Genetics and Health: Genetic Approaches to Reduce Bovine Respiratory Disease in Beef Cattle ORGANIZATION

Transcription

1 Genetics and Health: Genetic Approaches to Reduce Bovine Respiratory Disease in Beef Cattle Holly Neibergs Washington State University ORGANIZATION James Womack Project Director Amy Young Project Coordinator H. Burrow, A. Confer, M. Engler, D. Grooms, P. Hullinger, W. Guterbock, J. Lunney, S. McGuirk, Advisory Board Holly Neibergs Research Coordinator Alison Van Eenennaam Extension Coordinator Milton Thomas Robert Hagevoort Education Coordinators D. Bullock, N. Cohen, S. Dindot, M. Enns, L. Gershwin, R. Hagevoort, T. Lehenbauer, J.S. Neibergs, T. Ross, C. Seabury, A. Sharif, L. Skow, J. Taylor, M. Thomas, C. Tucker, C. Van Tassell, A. Zanella BRD Consortium 1

2 Introduction OUTLINE Genomic approaches to health traits Beef Aims Results Heritability Loci identified Industry focus on phenotype Moving discoveries to the industry OUTLINE Remaining Challenges Refining QTL for industry use: Identification of causal variants for commercial genotyping Industry classification of disease Best selection strategies based on pathogens Validate BRD QTL using industry disease classifications Incorporate BRD markers into selection indexes 2

3 INTRODUCTION PROBLEM Same level of morbidity and mortality from BRDC over the past 20 years despite utilizing: Best management practices Preventative vaccines Improved treatments We are using genomic approaches to reduce the incidence of BRDC in addition to current approaches 3

4 HEALTH IMPROVEMENT THROUGH SELECTION GENETIC VARIATION Is there sufficient variation in cattle to select for health traits? Yes! Single nucleotide polymorphisms (SNP) are found every 70 bp and if rare SNPs are removed, one is found every 120 bp 4

5 HOW DO WE TELL IF A HEALTH TRAIT HAS A GENETIC BASIS? Differences noted between sire lines or breeds within the same herd Heritability estimates are >0 Animals with moderate to high pathogen exposure do not become affected WHEN IS DNA TESTING MOST BENEFICIAL? Traits with low heritability, expensive to measure, occur late in life Fertility Carcass Health 5

6 DNA-BASED TESTS vabenefitblog.com DNA can be extracted from any tissue (blood, hair and semen) Receive information at any age Increases accuracy of prediction for determining which animals should be kept in the breeding population Decreases generation interval Increase selection intensity Increases rate of genetic change RESEARCH AIMS 1. Identify genomic regions associated with BRD susceptibility in beef cattle 2. Develop BRD genotyping panel that can be used by the industry for selection of cattle more resistant to BRD 6

7 IDENTIFYING QTL FOR ENHANCED BRD RESISTANCE IDENTIFYING LOCI ASSOCIATED WITH BRD Used multiple approaches: Genome wide association analysis (GWAA) Gene set enrichment analysis (GSEA-SNP) Differential gene expression of calves challenged with BRD pathogens 7

8 ANIMALS Beef 1000 Bos taurus feedlot steers from Colorado 1000 Bos taurus feedlot heifers from Washington Diagnosing BRD: McGuirk Calf Health Scoring System 8

9 NASAL SWABS MID NASAL & DEEP PHARYNGEAL BEEF PATHOGENS Pathogen CO* N=1000 WA* N= 1005 OR OR 95% CI Pvalue A pyogenes 3.4 (0.8) 0 (0) Hsomni 26.2 (12.7) 23.7 (20.1) M haemolytica 38.2 (22.5) 49.8 (39.8) P multocida 36.4 (36.1) 58.1 (52.2) Mycoplasma spp (77.9) 84.6 (77.9) BCV 17.4 (9.6) 21.3 (13.8) BRSV 2.4 (0.8) 3.8 (0.9) IBR (BHV-1) 3.2 (1.6) 2.1 (0.0) BVDV 4.9 (1.6) 1 (0.6) * Cases (controls) 9

10 BEEF HERITABILITY ESTIMATES Model Colorado (month, breed, lot/pen, days-pull, experimental year) Washington (month, breed, lot/pen, days-pull, experimental year) Combined (sex, month, breed, lot/pen, days-pull, experimental year) Case- Control Clinical Scores h 2 h BEEF GWAA Results 2 statistical approaches (EMMAX and EIGENSTRAT) produced highly concordant results for case-control and clinical scores Population Phenotype # QTL (SNPs) EMMAX #QTL (SNPs) EIGENSTRAT # Significant in both (SNPs) Colorado Case-Control 19 (22) 14 (19) 8 (8) Washington Case-Control 14 (23) 21 (36) 8 (12) Combined Case-Control 16 (48) 39 (66) 15 (35) Colorado Clinical Score 14 (19) 18 (29) 7 (9) Washington Clinical Score 14 (25) 15 (31) 8 (17) Combined Clinical Score 23 (55) 27 (61) 16 (35) 10

11 SEABURY TAMU GWAS CLINICAL SCORES COMBINED (N = 1852) 778K EIGENSTRAT Breed, days to pull, month and location as covariates COMBINED CASE-CONTROL EMMAX EIGENSTRAT Breed, days to pull, month and location as covariates 11

12 SUBCLINICAL QTL IN COLORADO BEEF Assoc. Case-Control GWAA h 2 = 0.18 Assoc. clinical score GWAA LL consist of lungs with consolidation and fibrin in between the lobes h 2 =0.19 REMAINING CHALLENGES 12

13 REFINING LOCI FOR USE BY INDUSTRY Associations of traits with DNA markers don t typically work across breeds Most valuable DNA markers are those that identify the mutations responsible for the trait (casual mutations) as they are commonly the same across breeds and don t need to be re-validated each generation WHOLE GENOME SEQUENCING IN BEEF 30 Bos taurus beef cases and 30 controls are being sequenced to identify additional variants under QTL Determine if the new markers are more informative or predictive for BRDC susceptibility for genotyping Use for imputation to whole genome sequence 13

14 IDENTIFYING CAUSAL MUTATIONS Marker panels were designed from QTL with major individual or collective effects >7,000 BRD SNPs (includes beef and dairy QTL) are part of a custom array that is genotyping all 4900 animals Markers from these, BovineHD BeadChip, and imputed genotypes to WGS will be used to choose the best markers to be used commercially INDUSTRY CLASSIFICATION OF BOVINE RESPIRATORY DISEASE QTL and heritability (0.04 to 0.24) are dependent on phenotypes collected Our studies identified temperature, cough and nasal discharge as key components in beef and dairy diagnostics (Kiser et al., 2016) Beef Beef Improvement Federation Committee adopted guidelines for feedlot identification of BRD Validating with samples from Texas commercial feedlot 14

15 BRD PATHOGENS AND SELECTION How different are pathogen profiles across the country? Selection based on specific regions, combining pathogen frequencies across regions or a combination of the two? Choose validation populations in different regions of the country Individual and meta-analysis of populations to determine best selection strategies VALIDATE QTL WITH INDUSTRY CHOSEN PHENOTYPE Phenotypes chosen by industry similar enough to McGuirk s to validate? Phenotypes high-throughput, easy or already being collected in commercial settings? Integrated with commercial record keeping software Providing markers for commercial genotyping for easy translation Integrate with industry-used selection indexes Cost/benefit analysis 15

16 CONCLUSIONS SUMMARY Identified & continue to refine QTL to provide maximum benefit and impact for beef industry Heritability is sufficient for good progress Industry involvement is critical in classification of disease, validation of QTL, integration of phenotypes into records and selection 16

17 ACKNOWLEDGEMENTS BRD CAP Funded by: National Research Initiative competitive Grant no from the USDA National Institute of Food and Agriculture and GGP F250 Funded by: National Research Initiative competitive Grant no from the USDA National Institute of Food and Agriculture BOVINE RESPIRATORY DISEASE CONSORTIUM 17