The number of publications performing genome-wide association studies (GWAS) has increased dramatically. Penalized regression approaches have been developed to overcome the challenges caused by the high dimensional data, but these methods are relatively new in the GWAS field. In this study we have compared the statistical performance of two methods (the least absolute shrinkage and selection operator—lasso and the elastic net) on two simulated data sets and one real data set from a 50 K genome-wide single nucleotide polymorphism (SNP) panel of 5570 Fleckvieh bulls. The first simulated data set displays moderate to high linkage disequilibrium between SNPs, whereas the second simulated data set from the QTLMAS 2010 workshop is biologically more complex. We used cross-validation to find the optimal value of regularization parameter λ with both minimum MSE and minimum MSE + 1SE of minimum MSE. The optimal λ values were used for variable selection. Based on the first simulated data, we found that the minMSE in general picked up too many SNPs. At minMSE + 1SE, the lasso didn't acquire any false positives, but selected too few correct SNPs. The elastic net provided the best compromise between few false positives and many correct selections when the penalty weight α was around 0.1. However, in our simulation setting, this α value didn't result in the lowest minMSE + 1SE. The number of selected SNPs from the QTLMAS 2010 data was after correction for population structure 82 and 161 for the lasso and the elastic net, respectively. In the Fleckvieh data set after population structure correction lasso and the elastic net identified from 1291 to 1966 important SNPs for milk fat content, with major peaks on chromosomes 5, 14, 15, and 20. Hence, we can conclude that it is important to analyze GWAS data with both the lasso and the elastic net and an alternative tuning criterion to minimum MSE is needed for variable selection.

Background: Signatures of selection are regions in the genome that have been preferentially increased in frequency and fixed in a population because of their functional importance in specific processes. These regions can be detected because of their lower genetic variability and specific regional linkage disequilibrium (LD) patterns. Methods: By comparing the differences in regional LD variation between dairy and beef cattle types, and between indicine and taurine subspecies, we aim at finding signatures of selection for production and adaptation in cattle breeds. The VarLD method was applied to compare the LD variation in the autosomal genome between breeds, including Angus and Brown Swiss, representing taurine breeds, and Nelore and Gir, representing indicine breeds. Genomic regions containing the top 0.01 and 0.1 percentile of signals were characterized using the UMD3.1 Bos taurus genome assembly to identify genes in those regions and compared with previously reported selection signatures and regions with copy number variation. Results: For all comparisons, the top 0.01 and 0.1 percentile included 26 and 165 signals and 17 and 125 genes, respectively, including TECRL , BT.23182 or FPPS , CAST, MYOM1, UVRAG and DNAJA1 . Conclusions: The VarLD method is a powerful tool to identify differences in linkage disequilibrium between cattle populations and putative signatures of selection with potential adaptive and productive importance.

The Survival Kit is a Fortran 90 Software intended for survival analysis using proportional hazards models and their extension to frailty models with a single response time. The hazard function is described as the product of a baseline hazard function and a positive (exponential) function of possibly time-dependent fixed and random covariates. Stratified Cox, grouped data and Weibull models can be used. Random effects can be either log-gamma or normally distributed and can account for a pedigree structure. Variance parameters are estimated in a Bayesian context. It is possible to account for the correlated nature of two random effects either by specifying a known correlation coefficient or estimating it from the data. An R interface of the Survival Kit provides a user friendly way to run the software.

Runs of homozygosity (ROH) are chromosomal stretches that in a diploid genome appear in a homozygous state and display identical alleles at multiple contiguous loci. This study aimed to systematically compare the genomic distribution of the ROH islands among five populations of wild vs. commercial chickens of both layer and broiler type. To this end, we analyzed whole genome sequences of 115 birds including white layer (WL, n=25), brown layer (BL, n=25), broiler line A (BRA, n=20), broiler line B (BRB, n=20) and Red Junglefowl (RJF, n=25). The ROH segments varied in size markedly among populations, ranging from 0.3 to 21.83 Mb reflecting their past genealogy. White layers contained the largest portion of the genome in homozygous state with an average ROH length of 432.1 Mb (±18.7) per bird, despite carrying it in short segments (0.3-1 Mb). Population-wise inbreeding measures based on Wright9s (F_is) and genomic (F_ROH) metrics revealed highly inbred genome of layer lines relative to the broilers and Red Junglefowl. We further revealed the ROH islands, among commercial lines overlapped with QTLs related to limb development (GREM1, MEOX2), body weight (Meis2a.1, uc_338), eggshell color (GLCCI1, ICA1, UMAD1), antibody response to Newcastle virus (ROBO2), and feather pecking. Comparison of ROH landscape in sequencing resolution demonstrated that a sizable portion of genome of commercial lines segregates in homozygote state, reflecting many generations of assortative mating and intensive selection in their recent history. In contrary, wild birds carry shorter ROH segments, likely suggestive of older evolutionary events.

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.