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Simple Summary: The synchronization process of yak estrus plays a crucial role in enhancing the reproductive success rate of yaks and safeguarding the continuation of the species. Metabolomics, a branch of bio-chemistry, primarily focuses on the quantitative analysis of all metabolites within an organism, aiming to identify the relative relationships between metabolites and physiological changes. It serves as a valuable tool for delving into the molecular mechanisms and responses of metabolic pathways under various perturbations. In this study, metabolomics methods were utilized to analyze blood samples collected from non-estrus yaks as well as those that underwent hormonally induced synchronized estrus to identify differential metabolites. The research results provide a theoretical basis for the optimization and application of synchronized estrus technology in yaks, promoting the healthy development of the yak industry. The yak is a unique species of livestock found in the Qinghai-Tibet Plateau and its surrounding areas. Due to factors such as late sexual maturity and a low rate of estrus, its reproductive efficiency is relatively low. The process of estrus synchronization in yaks plays a crucial role in enhancing their reproductive success and ensuring the continuation of their species. In order to clarify the characteristics of the serum metabolites of yak estrus synchronization, the yaks with inactive ovaries were compared with the estrus synchronization yaks. In this study, yaks were divided into the inactive ovaries group (IO), gonarelin-induced yak estrus group (GnRH), and chloprostenol sodium-induced yak estrus group (PGF). After the completion of the estrus synchronization treatment, blood samples were collected from the jugular veins of the non-estrus yaks in the control group and the yaks with obvious estrus characteristics in the GnRH and PGF groups. Metabolites were detected by ultra-high performance liquid chromatography-mass spectrometry, and differential metabolites were screened by multivariate statistical analysis. The results showed that a total of 70 significant differential metabolites were screened and identified in the GnRH vs. IO group, and 77 significant differential metabolites were screened and identified in the PGF vs. IO group. Compared with non-estrus yaks, 36 common significant differential metabolites were screened out after the induction of yak estrus by gonarelin (GnRH) and cloprostenol sodium (PGF), which were significantly enriched in signaling pathways such as the beta oxidation of very long chain fatty acids, bile acid biosynthesis, oxidation of branched chain fatty acids, steroidogenesis, steroid biosynthesis, and arginine and proline metabolism. This study analyzed the effects of gonadotropin releasing hormone (GnRH) and prostaglandin F (PGF) on the reproductive performance of yaks treated with estrus synchronization, which provides a theoretical basis for the optimization and application of yak estrus synchronization technology and promotes the healthy development of the yak industry. [ABSTRACT FROM AUTHOR]

Simple Summary: Yaks are a major economic source for people in the Tibetan Plateau region. Yaks are rich in nutrients, but their low fat content is not conducive to the large-scale promotion of yak meat, so the study of the mechanism of yak lipid deposition is beneficial to the marketing of yak meat. In this paper, the results of transcriptome sequencing analysis of yak liver showed that it could be determined that the expression levels of genes associated with partial lipid deposition were significantly up-regulated during yak fattening. In addition, this study found that the tenderness of yak meat improved during this process. Fattening significantly affects fat deposition in yaks, which may be realized through its effects on lipid metabolic pathways. Therefore, studying the mechanism of lipid deposition in yaks and fattening yaks will improve the quality of yak meat. Yak meat is nutritionally superior to beef cattle but has a low fat content and is slow-growing. The liver plays a crucial role in lipid metabolism, and in order to determine whether different feeding modes affect lipid metabolism in yaks and how it is regulated, we employed RNA sequencing (RNA-seq) technology to analyze the genome-wide differential gene expression in the liver of yaks maintained under different raising systems. A total of 1663 differentially expressed genes (DEGs) were identified (|log2FC| ≥ 0 and p-value ≤ 0.05), including 698 down-regulated and 965 up-regulated genes. According to gene ontology (GO) and KEGG enrichment analyses, these DEGs were significantly enriched in 13 GO terms and 26 pathways (p < 0.05). Some DEGs were enriched in fatty acid degradation, PPAR, PI3K-Akt, and ECM receptor pathways, which are associated with lipid metabolism. A total of 16 genes are well known to be related to lipid metabolism (e.g., APOA1, FABP1, EHHADH, FADS2, SLC27A5, ACADM, CPT1B, ACOX2, HMGCS2, PLIN5, ACAA1, IGF1, FGFR4, ALDH9A1, ECHS1, LAMA2). A total of 11 of the above genes were significantly enriched in the PPAR signaling pathway. The reliability of the transcriptomic data was verified using qRT-PCR. Our findings provide new insights into the mechanisms regulating yak meat quality. It shows that fattening improves the expression of genes that regulate lipid deposition in yaks and enhances meat quality. This finding will contribute to a better understanding of the various factors that determine yak meat quality and help develop strategies to improve yield and quality. [ABSTRACT FROM AUTHOR]

Simple Summary: The aim of our study was to investigate the effects of dietary supplementation with different protein levels after grazing on growth performance as well as on the proteomics of the LL muscle of Jersey-yak. The results showed that a certain amount of crude protein supplementation to Jersey-yak at the end of grazing significantly improved growth performance and increased their economic efficiency. In addition, we analyzed the proteomic differences in the longest dorsal muscle of Jersey-yak. From our analyses, we identified differences in the abundance of 434 proteins involved in pathways related to muscle growth and development and energy metabolism, among others. Several of the proteins enriched in these pathways, such as MYH8, are associated with myoblast development and differentiation as well as muscle development. In conclusion, the results of this study provide proteomic insights into the different feeding patterns of yak crossbred progeny, suggesting that a greater economic income can be achieved by improving their feeding conditions. Jersey-yak is a hybrid offspring of Jersey cattle and yak (Bos grunniens). Changing the feeding system of Jersey-yak can significantly improve its growth performance. In this study, tandem mass tag (TMT) proteomics technology was used to determine the differentially expressed proteins (DEPs) of the longissimus lumborum (LL) muscle of Jersey-yak fed different protein levels of diet. The results showed that compared with the traditional grazing feeding, the growth performance of Jersey-yaks was significantly improved by crude protein supplementation after grazing. A total of 3368 proteins were detected in these muscle samples, of which 3365 were quantified. A total of 434 DEPs were identified. Through analyses, it was found that some pathways related to muscle growth and development were significantly enriched, such as Rap1 signaling pathway, mTOR signaling pathway, and TGF-beta signaling pathway. A number of DEPs enriched in these pathways are related to muscle cell development, differentiation, and muscle development, including integrin subunit alpha 7 (ITGA7), myosin heavy chain 8 (MYH8), and collagen type XII alpha 1 chain (COL12A1). In conclusion, the results of this study provide insights into the proteomics of different feeding patterns of Jersey-yak, providing a stronger basis for further understanding the biological mechanism of hybrid varieties. [ABSTRACT FROM AUTHOR]

Simple Summary: Ashidan yak is a new breed of hornless yak developed by Chinese scientists, which has an important economic value. However, little is known about the growth of Ashidan yaks. This study analyzed the body weight and body size measurements of 260 female Ashdan yaks and compared the performance of five nonlinear models (Logistic model, Gompertz model, Brody model, von Bertalanffy model and Richards model). Our results showed that the early growth and development of Ashidan yak change with the seasons, and the Richards model performs better among the five models. Understanding animal growth plays an important role in improving animal genetics and breeding. In order to explore the early growth and development law of Ashidan yak, the body weight (BW), wither height (WH), body oblique length (BL) and chest girth (CG) of 260 female Ashidan yaks were measured. These individuals grew under grazing conditions, and growth traits were measured at 6, 12, 18 and 30 months of age. Then the absolute growth and relative growth of Ashidan yak were calculated, and five nonlinear models (Logistic model, Gompertz model, Brody model, von Bertalanffy model and Richards model) were used to fit the growth curve of Ashidan yak. The fitting effect of the model was evaluated according to MSE, AIC and BIC. The results showed that the growth rate of Ashidan yak was the fastest from 12 to 18 months old, and the growth was slow or even stagnant from 6 to 12 months old. The AIC and BIC values of the Richards model were the lowest among the five models, with an AIC value of 4543.98 and a BIC value of 4563.19. The Richards model estimated body weight at 155.642 kg. In summary, the growth rate of female Ashidan yak changes with the seasons, growing faster in warm seasons and slower in cold seasons. Richards model is the best model to describe the growth curve of female Ashidan yak in five nonlinear models. [ABSTRACT FROM AUTHOR]

Simple Summary: Yak is the dominant animal species in China's plateau regions. The development of the yak industry is conducive to protecting the ecosystem of the Qinghai–Tibet Plateau and promoting local economic development. However, the slow growth and development of yak have seriously affected the development of the yak industry. Structural variation (SV) has been widely applied in livestock breeding for growth traits. Therefore, it is of great significance to use SV to improve yak growth traits in yak breeding. Meanwhile, the GHR gene plays an important role in the formation and normal development of bones. This study associated the correlation between the yak GHR SV gene and growth traits and confirmed that GHR-SV can be used as a molecular marker for the early reproduction of yaks. This study provides a theoretical basis for the early growth and development of yaks. The growth hormone receptor (GHR) is a member of the cytokine/hematopoietic factor receptor superfamily, which plays an important role in the growth and development, immunity, and metabolism of animals. This study identified a 246 bp deletion variant in the intronic region of the GHR gene, and three genotypes, including type II, type ID, and type DD, were observed. Genotype analysis of structural variation (SV) was performed on 585 individuals from 14 yak breeds, and it was found that 246 bp deletion was present in each breed. The II genotype was dominant in all yak breeds except for SB yak. The association analysis of gene polymorphisms and growth traits in the ASD yak population showed that the 246 bp SV was significantly associated with body length at 6 months (p < 0.05). GHR messenger RNA (mRNA) was expressed in all the tested tissues, with significantly higher levels in the liver, muscle, and fat than in other organs. The results of transcription activity showed that the luciferase activity of the pGL4.10-DD vector was significantly higher than that of the pGL4.10-II vector (p < 0.05). Additionally, the transcription-factor binding prediction results showed that the SV in the runt-related transcription factor 1 (Runx1) transcription-factor binding site may affect the transcriptional activity of the GHR gene, regulating yak growth and development. This study showed that the novel SV of the GHR gene could be used as a candidate molecular marker for the selection of the early growth trait in ASD yak. [ABSTRACT FROM AUTHOR]

Simple Summary: Exosomes are multivesicular bodies produced and secreted by living cells as membranous vesicles with a diameter of about 30–150 nm, density of 1.13–1.19 g/mL, and a typical "cup dish" shape. Exosomes carry proteins, miRNA, lncRNA, circRNA, and mRNA and their degradation fragments are involved in intracellular signal transduction important for regulation of cellular activities. Of these, miRNAs play an important role in the regulation of gene expression in important biological processes such as cell division, tissue development, and immune response. In this study, milk quality was determined and exosome miRNAs from yak and Jeryak milk sampled in June and December were characterized by sequencing. Differentially expressed miRNAs (DEMs) and pathways related to lactation performance were identified. In summary, this study provides data that can be used to develop alternative strategies for improving the lactation performance of yaks and Jeryaks. The Jeryak is the hybrid offspring of yaks and Jersey cattle and exhibit improved milk and meat yields. Biomolecules carried within milk exosomes are important for cell growth, development, immune regulation, and various pathophysiological processes. Previous studies showed that miRNAs regulate mammary gland development, lactation, and milk quality. This study explored the relationship between milk exosomes miRNAs and lactation performance. A comparison of the milk content showed that yak milk was of a better quality compared to Jeryak milk (casein, fat, TS, SNF, lactose). Milk collected in December was superior to that collected in June for both yak and Jeryak, except for lactose concentrations. Exosomes were extracted by density gradient centrifugation and miRNA expression profiles in milk exosomes from three yaks and three Jeryaks collected in June and December were detected by small RNA sequencing. In all, 22, 120, 78, and 62 differentially expressed miRNAs (DEMs) were identified in Jun_ JY vs. Jun_ Y (P1: Jeryak in June vs. Yak in June), Jun_ JY vs. Dec_ JY (P2: Jeryak in June vs. Jeryak in December), Dec_ JY vs. Dec_ Y (P3: Jeryak in December vs. Yak in December), and Jun_ Y vs. Dec_ Y (P4: Yak in June vs. Yak in December) groups. These DEMs were enriched in functions and signaling pathways related to lactation performance. In conclusion, these findings are a reference tool to study the molecular basis of lactation performance. [ABSTRACT FROM AUTHOR]

Simple Summary: The SOX6 (sex determining region Y-box 6) gene belongs to one of the transcription factors in the SRY (sex-determining region Y) family, which affects sex determination, embryonic and nervous system development, bone and various organ formation. In the previous study, the whole-genome sequencing was used to detect multiple genes located in the copy number variation region, including SOX6 gene. In this study, we identified the correlation between the growth traits and CNV of SOX6 in 311 Ashidan yaks. The results showed that SOX6-CNV was significantly correlated with the chest girth of the 6-months old yaks (p < 0.05) and 30-months yaks (p < 0.05), and withers height of 6 months yaks (p < 0.05) and 18-months yaks (p < 0.05), suggesting the SOX6-CNV affect growth traits in yaks, and could be new markers for the selection of yak breeding. Copy number variation (CNV) is a fundamental type of structural variation of the genome affecting the economic traits of livestock. The SOX6 gene (sex-determining region Y-box 6), as a transcription factor, has multiple functions with regard to sex determination, embryonic growth, the nervous system development, as well as bone, and various organ formation. This study employed quantitative real-time fluorescence quota PCR (qPCR) for detecting the SOX6-CNV of the 311 Ashidan yaks and analyzed the correlation of the SOX6-CNV with four phenotypes (including body weight, withers height, body length, and chest girth) of the yaks aged 6, 12, 18, and 30 months using ANOVA and multiple comparisons. Furthermore, the SOX6 gene expression was identified in seven different tissues of the yaks. The experiment results demonstrated the expression of SOX6 in each tissue, and the kidney and muscle tissue were found to have higher relative expression levels. Based on the processing by IBM SPSS software, SOX6-CNV was significantly correlated with the chest girth of the 6-months old yaks (p < 0.05) and 30-months yaks (p < 0.05), and withers height of 6 months yaks (p < 0.05) and 18-months yaks (p < 0.05), as well as the normal type of CNV, was chosen for yak breeding. In conclusion, SOX6 might be prominently involved in promoting growth and development of yaks, suggesting that the SOX6 gene can be used in breeding yaks by molecular marker-assisted selection (MAS). The study also offered some important insights into the references and clues for the genetic breeding of yaks. [ABSTRACT FROM AUTHOR]

Simple Summary: Automatic species recognition, such as butterflies or other insects, plays a crucial role in intelligent agricultural production management and the study of species diver-sity. However, the quite diverse and subtle interspecific differences and the long-tailed distribution of sample data in fine-grained species recognition are insufficient to learn robust feature representation and alleviate the bias and variance problems of the long-tailed classifier on insect recognition. The objective of this study is to develop a peer learning network with a distribution-aware penalty mechanism proposed to learn discriminative feature representation and mitigate the bias and variance problems in the long-tailed distribution. The results of various contrast experiments on collecting the butterfly-914 dataset show that the proposed PLN-DPM has a higher Rank-1 ac-curacy rate (86.2% on the butterfly dataset and 73.51% on the IP102 dataset). Addi-tionally, we deployed the PLN-DPM model on the smartphone app for butterfly recognition in a real-life environment. Automatic species recognition plays a key role in intelligent agricultural production management and the study of species diversity. However, fine-grained species recognition is a challenging task due to the quite diverse and subtle interclass differences among species and the long-tailed distribution of sample data. In this work, a peer learning network with a distribution-aware penalty mechanism is proposed to address these challenges. Specifically, the proposed method employs the two-stream ResNeSt-50 as the backbone to obtain the initial predicted results. Then, the samples, which are selected from the instances with the same predicted labels by knowledge exchange strategy, are utilized to update the model parameters via the distribution-aware penalty mechanism to mitigate the bias and variance problems in the long-tailed distribution. By performing such adaptive interactive learning, the proposed method can effectively achieve improved recognition accuracy for head classes in long-tailed data and alleviate the adverse effect of many head samples relative to a few samples of the tail classes. To evaluate the proposed method, we construct a large-scale butterfly dataset (named Butterfly-914) that contains approximately 72,152 images belonging to 914 species and at least 20 images for each category. Exhaustive experiments are conducted to validate the efficiency of the proposed method from several perspectives. Moreover, the superior Top-1 accuracy rate (86.2%) achieved on the butterfly dataset demonstrates that the proposed method can be widely used for agricultural species identification and insect monitoring. [ABSTRACT FROM AUTHOR]

Simple Summary: Yaks are among the largest high-altitude mammals in the world, and they are ideally adapted to the harsh environmental conditions of the plateau regions. Yaks are thus central to the lives of herdsmen and other local populations in these high-altitude areas. Copy number variations (CNVs) are an important cause of genomic variation in livestock and identifying advantageous CNVs can aid in livestock breeding efforts. In this study, an association between CNVs in the MICALL2 and MOGAT2 genes and Ashidan yak growth traits was confirmed, providing a theoretical foundation for Ashidan yak breeding and meat production efforts. Copy number variations (CNVs) are a result of genomic rearrangement affecting DNA regions over 1 kb in length, and can include inversions, translocations, deletions, and duplications. The molecule interacting with CasL-like protein 2 (MICALL2) gene is primarily associated with mitochondrial protein targeting and exhibits predicted stress fiber colocalization. The monoacylglycerol O-acyltransferase 2 (MOGAT2) gene encodes an enzyme responsible for catalyzing diacylglycerol synthesis from 2-monoacylglycerol and fatty acyl-CoA. For this study, blood samples were obtained from 315 yaks, and the body weight, body length, withers height, and chest girth of these animals were measured at 6, 12, 18, and 30 months of age. Genomic DNA was harvested from the collected blood samples, and CNVs in these samples were detected by qPCR. The resultant data were compared using ANOVAs, revealing significant associations between MICALL2 gene CNVs and body weight at 6 months of age (p < 0.05), body length and chest girth at 30 months of age (p < 0.05), and withers height at 18 months of age (p < 0.01) in Ashidan yaks. Similarly, MOGAT2 CNVs were significantly associated with body weight at 6 and 30 months of age (p < 0.05), and with withers height at 18 months of age (p < 0.01) in these Ashidan yaks. MICALL2 and MOGAT2 gene expression was further analyzed in yak tissue samples, revealing that MICALL2 was most highly expressed in the adipose tissue, whereas MOGAT2 was most highly expressed in the lung. These results thus confirmed the relationship between CNVs in the MICALL2 and MOGAT2 genes and Ashidan yak growth traits, providing a valuable gene locus that can be leveraged for future marker-assisted yak breeding efforts. [ABSTRACT FROM AUTHOR]

Simple Summary: The domesticated yak is among the most important livestock species on the Qinghai-Tibet Plateau. Breeders have the task of developing varieties that provide growth performance and disease resistance. Traditional breeding processes rely on complete family pedigree information and large numbers of data records. However, there are inevitably records that are missing, including incomplete pedigrees and long-term data tracking, resulting in prolonged breeding cycles, reduced breeding efficiency, and the lack of economic benefit. Genome selection (GS), also known as whole genomic selection (WGS), can significantly reduce the selection cycle of quantitative traits and accelerate genetic progression while displaying appropriate prediction accuracy (PA). It combines a reference population and single nucleotide polymorphism (SNP) loci rather than pedigrees to estimate the effect of all SNPs. Then breeding values of target traits are predicted. The key for GS is genomic prediction (GP) and an assessment of PA. The aim of this study was to explore the possibility of applying GP to important economic traits in the domesticated yak, thus providing theoretical support for its molecular breeding. A reference population was constructed consisting of 354 polled yaks, measuring four growth traits and eight hematological traits related to resistance to disease (involved in immune response and phagocytosis). The Illumina bovine HD 770k chip was used to obtain SNP information of all the individuals. With these genotypes and phenotypes, GBLUP, Bayes B and Bayes Cπ methods were used to predict genomic estimated breeding values (GEBV) and assess prediction capability. The correlation coefficient of the association of GEBV with estimated breeding value (EBV) was used as PA for each trait. The prediction accuracy varied from 0.043 to 0.281 for different traits. Each trait displayed similar PAs when using the three methods. Lymphocyte counts (LYM) exhibited the highest predictive accuracy (0.319) during all GP, while chest girth (CG) provided the lowest predictive accuracy (0.043). Our results showed moderate PA in most traits such as body length (0.212) and hematocrit (0.23). Those traits with lower PA could be improved by using SNP chips designed specifically for yak, a better optimized reference group structure, and more efficient statistical algorithms and tools. [ABSTRACT FROM AUTHOR]