Animal Breeding and Genetics announces Lush Visiting Professors and Short Course Programs for 2018

Event
Monday, May 7, 2018 - 8:00am
Event Type: 

Lush Visiting Professors and Short Courses in Animal Breeding and Genetics

The Animal Breeding and Genetics Group of the Department of Animal Science is pleased to announce the Lush Visiting Professors and Short Courses Program for 2018. The Lush Visiting Professors program will bring three premier scientists in the fields of Quantitative Genetics and Animal Breeding to Iowa State University for up to 2 months each, during which they will offer short courses that will be open for registration by all interested:

Dr. JOHN HICKEY from the Roslin Institute (https://www.ed.ac.uk/roslin/about/contact-us/staff/john-hickey) will be a Lush Visiting Professor at Iowa State University in April and May, 2018.

Dr. Hickey will give a 2-day short course May 10 and 11 entitled "Plant and animal breeding – exploiting new technologies in different ways and at different scale”. A course synopsis is given at the end of this message. For registration, please go to the following site: http://bit.ly/2018abg  

NOTE: this course immediately follows two other conferences/workshops that will be held at Iowa State University during that same week (these require separate registration at the websites given)

- May 7&8       Predictive Inference and its Applications.   Register at:   https://predictiveinference.github.io/

- May 9           Statistical Machine Learning Symposium.  Register at:   https://register.extension.iastate.edu/msmlc 

- May 10&11   Hickey and Gorjanc Short course.              Register at:   http://bit.ly/2018abg  

Dr. HENNER SIMIANER from the University of Goettingen (https://www.uni-goettingen.de/en/104188.html) will be a Lush Visiting Professor at Iowa State University in August and September, 2018

Dr. Simianer will give a short course August 13-17 entitled: "Mapping signatures of selection with applications to animal breeding populations”. Registration details will follow later. A course synopsis is given below.

Dr. DAN GIANOLA from the University of Wisconsin (http://www.ansci.wisc.edu/Facultypages/gianola.html) will be a Lush Visiting Professor at Iowa State University in September and October, 2018

Dr. Gianola will teach a course on “Prediction of Complex Traits”, with timing and details to be announced later.

Course synopsis: "Plant and animal breeding – exploiting new technologies in different ways and at different scales” by Drs. John Hickey and Gregor Gorjanc,  May 10 and 11, 2018. Registration at: http://bit.ly/2018abg

There are many emerging and new technologies that could have application in livestock and plant breeding programs. These technologies present new opportunities to increase the rates of gain and or to increase the efficiency of breeding programs. Some of the technologies can be implemented in small scale breeding programs, others require large amounts of infrastructure. Some require subtle changes to existing breeding program designs, others require fundamental changes. One route to discovering the optimal way to use these technologies is to harness stochastic simulation within the context of the breeders equation with constrained economic resources.  

The objective of this short course is to equip the participants with techniques and tools to think about how such technologies could be exploited. Specifically this will include:

1.       Compare and contrast existing breeding program designs in different plant and animal species

2.       Overview of different emerging and new technologies (e.g., sequence, genotype, phenomics, gene editing, manipulation of recombination) and some thoughts about how they can affect breeding programs

3.       Use of the breeders equation and stochastic simulation to explore different applications of such technologies

4.       Optimal contribution selection and the manipulation of recombination

5.       Genotyping and sequencing strategies and their optimisation

6.       Phasing and imputation methods

7.       Mechanics of genomic prediction

The course targets graduate students and researchers interested in animal and plant breeding. Basic knowledge of quantitative and molecular genetics, linear mixed models, and elementary probability and statistics is expected, as well as a working knowledge of R. Bring a laptop with R installed.

Course Synopsis: "Mapping signatures of selection with applications to animal breeding populations” by Drs. Henner Simianer and Christian Reimer, August 13-17, 2018. Registration details will follow later.

The course aims at providing insight into current approaches to detect patterns selection has left in the genomes of livestock populations. While most selection signature approaches were developed in an evolutionary context, we will focus on statistics that can be used to reveal patterns caused by recent and ongoing selection.

Starting with an introduction to the relevant quantitative genetic and population genetic framework, the basic selection signature statistics usable for within and between population analyses will be introduced. We will review several possibilities to derive empirical null distributions for statistical testing and will address the power of different statistics and factors affecting the power, before an overview of the portfolio of current methods of signature of selection detection methods will be presented An approach to improve power and positional resolution by combining different statistics will be discussed, as well as integrating SNP based results for larger functional units, like genes or pathways. If time permits, ways of annotation of detected loci and regions to enable interpretation of functional  consequences of selection will be introduced. We also will discuss possible validation strategies and approaches to detect selection for (quasi-) infinitesimal traits.

The teaching of theoretical concepts will be illustrated with practical exercises, both with simulated selection using an R-script and with applications to real array- and NGS based data sets. The required data formats, pipelines and free software tools will be introduced. A short introduction to variant calling from NGS data optionally can be offered.

Students taking the course are expected to have a solid background in quantitative and population genetics and selection theory (Falconer & Mackay level) and basic statistical inference. They should be familiar with R and with working with scripts in a UNIX/LINUX environment. Participants will be expected to bring their own laptop with pre-installed software (instructions will be circulated in advance of the course). In principle the course would also be interest to those working on plant breeding and natural populations, although the focus will be on recent rather than historical selection.