PhD Student position in Computational Genetics, Uppsala University ~

3 de abril de 2019

PhD Student position in Computational Genetics, Uppsala University

The Carlborg research group at the Department of Medical Biochemistry and Microbiology, Uppsala University, are looking for PhD student candidates for admission during the fall semester of 2019.

The research group focus on studying the genetics of complex traits
with a particular emphasis on non-additive genetic inheritance in
polygenic genetic architectures. An interdisciplinary, interspecies
approach is used, where new genetic models, statistical methods,
and bioinformatics approaches are developed to explore experimental
data from a range of species – from yeast to plants and domestic
animals. Powerful experimental datasets are obtained from a variety
of sources, including public repositories, collaborators or own
experimental work. Researchers and PhD-students in the group are
all involved in both methods development and experimental data
analyses. You can find more information about the research group at

In the fall semester of 2019, we will be able to offer up to two
candidates funding for performing their PhD studies with us. This
funding is in the form of a full time four-year employment at Uppsala
University. The position comes with salary and full benefits of being
a Swedish University employee. During the studies, the PhD candidate
will have full access to state of art computing resources and training
programs provided by SciLife & Uppsala University. Limited travel
funding for attending conference and summer schools are available
within the program. Up to 20% teaching can be requested annually,
in which case the position will be prolonged to five years. The
PhD program includes a total of 30 credits (20 weeks) of courses,
a few obligatory and most optional, the rest of the program is
own research. More information on the PhD program can be found at
The starting date is flexible, but the initial plan is for admission
during the fall semester of 2019. Review of applications will start
immediately and will continue until suitable candidates have been found.

The first half (2 years) of the PhD projects will include work with the
Virginia lines – a chicken population developed during a long-term
(60 year) bi-directional, single-trait selection experiment. This is
an excellent model to study the genetic basis of long-term selection
response on an adaptive trait that is highly polygenic. Earlier work
has shown that selection has acted on a complex genetic architecture
including loci with either tightly linked adaptive variants, multiple
segregating haplotypes and/or interactions between loci. By working with
this experimental data, the PhD students will get training and hands-on
experience with standard sequencing bioinformatics methods and tools,
as well as state of the art statistical, population and quantitative
genetics analyses. A valuable resource to the project is a dataset
including approximately 4000 phenotyped, pedigreed and individually
low-coverage sequenced individuals from a 19 generation deep advanced
intercross line between the divergently selected lines. The later half
(2 years) of the project will be decided depending on the interest and
competence of the admitted PhD student, and could therefore involve,
for example, detailed explorations of specific genetic mechanisms via
analyses of data from other species or data simulations, or more focus
on development of new models and methods for trait mapping or modeling
of genotype-to-phenotype mappings.


MSc in Bioinformatics, Statistics, Computational biology,
Quantitative/Population/Evolutionary genetics or similar qualifications
is a requirement. If the degree is not already completed, it should be
indicated when it is estimated to be obtained.

Given the analytical content of the project, it is a merit to have good
knowledge and experience of both genetics and informatics. This can be
shown through earlier research experience in the field. Programming
is an important tool in the project and therefore you should have
experience in programming in e.g. R, C++, Fortran, Perl, Python or
Java. You should have excellent English abilities, both orally and in
writing. If you are a mathematician/statistician/computer scientist,
complementary knowledge in genetics or genomics is meriting. Knowledge
in mathematics/statistics/computer science is in the same way meriting
if your exam is in biology.

If you are interested in this PhD student, send us a letter of interest
(including a description of formal qualifications, research interests and
a motivation of why this particular PhD project is something for you)
directed to Prof. Örjan Carlborg, Department of Medical Biochemistry
and Microbiology, Uppsala University;

Selected references of relevance to the project are (1-8):

1. Carlborg, Ö., Jacobsson, L., Åhgren, P., Siegel, P. &
Andersson, L. Epistasis and the release of genetic variation
during long-term selection. Nat Genet 38, 418–420 (2006).
2. Le Rouzic, A., Siegel, P. B. & Carlborg, Ö. Phenotypic evolution
from genetic polymorphisms in a radial network architecture. BMC
Biol. 5, 50 (2007).
3. Johansson, A. M., Pettersson, M. E., Siegel, P. B. & Carlborg,
Ö. Genome-wide effects of long-term divergent selection. PLoS
Genet 6, e1001188 (2010).
4. Pettersson, M., Besnier, F., Siegel, P. B. & Carlborg, Ö.
Replication and explorations of high-order epistasis using a
large advanced intercross line pedigree. PLoS Genet 7,
e1002180 (2011).
5. Sheng, Z., Pettersson, M. E., Honaker, C. F., Siegel, P. B. &
Carlborg, Ö. Standing genetic variation as a major contributor
to adaptation in the Virginia chicken lines selection experiment.
Genome Biol. 16, 219 (2015).
6. Zan, Y. et al. Artificial Selection Response due to Polygenic
Adaptation from a Multilocus, Multiallelic Genetic Architecture.
Mol Biol Evol 34, 2678–2689 (2017).
7. Forsberg, S. K. G., Bloom, J. S., Sadhu, M. J., Kruglyak, L. &
Carlborg, Ö. Accounting for genetic interactions improves
modeling of individual quantitative trait phenotypes in yeast.
Nat Genet 49, 497–503 (2017).
8. Forsberg, S. K. G. & Carlborg, Ö. On the relationship between
epistasis and genetic variance heterogeneity. Journal of
Experimental Biology doi:doi:10.1093/jxb/erx283

Örjan Carlborg
Professor in Computational Genomics
Uppsala University

Mailing address:
Department of Medical Biochemistry and Microbiology, Genomics
Box 582
SE-751 23 Uppsala

Visiting address:
Uppsala biomedical centre BMC (D11 room 311e)
Husargatan 3
SE-751 23 Uppsala

Phone: +46-18-4714592
Twitter: @OrjanGenetiker @Uppsalauni

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