Computational analysis of eukaryotic metatranscriptomes from diverse marine environments

Phytoplankton are photosynthetic microbes that form the basis of the marine food web and are estimated to produce over half of all oxygen in the Earth's atmosphere. Recent advances in high-throughput DNA sequencing technologies have allowed scientists to sample the set of genes actively transcribed from communities of microbes in-situ. This set of transcripts (the metatranscriptome) provides a snapshot of actively transcribed genes at the time of sampling, and can provide insights into microbial metabolism and their relationship with their environment. In this thesis we present the computational analysis of eukaryotic phytoplankton metatranscriptome data sampled from representative marine environments; the simulation of metatranscriptome data for benchmarking computational tools; and analysis carried out on a newly sequenced eukaryotic phytoplankton genome. Transcripts a�liated with ribosomal proteins and associated with translation dominated in all but the Equatorial Paci�c metatranscriptome sample. Hierarchical clustering of the metatranscriptome samples by taxa produced two groups: the diatom dominated and the alveolate dominated. However, clustering by Gene Ontology terms clustered the samples by environment type (tropical, temperate and polar), producing a gradient of translation-associated transcripts which increased as the in-situ temperature of the samples decreased. A strong i correlation (R = 0:9) was detected between the relative proportion of transcripts associated with temperature and the in-situ temperature. Laboratory experiments on model diatom species under control conditions con�rmed that as the in-situ temperature decreases, these model diatoms produce more transcripts and consequently more ribosomal proteins. A translational e�ciency experiment demonstrated that the rate of translation decreased under low temperatures for a model diatom species. This suggested that the increased production of ribosomes acts as a compensatory mechanism under low temperatures. As more ribosomes require more phosphate-rich rRNAs we hypothesised that this could have an impact on biogeochemical cycles (E.g. the Red�eld ratio of Nitrate (N) to Phosphate (P)). This was modelled by our collaborators from the University of Exeter, who produced a global phytoplankton cell model of resource allocation. They showed how the N:P ratio di�ers across latitudinal temperature zones and predicted the impact of increasing temperature on global N:P.

Name dc:type.qualificationname

phd

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

University of East Anglia

Year dc:date.issued

2013

Author dc:creator

• Toseland, Andrew

Language dc:language

en