Unveiling the Genetic Landscape of Feed Efficiency in Holstein Dairy Cows: Insights into Heritability, Genetic Markers, and Pathways via Meta-Analysis.

Improving 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.

A thorough understanding of the genetic factors that influence the feed efficiency of dairy cows is a prerequisite for planning and implementing selective breeding programs. Therefore, a systematic review of reported heritability, genetic markers, and biological pathways affecting FE-related traits in Holstein dairy cows was conducted and followed by a meta-analysis. A total of 47 articles were refined after literature screening and were presented in this review. A meta-analysis based on a random-effects model was then performed to combine the heritability estimates from studies. The meta-analysis showed heritability estimates of residual feed intake, dry matter intake, and energy balance were 0.22, 0.34, and 0.24, respectively. The systematic review demonstrated that 169 significant candidate genes, 13 genetic markers, and 29 biological mechanisms were previously reported on FE in Holstein dairy cows. Involved candidate genes and biological mechanisms are presented mainly in four biological mechanisms (insulin-like growth factors axis, lipid metabolism, oxidative phosphorylation pathways, tryptophan metabolism). The meta-analysis of the reported candidate genes showed three statistically significant KEGG terms and four GO:BP terms, which mainly focused on ATP synthesis, electron transport chain, and OXPHOS pathway.

Insights into the influence of diet and genetics on feed efficiency and meat production in sheep.

Feed 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.

In-silico characterization of a thermophilic serine protease via homology modeling, docking and molecular dynamics simulations.

One of the major categories of industrial enzymes, proteases is crucial to the survival of living things. The purpose of this research was to newly thermostable protease from the thermophilum Geobacillus stearothermophilus. With the conserved catalytic tetrad, protease (Protease JJ) is closely related to the serine proteases from the subtilisin S8 peptidase, according to phylogenetic tree analysis. The tertiary structure of Protease JJ was predicted structurally using RoseTTAFold, and it is a sandwich structure overall. Homology modeling validation showed Protease JJ was modeled in X-ray's protein areas, and it has gained a favored Ramachandran graph regarding Phi/Psi angels. Protease JJ showed structure stability through Molecular dynamics simulation in the presence of Tween20 and Methanol in 1% concentration. Also, Protease JJ exhibited thermal stability at 60 to 90 °C so that amino acid exposure of Protease JJ was low and constant throughout the MD simulation. Docking results of Protease JJ with BSA and ßcasein were simulated via MD and it was found that Protease JJ could interact with both BSA and ßcasein strongly. MM/PBSA analysis showed Protease JJ may be involved via more amino acids with BSA as well as established more interaction hydrogen bonds. Overall, evidence suggests Protease JJ probably has merit for future experimental investigation as a thermostable protease.Communicated by Ramaswamy H. Sarma.

Identification of Hub Genes and Target miRNAs Crucial for Milk Production in Holstein Friesian Dairy Cattle.

Dairy 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.

Integrated Comparative Transcriptome and circRNA-lncRNA-miRNA-mRNA ceRNA Regulatory Network Analyses Identify Molecular Mechanisms Associated with Intramuscular Fat Content in Beef Cattle.

Intramuscular 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.

De Novo transcriptome assembly and differential expression analysis of catharanthus roseus in response to salicylic acid.

The 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.

Behavioural Traits in Bos taurus Cattle, Their Heritability, Potential Genetic Markers, and Associations with Production Traits.

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 required.

Single Nucleotide Polymorphism Effects on Lamb Fecal Egg Count Estimated Breeding Values in Progeny-Tested Katahdin Sires.

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 between markers and FEC EBV were 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 70 Mb, with LD among these SNP of r 2 ≤ 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 69.9 Mb 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 Mb codes 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.

Human-Animal Interactions with Bos taurus Cattle and Their Impacts on On-Farm Safety: A Systematic Review.

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.

Nontrivial Replication of Loci Detected by Multi-Trait Methods.

The ever-growing genome-wide association studies (GWAS) have revealed widespread pleiotropy. To exploit this, various methods that jointly consider associations of a genetic variant with multiple traits have been developed. Most efforts have been made concerning improving GWAS discovery power. However, how to replicate these discovered pleiotropic loci has yet to be discussed thoroughly. Unlike a single-trait scenario, multi-trait replication is not trivial considering the underlying genotype-multi-phenotype map of the associations. Here, we evaluate four methods for replicating multi-trait associations, corresponding to four levels of replication strength. Weak replication cannot justify pleiotropic genetic effects, whereas strong replication using our developed correlation methods can inform consistent pleiotropic genetic effects across the discovery and replication samples. We provide a protocol for replicating multi-trait genetic associations in practice. The described methods are implemented in the free and open-source R package MultiABEL.

The expression of Terpenoid Indole Alkaloid (TIAs) pathway genes in Catharanthus roseus in response to salicylic acid treatment.

Vinblastine 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 h 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 h 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.

Insulin resistance: Genetic associations with depression and cognition in population based cohorts.

Insulin resistance, broadly defined as the reduced ability of insulin to exert its biological action, has been associated with depression and cognitive dysfunction in observational studies. However, it is unclear whether these associations are causal and whether they might be underpinned by other shared factors. To address this knowledge gap, we capitalized on the stability of genetic biomarkers through the lifetime, and on their unidirectional relationship with depression and cognition. Specifically, we determined the association between quantitative measures of cognitive function and depression and genetic instruments of insulin resistance traits in two large-scale population samples, the Generation Scotland: Scottish Family Health Study (GS: SFHS; N = 19,994) and in the UK Biobank (N = 331,374). In the GS:SFHS, the polygenic risk score (PRS) for fasting insulin was associated with verbal intelligence and depression while the PRS for the homeostasis model assessment of insulin resistance was associated with verbal intelligence. Despite this overlap in genetic architecture, Mendelian randomization analyses in the GS:SFHS and in the UK Biobank samples did not yield evidence for causal associations from insulin resistance traits to either depression or cognition. These findings may be due to weak genetic instruments, limited cognitive measures and insufficient power but they may also indicate the need to identify other biological mechanisms that may mediate the relationship from insulin resistance to depression and cognition.

Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions.

Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.

Author Correction: Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism.

In the version of this article initially published, in Table 2, the descriptions of pathways and definitions in the first and last columns did not correctly correspond to the values in the other columns. The error has been corrected in the HTML and PDF versions of the article.

Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways.

Depression is a polygenic trait that causes extensive periods of disability. Previous genetic studies have identified common risk variants which have progressively increased in number with increasing sample sizes of the respective studies. Here, we conduct a genome-wide association study in 322,580 UK Biobank participants for three depression-related phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. We identify 17 independent loci that are significantly associated (P < 5 × 10-8) across the three phenotypes. The direction of effect of these loci is consistently replicated in an independent sample, with 14 loci likely representing novel findings. Gene sets are enriched in excitatory neurotransmission, mechanosensory behaviour, post synapse, neuron spine and dendrite functions. Our findings suggest that broad depression is the most tractable UK Biobank phenotype for discovering genes and gene sets that further our understanding of the biological pathways underlying depression.

Haplotype Heritability Mapping Method Uncovers Missing Heritability of Complex Traits.

We propose a novel approach to analyze genomic data that incorporates haplotype information for detecting rare variants within a regional heritability mapping framework. The performance of our approach was tested in a simulation study based on human genotypes. The phenotypes were simulated by generating regional variance using either SNP(s) or haplotype(s). Regional genomic relationship matrices, constructed with either a SNP-based or a haplotype-based estimator, were employed to estimate the regional variance. The results from the study show that haplotype heritability mapping captures the regional effect, with its relative performance decreasing with increasing analysis window size. The SNP-based regional mapping approach often misses the effect of causal haplotype(s); however, it has a greater power to detect simulated SNP-based-variants. Heritability estimates suggest that the haplotype heritability mapping estimates the simulated regional heritability accurately for all phenotypes and analysis windows. However, the SNP-based analysis overestimates the regional heritability and performs less well than our haplotype-based approach for the simulated rare haplotype-based-variant. We conclude that haplotype heritability mapping is a useful tool to capture the effect of rare variants, and explain a proportion of the missing heritability.

Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism.

Neuroticism is a relatively stable personality trait characterized by negative emotionality (for example, worry and guilt) 1 ; heritability estimated from twin studies ranges from 30 to 50% 2 , and SNP-based heritability ranges from 6 to 15% 3-6 . Increased neuroticism is associated with poorer mental and physical health 7,8 , translating to high economic burden 9 . Genome-wide association studies (GWAS) of neuroticism have identified up to 11 associated genetic loci 3,4 . Here we report 116 significant independent loci from a GWAS of neuroticism in 329,821 UK Biobank participants; 15 of these loci replicated at P < 0.00045 in an unrelated cohort (N = 122,867). Genetic signals were enriched in neuronal genesis and differentiation pathways, and substantial genetic correlations were found between neuroticism and depressive symptoms (r g = 0.82, standard error (s.e.) = 0.03), major depressive disorder (MDD; r g = 0.69, s.e. = 0.07) and subjective well-being (r g = -0.68, s.e. = 0.03) alongside other mental health traits. These discoveries significantly advance understanding of neuroticism and its association with MDD.

Genome-wide Regional Heritability Mapping Identifies a Locus Within the TOX2 Gene Associated With Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) is the second largest cause of global disease burden. It has an estimated heritability of 37%, but published genome-wide association studies have so far identified few risk loci. Haplotype-block-based regional heritability mapping (HRHM) estimates the localized genetic variance explained by common variants within haplotype blocks, integrating the effects of multiple variants, and may be more powerful for identifying MDD-associated genomic regions. METHODS: We applied HRHM to Generation Scotland: The Scottish Family Health Study, a large family- and population-based Scottish cohort (N = 19,896). Single-single nucleotide polymorphism (SNP) and haplotype-based association tests were used to localize the association signal within the regions identified by HRHM. Functional prediction was used to investigate the effect of MDD-associated SNPs within the regions. RESULTS: A haplotype block across a 24-kb region within the TOX2 gene reached genome-wide significance in HRHM. Single-SNP- and haplotype-based association tests demonstrated that five of nine genotyped SNPs and two haplotypes within this block were significantly associated with MDD. The expression of TOX2 and a brain-specific long noncoding RNA RP1-269M15.3 in frontal cortex and nucleus accumbens basal ganglia, respectively, were significantly regulated by MDD-associated SNPs within this region. Both the regional heritability and single-SNP associations within this block were replicated in the UK-Ireland group of the most recent release of the Psychiatric Genomics Consortium (PGC), the PGC2-MDD (Major Depression Dataset). The SNP association was also replicated in a depressive symptom sample that shares some individuals with the PGC2-MDD. CONCLUSIONS: This study highlights the value of HRHM for MDD and provides an important target within TOX2 for further functional studies.