Sheep milk is important for the economy of Mediterranean countries. A large part of its production is reserved for traditional cheese making, usually protected by the European Community regulations. Milk fat content balance between MUFA and PUFA is important for cheese flavour and, although it is well known that fat is significantly influenced by both genetic and environmental factors, there is no relevant literature reporting genetic or genomic parameters influencing it in sheep populations. Nowadays, genome-wide association (GWA) studies represent the gold standard method to investigate the genetic architecture of complex traits, such as milk fat composition. However, because of the nature of this multiple-trait, performing an effective association analysis is not an easy task. In fact, when correlated traits are analysed, because of GWAS stringent cut-off, the outcomes may lead to false negatives and broadly are difficult to interpret. Methods that generate uncorrelated traits represent useful and promising approaches to overcome this problem. In this study, a multivariate factor analysis (MFA) was performed to extract latent factors able to explain metabolic information of the original variables and usable in a GWA analysis. To achieve this, we first characterised milk samples from 200 Comisana ewes, reared in genetic Centre of Asciano for their fat profile by gas-chromatography. Subjects were genotyped with SNP array and a single-marker regression model for GWAS was performed. The extracted factors were representative of the following groups: de novo fatty acids, biohydrogenation, branched fatty acids and desaturation. Moreover, GWA analysis showed a general increase of significances compared with the analysis using the original variables. Nevertheless, this was not sufficient to reach the Bonferroni statistical threshold, except for a single SNP on Chr 6 in association with desaturation factor group. To the best of our knowledge, this was the first study performing a MFA on milk FA in Comisana. The preliminary results were interesting and in line with previously published studies on bovine
Multivariate Factor Analysis of milk fatty acids profile for GWAS analysis in Comisana sheep breed.
Giustino Gaspa;
2019-01-01
Abstract
Sheep milk is important for the economy of Mediterranean countries. A large part of its production is reserved for traditional cheese making, usually protected by the European Community regulations. Milk fat content balance between MUFA and PUFA is important for cheese flavour and, although it is well known that fat is significantly influenced by both genetic and environmental factors, there is no relevant literature reporting genetic or genomic parameters influencing it in sheep populations. Nowadays, genome-wide association (GWA) studies represent the gold standard method to investigate the genetic architecture of complex traits, such as milk fat composition. However, because of the nature of this multiple-trait, performing an effective association analysis is not an easy task. In fact, when correlated traits are analysed, because of GWAS stringent cut-off, the outcomes may lead to false negatives and broadly are difficult to interpret. Methods that generate uncorrelated traits represent useful and promising approaches to overcome this problem. In this study, a multivariate factor analysis (MFA) was performed to extract latent factors able to explain metabolic information of the original variables and usable in a GWA analysis. To achieve this, we first characterised milk samples from 200 Comisana ewes, reared in genetic Centre of Asciano for their fat profile by gas-chromatography. Subjects were genotyped with SNP array and a single-marker regression model for GWAS was performed. The extracted factors were representative of the following groups: de novo fatty acids, biohydrogenation, branched fatty acids and desaturation. Moreover, GWA analysis showed a general increase of significances compared with the analysis using the original variables. Nevertheless, this was not sufficient to reach the Bonferroni statistical threshold, except for a single SNP on Chr 6 in association with desaturation factor group. To the best of our knowledge, this was the first study performing a MFA on milk FA in Comisana. The preliminary results were interesting and in line with previously published studies on bovine
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