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A previous study on ovarian and hypothalami transcriptome analysis in white Muscovy duck revealed that MAP3K8 gene participated in MAPK signaling pathway that influence egg production. Additionally, MAP3K8 was predicted as a target gene of miRNA-509-3p that promotes the secretion of oestradiol which is an important hormone in egg ovulation. This suggested that MAP3K8 might have a functional role in the reproductive performance "egg production" of white Muscovy ducks. Herein, we focused on expression level of MAP3K8 in reproductive and non-reproductive tissues of highest (HP) and lowest (LP) egg producing white Muscovy ducks and identified the polymorphism in MAP3K8 and its association with three egg production traits; Age at first egg (AFE), number of eggs at 300 days (N300D) and 59 weeks (N59W). The results of expression level indicated that mRNA of MAP3K8 was significantly (p < 0.01) expressed in the oviduct than in the ovary and hypothalamus. Seven synonymous SNPs were detected, and association analysis showed that g.148303340 G>A and g.148290065 A>G were significantly (p < 0.05) associated with N300D and N59W. The results of this study might serve as molecular marker for marker-assisted selection of white Muscovy ducks for egg production.

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Mastitis (MAS), endometritis (MET), and ketosis (KET) are prevalent diseases in dairy cows that result in substantial economic losses for the dairy farming industry. This study gathered 26,014 records of the health and sickness of dairy cows and 99,102 data of reproduction from 13 Holstein dairy farms in Central China; the milk protein and milk fat content from 56,640 milk samples, as well as the pedigree data of 37,836 dairy cows were obtained. The logistic regression method was used to analyze the variations in the prevalence rates of MAS, MET, and KET among various parities; the mixed linear model was used to examine the effects of the three diseases on milk production, milk quality, and reproductive traits. DMU software (version 5.2) utilized the DMUAI module in conjunction with the single-trait and two-trait animal model, as well as best linear unbiased prediction (BLUP), to estimate the genetic parameters for the three diseases, milk production, milk quality, and reproductive traits in dairy cows. The primary findings of the investigation comprised the following: (1) The prevalence rates of MAS, MET, and KET in dairy farms were 20.04%, 10.68%, and 7.33%, respectively. (2) MAS and MET had a substantial impact (p < 0.01) on milk production, resulting in significant decreases of 112 kg and 372 kg in 305-d Milk Yield (305-d MY), 4 kg and 12 kg in 305-d Protein Yield (305-d PY), and 6 kg and 16 kg in 305-d Fat Yield (305-d FY). As a result of their excessive 305-d MY, some cows were diagnosed with KET due to glucose metabolism disorder. The 305-d MY of cows with KET was significantly higher than that of healthy cows (205 kg, p < 0.01). (3) All three diseases resulted in an increase in the Interval from Calving to First Service (CTFS, 0.60-1.50 d), Interval from First Service to Conception (FSTC, 0.20-16.20 d), Calving Interval (CI, 4.00-7.00 d), and Number of Services (NUMS, 0.07-0.35). (4) The heritabilities of cows with MAS, MET, and KET were found to be low, with values of 0.09, 0.01, and 0.02, respectively. The genetic correlation between these traits ranged from 0.14 to 0.44. This study offers valuable insights on the prevention and control of the three diseases, as well as feeding management and genetic breeding.

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Understanding the differences in genetic variation between local Chinese dairy goat breeds and imported breeds can help germplasm innovation and molecular breeding. However, the research is limited in this area. In this study, whole-genome resequencing data from 134 individuals of both local and imported dairy goat breeds were analyzed, and their differences in genomic genetic variation, genetic diversity, and population structure were subsequently identified. We also screened candidate genes associated with important traits of dairy goats such as milk production (STK3, GHR, PRELID3B), reproduction (ATP5E), growth and development (CTSZ, GHR), and immune function (CTSZ, NELFCD). Furthermore, we examined allele frequency distributions for the genes of interest and found significant differences between the two populations. This study provides valuable resources for the study of genetic diversity in dairy goats and lays the foundation for the selective breeding of dairy goats in the future.

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Milk production is an important trait that influences the economic value of camels. However, the genetic regulatory mechanisms underlying milk production in camels have not yet been elucidated. We aimed to identify candidate molecular markers that affect camel milk production. We classified Junggar Bactrian camels (9-10-year-old) as low-yield (<1.96 kg/d) or high-yield (>2.75 kg/d) based on milk production performance. Milk fat (5.16 ± 0.51 g/100 g) and milk protein (3.59 ± 0.22 g/100 g) concentrations were significantly lower in high-yielding camels than those in low-yielding camels (6.21 ± 0.59 g/100 g, and 3.93 ± 0.27 g/100 g, respectively) (p < 0.01). There were no apparent differences in gland tissue morphology between the low- and high-production groups. Whole-genome resequencing of 12 low- and 12 high-yield camels was performed. The results of selection mapping methods, performed using two methods (FST and θπ), showed that 264 single nucleotide polymorphism sites (SNPs) overlapped between the two methods, identifying 181 genes. These genes were mainly associated with the regulation of oxytocin, estrogen, ErbB, Wnt, mTOR, PI3K-Akt, growth hormone synthesis/secretion/action, and MAPK signaling pathways. A total of 123 SNPs were selected, based on significantly associated genomic regions and important pathways for SNP genotyping, for verification in 521 additional Bactrian camels. This analysis showed that 13 SNPs were significantly associated with camel milk production yield and 18 SNPs were significantly associated with camel milk composition percentages. Most of these SNPs were located in coding regions of the genome. However, five and two important mutation sites were found in the introns of CSN2 (ß-casein) and CSN3 (κ-casein), respectively. Among the candidate genes, NR4A1, ADCY8, PPARG, CSN2, and CSN3 have previously been well studied in dairy livestock. These observations provide a basis for understanding the molecular mechanisms underlying milk production in camels as well as genetic markers for breeding programs aimed at improving milk production.

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Egg production traits are crucial in the poultry industry, including age at first egg (AFE), egg number (EN) at different stages, and laying rate (LR). Ducks exhibit higher egg production capacity than other poultry species, but the genetic mechanisms are still poorly understood. In this study, we collected egg-laying data of 618 Peking ducks from 22 to 66 weeks of age and genotyped them by whole-genome resequencing. Genetic parameters were calculated based on SNPs, and a genome-wide association study (GWAS) was performed for these traits. The SNP-based heritability of egg production traits ranged from 0.09 to 0.54. The GWAS identified nine significant SNP loci associated with AFE and egg number from 22 to 66 weeks. These loci showed that the corresponding alleles were positively correlated with a decrease in the traits. Moreover, three potential candidate genes (ENSAPLG00020011445, ENSAPLG00020012564, TMEM260) were identified. Functional enrichment analyses suggest that specific immune responses may have a critical impact on egg production capacity by influencing ovarian function and oocyte maturation processes. In conclusion, this study deepens the understanding of egg-laying genetics in Peking duck and provides a sound theoretical basis for future genetic improvement and genomic selection strategies in poultry.

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BACKGROUND: Sheep and goats have undergone domestication and improvement to produce similar phenotypes, which have been greatly impacted by structural variants (SVs). Here, we report a high-quality chromosome-level reference genome of Asiatic mouflon, and implement a comprehensive analysis of SVs in 897 genomes of worldwide wild and domestic populations of sheep and goats to reveal genetic signatures underlying convergent evolution. RESULTS: We characterize the SV landscapes in terms of genetic diversity, chromosomal distribution and their links with genes, QTLs and transposable elements, and examine their impacts on regulatory elements. We identify several novel SVs and annotate corresponding genes (e.g., BMPR1B, BMPR2, RALYL, COL21A1, and LRP1B) associated with important production traits such as fertility, meat and milk production, and wool/hair fineness. We detect signatures of selection involving the parallel evolution of orthologous SV-associated genes during domestication, local environmental adaptation, and improvement. In particular, we find that fecundity traits experienced convergent selection targeting the gene BMPR1B, with the DEL00067921 deletion explaining ~10.4% of the phenotypic variation observed in goats. CONCLUSIONS: Our results provide new insights into the convergent evolution of SVs and serve as a rich resource for the future improvement of sheep, goats, and related livestock.

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In this study, our primary aim was to explore the genomic landscape of Barka cattle, a breed recognized for high milk production in a semi-arid environment, by focusing on genes with known roles in milk production traits. We employed genome-wide analysis and three selective sweep detection methods (ZFST, θπ ratio, and ZHp) to identify candidate genes associated with milk production and composition traits. Notably, ACAA1, P4HTM, and SLC4A4 were consistently identified by all methods. Functional annotation highlighted their roles in crucial biological processes such as fatty acid metabolism, mammary gland development, and milk protein synthesis. These findings contribute to understanding the genetic basis of milk production in Barka cattle, presenting opportunities for enhancing dairy cattle production in tropical climates. Further validation through genome-wide association studies and transcriptomic analyses is essential to fully exploit these candidate genes for selective breeding and genetic improvement in tropical dairy cattle.

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Buffaloes are vital contributors to the global dairy industry. Understanding the genetic basis of milk production traits in buffalo populations is essential for breeding programs and improving productivity. In this study, we conducted whole-genome resequencing on 387 buffalo genomes from 29 diverse Asian breeds, including 132 river buffaloes, 129 swamp buffaloes, and 126 crossbred buffaloes. We identified 36,548 copy number variants (CNV) spanning 133.29 Mb of the buffalo genome, resulting in 2,100 CNV regions (CNVR), with 1,993 shared CNVR being found within the studied buffalo types. Analyzing CNVR highlighted distinct genetic differentiation between river and swamp buffalo subspecies, verified by evolutionary tree and principal component analyses. Admixture analysis grouped buffaloes into river and swamp categories, with crossbred buffaloes displaying mixed ancestry. To identify candidate genes associated with milk production traits, we employed 3 approaches. First, we used Vst-based population differentiation, revealing 11 genes within CNVR that exhibited significant divergence between different buffalo breeds, including genes linked to milk production traits. Second, expression quantitative loci analysis revealed differentially expressed CNVR-derived genes (DECG) associated with milk production traits. Notably, known milk production-related genes were among these DECG, validating their relevance. Last, a GWAS identified 3 CNVR significantly linked to peak milk yield. Our study provides comprehensive genomic insights into buffalo populations and identifies candidate genes associated with milk production traits. These findings facilitate genetic breeding programs aimed at increasing milk yield and improving quality in this economically important livestock species.

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Our preliminary research proposed the cytochrome P450 family 7 subfamily A member 1 (CYP7A1) and hydroxyacyl-coenzyme A dehydrogenase trifunctional multienzyme complex beta subunit (HADHB) genes as candidates for association with milk-production traits in dairy cattle because of their differential expression across different lactation stages in the liver tissues of Chinese Holstein cows and their potential roles in lipid metabolism. Hence, we identified single-nucleotide polymorphisms (SNPs) of the CYP7A1 and HADHB genes and validated their genetic effects on milk-production traits in a Chinese Holstein population with the goal of providing valuable genetic markers for genomic selection (GS) in dairy cattle, This study identified five SNPs, 14:g.24676921A>G, 14:g.24676224G>A, 14:g.24675708G>T, 14:g.24665961C>T, and 14:g.24664026A>G, in the CYP7A1 gene and three SNPs, 11:g.73256269T>C, 11:g.73256227A>C, and 11:g.73242290C>T, in HADHB. The single-SNP association analysis revealed significant associations (p value ≤ 0.0461) between the eight SNPs of CYP7A1 and HADHB genes and 305-day milk, fat and protein yields. Additionally, using Haploview 4.2, we found that the five SNPs of CYP7A1 formed two haplotype blocks and that the two SNPs of HADHB formed one haplotype block; notably, all three haplotype blocks were also significantly associated with milk, fat and protein yields (p value ≤ 0.0315). Further prediction of transcription factor binding sites (TFBSs) based on Jaspar software (version 2023) showed that the 14:g.24676921A>G, 14:g.24675708G>T, 11:g.73256269T>C, and 11:g.73256227A>C SNPs could alter the 5' terminal TFBS of the CYP7A1 and HADHB genes. The 14:g.24665961C>T SNP caused changes in the structural stability of the mRNA for the CYP7A1 gene. These alterations have the potential to influence gene expression and, consequently, the phenotype associated with milk-production traits. In summary, we have confirmed the genetic effects of CYP7A1 and HADHB genes on milk-production traits in dairy cattle and identified potential functional mutations that we suggest could be used for GS of dairy cattle and in-depth mechanistic studies of animals.

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Genetic research for the assessment of mastitis and milk production traits simultaneously has a long history. The main issue that arises in this context is the known existence of a positive correlation between the risk of mastitis and lactation performance due to selection. The transcriptome-wide association study (TWAS) approach endeavors to combine the expression quantitative trait loci and genome-wide association study summary statistics to decode complex traits or diseases. Accordingly, we used the farmgtex project results as a complete bovine database for mastitis and milk production. The results of colocalization and TWAS approaches were used for the detection of functional associated candidate genes with milk production and mastitis traits on multiple tissue-based transcriptome records. Also, we used the david database for gene ontology to identify significant terms and associated genes. For the identification of interaction networks, the genemania and string databases were used. Also, the available z-scores in TWAS results were used for the calculation of the correlation between tissues. Therefore, the present results confirm that LYNX1, DGAT1, C14H8orf33, and LY6E were identified as significant genes associated with milk production in eight, six, five, and five tissues, respectively. Also, FBXL6 was detected as a significant gene associated with mastitis trait. CLN3 and ZNF34 genes emerged via both the colocalization and TWAS approaches as significant genes for milk production trait. It is expected that TWAS and colocalization can improve our perception of the potential health status control mechanism in high-yielding dairy cows.

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Qingyuan partridge chicken is a renowned indigenous yellow broiler breed in China. Egg production traits are important economic traits for chickens. With the decreasing cost of whole genome resequencing, identifying candidate genes with more precision has become possible. In order to identify molecular markers and candidate genes associated with egg production traits, we conducted genome-wide association studies based on the resequencing data of 287 female Qingyuan partridge chickens. For each hen, age at first egg and egg laying rate were recorded and calculated, respectively. With a univariate linear mixed model, we detected one genome-wide significant single nucleotide polymorphism (SNP) and three chromosome-wide significant SNPs associated with egg laying rate. MTA2 is highly likely to be a functional gene for egg laying rate. Our study identifies MTA2 as the first time to be associated with egg laying rate. Findings in our study will advance our understanding of the genetic basis of egg production and have the potential to improve the efficiency of genomic selection in chickens.

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Identifying key causal genes is critical for unraveling the genetic basis of complex economic traits, yet it remains a formidable challenge. The advent of large-scale sequencing data and computational algorithms, such as transcriptome-wide association studies (TWASs), offers a promising avenue for identifying potential causal genes. In this study, we harnessed the power of TWAS to identify genes potentially responsible for milk production traits, including daily milk yield (MY), fat percentage (FP), and protein percentage (PP), within a cohort of 100 buffaloes. Our approach began by generating the genotype and expression profiles for these 100 buffaloes through whole-genome resequencing and RNA sequencing, respectively. Through comprehensive genome-wide association studies (GWAS), we pinpointed a total of seven and four single nucleotide polymorphisms (SNPs) significantly associated with MY and FP traits, respectively. By using TWAS, we identified 55, 71, and 101 genes as significant signals for MY, FP, and PP traits, respectively. To delve deeper, we conducted protein-protein interaction (PPI) analysis, revealing the categorization of these genes into distinct PPI networks. Interestingly, several TWAS-identified genes within the PPI network played a vital role in milk performance. These findings open new avenues for identifying potentially causal genes underlying important traits, thereby offering invaluable insights for genomics and breeding in buffalo populations.

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High resilience against diseases, changing environmental conditions, and other stress factors and the ability to efficiently recover to normal status, is becoming increasingly important in pig production. Finding new phenotypes that relate to resilience is a crucial step for improving the resilience of pigs through selection. The objective of this study was to extract resilience-related phenotypes based on fluctuations in daily feed intake (DFI, g) and time spent in feeding per day (TPD, min) and to estimate the heritability of these traits and genetic correlations with production traits (PT). Resilience-related traits with high enough heritability and with either favorable or neutral genetic correlation with PT could be used in the selection program to improve the productivity and welfare of pigs. In this study, we used data from 7,347 Finnish Yorkshire, Landrace, and crossbred pigs raised at the test station. Six pig-specific resilience-related phenotypes were extracted from the individual DFI and TPD: root mean square error (RMSE), quantile regression (QR), and coefficient of variation (CV). RMSE was calculated from the differences between the actual DFI (or TPD) and the pig-specific predicted values. QR was based on the number of days that a pig belonged to the group with the lowest 5% of pigs based on DFI (or TPD), and CV was calculated over the daily observations of DFI (or TPD). PT included average daily gain (ADG, g), backfat thickness (BF, mm), and feed conversion rate (FCR, g/g). The heritability estimates for resilience-related traits varied between 0.07 ±â€…0.02 (QRDFI) and 0.20 ±â€…0.03 (RMSETPD). The genetic correlations between resilience-related traits and PT were mostly neutral, but for example, RMSEDFI had a favorable genetic correlation with FCR and BF but an unfavorable correlation with ADG. Lastly, we observed that pigs belonging to the lowest 10% group based on their breeding value (BV) for QRTPD had a lower proportion (10% incidence) of sick days compared to the highest 10% BV group (30% incidence). Therefore, pigs exhibiting small TPD variation (related to high resilience) tend to be less susceptible to sickness than pigs with large TPD variation (related to low resilience). Given its moderate heritability, neutral genetic correlation with PT, and positive effect on health, QRTPD can be considered the most promising resilience-related trait in the Finnish production system.

Improving resilience, i.e., the capacity to respond to the impacts of stressors and to effectively recover to normal status, is a promising approach to enhancing the well-being of pigs and the productivity of the pig industry. Animals with high resilience can maintain their performance under challenging conditions. However, obtaining heritable measurements and indicators of resilience is challenging. One indicator of resilience is fluctuation in daily feed intake (DFI) and time spent in feeding per day (TPD). In our study, the proportion of days during which a particular pig belongs to the lowest 5% of pigs based on TPD (QRTPD) turned out to be the most promising resilience-related trait. This trait is moderately inheritable and has only a weak genetic correlation with production traits (PTs). Pigs with the most favorable breeding values (BVs) for QRTPD had four times fewer sick days than pigs with less favorable BVs for QRTPD. Overall, selecting QRTPD would improve pig resilience and health without negative effects on PTs.

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Genomic structural variants (SVs) constitute a significant proportion of genetic variation in the genome. The rapid development of long-reads sequencing has facilitated the detection of long-fragment SVs. There is no published study to detect SVs using long-read data from sheep. We applied a long-read mapping approach to detect SVs and characterized a total of 30,771 insertions, deletions, inversions and translocations. We identified 716, 916, 842 and 303 specific SVs in Southdown sheep, Alpine merino sheep, Qilian White Tibetan sheep and Oula sheep, respectively. We annotated these SVs and found that these SV-related genes were primarily enriched in the well-established pathways involved in the regulation of the immune system, growth and development and environmental adaptability. We detected and annotated SVs based on NGS resequencing data to validate the accuracy based on third-generation detection. Moreover, five candidate SVs were verified using the PCR method in 50 sheep. Our study is the first to use a long-reads sequencing approach to construct a novel structural variation map in sheep. We have completed a preliminary exploration of the potential effects of SVs on sheep.

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OBJECTIVE: This study aims to investigate the genetic structure and characteristics of the Angus cattle population in Hungary. The survey was performed with the assistance of the Hungarian Hereford, Angus, Galloway Association (HHAGA). METHODS: Genetic parameters of 1,369 animals from 16 Angus herds were analyzed using the genotyping results of 12 microsatellite markers with the aid of PowerMarker, Genalex, GDA-NT2021, and STRUCTURE software. Genotyping of DNA was performed using an automated genetic analyzer. Based on pairwise identity by state values of animals, the Python networkx 2.3 library was used for network analysis of the breed and to identify the central animals. RESULTS: The observed numbers of alleles on the 12 loci under investigation ranged from 11 to 18. The average effective number of alleles was 3.201. The overall expected heterozygosity was 0.659 and the observed heterozygosity was 0.710. Four groups were detected among the 16 Angus herds. The breeders' information validated the grouping results and facilitated the comparison of birth weight, age at first calving, number of calves born and productive lifespan data between the four groups, revealing significant differences. We identified the central animals/herd of the Angus population in Hungary. The match of our group descriptions with the phenotypic data provided by the breeders further underscores the value of cooperation between breeders and researchers. CONCLUSION: The observation that significant differences in the measured traits occurred among the identified groups paves the way to further enhancement of breeding efficiency. Our findings have the potential to aid the development of new breeding strategies and help breeders keep the Angus populations in Hungary under genetic supervision. Based on our results the efficient use of an upcoming genomic selection can, in some cases, significantly improve birth weight, age at first calving, number of calves born and the productive lifespan of animals.

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Milk production traits as the most important economic traits of dairy cows, they directly reflect the benefits of breeding and the economic benefits of pasture. In this study, A disintegrin and metalloproteinase-12 (ADAM12), Parkinson's disease gene 2 (PRKN) and dipeptidyl peptidase-like protein subtype 6 (DPP6) polymorphism in 384 Chinese Holstein cows were detected by time-of-flight mass spectrometry and through statistical analysis using software such as Popgene 32, SAS 9.4 and Origin 2022, the relationship between single nucleotide polymorphisms (SNPs) of three genes with four milk production traits such as daily milk yield (DMY), milk fat percentage (MFP), milk protein percentage (MPP) and somatic cell score (SCS) was verified at molecular level. The results showed that four polymorphic loci (116,467,133, 116,604,487, 116,618,268 and 116,835,111) of DPP6 gene, two polymorphic loci (97,665,052 and 97,159,837) of PRKN gene and two polymorphic loci (45,542,714 and 45,553,888) of ADAM12 gene were detected. PRKN-97665052, DPP6-116467133, ADAM12-45553888, DPP6-116604487 and DPP6-116835111 were all in Hardy-Weinberg equilibrium state (p > .05). ADAM12-45542714, PRKN-97159837 and PRKN-97665052 were moderately polymorphic (0.25 ≤ PIC <0.50) in Holstein. It is evident that the selection potential and genetic variation of these five loci are relatively large, and the genetic richness is relatively high. The correlation analysis of different genotypes between these eight loci and milk production traits of Holstein showed that ADAM12-45542714 and DPP6-116835111 (p < .01) had an extremely significant effects on the DMY of Chinese Holstein in Ningxia, while PRKN-97665052 had an extremely significant effect on MFP (p < .01). The effect of PRKN-97665052 and DPP6-116467133 on MPP of Holstein were extremely significant (p < .01). DPP6-116618268 had an extremely significant effect on the SCS of Holstein in Ningxia (p < .01), and AA genotype individuals showed a higher SCS than GG genotype individuals; the other two loci (ADAM12-45553888 and DPP6-116604487) had no significant effects on milk production traits of Holstein (p > .05). In addition, through the joint analysis of DPP6, PRKN and ADAM12 gene loci, it was found that the interaction effect between the three gene loci could significantly affect the DMY, SCS (p < .01) and MPP (p < .05). In conclusion, several different loci of DPP6, PRKN and ADAM12 genes can affect the milk production traits of Holstein to different degrees. PRKN, DPP6 and ADAM12 genes can be used as potential candidate genes for milk production traits of Holstein for marker-assisted selection, providing theoretical basis for breeding of Holstein.

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BACKGROUND: Milk production traits are complex traits with vital economic importance in the camel industry. However, the genetic mechanisms regulating milk production traits in camels remain poorly understood. Therefore, we aimed to identify candidate genes and metabolic pathways that affect milk production traits in Bactrian camels. METHODS: We classified camels (fourth parity) as low- or high-yield, examined pregnant camels using B-mode ultrasonography, observed the microscopic changes in the mammary gland using hematoxylin and eosin (HE) staining, and used RNA sequencing to identify differentially expressed genes (DEGs) and pathways. RESULTS: The average standard milk yield over the 300 days during parity was recorded as 470.18 ± 9.75 and 978.34 ± 3.80 kg in low- and high-performance camels, respectively. Nine female Junggar Bactrian camels were subjected to transcriptome sequencing, and 609 and 393 DEGs were identified in the low-yield vs. high-yield (WDL vs. WGH) and pregnancy versus colostrum period (RSQ vs. CRQ) comparison groups, respectively. The DEGs were compared with genes associated with milk production traits in the Animal Quantitative Trait Loci database and in Alashan Bactrian camels, and 65 and 46 overlapping candidate genes were obtained, respectively. Functional enrichment and protein-protein interaction network analyses of the DEGs and candidate genes were conducted. After comparing our results with those of other livestock studies, we identified 16 signaling pathways and 27 core candidate genes associated with maternal parturition, estrogen regulation, initiation of lactation, and milk production traits. The pathways suggest that emerged milk production involves the regulation of multiple complex metabolic and cellular developmental processes in camels. Finally, the RNA sequencing results were validated using quantitative real-time PCR; the 15 selected genes exhibited consistent expression changes. CONCLUSIONS: This study identified DEGs and metabolic pathways affecting maternal parturition and milk production traits. The results provides a theoretical foundation for further research on the molecular mechanism of genes related to milk production traits in camels. Furthermore, these findings will help improve breeding strategies to achieve the desired milk yield in camels.

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This study provides estimates on genetic parameters, inbreeding depression and purging for meat performance measures from 25 German sheep breeds. All German meat, merino sheep breeds and breeds of other breeding directions with a sufficient number of pedigree and performance data were included in this study. Phenotypic traits retrieved from the national database OviCap were evaluated: daily weight gain, meatiness score and ultrasound measurements for muscle and fat thickness. We employed animal models to estimate heritability, variance and covariance components for these meat performance traits as well as inbreeding depression and purging. The heritabilities, on average, reached estimates of 0.55, 0.34, 0.53 and 0.61 for daily weight gain, meatiness score and ultrasound measurements for muscle and fat thickness, respectively. We estimated the linear regression slopes for the individual rate of inbreeding, new and ancestral inbreeding, as well as the inbreeding coefficient and its interaction with the inbreeding coefficient of Ballou, employing animal models with non-genetic effects and the additive genetic effect of the animal. Across all breeds, inbreeding was only significant for daily weight gain, whereas for all other traits, estimates were not significant. Within sheep breeds, we found significant inbreeding depression for daily weight gain in German Mutton Merino and German Blackheaded Mutton as well as for the meatiness score in German Whiteheaded Mutton. Significant effects for purging, based on ancestral inbreeding and the interaction effect of the classical inbreeding coefficient with the inbreeding coefficient of Ballou, were not obvious either across or within any sheep breed. A 1% increase in inbreeding significantly decreased the phenotypic trait median of daily weight gain across all sheep breeds by 0.50% and 0.70% of phenotypic and genetic standard deviation, respectively. Purging effects due to ancestral inbreeding were not significant in any breed or across breeds. The results of this study may indicate that inbreeding depression may be more harmful in traits under stronger selection than in traits that exert low selection pressure. The results of this study demonstrate the different effects that result in meat performance traits due to inbreeding. With increasing rates of inbreeding and critical effective population sizes, selection intensity for breeding objectives has to be critically reviewed for each sheep breed. Inbreeding depression and purging should be evaluated in order to prevent a decrease in trait means due to inbreeding and to determine whether detrimental alleles are eliminated.

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BACKGROUND: Our previous research identified the Kruppel like factor 6 (KLF6) gene as a prospective candidate for milk production traits in dairy cattle. The expression of KLF6 in the livers of Holstein cows during the peak of lactation was significantly higher than that during the dry and early lactation periods. Notably, it plays an essential role in activating peroxisome proliferator-activated receptor α (PPARα) signaling pathways. The primary aim of this study was to further substantiate whether the KLF6 gene has significant genetic effects on milk traits in dairy cattle. RESULTS: Through direct sequencing of PCR products with pooled DNA, we totally identified 12 single nucleotide polymorphisms (SNPs) within the KLF6 gene. The set of SNPs encompasses 7 located in 5' flanking region, 2 located in exon 2 and 3 located in 3' untranslated region (UTR). Of these, the g.44601035G > A is a missense mutation that resulting in the replacement of arginine (CGG) with glutamine (CAG), consequently leading to alterations in the secondary structure of the KLF6 protein, as predicted by SOPMA. The remaining 7 regulatory SNPs significantly impacted the transcriptional activity of KLF6 following mutation (P < 0.005), manifesting as changes in transcription factor binding sites. Additionally, 4 SNPs located in both the UTR and exons were predicted to influence the secondary structure of KLF6 mRNA using the RNAfold web server. Furthermore, we performed the genotype-phenotype association analysis using SAS 9.2 which found all the 12 SNPs were significantly correlated to milk yield, fat yield, fat percentage, protein yield and protein percentage within both the first and second lactations (P < 0.0001 ~ 0.0441). Also, with Haploview 4.2 software, we found the 12 SNPs linked closely and formed a haplotype block, which was strongly associated with five milk traits (P < 0.0001 ~ 0.0203). CONCLUSIONS: In summary, our study represented the KLF6 gene has significant impacts on milk yield and composition traits in dairy cattle. Among the identified SNPs, 7 were implicated in modulating milk traits by impacting transcriptional activity, 4 by altering mRNA secondary structure, and 1 by affecting the protein secondary structure of KLF6. These findings provided valuable molecular insights for genomic selection program of dairy cattle.

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This trial was carried out to find out the effects of the parent flock and hatching time of broiler chickens on the production traits and bacteriota development of animals. Two sets of 730 hatching eggs were collected from two different parent flocks with ages of 25 and 50 weeks. In the hatchery, both groups were divided into two subgroups: those hatched during the first 10 and the subsequent 10 h of the hatching window. A feeding trial was carried out afterwards, using the four treatments in six replicate floor pens and feeding commercial starter, grower, and finisher diets that contained all the nutrients according to the breeder's recommendations. The day-old chickens of the older parent flock and those hatched later were heavier, and this advantage remained until the end of the production period. The different ages and origins of the parent flocks failed to modify the microbiological parameters of the chicken's ceca; however, the hatching time significantly influenced the different bacteriota diversity indices: the late-hatched chickens showed higher Bacteroidetes and lower Firmicutes and Actinobacteria abundances at day 11. These treatments resulted in differences in the main families, Ruminococcaceae, Lactobacillaceae, and Bacteroidaceae. These differences could not be found at day 39.