Program BR22885686 – Development of a system for the genetic improvement of beef cattle breeds using innovative methods of molecular genetics, breeding, and digital technologies

Program Title: BR22885686 "Development of a System for the Genetic Improvement of Beef Cattle Breeds Using Innovative Methods of Molecular Genetics, Breeding, and Digital Technologies"

Type of funding: PCF of the Ministry of Agriculture of the Republic of Kazakhstan

Applicant: Kazakh Research Institute of Animal Husbandry and Feed Production, LLP

Principal Investigator: T.N. Karymsakov, Ph.D. in Agricultural Sciences, Associate Professor

Implementation period: 2024–2026

Relevance

Currently, beef cattle breeding in the Republic of Kazakhstan is conducted using traditional methods in accordance with the regulatory provisions of the Law "On Breeding Livestock," which was drafted as far back as the 1950s and 1960s. We believe that the main drawback of such regulations is the direct comparison of an animal's phenotype with the breed standard. Moreover, these standards have remained unchanged for the past 60–70 years. During this period, 10–15 generations have passed, which has, to some extent, influenced the genetic progress of the animals.

In addition, it should be noted that in developed countries, the breeding value of beef cattle is assessed using the best linear statistical model (BLUP), and in recent years, genomic selection has become widely adopted. These technologies make it possible to select the best individuals within a breed for further breeding with a high degree of reliability and to reduce the generation interval by 2 to 2.5 times. When selecting bulls for breeding, they are required to be tested for the presence of genetically determined diseases. Additionally, the pastures on each farm are fenced, and the entire production process is digitized.

In this regard, drawing on the experience of countries with well-developed beef cattle industries, there is a need to develop a domestic program for the development of the beef cattle industry, taking into account the economic situation, natural and climatic conditions, and the national characteristics of the Republic of Kazakhstan.

Objective

Develop a system for rapidly improving the genetic potential of beef cattle and effective technologies for beef production

In accordance with the objectives set, the following results will be achieved upon completion of the Program's activities:

  1. A reliable database of economically valuable traits for breeding bulls of the Kazakh White-headed and Auliekol breeds and their offspring has been established in the IAS, along with the creation of a DNA genetic bank;
  2. Genotyping was performed on at least 2,500 biological samples from the Kazakh White-headed breed and 1,500 from the Auliekol breed, using at least 50,000 SNPs;
  3. A bioinformatic analysis of the relationship between genes and phenotypic traits was conducted, a reference population of the Kazakh White-headed and Auliekol breeds was established, and a method for the early prediction of the breeding value of sires was developed;
  4. A methodology has been developed for calculating the economic weighting coefficients of economically important traits to determine a comprehensive index of breeding value for cattle, broken down by major breeds (Kazakh White-headed, Auliekol, Angus, and Hereford);
  5. Recommendations have been developed regarding effective grazing management techniques for beef cattle in various natural and climatic zones of the republic;
  6. Software for herd management in beef cattle farming has been developed;
  7. Studies were conducted to detect the presence of genetically determined diseases in populations of Kazakh White-headed, Auliekol, Kalmyk, and Santa Gertrud cattle breeds.

In accordance with the objectives set, the following results will be achieved upon completion of the Program's activities:

1. To establish reference populations for the Kazakh White-headed and Auliekol breeds, the IBSPR identified farms whose data on all animals showed minimal errors in accordance with standards for biological growth and development. Thus, based on the results of data analysis by farm, 9 farms were selected for breeding the Kazakh White-headed breed and 9 for the Auliekol breed. It was from these farms that 3,000 and 2,599 biological samples, respectively, were collected from the animals for further genotyping.

2. As part of the research aimed at developing scientifically sound weighting coefficients for economically important traits in beef cattle, a theoretical model was developed for constructing a comprehensive index to evaluate an animal's breeding qualities based on selected traits, namely live birth weight, at weaning (205 days), and at one year of age (365 days). An algorithm was developed for constructing a comprehensive index based on correlation relationships between traits at different stages of the animal's life and the evaluation of breeding value using the least squares method (LSM).

3. To introduce and evaluate new breeding achievements in the beef cattle industry, 10,309 head of cattle were evaluated at 5 farms breeding the Kazakh White-headed breed and 2 farms breeding the Auliekol breed, including 6,529 Kazakh White-headed and 37,802 Auliekol cattle.

Based on the results of the beef cattle evaluation, promising genotypes for further selection were identified across seven farms. Thus, at 5 farms breeding Kazakh White-headed cattle, a selection group of 1,328 cows was formed, and 492 head were selected for the breeding nucleus. For the Auliekol breed, the numbers were 1,006 and 178, respectively.

A study of the genetic groups of these animals has shown that the largest number of descendants of the Kazakh White-headed breed belong to the lines of Veteran 7880, Cactus 7969, and Viscount FR-11. In the Auliekol breed, the most common lines are those of the sires Tabakura 1350, Budilnik 825, and Zenit-Chubatyi 1060.

Thus, the studies conducted made it possible to determine the lineage of breeding bulls and the breeding herd, with the aim of identifying promising genotypes and forming separate groups of animals based on lineage.

To test the bulls for their own productivity, 325 breeding bulls of the Kazakh White-headed breed and 152 bulls of the Auliekol breed were selected. These bulls are the sons of prospective sires intended for the establishment of breeding programs and preparation for the evaluation of new breeding lines.

4. To develop effective pasture management techniques for feeding beef cattle, six model farms located in different natural and climatic zones were selected. Based on the results of pasture forage yield assessments at these model farms.

The results of the study showed that each of the pasture plots selected by the farms under study differed in terms of topography, plant species composition, and grazing periods. Therefore, for rational use, the following were proposed: seasonal "spring-summer-fall" pasture use on four farms; at the "Bereke S" farm—four-year, four-plot rotation schemes; and at the "Dauren" farm—three-year, four-plot rotation schemes.

5. To develop the herd management software, the system's core modules—such as animal registration, event logging, and user management—have been implemented and integrated. To streamline subsequent stages, data monitoring and analysis modules, as well as a reporting module, have been prepared in advance.

6. To conduct a representative study of genetically determined diseases, biological samples were collected from four breeds of beef cattle during the initial phase. In total, biological samples were collected from 390 animals of the Kazakh White-headed breed, 255 of the Auliekol breed, and 210 of the Kalmyk breed, as well as 30 samples from animals of the "Zhetisu" zonal type of the Santa Gertrudis breed. The study was conducted on four breeds raised at 50 base farms located in 15 regions of the country.

The following individuals participated in the program:

Talgat Nikolaevich Karymsakov, Ph.D. in Agricultural Sciences, Associate Professor, (https://orcid.org/0000-0003-4398-8840).

Sailubek Pernebek Zhenisbekuly, Master of Agricultural Sciences. (https://orcid.org/0000-0002-2712-7445).

Serik Ganievich Kanatbaev, Ph.D., Professor (https://orcid.org/0000-0003-0640-4316)

Ertai Kozhemzharov, Ph.D. in Agricultural Sciences, (https://orcid.org/0009-0006-8381-4246)

Kairat Zhumagaliyevich Dosybaev, PhD (https://orcid.org/0000-0003-1136-833X)

Nurgul Alikhanovna Meldebekova, Ph.D. in Agricultural Sciences, (https://orcid.org/0000-0002-5539-7506)

Kanysh Imanovich Kushenov, Ph.D. in Agricultural Sciences, (https://orcid.org/0000-0001-5298-3334)

Kanat Shanbaev, Ph.D. in Agricultural Sciences, (https://orcid.org/0000-0003-3842-0038)

Elena Anatolyevna Babich, Ph.D. in Agricultural Sciences, (https://orcid.org/0000-0003-2945-5191)

Aigul Kalyrbaevna Tadzhieva, Candidate of Agricultural Sciences (https://orcid.org/0000-0001-5621-4700, H-index – 1).

Anton Shkryl, (https://orcid.org/0009-0004-0537-2062)