Prof. Dr. István Nagy - MATE Research
Overview
Dr Gábor Markó is a behaviour ecologist who works at the Institute of Plant Protection. His expertise covers several fields of study and reflects a multidisciplinary approach to agricultural, ecological and behavioural sciences. Dr. Markó's research program is diverse and aims to understand the different aspects of complex ecological systems and their interactions with human activities. He uses various model organisms in urban, agricultural and natural habitats to address these issues. One of his current areas of focus is deepening our understanding of plant pathogen infection mechanisms and the factors that affect it. This research could be crucial in preventing and controlling the spread of harmful organisms. Dr. Markó actively participates in various international scientific collaborations.
Prof. Dr. István Nagy DSc. is a professor at the Institute of Animal Sciences, MATE, Kaposvár Campus, the head of the Animal Breeding Department. He is a senior member of the Agricultural and Food Sciences Doctoral school, the head of the Hungarian Branch of the World Rabbit Science Association (WRSA) and member of EAAP working group representing East and Central Europe.His main field of interests involve breeding value estimation in rabbits and pigs, quantitative genetics, especially inbreeding related topics. In the Hungarian animal breeding he introduced several novel concepts like Bayesian inference, ROC Curves, partial inbreeding, ancestral inbreeding, genetic purging and hidden individual inbreeding load. He authored or co-authored 107 publications that were referenced in SCOPUS. His Hirsch index is 27. Based on his scientific achievements in 2025 he received the Darányi Ignác award.
Research keywords:
Publications
Projects
Genetic evaluation of the dominance effect in domesticated rabbits (K 106175)
In the course of this project three populations of different rabbit genotypes (Pannon White breed, Pannon Ka (maternal line) and Pannon Terminal line) will be analyzed from quantitative genetic aspects. The main objective of this study is to estimate genetic parameters (additive genetic effects, dominance effects), inbreeding depression and breeding value stability for the available reproductive (number of kits born alive, number of kits born dead, total number of born kits and litter weight at day 21), growth (average daily gain between the ages of 5 and 10 weeks) and slaughter (thigh muscle volume, thigh muscle weight, dressing out percentage, perirenal fat weight, intramuscular fat weight and ratio of the hind part of the carcass) traits using different animal models.
Analysis of purging and likelihood of genetic death in Pannon White rabbit and Border Collie dog populations (K 128177)
In the course of this project two populations (Pannon White rabbit breed and Hungarian Border collie dog) will be analysed from complex inbreeding aspects. The main objectives of this study are to estimate genetic parameters, inbreeding depression (including number of lethal equivalents and likelihood of genetic death) for the available reproductive traits (number of kits born alive, number of kits born dead, total number of born kits and survival rate at birth) of the rabbits and genetic diseases (Collie eye anomaly, trapped neutrophil syndrome, elbow and hip dysplasia) of the Hungarian Border collie dogs. Ancestors carrying inbreeding load will be identified which can subsequently be utilised getting rid of their contribution to inbreeding of future generation.
Assessment of Inbreeding Burden in Hungarian Breeds: Challenging Technological Solutions to Improve Genetic Health and Resilience (NKFI ADVANCED 150863)
Our main objective in this project is to improve the current estimation of harmful inbreeding burden based on pedigree phenotype or whole genome sequence (WGS) information, focusing on advanced technological solutions to improve the monitoring and management of harmful inbreeding load in several important Hungarian breeds (Mangalica pigs, Pannon rabbits and Thoroughbred horses). The scientific challenges are in particular: i) the development of software to calculate sex-specific classical and ancestral inbreeding coefficients, ii) the estimation of inbreeding depression and purging, iii) the prediction of individual inbreeding load and iv) the quantification of harmful mutation load using WGS information.
