AgResearch Ltd
Summer Intern Scheme
AgResearch Invermay
2012-2013 Summer Intern Scheme
The AgResearch Summer Intern scheme has now been running for some years. In that time it has had
success in introducing 3rd and 4th year tertiary science students who intend returning to University for
further study in 2013 to the rigours and demands of research in a working science environment. The
aim of the scheme is to provide a link between the tertiary and research campus.
The scheme involves students completing a specific science project drawn from AgResearch’s local
programmes. The projects must be completed over a ten week period over the University summer
vacation (40 hours per week) - the Intern salary is for a taxable total of $6,200 paid on an hours-worked
basis every fortnight ($15.50 per hour).
At the end of the period the students complete a written report and present a short talk on the project,
its results, and its implications in a Summer Interns’ Seminar held in February.
The scheme will give a group of talented, potential science graduates exposure to research in the real
world, while giving both students and AgResearch a view of future employment opportunities.
The projects available this year are:
PROJECT/S
Quantitative genetics of sheep (AGR-SIS-IVY-01)
The project will focus on data-analysis related to
quantitative genetics and bioinformatics. An
overarching aim is to gain insight into the genetic
structure that forms the sheep population in New
Zealand, and to develop tools to better achieve this.
A number of sub-projects are available and will be
chosen from as best suits the intern’s skills and
interest. Data resources include millions of
individually recorded sheep and thousands of
genotypes from many thousands of individual
animals. The project areas of interest are: 1.)
investigating the necessary infrastructure (e.g.
hardware) and fast and reliable software to impute
from 50,000 genotypes to up to one million
genotypes 2.) Conduct studies on genomic data in
sheep to better understand the genetic architectural
with respect to linkage disequilibrium between DNA
markers in the context of effective population size
and the NZ sheep population. 3.) Investigate
whether any recorded sheep trait has important Xlinked inheritance patterns that would allow more
efficient selection strategies 4) Investigate the
influence of the degree of inbreeding on sheep
performance (particularly lamb survival) and on the
efficacy of selection. 5) Investigate whether lamb
and maternal performance to weaning and genetic
parameters, differs for shepherded compared with
easy care (non-shepherded) flocks.
The intern, depending on the project, may be
Knowledge
Area/s
Supervisor & Project
location
Quantitative
Genetics
Bioinformatics
Statistics
Biology
Computing
Mathematics
Michael Lee
michael.lee@agresearch.co.nz
Ken Dodds
Benoit Auvray
Sheryl-Anne Newman
Invermay
AgResearch Ltd
Summer Intern Scheme
computer literate, have a background in genetics or
statistics, and interested in R&D.
Data analysis of meat traits (AGR-SIS-IVY-02)
The red meat industry is of high value to the New
Zealand economy with export earnings of $8 billion
annually. In addition to increasing meat yield, quality
of meat is paramount. Key productive meat traits
have been and are continuing to be developed by
the industry. Utilising genetics and genomics it is
possible to estimate breeding values for a variety of
traits including meat yield and meat quality allowing
the industry to make significant genetic gains in
these traits. This summer internship involves the
collection of meat phenotypes from processing
plant, QC of meat trait data and subsequent data
analysis. The student is required to have good data
analysis skills in a statistical package such as R,
SAS or equivalent.
Mating allocation in salmon (AGR-SIS-IVY-03)
In a breeding programme, pairs of animals are
chosen for mating in a way that maximizes genetic
gain subject to constraints on immediate and longterm inbreeding. However, for salmon the pool of
candidates changes from day to day, depending on
the maturation status of the fish. Therefore, preassigned mate allocations fail. This project aims to
devise a computational tool that can input
information on candidates that are available for
selection on a particular day, along with matings that
have already been done and possible future
matings, and select a near-optimal set of matings to
be performed on that day.
Novel methods for breed prediction (AGR-SISIVY-04)
DNA markers can be used for breed prediction.
Some statistical techniques for assigning group
membership do not perform well when there are
many predictors. This project will investigate novel
methods of utilising large datasets of DNA markers
for predicting breed. The methods will be trialled
using sheep data with 50,000 genotypes per animal.
Identification of SNP (single nucleotide
polymorphisms) markers in Greenshell mussel
(AGR-SIS-IVY-05)
Technologies now exist that enable us to quickly
and efficiently locate, characterise, and isolate
genes linked to traits of economic importance. The
application of this information can have far reaching
benefits in terms of stock enhancement and the
identification and generation of novel commercial
products, but has thus far been applied only
sparingly to global aquaculture and never in a New
Statistics
Biology
Agriculture
Michael Lee
michael.lee@agresearch.co.nz
Invermay
Computing,
Mathematics,
Genetics
Ken Dodds
ken.dodds@agresearch.co.nz
Invermay
Statistics,
Mathematics,
Genetics
Ken Dodds
ken.dodds@agresearch.co.nz
Invermay
Bioinformatics
Anar Khan
anar.khan@agresearch.co.nz
Invermay
AgResearch Ltd
Summer Intern Scheme
Zealand context.
We are currently developing a genomic scaffold and
genetic markers for GreenshellTM mussel (Perna
canaliculus), a species that with export earnings of
NZ$202m (2009) is the cornerstone of the NZ
aquaculture industry, but which thus far has been
the subject of little genetic improvement. Interfacing
traditional animal husbandry, aquaculture and new
genomic approaches we will develop and apply a
suite of genomic tools to rapidly enhance this
species through marker based selective breeding.
Using this approach we hope to produce a product
that has, for example, more appealing colouration
and flesh characteristics, enhanced food conversion
and growth rates, heightened resistance to disease,
improved shelf life, and higher levels of valuable
nutraceutical compounds. This summer intern
project will involve the QC and analysis of next
generation sequencing data to identify SNPs (single
nucleotide polymorphisms) in the mussel genome.
This project requires a student with good
bioinformatics skills.
To summarise, the scheme involves:
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Ten weeks work over the summer vacation, 40 hours per week
Based at Invermay Agricultural Centre, Puddle Alley, Mosgiel, Dunedin (no public transport
available)
A taxable salary of $6,200
Training in research methodology
Providing written and oral presentations
For any further information or queries please contact the Project Supervisor or email
linda.murray@agresearch.co.nz
Applications close on Wednesday 14th September 2012 to:
Linda Murray
AgResearch
Private Bag 50034
MOSGIEL 9053
By Email: linda.murray@agresearch.co.nz