Assessing the population structure and genetic variability of Kenyan native goats under extensive production system.

Indigenous goats are important to many livelihoods. Despite this, they are subjected to indiscriminate crossbreeding. This affects their genetic variability which is needed to survive in current regime of climate change. The study assessed population structure and genetic diversity of Galla and Small East African goats (SEA) using pedigree information. A total of 7384 animals, 5222 of the Galla and 2162 of the SEA breeds, born between the years 1983 and 2022, were utilized. Individuals with known parents were defined as reference population. From the results, the maximum generation traced for Galla and SEA populations was 14.6 and 14.5, respectively. However, only 6 and 5 generations for Galla and SEA were complete. Pedigree completeness increased with the increasing number of generations. The average generation interval (GI) for Galla and SEA was 3.84 ± 0.04 and 4.4 ± 0.13 years. The average increase in the rate of inbreeding per generation for Galla and SEA was 0.04 and 0.05, with the effective ancestors and founders (fa/fe) ratio being same (1.00) for both breeds. Fifty percent (50%) of the genetic variability in the populations was contributed by 3 and 1 ancestor for Galla SEA, respectively. The effective population size (Ne) was 5.19 and 4.77 for Galla and SEA. Therefore, the current breeding programs should be changed to avoid future genetic bottlenecks in this population. These findings offer an opportunity to enhance the current genetic status and management of Kenyan native goats and other regions with similar production systems.

Buzzing with Intelligence: Current Issues in Apiculture and the Role of Artificial Intelligence (AI) to Tackle It.

Honeybees (Apis mellifera L.) are important for agriculture and ecosystems; however, they are threatened by the changing climate. In order to adapt and respond to emerging difficulties, beekeepers require the ability to continuously monitor their beehives. To carry out this, the utilization of advanced machine learning techniques proves to be an exceptional tool. This review provides a comprehensive analysis of the available research on the different applications of artificial intelligence (AI) in beekeeping that are relevant to climate change. Presented studies have shown that AI can be used in various scientific aspects of beekeeping and can work with several data types (e.g., sound, sensor readings, images) to investigate, model, predict, and help make decisions in apiaries. Research articles related to various aspects of apiculture, e.g., managing hives, maintaining their health, detecting pests and diseases, and climate and habitat management, were analyzed. It was found that several environmental, behavioral, and physical attributes needed to be monitored in real-time to be able to understand and fully predict the state of the hives. Finally, it could be concluded that even if there is not yet a full-scale monitoring method for apiculture, the already available approaches (even with their identified shortcomings) can help maintain sustainability in the changing apiculture.

A Review on Indigenous Goats of East Africa: A Case for Conservation and Management.

Indigenous goats are important in the livelihoods of rural households in East African countries. This is due to their ability to produce and reproduce in different environments and climatic conditions. Even though these indigenous goats are important, there is little available information on the genetic characterization of these breeds in Africa and at the international level. This paper reviews the status of indigenous goats, highlighting their production systems, phenotypic and genetic characteristics, and genetic diversity, and proposes potential ways for sustainable improvement and conservation in East African countries. Most households use traditional production systems with various uncharacterized goat breeds and ecotypes, which are hence named after the tribe or locality in which they are found. Most of these goats are classified as small East African breeds, with significant variability in morphological features. Some of the challenges to goat production in this region are indiscriminate crossbreeding, lack of pedigree records, parasites and disease incidences, low-quality pastures, and low levels of management. There is a need for a collaborative approach amongst the actors in goat breeding value chains as well as integrating modern genomic tools into breeding programs to enhance selection. This will ensure the resilience and sustainability of these unique indigenous goat populations in East Africa.

Climate change and dairy farming sustainability; a causal loop paradox and its mitigation scenario.

It is arguable at this time whether climate change is a cause or effect of the disruption in dairy farming. Climate change drastically affects the productive performance of livestock, including milk and meat production, and this could be attributed to the deviation of energy resources towards adaptive mechanisms. However, livestock farming also contributes substantially to the existing greenhouse gas pool, which is the causal of the climate change. We gathered relevant information from the recent publication and reviewed it to elaborate on sustainable dairy farming management in a changing climatic scenario, and efforts are needed to gather this material to develop methods that could help to overcome the adversities associated with livestock industries. We summarize the intervention points to reverse these adversities, such as application of genetic technology, nutrition intervention, utilization of chemical inhibitors, immunization, and application of metagenomics, which may help to sustain farm animal production in the changing climate scenario.

Hungarian indigenous Tsigai, a promising breed for excellent heat tolerance and immunity.

The adverse effects of climate change on sheep farming have become more noticeable in recent decades. Extensive efforts have been made to untangle the complex relationship between heat tolerance, animal health, and productivity, also to identify a resilient and economically suitable breed for selection that can be resilient to future climate change conditions. Using quantitative real-time polymerase chain reaction (qRT-PCR), we observed the seasonal variations in the expression of several important genes related to heat stress and immunity (HSP70, IL10, TLR2, TLR4, and TLR8) in three of the most widely kept sheep breeds in Hungary: The indigenous Tsigai, Hungarian Merino, and White Dorper. We found that the seasonal stressor affected the relative gene expression of all genes in this study. Notably, The Hungarian indigenous Tsigai was the most robust breed adapted to the Hungarian continental (hot summer, cold winter) environment, with excellent thermotolerance and immunity. Furthermore, despite suffering from heat stress in the summer, Hungarian Merino maintained their robust immune system well throughout the year.

Genetic polymorphism in European and African sheep breeds reared in Hungary based on 48 SNPs associated with resistance to gastrointestinal parasite infection using KASP-PCR technique.

This pilot study used an alternative and economically efficient technique, the Kompetitive Allele-Specific Polymerase Chain Reaction (KASP-PCR) to examine 48 SNPs from 11 parasite-resistance genes found on 8 chromosomes in 110 animals from five sheep breeds reared in Hungary; Hungarian Tsigai, White Dorper, Dorper, Ile de France, and Hungarian Merino. Allele and genotype frequencies, fixation index, observed heterozygosity, expected heterozygosity, F statistic, and their relationship with the Hardy-Weinberg equilibrium (WHE) and the polymorphic information content (PIC) were determined, followed by principal component analysis (PCA). As much as 32 SNPs out of the 48 initially studied were successfully genotyped. A total of 9 SNPs, 4 SNPs in TLR5, 1 SNP in TLR8, and 4 SNPs in TLR2 genes, were polymorphic. The variable genotype and allele frequency of the TLRs gene indicated genetic variability among the studied sheep breeds, with the Hungarian Merino exhibiting the most polymorphisms, while Dorper was the population with the most SNPs departing from the HWE. According to the PIC value, the rs430457884-TLR2, rs55631273-TLR2, and rs416833129-TLR5 were found to be informative in detecting polymorphisms among individuals within the populations, whereas the rs429546187-TLR5 and rs424975389-TLR5 were found to have a significant influence in clustering the population studied. This study reported a moderate level of genetic variability and that a low to moderate within-breed diversity was maintained in the studied populations.

Assessing the Genomics Structure of Dorper and White Dorper Variants, and Dorper Populations in South Africa and Hungary.

Dorper sheep was developed for meat production in arid and semi-arid regions under extensive production systems in South Africa. Two variants with distinct head and neck colors were bred during their development process. White Dorper have a white coat while Dorper have a black head and neck. Both variants have grown in popularity around the world. Therefore, understanding the genomic architecture between South African Dorpers and Dorper populations adapted to other climatic regions, as well as genomic differences between Dorper and White Dorper variants is vital for their molecular management. Using the ovine 50K SNP chip, this study compared the genetic architecture of Dorper variants between populations from South Africa and Hungary. The Dorper populations in both countries had high genetic diversity levels, although Dorper in Hungary showed high levels of inbreeding. White Dorpers from both countries were genetically closely related, while Dorpers were distantly related according to principal component analysis and neighbor-joining tree. Additionally, whereas all groups displayed unique selection signatures for local adaptation, Dorpers from Hungary had a similar linkage disequilibrium decay. Environmental differences and color may have influenced the genetic differentiation between the Dorpers. For their molecular management and prospective genomic selection, it is crucial to understand the Dorper sheep's genomic architecture, and the results of this study can be interpreted as a step in this direction.

An On-Station Analysis of Factors Affecting Growth Traits of Pure Red Maasai and Dorper Sheep Breeds under an Extensive Production System.

This comparative study aimed to evaluate genetic and environmental factors' effects on the growth traits of lambs in Dorper and Red Maasai (RedM) sheep breeds. The data analyzed contained the following measurements: birth weight (Bwt), weaning weight (Wwt), yearling weight (Ywt), birth type (single or twins), and details on each lamb's dam (dam ID and age) and sire. Except for the RedM, whose birth weight decreased with time, both breeds generally showed an increase in other growth weights across the study period, with yearly variations affecting both breeds. Additionally, analysis by a linear mixed model with restricted maximum likelihood (REML) showed that only breed as a factor significantly (p < 0.05) influenced birth weight; breed, sex, and birth type all significantly (p < 0.05) influenced weaning weight, whereas season, sex, and dam age significantly (p < 0.05) influenced yearling weight. The RedM breed outperformed the Dorper breed in post-weaning growth rate, demonstrating early resilience and adaptation to local environmental factors independent of maternal influence. Breed and non-genetic factors play a vital role in the growth of lambs, and the results of this study offer an opportunity for improved farm management under an extensive production system and selection for the conservation of the indigenous Red Maasai breed.

Validation of SNP markers for thermotolerance adaptation in Ovis aries adapted to different climatic regions using KASP-PCR technique.

A study on 51 SNPs belonging to 29 genes related to heat stress was carried out in 720 sheep from 17 different breeds adapted to different climates from Hungary, Bosnia and Herzegovina, Morocco and Romania, using Kompetitive Allele-Specific Polymerase Chain Reaction. Genotype frequency and the Hardy-Weinberg equilibrium were calculated, followed by a clustering using the Principal Component Analysis. We analyzed the polymorphisms in the following genes analyzed: HSPA12A, HSP90AA1, IL33, DIO2, BTNL2, CSN2, ABCG1, CSN1S1, GHR, HSPA8, STAT3, and HCRT. We emphasized on HSPA12A and HSPA8 genes as they were successfully genotyped in all studied flocks in which genotype frequency patterns were identified. Contrary to previous findings, the A allele for HSPA8 SNP was not observed in the heat tolerant breeds, being found exclusively in cold-tolerant breeds. The principal component analysis could not clearly differentiate the breeds, while plot concentration was slightly varied among the three groups, with HSP90AA1 and IL33 SNPs' loading values significantly contributing to PC1 and PC2. We confirmed previous works that the HSPA12A, HSPA8, HSP90AA1 and IL33 SNPs are potential candidate markers for thermotolerance adaptation in sheep. This research contributes to the genetic variability of SNPs for thermotolerance adaptability in sheep.

Population Genetic Structure of the Wild Boar (Sus scrofa) in the Carpathian Basin.

In the Carpathian Basin the wild boar (Sus scrofa) belongs among the most important game species both ecologically and economically, therefore knowing more about the basics of the genetics of the species is a key factor for accurate and sustainable management of its population. The aim of this study was to estimate the genetic diversity and to elucidate the genetic structure and location of wild boar populations in the Carpathian Basin. A total of 486 samples were collected and genotyped using 13 STR markers. The number of alleles varied between 4 and 14, at 9 of the 13 loci the observed heterozygosity was significantly different (p < 0.05) from the expected value, showing remarkable introgression in the population. The population was separated into two groups, with an Fst value of 0.03, suggesting the presence of two subpopulations. The first group included 147 individuals from the north-eastern part of Hungary, whereas the second group included 339 samples collected west and south of the first group. The two subpopulations' genetic indices are roughly similar. The lack of physical barriers between the two groups indicates that the genetic difference is most likely caused by the high reproduction rate and large home range of the wild boars, or by some genetic traces' having been preserved from both the last ice age and the period before the Hungarian water regulation.