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Investigating the community structure of eukaryotic benthic organisms by the extraction and analysis of limited mRNA

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Investigating the community structure of eukaryotic benthic organisms
by the extraction and analysis of limited mRNA

 

Background
Metatranscriptomic research has recently flourished in numerous fields, among others in research
looking at the environmental effect on adjacent communities.
Focus on the eukaryotic domain of the benthos: only recently been rarely investigated as a whole
even though
certain constituents of it have been shown to have important functional role to their community.
Advantages of Using of mRNa
Possible to use the same mRNA sample for analysing both the functional and structural patterns
of the community -> a more cost-effective solution
Easy to select, especially when looking at the eukaryotic communities, no PCR bias
Accurate view of what was happening at that community at the time of sampling
Our aim: How much can we learn about species identification and comparative abundances based
on small samples of environmental mRNA material

 

Part 1 - Field Sampling Methods
Samples were taken from 15 sites around two fish farms in Handagerfjord, Norway (fish farm 1:
60o.06N, 005o,55E, fish farm 2: 59o.57N, 05o,39E) on September 2016, over the span of four days.
Boxcores were collected from highly and low impacted sites (two depths per replicate, two replicates
per core).

 

Subsampled 10000 sequences from the raw output, used BLAST against the nt/nr database,
traversed the nodes of the taxonomy browser database to find the corresponding superkingdom.
The following equation was used to determine the distribution of the superkingdoms
The pie chart was constructed using the frequency of positive score values among the taxonomic groups
Eukaryotes compose the overwhelming majority of the raw reads with a high degree of certainty.
These proportions show a successful eukaryotic mRNA capture during the laboratory preparation

 

Trinity contigalignmentstoeitherRefseqcompletemitochondriagenomes(uppergraph) or/andtotheBOLD database (lowergraph).

Figure a. ContigsallignedsignificantlywellwiththeNannochloropsisgene withnearly 100% . Sincethecontigwasaligning in the ribosomal region, therewasnoavailablereference gene in the BOLD database.

Figure bContigsallignedwithP. jeffreysiBOLD reference gene at 99.6% similarity. The presenceoftheAmphinomid polychaete has alsobeenconfirmed by themorphologicaltaxonomy data from theJellyfarmproject. The closestcompletemitochondrionavailable in Refseqwas for theAmphinomidCryptonomebarbada. Therewasnearlycompletecoverageofthewholemitochondrionbutpercentageidentitywaslower, withthehighestsimilarcontigaligning at the Cox 1 region.

Figure c. This is an exampleof a contigwith a more ambivalent source. Thesequencealignsadequatelywith BOLD genes from two different groupsofnematodes (90.5% for Enoplida and 84% for Desmodora). Incontrast,thebestmappingwiththeRefseqdatabasebelonged to a dipteran,Hydrotaeaignava, withsimilaridentityvaluesattheCOX 1 region

 

Taxonomic Alignments of the top ten eukaryotic clusters of the trinity contigs to the a) BOLD reference database b) Refseq database. The NCBI Taxonomy Database was used to construct the nodes of the trees. Colors indicate the number of contig clusters that map to each clade. As the taxonomy hierarchy increases, the colors get warmer.

 

Polychaetes constitute the highest cluster group in both Refseq and BOLD. This trend is corroborated with the morphotaxonomical data. The Refseq database also provides a wider content as seen with the protist and algal alignments at the top and bottom of the tree respectively.

 

Our workflow yielded a majority of eukaryotic sequences that mapped  significantly well with reasonable benthic groups.

This paper shows the importance of consulting and comparing multiple database sources for species delimitation analysis when using mRNA as starting material.

The available databases, though exponentially growing, may still have ‘‘blindspots’’ that could obscure important ecological trends. For example, BOLD lacks genes references for algae groups and neither databases we used had foraminiferan reference genes which are expected to be present in the sediment according to morphotaxonomists.

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