Data di Pubblicazione:
2020
Citazione:
GENOMIC VARIATION IN LIVESTOCK USING DENSE SNP CHIP DATA / E. Gorla ; tutor: A.Bagnato; co-tutor: M. G. Strillaci ; coordinatore V.Grieco. DIPARTIMENTO DI MEDICINA VETERINARIA, 2020 Feb 05. 32. ciclo, Anno Accademico 2019. [10.13130/gorla-erica_phd2020-02-05].
Abstract:
Part I describes two possible approaches to investigate Mexican chicken genetic variation, using selective sweeps and Copy Number Variants (CNV). CNVs are genomic polymorphisms that influence phenotypic expression and are an important source of genetic variation in populations.
The aim of the first study here presented was to characterize the genetic variability of the Mexican chicken’s population and to disclose any underlying population structure. A total of 213 chickens were sampled in different rural production units located in 25 states of México. Genotypes were obtained using the Affymetrix Axiom® 600K Chicken Genotyping Array. The Identity by Descent (IBD) and the Principal Components Analysis (PCA) were performed by SVS software on pruned SNPs. Analyses done with ADMIXTURE identified three ancestors and determined, for each individual, the proportion of the genetic contribution from each of the three ancestors. The results of the Neighbor-Joining (NJ) analysis were consistent with those obtained by the PCA. All methods used in this study did not allow a classification of Mexican chicken in distinct genetic groups. A total of 3,059 Run of homozygosity (ROH) were identified and, being mainly short in length (< 4 Mb), these regions are indicative of a low inbreeding level in the population. Finally, findings from the ROH analysis indicated the presence of natural selective pressure in the population of Mexican chicken.
In the second study we used CNVs to investigate genetic variability in the Mexican Creole chicken and to relate this variation to the available gene annotation. The Hidden Markov Model of the PennCNV software detected a total of 1,924 CNVs in the chicken genome of 256 individuals. Input data were LOGR Ratio and B allele frequency obtained with the Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix). The mapped CNVs comprised 1,538 gains and 386 losses resulting, at population level, in 1,216 CNV regions (CNVRs), of which 959 gains, 226 losses and 31 complexes (i.e. containing both losses and gains). The CNVRs covered a total of 47 Mb of the whole genome sequence length, corresponding to 5.12 % of the chicken galGal4 autosome assembly. This study allowed a deep insight into the structural variation in the genome of unselected Mexican chicken population, which up to now has not been genetically characterized. The genomic study disclosed that the population, even if presenting extreme morphological variation, couldn’t be organized in differentiated genetic subpopulations. Finally, this study provided a chicken CNV map based on the 600K SNP chip array, jointly with a genome-wide gene copy number estimates in a native, unselected for more than 500 years, chicken population.
Genetic variation can be caused by adaptive evolutionary changes and by artificial selection. The genetic makeup of populations is the result of a long-term process of selection and adaptation to specific environments and ecosystems.
The two studies here presented indicate that the Mexican chicken clearly appear to be a unique Creole chicken population that was not subjected to a specific directional selection. Results provide a genetic knowledge that can be used as a basis for the genetic management of a unique genetic resource. Industry is likely envisaging to use the female native populations mating them with selected males to increase the productivity and the economic revenue of family farming agriculture, which is a large reality of United States of México.
• Part II describes a CNV scan and a population analysis of turkey populations coming from different countries.
The domesticated turkey was brought to Europe in late 1500 by Spanish conquerors from Central America, likely from Mexico.
The evolution of the Mex
Tipologia IRIS:
Tesi di dottorato
Elenco autori:
E. Gorla
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