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Lifecycle assessment (LCA) quantified changes in environmental impact categories (global warming, eutrophication, etc.) from 2021 to 2030 due to genetic trends in (re)production traits in pig lines of the breeding company Genus-PIC. The 2030 levels were projected with selection index theory based on weightings of traits in the breeding goals and genetic covariances among them. The projected improvement was 0.9% annually for most impact categories. Another LCA compared the impacts of 2021 North American pig production based on PIC genetics versus the industry average. Software openLCA converted material and energy flows to impact categories of frameworks ReCiPe-2016, PEF-3.1, and IPCC-2021. Flows came from data recorded by customers (1.1/4.7 million sows/finishing pigs) and by subscribers to a third-party data aggregator (1.3/9.1 million). PIC genetics have a 7-8% better impact than industry average for 13/18 categories of ReCiPe-2016, 19/25 of PEF-3.1, and all categories of IPCC-2001. Pig breeding delivers positive environmental outcomes as correlated responses to selection for profitability-oriented breeding goals. This trend is additive; technology development will increase it. Different investment levels in breeding population structure and technology and different operational efficiencies of breeding companies cause substantial differences in the environmental impact of pig production.

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Heat shock proteins (HSPs) play an important role in all living organisms under stress conditions by acting as molecular chaperones. The expression of different HSPs during stress varies depending on their protective functions and anti-apoptotic activities. The application of HSPs improves the efficiency and decreases the economic cost of animal breeding. By upregulating the expression of HSPs, feed supplements can improve stress tolerance in farm animals. In addition, high expression of HSPs is often a feature of tumor cells, and inhibiting the expression of HSPs is a promising novel method for killing these cells and treating cancers. In the present review, the findings of previous research on the application of HSPs in animal breeding and veterinary medicine are summarized, and the knowledge of the actions of HSPs in animals is briefly discussed.

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It has been well-established that the number of vertebrae is associated with body size and meat productivity. In current study we utilized a digital radiography (DR) technology to detect the number of thoracolumbar vertebrae in live donkeys. For this purpose, we introduced for the first time a groundbreaking device designed by our team for assessing thoracolumbar vertebrae number traits in equids, employing a sample of 1,000 donkeys sourced from five distinct donkey farms. This assessment incorporates a range of crucial body metrics, including body height, length, and various other measurements. Subsequently, our study determined the number of thoracolumbar vertebrae in 112 donkeys, utilizing the DR system. These findings were further validated through post-mortem evaluations conducted by slaughtering the donkeys. Our findings demonstrated a remarkable resemblance between the thoracolumbar vertebrae numbers visualized through the DR system in live donkeys and those obtained via slaughter verification. In conclusion, this research underscores the accuracy and effectiveness of the DR system for the detection of thoracolumbar vertebrae in live donkeys, which might be helpful for assessing the body size and meat productivity. We also recommended the utilization of DR system for counting thoracolumbar vertebrae in other animals in live state and could be a useful addition to livestock business industry for the prediction of body size and meat productivity efficiency.

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One of the limitations of implementing animal breeding programs in small-scale or extensive production systems is the lack of production records and genealogical records. In this context, molecular markers could help to gain information for the breeding program. This study addresses the inclusion of molecular data into traditional genetic evaluation models as a random effect by molecular pedigree reconstruction and as a fixed effect by Bayesian clustering. The methods were tested for lactation curve traits in 14 dairy goat herds with incomplete phenotypic data and pedigree information. The results showed an increment of 37.3% of the relationships regarding the originals with MOLCOAN and clustering into five genetic groups. Data leads to estimating additive variance, error variance, and heritability with four different models, including pedigree and molecular information. Deviance Information Criterion (DIC) values demonstrate a greater fitting of the models that include molecular information either as fixed (genetic clusters) or as random (molecular matrix) effects. The molecular information of simple markers can complement genetic improvement strategies in populations with little information.

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Genomic studies in animal breeding have provided a wide range of references; however, it is important to note that genes and mRNA alone do not fully capture the complexity of living organisms. Protein post-translational modification, which involves covalent modifications regulated by genetic and environmental factors, serves as a fundamental epigenetic mechanism that modulates protein structure, activity, and function. In this review, we comprehensively summarize various phosphorylation and acylation modifications on metabolic enzymes relevant to energy metabolism in animals, including acetylation, succinylation, crotonylation, ß-hydroxybutylation, acetoacetylation, and lactylation. It is worth noting that research on animal energy metabolism and modification regulation lags behind the demands for growth and development in animal breeding compared to human studies. Therefore, this review provides a novel research perspective by exploring unreported types of modifications in livestock based on relevant findings from human or animal models.

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Fucoidan, a water-soluble heteropolysaccharide predominantly found in brown algae, comprises active components such as fucose and sulfate groups. This polysaccharide exhibits a range of physiological activities, including antioxidant, antiviral, anticancer, and immunomodulatory activities. In light of the global prohibition of antibiotics in animal feed, there is increasing interest in identifying safe, natural antibiotic alternatives that lack toxic side effects. This study focuses on analysing the impact of fucoidan in animal husbandry and provides a comprehensive review of the methods for preparing fucoidan, along with its physical and chemical characteristics. Its applications in the breeding of aquatic species, livestock, and poultry have also been summarized. The aim of this study was to establish a theoretical framework for the use of fucoidan in animal husbandry and to contribute to the theoretical underpinnings of the animal breeding and feed industries.

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The aim of this study was to assess the impact of incorporating genomic data using the single-step genomic best linear unbiased prediction (ssGBLUP) method compared to the best linear unbiased prediction (BLUP) method on the reliability of breeding values for age at first calving, calving interval, and productive longevity at 78 months in Charolais cattle. The study included 48,590 purebred Charolais individuals classified into four subgroups based on genotyping and performance records. The results showed that considering genotypes significantly improved genomic estimated breeding values (GEBV) reliability across all categories except nongenotyped individuals. For young genotyped individuals, the increase in reliability was up to 27% for both sexes. The highest average reliability was achieved for genotyped proven bulls and cows with performance records, and the inclusion of genomic data further improved the reliability by up to 22% and 21% for cows and bulls, respectively. The gain in reliability was observed mainly during the first three calvings, and then the differences decreased. The imported individuals showed lower estimated breeding values (EBV) and GEBV reliabilities than the domestic population, probably due to the weak genetic connection with the domestic population. However, when the progeny of imported heifers were sired by domestic bulls, the reliability increased by up to 24%. For nongenotyped individuals, only a slight increase in reliability was observed; however, the number of genotyped individuals in the population was still relatively small.

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The long 19th century was a period of many developments and technical innovations in agriculture and animal biology, during which actors sought to incorporate new practices in light of new information. By the middle of the century, however, while heredity steadily became the dominant concept in animal husbandry, some policies related to livestock improvement in Brazil seemed to have been tailored following a climate-deterministic concept established in the mid-18th century by the French naturalist Georges-Louis Leclerc, the Comte de Buffon. His theory of animal degeneration posited, among other things, the necessity of recurrent crossbreeding to preserve animal species living in nonnative environments from climate-induced degeneration. Although largely discredited by the early 19th century, the teachings of the French naturalist seem to have found supporters in a Brazilian program to modernize national agriculture through the application of the natural sciences. Herein I examine the revival of Buffon's theories in that government-sponsored program to improve animal husbandry and breeding techniques, including actual applications of this theory in the real world. Ultimately, I argue that Buffon's theory of degeneration was used to tailor public policies and funding for the improvement of domesticated animals in Brazil between 1856 and 1860.

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The study was conducted with the objective of estimating genetic and phenotypic parameters for tick (CRM) and Babesia bigemina (IBBi), Babesia bovis (IBBo), and Anaplasma marginale (IAM) burden in Angus female breed in Brazil. The sample group was composed of Angus females raised in herds located in a region of endemic instability for cattle tick fever in the state of Rio Grande Sul (RS), Brazil. The variance components were estimated using Bayesian inference and Gibbs sampling algorithm, considering a multi-trait animal model. Heritability estimates showed values of low magnitude, ranging from 0.03 (IBBo) to 0.16 (CRM), while repeatability estimates ranged between 0.07 (IBBo) and 0.21 (CRM). Regarding the genetic correlation estimates, the values showed low (-0.01 for IBBo × IAM) to moderate (0.55 between IBBi × IAM) magnitudes. The results indicate that it is possible to use tick count and hemoparasite infection levels as selection criteria, with small genetic gains.

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Sheep farming plays a crucial role for Mediterranean countries, wherefrom a plethora of dairy products is produced. Yet, numerous indigenous sheep breeds in temperate latitudes such as the Mediterranean present a serious drawback that milk production is impaired by the seasonality of reproduction. Towards the efforts for reduction of this phenomenon, the purpose of this study was to evaluate and compare different oestrus synchronization treatments, as well as to associate two genes alleles', namely the MTNR1A and the GDF9, with the response to those treatments. Three indigenous breeds were investigated (Florina, Chios and Karagouniko sheep) and inside each breed three different oestrus synchronization treatments were applied (A: intravaginal sponges, B: GNRH use and C: male effect). In group A, Florina ewes expressed oestrus at 90% in July and fecundity was 85%. Karagouniko and Chios ewes exhibited an oestrus expression of 100% with fecundity rates at 95% and 99%, respectively. In group B, Florina ewes expressed oestrus at 60% with fecundity at 57%, Karagouniko ewes expressed oestrus at 65% with fecundity at 54%, whereas Chios breed animals expressed oestrus at 87% with fecundity rate at 85%. In group C, 68% of the Florina breed expressed oestrus 20-25 days post ram induction, whereas this proportion was 84% and 94%, for Karagouniko and Chios breed, respectively. For the molecular analysis, partial segments of the two genes were sequenced and analysed, whereas alleles were scored based on the detected SNPs. All frequencies of the four detected SNPs in MTNR1A gene were statistically and significantly different in ewes that expressed oestrus in comparison with ewes that did not express oestrus in Florina and Karagouniko breeds concerning all treatments. Two SNP's were detected in GDF9 gene, G1 and FecG , from which, only the FecG mutation exhibited statistically significant difference in twins and triplets than in singles in Florina and Karagouniko breeds.

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The advent of modern genotyping technologies has revolutionized genomic selection in animal breeding. Large marker datasets have shown several drawbacks for traditional genomic prediction methods in terms of flexibility, accuracy, and computational power. Recently, the application of machine learning models in animal breeding has gained a lot of interest due to their tremendous flexibility and their ability to capture patterns in large noisy datasets. Here, we present a general overview of a handful of machine learning algorithms and their application in genomic prediction to provide a meta-picture of their performance in genomic estimated breeding values estimation, genotype imputation, and feature selection. Finally, we discuss a potential adoption of machine learning models in genomic prediction in developing countries. The results of the reviewed studies showed that machine learning models have indeed performed well in fitting large noisy data sets and modeling minor nonadditive effects in some of the studies. However, sometimes conventional methods outperformed machine learning models, which confirms that there's no universal method for genomic prediction. In summary, machine learning models have great potential for extracting patterns from single nucleotide polymorphism datasets. Nonetheless, the level of their adoption in animal breeding is still low due to data limitations, complex genetic interactions, a lack of standardization and reproducibility, and the lack of interpretability of machine learning models when trained with biological data. Consequently, there is no remarkable outperformance of machine learning methods compared to traditional methods in genomic prediction. Therefore, more research should be conducted to discover new insights that could enhance livestock breeding programs.

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In this study, we analysed the effect of human-mediated selection on the gene pool of wild and farmed red deer populations based on genotyping-by-sequencing data. The farmed red deer sample covered populations spread across seven countries and two continents (France, Germany, Hungary, Latvia, New Zealand, Poland, and Slovakia). The Slovak and Spain wild red deer populations (the latter one in a large game estate) were used as control outgroups. The gene flow intensity, relationship and admixture among populations were tested by the Bayesian approach and discriminant analysis of principal components (DAPC). The highest gene diversity (He = 0.19) and the lowest genomic inbreeding (FHOM = 0.04) found in Slovak wild population confirmed our hypothesis that artificial selection accompanied by bottlenecks has led to the increase in overall genomic homozygosity. The Bayesian approach and DAPC consistently identified three separate genetic groups. As expected, the farmed populations were clustered together, while the Slovak and Spanish populations formed two separate clusters. Identified traces of genetic admixture in the gene pool of farmed populations reflected a strong contemporary migration rate between them. This study suggests that even if the history of deer farming has been shorter than traditional livestock species, it may leave significant traces in the genome structure.

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BACKGROUND: This paper describes genomics from two perspectives that are in use in animal breeding and genetics: a statistical perspective concentrating on models for estimating breeding values, and a sequence perspective concentrating on the function of DNA molecules. MAIN BODY: This paper reviews the development of genomics in animal breeding and speculates on its future from these two perspectives. From the statistical perspective, genomic data are large sets of markers of ancestry; animal breeding makes use of them while remaining agnostic about their function. From the sequence perspective, genomic data are a source of causative variants; what animal breeding needs is to identify and make use of them. CONCLUSION: The statistical perspective, in the form of genomic selection, is the more applicable in contemporary breeding. Animal genomics researchers using from the sequence perspective are still working towards this the isolation of causative variants, equipped with new technologies but continuing a decades-long line of research.

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Genomic selection (GS) techniques have improved animal breeding by enhancing the prediction accuracy of breeding values, particularly for traits that are difficult to measure and have low heritability, as well as reducing generation intervals. However, the requirement to establish genetic reference populations can limit the application of GS in pig breeds with small populations, especially when small populations make up most of the pig breeds worldwide. We aimed to propose a kinship index based selection (KIS) method, which defines an ideal individual with information on the beneficial genotypes for the target trait. Herein, the metric for assessing selection decisions is a beneficial genotypic similarity between the candidate and the ideal individual; thus, the KIS method can overcome the need for establishing genetic reference groups and continuous phenotype determination. We also performed a robustness test to make the method more aligned with reality. Simulation results revealed that compared to conventional genomic selection methods, the KIS method is feasible, particularly, when the population size is relatively small.

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Community-based breeding programs (CBBPs) have shown, at pilot scale, to be effective and beneficial in achieving genetic progress and in improving livelihoods of smallholder communities. In Ethiopia 134 sheep and goat CBBPs were operational producing their own improved rams and bucks. Based on experience the implementation of further programs is possible with appropriate private and public support. A different challenge is the efficient dissemination of the improved genetics produced in current CBBPs to create population-wide economic impact. We present a framework applied to the Ethiopian Washera sheep breed to meet this challenge. We propose the establishment of a genetic improvement structure that supports a meat commercialization model based on the integration of community-based breeding program cooperatives, client communities and complementary services such as fattening enterprises. We calculated that the recently established 28 community-based breeding programs in the Washera breeding tract can provide genetically improved rams to 22% of the four million head. To reach the whole population 152 additional CBBPs are needed. We simulated the genetic improvements obtainable in the current 28 CBBPs assuming realized genetic progress in CBBPs of a similar breed and calculated the expected additional lamb carcass meat production after 10 years of selection to be 7 tons and the accumulated discounted benefit 327 thousand USD. These benefits could be increased if the CBBPs are linked to client communities by providing them with improved rams: additional meat production would be 138 tons with a value of 3,088 thousand USD. The total meat production of the existing Washera CBBPs was calculated at 152 tons and the joint meat production of CBBPs if integrated with client communities would be 3,495 tons. A full integration model, which includes enterprises purchasing lambs for fattening, can produce up to 4,255 tons of meat. We conclude that Washera CBBPs cooperatives can benefit from a higher level of organization to produce population-wide genetic improvement and economic benefits. Unlike in the dairy and chicken industries, for low input sheep and goat smallholder systems the proposed commercialization model puts breeder cooperatives at the center of the operation. Cooperatives need to be capacitated and supported to become fully functional business ventures.