AlphaSimR Breeding Programme Modeling

Gregor Gorjanc is a Professor of Selective Breeding at The Roslin Institute, University of Edinburgh, where he leads the HighlanderLab focusing on population improvement through data science, genetics, and breeding. His academic journey began in Slovenia, earning an engineering degree in Animal Science (2003) and a PhD in Genetics (2010) from the University of Ljubljana, where he subsequently held a teaching position before moving to The Roslin Institute in 2013. His research encompasses three main areas: developing methods for genetics and breeding, designing and optimizing breeding programs, and analyzing phenotypic and genetic data to understand biology and improve populations. Gorjanc's expertise uniquely spans multiple domains, including data science, genetics, and breeding, with applications across diverse agricultural populations including animals, plants, and insects. His work at the HighlanderLab demonstrates his commitment to advancing selective breeding techniques through innovative approaches to population management and improvement.

Ivan Pocrnic is a Career Track Fellow at The Roslin Institute, University of Edinburgh, where he specializes in developing novel breeding methodologies and tools at the interface of theoretical quantitative genetics and practical animal breeding. His academic journey began at the University of Zagreb, Croatia, where he earned a BSc in Agricultural Economics and an MSc in Animal Genetics and Breeding. After gaining practical experience at the Croatian Agricultural Agency, he completed his PhD in Animal Breeding and Genetics at the University of Georgia under distinguished scientist Professor Ignacy Misztal. Pocrnic's expertise lies in applying genomic selection to mega-scale datasets across various species including pigs, chickens, and cattle, with a particular focus on single-step genomic prediction. His significant contributions include developing algorithms for mega-scale evaluations now implemented by major livestock breeding companies. At Roslin, he works with diverse data types, from genomic and pedigree information to productivity and environmental records, developing statistical models to predict optimal breeding strategies. His current research focuses on cross-breeding programs and the development of statistical models for analyzing genetic variability in relation to climate challenges.

Dr. Steph Smith serves as a Teaching Fellow at the University of Edinburgh's Global Academy of Agriculture and Food Systems, while also coordinating Agritech talent for the DDI Agritech hub. Her expertise bridges population genetics, molecular ecology, and evolutionary biology, with significant experience in both wild systems and domesticated species research. After completing her PhD, she spent over five years as a post-doctoral researcher studying dairy cattle at Scotland's Rural College (SRUC). In her current roles, Smith focuses on developing undergraduate and postgraduate courses while facilitating educational activities in Agritech. Her research interests center on applying genetic approaches to conservation biology and sustainable living challenges. Beyond her academic work, she actively engages in science communication, believing in the importance of making scientific research accessible to wider audiences.

Laura Strachan is a PhD student at The Roslin Institute's HighlanderLab under the supervision of Dr. Gregor Gorjanc, focusing on honeybee genetics and breeding program simulation. Her research centers on extending the AlphaSimR software package to incorporate honeybee biology, developing specialized tools for simulating honeybee breeding programs. Working at the intersection of quantitative genetics and apiculture, Strachan's work aims to explore various breeding strategies for honeybees and analyze the application of genomic data in honeybee breeding. Her research contributes to the broader field of agricultural genetics by adapting existing breeding simulation tools to accommodate the unique biological characteristics of honeybees, utilizing the SIMplyBee extension of AlphaSimR to model complex colony dynamics including queens, drones, workers, and virgin queens.

Gabriela M. Fortuna is a PhD student at the HighlanderLab, University of Edinburgh, focusing on genetics and breeding optimization of Taurine-Indicine dairy cattle, specifically the Girolando breed in Brazil. Her research aims to analyze genomic data to quantify differences between parent breeds, study dairy performance under various Brazilian environments, and develop optimized breeding strategies through digital twin simulation. A veterinary graduate from Universidade Federal Fluminense in Brazil, Fortuna completed her MSc in Animal Breeding and Genetics through the European Masters program (EMABG), studying at both the University of Göttingen and the Swedish University of Agricultural Sciences. Her master's research involved using AlphaSimR to simulate the incorporation of mitochondrial DNA variation in breeding value estimations for dairy cattle. Her current work at the HighlanderLab under Dr. Gregor's supervision aims to develop strategies for continuous improvement of adaptability and productivity in Brazilian dairy cattle through selective breeding and mating strategies based on phenotypic and genomic information.