western Australia

Journal: Journal of Virology
Impact factor: 4.663
Published: 21 June 2017

Background

Mosquitoes harbor a high diversity of RNA viruses, including many that impact human health. Although many efforts to reveal the extent and nature of the mosquito virome, little is known about how these viruses persist, spread, and interact with both their hosts and other microbes. To infer features of virome ecology among mosquito species from different geographic locations, the authors characterized the total transcriptome of 12 populations.

Methods

Results

1. The mosquito virome

Blast analyses showed the complete genomes of 24 RNA viruses species, of which 19 were newly described here. For each library, the number of virus species varied from 1 to 10 (Table 1).

2. Virome ecology

The virus composition and abundance revealed substantial differences between the Culex and Aedes genera (Figure 1). Generally, the Aedes mosquitoes harbour fewer viruses. Of the 24 viral species discovered, only Wilkie qin-like virus (WQLV) and Wilkie narna-like virus 1 (WNLV1) were shared between the two genera (Figure 2).

Figure 1. An overview of the diversity and abundance of the RNA viruses discovered.

Figure 2. The similarity of viromes between host species (A) and geographic locations (B).

3. Evolutionary analysis

The authors discovered eight putative negative-sense RNA viruses and seven double-stranded RNA viruses. The positive-sense RNA viruses discovered fell with the Narnaviridae, Mesoniviridae, Negev-like viruses, and Luteoviridae-related viruses. The authors performed phylogenetic analyses and genomic characterizations (please refer to the original paper for more detailed phylogenetic information). interestingly, two viruses (WQLV and WPLV2) were co-appeared with a group of fungi termed "Unknown sp1, 2, and 3" and they had matching evolutionary histories (Figure 3).

Figure 3. The matching tree topologies of the Wilkie qin-like viruses and a group of fungi (cox 1 gene) discovered in three mosquito pools.

Reference

1. Shi M, Neville P, Nicholson J, et al. High-Resolution Metatranscriptomics Reveals the Ecological Dynamics of Mosquito-Associated RNA Viruses in Western Australia. Journal of Virology, 2017, 91(17): e00680-17.