Survival analysis of piglet pre-weaning mortality

Survival analysis methodology was applied in order to analyse sources of variation of preweaning survival time and to estimate variance components using data from a crossbred piglets population. A frailty sire model was used with the litter effect treated as an additional random source of variation. All the variables considered had a significant effect on survivability: sex, cross-fostering, parity of the nurse-sow and litter size. The variance estimates of sire and litter were closed to 0.08 and 2 respectively and the heritability of pre-weaning survival was 0.03

Finding 16S rRNA gene-based SNPs for the genetic traceability of commercial species belonging to Gadiformes

A SNPs (Single Nucleotide Polymorphism) based analysis was developed to differentiate four economically important species belonging to the Gadiformes order: Pacific cod Gadus macrocephalus, Atlantic cod Gadus morhua, Haddock Melanogrammus aeglefinus and Ling Molva molva. A 430bp fragment of the 16s rRNA gene was amplified using interspecific conserved primer and sequenced. The sequences were aligned and analyzed for the presence of SNPs; three SNPs (MerSNP1, MerSNP7 and MerSNP9) were identified and selected to allow discrimination between the four species. Aplotypes were TCC, CCC, CAT and CAC for Pacific cod, Atlantic cod, Haddock and Ling respectively. Confirmation of results was achieved by sequencing 16s rRNA gene fragments of 16 G. morhua, 7 G. macrocephalus, 15 M. aeglefinus and 5 M. molva samples collected at different fish catching campaign. Nucleotide sequence of 16s rRNA mitochondial gene has been shown to be a useful tool to allow rapid reliable and fully automatable for discrimination of 4 economically important species in fisheries industry

Association of candidate gene polymorphisms with milk technological traits, yield, composition, and somatic cell score in Italian Holstein-Friesian sires

open6siAdvances in DNA-based marker technology have enabled the identification of genomic regions underlying complex phenotypic traits in livestock species. The incorporation of detected quantitative trait loci into genetic evaluation provides great potential to enhance selection accuracies, hence expediting the genetic improvement of economically important traits. The objective of the present study was to investigate 96 single nucleotide polymorphisms (SNP) located in 53 candidate genes previously reported to have effects on milk production and quality traits in a population of highly selected Holstein-Friesian bulls. A total of 423 semen samples were used to genotype the bulls through a custom oligo pool assay. Forty-five SNP in 32 genes were found to be associated with at least 1 of the tested traits. Most significant and favorable SNP trait associations were observed for polymorphisms located in CCL3 and AGPAT6 genes for fat yield (0.037 and 0.033 kg/d, respectively), DGKG gene for milk yield (0.698 kg/d), PPARGC1A, CSN1S1, and AGPAT6 genes for fat percentage (0.127, 0.113, and 0.093%, respectively), GHR gene for protein (0.064%) and casein percentage (0.053%), and TLR4 gene for fat (0.090%), protein (0.066%), and casein percentage (0.050%). Somatic cell score was favorably affected by GHR (−0.095) and POU1F1 (−0.137), and interesting SNP-trait associations were observed for polymorphisms located in CSN2, POU1F1, and AGPAT6 genes for rennet coagulation time (−0.592, −0.558, and −0.462 min, respectively), and GHR and CSN2 genes for curd firmness 30 min after rennet addition (1.264 and 1.183 mm, respectively). In addition to the influence of individual SNP, the effects of composite genotypes constructed by grouping SNP according to their individual effects on traits considered in the analysis were also examined. Favorable and significant effects on milk traits were observed for 2 composite genotypes, one including 10 SNP and the other 4 SNP. The former was associated with an increase of milk (0.075 kg/d), fat (0.097 kg/d), protein (0.083 kg/d), and casein yields (0.065 kg/d), and the latter was associated with an increase of fat (0.244%), protein (0.071%), and casein percentage (0.047%). Although further research is required to validate the identified SNP loci in other populations and breeds, our results can be considered as a preliminary foundation for further replication studies on gene-assisted selection programs.openViale, E.; F., Tiezzi; Maretto, F.; De Marchi, M.; Penasa, M.; Cassandro, M.Viale, E.; Tiezzi, F.; Maretto, F.; De Marchi, M.; Penasa, M.; Cassandro, M

Genetic structure and variability within and among populations of the fat-tailed Barbarine sheep breed using microsatellites markers

This study investigates the genetic diversity and the structure of the most dominant native fat-tailed Tunisian sheep breed (Barbarine, BAR) using microsatellite markers. Blood samples from 183 BAR animals, belonging to 4 subpopulations according to phenotypic traits, were collected across all regions in Tunisia. BAR animals and 31 Appenninica Italian sheep breed (APP) used as an out-group were genotyped at 17 microsatellites loci. A total of 270 alleles were identified with average gene diversity equal to 0.812. The mean observed heterozygosity (0.745) and allelic richness (8.09) estimates were high within BAR breed highlighting notable levels of genetic diversity. The low FIS (0.078) and FIT (0.084) values indicate low level of inbreeding within this breed while a low FST estimate (0.007) shows that the subpopulations are not genetically differentiated. The clustering analysis performed with ‘structure’ detected the absence of substructures and the clear uniqueness of the BAR. Tomiuk and Loeschcke’s DTL genetic distance values confirmed the distinction between APP and BAR breeds. Results arising from our microsatellites analysis represent a starting point for the valorization of this indigenous Tunisian sheep breed. A suggestion was made to monitor its genetic variability and for the preservation of this breed for the next generations.Keywords: Tunisian Barbarine sheep breed, microsatellite markers, genetic variability, population structureAfrican Journal of Biotechnology, Vol. 13(1), pp. 44-54, 1 January, 201

Genetic structure and variability within and among populations of the fat-tailed Barbarine sheep breed using microsatellites markers

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Noninvasive biomarkers of colorectal cancer: role in diagnosis and personalised treatment perspectives

Colorectal cancer (CRC) is the third leading cause of cancer-related deaths worldwide. It has been estimated that more than one-third of patients are diagnosed when CRC has already spread to the lymph nodes. One out of five patients is diagnosed with metastatic CRC. The stage of diagnosis influences treatment outcome and survival. Notwithstanding the recent advances in multidisciplinary management and treatment of CRC, patients are still reluctant to undergo screening tests because of the associated invasiveness and discomfort (e.g., colonoscopy with biopsies). Moreover, the serological markers currently used for diagnosis are not reliable and, even if they were useful to detect disease recurrence after treatment, they are not always detected in patients with CRC (e.g., CEA). Recently, translational research in CRC has produced a wide spectrum of potential biomarkers that could be useful for diagnosis, treatment, and follow-up of these patients. The aim of this review is to provide an overview of the newer noninvasive or minimally invasive biomarkers of CRC. Here, we discuss imaging and biomolecular diagnostics ranging from their potential usefulness to obtain early and less-invasive diagnosis to their potential implementation in the development of a bespoke treatment of CRC

A functional biological network centered on XRCC3: a new possible marker of chemoradiotherapy resistance in rectal cancer patients

Preoperative chemoradiotherapy is widely used to improve local control of disease, sphincter preservation and to improve survival in patients with locally advanced rectal cancer. Patients enrolled in the present study underwent preoperative chemoradiotherapy, followed by surgical excision. Response to chemoradiotherapy was evaluated according to Mandard's Tumor Regression Grade (TRG). TRG 3, 4 and 5 were considered as partial or no response while TRG 1 and 2 as complete response. From pretherapeutic biopsies of 84 locally advanced rectal carcinomas available for the analysis, only 42 of them showed 70% cancer cellularity at least. By determining gene expression profiles, responders and non-responders showed significantly different expression levels for 19 genes (P < 0.001). We fitted a logistic model selected with a stepwise procedure optimizing the Akaike Information Criterion (AIC) and then validated by means of leave one out cross validation (LOOCV, accuracy = 95%). Four genes were retained in the achieved model: ZNF160, XRCC3, HFM1 and ASXL2. Real time PCR confirmed that XRCC3 is overexpressed in responders group and HFM1 and ASXL2 showed a positive trend. In vitro test on colon cancer resistant/susceptible to chemoradioterapy cells, finally prove that XRCC3 deregulation is extensively involved in the chemoresistance mechanisms. Protein-protein interactions (PPI) analysis involving the predictive classifier revealed a network of 45 interacting nodes (proteins) with TRAF6 gene playing a keystone role in the network. The present study confirmed the possibility that gene expression profiling combined with integrative computational biology is useful to predict complete responses to preoperative chemoradiotherapy in patients with advanced rectal cance