Tools for Science and Selection: Numerical Genomics

An overview of the reasons for genomic analysis and software tool development from the final scientific report from the EU group, Sustainable Animal Breeding (SABRE) subtitled 'Cutting Edge Genomics for Sustainable Animal Breeding'.
calendar icon 28 December 2011
clock icon 4 minute read
By: Banrie

The availability of genomic data provides opportunities to understand and exploit the genetic control of complex traits to the benefit of livestock, consumers and environment. Several research groups developed software tools for genome analysis, integration of genome analysis with gene expression data as well as tools for breeding value estimation, that incorporate genomic information.

Why Analyse the Genome?

Most traits of economical importance, such as fertility, product quality and disease resistance, are normally determined by the joint effect of multiple genes and the environment. An important part of SABRE and other livestock research is the identification of genes (QTL) and pathways controlling genetic variation in these complex traits. Once genes are identified, this information can be combined with information from phenotypic data into so-called breeding values to select the best parents to produce the next generation of animals. This all happens with the expectation that the next generation will have a better performance than the current generation. For these analyses, several software packages have been developed and used within SABRE. The new aspects of these software packages compared to existing packages is that they all have the possibility to incorporate genomic information (like: DNA sequence, high-density SNP genotyping, expression profiling and proteomics).

Software Tools Developed

A detailed understanding of the genetic regulation will facilitate decisions about breeding objectives by taking account of linked effects of gene regions that may be targeted for selection. The developed software tools have already been applied within SABRE to several traits of great importance to livestock sustainability.

Software Packages

Within this project, we have enabled researchers to model interactions between QTLs. These interactions are a phenomenon called epistasis. Because these analyses are two-dimensional, the calculations are computationally very intensive. Thanks to the use of high performance computing and web-based portals for analysis, several tools are now available, free of charge, to any researcher worldwide.

GridQTL and QTLMap

GridQTL and QTLMap software tools are developed to map genes in more detail using dense genetic markers. With the increase of the number of genetic markers that can be assayed in one reaction, studies have moved from QTL mapping using family structures to genome-wide association studies (GWAS) using population samples. Wageningen UR has developed methodology for doing GWAS in livestock samples where family relationships are always present. These methods have been applied elsewhere within SABRE to the analysis of mastitis, boar taint and egg shell strength.


eQTL-soft ware has been developed for high-throughput statistical analyses of combined gene expression data and genotypic data. Regulatory genomic regions for complex traits (obesity, diabetes) and expression traits are identified by single trait analyses using either a regression method or a variance component method. Using this methodology, it is possible to identify regulatory regions affecting functionally related genes and is complementary to analyses at the level of individual expression traits.


For commercial breeding applications, the authors have developed the MiXBLUP soft ware that can estimate breeding values for selection candidates including molecular information in different ways. Furthermore, methods were developed and evaluated to deal with genotyped and non-genotyped animals in marker-assisted breeding value estimation. These methods have been applied in SABRE to analysis of mastitis resistance in Finnish Ayrshire cattle. The MiXBLUP-soft ware has been tested within the SABRE project and is now available to a wider range of users.

Further Reading

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December 2011
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