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National Institute for Applied Statistics Research Australia Seminar Series

July 10 @ 10:30 am - 11:30 am

Speaker:

Valeria Paccapelo

Senior Biometrician

Department of Agriculture and Fisheries QLD

Title:

A whole‑genome QTL analysis for NAM populations

Abstract:

In plant breeding, the nested association mapping (NAM) strategy can provide a high-power and fine resolution QTL mapping tool. In a NAM population, the QTL analysis needs to incorporate the population design, the founder genetic data and a large number of molecular markers. We propose a whole-genome QTL analysis for NAM populations that models raw phenotypic data in a single-stage linear mixed model including terms for population design and marker effects.

Genetic dissection of quantitative traits in plants has become an important tool for breeding improved varieties. Multi-parent populations, such as multi-parent advanced generation inter-cross (MAGIC) and nested association mapping (NAM) populations, have been developed to combine the strengths of conventional QTL mapping in bi-parental populations and association mapping in diversity panels. Multi-parent populations capture more recombination events and greater allelic diversity than a bi-parental population while reducing the problem of rare allele frequencies present in diversity panels. NAM populations consist of multiple families of recombinant inbred lines (RIL) resulting from crosses between a single common reference parent and a different parental donor for each family. Compared to traditional QTL analysis, the NAM strategy presents additional challenges such as, the population design, the need to incorporate the founder genetic data, and the large number of molecular markers. We propose a whole-genome QTL mapping method for NAM populations that is adapted from the multi-parent whole genome average interval mapping (MPWGAIM) approach. The population design and founder genetic data is incorporated through the known probability of inheriting founder alleles for every marker across the genome simultaneously. Our method can also accommodate a multiple reference-parent NAM (MR-NAM) population structure with donors in common between reference parents to increase genetic diversity. This method, based on a linear mixed model, provides a single-stage analysis of raw phenotypic data, molecular markers and population design. It simultaneously scans the whole-genome through an iterative process leading to a model with the full set of significant QTL. The method was developed in R, with main dependencies being the R packages MPWGAIM and ASReml. The QTL analysis method was demonstrated using a wheat MR-NAM population in order to perform QTL mapping for plant height. This approach establishes the basis for further QTL mapping studies for NAM and MR-NAM populations.

References

Butler, D. G., Cullis, B. R., Gilmour, A. R., Gogel, B. J. (2009). ASReml-R reference manual. The State of Queensland, Department of Primary Industries and Fisheries, Brisbane.

Verbyla, A. P., George, A. W., Cavanagh, C. R., Verbyla, K. L. (2014). Whole-genome QTL analysis for MAGIC. Theoretical and applied genetics 127, 1753-1770.

Yu, J., Holland, J. B., McMullen, M. D., & Buckler, E. S. (2008). Genetic design and statistical power of nested association mapping in maize. Genetics 178, 539-551.

This is a joint with Kelly A1, Christopher J2 and Verbyla A3

1 Queensland Department of Agriculture and Fisheries, Toowoomba, QLD 4350, Australia

2 University of Queensland, Queensland Alliance for Agriculture and Food Innovation, Toowoomba, QLD 4350, Australia

3 Data61, CSIRO, Atherton, QLD 4883, Australia

 

 

 

Details

Date:
July 10
Time:
10:30 am - 11:30 am
Events Categories:
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Events Tags:
Website:
https://niasra.uow.edu.au/index.html

Organiser

NIASRA
Phone:
Pauline O'Shaughnessy
Website:
https://niasra.uow.edu.au/index.html

Other

Speaker
Valeria Paccapelo

Venue

Building 39A Room 208
University of Wollongong
Wollongong, NSW Australia
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