Relative extended haplotype homozygosity signals across breeds reveal dairy and beef specific signatures of selection

Background: A number of methods are available to scan a genome for selection signatures by evaluating patterns of diversity within and between breeds. Among these, "extended haplotype homozygosity" (EHH) is a reliable approach to detect genome regions under recent selective pressure. The objective of this study was to use this approach to identify regions that are under recent positive selection and shared by the most representative Italian dairy and beef cattle breeds. Results: A total of 3220 animals from Italian Holstein (2179), Italian Brown (775), Simmental (493), Marchigiana (485) and Piedmontese (379) breeds were genotyped with the Illumina BovineSNP50 BeadChip v.1. After standard quality control procedures, genotypes were phased and core haplotypes were identified. The decay of linkage disequilibrium (LD) for each core haplotype was assessed by measuring the EHH. Since accurate estimates of local recombination rates were not available, relative EHH (rEHH) was calculated for each core haplotype. Genomic regions that carry frequent core haplotypes and with significant rEHH values were considered as candidates for recent positive selection. Candidate regions were aligned across to identify signals shared by dairy or beef cattle breeds. Overall, 82 and 87 common regions were detected among dairy and beef cattle breeds, respectively. Bioinformatic analysis identified 244 and 232 genes in these common genomic regions. Gene annotation and pathway analysis showed that these genes are involved in molecular functions that are biologically related to milk or meat production. Conclusions: Our results suggest that a multi-breed approach can lead to the identification of genomic signatures in breeds of cattle that are selected for the same production goal and thus to the localisation of genomic regions of interest in dairy and beef production

A practical approach to detect ancestral haplotypes in livestock populations

Background The effects of different evolutionary forces are expected to lead to the conservation, over many generations, of particular genomic regions (haplotypes) due to the development of linkage disequilibrium (LD). The detection and identification of early (ancestral) haplotypes can be used to clarify the evolutionary dynamics of different populations as well as identify selection signatures and genomic regions of interest to be used both in conservation and breeding programs. The aims of this study were to develop a simple procedure to identify ancestral haplotypes segregating across several generations both within and between populations with genetic links based on whole-genome scanning. This procedure was tested with simulated and then applied to real data from different genotyped populations of Spanish, Fleckvieh, Simmental and Brown-Swiss cattle. Results The identification of ancestral haplotypes has shown coincident patterns of selection across different breeds, allowing the detection of common regions of interest on different bovine chromosomes and mirroring the evolutionary dynamics of the studied populations. These regions, mainly located on chromosomes BTA5, BTA6, BTA7 and BTA21 are related with certain animal traits such as coat colour and milk protein and fat content. Conclusion In agreement with previous studies, the detection of ancestral haplotypes provides useful information for the development and comparison of breeding and conservation programs both through the identification of selection signatures and other regions of interest, and as indicator of the general genetic status of the populations

Genome-wide associations for coagulation traits, individual cheese yield and curd nutrient recoveries in bovine milk

The cow’s ability to produce cheese was decomposed into eleven milk coagulation curd-firming and syneresis properties (MCP), three cheese yield (CY) and 4 milk component recoveries into the curd (REC) traits, and genome-wide association analyses were conducted. The MCP traits were: 3 traditional single point lacto-dynamographic properties (RCT: rennet coagulation time, min; k20: time to a curd firmness (CF) of 20 mm, min; a30: CF 30 min after rennet addition), 6 parameters modeling 360 CF data for each milk sample (CFP: potential asymptotic CF at infinite time, mm; kCF: curd firming instant rate constant, %×min-1; kSR: syneresis instant rate constant, %×min-1; RCTeq: RCT from modeling; CFmax: maximum CF, mm; tmax: time at CFmax, min), milk- protein (%) and pH. The 3 CY traits were the weight (wt) of fresh curd (%CYCURD), curd solids (%CYSOLIDS), and curd moisture (%CYWATER) as % of wt of milk processed. The 4 REC (RECFAT, RECPROTEIN, RECSOLIDS, and RECENERGY) were calculated as the % ratio between the nutrient in curd and the corresponding nutrient in processed milk. Animals (n=1,043) from 85 herds were genotyped with the Illumina SNP50 Beadchip v.2. A single marker regression was fitted using the GenABEL R package (GRAMMAR-GC). The %CYCURD was linked to chromosome 6 (P<5x10-5). However, SNP located in 16 more chromosomes (1, 2, 9, 11, 12, 13, 14, 15, 16, 18, 19, 20, 23, 26, 27 and 28) were significantly associated to other traits, displaying the importance of decomposing a complex phenotype into different parts, to unravel its genomic background. Acknowledgements: Trento Province (Italy), Italian Brown Swiss Cattle Breeders Association (ANARB, Verona, Italy) and Superbrown Consortium of Bolzano and Trent

Genome-wide association study for cheese yield and curd nutrient recovery in dairy cows

Cheese production and consumption are increasing in many countries worldwide. As a result, interest has increased in strategies for genetic selection of individuals for technological traits of milk related to cheese yield (CY) in dairy cattle breeding. However, little is known about the genetic background of a cow's ability to produce cheese. Recently, a relatively large panel (1,264 cows) of different measures of individual cow CY and milk nutrient and energy recoveries in the cheese (REC) became available. Genetic analyses showed considerable variation for CY and for aptitude to retain high proportions of fat, protein, and water in the coagulum. For the dairy industry, these characteristics are of major economic importance. Nevertheless, use of this knowledge in dairy breeding is hampered by high costs, intense labor requirement, and lack of appropriate technology. However, in the era of genomics, new possibilities are available for animal breeding and genetic improvement. For example, identification of genomic regions involved in cow CY might provide potential for marker-assisted selection. The objective of this study was to perform genome-wide association studies on different CY and REC measures. Milk and DNA samples from 1,152 Italian Brown Swiss cows were used. Three CY traits expressing the weight (wt) of fresh curd (%CYCURD), curd solids (%CYSOLIDS), and curd moisture (%CYWATER) as a percentage of weight of milk processed, and 4 REC (RECFAT, RECPROTEIN, RECSOLIDS, and RECENERGY, calculated as the % ratio between the nutrient in curd and the corresponding nutrient in processed milk) were analyzed. Animals were genotyped with the Illumina BovineSNP50 Bead Chip v.2. Single marker regressions were fitted using the GenABEL R package (genome-wide association using mixed model and regression\u2013genomic control). In total, 103 significant associations (88 single nucleotide polymorphisms) were identified in 10 chromosomes (2, 6, 9, 11, 12, 14, 18, 19, 27, 28). For RECFAT and RECPROTEIN, high significance peaks were identified in Bos taurus autosome (BTA) 6 and BTA11, respectively. Marker ARS-BFGL-NGS-104610 ( 3c104.3 Mbp) was highly associated with RECPROTEIN and Hapmap52348-rs29024684 ( 3c87.4 Mbp), closely located to the casein genes on BTA6, with RECFAT. Genomic regions identified may enhance marker-assisted selection in bovine cheese breeding beyond the use of protein (casein) and fat contents, whereas new knowledge will help to unravel the genomic background of a cow's ability for cheese production

Imputation accuracy is robust to cattle reference genome updates

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

Genome Wide Analysis of Fertility and Production Traits in Italian Holstein Cattle

A genome wide scan was performed on a total of 2093 Italian Holstein proven bulls genotyped with 50K single nucleotide polymorphisms (SNPs), with the objective of identifying loci associated with fertility related traits and to test their effects on milk production traits. The analysis was carried out using estimated breeding values for the aggregate fertility index and for each trait contributing to the index: angularity, calving interval, non-return rate at 56 days, days to first service, and 305 day first parity lactation. In addition, two production traits not included in the aggregate fertility index were analysed: fat yield and protein yield. Analyses were carried out using all SNPs treated separately, further the most significant marker on BTA14 associated to milk quality located in the DGAT1 region was treated as fixed effect. Genome wide association analysis identified 61 significant SNPs and 75 significant marker-trait associations. Eight additional SNP associations were detected when SNP located near DGAT1 was included as a fixed effect. As there were no obvious common SNPs between the traits analyzed independently in this study, a network analysis was carried out to identify unforeseen relationships that may link production and fertility traits

New approaches to investigate the genetic basis of animal adaptation to different environments

The understanding of the genetic mechanisms of livestock adaptation to environmental challenges is becoming an important research topic in this time of rapid climate change. New tools and approaches are now available to investigate this complex phenomenon. Low-cost high-throughput technologies have opened the genomic era to agricultural species. All major farm animals have been completely sequenced and HapMap projects are completed or in progress. Low, medium and high-density SNP panels are available or under construction. Molecular information on many thousand markers has initiated the era of population genomics, which is the application of genomic approaches to population genetics. The comparison of patterns of diversity along the genome in animals originating in different environments and new GIScience-based models able to associate molecular markers to environmental variables promise to discover genomic regions associated to traits important for adaptation and to pave the way to the identification of causative genes. Local breeds adapted to a sustainable production in extreme and harsh environments will play a fundamental role in this process