Ellen Freebern

Participant: PROMISE AGEP Research Symposium

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Ellen Freebern

Department: Animal and Avian Sciences

Institution: University of Maryland, College Park (UMD)



GWAS and Fine-Mapping of Health Traits in Holstein Cattle

Health traits are of significant economic importance to the dairy industry due to the costs associated with treating infectious diseases and decreased cow performance. Genome-wide association studies (GWAS) provide a means to analyze genomic regions underlying complex traits and to identify disease-associated SNPs. The objective was to investigate the genetic basis of seven health and related traits in dairy cattle, and to explore candidate genes with expression data across tissues. GWAS and fine-mapping analyses were performed on de-regressed predicted transmitting abilities (PTA) for livability and six health traits: hypocalcemia (CALC), displaced abomasum (DSAB), ketosis (KETO), mastitis (MAST), metritis (METR), and retained placenta (RETP). The genotype data consisted of 3,148,506 selected sequence variants of over 27K bulls, which were imputed by findhap software v.3. GWAS was performed on the sequence variants using the mixed-model based association test in MMAP software. A fine-mapping procedure using a Bayesian method was conducted by assigning a posterior probability of causality (PPC) to each variant and gene. The GWAS results detected significant associations for three traits: CALC, KETO, and livability. Fine-mapping identified 23 candidate genes with the highest PPC values associated with the traits. The candidate genes were further investigated for tissue-specific expression, and three were found for DSAB, one for MAST, and three for livability. For example, a candidate gene for CALC, NDST4, is specifically expressed in the thyroid and uterine myometrium. These results provide insight to the biological relationship between genetics and disease susceptibility in dairy cattle.



I am a second year PhD student in the Animal and Avian Sciences department at the University of Maryland. I have always been interested in the STEM field, and I developed my research skills when I completed an internship in the summer of 2016 at the NIH. I received my bachelor’s degree in Biology with a minor in Biostatistics from Ursinus College in 2017. Currently, I’m pursing my graduate studies in biostatistics research. I look forward to exploring my passion further by attending research conferences and publishing manuscripts as I advance in my scientific career.



As a doctoral student at the University of Maryland, my current research project applies statistical methods to biological data. In particular, I utilize information from empirical animal and human datasets to develop a greater understanding of population genetics. The aim of my research is to develop more efficient statistical and computational approaches to improve the accuracy of genetic studies. My background is in biological science, and my other research interests include sequencing-based genetic studies and the analysis of candidate genes for disease susceptibility.



Presentation and Conference Attended:

Plant & Animal Genome Conference (PAG) – January 2019


ANSC Annual Symposium – May 2018

Completed manuscript in the publication process:

Freebern, E., Santos, D.J.A., Cole J.B., Fang, L., Jiang, J., & Ma, L. Genomic Fine-Mapping of Livability and Six Health Traits in Holstein Cattle.


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