AUTHOR=Gaspa Giustino , Correddu Fabio , Cesarani Alberto , Congiu Michele , Dimauro Corrado , Pauciullo Alfredo , Macciotta Nicolò Pietro Paolo TITLE=Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed JOURNAL=Frontiers in Animal Science VOLUME=Volume 3 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/animal-science/articles/10.3389/fanim.2022.889797 DOI=10.3389/fanim.2022.889797 ISSN=2673-6225 ABSTRACT=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 up to 20% of NCM has been reported in literature. 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 and NCM. The main goals of this work were: i) to assess the predictivity of MIR spectra for NCM classification; ii) to conduct a genome-wide association on the coagulation ability. Milk sample from 949 Sarda ewes genotyped and phenotyped for milk coagulation properties (MCP) served as training dataset. Validation dataset included of 662 ewes. Three classical MCP were measured: rennet coagulation time (RCT), curd firmness (a30) and curd firming time (k20). Moreover, the MIR spectra were acquired and stored in the region between 925.92 and 5011.54 cm−1. The probability of a sample to be NCM was modelled through: step-wise logistic-regression on milk spectral information (LR-W), logistic regression on principal component (PC-LR) and canonical discriminant analysis of spectral wavenumber (DA-W). About 9% of samples did not coagulate at 30 min. The use LR-W gave the poorer classification of NCM. Use of PC-LR improve the % of correct assignment (45%±9.0%). DA-W method allows to reach 75.1%±10.3% and 76.5%±18.4% of correct assignment inner and external validation dataset, respectively. As far as GWA of NCM detected 458 SNP associations and 45 candidate genes. The genes retrieved from public databases were mostly linked to mammary gland metabolism, udder health status and milk compound known also to affect the ability of milk to coagulate. In particular, a potential involvement of CAPNs deserves further investigations.