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Discriminant Canonical Analysis as a Validation Tool for Multivariety Native Breed Egg Commercial Quality Classification.

ABSTRACT: This study aimed to develop a tool to validate multivariety breed egg quality classification depending on quality-related internal and external traits using a discriminant canonical analysis approach. A flock of 60 Utrerana hens (Franciscan, White, Black, and Partridge) and a control group of 10 Leghorn hens were placed in individual cages to follow the traceability of the eggs and perform an individual internal and external quality assessment. Egg groups were determined depending on their commercial size (S, M, L, and XL), laying hen breed, and variety. Egg weight, major diameter, minor diameter, shell b*, albumen height, and the presence or absence of visual defects in yolk and/or albumen showed multicollinearity problems (variance inflation factor (VIF) > 5) and were discarded. Albumen weight, eggshell weight, and yolk weight were the most responsible traits for the differences among egg quality categories (Wilks' lambda: 0.335, 0.539, and 0.566 for albumen weight, eggshell weight, and yolk weight, respectively). The combination of traits in the first two dimensions explained 55.02% and 20.62% variability among groups, respectively. Shared properties between Partridge and Franciscan varieties may stem from their eggs presenting heavier yolks and slightly lower weights, while White Utrerana and Leghorn hens' similarities may be ascribed to hybridization reminiscences.

SUBMITTER: Gonzalez Ariza A

PROVIDER: S-EPMC8002516 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Cattle include a large number of breeds that are characterized by marked phenotypic differences and thus constitute a valuable model to study genome evolution in response to processes such as selection and domestication. Detection of "signatures of selection" is a useful approach to study the evolutionary pressures experienced throughout history. In the present study, signatures of selection were investigated in five cattle breeds farmed in Italy using a multivariate approach.A total of 4094 bulls from five breeds with different production aptitudes (two dairy breeds: Italian Holstein and Italian Brown Swiss; two beef breeds: Piemontese and Marchigiana; and one dual purpose breed: Italian Simmental) were genotyped using the Illumina BovineSNP50 v.1 beadchip. Canonical discriminant analysis was carried out on the matrix of single nucleotide polymorphisms (SNP) genotyping data, separately for each chromosome. Scores for each canonical variable were calculated and then plotted in the canonical space to quantify the distance between breeds. SNPs for which the correlation with the canonical variable was in the 99th percentile for a specific chromosome were considered to be significantly associated with that variable. Results were compared with those obtained using an FST-based approach.Based on the results of the canonical discriminant analysis, a large number of signatures of selection were detected, among which several had strong signals in genomic regions that harbour genes known to have an impact on production and morphological bovine traits, including MSTN, LCT, GHR, SCD, NCAPG, KIT, and ASIP. Moreover, new putative candidate genes were identified, such as GCK, B3GALNT1, MGAT1, GALNTL1, PRNP, and PRND. Similar results were obtained with the FST-based approach.The use of canonical discriminant analysis on 50 K SNP genotypes allowed the extraction of new variables that maximize the separation between breeds. This approach is quite straightforward, it can compare more than two groups simultaneously, and relative distances between breeds can be visualized. The genes that were highlighted in the canonical discriminant analysis were in concordance with those obtained using the FST index.

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Discriminant Canonical Analysis as a Validation Tool for Multivariety Native Breed Egg Commercial Quality Classification.

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