Browsing by Author "Shirali, Masoud"
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Item Behavioural Traits in Bos taurus Cattle, Their Heritability, Potential Genetic Markers, and Associations with Production Traits.(MDPI, 2022-09-28) Titterington, Frances Margaret; Knox, Rachel; Morrison, Steven J.; Shirali, MasoudSimple Summary Cattle have the potential to seriously injure humans and cause damage to property. The risk of cattle reacting in a dangerous manner can be reduced through genetic selection for cattle which have a better temperament. A literature search was undertaken which returned papers which met the criteria of “Bovine”, “Genetics” and “Behaviour” or terms therein. Behavioural traits were grouped and their heritability, genomic associations and correlations with production traits examined. It was found that heritability estimates were more accurate in studies with large populations (n > 1000). Gene associations with behavioural traits were found on all chromosomes except for chromosome 13, with associated SNPs reported on all chromosomes except 5, 13, 17, 18 and 23. Generally, it was found that correlations between behaviour and production traits were low or negligible, suggesting that genetic improvement can be undertaken without negatively affecting production. There was variation between the results of the studies examined, and this underlines that any genetic study is population specific. Thus, to assess the heritability, genetic associations with production and genomic areas of interest for behavioural traits, a large-scale study of the population of interest would be required. Abstract People who work with cattle are at severe risk of serious injury due to the size and strength of the cattle. This risk can be minimised by breeding less dangerous cattle, which have a more favourable reaction to humans. This study provides a systematic review of literature pertaining to cattle genetics relating to behaviour. The review protocol was developed using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework, with Population, Exposure and Outcome components identified as Bovine, Genetics and Behaviour respectively. Forty-nine studies were identified in the sifting and assigned non-exclusively to groups of heritability (22), genomic associations (13) and production traits related to behaviour (24). Behavioural traits were clustered into the following groups: “temperament, disposition and/ or docility”, “aggression”, “chute score”, “flight speed”, “milking temperament”, “non-restrained methods” and “restrained methods”. Fourteen papers reported high accuracy (Standard Error ≤ 0.05) estimates of heritability, the majority (n = 12) of these studies measured over 1000 animals. The heritability estimates were found to vary between studies. Gene associations with behavioural traits were found on all chromosomes except for chromosome 13, with associated SNPs reported on all chromosomes except 5, 13, 17, 18 and 23. Generally, it was found that correlations between behaviour and production traits were low or negligible. These studies suggest that additive improvement of behavioural traits in cattle is possible and would not negatively impact performance. However, the variation between studies demonstrates that the genetic relationships are population specific. Thus, to assess the heritability, genetic associations with production and genomic areas of interest for behavioural traits, a large-scale study of the population of interest would be requiredItem Bioinformatics analysis of differentially gene expression profiles related to heat stress in brain, liver, and leg muscle of broiler chickens based on microarray technique(University of Tehran Press, 2023-09-23) Ekhtiyari, Mohammad Soleiman; Javanmard, Arash; Ghafouri, Farzad; Sadr, Ayeh Sadat; Miraei-Ashtiani, Seyed Reza; Shirali, Masoud; EconomicsIn the poultry industry, the heat stress caused by high environmental temperature has a negative influence on broiler chicken performance and has become a major challenge. Transcriptome profile analysis of the data and identification of patterns of differential gene expression in related tissues can be involved in the discovery of molecular mechanisms resistant to heat stress. The main purpose of this study was to use transcriptome profiles of three tissues brain, liver, and leg muscle of two groups of the control and heat stress broiler chickens to identify candidate genes associated with heat stress. By the analysis of microarray data to express the gene differences, 657 significant genes (P<0.05) were extracted, which a total of 94 genes showed significant expression differences (FDR < 0.05, Fold change > ± 2). Then, by studying the ontology of the relevant genes resulting from data analysis and literature mining as well as the reconstructed protein-protein interaction network, hub genes including NSDHL, DHCR24, LSS, FDPS, PCK1, ACTA1, HSP90AA1, HSPA2, HSPB1, HSF1, CRYAB, APOB, and IL6 were identified. Annotation results of these genes indicated that they have a role in the main process of metabolic and signaling pathways related to the ion transport system, steroid, antibodies, cholesterol biosynthesis, lipid metabolism, immune system function, and various signaling pathways such as MAP kinase, RET, and ERK. Overall, the present study can provide new insights into evidence of the pathways activated by these genes to identify effective genes and a better understanding of biological processes related to heat stress.Item Competing Endogenous RNAs (ceRNAs) and Application of Their Regulatory Networks in Complex Traits and Diseases of Ruminants(MDPI, 2024-04-01) Ghafouri, Farzad; Dehghanian Reyhan, Vahid; Sadeghi, Mostafa; Miraei-Ashtiani, Seyed Reza; Kastelic, John P.; Barkema, Herman W.; Shirali, Masoud; Sustainable LivestockThis manuscript summarizes information on the diverse range of RNA molecules and their role as competing endogenous RNAs (ceRNAs). Moreover, it provides an overview of ceRNA regulatory networks and their applications in ruminant biology. Knowledge of co-expression networks has increased with microarrays, RNA-seq, and scRNA-seq characterizing molecular mediators across various biological scales, using sequences from numerous blood and tissue samples. By synthesizing existing knowledge, this study summarizes interactions between coding and non-coding RNAs through microRNA response elements (MREs), elucidating large-scale regulatory networks throughout the transcriptome that influence the expression and activities of various ceRNAs. Identification of non-coding RNAs with important regulatory functions will revolutionize understanding of RNA biology, shifting from an mRNA-centric model to a complex network of RNA crosstalk. The ceRNA networks offer a more comprehensive and arguably more realistic perspective compared to protein–protein interaction (PPI) networks and weighted gene co-expression networks (WGCN). These ceRNA regulatory networks can describe potential molecular regulatory mechanisms related to functional and economically important traits in ruminants, plus contribute to disease and pathology research, by elucidating pathogenesis and potential drug effects in disease and cancer models. Furthermore, they can provide insights into farm animal biology, e.g., reproductive traits in goats and sheep, regulation of fat metabolism in beef cattle, heat stress responses, and lactation regulation in dairy cattle, fertility and muscle characteristics in buffalo, and resistance to high-salt and water-deprivation conditions in camels. In conclusion, ceRNA and associated regulatory networks should promote a new understanding of molecular mechanisms and identify candidate genes and metabolic-signaling pathways in ruminants.Item Evaluation of three methods related to Genome-Wide Association studies for identify gene locus using simulated data(University of Tabriz, 2022-03-16) Beiranvand, Fatemeh; Nassiri, Mohamad Taghi Beigi; Shirali, Masoud; Shirali, MahmoudIntroduction: Due to the widespread distribution of SNPs throughout the genome, these markers are widely used in livestock breeding research. These markers were used to predict the disease risk in human, to localize genetic variations responsible for complex traits through genome wide association study (GWAS), and to predict the genetic values of economically important traits in plant and animal breeding (Zhang et al 2015). Mostly whole genome scanning methods are based on two SSGWAS (Single SNP Genome-Wide Association Studies) and multiple markers methods. The SSGWAS method is able to identify a large number of common variables affecting quantitative traits. However, a large proportion of the genetic variance remains to be explained (Shirali et al 2018). In quantitative traits the proportion of phenotypic variance explained by SNPs is related to the number of adjacent SNPs in the genomic region. The heritability created by these genomic regions is defined as the regional heritability. The RHM (Regional Heritability Mapping) method is used to identify small genomic regions. This method can capture more of the missing genetic variation (Nagamine et al 2012). In RHM, a mixed model framework based on Restricted Maximum Likelihood (REML) is used, and two variance components, one contributed by the whole genome and a second one by a specific genomic region, are fitted in the model to estimate genomic and regional heritabilities, respectively (Uemoto et al 2013). Also fastBAT (fast and flexible set-Based Association Test) is a method that performs a fast set-based association analysis (Bakshi et al 2016). The purpose of this study is compare SNPs and regions identified by the Genome-Wide Association methods, compare these results with the simulated QTLs and also investigate and determine the false positive results in each method. Material and methods: In this study, markers and populations were simulated as a Forward-in-time process using QMSim software (Sargolzaei and Schenkel 2009). For this population, 27586 single nucleotide polymorphisms (SNPs) were counted on 3 pairs of autosomal chromosomes. Simulation was performed in 3 scenarios with 75, 150 and 300 quantitative trait loci (QTL). The minimum and maximum number of SNPs in the analysis after quality control were 19662 and 23817 SNPs, respectively. For each scenario, 10 replicates were simulated, in all scenarios, heritability was 0.2 which corresponded equally to the polygenic and QTLs effects. Whole genomic relationship and pedigree base genetic relationship matrices were used in all 3 methods to estimate genetic parameters. To create the whole genomic relationships matrix, whole genomic additive effects was estimated using all SNPs. Also the additive effect of genomic regions was estimated using the regional genomic relationship matrix. Whole genomic relationships matrix and regional genomic relationship matrix were estimated based on genetic relationships between individuals using SNPs by GCTA software (Yang et al 2011). Pedigree based genetic relationship matrix was created by the kinship relationship between individuals using pedigree package (Coster 2013) of RStudio software (RStudio Inc 2013). To perform RHM and to estimate variance components, windows containing 50 genotyped SNPs were considered. Also windows containing 25 genotyped SNPs to overlap between two consecutive windows throughout the genome were used. SSGWAS analysis were performed by MLMA (Yu et al 2006) method using GCTA software. MLMA results were adjusted based on P-value at 5% significant threshold using Bonferroni correction. To evaluate the results of SSGWAS using fastBAT method, GCTA software was used. Results and discussion: For each replication after identifying significant SNPs, the genetic variance explained by these SNPs was estimated by equation (Faulkner & McKay 1996). In Table 1, the number of QTLs detected by the SSGWAS method, the MAF of QTLs, the range and mean of genetic variance explained by significant SNPs and QTLs are reported. For 30 replicates of simulation in SSGWAS, 16 QTLs were detected containing 2 QTLs with MAF≤0.1 and other detected QTLs with MAF≥0.1. 107 Significant regions were identified in fastBAT method. In this method, 120 QTLs were detected in 3 scenarios containing 52 QTLs with MAF≤0.1. All QTLs detected in the fastBAT and SSGWAS methods were also detected in the RHM method. In RHM method, 612 regions containing simulated QTLs and number of 316 QTLs with MAF≤0.1 were detected. In all replications, the variance explained by SNPs was equal to the variance explained by QTLs. In SSGWAS, less number of QTLs were detected than the other two methods and the maximum variance explained by QTLs was 14.9%. The criterion used to determine false positive QTLs was the absence of significant QTL in the before and after significant windows containing QTLs. In SSGWAS method the percentage of false positive QTLs was higher than the other two methods. In fastBAT, unlike the other two methods, detected QTLs were not false positive. In table 5 Number of detected QTLs, MAF range of QTLs, range and mean of genetic variance explained by detected QTLs and SNPs in fastBAT are shown. Many QTLs and regions detected by RHM method were not detected by SSGWAS and fastBAT methods. The genetic variance explained by detected QTLs in the RHM was at the range of 7.26 to 46.86% that was higher than other two methods. In table 6 the three methods compared by the number of detected QTLs, number of false positive QTLs, number of stable QTLs and the number of detected QTLs with MAF≤0.1. We found that QTLs with MAF≤0.1 were more frequently detected in RHM than the other two methods. These results confirmed that the RHM method was able to identifying more of QTLs affecting the trait variance.Item The Expression of Terpenoid Indole Alkaloid (TIAs) Pathway Genes in Catharanthus roseus in Response to Salicylic Acid treatment(Springer, 2020-08-26) Soltani, Narges; Nazarian-Firouzabadi, Farhad; Shafeinia, Alireza; Sadr, Ayeh Sadat; Shirali, MasoudVinblastine and vincristine are two important anti-cancer drugs that are synthesized by the Terpenoid Indole Alkaloids (TIAs) pathway in periwinkle (Catharanthus roseus). The major challenge in the pharmaceutical industry is the low production rate of these alkaloids. TIA pathway is affected by elicitors, such as salicylic acid (SA). This study aimed to investigate the expression pattern of some key genes in TIAs pathway under SA treatment. Foliar application of SA (0.01 and 0.1 mM) was used and leaves samples were taken at 0, 12, 18, 24 and 48 hours after the treatment. qRT-PCR was used to investigate the expression pattern of Chorismate mutase (Cm), Tryptophan decarboxylase (Tdc), Geraniol-10-hydroxylase (G10h), Secologanin synthase (Sls), Strictosidine synthase (Str), Desacetoxyvindoline-4-hydroxylase (D4h) and Deacetylvindoline-4-O-acetyltransferase (Dat) genes, following the SA treatment. The results of this experiment showed that transcript levels of Tdc, G10h, Sls, Str, D4h and Dat genes were significantly up-regulated in both SA concentration treatments. Furthermore, the highest transcript levels of Dat was observed after 48 hours of the SA treatments. qRT-PCR results suggests that SA induces transcription of major genes involved in alkaloids biosynthesis in Catharanthus roseus. It can be concluded that up-regulation of Tdc, G10h, Sls, Str, D4h and Dat genes can result in a higher production rate of vinblastine and vincristine alkaloids.Item Human–Animal Interactions with Bos taurus Cattle and Their Impacts on On-Farm Safety: A Systematic Review(MDPI, 2022-03-19) Titterington, Frances; Knox, Rachel; Buijs, Stephanie; Lowe, Denise; Morrison, Steven; Lively, Francis; Shirali, MasoudSimple Summary: Cattle are large animals that can cause serious injuries to humans. Humans may encounter cattle through working on farms, living on a farm, or traversing fields with cattle. A systematic review was carried out to assess the factors which may lead to a dangerous interaction with cattle. A literature search was carried out to find papers that included the criteria ‘Bovine’, ‘Handling’, ‘Behaviour’ and ‘Safety’, or terms therein. The search returned 17 papers, and after collation, six themes were identified: actions of humans; human demographics, attitude, and experience; facilities and the environment; the animal involved; under-reporting and poor records; and mitigation of dangerous interactions. Exploration of these themes shows that more accurate recording of interactions before an injury is required. Furthermore, targeted, tailored education for anyone who may come into contact with cattle could reduce cattle-induced injuries. Abstract: Cattle production necessitates potentially dangerous human–animal interactions. Cattle are physically strong, large animals that can inflict injuries on humans accidentally or through aggressive behaviour. This study provides a systematic review of literature relating to farm management practices (including humans involved, facilities, and the individual animal) associated with cattle temperament and human’s on-farm safety. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) was used to frame the review. Population, Exposure, and Outcomes (PEO) components of the research question are defined as “Bovine” (population), “Handling” (exposure), and outcomes of “Behaviour”, and “Safety”. The review included 17 papers and identified six main themes: actions of humans; human demographics, attitude, and experience; facilities and the environment; the animal involved; under-reporting and poor records; and mitigation of dangerous interactions. Cattle-related incidents were found to be underreported, with contradictory advice to prevent injury. The introduction of standardised reporting and recording of incidents to clearly identify the behaviours and facilities which increase injuries could inform policy to reduce injuries. Global differences in management systems and animal types mean that it would be impractical to impose global methods of best practice to reduce the chance of injury. Thus, any recommendations should be regionally specific, easily accessible, and practicable.Item Identification of hub genes and target miRNAs crucial for milk production in Holstein Friesian dairy cattle(MDPI, 2023-11-20) Roudbari, Zahra; Mokhtari, Morteza; Gorji, Abdolvahab Ebrahimpour; Sadkowski, Tomasz; Sadr, Ayeh Sadat; Shirali, Masoud; Sustainable LivestockDairy milk production is a quantitative trait that is controlled by many biological and environmental factors. This study employs a network-driven systems approach and clustering algorithm to uncover deeper insights into its genetic associations. We analyzed the GSE33680 dataset from the GEO database to understand the biological importance of milk production through gene expression and modules. In this study, we employed CytoNCA and ClusterONE plugins within Cytoscape for network analysis. Moreover, miRWalk software was utilized to detect miRNAs, and DAVID was employed to identify gene ontology and pathways. The results revealed 140 up-regulated genes and 312 down-regulated genes. In addition, we have identified 91 influential genes and 47 miRNAs that are closely associated with milk production. Through our examination of the network connecting these genes, we have found significant involvement in important biological processes such as calcium ion transit across cell membranes, the BMP signaling pathway, and the regulation of MAPK cascade. The conclusive network analysis further reveals that GAPDH, KDR, CSF1, PYGM, RET, PPP2CA, GUSB, and PRKCA are closely linked to key pathways essential for governing milk production. Various mechanisms can control these genes, making them valuable for breeding programs aiming to enhance selection indexes.Item In silico Methods for Modeling of Genomic Regions for Immunological and Metabolic Gene Modulating to Stress Response in Chicken: Where We Are?(Islamic Azad University, Rasht Branch, Islamic Republic of Iran, 2022-09-01) Ekhtiyari, M.S.; Sadr, A.S.; Shirali, Masoud; Javanmard, A.Traditionally, commercial broilers are not well adapted and currently subjected to a variety of environmental challenges. In recent years, researchers have shown an increased interest in stress as one of the greatest environmental challenges to the profitability of sustainable intensive poultry production. In this scenario, understanding the complexity of the molecular basis and genomics of the stress response is critical to successful breeding programs for climate-adapted chickens. Recently, numerous popular studies have attempted to identify candidate genes that control stress responses in chickens. However, a number of questions regarding the choice of stress response remain unanswered or inadequately answered regarding the number of lead candidate genes that control components of the non-infectious and infectious stress response. With this motivation, 89 journal articles were collected for the primary investigation and those with low validity were excluded from further analysis. In short, we used three types of information sources, namely: text-based systematic review, in silico modeling, and both network and pathway approaches, to introduce more effective and bio-indicators of gene-controlling stress responses in chickens through older literature. Gene ontology (GO) and pathway networking of candidate gene associated with stress was loaded into Cytoscape for analysis. The result provides additional evidence and highlights, including nearly 9 candidate genes. According to published studies, CRYAB, HSP90AA1, IL6, HSPA2, HSF2, HSPB1, HSF3, PLK1, BAG3 are mostly associated with non-infectious and infectious stressors and may deserve further attention. String database analysis illustrated role of highlighted gene in multiple cellular task and functionally such as ATPase activity, cellular processes, including protection of the proteome from stress, folding and transport of newly synthesized polypeptides, activation of proteolysis of misfold proteins and the formation and dissociation of protein complexes. Obtained information from Animal QTL database indicated important role of chromosomes numbers 2, 3, 4, 5, 12, 14 and 24 associated with stress resistance and susceptibility. On this basis, this report attempts to find out whicItem Insights into the influence of diet and genetics on feed efficiency and meat production in sheep(Wiley, 2023-12-19) Chacko Kaitholil, Steffimol Rose; Mooney, Mark H.; Aubry, Aurélie; Rezwan, Faisal; Shirali, Masoud; Animal Health and WelfareFeed costs and carcass yields affect the profitability and sustainability of sheep production. Therefore, it is crucial to select animals with a higher feed efficiency and high-quality meat production. This study focuses on the impact of dietary and genetic factors on production traits such as feed efficiency, carcass quality, and meat quality. Diets promote optimal sheep growth and development and provide sufficient protein can lead to higher-quality meat. However, establishing an optimized production system requires careful consideration and balance of dietary parameters. This includes ensuring adequate protein intake and feeding diets with higher intestinal absorption rates to enhance nutrient absorption in the gut. The study identifies specific genes, such as Callipyge, Calpastatin, and Myostatin, and the presence of causal mutations in these genes, as factors influencing animal growth rates, feed efficiency, and meat fatty acid profiles. Additionally, variants of other reported genes, including PIGY, UCP1, MEF2B, TNNC2, FABP4, SCD, FASN, ADCY8, ME1, CA1, GLIS1, IL1RAPL1, SOX5, SOX6, and IGF1, show potential as markers for sheep selection. A meta-analysis of reported heritability estimates reveals that residual feed intake (0.27 ± 0.07), hot carcass weight (0.26 ± 0.05), dressing percentage (0.23 ± 0.05), and intramuscular fat content (0.45 ± 0.04) are moderately to highly heritable traits. This suggests that these traits are less influenced by environmental factors and could be improved through genetic selection. Additionally, positive genetic correlations exist between body weight and hot carcass weight (0.91 ± 0.06), dressing percentage (0.35 ± 0.15), and shear force (0.27 ± 0.24), indicating that selecting for higher body weight could lead to favorable changes in carcass quality, and meat quality.Item Integrated Comparative Transcriptome and circRNA-lncRNA-miRNA-mRNA ceRNA Regulatory Network Analyses Identify Molecular Mechanisms Associated with Intramuscular Fat Content in Beef Cattle(MDPI, 2023-08-11) Dehghanian Reyhan, Vahid; Ghafouri, Farzad; Sadeghi, Mostafa; Miraei-Ashtiani, Seyed Reza; Kastelic, John P.; Barkema, Herman W.; Shirali, MasoudIntramuscular fat content (IMF), one of the most important carcass traits in beef cattle, is controlled by complex regulatory factors. At present, molecular mechanisms involved in regulating IMF and fat metabolism in beef cattle are not well understood. Our objective was to integrate comparative transcriptomic and competing endogenous RNA (ceRNA) network analyses to identify candidate messenger RNAs (mRNAs) and regulatory RNAs involved in molecular regulation of longissimus dorsi muscle (LDM) tissue for IMF and fat metabolism of 5 beef cattle breeds (Angus, Chinese Simmental, Luxi, Nanyang, and Shandong Black). In total, 34 circRNAs, 57 lncRNAs, 15 miRNAs, and 374 mRNAs were identified by integrating gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, 7 key subnets with 16 circRNAs, 43 lncRNAs, 7 miRNAs, and 237 mRNAs were detected through clustering analyses, whereas GO enrichment analysis of identified RNAs revealed 48, 13, and 28 significantly enriched GO terms related to IMF in biological process, molecular function, and cellular component categories, respectively. The main metabolic-signaling pathways associated with IMF and fat metabolism that were enriched included metabolic, calcium, cGMP-PKG, thyroid hormone, and oxytocin signaling pathways. Moreover, MCU, CYB5R1, and BAG3 genes were common among the 10 comparative groups defined as important candidate marker genes for fat metabolism in beef cattle. Contributions of transcriptome profiles from various beef breeds and a competing endogenous RNA (ceRNA) regulatory network underlying phenotypic differences in IMF provided novel insights into molecular mechanisms associated with meat quality.Item De novo Transcriptome Assembly and Differential Expression Analysis of Catharanthus roseus in Response to Salicylic acid(Nature Research, 2022-10-24) Soltani, Narges; Firouzabadi, Farhad Nazarian; Shafeinia, Alireza; Shirali, Masoud; Sadr, Ayeh SadatThe anti-cancer vinblastine and vincristine alkaloids can only be naturally found in periwinkle (Catharanthus roseus). Both of these alkaloids' accumulations are known to be influenced by salicylic acid (SA). The transcriptome data to reveal the induction effect (s) of SA, however, seem restricted at this time. In this study, the de novo approach of transcriptome assembly was performed on the RNA-Sequencing (RNA-Seq) data in C. roseus. The outcome demonstrated that SA treatment boosted the expression of all the genes in the Terpenoid Indole Alkaloids (TIAs) pathway that produces the vinblastine and vincristine alkaloids. These outcomes supported the time-course measurements of vincristine alkaloid, the end product of the TIAs pathway, and demonstrated that SA spray had a positive impact on transcription and alkaloid synthesis. Additionally, the abundance of transcription factor families including bHLH, C3H, C2H2, MYB, MYB-related, AP2/ ERF, NAC, bZIP, and WRKY suggests a role for a variety of transcription families in response to the SA stimuli. Di-nucleotide and tri-nucleotide SSRs were the most prevalent SSR markers in microsatellite analyses, making up 39% and 34% of all SSR markers, respectively, out of the 77,192 total SSRs discovered.Item Single Nucleotide Polymorphism Effects on Lamb Fecal Egg Count Estimated Breeding Values in Progeny-Tested Katahdin Sires(2022-05-03) Notter, David R.; Heidaritabar, Marzieh; Burke, Joan M.; Shirali, Masoud; Murdoch, Brenda M.; Morgan, James L. M.; Morota, Gota; Sonstegard, Tad S.; Becker, Gabrielle M.; Spangler, Gordon L.; MacNeil, Michael D.; Miller, James E.Estimated breeding values (EBV) for fecal egg counts (FEC) at 42–90 days of age (WFEC) and 91–150 days of age (PFEC) for 84 progeny-tested Katahdin sires were used to identify associations of deregressed EBV with single-nucleotide polymorphisms (SNP) using 388,000 SNP with minor-allele frequencies ≥0.10 on an Illumina high-density ovine array. Associations betweenmarkers and FEC EBVwere initially quantified by single-SNP linear regression. Effects of linkage disequilibrium (LD) were minimized by assigning SNP to 2,535 consecutive 1-Mb bins and focusing on the effect of the most significant SNP in each bin. Bonferroni correction was used to define bin-based (BB) genome- and chromosome-wide significance. Six bins on chromosome 5 achieved BB genome-wide significance for PFEC EBV, and three of those SNP achieved chromosome-wide significance after Bonferroni correction based on the 14,530 total SNP on chromosome 5. These bins were nested within 12 consecutive bins between 59 and 71 Mb on chromosome 5 that reached BB chromosome-wide significance. The largest SNP effects were at 63, 67, and 70Mb, with LD among these SNP of r2 ≤ 0.2. Regional heritability mapping (RHM) was then used to evaluate the ability of different genomic regions to account for additive variance in FEC EBV. Chromosome-level RHM indicated that one 500-SNP window between 65.9 and 69.9Mb accounted for significant variation in PFEC EBV. Five additional 500-SNP windows between 59.3 and 71.6 Mb reached suggestive (p < 0.10) significance for PFEC EBV. Although previous studies rarely identified markers for parasite resistance on chromosome 5, the IL12B gene at 68.5 Mbcodes for the p40 subunit of both interleukins 12 and 23. Other immunoregulatory genes are also located in this region of chromosome 5, providing opportunity for additive or associative effects.Item Unveiling the Genetic Landscape of Feed Efficiency in Holstein Dairy Cows: Insights into Heritability, Genetic Markers, and Pathways via Meta-Analysis(Oxford University Press, 2024-02-13) Jiang, Wentao; Mooney, Mark H.; Shirali, Masoud; Sustainable LivestockImproving the feeding efficiency of dairy cows is a key component to improve the utilization of land resources and meet the demand for high-quality protein. Advances in genomic methods and omics techniques have made it possible to breed more efficient dairy cows through genomic selection. The aim of this review is to obtain a comprehensive understanding of the biological background of feed efficiency (FE) complex traits in purebred Holstein dairy cows including heritability estimate, and genetic markers, genes, and pathways participating in FE regulation mechanism. Through a literature search, we systematically reviewed the heritability estimation, molecular genetic markers, genes, biomarkers, and pathways of traits related to feeding efficiency in Holstein dairy cows. A meta-analysis based on a random-effects model was performed to combine reported heritability estimates of FE complex. The heritability of residual feed intake, dry matter intake, and energy balance was 0.20, 0.34, and 0.22, respectively, which proved that it was reasonable to include the related traits in the selection breeding program. For molecular genetic markers, a total of 13 single-nucleotide polymorphisms and copy number variance loci, associated genes, and functions were reported to be significant across populations. A total of 169 reported candidate genes were summarized on a large scale, using a higher threshold (adjusted P value < 0.05). Then, the subsequent pathway enrichment of these genes was performed. The important genes reported in the articles were included in a gene list and the gene list was enriched by gene ontology (GO):biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis. Three GO:BP terms and four KEGG terms were statistically significant, which mainly focused on adenosine triphosphate (ATP) synthesis, electron transport chain, and OXPHOS pathway. Among these pathways, involved genes such as ATP5MC2, NDUFA, COX7A2, UQCR, and MMP are particularly important as they were previously reported. Twenty-nine reported biological mechanisms along with involved genes were explained mainly by four biological pathways (insulin-like growth factor axis, lipid metabolism, oxidative phosphorylation pathways, tryptophan metabolism). The information from this study will be useful for future studies of genomic selection breeding and genetic structures influencing animal FE. A better understanding of the underlying biological mechanisms would be beneficial, particularly as it might address genetic antagonism.