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The 'omics revolution has made a large amount of sequence data available to researchers and the industry. This has had a profound impact in the field of bioinformatics, stimulating unprecedented advancements in this discipline. Mostly, this is usually looked at from the perspective of human 'omics, in particular human genomics. Plant and animal genomics, however, have also been deeply influenced by next-generation sequencing technologies, with several genomics applications now popular among researchers and the breeding industry. Genomics tends to generate huge amounts of data, and genomic sequence data account for an increasing proportion of big data in biological sciences, due largely to decreasing sequencing and genotyping costs and to large-scale sequencing and resequencing projects. The analysis of big data poses a challenge to scientists, as data gathering currently takes place at a faster pace than does data processing and analysis, and the associated computational burden is increasingly taxing, making even simple manipulation, visualization and transferring of data a cumbersome operation. The time consumed by the processing and analysing of huge data sets may be at the expense of data quality assessment and critical interpretation. Additionally, when analysing lots of data, something is likely to go awry-the software may crash or stop-and it can be very frustrating to track the error. We herein review the most relevant issues related to tackling these challenges and problems, from the perspective of animal genomics, and provide researchers that lack extensive computing experience with guidelines that will help when processing large genomic data sets., (© 2018 Stichting International Foundation for Animal Genetics.)

Local breeds of livestock are of conservation significance as components of global biodiversity and as reservoirs of genetic variation relevant to the future sustainability of agriculture. One such rare historic breed, the Chillingham cattle of northern England, has a 350-year history of isolation and inbreeding yet shows no diminution of viability or fertility. The Chillingham cattle have not been subjected to selective breeding. It has been suggested previously that the herd has minimal genetic variation. In this study, high-density SNP genotyping with the 777K SNP chip showed that 9.1% of loci on the chip are polymorphic in the herd, compared with 62-90% seen in commercial cattle breeds. Instead of being homogeneously distributed along the genome, these loci are clustered at specific chromosomal locations. A high proportion of the Chillingham individuals examined were heterozygous at many of these polymorphic loci, suggesting that some loci are under balancing selection. Some of these frequently heterozygous loci have been implicated as sites of recessive lethal mutations in cattle. Linkage disequilibrium equal or close to 100% was found to span up to 1350 kb, and LD was above r(2) = 0.25 up to more than 5000 kb. This strong LD is consistent with the lack of polymorphic loci in the herd. The heterozygous regions in the Chillingham cattle may be the locations of genes relevant to fitness or survival, which may help elucidate the biology of local adaptation in traditional breeds and facilitate selection for such traits in commercial cattle., (© 2015 Stichting International Foundation for Animal Genetics.)

Since the beginning of the genomic era, the number of available single nucleotide polymorphism (SNP) arrays has grown considerably. In the bovine species alone, 11 SNP chips not completely covered by intellectual property are currently available, and the number is growing. Genomic/genotype data are not standardized, and this hampers its exchange and integration. In addition, software used for the analyses of these data usually requires not standard (i.e. case specific) input files which, considering the large amount of data to be handled, require at least some programming skills in their production. In this work, we describe a software toolkit for SNP array data management, imputation, genome-wide association studies, population genetics and genomic selection. However, this toolkit does not solve the critical need for standardization of the genotypic data and software input files. It only highlights the chaotic situation each researcher has to face on a daily basis and gives some helpful advice on the currently available tools in order to navigate the SNP array data complexity., (© 2015 Stichting International Foundation for Animal Genetics.)

Genotype imputation is routinely applied in a large number of cattle breeds. Imputation has become a need due to the large number of SNP arrays with variable density (currently, from 2900 to 777,962 SNPs). Although many authors have studied the effect of different statistical methods on imputation accuracy, the impact of a (likely) change in the reference genome assembly on imputation from lower to higher density has not been determined so far. In this work, 1021 Italian Simmental SNP genotypes were remapped on the three most recent reference genome assemblies. Four imputation methods were used to assess the impact of an update in the reference genome. As expected, the four methods behaved differently, with large differences in terms of accuracy. Updating SNP coordinates on the three tested cattle reference genome assemblies determined only a slight variation on imputation results within method., (© 2014 Stichting International Foundation for Animal Genetics.)

In an earlier study, serum levels of natural antibody isotypes IgM- and IgG-binding keyhole limpet hemocyanin were found to be indicative for survival through the laying period of hens and therefore considered as promising traits for future implementation in breeding programs for higher survival of layers. In the present study, we first estimated the genetic parameters for the two isotypes at 20, 40 and 65 weeks of age (IgM20, IgM40 and IgM65; IgG20, IgG40 and IgG65). Pooled genetic parameters were estimated from the total population of 2504 hens from nine purebred layer lines, with line included in the model to account for admixture. Moderate heritabilities (0.14-0.44) indicated that selection for isotype titers is feasible, especially for IgM. Secondly, associations between 1022 SNP markers and the above-mentioned six immunological traits were estimated in 650 genotyped hens from the nine lines. The association study was performed across lines to detect markers that are closer to the QTL and have the same phase of association in the entire population. Forty-three significant associations between SNPs and isotype titers were detected. The SNPs of interleukins IL10 and IL19 were associated with both isotypes; SNPs of tripartite motif containing 33 (TRIM33) and IL6 showed significant association with IgG20 and IgM20 respectively; SNPs of heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1) were associated with IgG titers at older ages. Some detected SNPs were also reported associated with other immune and behavioral traits., (© 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.)

The aim of the present study was to detect quantitative trait loci (QTL) for innate and adaptive immunity in laying hens. For this purpose, the associations between 1022 single nucleotide polymorphism (SNP) markers and immune traits were studied in 583 hens from nine different layer lines. Immune traits were natural antibodies for keyhole limpet haemocyanin (KLH) and lipopolysaccharide (LPS) at 20, 40 and 65 weeks, acquired antibodies to the vaccinal virus of Newcastle disease at 20 weeks, and complement activity measured on sheep and bovine red blood cells at 20, 40 and 65 weeks. We adopted a novel approach based on across-line analysis and testing of the SNP-by-line interaction. Among lines, linkage disequilibrium is conserved at shorter distances than in individual lines; therefore, SNPs significantly associated with immune traits across lines are expected to be near the functional mutations. In the analysis, the SNPs that had a significant across-line effect but did not show significant SNP-by-line interaction were identified to test whether the association was consistent in the individual lines. Ultimately, 59 significant associations between SNPs and immune traits were detected. Our results confirmed some previously identified QTL and identified new QTL potentially involved in the immune function. We found evidence for a role of IL17A (chromosome 3) in natural and acquired antibody titres and in the classical and alternative pathways of complement activation. The major histocompatibility genes on chromosome 16 showed significant association with natural and acquired antibody titres and classical complement activity. The IL12B gene on chromosome 13 was associated with natural antibody titres.