University of Dundee

Postdoctoral Research Assistant

Unit: 
Plant Sciences
Job Reference: 
SLSC0419
Closing Date: 
Friday, June 22, 2018
Salary: 
Grade 7 (£31,604 - £38,833)

Developing a Reference Transcript Dataset (RTD) for barley



Applications are invited for a 21 month post-doctoral position funded by the BBSRC. We are looking to appoint an enthusiastic and motivated post-doctoral scientist to construct a Reference Transcript Dataset for cultivated barley.



To understand how gene expression responds to internal and external cues, whole research communities require datasets and tools that allow dynamic changes in transcript abundance to be accurately defined. High-throughput genome-wide RNA sequencing (RNA-seq) can generate such data but there are major (so far largely ignored) challenges in data analysis due to the diversity of transcript isoforms arising from extensive post-transcriptional processes such as alternative splicing (AS). Consequently, the occurrence of multiple transcripts derived from single genes impacts significantly upon both transcript diversity and quantification.



In this project we propose to address this problem by developing a Reference Transcript Database, or RTD, that contains the majority of genome-wide transcript isoforms using a combination of deep PacBio IsoSeq and Illumina short read data obtained from a wide range of barley varieties, tissues and treatments. We will validate the RTD using wet-lab experiments and then exploit it using novel software (Salmon/kallisto, SUPPA) to rapidly and accurately quantify individual transcript abundances and alternative splicing indices within a range of local Illumina-based RNA-seq datasets. Working with a number collaborating biologists our observations will allow us to identify new genes, mechanisms and networks involved in different biological responses. As an output we aim to provide the RTD freely to the barley community to aid in the analysis and interpretation of diverse RNA-seq datasets.

 

Summary of Skills, Experience and Qualifications:

 

Applicants should have, or be about to obtain, a PhD, and have a solid background in computational biology, preferably in handling large and complex RNA seq datasets. Strong interest and prior evidence of developing novel mathematical and computational approaches to data analysis would be advantageous. Experience in RNA-seq and capabilities to develop new packages and tools in R are essential.

 

College / Division Information:

 

The position is in the laboratories of Profs. Robbie Waugh and John Brown at the University of Dundee (School of Life Sciences; Division of Plant Sciences - http://www.lifesci.dundee.ac.uk/ps) based at the James Hutton Institute. Dundee (http://www.lifesci.dundee.ac.uk/) is currently ranked as the #1 University in the UK for life science research by the UK government research assessment (REF 2014) with world leading expertise in cell signalling and proteomics and outstanding laboratory and technology facilities for fundamental research and translation. With more than 900 staff from over 60 countries worldwide, the School of Life Sciences enjoys an international reputation as one of the most vibrant and productive research centres in Europe and is frequently voted “the best place to work in Europe” by readers of The Scientist magazine. The James Hutton Institute is the largest plant breeding and research institute in Scotland with particular expertise in translational plant science.

 

Appointment as a Postdoctoral Research Assistant on the Grade 7 salary scale is dependent upon you having been awarded a PhD. An appointment may be considered if you are shortly expected to be awarded a PhD. The initial appointment will be made as a Research Assistant on the Training Grade 7 salary scale (Spinal Point 28, £30,688).

 

This post is available for 21 months, Full Time, start date July 1 – Oct 1 2018.

 

Informal enquiries are welcome: Prof Robbie Waugh, e-mail: Robbie.waugh@hutton.ac.uk

                                               Prof John Brown, e-mail: j.w.s.brown@dundee.ac.uk

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