Understanding and utilizing genetic diversity in Dual-Purpose Blue: genome‐wide association for type traits

peer reviewedDual-Purpose Blue in Belgium and northern France is a local breed that is currently in the focus in order to understand its genetic distinctiveness and its use for local products. Its genomic evaluation systems are evolving, and its specific genetic distinctness was here studied for type traits. Results showed that throughout the 23 traits, there were two distinguishable genomic regions (BTA2 and BTA26) where BTA26 was associated with development traits and BTA2 was associated with muscularity traits, but also with associated traits as overall rump, udder depth, overall udder, and rear udder. Given these results future genomic evaluation systems should consider the segregating MSTN (myostatin), which is located on BTA2

Is it possible to differentiate meat products of a local breed from those of its sister breed based on genotypes?

peer reviewedTo maintain endangered breeds and preserve their intrinsic diversity, it is often advocated to develop derived labelled products and the related certification process. However, this certification process is not always easily implemented if the endangered breed is closely related to another one. The breed traceability is only possible if the genetic diversity between those breeds is high enough. In this study, it was determined if meat of Dual-Purpose Blue (DPB) animals can be differentiated from meat of its sister breed, the Beef Belgian Blue (BBB), by the application of a genomic test. The results showed that the meat of DPB was completely distinguished from the meat of BBB, and this, with a probability of one for all meat samples. It therefore seemed possible to differentiate the DPB derived products from those of BBB with a high accuracy, meaning the implementation in routine of a certification process seemed possible

Genome-wide association study for mid-infrared methane predictions in Walloon dairy cows

peer reviewedThis study aimed to identify genomic regions associated with two mid infrared-based CH4 traits [predicted daily CH4 emission (PME, g/d), and log-transformed predicted CH4 intensity (LMI)] in Walloon dairy cows. The data consisted of 1,529,282 test-day records from 229,465 cows distributed in 1,530 herds collected from 2006 to 2021. Random regression test-day models were used to estimate variance components. The proportion of genetic variance explained by windows of 50 consecutive SNPs was calculated and regions accounting for at least 1.0% of the total genetic variance were identified. Mean (SD) daily h2 estimated for PME and LMI were 0.14 (0.05) and 0.24 (0.05), respectively. Two regions on BTA14 (positions 1.86 to 2.12, and 1.48 to 1.68 Mb) were associated with both PME and LMI. A region between 144.38 to 144.46 Mb on BTA1 was associated with PME; and the region between 2.68 and 2.94 Mb on BTA14 was associated with LMI. Results showed potential for genome-enhanced advisory systems to reduce methane emissions

Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows

peer reviewedThis study aimed to estimate genetic parameters and identify genomic region(s) associated with selected cheese-making properties (CMP) in Dual-Purpose Belgian Blue (DPBB) cows. Edited data were 46,301 test-day records of milk yield, fat percentage, protein percentage, casein percentage, milk calcium content (CC), coagulation time (CT), curd firmness after 30 min from rennet addition (a30), and milk titratable acidity (MTA) collected from 2014 to 2020 on 4,077 first-parity (26,027 test-day records), and 3,258 secondparity DPBB cows (20,274 test-day records) distributed in 124 herds in the Walloon Region of Belgium. Data of 28,266 SNP, located on 29 Bos taurus autosomes (BTA) of 1,699 animals were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 25 consecutive SNPs (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Heritability estimates for the included CMP ranged from 0.19 (CC) to 0.50 (MTA), and 0.24 (CC) to 0.41 (MTA) in the first and second parity, respectively. The genetic correlation estimated between CT and a30 varied from −0.61 to −0.41 and from −0.55 to −0.38 in the first and second lactations, respectively. Negative genetic correlations were found between CT and milk yield and composition, while those estimated between curd firmness and milk composition were positive. Genome-wide association analyses results identified 4 genomic regions (BTA1, BTA3, BTA7, and BTA11) associated with the considered CMP. The identified genomic regions showed contrasting results between parities and among the different stages of each parity. It suggests that different sets of candidate genes underlie the phenotypic expression of the considered CMP between parities and lactation stages of each parity. The findings of this study can be used for future implementation and use of genomic evaluation to improve the cheese-making traits in DPBB cows

Single-step genome-wide association analyses for selected infrared-predicted cheese-making traits in Walloon Holstein cows.

peer reviewedThis study aimed to perform genome-wide association study to identify genomic regions associated with milk production and cheese-making properties (CMP) in Walloon Holstein cows. The studied traits were milk yield, fat percentage, protein percentage, casein percentage (CNP), calcium content, somatic cell score (SCS), coagulation time, curd firmness after 30 min from rennet addition, and titratable acidity. The used data have been collected from 2014 to 2020 on 78,073 first-parity (485,218 test-day records), 48,766 second-parity (284,942 test-day records), and 21,948 third-parity (105,112 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA) of 6,617 animals (1,712 males), were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 KB) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for positional candidate genes. Heritability estimates for the studied traits ranged from 0.10 (SCS) to 0.53 (CNP), 0.10 (SCS) to 0.50 (CNP), and 0.12 (SCS) to 0.49 (CNP) in the first, second, and third parity, respectively. Genome-wide association analyses identified 6 genomic regions (BTA1, BTA14 [4 regions], and BTA20) associated with the considered traits. Genes including the SLC37A1 (BTA1), SHARPIN, MROH1, DGAT1, FAM83H, TIGD5, MROH6, NAPRT, ADGRB1, GML, LYPD2, JRK (BTA14), and TRIO (BTA20) were identified as positional candidate genes for the studied CMP. The findings of this study help to unravel the genomic background of a cow's ability for cheese production and can be used for the future implementation and use of genomic evaluation to improve the cheese-making traits in Walloon Holstein cows

Analyzing the genetic diversity in Walloon and European Piétrain pig populations using pseudo-phenotypes, pedigree and SNP marker data

Cette étude a pour objectifs de déterminer l’origine du porc Piétrain, d’estimer la diversité des Piétrains wallons et d’analyser la diversité génétique existante chez différentes populations européennes de Piétrain. A cette fin, le pedigree et les pseudo-phénotypes (i.e. les valeurs d’élevage dérégressées) de la population wallonne et les génotypes de différentes populations européennes ont été étudiées. Le positionnement multi-dimensionnel, basé sur les génotypes, n’a pas permis de déduire l’origine des Piétrains avec certitude. Cependant, cette analyse suggère l’implication de différentes races locales anglaises (e.g. le Berkshire) et de différentes races locales tachetées. Ensuite, différents paramètres basés sur le pedigree de verrats dont la descendance a été testée en station ont été analysés pour avoir un aperçu de la diversité génétique de la population wallonne. Le coefficient de consanguinité moyen a été estimé à 2,74%, la taille effective de la population à 223 et le paramètre de diversité génétique à 97,96%. Ces paramètres indiquent que la diversité génétique de la population wallonne semble relativement préservée. Les flux génétiques, peu fréquents entre fermes, ont également été étudiés grâce à un positionnement multi-dimensionnel basé sur l’opposé des coefficients de kinship. Une Analyse en Composante Principale basée sur les pseudo-phénotypes a donné une indication de la trajectoire de la population via les objectifs de sélection actuels. En effet, ceux-ci sont orientés soit vers les traits de croissance, soit vers les traits viandeux. Il peut donc être suggéré au programme Belgian Piétrain, basé sur la cryopréservation de la semence des verrats, d’échantillonner de façon représentative les verrats en fonction des diversités génétique et phénotypique estimées dans cette étude. On peut également recommander aux éleveurs de contribuer de façon plus équilibrée au testage en station puisqu’un seul éleveur a envoyé 55% des verrats testés. Finalement, les génotypes de Piétrains européens et américains ont été analysés. Les estimations de la consanguinité et des segments génomiques en homozygotie ont permis de déduire que les populations néerlandaises et américaines, supposées commerciales, étaient plus consanguines et moins variables. Pour éviter une situation de goulot d’étranglement dans le futur, ces populations devraient favoriser les échanges d’animaux.This study aims to infer the origin of the Piétrain breed, to estimate the diversity of the Walloon Piétrain population and to analyze the existing genetic diversity of different European Piétrain populations. For these purposes, pedigree and pseudo-phenotypes (i.e. deregressed estimated breeding values) of the Walloon population and genotypes of several European populations were analyzed. The Multi-Dimensional Scaling (MDS) based on genotypes did not allow to have an exact assumption of the Piétrain breed origin. However, it suggested the involvement of different local English (e.g. Berkshire) and Spotted breeds. To have an insight of the Walloon genetic diversity, different pedigree parameters of boars provided to progeny testing were then analyzed. The average inbreeding coefficient was 2.74%, the effective population size (Ne) was 223 and the genetic diversity parameter was 97.96%. The genetic diversity found in the Walloon population seemed therefore relatively high. Gene flows, relatively uncommon between farms, were also studied by a MDS based on the opposite of kinship coefficients. A Principal Component Analysis (PCA) based on pseudo-phenotypes provided complementary information about breeding objectives as it was found that owners focused on meat or growth traits. It could therefore be suggested to the Belgian Piétrain program, based on the boar’s semen cryopreservation, to sample representative boars in the population regarding its genetic and phenotypic diversities. Moreover, as one owner provided 55% of the tested boars, owners should equally contribute to progeny testing. Finally, different European and an American Piétrain populations were analyzed through genotypes. Inbreeding estimations and Runs of Homozygosity (ROHs) stated that Dutch and American populations, supposedly held by commercial firms, were more inbred and uniform. More exchanges of animals should be done in these populations to avoid bottleneck in the future

Supporting the management and diversity of local breeds through the use of genomic tools

The main objective of this thesis was to develop genomic tools to support the conservation of local and endangered breeds in the long run. Different strategies can be considered to achieve this goal. On the one hand, collaboration between breeds can be enhanced by optimizing exchanges among them while preserving their intrinsic diversity and specificities. To investigate how different red-pied cattle breeds could collaborate, their between- and within-breed diversity were first studied. The principal component analysis (PCA), the fixation index (Fst) and the phylogenic tree based on genotypes (39,967 single nucleotide polymorphisms [SNPs]) of eight red-pied cattle breeds (795 animals) from Benelux showed that the East Belgian Red and White (EBRW), the Red-Pied of the Ösling (RPO), the Meuse-Rhine-Yssel (MRY), the Deep Red (DR) and the Improved Red (IR) breeds were part of a genomic continuum, making collaborations between these breeds theoretically possible. Moreover, Euclidean distances of animals to PCA centroids and ADMIXTURE proportions allowed to detect animals that could potentially be part of the reference population of EBRW and RPO for further genomic evaluations. For both breeds, animals from MRY, DR and IR could potentially be used for such a purpose. This is a first step for the development of an across-breed reference population necessary to build a genomic evaluation system for EBRW and RPO. Inbreeding coefficients (F) were also estimated through the study of runs of homozygosity (ROH) and were found to be relatively low, except for the Groningen White Headed (GWH) breed. To have a first insight of the gene flow between breeds, an ADMIXTURE clustering was performed. It was found that the EBRW, DR and IR breeds shared a similar pattern of ADMIXTURE. The history of these breeds can be further investigated, for example with D-statistics. On the other hand, genomic breed assignment tools can also be used for the conservation of endangered breeds and the building of a reference population. This kind of tools can help to register animals from endangered breeds, which often lack pedigree, to their breeding book. They can also ensure the consumer’s trust by certifying the breed of origin of local breed-derived products. This is of particular interest for Dual-Purpose Blue (DPB), whose meat is marketed under a specific brand. In this case, it is important to clearly distinguish meat of DPB from this of Beef Belgian Blue (BBB) which is its mainstream sister breed. To develop a breed assignment tool, there are three main steps to follow: 1. The selection of breed-informative markers 2. Optimization of a classification method based on a training population 3. Validation of the developed model on new animals In this thesis, to develop a breed assignment tool, 17,773 SNPs and 557 animals from 12 breeds were used. For the selection of SNPs, five different methodologies were followed: three different kinds of PCA combined with a random forest (RF), Fst values combined with RF, and the partial least squares-discriminant analysis (PLS-DA). The whole available SNP panel was also tested. Then, the different SNP panels were used in four different classification methods: PLS-DA, nearest shrunken centroids (NSC), RF and linear support vector machine (SVM). Best models, with more than 90% of global accuracy in cross-validation, were finally evaluated on new animals. Results showed that the PLS-DA for selection of SNPs followed by the NSC for classification of animals provided the best results in validation (99% or 98% of correct assignment depending on the threshold used for SNP selection). The developed tool was also applied on meat samples of DPB, BBB and Holstein (HOL) to determine the feasibility to distinguish DPB from BBB meat. It was possible to assign each meat sample to its breed with a probability of one, making the development of a certification tool plausible. Finally, a model based on a genomic relationship matrix (GRM) as an input of a linear SVM was compared to the previously developed model. The objective was to get rid of the step of selection of SNPs. This model based on all SNPs gave a similar level of global accuracy in validation compared to the model based on a SNP subset (97.97% vs. 97.86%). It was also faster to compute. Further developments of breed assignment tools involve their adaptation for the detection of crossbreds. Another perspective is the simulation of exchanges between local sister breeds to optimize them in real conditions. A final suggestion is to include explicitly genotypes in guidelines to define endangered breeds, for the creation of breeding programs and herd books and for the optimization of exchanges between sister breeds.L’objectif principal de cette thèse est le développement d’outils génomiques permettant le soutien et la conservation sur le long terme de races locales et/ou menacées. Pour atteindre cet objectif, plusieurs stratégies peuvent être élaborées. D’une part, la collaboration entre les différentes races locales peut être améliorée en optimisant les échanges d’animaux et/ou de semence. Ces échanges doivent simultanément préserver la diversité et les spécificités intrinsèques des différentes races locales. Pour déterminer comment différentes races locales pie-rouges pourraient collaborer, leur diversité inter- et intra-raciale a premièrement été étudiée. L’analyse en composante principale, l’index de fixation (Fst) et l’arbre phylogénétique basés sur les génotypes (39,967 polymorphismes d’un seul nucléotide [SNPs]) de huit races bovines locales (795 animaux) du Benelux ont démontré que la Rouge-Pie de l’Est de la Belgique, la Pie-Rouge de l’Ösling, la Meuse-Rhin-Yssel, la « Brandrode rund » et la Rouge améliorée font partie d’un continuum génomique. La collaboration entre ces différentes races semble donc possible. De plus, les distances euclidiennes des animaux par rapport aux centroïdes de l’analyse en composantes principales et aux proportions du clustering « ADMIXTURE » ont permis de détecter les animaux qui pourraient faire partie des populations de référence des races Rouge-Pie de l’Est de la Belgique et Pie-Rouge de l’Ösling pour de futures évaluations génomiques. Pour les deux races, des animaux appartenant aux races Meuse-Rhin-Yssel, « Brandrode rund » et Rouge améliorée peuvent potentiellement être utilisés dans ce but. Il s’agit d’une première étape pour le développement d’une population de référence conjointe, nécessaire pour le développement d’un système d’évaluations génomiques. Les coefficients de consanguinité (F) ont aussi été estimés grâce à l’étude des segments en homozygotie. Ils étaient relativement bas, sauf pour la race « Groningen White Headed». Pour avoir un aperçu des flux génétiques entre races, un clustering a été réalisé. Il a permis de démontrer que les races Rouge-Pie de l’Est de la Belgique, « Brandrode rund » et Rouge améliorée partagent un motif similaire de clustering. L’histoire de ces races peut être étudiée de façon plus approfondie, par exemple à l’aide des statistiques D. D’autre part, un autre outil génomique peut être utilisé pour aider à la conservation des races menacées et construire une population de référence: l’outil génomique d’assignation à la race. Ce type d’outil peut aider à l’enregistrement des animaux de races menacées, pour lesquels le pedigree est souvent manquant, dans leur livre généalogique. Il peut aussi assurer la confiance du consommateur en certifiant la race d’origine de produits dérivés de races locales. Cette application trouve un intérêt particulier pour la race Bleue mixte, dont la viande est vendue sous une marque spécifique. Dans ce cas, il est important de clairement distinguer la viande de Bleue mixte de celle de sa race sœur, la Blanc Bleu Belge, qui est une race à grands effectifs. Pour développer un outil d’assignation à la race, trois étapes principales doivent être suivies : 1. La sélection de marqueurs informatifs 2. L’optimisation d’une méthode de classification en utilisant une population d’entraînement 3. La validation du modèle développé sur de nouveaux animaux Dans cette thèse, pour développer un outil d’assignation à la race, 17 773 SNPs et 557 animaux appartenant à 12 races ont été utilisés. Pour la sélection des SNPs, cinq méthodologies différentes ont été suivies : trois différents types d’analyse en composantes principales combinée avec une forêt aléatoire, l’index de fixation également combiné avec la forêt aléatoire, et l’analyse discriminante dite « PLS-DA ». En plus de ces panels sélectionnés, la classification a également été développée sur l’ensemble des SNPs disponibles. Quatre méthodes de classification ont ensuite été testées : la PLS-DA, la méthode du plus proche centroïde corrigé, la forêt aléatoire et la machine à vecteurs de support linéaire. Les meilleurs modèles, avec plus de 90% d’assignation correcte en validation croisée, ont finalement été évalués sur de nouveaux animaux. Les résultats ont démontré que l’utilisation de la PLS-DA pour la sélection des SNPs suivie de la classification basée sur la méthode du plus proche centroïde corrigé donnait les meilleurs résultats en validation (99% ou 98% d’assignation correcte en fonction du seuil choisi pour la sélection des SNPs). L’outil développé a aussi été utilisé sur des morceaux de viande de Bleue mixte, de Blanc Bleue Belge et de Holstein pour déterminer la faisabilité de distinguer la viande de Bleue mixte de celle de la Blanc Bleu Belge. Il a été possible d’assigner chaque morceau de viande à sa race avec une probabilité de un. Le développement d’un outil de certification semble donc faisable. Finalement, un modèle utilisant différentes variables basées sur la matrice de relation génomique comme entrées pour une machine à vecteurs de support linéaire a été comparée au modèle précédemment développé. L’objectif était de passer outre l’étape de sélection des SNPs. Le modèle basé sur tous les SNPs a donné un pourcentage d’assignation correcte en validation similaire à celui du modèle basé sur un sous-jeu de SNPs (97,97% vs. 97,86%). Il était aussi plus rapide pour effectuer l’assignation. Les prochains développements pour l’outil d’assignation à la race comprennent leur adaptation pour la détection d’animaux croisés. Une autre perspective de ce travail est la simulation d’échanges d’animaux et/ou de semence entre animaux de races locales afin de les optimiser en conditions réelles. Une suggestion finale est l’inclusion explicite des génotypes dans les lignes directrices permettant de définir les races menacées, la création de programmes d’élevage, de livres généalogiques et l’optimisation d’échanges d’animaux et/ou de semence entre races locales