100 research outputs found

    Analysis of the pig genome for the identification of genomic regions affecting production traits

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    The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans

    Genomic diversity and signatures of selection in meat and fancy rabbit breeds based on high-density marker data

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    open6noThe study was funded by the PSRN (Programma di Sviluppo Rurale Nazionale) Cun-Fu and Cun-Fu 2 projects (co-funded by the European Agricultural Fund for Rural Development of the European Union and by the Italian Ministry of Agriculture, Food and Forestry—MiPAAF) and by the University of Bologna RFO 2019 programme.Background: Domestication of the rabbit (Oryctolagus cuniculus) has led to a multi-purpose species that includes many breeds and lines with a broad phenotypic diversity, mainly for external traits (e.g. coat colours and patterns, fur structure, and morphometric traits) that are valued by fancy rabbit breeders. As a consequence of this human-driven selection, distinct signatures are expected to be present in the rabbit genome, defined as signatures of selection or selective sweeps. Here, we investigated the genome of three Italian commercial meat rabbit breeds (Italian Silver, Italian Spotted and Italian White) and 12 fancy rabbit breeds (Belgian Hare, Burgundy Fawn, Champagne d’Argent, Checkered Giant, Coloured Dwarf, Dwarf Lop, Ermine, Giant Grey, Giant White, Rex, Rhinelander and Thuringian) by using high-density single nucleotide polymorphism data. Signatures of selection were identified based on the fixation index (FST) statistic with different approaches, including single-breed and group-based methods, the latter comparing breeds that are grouped based on external traits (different coat colours and body sizes) and types (i.e. meat vs. fancy breeds). Results: We identified 309 genomic regions that contained signatures of selection and that included genes that are known to affect coat colour (ASIP, MC1R and TYR), coat structure (LIPH), and body size (LCORL/NCAPG, COL11A1 and HOXD) in rabbits and that characterize the investigated breeds. Their identification proves the suitability of the applied methodologies for capturing recent selection events. Other regions included novel candidate genes that might contribute to the phenotypic variation among the analyzed breeds, including genes for pigmentation-related traits (EDNRA, EDNRB, MITF and OCA2) and body size, with a strong candidate for dwarfism in rabbit (COL2A1). Conclusions: We report a genome-wide view of genetic loci that underlie the main phenotypic differences in the analyzed rabbit breeds, which can be useful to understand the shift from the domestication process to the development of breeds in O. cuniculus. These results enhance our knowledge about the major genetic loci involved in rabbit external traits and add novel information to understand the complexity of the genetic architecture underlying body size in mammals.openBallan, Mohamad; Bovo, Samuele; Schiavo, Giuseppina; Schiavitto, Michele; Negrini, Riccardo; Fontanesi, LucaBallan, Mohamad; Bovo, Samuele; Schiavo, Giuseppina; Schiavitto, Michele; Negrini, Riccardo; Fontanesi, Luc

    Reduced representation libraries from DNA pools analysed with next generation semiconductor based-sequencing to identify SNPs in extreme and divergent pigs for back fat thickness

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    The aim of this study was to identify single nucleotide polymorphisms (SNPs) that could be associated with back fat thickness (BFT) in pigs. To achieve this goal, we evaluated the potential and limits of an experimental design that combined several methodologies. DNA samples from two groups of Italian Large White pigs with divergent estimating breeding value (EBV) for BFT were separately pooled and sequenced, after preparation of reduced representation libraries (RRLs), on the Ion Torrent technology. Taking advantage from SNAPE for SNPs calling in sequenced DNA pools, 39,165 SNPs were identified; 1/4 of them were novel variants not reported in dbSNP. Combining sequencing data with Illumina PorcineSNP60 BeadChip genotyping results on the same animals, 661 genomic positions overlapped with a good approximation of minor allele frequency estimation. A total of 54 SNPs showing enriched alleles in one or in the other RRLs might be potential markers associated with BFT. Some of these SNPs were close to genes involved in obesity related phenotypes

    A genotyping by sequencing approach can disclose Apis mellifera population genomic information contained in honey environmental DNA

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    Awareness has been raised over the last years on the genetic integrity of autochthonous honey bee subspecies. Genomic tools available in Apis mellifera can make it possible to measure this information by targeting individual honey bee DNA. Honey contains DNA traces from all organisms that contributed or were involved in its production steps, including the honey bees of the colony. In this study, we designed and tested a genotyping by sequencing (GBS) assay to analyse single nucleotide polymorphisms (SNPs) of A. mellifera nuclear genome using environmental DNA extracted from honey. A total of 121 SNPs (97 SNPs informative for honey bee subspecies identification and 24 SNPs associated with relevant traits of the colonies) were used in the assay to genotype honey DNA, which derives from thousands of honey bees. Results were integrated with information derived from previous studies and whole genome resequencing datasets. This GBS method is highly reliable in estimating honey bee SNP allele frequencies of the whole colony from which the honey derived. This assay can be used to identify the honey bee subspecies of the colony that produced the honey and, in turn, to authenticate the entomological origin of the honey

    Signatures of Admixture and Genetic Uniqueness in the Autochthonous Greek Black Pig Breed Deduced from Gene Polymorphisms Affecting Domestication-Derived Traits

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    Autochthonous pig breeds are important genetic resources, well adapted to local climatic conditions, environments, and traditional production systems, where they are associated with local and niche markets. The Greek Black Pig breed is the only local pig breed recognized in Greece. In this study, we started a population genetic characterization of this breed by analyzing a few gene markers associated with morphological and production traits and that usually differentiate wild boars from domestic breeds. The obtained results showed that, in the past, this breed experienced genetic admixture from two sources, wild boars and cosmopolitan breeds. On the one hand, this situation might raise some concerns for the genetic integrity of this animal genetic resource. On the other hand, this might contribute to within-population genetic variability reducing the problem of inbreeding of the small breed population. In this breed, we also identified a novel allele in the melanocortin 1 receptor (MC1R) gene, resulting in a new hypothesis on the function of the encoded protein in regulating the cascade signals and leading to the production of different pigmentation. This result showed that local untapped breeds can be the reservoir of interesting genetic variants useful to better understanding underlying basic biological functions in mammals

    Next generation semiconductor based sequencing of the donkey (Equus asinus) genome provided comparative sequence data against the horse genome and a few millions of single nucleotide polymorphisms

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    Few studies investigated the donkey (Equus asinus) at the whole genome level so far. Here, we sequenced the genome of two male donkeys using a next generation semiconductor based sequencing platform (the Ion Proton sequencer) and compared obtained sequence information with the available donkey draft genome (and its Illumina reads from which it was originated) and with the EquCab2.0 assembly of the horse genome. Moreover, the Ion Torrent Personal Genome Analyzer was used to sequence reduced representation libraries (RRL) obtained from a DNA pool including donkeys of different breeds (Grigio Siciliano, Ragusano and Martina Franca). The number of next generation sequencing reads aligned with the EquCab2.0 horse genome was larger than those aligned with the draft donkey genome. This was due to the larger N50 for contigs and scaffolds of the horse genome. Nucleotide divergence between E. caballus and E. asinus was estimated to be similar to 0.52-0.57%. Regions with low nucleotide divergence were identified in several autosomal chromosomes and in the whole chromosome X. These regions might be evolutionally important in equids. Comparing Y-chromosome regions we identified variants that could be useful to track donkey paternal lineages. Moreover, about 4.8 million of single nucleotide polymorphisms (SNPs) in the donkey genome were identified and annotated combining sequencing data from Ion Proton (whole genome sequencing) and Ion Torrent (RRL) runs with Illumina reads. A higher density of SNPs was present in regions homologous to horse chromosome 12, in which several studies reported a high frequency of copy number variants. The SNPs we identified constitute a first resource useful to describe variability at the population genomic level in E. asinus and to establish monitoring systems for the conservation of donkey genetic resources

    Investigation of genetic markers for resistance to infectious diseases in different pig breeds: antagonism with production and performance traits?

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    Infectious diseases have devastating economic impacts on the pig breeding industry worldwide. A few genetic markers associated with disease resistance have been recently identified and used in Marker Assisted Selection (MAS) in a few pig populations as part of disease control programs

    Comparative analysis of genomic inbreeding parameters and runs of homozygosity islands in several fancy and meat rabbit breeds

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    Runs of homozygosity (ROH) are defined as long stretches of DNA homozygous at each polymorphic position. The proportion of genome covered by ROH and their length are indicators of the level and origin of inbreeding. In this study, we analysed SNP chip datasets (obtained using the Axiom OrcunSNP Array) of a total of 702 rabbits from 12 fancy breeds and four meat breeds to identify ROH with different approaches and calculate several genomic inbreeding parameters. The highest average number of ROH per animal was detected in Belgian Hare (~150) and the lowest in Italian Silver (~106). The average length of ROH ranged from 4.001 ± 0.556 Mb in Italian White to 6.268 ± 1.355 Mb in Ermine. The same two breeds had the lowest (427.9 ± 86.4 Mb, Italian White) and the highest (921.3 ± 179.8 Mb, Ermine) average values of the sum of all ROH segments. More fancy breeds had a higher level of genomic inbreeding (as defined by ROH) than meat breeds. Several ROH islands contain genes involved in body size, body length, pigmentation processes, carcass traits, growth, and reproduction traits (e.g.: AOX1, GPX5, IFRD1, ITGB8, NELL1, NR3C1, OCA2, TRIB1, TRIB2). Genomic inbreeding parameters can be useful to overcome the lack of information in the management of rabbit genetic resources. ROH provided information to understand, to some extent, the genetic history of rabbit breeds and to identify signatures of selection in the rabbit genome

    Comparative targeted metabolomic profiles of porcine plasma and serum

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    Metabolomics has been used to characterise many biological matrices and obtain detailed pictures of biological systems based on many metabolites. Plasma and serum are two blood-derived biofluids commonly used to assess and monitor the organismal metabolism and obtain information on the physiological and health conditions of an animal. Plasma is the supernatant that is separated from the cellular components after centrifugation of the blood that is first added with an anticoagulant. Serum is obtained after centrifugation of the blood that has been coagulated. The choice of one or the other biofluid for metabolomic analyses is related to specific analytical needs and technical issues, to problems derived by the collection and preparation steps, in particular when specimens are sampled from animals involved in field studies. Thus far, most of the metabolomic studies that compared plasma and serum have been carried out in humans and very little is known on the pigs. In this study, we used a targeted metabolomic platform that can detect about 180 metabolites of five biochemical classes to compare plasma and serum profiles of samples collected from 24 pigs. To also obtain a cross-species comparative metabolomic analysis, information for human plasma and serum derived from the same platform was retrieved from previous studies. Statistical analyses included univariate and multivariate approaches aimed at identifying stable and/or differentially abundant metabolites between the two porcine biofluids. A total of 154 (∼83%) metabolites passed the initial quality control, indicating a good repeatability of the analytical platform in pigs. Discarded metabolites included aspartate and biogenic amines that were already reported to be unstable in human studies. More than 80% of the metabolites had similar profiles in both porcine biofluids (average correlation was 0.75). Concentrations were usually higher in serum than in plasma, in agreement with what was already reported in humans. The univariate analysis identified 44 metabolites that had statistically different concentrations between porcine plasma and serum, of which 28 metabolites were also confirmed by the multivariate analysis. The obtained picture described similarities and differences between these two biofluids in pigs and the related human-pig comparisons. The obtained information can be useful for the choice of one or the other matrix for the implementation of metabolomic studies in this livestock species. The results can also provide useful hints to valuing the pig as animal model, in particular when metabolite-derived physiological states are relevant

    A genome wide association study for backfat thickness in Italian Large White pigs highlights new regions affecting fat deposition including neuronal genes.

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    open9noBACKGROUND: Carcass fatness is an important trait in most pig breeding programs. Following market requests, breeding plans for fresh pork consumption are usually designed to reduce carcass fat content and increase lean meat deposition. However, the Italian pig industry is mainly devoted to the production of Protected Designation of Origin dry cured hams: pigs are slaughtered at around 160 kg of live weight and the breeding goal aims at maintaining fat coverage, measured as backfat thickness to avoid excessive desiccation of the hams. This objective has shaped the genetic pool of Italian heavy pig breeds for a few decades. In this study we applied a selective genotyping approach within a population of ~ 12,000 performance tested Italian Large White pigs. Within this population, we selectively genotyped 304 pigs with extreme and divergent backfat thickness estimated breeding value by the Illumina PorcineSNP60 BeadChip and performed a genome wide association study to identify loci associated to this trait. RESULTS: We identified 4 single nucleotide polymorphisms with P≤5.0E-07 and additional 119 ones with 5.0E-07<P≤5.0E-05. These markers were located throughout all chromosomes. The largest numbers were found on porcine chromosomes 6 and 9 (n=15), 4 (n=13), and 7 (n=12) while the most significant marker was located on chromosome 18. Twenty-two single nucleotide polymorphisms were in intronic regions of genes already recognized by the Pre-Ensembl Sscrofa10.2 assembly. Gene Ontology analysis indicated an enrichment of Gene Ontology terms associated with nervous system development and regulation in concordance with results of large genome wide association studies for human obesity. CONCLUSIONS: Further investigations are needed to evaluate the effects of the identified single nucleotide polymorphisms associated with backfat thickness on other traits as a pre-requisite for practical applications in breeding programs. Reported results could improve our understanding of the biology of fat metabolism and deposition that could also be relevant for other mammalian species including humans, confirming the role of neuronal genes on obesity.To June 10, 2013 the paper is labelled as "Highly accessed" on the BMC genomics website http://www.biomedcentral.com/1471-2164/13/583openFontanesi L;Schiavo G;Galimberti G;Calò DG;Scotti E;Martelli PL;Buttazzoni L;Casadio R;Russo VFontanesi L;Schiavo G;Galimberti G;Calò DG;Scotti E;Martelli PL;Buttazzoni L;Casadio R;Russo
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