Cattle are one of the most important livestock species in West Africa, providing multiple services to farmers and contributing to national economies. Various breeding strategies have been implemented to enhance their productivity and have improved farmer livelihoods. This review describes cattle breeding experiences across West Africa, spanning the N’Dama breed in Mali, Senegal, and The Gambia to the breeds Azawak Zebu, Fulani Zebu, and taurine Baoulé in Burkina Faso. The main objectives of most breeding programs have been to optimize meat and milk performance of taurine and Zebu cattle as well as trypanotolerance of taurine cattle. In some cases, “closed nucleus” schemes have proven limited and so have evolved into “open nucleus” schemes. Recent community-based breeding programs have shown promise. The major challenges of breeding programs remain defining realistic breeding objectives and securing the involvement of stakeholders. All the strategies reviewed here have been funded externally within development or research projects that are often too short to yield tangible genetic improvement, and whether they will continue beyond those projects is uncertain. This review highlights the need for continuing government support to ensure the sustainability of local cattle breeding programs.

Runs of homozygosity (ROH) islands are stretches of homozygous sequence in the genome of a large proportion of individuals in a population. Algorithms for the detection of ROH depend on the similarity of haplotypes. Coverage gaps and copy number variants (CNV) may result in incorrect identification of such similarity, leading to the detection of ROH islands where none exists. Misidentified hemizygous regions will also appear as homozygous based on sequence variation alone. Our aim was to identify ROH islands influenced by marker coverage gaps or CNV, using Illumina BovineHD BeadChip (777 K) single nucleotide polymorphism (SNP) data for Austrian Brown Swiss, Tyrol Grey and Pinzgauer cattle. ROH were detected using clustering, and ROH islands were determined from population inbreeding levels for each marker. CNV were detected using a multivariate copy number analysis method and a hidden Markov model. SNP coverage gaps were defined as genomic regions with intermarker distances on average longer than 9.24 kb. ROH islands that overlapped CNV regions (CNVR) or SNP coverage gaps were considered as potential artefacts. Permutation tests were used to determine if overlaps between CNVR with copy losses and ROH islands were due to chance. Diversity of the haplotypes in the ROH islands was assessed by haplotype analyses. In Brown Swiss, Tyrol Grey and Pinzgauer, we identified 13, 22, and 24 ROH islands covering 26.6, 389.0 and 35.8 Mb, respectively, and we detected 30, 50 and 71 CNVR derived from CNV by using both algorithms, respectively. Overlaps between ROH islands, CNVR or coverage gaps occurred for 7, 14 and 16 ROH islands, respectively. About 37, 44 and 52% of the ROH islands coverage in Brown Swiss, Tyrol Grey and Pinzgauer, respectively, were affected by copy loss. Intersections between ROH islands and CNVR were small, but significantly larger compared to ROH islands at random locations across the genome, implying an association between ROH islands and CNVR. Haplotype diversity for reliable ROH islands was lower than for ROH islands that intersected with copy loss CNVR. Our findings show that a significant proportion of the ROH islands in the bovine genome are artefacts due to CNV or SNP coverage gaps.

Genome-wide prediction has become the method of choice in animal and plant breeding. Prediction of breeding values and phenotypes are routinely performed using large genomic data sets with number of markers on the order of several thousands to millions. The number of evaluated individuals is usually smaller which results in problems where model sparsity is of major concern. The LASSO technique has proven to be very well-suited for sparse problems often providing excellent prediction accuracy. Several computationally efficient LASSO algorithms have been developed, but optimization of hyper-parameters can be demanding. We have developed a novel automatic adaptive LASSO (AUTALASSO) based on the alternating direction method of multipliers (ADMM) optimization algorithm. The two major hyper-parameters of ADMM are the learning rate and the regularization factor. The learning rate is automatically tuned with line search and the regularization factor optimized using Golden section search. Results show that AUTALASSO provides superior prediction accuracy when evaluated on simulated and real bull data compared to the adaptive LASSO, LASSO and ridge regression implemented in the popular glmnet software. The AUTALASSO provides a very flexible and computationally efficient approach to GWP, especially when it is important to obtain high prediction accuracy and genetic gain. The AUTALASSO also has the capability to perform GWAS of both additive and dominance effects with smaller prediction error than the ordinary LASSO.

The genomes of crossbred (admixed) individuals are a mosaic of ancestral haplotypes formed by recombination in each generation. The proportion of these ancestral haplotypes in certain genomic regions can be responsible for either susceptibility or tolerance against pathogens, and for performances in production traits. Using a medium-density genomic marker panel from the Illumina Bovine SNP50 BeadChip, we estimated individual admixture proportions for Baoulé x Zebu crossbred cattle in Burkina Faso, which were tested for trypanosome infection by direct ELISA from blood samples. Furthermore, we calculated local ancestry deviation from average for each SNP across 29 autosomes to identify potential regions under selection in the trypanotolerant Baoulé cattle and their crossbreds. We identified significant deviation from the local average ancestry (above 5 and 10% genome-wide thresholds) on chromosomes 8 and 19 in the positive animals, while the negative ones showed higher deviation on chromosomes 6, 19, 21, and 22. Some candidate genes on chromosome 6 (PDGFRA) and chromosome 19 (CDC6) have been found associated to trypanotolerance in West African taurines. Screening for F_ST outliers in trypanosome positive/negative animals we detected seven variants putatively under selection. Finally, we identified a minimum set of highly ancestry informative markers for routine admixture testing. The results of this study contribute to a better understanding of the genetic basis of trypanotolerance in Baoulé cattle and their crossbreeds. Furthermore, we provide a small informative marker set to monitor admixture in this valuable indigenous breed. As such, our results are important for conserving the genetic uniqueness and trypanotolerance of Baoulé cattle, as well as for the improvement of Baoulé and Zebu crossbreds in specific community-based breeding programs.

Monitoring for mastitis on dairy farms is of particular importance, as it is one of the most prevalent bovine diseases. A commonly used indicator for mastitis monitoring is somatic cell count. A supplementary tool to predict mastitis risk may be mid-infrared (MIR) spectroscopy of milk. Because bovine health status can affect milk composition, this technique is already routinely used to determine standard milk components. The aim of the present study was to compare the performance of models to predict clinical mastitis based on MIR spectral data and/or somatic cell count score (SCS), and to explore differences of prediction accuracies for acute and chronic clinical mastitis diagnoses. Test-day data of the routine Austrian milk recording system and diagnosis data of its health monitoring, from 59,002 cows of the breeds Fleckvieh (dual purpose Simmental), Holstein Friesian and Brown Swiss, were used. Test-day records within 21 days before and 21 days after a mastitis diagnosis were defined as mastitis cases. Three different models (MIR, SCS, MIR + SCS) were compared, applying Partial Least Squares Discriminant Analysis. Results of external validation in the overall time window (−/+21 days) showed area under receiver operating characteristic curves (AUC) of 0.70 when based only on MIR, 0.72 when based only on SCS, and 0.76 when based on both. Considering as mastitis cases only the test-day records within 7 days after mastitis diagnosis, the corresponding areas under the curve were 0.77, 0.83 and 0.85. Hence, the model combining MIR spectral data and SCS was performing best. Mastitis probabilities derived from the prediction models are potentially valuable for routine mastitis monitoring for farmers, as well as for the genetic evaluation of the trait udder health.

Livestock keepers in southwestern Burkina Faso hold the local Lobi taurine breed, local Zebu cattle, and their crosses. Some communities in the region have begun to implement community-based cattle breeding programs (CBBPs), which involve animal tagging and recording and, potentially, also bull sharing. Based on the hypothesis that the participation of livestock keepers in CBBPs depends on their attitudes towards these programs, we used questionnaires to survey the attitudes of 125 farmers towards cattle breeding strategies and tools. Results were analyzed using principal component analysis. Farmers showed a highly positive attitude towards maintaining the features of their preferred cattle breed, but their attitudes varied substantially towards crossbreeding for breed improvement. Farmers generally agreed that performance was more important than animal appearance, and most of them were willing to cooperate with breeders’ associations but were skeptical about sharing their bulls with other farmers. The majority was reluctant to record performance data, which may be due to a capacity deficit and their confidence in being able to select the best animals based purely on phenotype. Our analysis suggests that breeders’ associations, as a key component of CBBPs, should lay down clear rules and obligations for their members from the outset. Timely consideration of farmers’ attitudes towards different breeding tools may improve their uptake and guarantee the sustainability of CBBPs.