Heather Huson
Associate Professor, Animal Science
Areas of Interest
Genetic Improvement of Animal Health and Production, Dairy Cattle Management and Genetic Evaluations, Population Structure and Adaptation, Genomic Tool Development, Wildlife and Indigenous Population Conservation, Canine Genetics Current Research: My research utilizes genomic tools to identify population structure and relatedness to production, adaption, and disease in animals. I specifically focus on dairy cattle and goat production and improvement through the identification of genetic markers influencing traits and those markers potential as diagnostic tools for herd management.
Research Focus
Improving Overall Dairy Cattle Performance- Numerous genetic loci have been associated with milk, fat, and protein yield, as well as reproductive traits and diseases. While geneticists can narrow these regions of interest and identify causative mutations within genes, I am also interested in looking at genetic factors of feed efficiency, fitness, and longevity in dairy cattle. These are topics either directly through "Productive Life" or indirectly through "Yield Traits", which contribute to the USDA-AIPL genomic evaluations which are commonly used by industry and farmers alike to guide breeding practices which accelerate genetic improvement. They are also topics of increased importance due to rising feed costs and a desire to improve productive longevity with decreased health costs. These are areas having less genetic background within individual breeds and across breeds, therefore being candidate topics for the identification of associated markers for improved efficiency in feed consumption and processing, and improved fitness and longevity.
Criollo Cattle Ancestry & Trait Improvement – Many tropical cattle are composite breeds, crossing naturally adapted indigenous cattle with higher production dairy and beef breeds. Utilizing admixture mapping and ancestry modeling, I would like to identify genomic loci, with corresponding ancestral haplotypes, relating to production, environmental adaptation, disease resistance, and temperament traits. Ancestral characterization of genomic regions to economically and culturally important traits would improve the efficacy of selection for propagation and genetic stabilization of desirable traits in cross-bred animals.
African Goat Improvement Project- Goats are a leading resource of animal protein in developing countries due to their hardiness, adaptability, and low cost of maintenance. Unfortunately, importation and cross-breeding of high-producing exotic dairy and meat breeds to indigenous goats has had little success because of reduced adaptability. In collaboration with the USDA and the African Goat Improvement Network, (http://www.ars.usda.gov/Research/docs.htm?docid=23247), we are identifying distinct genetic goat populations for future genetic improvement based on selection for disease and parasite resistance, climate resiliency, and improved production.
Teaching Focus
I view teaching as an opportunity to share my passion for science in a way that will not only educate but will also motivate the student to think for themselves and enjoy the topic of discussion. Genomic analysis is my tool of preference to answer scientific questions with various approaches and software being utilized to address the details of those questions. I feel that it is very important to present material in a manner appropriate and understandable for the audience and in a context in which they can relate. Therefore, I demonstrate the use of genetics with realistic and practical principles (milk yield, fat content, growth, fertility, diseases) pertaining to the subject of our research, dairy cattle, but also feel it is relevant to go beyond those boundaries to view the larger scientific impact, similarities, and differences when comparing other animals/plants (comparative genomics with humans, livestock, companion animals, and wildlife). With these teaching principles serving as a guide, the amount of research, data, and practical applications relevant to dairy cattle genomics supplies an ample source of information for an applied dairy cattle genetics course.
My background of genetic population structure, admixture mapping, and ancestry modeling also give me the tools to teach a more intensive applied genomics course. This course would address the specific details and methodologies to identify and interpret population structure and how to utilize that information to optimize future analyses such as genome-wide association studies. It would also look at the utility of admixture mapping to identify genetic relatedness and ancestral lineages. Ancestry modeling builds upon the reference ancestral lineages from admixture mapping and localizes ancestral chromosomal segments within study individuals. Over or under-representation of ancestry at a particular genomic region can be associated with phenotypic traits of interest and therefore help explain the genetics behind successful cross-bred animals. Understanding population structure with its many facets including inbreeding, admixture, and phylogeny, establish a strong foundation for future genetic analyses, herd management, biological pathway and comparative biology, conservation, and genetic improvement projects.
Education
- Doctorate
University of Alaska - 2011 - Bachelor of Science
Cornell University - 1997 - AAS
Jefferson Community College - 1995
Awards & Honors
- CALS Alumni Recognition - 2022 Rising Star Faculty Award
- Atkinson Center Faculty Fellow 2017 Atkinson Center
Courses Taught
- ANSC 2210: Principles of Animal Genetics
- ANSC 3310: Applied Dairy Cattle Genetics
- ANSC 9900: Doctoral-Level Thesis Research
- ANSC 8900: Master's Level Thesis Research
- ANSC 4990: Undergraduate Research in Animal Science
Contact Information
201 Morrison Hall
Ithaca, NY 14853
hjh3 [at] cornell.edu
Additional Links
Heather in the news
News
A massive multi-institution genomic survey of the Siberian husky has revealed that sled dogs descended from two distinct lineages of Arctic canids and originated in the northeastern Siberian Arctic generations earlier than previously thought.
- Genetics
- Animals
- Animal Science
News
- Animal Science
- Animals