Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed
Milk coagulation ability is crucial for the dairy sheep industry since the whole amount of milk is processed into cheese. Non-coagulating milk (NCM) is defined as milk not forming a curd within the testing time. In sheep milk, it has been reported in literature that up to 20% of milk is NCM. Althoug...
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Animal Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fanim.2022.889797/full |
| _version_ | 1818197783490854912 |
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| author | Giustino Gaspa Fabio Correddu Alberto Cesarani Alberto Cesarani Michele Congiu Corrado Dimauro Alfredo Pauciullo Nicolò Pietro Paolo Macciotta |
| author_facet | Giustino Gaspa Fabio Correddu Alberto Cesarani Alberto Cesarani Michele Congiu Corrado Dimauro Alfredo Pauciullo Nicolò Pietro Paolo Macciotta |
| author_sort | Giustino Gaspa |
| collection | DOAJ |
| description | Milk coagulation ability is crucial for the dairy sheep industry since the whole amount of milk is processed into cheese. Non-coagulating milk (NCM) is defined as milk not forming a curd within the testing time. In sheep milk, it has been reported in literature that up to 20% of milk is NCM. Although the clotting properties of individual milk have been widely studied, little attention has been given to NCM and genomic dissection of this trait. Mid-infrared (MIR) spectra can be exploited both to predict cheese-making aptitude and to discriminate between coagulating milk and NCM. The main goals of this work were (i) to assess the predictivity of MIR spectra for NCM classification and (ii) to conduct a genome-wide association study on coagulation ability. Milk samples from 949 Sarda ewes genotyped and phenotyped for milk coagulation properties (MCPs) served as the training dataset. The validation dataset included 662 ewes. Three classical MCPs were measured: rennet coagulation time (RCT), curd firmness (a30), and curd firming time (k20). Moreover, MIR spectra were acquired and stored in the region between 925.92 and 5,011.54 cm−1. The probability of a sample to be NCM was modeled by step-wise logistic regression on milk spectral information (LR-W), logistic regression on principal component (LR-PC), and canonical discriminant analysis of spectral wave number (DA-W). About 9% of the samples did not coagulate at 30 min. The use of LR-W gave a poorer classification of NCM. The use of LR-PC improved the percentage of correct assignment (45 ± 9%). The DA-W method allows us to reach 75.1 ± 10.3 and 76.5 ± 18.4% of correct assignments of the inner and external validation datasets, respectively. As far as GWA of NCM, 458 SNP associations and 45 candidate genes were detected. The genes retrieved from public databases were mostly linked to mammary gland metabolism, udder health status, and a milk compound also known to affect the ability of milk to coagulate. In particular, the potential involvement of CAPNs deserves further investigation. |
| first_indexed | 2024-12-12T01:55:28Z |
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| id | doaj.art-1264e728d40d434bad7021673104f67b |
| institution | Directory Open Access Journal |
| issn | 2673-6225 |
| language | English |
| last_indexed | 2024-12-12T01:55:28Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Animal Science |
| spelling | doaj.art-1264e728d40d434bad7021673104f67b2022-12-22T00:42:23ZengFrontiers Media S.A.Frontiers in Animal Science2673-62252022-05-01310.3389/fanim.2022.889797889797Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep BreedGiustino Gaspa0Fabio Correddu1Alberto Cesarani2Alberto Cesarani3Michele Congiu4Corrado Dimauro5Alfredo Pauciullo6Nicolò Pietro Paolo Macciotta7Department of Agricultural Forest and Food Science, University of Turin, Grugliasco, ItalyDepartment of Agricultural Science, University of Sassari, Sassari, ItalyDepartment of Agricultural Science, University of Sassari, Sassari, ItalyDepartment of Animal and Dairy Science, University of Georgia, Athens, GA, United StatesDepartment of Agricultural Science, University of Sassari, Sassari, ItalyDepartment of Agricultural Science, University of Sassari, Sassari, ItalyDepartment of Agricultural Forest and Food Science, University of Turin, Grugliasco, ItalyDepartment of Agricultural Science, University of Sassari, Sassari, ItalyMilk coagulation ability is crucial for the dairy sheep industry since the whole amount of milk is processed into cheese. Non-coagulating milk (NCM) is defined as milk not forming a curd within the testing time. In sheep milk, it has been reported in literature that up to 20% of milk is NCM. Although the clotting properties of individual milk have been widely studied, little attention has been given to NCM and genomic dissection of this trait. Mid-infrared (MIR) spectra can be exploited both to predict cheese-making aptitude and to discriminate between coagulating milk and NCM. The main goals of this work were (i) to assess the predictivity of MIR spectra for NCM classification and (ii) to conduct a genome-wide association study on coagulation ability. Milk samples from 949 Sarda ewes genotyped and phenotyped for milk coagulation properties (MCPs) served as the training dataset. The validation dataset included 662 ewes. Three classical MCPs were measured: rennet coagulation time (RCT), curd firmness (a30), and curd firming time (k20). Moreover, MIR spectra were acquired and stored in the region between 925.92 and 5,011.54 cm−1. The probability of a sample to be NCM was modeled by step-wise logistic regression on milk spectral information (LR-W), logistic regression on principal component (LR-PC), and canonical discriminant analysis of spectral wave number (DA-W). About 9% of the samples did not coagulate at 30 min. The use of LR-W gave a poorer classification of NCM. The use of LR-PC improved the percentage of correct assignment (45 ± 9%). The DA-W method allows us to reach 75.1 ± 10.3 and 76.5 ± 18.4% of correct assignments of the inner and external validation datasets, respectively. As far as GWA of NCM, 458 SNP associations and 45 candidate genes were detected. The genes retrieved from public databases were mostly linked to mammary gland metabolism, udder health status, and a milk compound also known to affect the ability of milk to coagulate. In particular, the potential involvement of CAPNs deserves further investigation.https://www.frontiersin.org/articles/10.3389/fanim.2022.889797/fullFourier Transform Infra Red (FTIR)spectroscopydairy sheepSNPclotting properties |
| spellingShingle | Giustino Gaspa Fabio Correddu Alberto Cesarani Alberto Cesarani Michele Congiu Corrado Dimauro Alfredo Pauciullo Nicolò Pietro Paolo Macciotta Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed Frontiers in Animal Science Fourier Transform Infra Red (FTIR) spectroscopy dairy sheep SNP clotting properties |
| title | Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed |
| title_full | Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed |
| title_fullStr | Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed |
| title_full_unstemmed | Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed |
| title_short | Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed |
| title_sort | multivariate and genome wide analysis of mid infrared spectra of non coagulating milk of sarda sheep breed |
| topic | Fourier Transform Infra Red (FTIR) spectroscopy dairy sheep SNP clotting properties |
| url | https://www.frontiersin.org/articles/10.3389/fanim.2022.889797/full |
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