Search

Simple Summary: Indigenous goats are important in the daily lives of people in East Africa because they adapt well to various climatic conditions. However, there is little information about these breeds both locally and internationally. This review discusses how these goats are raised, their physical and genetic characteristics, and diversity. It shows that there is no proper way by which these breeds are identified as most of them appear to be similar, hence they are named based on the region or tribe they are raised in. This review also points out several challenges like mixed breeding, lack of records, animal health problems, poor grazing fields, and basic care practices. To overcome these issues, it suggests the adoption of a participatory approach across goat value chains and the use of modern genomic tools in selection to improve goat breeding. This approach aims to protect the unique genetic resources of East African indigenous goats and ensure their future conservation. 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 [ABSTRACT FROM AUTHOR]

Simple Summary: Worldwide, honeybees (Apis mellifera L.) are involved in pollinating both wild and economically useful plants, while their products are also used by the food and pharmaceutical industries. But currently, apiculture is encountering the adverse effects of global climate change, including more variable rainfall, shifting seasonal precipitation, and increasing temperature averages. These changes threaten the sustainable future of apiculture as these anomalies have already contributed significantly to the economic downturn of the apiculture industry in recent years. In this review, we provide an overview of the current challenges faced by apiculture due to climate change, as well as artificial intelligence (AI) applications in apiculture that can assist to address them. AI has been utilized in various scientific aspects of apiculture, such as managing hives, maintaining health, detecting pests and diseases, monitoring habitats, and managing population distribution. This is achieved by analyzing data objects such as text, audio, images, videos, sensor readings, and numerical values to investigate, model, predict, and make supporting decisions. Several shortcomings of the existing AI application are identified in this review, and the knowledge gaps regarding the development of autonomous intelligent systems for sustainable beekeeping are also highlighted. 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. [ABSTRACT FROM AUTHOR]

Simple Summary: The Dorper sheep breed was created to thrive in harsh environments in South Africa. Two breed variants were developed in the selection process. The breed gained popularity and was exported to several regions of the world where it is reported to be doing better than the purported locally adapted sheep breeds. To enhance the performance of other native sheep breeds, Dorper is widely utilized in crossbreeding with native breeds. There has not been any research done to examine the genomic status of Dorper in South Africa and Dorper in other places outside of South Africa. The genomic architecture of white Dorper and Dorper from South Africa and Hungary are compared in this study. White Dorper, Dorper, and Dorpers from South Africa and Hungary all have significantly distinct genomes. Different environmental factors and variations in coat color could be the cause of the genetic variations. 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. [ABSTRACT FROM AUTHOR]

In this era of rapid climate change, heat stress has emerged as a major problem for sheep farming. The quantity and quality of sheep production, as well as the welfare, are all shown to be negatively impacted by heat stress. Reduced cellular immune function in sheep exposed to high temperatures increases susceptibility to various diseases, although the underlying mechanisms are unclear. The imbalance between oxidants and antioxidants, known as oxidative stress, negatively impacts animal health due to heat stress-induced impairments in immune responses, increased production of reactive oxygen species, and/or a lack of antioxidants. Heat stress in livestock has negative effects on both the cell-mediated and humoral immune responses. However, the negative effects of heat stress on immune response in sheep can vary by breed. This review discusses how heat stress affects sheep's immunity. An overview of some molecular markers related to immunity, such as interleukin (ILs), Toll-like receptors (TLRs), and also the heat stress protein (HSPs) in sheep, is also discussed. Finally, recent research on the effects of antioxidant supplementation and other promising nutritional strategies for reducing heat stress and improving animal health is presented. [ABSTRACT FROM AUTHOR]

The Merino breed of sheep is one of the oldest breeds still in existence. All around the world, purebred and mixed populations of the Merino and Merino-derived sheep breeds can be found. This is a result of their wide distribution and increasing popularity. They constitute a huge genetic resource that has been applied historically to create numerous new breeds. The current Hungarian Merino sheep breed has evolved over many years as a result of crossbreeding with different breeds. Consequently, the objective of this study is to compare the genomic inbreeding coefficient (FROH) and patterns of runs of homozygosity (ROH) between the Hungarian Merino and other closely related Merino breeds. Following Rambouillet, Hungarian Merino had the second highest number of ROH class of 1-6 mbs. The Spanish Merinos Cordoba had the most ROH class of > 48Mbs, while the Hungarian Merino had none. The FROH of Hungarian Merinos was comparable to that of other studied breeds, while Spanish Merinos Cordoba had the highest. This study confirms that Hungarian Merino has several intermediate ancestors, and its breeding management is comparable to other Merino breeds and may also indicate greater genetic diversity within the breed. The results can therefore be used to improve genomic management of Hungarian Merino sheep breed. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Simple Summary: One of the indigenous sheep breeds that is primarily produced in Kenya under an extensive production system is the Red Maasai sheep. It has a reputation for being able to thrive in arid and semi-arid environments. A common belief is that, when contrasted with the Dorper breed, it performs poorly in terms of growth traits. Therefore, to enhance their growth traits, the Red Maasai are randomly crossed with Dorper. In contrast, the Red Maasai sheep breed outperformed the Dorper sheep breed in this study in terms of post-weaning growth rate, once more demonstrating early resilience and adaptation to local environmental conditions independent of maternal influence. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]