WO2005078133B1 - Marker assisted best linear unbiased predicted (ma-blup): software adaptions for practical applications for large breeding populations in farm animal species - Google Patents

Abstract

The invention provides methodologies for improved molecular genetic analysis of individual animals and animal populations. The invention includes methods and systems for identifying those animals in a population that are most likely to heritably pass on desirable traits. Provided are means for evaluating the estimated breeding values and increasing the average genetic merit for animals in a population. For each trait, the instant invention provides methods for evaluating the relative effect of one or more quantitative trait loci (QTL) and three or more molecular genetic markers for each QTL. The relationship between these various markers and the pre-selected trait and QTL is calculated, along with the contribution of other factors such as pedigree and known measures with respect to quantitative trait, and these data are used to calculate estimated breeding values for the animals in the herd and to rank the animals according to these estimated breeding values.

Claims

AMENDED CLAIMS Received by the International Bureau on 09 February 2006 (09.02.2006)

1. A method of increasing an animal population's average genetic merit, comprising; a. selecting one or more traits for which an improved genetic merit is desired: b. selecting one or more quantitative trait locus (QTL) for each selected trait; c. selecting three or more molecular genetic markers of interest for each QTL for each selected trait; d. providing databases comprising: i. genotype data for three or more molecular genetic markers for each selected trait, for a plurality of animals in the population; ii. data providing the pedigree for each animal in the population; iii. optionally, data for one or more fixed effects; e. using a computer program capable of performing a marker assisted best linear unbiased prediction to simultaneously analyze the data from the provided databases to calculate a ranking of the animals; wherein the computer program uses a variable-size block-diagonal preconditioned gradient (PCCG) algorithm to rank the animals; wherein the animals are ranked according to their estimated breeding value (EBV) for the selected molecular genetic markers and, if provided, quantitative traits.

2. The method of 1 further comprising using the calculated EBVs to prepare a breeding plan for the animal population that provides for optimal improvement in the genetic merit of the population.

3. The method of claim 1 wherein the animal population is a swine herd.

4. The method of claim 1 wherein the trait is selected from the group consisting of: efficient growth traits, meat quality traits, reproduction traits, and health traits.

5. The method of claim 1 wherein the molecular genetic markers are selected from any polymorphism known to affect expression of the mRNA or protein from a gene.

6. The method of claim 5 where the polymorphism is selected from the group consisting of: single nucleotide polymorphisms, simple sequence repeats, protein point mutations, and gene isoforms. 7. The method of claim 3 wherein at least one molecular genetic marker is selected from those markers known to modulate a favorable phenotype.

8. The method of claim 3 wherein at least one of the molecular genetic markers is a marker for selected from the group consisting of: a single nucleotide polymorphism in the porcine PRKAG3 (protein kinase, AMP-activated gamma-3 subunit) gene, and a polymorphism in the porcine melanocortin-4-receptor.

9. The method of claim 3 wherein at least one of the molecular genetic markers is a marker for a single nucleotide polymorphism in the porcine PRKAG3 gene.

10. The method of claim 1 wherein the computer program uses an iteration-on-data (IOD) algorithm.

12. The method of claim 1 wherein the output of the computer program further comprises results that indicate the informativeness of one or more of the selected molecular genetic marker for at least one quantitative trait locus (QTL) and/or a calculation of the genetic closeness/proximity of one or more molecular markers to at least one QTL.

13. The method of claim 12 wherein the molecular genetic markers having the highest degree of informativeness and/or closeness for at least one QTL are identified.

14. The method of claim 1 wherein the computer program utilizes a scripting feature to improve the ease of user interface.

15. The method of claiml wherein the selected molecular genetic markers comprise a marker haplotype.

16. A system for increasing an animal population's average genetic merit for at one or more selected traits, the system comprising: a. a computer; b. a computer accessible database providing data on one or more quantitative trait locus (QTL) for each selected trait; c. a computer accessible database providing data, for animals in population, for three or more molecular genetic markers for each selected QTL for each selected trait; d. a computer accessible database providing pedigree data for animals in the population; e. optionally, a computer accessible database providing individual data for each animal in the population for at least one fixed effect; f. a computer program capable of performing marker-assisted best linear unbiased prediction and simultaneously evaluating the data in all databases and ranking the animals in the population according to their respective estimated breeding value for each of the selected traits; wherein the computer program uses a variable-size block-diagonal preconditioned gradient (PCCG) algorithm to rank the animals; g. a user interface including a data entry system, said user interface coupled to said computer and configured to allow the user to instruct the computer to access the available databases and use the computer program to generate output that includes a ranking of the animals according to their estimated breeding values and/or their individual estimated breeding values.

17. The system of claim 16 wherein the animal population is a swine herd.

18. The system of claim 17 wherein at least one of the molecular genetic markers is selected from the group consisting of markers for the porcine PRKAG3 gene and the gene encoding the melanocortin-4-receptor.

19. The system of claim 17 wherein at least one of the molecular genetic markers is a marker for a single nucleotide polymorphism in the porcine PRKAG3 gene.

20. The system of claim 17 wherein the selected molecular genetic markers comprise a marker haplotype.

21. A system for identifying the molecular genetic marker(s) having the highest degree of informativeness for one or more selected quantitative trait locus (QTL), the system comprising: a. a computer; b. a computer accessible database providing individual data, for animals in population, for three or more molecular genetic markers for each selected quantitative trait locus; c. a computer program capable of simultaneously evaluating the data in all databases and determining the relative informativeness for each of the molecular genetic markers for which data is provided; wherein the computer program is capable of performing marker-assisted best linear unbiased prediction and uses a variable-size block-diagonal preconditioned gradient (PCCG) algorithm to determine the relative informativeness of each molecular genetic marker; d. a user interface including a data entry system, said user interface coupled to said computer and configured to allow the user to instruct the computer to access the available databases and use the computer program to generate output that includes a indication of the informativeness of each molecular genetic marker for which data was provided.

22. The system of claim 21 wherein the quantitative trait locus is selected from any locus known to be associated with a known trait.

23. The system of claim 21 wherein the quantitative trait locus is selected from any locus for traits selected from the group consisting of efficient growth traits, meat quality traits, reproduction traits, and health traits.

24. The system of claim 21 further comprising providing computer accessible database(s) containing individual data for animals in the population for at least one fixed effect; wherein the computer executable program is capable of simultaneously evaluating the data in all provided databases and ranking the animals in the population according to their respective estimated breeding value for each of the selected traits.

25. The system of claim 21 wherein the selected molecular genetic markers comprise a marker haplotype.

29. The method of claim 1 further comprising using the animals' ranks to identify the optimal breeding pairs in the population.

30. The method of claim 29 wherein the selected molecular genetic markers comprise a marker haplotype. 31. A method of enhancing one or more meat quality trait(s) in pigs, the method comprising: a) screening a plurality of pigs to identify the nature of one or more single nucleotide polymorphisms (SNPs) in the porcine PRKAG3 gene, wherein said SNP(s) is/are selected from the group consisting of: an A/G at position 51, A/G at position 462, A/G at position 1011, C/T at position 1053, C/T at position 2475, A/G at position 2607, A/G at position 2906, A/G at position 2994, and C/T at position 4506, wherein all numbering is according to the sequence of SEQ ID NO:1 and identifying those having a desired allele; b) selecting those pigs identified as having a desired allele; c) using the selected pigs as sires/dams in a breeding plan to produce offspring; wherein the offspring have an increase frequency of the desired allele.

32. The method of claim 31 wherein the presence or absence of the polymorphism is determined by a method selected from the group consisting of: DNA sequencing, restriction fragment length polymorphism (RFLP) analysis, heteroduplex analysis, single strand conformational polymorphism (SSCP) analysis, denaturing gradient gel electrophoresis (DGGE), real time PCR analysis (TAQMAN®), temperature gradient gel electrophoresis (TGGE), primer extension, allele-specific hybridization, and INVADER® genetic analysis assays.

33. The method of claim 31 wherein at least one meat quality trait is selected from the group consisting of increased pH and decreased 7-day purge.

34. A kit for detecting the nature of one or more polymorphisms in the porcine PRKAG3) gene; the kit comprising a means for detecting for detecting the polymorphism in the

DNA and or RNA from the gene; wherein the polymorphisms are selected from the group consisting of one or more of the following SNP(s): an A/G at position 51, A/G at position 462, A/G at position 101I₅ C/T at position 1053, C/T at position 2475, A/G at position 2607, A/G at position 2906, A/G at position 2994, and C/T at position 4506, wherein all numbering is according to the sequence of SEQ ID NO: 1. 35. The kit of claim 34 whereby the polymorphism is detected by one or more of the following means of detection: DNA sequencing, restriction fragment length polymorphism (RFLP) analysis, heteroduplex analysis, single strand conformational polymorphism (SSCP), denaturing gradient gel electrophoresis (DGGE), polymerase chain reaction (PCR), real time PCR analysis (TAQMAN®), temperature gradient gel electrophoresis (TGGE), enzyme linked immunosorbent assay (ELISA) and other immunoassay; wherein the kit comprises one or more of the following: a restriction endonuclease enzyme, a DNA polymerase, a reverse transcriptase, a buffer, deoxyribonucleotides, an oligonucleotide suitable for use as a DNA or RNA probe, an oligonucleotide suitable for use as a primer in DNA or RNA synthesis, a fluorescent marker, and an antibody.

36. An oligonucleotide suitable for use in a kit according to claim 35.

37. The oligonucleotide of claim 36 selected from primers comprising the sequence of any of the primers listed in Table 1 (SEQ ID NO:2-17).

38. The oligonucleotide of claim 36 selected from the group consisting of the primers provided in Table 1 (SEQ ID NO:2-17).