The Prevalence of Two Common Internal Parasites in White-tailed Deer With and Without Significant Interaction With Domestic Sheep

The objective of this study was to evaluate the prevalence of two internal parasites (strongylate nematodes and Nematodirus spp.) in white-tailed deer (Odocoileus virginianus) sharing a home range with domestic sheep (Ovis aries), compared to deer likely having minimal contact with sheep. Fecal samples were collected from sheep (n=75), deer (n=99) within 300m of the sheep center, and deer (n=98) located 1.3km away from the livestock center, over a 7-week period during the summer. Sheep had the highest (p\u3c.001) number of strongylate eggs (1,212.7 ± 2.8/g) compared to deer near the livestock facility (13.9 ± 0.3/g) or deer located away from the sheep center (18.3 ± 0.3/g). Eggs of Nematodirus spp. were greater (p\u3c.001) in sheep (33.7 ± 0.5/g) compared to deer samples collected near the sheep center (5.1 ± 0.2/g) and deer away from the sheep facility (3.0 ± 0.1/g). Additionally, strongyle and Nematodirus spp. egg counts were different (p\u3c0.001) in the fecal samples collected from deer residing closer to the sheep facility compared to those located farther away. Results of this study suggest the interactions of white-tailed deer and domestic sheep does not influence the prevalence of these internal parasites within the deer

Genetic variance components of the growth curve for Isfahan indigenous chicken

BACKGROUND: Being able to model a growth curve using three or four non-linear functional parameters could help explain the growth phenomenon in a precise way and would allow the comparison of an animal's development rate, optimize management and feeding strategies and guide animal production strategies.OBJECTIVE: The goal of this study was to estimate the genetic parameters of growth traits of Isfahan indigenous chicken in Iran and to determine the best non-linear model describing the growth curve.METHODS: The prediction of additive genetic parameters was performed using the REML method by WOMBAT. Direct heritability of the studied traits and genetic correlations between them were obtained. The Logistic, Gompertz, von Bertalanffy, Brody, Negative exponential, Weibull, Janoschek and Bridges models were compared based on the coefficient of determination (R2 ), mean square error (MSE) and akaike information criterion.RESULTS: The Gompertz model was identified as the best model for describing the growth curve for Isfahan native chicken. The heritability of maturity weights (A), initial weight (B) and maturity rate (K) parameters were 0.223 ± 0.002, 0.016 ± 0.005 and 0.087 ± 0.001, respectively.CONCLUSION: This study shows that Isfahan indigenous chicken has the genetic potential for improving growth and reproduction based on their desirable heritabilities and correlations using appropriate models.</p

Constraint-Based, Score-Based and Hybrid Algorithms to Construct Bayesian Gene Networks in the Bovine Transcriptome

SIMPLE SUMMARY: In this study, we investigated and compared six different Bayesian network algorithms from three different categories to identify hub genes critical to gene expression networks activated in response to progesterone in the bovine uterus. We observed many common hub genes identified between constraint-based algorithms (CBAs) and hybrid algorithms (HAs), while it appeared that score-based algorithm (SBA) methods led to more accurate and relevant predictions of core genes. The results revealed that the identification of hub genes was affected by the type of network reconstruction and by the subsequently used topological parameters. Two identified genes known to have roles during pregnancy are ISG15 and DGAT2. The identified hub genes are associated with biological processes such as amino acid metabolism, hormonal signaling pathways and the immune system. Our analysis revealed a role for miRNAs in the regulation of this system. The biological and physiological roles (enzymatic and hormonal effects) of unannotated identified hub genes should be functionally validated by further studies. ABSTRACT: Bayesian gene networks are powerful for modelling causal relationships and incorporating prior knowledge for making inferences about relationships. We used three algorithms to construct Bayesian gene networks around genes expressed in the bovine uterus and compared the efficacies of the algorithms. Dataset GSE33030 from the Gene Expression Omnibus (GEO) repository was analyzed using different algorithms for hub gene expression due to the effect of progesterone on bovine endometrial tissue following conception. Six different algorithms (grow-shrink, max-min parent children, tabu search, hill-climbing, max-min hill-climbing and restricted maximum) were compared in three higher categories, including constraint-based, score-based and hybrid algorithms. Gene network parameters were estimated using the bnlearn bundle, which is a Bayesian network structure learning toolbox implemented in R. The results obtained indicated the tabu search algorithm identified the highest degree between genes (390), Markov blankets (25.64), neighborhood sizes (8.76) and branching factors (4.38). The results showed that the highest number of shared hub genes (e.g., proline dehydrogenase 1 (PRODH), Sam-pointed domain containing Ets transcription factor (SPDEF), monocyte-to-macrophage differentiation associated 2 (MMD2), semaphorin 3E (SEMA3E), solute carrier family 27 member 6 (SLC27A6) and actin gamma 2 (ACTG2)) was seen between the hybrid and the constraint-based algorithms, and these genes could be recommended as central to the GSE33030 data series. Functional annotation of the hub genes in uterine tissue during progesterone treatment in the pregnancy period showed that the predicted hub genes were involved in extracellular pathways, lipid and protein metabolism, protein structure and post-translational processes. The identified hub genes obtained by the score-based algorithms had a role in 2-arachidonoylglycerol and enzyme modulation. In conclusion, different algorithms and subsequent topological parameters were used to identify hub genes to better illuminate pathways acting in response to progesterone treatment in the bovine uterus, which should help with our understanding of gene regulatory networks in complex trait expression

An Integrated Bioinformatics Approach to Identify Network Derived Hub Genes in Starving Zebrafish

The present study was aimed at identifying causative hub genes within modules formed by co-expression and protein&ndash;protein interaction (PPI) networks, followed by Bayesian network (BN) construction in the liver transcriptome of starved zebrafish. To this end, the GSE11107 and GSE112272 datasets from the GEO databases were downloaded and meta-analyzed using the MetaDE package, an add-on R package. Differentially expressed genes (DEGs) were identified based upon expression intensity N(&micro; = 0.2, &sigma;2 = 0.4). Reconstruction of BNs was performed by the bnlearn R package on genes within modules using STRINGdb and CEMiTool. ndufs5 (shared among PPI, BN and COEX), rps26, rpl10, sdhc (shared between PPI and BN), ndufa6, ndufa10, ndufb8 (shared between PPI and COEX), skp1, atp5h, ndufb10, rpl5b, zgc:193613, zgc:123327, zgc:123178, wu:fc58f10, zgc:111986, wu:fc37b12, taldo1, wu:fb62f08, zgc:64133 and acp5a (shared between COEX and BN) were identified as causative hub genes affecting gene expression in the liver of starving zebrafish. Future work will shed light on using integrative analyses of miRNA and DNA microarrays simultaneously, and performing in silico and experimental validation of these hub-causative (CST) genes affecting starvation in zebrafish

Leveraging Available Resources and Stakeholder Involvement for Improved Productivity of African Livestock in the Era of Genomic Breeding

The African continent is home to diverse populations of livestock breeds adapted to harsh environmental conditions with more than 70% under traditional systems of management. Animal productivity is less than optimal in most cases and is faced with numerous challenges including limited access to adequate nutrition and disease management, poor institutional capacities and lack of adequate government policies and funding to develop the livestock sector. Africa is home to about 1.3 billion people and with increasing demand for animal proteins by an ever growing human population, the current state of livestock productivity creates a significant yield gap for animal products. Although a greater section of the population, especially those living in rural areas depend largely on livestock for their livelihoods; the potential of the sector remains underutilized and therefore unable to contribute significantly to economic development and social wellbeing of the people. With current advances in livestock management practices, breeding technologies and health management, and with inclusion of all stakeholders, African livestock populations can be sustainably developed to close the animal protein gap that exists in the continent. In particular, advances in gene technologies, and application of genomic breeding in many Western countries has resulted in tremendous gains in traits like milk production with the potential that, implementation of genomic selection and other improved practices (nutrition, healthcare, etc.) can lead to rapid improvement in traits of economic importance in African livestock populations. The African livestock populations in the context of this review are limited to cattle, goat, pig, poultry, and sheep, which are mainly exploited for meat, milk, and eggs. This review examines the current state of livestock productivity in Africa, the main challenges faced by the sector, the role of various stakeholders and discusses in-depth strategies that can enable the application of genomic technologies for rapid improvement of livestock traits of economic importance

The Rachel Carson Letters and the Making of Silent Spring

Environment, conservation, green, and kindred movements look back to Rachel Carson’s 1962 book Silent Spring as a milestone. The impact of the book, including on government, industry, and civil society, was immediate and substantial, and has been extensively described; however, the provenance of the book has been less thoroughly examined. Using Carson’s personal correspondence, this paper reveals that the primary source for Carson’s book was the extensive evidence and contacts compiled by two biodynamic farmers, Marjorie Spock and Mary T. Richards, of Long Island, New York. Their evidence was compiled for a suite of legal actions (1957-1960) against the U.S. Government and that contested the aerial spraying of dichlorodiphenyltrichloroethane (DDT). During Rudolf Steiner’s lifetime, Spock and Richards both studied at Steiner’s Goetheanum, the headquarters of Anthroposophy, located in Dornach, Switzerland. Spock and Richards were prominent U.S. anthroposophists, and established a biodynamic farm under the tutelage of the leading biodynamics exponent of the time, Dr. Ehrenfried Pfeiffer. When their property was under threat from a government program of DDT spraying, they brought their case, eventually lost it, in the process spent US$100,000, and compiled the evidence that they then shared with Carson, who used it, and their extensive contacts and the trial transcripts, as the primary input for Silent Spring. Carson attributed to Spock, Richards, and Pfeiffer, no credit whatsoever in her book. As a consequence, the organics movement has not received the recognition, that is its due, as the primary impulse for Silent Spring, and it is, itself, unaware of this provenance

Genomic Prediction Accuracies for Growth and Carcass Traits in a Brangus Heifer Population

The predictive abilities and accuracies of genomic best linear unbiased prediction (GBLUP) and the Bayesian (BayesA, BayesB, BayesC and Lasso) genomic selection (GS) methods for economically important growth (birth, weaning, and yearling weights) and carcass (depth of rib fat, apercent intramuscular fat and longissimus muscle area) traits were characterized by estimating the linkage disequilibrium (LD) structure in Brangus heifers using single nucleotide polymorphisms (SNP) markers. Sharp declines in LD were observed as distance among SNP markers increased. The application of the GBLUP and the Bayesian methods to obtain the GEBV for growth and carcass traits within k-means and random clusters showed that k-means and random clustering had quite similar heritability estimates, but the Bayesian methods resulted in the lower estimates of heritability between 0.06 and 0.21 for growth and carcass traits compared with those between 0.21 and 0.35 from the GBLUP methodologies. Although the prediction ability of the GBLUP and the Bayesian methods were quite similar for growth and carcass traits, the Bayesian methods overestimated the accuracies of GEBV because of the lower estimates of heritability of growth and carcass traits. However, GBLUP resulted in accuracy of GEBV for growth and carcass traits that parallels previous reports

Sequence variation of necdin gene in Bovidae

Abstract Background Necdin (NDN), a member of the melanoma antigen family showing imprinted pattern of expression, has been implicated as causing Prader-Willi symptoms, and known to participate in cellular growth, cellular migration and differentiation. The region where NDN is located has been associated to QTLs affecting reproduction and early growth in cattle, but location and functional analysis of the molecular mechanisms have not been established. Methods Here we report the sequence variation of the entire coding sequence from 72 samples of cattle, yak, buffalo, goat and sheep, and discuss its variation in Bovidae. Median-joining network analysis was used to analyze the variation found in the species. Synonymous and non-synonymous substitution rates were determined for the analysis of all the polymorphic sites. Phylogenetic analysis were carried out among the species of Bovidae to reconstruct their relationships. Results From the phylogenetic analysis with the consensus sequences of the studied Bovidae species, we found that only 11 of the 26 nucleotide changes that differentiate them produced amino acid changes. All the SNPs found in the cattle breeds were novel and showed similar percentages of nucleotides with non-synonymous substitutions at the N-terminal, MHD and C-terminal (12.3, 12.8 and 12.5%, respectively), and were much higher than the percentage of synonymous substitutions (2.5, 2.6 and 4.9%, respectively). Three mutations in cattle and one in sheep, detected in heterozygous individuals were predicted to be deleterious. Additionally, the analysis of the biochemical characteristics in the most common form of the proteins in each species show very little difference in molecular weight, pI, net charge, instability index, aliphatic index and GRAVY (Table 4) in the Bovidae species, except for sheep, which had a higher molecular weight, instability index and GRAVY. Conclusions There is sufficient variation in this gene within and among the studied species, and because NDN carry key functions in the organism, it can have effects in economically important traits in the production of these species. NDN sequence is phylogenetically informative in this group, thus we propose this gene as a phylogenetic marker to study the evolution and conservation in Bovidae

Conservation of Repeats at the Mammalian KCNQ1OT1-CDKN1C Region Suggests a Role in Genomic Imprinting

KCNQ1OT1 is located in the region with the highest number of genes showing genomic imprinting, but the mechanisms controlling the genes under its influence have not been fully elucidated. Therefore, we conducted a comparative analysis of the KCNQ1/KCNQ1OT1-CDKN1C region to study its conservation across the best assembled eutherian mammalian genomes sequenced to date and analyzed potential elements that may be implicated in the control of genomic imprinting in this region. The genomic features in these regions from human, mouse, cattle, and dog show a higher number of genes and CpG islands (detected using cpgplot from EMBOSS), but lower number of repetitive elements (including short interspersed nuclear elements and long interspersed nuclear elements), compared with their whole chromosomes (detected by RepeatMasker). The KCNQ1OT1-CDKN1C region contains the highest number of conserved noncoding sequences (CNS) among mammals, where we found 16 regions containing about 38 different highly conserved repetitive elements (using mVista), such as LINE1 elements: L1M4, L1MB7, HAL1, L1M4a, L1Med, and an LTR element: MLT1H. From these elements, we found 74 CNS showing high sequence identity (>70%) between human, cattle, and mouse, from which we identified 13 motifs (using Multiple Em for Motif Elicitation/Motif Alignment and Search Tool) with a significant probability of occurrence, 3 of which were the most frequent and were used to find transcription factor–binding sites. We detected several transcription factors (using JASPAR suite) from the families SOX, FOX, and GATA. A phylogenetic analysis of these CNS from human, marmoset, mouse, rat, cattle, dog, horse, and elephant shows branches with high levels of support and very similar phylogenetic relationships among these groups, confirming previous reports. Our results suggest that functional DNA elements identified by comparative genomics in a region densely populated with imprinted mammalian genes may be related to the regulation of imprinted gene expression