44 research outputs found
Identification of SNP markers for resistance to Salmonella and IBDV in indigenous Ethiopian chickens
Comparison of eleven methods for genomic DNA extraction suitable for large-scale whole-genome genotyping and long-term DNA banking using blood samples
Over the recent years, next generation sequencing and microarray technologies have revolutionized scientific research with their applications to high-throughput analysis of biological systems. Isolation of high quantities of pure, intact, double stranded, highly concentrated, not contaminated genomic DNA is prerequisite for successful and reliable large scale genotyping analysis. High quantities of pure DNA are also required for the creation of DNA-banks. In the present study, eleven different DNA extraction procedures, including phenol-chloroform, silica and magnetic beads based extractions, were examined to ascertain their relative effectiveness for extracting DNA from ovine blood samples. The quality and quantity of the differentially extracted DNA was subsequently assessed by spectrophotometric measurements, Qubit measurements, real-time PCR amplifications and gel electrophoresis. Processing time, intensity of labor and cost for each method were also evaluated. Results revealed significant differences among the eleven procedures and only four of the methods yielded satisfactory outputs. These four methods, comprising three modified silica based commercial kits (Modified Blood, Modified Tissue, Modified Dx kits) and an in-house developed magnetic beads based protocol, were most appropriate for extracting high quality and quantity DNA suitable for large-scale microarray genotyping and also for long-term DNA storage as demonstrated by their successful application to 600 individuals
Genomic markers associated with antibody response to Newcastle disease virus of Sasso chickens raised in Ethiopia
Newcastle disease virus (NDV) is one of the highly contagious avian pathogens that threatens poultry producers in endemic zones due to its epidemic potential. Selection for antibody (Ab) response can effectively improve disease resistance in chickens. However, the molecular basis of the variation in Ab response to NDV is unclear. This study aimed to detect genomic markers and genes modulating Ab response to NDV in chickens reared under tropical, outdoor conditions. A genome-wide association study (GWAS) was conducted on Sasso T451A chickens that were naturally exposed to infectious diseases from 56 to 112 days of age to identify regions associated with Ab response to NDV. Phenotypic immune data from 935 chickens, monitored in two batches, and genotyping data of these chickens based low-pass sequencing (2,676,181 single nucleotide polymorphisms, SNPs) were used. BioMart data mining and variant effect predictor tools were used to annotate SNPs and candidate genes, respectively. A total of five SNPs (rs316795557 (FOXP2), chr 1; rs313761644 (CEP170B), chr 5; rs733628728, chr 13; and two unnamed SNPs, chr 30 and chr 33) were associated with the chicken antibody response to NDV at the suggestive significance level. These SNPs are located on chromosomes 1, 5, and 13 and are in genomic regions that contain several genes with roles in the regulation of the immune response. The results of this study pave the path for more investigation into the host immune response of chickens to NDV.</p
Novel Quantitative Real-Time LCR for the Sensitive Detection of SNP Frequencies in Pooled DNA: Method Development, Evaluation and Application
BACKGROUND: Single nucleotide polymorphisms (SNP) have proven to be powerful genetic markers for genetic applications in medicine, life science and agriculture. A variety of methods exist for SNP detection but few can quantify SNP frequencies when the mutated DNA molecules correspond to a small fraction of the wild-type DNA. Furthermore, there is no generally accepted gold standard for SNP quantification, and, in general, currently applied methods give inconsistent results in selected cohorts. In the present study we sought to develop a novel method for accurate detection and quantification of SNP in DNA pooled samples. METHODS: The development and evaluation of a novel Ligase Chain Reaction (LCR) protocol that uses a DNA-specific fluorescent dye to allow quantitative real-time analysis is described. Different reaction components and thermocycling parameters affecting the efficiency and specificity of LCR were examined. Several protocols, including gap-LCR modifications, were evaluated using plasmid standard and genomic DNA pools. A protocol of choice was identified and applied for the quantification of a polymorphism at codon 136 of the ovine PRNP gene that is associated with susceptibility to a transmissible spongiform encephalopathy in sheep. CONCLUSIONS: The real-time LCR protocol developed in the present study showed high sensitivity, accuracy, reproducibility and a wide dynamic range of SNP quantification in different DNA pools. The limits of detection and quantification of SNP frequencies were 0.085% and 0.35%, respectively. SIGNIFICANCE: The proposed real-time LCR protocol is applicable when sensitive detection and accurate quantification of low copy number mutations in DNA pools is needed. Examples include oncogenes and tumour suppressor genes, infectious diseases, pathogenic bacteria, fungal species, viral mutants, drug resistance resulting from point mutations, and genetically modified organisms in food
A study on the use of thermal imaging as a diagnostic tool for the detection of digital dermatitis in dairy cattle
Phenotypic characterisation of African chickens raised in semi-scavenging conditions
In sub-Saharan Africa, most poultry production is traditional with birds being raised by smallholders in free-range semi-scavenging conditions. The aim of our project is to extensively characterise phenotypes of chickens raised in typical African farming conditions, by measuring production, immunity and survival characteristics. In total, 2,573 chickens were raised in five batches in the poultry facility at ILRI in Ethiopia. These chickens were phenotypically characterised and sampled across an eight-week period. Traits measured included weekly body weight, growth rate, breast muscle weight in carcass, mortality/survival, and immunological titres. The population of chickens had extensive variance at these phenotypes. For body weight, 65% of the total phenotypic variance was attributed to the individual birds providing an excellent source of variation for identifying potential selection markers. This data will subsequently be used along with whole genome sequencing data of these birds to identify selection targets to underpin future breeding programs
Integrating genetic and genomic analyses of combined health data across ecotypes to improve disease resistance in indigenous African chickens
Poultry play an important role in the agriculture of many African countries. The majority of chickens in sub-Saharan Africa are indigenous, raised in villages under semi-scavenging conditions. Vaccinations and biosecurity measures rarely apply, and infectious diseases remain a major cause of mortality and reduced productivity. Genomic selection for disease resistance offers a potentially sustainable solution but this requires sufficient numbers of individual birds with genomic and phenotypic data, which is often a challenge to collect in the small populations of indigenous chicken ecotypes. The use of information across-ecotypes presents an attractive possibility to increase the relevant numbers and the accuracy of genomic selection. In this study, we performed a joint analysis of two distinct Ethiopian indigenous chicken ecotypes to investigate the genomic architecture of important health and productivity traits and explore the feasibility of conducting genomic selection across-ecotype. Phenotypic traits considered were antibody response to Infectious Bursal Disease (IBDV), Marek’s Disease (MDV), Fowl Cholera (PM) and Fowl Typhoid (SG), resistance to Eimeria and cestode parasitism, and productivity [body weight and body condition score (BCS)]. Combined data from the two chicken ecotypes, Horro (n = 384) and Jarso (n = 376), were jointly analyzed for genetic parameter estimation, genome-wide association studies (GWAS), genomic breeding value (GEBVs) calculation, genomic predictions, whole-genome sequencing (WGS), and pathways analyses. Estimates of across-ecotype heritability were significant and moderate in magnitude (0.22–0.47) for all traits except for SG and BCS. GWAS identified several significant genomic associations with health and productivity traits. The WGS analysis revealed putative candidate genes and mutations for IBDV (TOLLIP, ANGPTL5, BCL9, THEMIS2), MDV (GRM7), SG (MAP3K21), Eimeria (TOM1L1) and cestodes (TNFAIP1, ATG9A, NOS2) parasitism, which warrant further investigation. Reliability of GEBVs increased compared to within-ecotype calculations but accuracy of genomic prediction did not, probably because the genetic distance between the two ecotypes offset the benefit from increased sample size. However, for some traits genomic prediction was only feasible in across-ecotype analysis. Our results generally underpin the potential of genomic selection to enhance health and productivity across-ecotypes. Future studies should establish the required minimum sample size and genetic similarity between ecotypes to ensure accurate joint genomic selection
Chicken caecal enterotypes in indigenous Kadaknath and commercial Cobb chicken lines are associated with Campylobacter abundance and influenced by farming practices
Identifying farming practices that decrease susceptibility to infectious diseases and optimise food conversion efficiency is valuable for chicken welfare and productivity, the environment, and public health. Enterotypes can be used to define microbial community phenotypes that have differential, potentially significant impacts on gut health. In this study, we delineated enterotypes by analysing the microbiomes of 300 indigenous Kadaknath and 300 commercial Cobb400 broiler chickens raised across 60 farms in western India. Using a compositional data approach, we identified three distinct enterotypes: PA1 (n=290), PA2 (n=142) and PA3 (n=67). PA1 and PA2 clustered more closely with each other than with PA3, however, PA2 had significantly lower alpha diversity than PA1. PA1 had a high Firmicutes: Bacteroides ratio, was dominated by Faecalibacterium and had a higher abundance of Prevotellamassilia than other enterotypes. PA2 was characterised by its low alpha diversity, a high abundance of the common taxa Phascolarctobacterium A and Phocaeicola dorei and a significantly higher Campylobacter abundance than PA1. PA3 had the highest Bacteroidota abundance of the three enterotypes and was defined by high prevalence of lower abundance taxa such as CAG-831 and Mucispirillum schaedleri. Network analysis showed that all enterotypes have different proportions of competing Firmicutes-dominant and Bacteroidota-dominant guilds. Random Forest Modelling using defined farm characteristics was predictive for enterotype. Factors affecting enterotype include whether farms were open, enclosed or caged, the location of farms, whether visitors were allowed inside, the number of people in contact with the chickens, chicken line, the presence of dogs and whether flock thinning took place. This study suggests that enterotypes are influenced by farming practices, hence modification of practices could potentially be used to reduce the burden of zoonotic pathogens such as Campylobacter
Microbial diversity and community composition of caecal microbiota in commercial and indigenous Indian chickens determined using 16s rDNA amplicon sequencing
Different alpha diversity indices for each sample of university farm data estimated using QIIME for primer pair P2 data. OTUs were clustered at > 97% similarity. (XLSX 12 kb
Method specific calibration corrects for DNA extraction method effects on relative telomere length measurements by quantitative PCR
Telomere length (TL) is increasingly being used as a biomarker in epidemiological, biomedical and ecological studies. A wide range of DNA extraction techniques have been used in telomere experiments and recent quantitative PCR (qPCR) based studies suggest that the choice of DNA extraction method may influence average relative TL (RTL) measurements. Such extraction method effects may limit the use of historically collected DNA samples extracted with different methods. However, if extraction method effects are systematic an extraction method specific (MS) calibrator might be able to correct for them, because systematic effects would influence the calibrator sample in the same way as all other samples. In the present study we tested whether leukocyte RTL in blood samples from Holstein Friesian cattle and Soay sheep measured by qPCR was influenced by DNA extraction method and whether MS calibration could account for any observed differences. We compared two silica membrane-based DNA extraction kits and a salting out method. All extraction methods were optimized to yield enough high quality DNA for TL measurement. In both species we found that silica membrane-based DNA extraction methods produced shorter RTL measurements than the non-membrane-based method when calibrated against an identical calibrator. However, these differences were not statistically detectable when a MS calibrator was used to calculate RTL. This approach produced RTL measurements that were highly correlated across extraction methods (r > 0.76) and had coefficients of variation lower than 10% across plates of identical samples extracted by different methods. Our results are consistent with previous findings that popular membrane-based DNA extraction methods may lead to shorter RTL measurements than non-membrane-based methods. However, we also demonstrate that these differences can be accounted for by using an extraction method-specific calibrator, offering researchers a simple means of accounting for differences in RTL measurements from samples extracted by different DNA extraction methods within a study