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Future Research in Genomics

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Presentation on theme: "Future Research in Genomics"— Presentation transcript:

1 Future Research in Genomics
Curt Van Tassell AIPL Centennial Celebration November 28, 2008

2 USDA Genomics Blueprint

3 Science to Practice Genome-enabled animal selection

4 Build a Better Black Box
Genotype!! Phenotype?? New and Improved! Predicted Genetic Merit

5 Numbers continue to increase
Historic Bulls Predictor Bulls Gap Bulls Predictee Bulls Unproven Bulls Cows

6 Reliability Gain by Breed
Trait HO JE BS Net merit 23 9 3 Milk 11 Fat 33 15 5 Protein 22 4 1 Fat % 43 41 10 Protein % 34 29

7 Science to Practice Genome-enabled animal selection
Precision mating systems Embryonic selection Non-additive genetic effects Cow data Precision Management Systems Merial, Pfizer?? Animal identity and traceability Low density-SNP project

8 Low Density-SNP Project
Collaboration with Illumina 384 SNP assay using pooling ~96 dedicated to pedigree verification/traceability 378 for genetic prediction Stages of development Alpha – test of multiplex Beta – 1-3 Groups Genotyping ~20K samples Commercialization ~300K+/yr Implications Obviate need for pedigree Increase heritability of phenotypes?!

9 Discovery Science Gene discovery Deleterious recessives
Causative mutations

10 Deleterious Recessives

11 Deleterious Recessives: Strategy
Identify affected and closely related unaffected: case – control population Identify region as narrowly as possible Obtain DNA for these animals Fragment and label DNA Recover for specific region in genome DNA sequence using next-generation instrument Total cost ~ $10,000 for DNA work Proof of concept Build infrastructure Next time more rapid`

12 Causative Mutations 12

13 Discovery Science Gene discovery Functional genomics
Deleterious recessives Causative mutations Functional genomics Ongoing – e.g., gene atlas, microarrays Next-generation sequencing Host-Pathogen interaction Mastitis Rumen microbes “Meta-genomics” Systems biology The big picture

14 Gene Atlas Vitals 7.2 million tag types ~85% of all tags map to genome
6.5 % of the tag types map to within gene boundaries 61 % of the tags that map within gene boundaries map to a single gene Majority of genes show evidence of alternative splicing

15

16 Tissue Specificity Only in fetal adrenal Only in liver Of juvenile

17 BGA Gbrowse Views

18 Infrastructure Genomic tools Databases and bioinformatics
Selection tools Inbreeding management Databases and bioinformatics Build large federated databases Share information Animal resource populations Large centralized populations “Falconer” flock model, NPB Education and training Critical!!

19 Acknowledgements BARC Illumina MARC Missouri USDA/CSREES/NRI USDA/ARS
Tad Sonstegard Lakshmi Matukumalli Paul VanRaden Jeff O’Connell George Wiggans John Cole Steven Schroeder Larry Shade Dan Null Alicia Bertles Illumina Marylinn Munson Cindy Taylor Lawley Christian Haudenschild MARC Tim Smith Mark Allan Renee Godtel Linda Flathman Kevin Tennill Kevin Beavers Bob Lee Steve Simcox Tara McDaneld Missouri Jerry Taylor Bob Schnabel Stephanie McKay Jae Woo Kim Matt McClure Megan Rolf Jared Decker USDA/CSREES/NRI USDA/ARS D D D AIPL Laboratories Paul Van Raden George Wiggans Merial, Ltd Stewart Bauck Bull Studs/NAAB ABS Global Accelerated Genetics Alta Genetics CRI/Genex Select Sires Semex Alliance Taurus Service 19

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