Leveraging SNP & Variation Suite to Identify putative functional mutations for Thermotolerance in Beef
Leveraging SNP & Variation Suite to Identify putative functional mutations for Thermotolerance in Beef
Heat stress is a major limiting factor of beef cattle production. Over 40% of the world’s beef cattle reside in tropical or subtropical climates known for their hot and humid conditions. When cattle experience heat stress they exhibit lower feed intake, reduced pregnancy rates and in extreme cases even death. In the U.S. alone, heat stress results in a loss of $369 million a year due to reduced animal performance. The overall goal of this project is to develop genomic tools to select for animals with superior thermal adaptation. In order to unravel the genetic architecture underlying heat tolerance this project utilizes 2,800 animals from a Bos indicus and Bos taurus crossbred population. Thermotolerance is a quantitative trait controlled by many genes and under environmental influence and it is also difficult and expensive to measure. These challenges can be overcome by collecting precise phenotypes on many of the underlying traits that contribute to an animal’s thermal adaptation. Under heat stress, cattle primarily lose heat via cutaneous evaporation at the skin-hair coat interface. Many factors affect the efficiency of evaporative cooling including sweating capacity, sweat gland properties and hair coat properties. This project not only measured continuous core body temperature of cattle in the crossbred population under low, average, and high heat stress conditions using iButton technology but also measured sweating rate and collected skin biopsies and hair samples. The skin biopsies were processed into histology slides, from which dermis thickness, sweat gland size, sweat gland number and sweat gland depth were measured. Hair samples were measured for length and diameter. These skin and hair properties have been found to have significant effects on the core body temperature under heat stress. Once thermotolerance had been described by these precise phenotypes, the genetic variants underlying these traits were characterized using genome wide association studies (GWAS) utilizing SVS. Several promising selection candidates have been identified for the hair traits through these methods. We intend to leverage the SVS software to also identify selection candidates and putative functional mutations for skin properties and ultimately perform a meta-analysis on the results of the multiple GWAS to determine the relationship of the sub phenotypes of thermotolerance to each other and also to other pertinent beef production traits.
More Related Content
More from Golden Helix
More from Golden Helix(20)
Recently uploaded
Recently uploaded(20)
Leveraging SNP & Variation Suite to Identify putative functional mutations for Thermotolerance in Beef
- 1. Department of Animal Sciences Leveraging SVS to Identify Putative Functional Mutations for Thermotolerance in Beef Cattle K.M. Sarlo Davila
- 2. Outline •Introduction •Hair Phenotypes •Skin Phenotypes •Conclusions & Future Work
- 3. What is thermotolerance? • Thermotolerance: ability to regulate body temperature in the presence of heat stress • Goals: discover genetic variants responsible for thermotolerance in beef cattle & develop genomic selection tools
- 4. Heat Stress •Heat stress limits beef production •Under heat stress: •Feed Intake •Growth •Reproduction
- 5. Economic Impact •The U.S. beef industry loses $369 million USD per year due to heat stress (St. Pierre et al., 2003)
- 6. Temperature Regulation Cooled by circulating air Heat loss through evaporation by panting and sweating Heat transferred to the ground via conduction. Direct radiation from the sun and the sky. Metabolic heat as a result of eating and digesting feed Reflected heat from ground surfaces.
- 7. Phenotypes Collected Temperature Skin Biopsy Hair Sample
- 8. Cattle Population Seminole Tribe of Florida •Commercial Brangus •2400 animals •Phenotypes collected over 3 years
- 10. A more precise phenotype •Hair collected from shoulder •Measured with ImageJ •Undercoat and Topcoat
- 11. GWAS •Objectives: identify genetic variants associated with: •Undercoat length • Topcoat length •2,161 heifers from 2016,2017 and 2018
- 12. Genotyping •DNA extracted from blood samples •Genotyped with Bovine GGP F250 array •After quality control 132,225 SNP for analysis •MAF = 0.01 •Call rate = 0.85
- 13. Association Analysis •Performed with SVS Golden Helix •Mixed model • Fitted year as fixed effect •Additive genetic model •GRM fitted to account for genetic covariance among animals •Benjamini-Hochberg FDR = 0.10
- 15. Results: Undercoat (Chu et al., 2019) •Proportion of variance in phenotype explained (PVE) or “chip heritability”= 0.24 (0.04) •SALL1 (Spalt Like Transcription Factor 1) • Transcriptional factor involved in organogenesis • PCCA (Propionyl-CoA Carboxylase Subunit Alpha) •Biotin transport and metabolism
- 17. Results: Topcoat •PVE = 0.35 (0.04) Marker PVE Gene SNP type rs135164815 0.019 PRLR Missense rs377826688 0.015 PRLR Intergenic rs383738120 0.013 PRLR Intergenic rs134538752 0.011 PRLR Splice variant
- 18. PRLR •Prolactin Receptor •SLICK mutations PRLR impacts hair length in cattle Littlejohn et al., 2014
- 19. Conclusions •These genetic variants may contribute to a shorter hair coat and more thermotolerant animals
- 20. Direct radiation from the sun and the sky. Reflected heat from ground surfaces. Cooled by circulating air Heat loss through evaporation by panting and Heat transferred to the ground via conduction. Metabolic heat as a result of eating and digesting feed Skin Characteristics sweating Sweating accounts for 85% of heat loss
- 21. Skin Histology
- 23. GWAS •Objectives: identify genetic variants associated with: •Dermis Thickness •Sweat Gland Number •Sweat Gland Area •637 heifers from 2017
- 24. Genotyping •DNA extracted from blood samples •Genotyped with Bovine GGP F250 array •After quality control 132,225 SNP for analysis •MAF = 0.01 •Call rate = 0.85
- 25. Association Analysis •Perfomed with SVS Golden Helix •Mixed model •Additive genetic model •GRM fitted to account for genetic covariance among animals •Benjamini-Hochberg FDR = 0.10
- 27. Results: Dermis Thickness •PVE = 0.038 (0.06) •GRIP1 (Glutamate receptor interacting protein 1) •Important for protein binding •Abnormal hair growth •Skin abnormalities Bladt et al., 2002
- 29. Results: Sweat Gland Number •PVE = 0.21 (0.09) •GJC3 (Gap Junction Protein Gamma 3) • Protein also called connexin • Role in formation of gap junctions • Important in skin homeostasis • (Martin & van Stenseel 2015) •SIK2 (Salt Inducible Kinase 2) • Important in regulating adipocytes
- 30. Results: Sweat Gland Area
- 31. Results: Sweat Gland Area • PVE = 0.34 (0.09) •GRIP1 •Skin & hair abnormalities •TRAPPC6B (trafficking protein particle complex 6B) •Vesicle transport •Membrane trafficking
- 32. Conclusions •These genetic variants may contribute to sweating and more thermotolerant animals •Relationship between traits
- 33. Future Work •Leverage SVS to: • Identify putative functional mutations •Determine relationship between thermotolerance traits and production traits
- 34. Acknowledgements •Dr. Raluca Mateescu • Eduardo Rodriguez • Gabriel Zayas • Andrea Nuñez • Serdal Dikmen •Golden Helix Abstract Competition •USDA-NIFA Grant 2017-67007-26143 •UF ANS Hatch Project •Seminole Tribe of Florida, Inc. •Alyssa Howell •Arseia Orelien •Victoria Roe •Dani Salces
Editor's Notes
- GSTA5 - Glutathione S transferase alpha 5 Peak at 10 -
- Missense, intergenic, intergenic, splice variant
- When air temperature greater than 30C