- Dr. Tuggle received a PhD (1986) and completed postdoctoral training in developmental genetics (1987-1991). Dr. Tuggle joined Iowa State University in 1991 as an Assistant Professor, achieving the rank of Professor in 2001. His research projects include functional genomics and bioinformatics of the pig genome, especially in understanding control of feed efficiency and the immune response. A new project is characterizing and exploiting a serendipitous mutation in the Iowa State University Yorkshire herd that causes severe combined immune deficiency as a biomedical model.
- Research and teaching in quantitative genetics and genomics with interest in all pigs, chickens, goats and cattle and other livestock species. Applications of gene discovery to improve production and ability to withstand disease and heat stress and with emphasis on applications in developing countries.
- Genetics of feed efficiency and disease resistance. Design and optimization of breeding strategies, including use of genomics
- The focus of the Lamont lab is to elucidate the genetic and genomic architecture controlling complex biological traits, especially those related to fitness and resistance to disease, by applying contemporary technologies to the study of unique populations of chickens.
- Dr. Kolte's research focuses on identifying new ways to select for healthier, more efficient dairy cattle. Current research efforts include projects investigating the genetics of feed efficiency and use of sensors in phenotyping and breeding applications. My group also develops software and bioinformatics resources to help animal breeders and geneticists to link phenotype to genotype in livestock species.
- Whole-genome analysis; Development of statistical and computational methods for genetic improvement of livestock, especially in the area of incorporating genomic information into breeding.
- Dr. Serao's research is focused on Quantitative Genetics and Genomics of Complex Traits, such as disease/stress response and fertility in livestock animals; QTL Mapping; Genomic Prediction/Selection; Gene Expression analysis; Statistical Methods for Genomic Analyses; Big Data; Modeling of immune response, and infectious diseases; Principles of Experimentation.