Mapping the Functional Gene-scape of the Oceans under Conditions of Global Change

(MOULTON_UCMP21ARIES)

Mapping the Functional Gene-scape of the Oceans under Conditions of Global Change

(MOULTON_UCMP21ARIES)

Project Description

Supervisors

Professor Vincent Moulton (School of Computing Sciences, University of East Anglia) contact me

Professor Thomas Mock (School of Environmental Sciences, University of East Anglia)

Dr Richard Leggett (Earlham Institute)

Project Background

Oceans cover over 70% of Earth’s surface, containing a majority of the planet’s animal biomass. Microbes form the base of the ocean food web, and play significant roles in the biogeochemical cycling of elements within and beyond the ocean, contributing about half of the oxygen in the planet’s atmosphere. Microbial communities are shifting geographically in response to anthropogenic climate change, and metagenomics is providing exciting new insights into these communities. Big data from large scale sampling expeditions such as the Global Ocean Survey and Tara Oceans have been used to characterise variations in taxonomy in different regions and show correlations between established metabolic pathways and environmental conditions. However, it has been recently shown that gene function within regions is not necessarily mirrored by variations in the taxonomy of the species inhabiting these regions.

Research Methodology

The main aim of this project is to analyse how the functional gene-scape varies between ocean regions so as to understand the metabolic potential of microbial communities responding to changing environmental conditions. The candidate will combine data from Tara Oceans, Mock’s lab and recent polar sequencing to identify groups of gene functions whose presence or abundance characterises different ocean regions. After functionally annotating sequence data using metagenomics pipelines, the candidate will use machine learning methods, such as non-negative matrix factorisation, to find groups of functions that describe variation in metabolic potential between ocean regions. Using clustering and visualisation techniques, the candidate will then identify groups of gene functions which characterise differences in ocean gene-scapes. In the latter stages of the project the candidate will develop models to predict function from environmental conditions, using approaches such as Bayesian networks.

Training

The candidate will gain skills in a broad range of bioinformatics, data analysis, machine learning techniques, as well as a background in ocean microbes and experience with high powered computing.

Person Specification

Degree in Computer Science, Data Science or equivalent. We are looking for an enthusiastic candidate who is excited about applying interdisciplinary techniques to under-stand the potential effects of global change on oceanic microbes.

References

  • 1. Mock et al. (2017) Evolutionary genomics of the cold-adapted diatom Fragilariopsis cylindrus. Nature (DOI: 10.1038/nature20803)
  • 2. Toseland et al. (2013) The impact of temperature on marine phytoplankton resource allocation and metabolism. Nature Climate Change (DOI: 10.1038/nclimate1989)
  • 3. Jiang et al. (2012) A non-negative matrix factorization framework for identifying modular patterns in metagenomic profile data. Journal of Mathematical Biology (DOI: 10.1371/journal.pone.0043866)
  • 4. Sunagawa S et al. (2015) Structure and function of the global ocean microbiome. Science (DOI: 10.1126/science.1261359)
  • 5. Aslam S et al. (2018) Identifying metabolic pathways for production of extracelluar polymeric substances by the diatom Fragilariopsis cylindrus inhabiting sea ice. The ISME journal (DOI: https://doi.org/10.1038/s41396-017-0039-z)

Key Information

  • This project has been shortlisted for funding by the ARIES NERC DTP and will start on 1st October 2021. The closing date for applications is 23:59 on 12th January 2021.
  • Successful candidates who meet UKRI’s eligibility criteria will be awarded a NERC studentship, which covers fees, stipend (£15,285 p.a. for 2020-21) and research funding. For the first time in 2021/22 international applicants (EU and non-EU) will be eligible for fully-funded UKRI studentships. Please note ARIES funding does not cover visa costs (including immigration health surcharge) or other additional costs associated with relocation to the UK.
  • ARIES students benefit from bespoke graduate training and ARIES provides £2,500 to every student for access to external training, travel and conferences. Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses in the subject area.
  • ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage enquiries and applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Academic qualifications are considered alongside significant relevant non-academic experience.
  • All ARIES studentships may be undertaken on a part-time or full-time basis, visa requirements notwithstanding
  • For further information, please contact the supervisor. To apply for this Studentship click on the “Apply now” link below.

Applications are Open

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