A high density linkage map of the bovine genome

Selective signatures in composite MONTANA TROPICAL beef cattle reveal potential genomic regions for tropical adaptation

Genomic regions related to tropical adaptability are of paramount importance for animal breeding nowadays, especially in the context of global climate change. Moreover, understanding the genomic architecture of these regions may be very relevant for aiding breeding programs in choosing the best selection scheme for tropical adaptation and/or implementing a crossbreeding scheme. The composite MONTANA TROPICAL® population was developed by crossing cattle of four different biological types to improve production in harsh environments. Pedigree and genotype data (51962 SNPs) from 3215 MONTANA TROPICAL® cattle were used to i) characterize the population structure; ii) identify signatures of selection with complementary approaches, i.e. Integrated Haplotype Score (iHS) and Runs of Homozygosity (ROH); and iii) understand genes and traits related to each selected region. The population structure based on principal components had a weak relationship with the genetic contribution of the different biological types. Clustering analyses (ADMIXTURE) showed different clusters according to the number of generations within the composite population. Considering results of both selection signatures approaches, we identified only one consensus region on chromosome 20 (35399405-40329703 bp). Genes in this region are related to immune function, regulation of epithelial cell differentiation, and cell response to ionizing radiation. This region harbors the slick locus which is related to slick hair and epidermis anatomy, both of which are related to heat stress adaptation. Also, QTLs in this region were related to feed intake, milk yield, mastitis, reproduction, and slick hair coat. The signatures of selection detected here arose in a few generations after crossbreeding between contrasting breeds. Therefore, it shows how important this genomic region may be for these animals to thrive in tropical conditions. Further investigations on sequencing this region can identify candidate genes for animal breeding and/or gene editing to tackle the challenges of climate change.

Detection of selective sweep in European wild sheep breeds

In wild animal populations, there is a differentiation between populations due to natural selection. The direction and pressure of natural selection in the wild sheep are different in the various geographic areas. Linkage disequilibrium studies showed that regions of the genome in whole wild sheep are under natural selection and that natural selection can affect immune or reproductive or metabolic traits. The study aimed to identify genomic regions under natural selection in wild sheep. For this purpose, the genetic information of 24 European wild sheep and 24 Sardinian wild sheep was used. The genotypes were determined using Illumina 50 K SNPChip arrays based on Oar_4.0 version of the sheep genome. After quality control steps, finally, 31,560 SNP markers were analyzed. The value of LD was calculated by calculating the r2 statistic between all pairs of locations through PLINK software. To identify signs of selection based on linkage disequilibrium methods, an extended haplotype homozygosity test of XP-EHH crossing population and iHS intrapopulation was used. The results of iHS studies showed that in European and Sardinian wild sheep, the highest iHS coefficient under natural selection was observed on 3 and 2 chromosome numbers, respectively. Also, the results of XP-EHH studies showed that the largest XP-EHH coefficients under natural selection in European wild sheep compared to Sardinian and vice versa in Sardinian wild sheep compared to European wild sheep were observed on 3 and 16 chromosome numbers, respectively. In addition, the results of gene cycle studies showed that COPB1, SEC24D, ZDHHC17, BBS4, RFX3, SLC26A8, CAMK2D, GRIA1, GRM1, GRID2, PPP2R1A, CPEB4, PLEKHA5 and KIF13A, VPS39, VPS53, DTNBP1, DYNC1I1, FAM91A genes are under natural selection in Sardinian and European wild sheeps, respectively. The direction and selection pressure of natural selection in the two breeds of wild sheep is different due to different geographic conditions.

Transmission ratio distortion detection by neutral genetic markers in the Pura Raza Española horse breed

Transmission Ratio Distortion (TRD) is a genetic phenomenon widely demonstrated in several livestock species, but barely in equine species. The TRD occurs when certain genotypes are over- or under-represented in the offspring of a particular mating and can be caused by a variety of factors during gamete formation or during embryonic development. For this study, 126 394 trios consisting of a stallion, mare, and offspring were genotyped using a panel of 17 neutral microsatellite markers recommended by the International Society for Animal Genetics for paternity tests and individual identification. The number of alleles available for each marker ranges from 13 to 18, been 268 the total number of alleles investigated. The TRDscan v.2.0 software was used with the biallelic procedure to identify regions with distorted segregation ratios. After completing the analysis, a total of 12 alleles (out of 11 microsatellites) were identified with decisive evidence for genotypic TRD; 3 and 9 with additive and heterosis patterns, respectively. In addition, 19 alleles (out of 10 microsatellites) were identified displaying allelic TRD. Among them, 14 and 5 were parent-unspecific and stallion-mare-specific TRD. Out of the TRD regions, 24 genes were identified and annotated, predominantly associated with cholesterol metabolism and homeostasis. These genes are often linked to non-specific symptoms like impaired fertility, stunted growth, and compromised overall health. The results suggest a significant impact on the inheritance of certain genetic traits in horses. Further analysis and validation are needed to better understand the TRD impact before the potential implementation in the horse breeding programme strategies.

Estimating inbreeding rate and effective population size in the Finnish Ayrshire population in the era of genomic selection

Genomic selection has been applied in dairy cattle breeding over the last decade. Using genomic information may speed up genetic gain as breeding values can be predicted reasonably accurately directly after birth. However, genetic diversity may decrease if the inbreeding rate per generation increases and the effective population size decreases. Despite many positive qualities of the Finnish Ayrshire, for example, high average protein yield and fertility, over time the breed has lost its place as the most common dairy breed in Finland. Thus, maintaining the genetic variability of the breed is becoming more important. The aim of our research was to estimate the impact of genomic selection on inbreeding rate and effective population size using both pedigree and genomic data. The genomic data included 46,914 imputed single nucleotide polymorphism (SNP) variants from 75,038 individuals, and the pedigree data included 2,770,025 individuals. All animals in the data were born between 2000 and 2020. Genomic inbreeding coefficients were estimated as the proportion of SNPs in runs of homozygosity (ROH) out of the total number of SNPs. The inbreeding rate was estimated by regressing the mean genomic inbreeding coefficients on birth years. Effective population size was then estimated based on the inbreeding rate. Additionally, effective population size was estimated from the mean increase in individual inbreeding using pedigree data. Introduction of genomic selection was assumed to have taken place gradually; years 2012-2014 were treated as a transition period from the traditional phenotype-based breeding value estimation to genomic-based estimation. The median length of the identified homozygous segments was 5.5 Mbp, and a slight increase in the proportion of segments over 10 Mbp was observed after 2010. The inbreeding rate decreased from 2000 to 2011 and subsequently increased slightly. The pedigree- and genomic-based estimates of inbreeding rate were similar to each other. The estimates of effective population size based on the regression method were very sensitive to the number of years considered; thus, the estimates were not very reliable. The effective population size estimated from the mean increase in individual inbreeding reached its highest value of 160 in 2011 and decreased to 150 after that. In addition, the generation interval in the sire path has decreased from 5.5 years to 3.5 years after genomic selection was implemented. Based on our results, after the implementation of genomic selection, the proportion of long ROH stretches has increased, the generation interval in the sire path has decreased, the inbreeding rate has increased and the effective population size has decreased. However, the effective population size is still at a good level, allowing for an efficient selection scheme in the Finnish Ayrshire breed.

The Innovative Informatics Approaches of High-Throughput Technologies in Livestock: Spearheading the Sustainability and Resiliency of Agrigenomics Research

For more than a decade, next-generation sequencing (NGS) has been emerging as the mainstay of agrigenomics research. High-throughput technologies have made it feasible to facilitate research at the scale and cost required for using this data in livestock research. Scale frameworks of sequencing for agricultural and livestock improvement, management, and conservation are partly attributable to innovative informatics methodologies and advancements in sequencing practices. Genome-wide sequence-based investigations are often conducted worldwide, and several databases have been created to discover the connections between worldwide scientific accomplishments. Such studies are beginning to provide revolutionary insights into a new era of genomic prediction and selection capabilities of various domesticated livestock species. In this concise review, we provide selected examples of the current state of sequencing methods, many of which are already being used in animal genomic studies, and summarize the state of the positive attributes of genome-based research for cattle (Bos taurus), sheep (Ovis aries), pigs (Sus scrofa domesticus), horses (Equus caballus), chickens (Gallus gallus domesticus), and ducks (Anas platyrhyncos). This review also emphasizes the advantageous features of sequencing technologies in monitoring and detecting infectious zoonotic diseases. In the coming years, the continued advancement of sequencing technologies in livestock agrigenomics will significantly influence the sustained momentum toward regulatory approaches that encourage innovation to ensure continued access to a safe, abundant, and affordable food supplies for future generations.

Development of a High-Density 665 K SNP Array for Rainbow Trout Genome-Wide Genotyping

Single nucleotide polymorphism (SNP) arrays, also named « SNP chips », enable very large numbers of individuals to be genotyped at a targeted set of thousands of genome-wide identified markers. We used preexisting variant datasets from USDA, a French commercial line and 30X-coverage whole genome sequencing of INRAE isogenic lines to develop an Affymetrix 665 K SNP array (HD chip) for rainbow trout. In total, we identified 32,372,492 SNPs that were polymorphic in the USDA or INRAE databases. A subset of identified SNPs were selected for inclusion on the chip, prioritizing SNPs whose flanking sequence uniquely aligned to the Swanson reference genome, with homogenous repartition over the genome and the highest Minimum Allele Frequency in both USDA and French databases. Of the 664,531 SNPs which passed the Affymetrix quality filters and were manufactured on the HD chip, 65.3% and 60.9% passed filtering metrics and were polymorphic in two other distinct French commercial populations in which, respectively, 288 and 175 sampled fish were genotyped. Only 576,118 SNPs mapped uniquely on both Swanson and Arlee reference genomes, and 12,071 SNPs did not map at all on the Arlee reference genome. Among those 576,118 SNPs, 38,948 SNPs were kept from the commercially available medium-density 57 K SNP chip. We demonstrate the utility of the HD chip by describing the high rates of linkage disequilibrium at 2–10 kb in the rainbow trout genome in comparison to the linkage disequilibrium observed at 50–100 kb which are usual distances between markers of the medium-density chip.

XSim version 2: simulation of modern breeding programs

Simulation can be an efficient approach to design, evaluate, and optimize breeding programs. In the era of modern agriculture, breeding programs can benefit from a simulator that integrates various sources of big data and accommodates state-of-the-art statistical models. The initial release of XSim, in which stochastic descendants can be efficiently simulated with a drop-down strategy, has mainly been used to validate genomic selection results. In this article, we present XSim Version 2 that is an open-source tool and has been extensively redesigned with additional features to meet the needs in modern breeding programs. It seamlessly incorporates multiple statistical models for genetic evaluations, such as GBLUP, Bayesian alphabets, and neural networks, and it can effortlessly simulate successive generations of descendants based on complex mating schemes by the aid of its modular design. Case studies are presented to demonstrate the flexibility of XSim Version 2 in simulating crossbreeding in animal and plant populations. Modern biotechnology, including double haploids and embryo transfer, can all be simultaneously integrated into the mating plans that drive the simulation. From a computing perspective, XSim Version 2 is implemented in Julia, which is a computer language that retains the readability of scripting languages (e.g. R and Python) without sacrificing much computational speed compared to compiled languages (e.g. C). This makes XSim Version 2 a simulation tool that is relatively easy for both champions and community members to maintain, modify, or extend in order to improve their breeding programs. Functions and operators are overloaded for a better user interface so they may concatenate, subset, summarize, and organize simulated populations at each breeding step. With the strong and foreseeable demands in the community, XSim Version 2 will serve as a modern simulator bridging the gaps between theories and experiments with its flexibility, extensibility, and friendly interface.

Relative Precision of the Sibship and LD Methods for Estimating Effective Population Size With Genomics-Scale Datasets

Computer simulations were used to compare relative precision of 2 widely used single-sample methods for estimating effective population size (Ne)-the sibship method and the linkage disequilibrium (LD) method. Emphasis is on performance when thousands of gene loci are used, which now can easily be achieved even for nonmodel species. Results show that unless Ne is very small, if at least 500-2000 diallelic loci are used, precision of the LD method is higher than the maximum possible precision for the sibship method, which occurs when all sibling relationships have been correctly identified. Results also show that when precision is high for both methods, their estimates of Ne are highly and positively correlated, which limits additional gains in precision that might be obtained by combining information from the 2 estimators.

Intensified Use of Reproductive Technologies and Reduced Dimensions of Breeding Schemes Put Genetic Diversity at Risk in Dairy Cattle Breeds

In the management of dairy cattle breeds, two recent trends have arisen that pose potential threats to genetic diversity: the use of reproductive technologies (RT) and a reduction in the number of bulls in breeding schemes. The expected outcome of these changes, in terms of both genetic gain and genetic diversity, is not trivial to predict. Here, we simulated 15 breeding schemes similar to those carried out in large French dairy cattle breeds; breeding schemes differed with respect to their dimensions, the intensity of RT use, and the type of RT involved. We found that intensive use of RT resulted in improved genetic gain, but deteriorated genetic diversity. Specifically, a reduction in the interval between generations through the use of ovum pick-up and in vitro fertilization (OPU-IVF) resulted in a large increase in the inbreeding rate both per year and per generation, suggesting that OPU-IVF could have severe adverse effects on genetic diversity. To achieve a given level of genetic gain, the scenarios that best maintained genetic diversity were those with a higher number of sires/bulls and a medium intensity of RT use or those with a higher number of female donors to compensate for the increased intensity of RT.

Genomic Breed Composition of Selection Signatures in Brangus Beef Cattle

Cattle breeding routinely uses crossbreeding between subspecies (Bos taurus taurus and Bos taurus indicus) to form composite breeds, such as Brangus. These composite breeds provide an opportunity to identify recent selection signatures formed in the new population and evaluate the genomic composition of these regions of the genome. Using high-density genotyping, we first identified runs of homozygosity (ROH) and calculated genomic inbreeding. Then, we evaluated the genomic composition of the regions identified as selected (selective sweeps) using a chromosome painting approach. The genomic inbreeding increased at approximately 1% per generation after composite breed formation, showing the need of inbreeding control even in composite breeds. Three selected regions in Brangus were also identified as Angus selection signatures. Two regions (chromosomes 14 and 21) were identified as signatures of selection in Brangus and both founder breeds. Five of the 10 homozygous regions in Brangus were predominantly Angus in origin (probability >80%), and the other five regions had a mixed origin but always with Brahman contributing less than 50%. Therefore, genetic events, such as drift, selection, and complementarity, are likely shaping the genetic composition of founder breeds in specific genomic regions. Such findings highlight a variety of opportunities to better control the selection process and explore heterosis and complementarity at the genomic level in composite breeds.

Estimation of Linkage Disequilibrium and Effective Population Size in Three Italian Autochthonous Beef Breeds

The objective was to investigate the pattern of linkage disequilibrium (LD) in three local beef breeds, namely, Calvana (n = 174), Mucca Pisana (n = 270), and Pontremolese (n = 44). As a control group, samples of the Italian Limousin breed (n = 100) were used. All cattle were genotyped with the GeneSeek GGP-LDv4 33k SNP chip containing 30,111 SNPs. The genotype quality control for each breed was conducted separately, and SNPs with call rate < 0.95 and minor allele frequency (MAF) > 1% were used for the analysis. LD extent was estimated in PLINK v1.9 using the squared correlation between pairs of loci (r²) across autosomes. Moreover, r² values were used to calculate historical and contemporary effective population size (N_e) in each breed. Average r² was similar in Calvana and Mucca Pisana (~0.14) and higher in Pontremolese (0.17); Limousin presented the lowest LD extent (0.07). LD up to 0.11-0.15 was persistent in the local breeds up to 0.75 Mbp, while in Limousin, it showed a more rapid decay. Variation of different LD levels across autosomes was observed in all the breeds. The results demonstrated a rapid decrease in N_e across generations for local breeds, and the contemporary population size observed in the local breeds, ranging from 41.7 in Calvana to 17 in Pontremolese, underlined the demographic alarming situation.

Mapping Recombination Rate on the Autosomal Chromosomes Based on the Persistency of Linkage Disequilibrium Phase Among Autochthonous Beef Cattle Populations in Spain

In organisms with sexual reproduction, genetic diversity, and genome evolution are governed by meiotic recombination caused by crossing-over, which is known to vary within the genome. In this study, we propose a simple method to estimate the recombination rate that makes use of the persistency of linkage disequilibrium (LD) phase among closely related populations. The biological material comprised 171 triplets (sire/dam/offspring) from seven populations of autochthonous beef cattle in Spain (Asturiana de los Valles, Avileña-Negra Ibérica, Bruna dels Pirineus, Morucha, Pirenaica, Retinta, and Rubia Gallega), which were genotyped for 777,962 SNPs with the BovineHD BeadChip. After standard quality filtering, we reconstructed the haplotype phases in the parental individuals and calculated the LD by the correlation -r- between each pair of markers that had a genetic distance < 1 Mb. Subsequently, these correlations were used to calculate the persistency of LD phase between each pair of populations along the autosomal genome. Therefore, the distribution of the recombination rate along the genome can be inferred since the effect of the number of generations of divergence should be equivalent throughout the genome. In our study, the recombination rate was highest in the largest chromosomes and at the distal portion of the chromosomes. In addition, the persistency of LD phase was highly heterogeneous throughout the genome, with a ratio of 25.4 times between the estimates of the recombination rates from the genomic regions that had the highest (BTA18-7.1 Mb) and the lowest (BTA12-42.4 Mb) estimates. Finally, an overrepresentation enrichment analysis (ORA) showed differences in the enriched gene ontology (GO) terms between the genes located in the genomic regions with estimates of the recombination rate over (or below) the 95^th (or 5^th) percentile throughout the autosomal genome.

Evidence for adaptive introgression of exons across a hybrid swarm in deer

Background

Secondary contact between closely related lineages can result in a variety of outcomes, including hybridization, depending upon the strength of reproductive barriers. By examining the extent to which different parts of the genome introgress, it is possible to infer the strength of selection and gain insight into the evolutionary trajectory of lineages. Following secondary contact approximately 8000 years ago in the Pacific Northwest, mule deer (Odocoileus hemionus hemionus) and black-tailed deer (O. h. columbianus) formed a hybrid swarm along the Cascade mountain range despite substantial differences in body size (up to two times) and habitat preference. In this study, we examined genetic population structure, extent of introgression, and selection pressures in freely interbreeding populations of mule deer and black-tailed deer using mitochondrial DNA sequences, 9 microsatellite loci, and 95 SNPs from protein-coding genes.

Results

We observed bi-directional hybridization and classified approximately one third of the 172 individuals as hybrids, almost all of which were beyond the F1 generation. High genetic differentiation between black-tailed deer and mule deer at protein-coding genes suggests that there is positive divergent selection, though selection on these loci is relatively weak. Contrary to predictions, there was not greater selection on protein-coding genes thought to be associated with immune function and mate choice. Geographic cline analyses were consistent across genetic markers, suggesting long-term stability (over hundreds of generations), and indicated that the center of the hybrid swarm is 20-30 km to the east of the Cascades ridgeline, where there is a steep ecological transition from wet, forested habitat to dry, scrub habitat.

Conclusions

Our data are consistent with a genetic boundary between mule deer and black-tailed deer that is porous but maintained by many loci under weak selection having a substantial cumulative effect. The absence of clear reproductive barriers and the consistent centering of geographic clines at a sharp ecotone suggests that ecology is a driver of hybrid swarm dynamics. Adaptive introgression in this study (and others) promotes gene flow and provides valuable insight into selection strength on specific genes and the evolutionary trajectory of hybridizing taxa.

Electronic supplementary material

The online version of this article (10.1186/s12862-019-1497-x) contains supplementary material, which is available to authorized users.

Key Genetic Parameters for Population Management

Population management has the primary task of maximizing the long-term competitiveness of a breed. Breeds compete with each other for being able to supply consumer demands at low costs and also for funds from conservation programs. The competition for consumer preference is won by breeds with high genetic gain for total merit who maintained a sufficiently high genetic diversity, whereas the competition for funds is won by breeds with high conservation value. The conservation value of a breed could be improved by increasing its contribution to the gene pool of the species. This may include the recovery of its original genetic background and the maintenance of a high genetic diversity at native haplotype segments. The primary objective of a breeding program depends on the genetic state of the population and its intended usage. In this paper, we review the key genetic parameters that are relevant for population management, compare the methods for estimating them, derive the formulas for predicting their value at a future time, and clarify their usage in various types of breeding programs that differ in their main objectives. These key parameters are kinships, native kinships, breeding values, Mendelian sampling variances, native contributions, and mutational effects. Population management currently experiences a transition from using pedigree-based estimates to marker-based estimates, which improves the accuracies of these estimates and thereby increases response to selection. In addition, improved measures of the factors that determine the competitiveness of a breed and utilize auxiliary parameters, such as Mendelian sampling variances, mutational effects, and native kinships, enable to improve further upon historic recommendations for genetic population management.

Whole Genome Linkage Disequilibrium and Effective Population Size in a Coho Salmon (Oncorhynchus kisutch) Breeding Population Using a High-Density SNP Array

The estimation of linkage disequilibrium between molecular markers within a population is critical when establishing the minimum number of markers required for association studies, genomic selection, and inferring historical events influencing different populations. This work aimed to evaluate the extent and decay of linkage disequilibrium in a coho salmon breeding population using a high-density SNP array. Linkage disequilibrium was estimated between a total of 93,502 SNPs found in 64 individuals (33 dams and 31 sires) from the breeding population. The markers encompass all 30 coho salmon chromosomes and comprise 1,684.62 Mb of the genome. The average density of markers per chromosome ranged from 48.31 to 66 per 1 Mb. The minor allele frequency averaged 0.26 (with a range from 0.22 to 0.27). The overall average linkage disequilibrium among SNPs pairs measured as r² was 0.10. The Average r² value decreased with increasing physical distance, with values ranging from 0.21 to 0.07 at a distance lower than 1 kb and up to 10 Mb, respectively. An r² threshold of 0.2 was reached at distance of approximately 40 Kb. Chromosomes Okis05, Okis15 and Okis28 showed high levels of linkage disequilibrium (>0.20 at distances lower than 1 Mb). Average r² values were lower than 0.15 for all chromosomes at distances greater than 4 Mb. An effective population size of 43 was estimated for the population 10 generations ago, and 325, for 139 generations ago. Based on the effective number of chromosome segments, we suggest that at least 74,000 SNPs would be necessary for an association mapping study and genomic predictions. Therefore, the SNP panel used allowed us to capture high-resolution information in the farmed coho salmon population. Furthermore, based on the contemporary N_e, a new mate allocation strategy is suggested to increase the effective population size.

Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition

Background

The power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. Milk fatty acid (FA) traits are scarcely recorded due to expensive and time-consuming analytical techniques. Combining multi-population datasets can enhance the power of GWAS enabling detection of genomic region explaining medium to low proportions of the genetic variation. GWAS often detect broader genomic regions containing several positional candidate genes making it difficult to untangle the causative candidates. Post-GWAS analyses with data on pathways, ontology and tissue-specific gene expression status might allow prioritization among positional candidate genes.

Results

Multi-population GWAS for 16 FA traits quantified using gas chromatography (GC) in sample populations of the Chinese, Danish and Dutch Holstein with high-density (HD) genotypes detects 56 genomic regions significantly associated to at least one of the studied FAs; some of which have not been previously reported. Pathways and gene ontology (GO) analyses suggest promising candidate genes on the novel regions including OSBPL6 and AGPS on Bos taurus autosome (BTA) 2, PRLH on BTA 3, SLC51B on BTA 10, ABCG5/8 on BTA 11 and ALG5 on BTA 12. Novel genes in previously known regions, such as FABP4 on BTA 14, APOA1/5/7 on BTA 15 and MGST2 on BTA 17, are also linked to important FA metabolic processes.

Conclusion

Integration of multi-population GWAS and enrichment analyses enabled detection of several novel genomic regions, explaining relatively smaller fractions of the genetic variation, and revealed highly likely candidate genes underlying the effects. Detection of such regions and candidate genes will be crucial in understanding the complex genetic control of FA metabolism. The findings can also be used to augment genomic prediction models with regions collectively capturing most of the genetic variation in the milk FA traits.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5573-9) contains supplementary material, which is available to authorized users.

High-resolution population structure and runs of homozygosity reveal the genetic architecture of complex traits in the Lipizzan horse

BACKGROUND

The sample ascertainment bias due to complex population structures remains a major challenge in genome-wide investigations of complex traits. In this study we derived the high-resolution population structure and levels of autozygosity of 377 Lipizzan horses originating from five different European stud farms utilizing the SNP genotype information of the high density 700 k Affymetrix Axiom™ Equine genotyping array. Scanning the genome for overlapping runs of homozygosity (ROH) shared by more than 50% of horses, we identified homozygous regions (ROH islands) in order to investigate the gene content of those candidate regions by gene ontology and enrichment analyses.

RESULTS

The high-resolution population network approach revealed well-defined substructures according to the origin of the horses (Austria, Slovakia, Croatia and Hungary). The highest mean genome coverage of ROH (SROH) was identified in the Austrian (SROH = 342.9), followed by Croatian (SROH = 214.7), Slovakian (SROH = 205.1) and Hungarian (SROH = 171.5) subpopulations. ROH island analysis revealed five common islands on ECA11 and ECA14, hereby confirming a closer genetic relationship between the Hungarian and Croatian as well as between the Austrian and Slovakian samples. Private islands were detected for the Hungarian and the Austrian Lipizzan subpopulations. All subpopulations shared a homozygous region on ECA11, nearly identical in position and length containing among other genes the homeobox-B cluster, which was also significantly (p < 0.001) highlighted by enrichment analysis. Gene ontology terms were mostly related to biological processes involved in embryonic morphogenesis and anterior/posterior specification. Around the STX17 gene (causative for greying), we identified a ROH island harbouring the genes NR4A3, STX17, ERP44 and INVS. Within further islands on ECA14, ECA16 and ECA20 we detected the genes SPRY4, NDFIP1, IMPDH2, HSP90AB1, whereas SPRY4 and HSP90AB1 are involved in melanoma metastasis and survival rate of melanoma patients in humans.

CONCLUSIONS

We demonstrated that the assessment of high-resolution population structures within one single breed supports the downstream genetic analyses (e.g. the identification of ROH islands). By means of ROH island analyses, we identified the genes SPRY4, NDFIP1, IMPDH2, HSP90AB1, which might play an important role for further studies on equine melanoma. Furthermore, our results highlighted the impact of the homeobox-A and B cluster involved in morphogenesis of Lipizzan horses.

Evaluation of fecal samples as a valid source of DNA by comparing paired blood and fecal samples from American bison (Bison bison)

Background

The collection and analysis of fecal DNA is a common practice, especially when dealing with wildlife species that are difficult to track or capture. While fecal DNA is known to be lower quality than traditional sources of DNA, such as blood or other tissues, few investigations have verified fecal samples as a valid source of DNA by directly comparing the results to high quality DNA samples from the same individuals. Our goal was to compare DNA from fecal and blood samples from the same 50 American plains bison (Bison bison) from Yellowstone National Park, analyze 35 short tandem repeat (STR) loci for genotyping efficiency, and compare heterozygosity estimates.

Results

We discovered that some of the fecal-derived genotypes obtained were significantly different from the blood-derived genotypes from the same bison. We also found that fecal-derived DNA samples often underestimated heterozygosity values, in some cases by over 20%.

Conclusions

These findings highlight a potential shortcoming inherent in previous wildlife studies that relied solely on a multi-tube approach, using exclusively low quality fecal DNA samples with no quality control to account for false alleles and allelic dropout. Herein, we present a rigorous marker selection protocol that is applicable for a wide range of species and report a set of 15 STR markers for use in future bison studies that yielded consistent results from both fecal and blood-derived DNA.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0722-3) contains supplementary material, which is available to authorized users.

Population Genomic Structure and Genome-Wide Linkage Disequilibrium in Farmed Atlantic Salmon (Salmo salar L.) Using Dense SNP Genotypes

Chilean Farmed Atlantic salmon (Salmo salar) populations were established with individuals of both European and North American origins. These populations are expected to be highly genetically differentiated due to evolutionary history and poor gene flow between ancestral populations from different continents. The extent and decay of linkage disequilibrium (LD) among single nucleotide polymorphism (SNP) impacts the implementation of genome-wide association studies and genomic selection and provides relevant information about demographic processes of fish populations. We assessed the population structure and characterized the extent and decay of LD in three Chilean commercial populations of Atlantic salmon with North American (NAM), Scottish (SCO), and Norwegian (NOR) origin. A total of 123 animals were genotyped using a 159 K SNP Axiom® myDesignTM Genotyping Array. A total of 32 K SNP markers, representing the common SNPs along the three populations after quality control were used. The principal component analysis explained 78.9% of the genetic diversity between populations, clearly discriminating between populations of North American and European origin, and also between European populations. NAM had the lowest effective population size, followed by SCO and NOR. Large differences in the LD decay were observed between populations of North American and European origin. An r 2 threshold of 0.2 was estimated for marker pairs separated by 7,800, 64, and 50 kb in the NAM, SCO, and NOR populations, respectively. In this study we show that this SNP panel can be used to detect association between markers and traits of interests and also to capture high-resolution information for genome-enabled predictions. Also, we suggest the feasibility to achieve similar prediction accuracies using a smaller SNP data set for the NAM population, compared with samples with European origin which would need a higher density SNP array.

Genetic mechanisms underlying spermatic and testicular traits within and among cattle breeds: systematic review and prioritization of GWAS results

Reduced bull fertility imposes economic losses in bovine herds. Specifically, testicular and spermatic traits are important indicators of reproductive efficiency. Several genome-wide association studies (GWAS) have identified genomic regions associated with these fertility traits. The aims of this study were as follows: 1) to perform a systematic review of GWAS results for spermatic and testicular traits in cattle and 2) to identify key functional candidate genes for these traits. The identification of functional candidate genes was performed using a systems biology approach, where genes shared between traits and studies were evaluated by a guilt by association gene prioritization (GUILDify and ToppGene software) in order to identify the best functional candidates. These candidate genes were integrated and analyzed in order to identify overlapping patterns among traits and breeds. Results showed that GWAS for testicular-related traits have been developed for beef breeds only, whereas the majority of GWAS for spermatic-related traits were conducted using dairy breeds. When comparing traits measured within the same study, the highest number of genes shared between different traits was observed, indicating a high impact of the population genetic structure and environmental effects. Several chromosomal regions were enriched for functional candidate genes associated with fertility traits. Moreover, multiple functional candidate genes were enriched for markers in a species-specific basis, taurine (Bos taurus) or indicine (Bos indicus). For the different candidate regions identified in the GWAS in the literature, functional candidate genes were detected as follows: B. Taurus chromosome X (BTX) (TEX11, IRAK, CDK16, ATP7A, ATRX, HDAC6, FMR1, L1CAM, MECP2, etc.), BTA17 (TRPV4 and DYNLL1), and BTA14 (MOS, FABP5, ZFPM2). These genes are responsible for regulating important metabolic pathways or biological processes associated with fertility, such as progression of spermatogenesis, control of ciliary activity, development of Sertoli cells, DNA integrity in spermatozoa, and homeostasis of testicular cells. This study represents the first systematic review on male fertility traits in cattle using a system biology approach to identify key candidate genes for these traits.

Karyomapping for simultaneous genomic evaluation and aneuploidy screening of preimplantation bovine embryos: The first live-born calves

In cattle breeding, the development of genomic selection strategies based on single nucleotide polymorphism (SNP) interrogation has led to improved rates of genetic gain. Additionally, the application of genomic selection to in-vitro produced (IVP) embryos is expected to bring further benefits thanks to the ability to test a greater number of individuals before establishing a pregnancy and to ensure only carriers of desirable traits are born. However, aneuploidy, a leading cause of developmental arrest, is known to be common in IVP embryos. Karyomapping is a comprehensive screening test based on SNP typing that can be used for simultaneous genomic selection and aneuploidy detection, offering the potential to maximize pregnancy rates. Moreover, Karyomapping can be used to characterize the frequency and parental origin of aneuploidy in bovine IVP embryos, which have remained underexplored to date. Here, we report the use of Karyomapping to characterize the frequency and parental origin of aneuploidy in IVP bovine embryos in order to establish an estimate of total aneuploidy rates in each parental germline. We report an estimate of genome wide recombination rate in cattle and demonstrate, for the first time, a proof of principle for the application of Karyomapping to cattle breeding, with the birth of five calves after screening. This combined genomic selection and aneuploidy screening approach was highly reliable, with calves showing 98% concordance with their respective embryo biopsies for SNP typing and 100% concordance with their respective biopsies for aneuploidy screening. This approach has the potential to simultaneously improve pregnancy rates following embryo transfer and the rate of genetic gain in cattle breeding, and is applicable to basic research to investigate meiosis and aneuploidy.

Genome-Wide Characterization of Selection Signatures and Runs of Homozygosity in Ugandan Goat Breeds

Both natural and artificial selection are among the main driving forces shaping genetic variation across the genome of livestock species. Selection typically leaves signatures in the genome, which are often characterized by high genetic differentiation across breeds and/or a strong reduction in genetic diversity in regions associated with traits under intense selection pressure. In this study, we evaluated selection signatures and genomic inbreeding coefficients, FROH, based on runs of homozygosity (ROH), in six Ugandan goat breeds: Boer (n = 13), and the indigenous breeds Karamojong (n = 15), Kigezi (n = 29), Mubende (n = 29), Small East African (n = 29), and Sebei (n = 29). After genotyping quality control, 45,294 autosomal single nucleotide polymorphisms (SNPs) remained for further analyses. A total of 394 and 6 breed-specific putative selection signatures were identified across all breeds, based on marker-specific fixation index (FST-values) and haplotype differentiation (hapFLK), respectively. These regions were enriched with genes involved in signaling pathways associated directly or indirectly with environmental adaptation, such as immune response (e.g., IL10RB and IL23A), growth and fatty acid composition (e.g., FGF9 and IGF1), and thermo-tolerance (e.g., MTOR and MAPK3). The study revealed little overlap between breeds in genomic regions under selection and generally did not display the typical classic selection signatures as expected due to the complex nature of the traits. In the Boer breed, candidate genes associated with production traits, such as body size and growth (e.g., GJB2 and GJA3) were also identified. Furthermore, analysis of ROH in indigenous goat breeds showed very low levels of genomic inbreeding (with the mean FROH per breed ranging from 0.8% to 2.4%), as compared to higher inbreeding in Boer (mean FROH = 13.8%). Short ROH were more frequent than long ROH, except in Karamojong, providing insight in the developmental history of these goat breeds. This study provides insights into the effects of long-term selection in Boer and indigenous Ugandan goat breeds, which are relevant for implementation of breeding programs and conservation of genetic resources, as well as their sustainable use and management.

Meta-analysis of chromosome-scale crossover rate variation in eukaryotes and its significance to evolutionary genomics

Understanding the distribution of crossovers along chromosomes is crucial to evolutionary genomics because the crossover rate determines how strongly a genome region is influenced by natural selection on linked sites. Nevertheless, generalities in the chromosome-scale distribution of crossovers have not been investigated formally. We fill this gap by synthesizing joint information on genetic and physical maps across 62 animal, plant and fungal species. Our quantitative analysis reveals a strong and taxonomically widespread reduction of the crossover rate in the centre of chromosomes relative to their peripheries. We demonstrate that this pattern is poorly explained by the position of the centromere, but find that the magnitude of the relative reduction in the crossover rate in chromosome centres increases with chromosome length. That is, long chromosomes often display a dramatically low crossover rate in their centre, whereas short chromosomes exhibit a relatively homogeneous crossover rate. This observation is compatible with a model in which crossover is initiated from the chromosome tips, an idea with preliminary support from mechanistic investigations of meiotic recombination. Consequently, we show that organisms achieve a higher genome-wide crossover rate by evolving smaller chromosomes. Summarizing theory and providing empirical examples, we finally highlight that taxonomically widespread and systematic heterogeneity in crossover rate along chromosomes generates predictable broad-scale trends in genetic diversity and population differentiation by modifying the impact of natural selection among regions within a genome. We conclude by emphasizing that chromosome-scale heterogeneity in crossover rate should urgently be incorporated into analytical tools in evolutionary genomics, and in the interpretation of resulting patterns.

The effect of using cow genomic information on accuracy and bias of genomic breeding values in a simulated Holstein dairy cattle population

Using cow data in the training population is attractive as a way to mitigate bias due to highly selected training bulls and to implement genomic selection for countries with no or limited proven bull data. However, one potential issue with cow data is a bias due to the preferential treatment. The objectives of this study were to (1) investigate the effect of including cow genotype and phenotype data into the training population on accuracy and bias of genomic predictions and (2) assess the effect of preferential treatment for different proportions of elite cows. First, a 4-pathway Holstein dairy cattle population was simulated for 2 traits with low (0.05) and moderate (0.3) heritability. Then different numbers of cows (0, 2,500, 5,000, 10,000, 15,000, or 20,000) were randomly selected and added to the training group composed of different numbers of top bulls (0, 2,500, 5,000, 10,000, or 15,000). Reliability levels of de-regressed estimated breeding values for training cows and bulls were 30 and 75% for traits with low heritability and were 60 and 90% for traits with moderate heritability, respectively. Preferential treatment was simulated by introducing upward bias equal to 35% of phenotypic variance to 5, 10, and 20% of elite bull dams in each scenario. Two different validation data sets were considered: (1) all animals in the last generation of both elite and commercial tiers (n = 42,000) and (2) only animals in the last generation of the elite tier (n = 12,000). Adding cow data into the training population led to an increase in accuracy (r) and decrease in bias of genomic predictions in all considered scenarios without preferential treatment. The gain in r was higher for the low heritable trait (from 0.004 to 0.166 r points) compared with the moderate heritable trait (from 0.004 to 0.116 r points). The gain in accuracy in scenarios with a lower number of training bulls was relatively higher (from 0.093 to 0.166 r points) than with a higher number of training bulls (from 0.004 to 0.09 r points). In this study, as expected, the bull-only reference population resulted in higher accuracy compared with the cow-only reference population of the same size. However, the cow reference population might be an option for countries with a small-scale progeny testing scheme or for minor breeds in large counties, and for traits measured only on a small fraction of the population. The inclusion of preferential treatment to 5 to 20% of the elite cows led to an adverse effect on both accuracy and bias of predictions. When preferential treatment was present, random selection of cows did not reduce the effect of preferential treatment.

The red deer Cervus elaphus genome CerEla1.0: sequencing, annotating, genes, and chromosomes

We present here the de novo genome assembly CerEla1.0 for the red deer, Cervus elaphus, an emblematic member of the natural megafauna of the Northern Hemisphere. Humans spread the species in the South. Today, the red deer is also a farm-bred animal and is becoming a model animal in biomedical and population studies. Stag DNA was sequenced at 74× coverage by Illumina technology. The ALLPATHS-LG assembly of the reads resulted in 34.7 × 10³ scaffolds, 26.1 × 10³ of which were utilized in Cer.Ela1.0. The assembly spans 3.4 Gbp. For building the red deer pseudochromosomes, a pre-established genetic map was used for main anchor points. A nearly complete co-linearity was found between the mapmarker sequences of the deer genetic map and the order and orientation of the orthologous sequences in the syntenic bovine regions. Syntenies were also conserved at the in-scaffold level. The cM distances corresponded to 1.34 Mbp uniformly along the deer genome. Chromosomal rearrangements between deer and cattle were demonstrated. 2.8 × 10⁶ SNPs, 365 × 10³ indels and 19368 protein-coding genes were identified in CerEla1.0, along with positions for centromerons. CerEla1.0 demonstrates the utilization of dual references, i.e., when a target genome (here C. elaphus) already has a pre-established genetic map, and is combined with the well-established whole genome sequence of a closely related species (here Bos taurus). Genome-wide association studies (GWAS) that CerEla1.0 (NCBI, MKHE00000000) could serve for are discussed.

Fixed-length haplotypes can improve genomic prediction accuracy in an admixed dairy cattle population

Background

Fitting covariates representing the number of haplotype alleles rather than single nucleotide polymorphism (SNP) alleles may increase genomic prediction accuracy if linkage disequilibrium between quantitative trait loci and SNPs is inadequate. The objectives of this study were to evaluate the accuracy, bias and computation time of Bayesian genomic prediction methods that fit fixed-length haplotypes or SNPs. Genotypes at 37,740 SNPs that were common to Illumina BovineSNP50 and high-density panels were phased for ~58,000 New Zealand dairy cattle. Females born before 1 June 2008 were used for training, and genomic predictions for milk fat yield (n = 24,823), liveweight (n = 13,283) and somatic cell score (n = 24,864) were validated within breed (predominantly Holstein–Friesian, predominantly Jersey, or admixed KiwiCross) in later-born females. Covariates for haplotype alleles of five lengths (125, 250, 500 kb, 1 or 2 Mb) were generated and rare haplotypes were removed at four thresholds (1, 2, 5 or 10%), resulting in 20 scenarios tested. Genomic predictions fitting covariates for either SNPs or haplotypes were calculated by using BayesA, BayesB or BayesN. This is the first study to quantify the accuracy of genomic prediction using haplotypes across the whole genome in an admixed population.

Results

A correlation of 0.349 ± 0.016 between yield deviation and genomic breeding values was obtained for milk fat yield in Holstein–Friesians using BayesA fitting covariates. Genomic predictions were more accurate with short haplotypes than with SNPs but less accurate with longer haplotypes than with SNPs. Fitting only the most frequent haplotype alleles reduced computation time with little decrease in prediction accuracy for short haplotypes. Trends were similar for all traits and breeds and there was little difference between Bayesian methods.

Conclusions

Fitting covariates for haplotype alleles rather than SNPs can increase prediction accuracy, although it decreased drastically for long (>500 kb) haplotypes. In this population, fitting 250 kb haplotypes with a 1% frequency threshold resulted in the highest genomic prediction accuracy and fitting 125 kb haplotypes with a 10% frequency threshold improved genomic prediction accuracy with comparable computation time to fitting SNPs. This increased accuracy is likely to increase genetic gain by changing the ranking of selection candidates.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-017-0329-y) contains supplementary material, which is available to authorized users.

Linkage disequilibrium, persistence of phase, and effective population size in Spanish local beef cattle breeds assessed through a high-density single nucleotide polymorphism chip

Linkage disequilibrium (LD) and persistence of phase are fundamental approaches for exploring the genetic basis of economically important traits in cattle, including the identification of QTL for genomic selection and the estimation of effective population size () to determine the size of the training populations. In this study, we have used the Illumina BovineHD chip in 168 trios of 7 Spanish beef cattle breeds to obtain an overview of the magnitude of LD and the persistence of LD phase through the physical distance between markers. Also, we estimated the time of divergence based on the persistence of the LD phase and calculated past from LD estimates using different alternatives to define the recombination rate. Estimates of average (as a measure of LD) for adjacent markers were close to 0.52 in the 7 breeds and decreased with the distance between markers, although in long distances, some LD still remained (0.07 and 0.05 for markers 200 kb and 1 Mb apart, respectively). A panel with a lower boundary of 38,000 SNP would be necessary to launch a successful within-breed genomic selection program. Persistence of phase, measured as the pairwise correlations between estimates of in 2 breeds at short distances (10 kb), was in the 0.89 to 0.94 range and decreased from 0.33 to 0.52 to a range of 0.01 to 0.08 when marker distance increased from 200 kb to 1 Mb, respectively. The magnitude of the persistence of phase between the Spanish beef breeds was similar to those found in dairy breeds. For across-breed genomic selection, the size of the SNP panels must be in the range of 50,000 to 83,000 SNP. Estimates of past showed values ranging from 26 to 31 for 1 generation ago in all breeds. The divergence among breeds occurred between 129 and 207 generations ago. The results of this study are relevant for the future implementation of within- and across-breed genomic selection programs in the Spanish beef cattle populations. Our results suggest that a reduced subset of the SNP panel would be enough to achieve an adequate precision of the genomic predictions.

Dimensionality of genomic information and performance of the Algorithm for Proven and Young for different livestock species

Background

A genomic relationship matrix (GRM) can be inverted efficiently with the Algorithm for Proven and Young (APY) through recursion on a small number of core animals. The number of core animals is theoretically linked to effective population size (N_e). In a simulation study, the optimal number of core animals was equal to the number of largest eigenvalues of GRM that explained 98% of its variation. The purpose of this study was to find the optimal number of core animals and estimate N_e for different species.

Methods

Datasets included phenotypes, pedigrees, and genotypes for populations of Holstein, Jersey, and Angus cattle, pigs, and broiler chickens. The number of genotyped animals varied from 15,000 for broiler chickens to 77,000 for Holsteins, and the number of single-nucleotide polymorphisms used for genomic prediction varied from 37,000 to 61,000. Eigenvalue decomposition of the GRM for each population determined numbers of largest eigenvalues corresponding to 90, 95, 98, and 99% of variation.

Results

The number of eigenvalues corresponding to 90% (98%) of variation was 4527 (14,026) for Holstein, 3325 (11,500) for Jersey, 3654 (10,605) for Angus, 1239 (4103) for pig, and 1655 (4171) for broiler chicken. Each trait in each species was analyzed using the APY inverse of the GRM with randomly selected core animals, and their number was equal to the number of largest eigenvalues. Realized accuracies peaked with the number of core animals corresponding to 98% of variation for Holstein and Jersey and closer to 99% for other breed/species. N_e was estimated based on comparisons of eigenvalue decomposition in a simulation study. Assuming a genome length of 30 Morgan, N_e was equal to 149 for Holsteins, 101 for Jerseys, 113 for Angus, 32 for pigs, and 44 for broilers.

Conclusions

Eigenvalue profiles of GRM for common species are similar to those in simulation studies although they are affected by number of genotyped animals and genotyping quality. For all investigated species, the APY required less than 15,000 core animals. Realized accuracies were equal or greater with the APY inverse than with regular inversion. Eigenvalue analysis of GRM can provide a realistic estimate of N_e.

Population genomic structure and linkage disequilibrium analysis of South African goat breeds using genome-wide SNP data

The sustainability of goat farming in marginal areas of southern Africa depends on local breeds that are adapted to specific agro-ecological conditions. Unimproved non-descript goats are the main genetic resources used for the development of commercial meat-type breeds of South Africa. Little is known about genetic diversity and the genetics of adaptation of these indigenous goat populations. This study investigated the genetic diversity, population structure and breed relations, linkage disequilibrium, effective population size and persistence of gametic phase in goat populations of South Africa. Three locally developed meat-type breeds of the Boer (n = 33), Savanna (n = 31), Kalahari Red (n = 40), a feral breed of Tankwa (n = 25) and unimproved non-descript village ecotypes (n = 110) from four goat-producing provinces of the Eastern Cape, KwaZulu-Natal, Limpopo and North West were assessed using the Illumina Goat 50K SNP Bead Chip assay. The proportion of SNPs with minor allele frequencies >0.05 ranged from 84.22% in the Tankwa to 97.58% in the Xhosa ecotype, with a mean of 0.32 ± 0.13 across populations. Principal components analysis, admixture and pairwise FST identified Tankwa as a genetically distinct population and supported clustering of the populations according to their historical origins. Genome-wide FST identified 101 markers potentially under positive selection in the Tankwa. Average linkage disequilibrium was highest in the Tankwa (r(2)  = 0.25 ± 0.26) and lowest in the village ecotypes (r(2) range = 0.09 ± 0.12 to 0.11 ± 0.14). We observed an effective population size of <150 for all populations 13 generations ago. The estimated correlations for all breed pairs were lower than 0.80 at marker distances >100 kb with the exception of those in Savanna and Tswana populations. This study highlights the high level of genetic diversity in South African indigenous goats as well as the utility of the genome-wide SNP marker panels in genetic studies of these populations.

A High-Resolution SNP Array-Based Linkage Map Anchors a New Domestic Cat Draft Genome Assembly and Provides Detailed Patterns of Recombination

High-resolution genetic and physical maps are invaluable tools for building accurate genome assemblies, and interpreting results of genome-wide association studies (GWAS). Previous genetic and physical maps anchored good quality draft assemblies of the domestic cat genome, enabling the discovery of numerous genes underlying hereditary disease and phenotypes of interest to the biomedical science and breeding communities. However, these maps lacked sufficient marker density to order thousands of shorter scaffolds in earlier assemblies, which instead relied heavily on comparative mapping with related species. A high-resolution map would aid in validating and ordering chromosome scaffolds from existing and new genome assemblies. Here, we describe a high-resolution genetic linkage map of the domestic cat genome based on genotyping 453 domestic cats from several multi-generational pedigrees on the Illumina 63K SNP array. The final maps include 58,055 SNP markers placed relative to 6637 markers with unique positions, distributed across all autosomes and the X chromosome. Our final sex-averaged maps span a total autosomal length of 4464 cM, the longest described linkage map for any mammal, confirming length estimates from a previous microsatellite-based map. The linkage map was used to order and orient the scaffolds from a substantially more contiguous domestic cat genome assembly (Felis catus v8.0), which incorporated ∼20 × coverage of Illumina fragment reads. The new genome assembly shows substantial improvements in contiguity, with a nearly fourfold increase in N50 scaffold size to 18 Mb. We use this map to report probable structural errors in previous maps and assemblies, and to describe features of the recombination landscape, including a massive (∼50 Mb) recombination desert (of virtually zero recombination) on the X chromosome that parallels a similar desert on the porcine X chromosome in both size and physical location.

Cattle Sex-Specific Recombination and Genetic Control from a Large Pedigree Analysis

Meiotic recombination is an essential biological process that generates genetic diversity and ensures proper segregation of chromosomes during meiosis. From a large USDA dairy cattle pedigree with over half a million genotyped animals, we extracted 186,927 three-generation families, identified over 8.5 million maternal and paternal recombination events, and constructed sex-specific recombination maps for 59,309 autosomal SNPs. The recombination map spans for 25.5 Morgans in males and 23.2 Morgans in females, for a total studied region of 2,516 Mb (986 kb/cM in males and 1,085 kb/cM in females). The male map is 10% longer than the female map and the sex difference is most pronounced in the subtelomeric regions. We identified 1,792 male and 1,885 female putative recombination hotspots, with 720 hotspots shared between sexes. These hotspots encompass 3% of the genome but account for 25% of the genome-wide recombination events in both sexes. During the past forty years, males showed a decreasing trend in recombination rate that coincided with the artificial selection for milk production. Sex-specific GWAS analyses identified PRDM9 and CPLX1 to have significant effects on genome-wide recombination rate in both sexes. Two novel loci, NEK9 and REC114, were associated with recombination rate in both sexes, whereas three loci, MSH4, SMC3 and CEP55, affected recombination rate in females only. Among the multiple PRDM9 paralogues on the bovine genome, our GWAS of recombination hotspot usage together with linkage analysis identified the PRDM9 paralogue on chromosome 1 to be associated in the U.S. Holstein data. Given the largest sample size ever reported for such studies, our results reveal new insights into the understanding of cattle and mammalian recombination.

Variation of Meiotic Recombination Rates and MLH1 Foci Distribution in Spermatocytes of Cattle, Sheep and Goats

Despite similar genome sizes, a great variability in recombination rates is observed in mammals. We used antibodies against SYCP3, MLH1 and centromeres to compare crossover frequency, position along chromosome arms and the effect of crossover interference in spermatocytes of 4 species from the family Bovidae (Bos taurus, 2n = 60, tribe Bovini; Ovis aries, 2n = 54, Capra hircus, 2n = 60 and Ammotragus lervia, 2n = 58, tribe Caprini). Despite significant individual variability, our results also show significant differences in both recombination rates and the total length of autosomal synaptonemal complexes (SC) between cattle (47.53 MLH1 foci/cell, 244.59 µm) and members of the tribe Caprini (61.83 MLH1 foci, 296.19 µm) which can be explained by the length of time that has passed since their evolutionary divergence. Sheep displayed the highest number of MLH1 foci per cell and recombination density, although they have a lower diploid chromosome number caused by centric fusions corresponding to cattle chromosomes 1;3, 2;8 and 5;11. However, the proportion of MLH1 foci observed on the fused chromosomes in sheep (26.14%) was significantly lower than on the orthologous acrocentrics in cattle (27.6%) and goats (28.2%), and their distribution along the SC arms differed significantly. The reduced recombination rate in metacentrics is probably caused by interference acting across the centromere.

A clone-free, single molecule map of the domestic cow (Bos taurus) genome

BACKGROUND

The cattle (Bos taurus) genome was originally selected for sequencing due to its economic importance and unique biology as a model organism for understanding other ruminants, or mammals. Currently, there are two cattle genome sequence assemblies (UMD3.1 and Btau4.6) from groups using dissimilar assembly algorithms, which were complemented by genetic and physical map resources. However, past comparisons between these assemblies revealed substantial differences. Consequently, such discordances have engendered ambiguities when using reference sequence data, impacting genomic studies in cattle and motivating construction of a new optical map resource--BtOM1.0--to guide comparisons and improvements to the current sequence builds. Accordingly, our comprehensive comparisons of BtOM1.0 against the UMD3.1 and Btau4.6 sequence builds tabulate large-to-immediate scale discordances requiring mediation.

RESULTS

The optical map, BtOM1.0, spanning the B. taurus genome (Hereford breed, L1 Dominette 01449) was assembled from an optical map dataset consisting of 2,973,315 (439 X; raw dataset size before assembly) single molecule optical maps (Rmaps; 1 Rmap = 1 restriction mapped DNA molecule) generated by the Optical Mapping System. The BamHI map spans 2,575.30 Mb and comprises 78 optical contigs assembled by a combination of iterative (using the reference sequence: UMD3.1) and de novo assembly techniques. BtOM1.0 is a high-resolution physical map featuring an average restriction fragment size of 8.91 Kb. Comparisons of BtOM1.0 vs. UMD3.1, or Btau4.6, revealed that Btau4.6 presented far more discordances (7,463) vs. UMD3.1 (4,754). Overall, we found that Btau4.6 presented almost double the number of discordances than UMD3.1 across most of the 6 categories of sequence vs. map discrepancies, which are: COMPLEX (misassembly), DELs (extraneous sequences), INSs (missing sequences), ITs (Inverted/Translocated sequences), ECs (extra restriction cuts) and MCs (missing restriction cuts).

CONCLUSION

Alignments of UMD3.1 and Btau4.6 to BtOM1.0 reveal discordances commensurate with previous reports, and affirm the NCBI's current designation of UMD3.1 sequence assembly as the "reference assembly" and the Btau4.6 as the "alternate assembly." The cattle genome optical map, BtOM1.0, when used as a comprehensive and largely independent guide, will greatly assist improvements to existing sequence builds, and later serve as an accurate physical scaffold for studies concerning the comparative genomics of cattle breeds.

Estimation of inbreeding using pedigree, 50k SNP chip genotypes and full sequence data in three cattle breeds

Background

Levels of inbreeding in cattle populations have increased in the past due to the use of a limited number of bulls for artificial insemination. High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. Various estimators based on different sources, e.g., pedigree or genomic data, have been used to estimate inbreeding coefficients in cattle populations. However, the comparative advantage of using full sequence data to assess inbreeding is unknown. We used pedigree and genomic data at different densities from 50k to full sequence variants to compare how different methods performed for the estimation of inbreeding levels in three different cattle breeds.

Results

Five different estimates for inbreeding were calculated and compared in this study: pedigree based inbreeding coefficient (F_PED); run of homozygosity (ROH)-based inbreeding coefficients (F_ROH); genomic relationship matrix (GRM)-based inbreeding coefficients (F_GRM); inbreeding coefficients based on excess of homozygosity (F_HOM) and correlation of uniting gametes (F_UNI). Estimates using ROH provided the direct estimated levels of autozygosity in the current populations and are free effects of allele frequencies and incomplete pedigrees which may increase in inaccuracy in estimation of inbreeding. The highest correlations were observed between F_ROH estimated from the full sequence variants and the F_ROH estimated from 50k SNP (single nucleotide polymorphism) genotypes. The estimator based on the correlation between uniting gametes (F_UNI) using full genome sequences was also strongly correlated with F_ROH detected from sequence data.

Conclusions

Estimates based on ROH directly reflected levels of homozygosity and were not influenced by allele frequencies, unlike the three other estimates evaluated (F_GRM, F_HOM and F_UNI), which depended on estimated allele frequencies. F_PED suffered from limited pedigree depth. Marker density affects ROH estimation. Detecting ROH based on 50k chip data was observed to give estimates similar to ROH from sequence data. In the absence of full sequence data ROH based on 50k can be used to access homozygosity levels in individuals. However, genotypes denser than 50k are required to accurately detect short ROH that are most likely identical by descent (IBD).

Genomic analysis for managing small and endangered populations: a case study in Tyrol Grey cattle

Analysis of genomic data is increasingly becoming part of the livestock industry. Therefore, the routine collection of genomic information would be an invaluable resource for effective management of breeding programs in small, endangered populations. The objective of the paper was to demonstrate how genomic data could be used to analyse (1) linkage disequlibrium (LD), LD decay and the effective population size (Ne_LD); (2) Inbreeding level and effective population size (Ne_ROH) based on runs of homozygosity (ROH); (3) Prediction of genomic breeding values (GEBV) using small within-breed and genomic information from other breeds. The Tyrol Grey population was used as an example, with the goal to highlight the potential of genomic analyses for small breeds. In addition to our own results we discuss additional use of genomics to assess relatedness, admixture proportions, and inheritance of harmful variants. The example data set consisted of 218 Tyrol Grey bull genotypes, which were all available AI bulls in the population. After standard quality control restrictions 34,581 SNPs remained for the analysis. A separate quality control was applied to determine ROH levels based on Illumina GenCall and Illumina GenTrain scores, resulting into 211 bulls and 33,604 SNPs. LD was computed as the squared correlation coefficient between SNPs within a 10 mega base pair (Mb) region. ROHs were derived based on regions covering at least 4, 8, and 16 Mb, suggesting that animals had common ancestors approximately 12, 6, and 3 generations ago, respectively. The corresponding mean inbreeding coefficients (F_ROH) were 4.0% for 4 Mb, 2.9% for 8 Mb and 1.6% for 16 Mb runs. With an average generation interval of 5.66 years, estimated Ne_ROH was 125 (Ne_{ROH>16 Mb}), 186 (Ne_{ROH>8 Mb}) and 370 (Ne_{ROH>4 Mb}) indicating strict avoidance of close inbreeding in the population. The LD was used as an alternative method to infer the population history and the Ne. The results show a continuous decrease in Ne_LD, to 780, 120, and 80 for 100, 10, and 5 generations ago, respectively. Genomic selection was developed for and is working well in large breeds. The same methodology was applied in Tyrol Grey cattle, using different reference populations. Contrary to the expectations, the accuracy of GEBVs with very small within breed reference populations were very high, between 0.13–0.91 and 0.12–0.63, when estimated breeding values and deregressed breeding values were used as pseudo-phenotypes, respectively. Subsequent analyses confirmed the high accuracies being a consequence of low reliabilities of pseudo-phenotypes in the validation set, thus being heavily influenced by parent averages. Multi-breed and across breed reference sets gave inconsistent and lower accuracies. Genomic information may have a crucial role in management of small breeds, even if its primary usage differs from that of large breeds. It allows to assess relatedness between individuals, trends in inbreeding and to take decisions accordingly. These decisions would be based on the real genome architecture, rather than conventional pedigree information, which can be missing or incomplete. We strongly suggest the routine genotyping of all individuals that belong to a small breed in order to facilitate the effective management of endangered livestock populations.

The effects of demography and long-term selection on the accuracy of genomic prediction with sequence data

The use of dense SNPs to predict the genetic value of an individual for a complex trait is often referred to as "genomic selection" in livestock and crops, but is also relevant to human genetics to predict, for example, complex genetic disease risk. The accuracy of prediction depends on the strength of linkage disequilibrium (LD) between SNPs and causal mutations. If sequence data were used instead of dense SNPs, accuracy should increase because causal mutations are present, but demographic history and long-term negative selection also influence accuracy. We therefore evaluated genomic prediction, using simulated sequence in two contrasting populations: one reducing from an ancestrally large effective population size (Ne) to a small one, with high LD common in domestic livestock, while the second had a large constant-sized Ne with low LD similar to that in some human or outbred plant populations. There were two scenarios in each population; causal variants were either neutral or under long-term negative selection. For large Ne, sequence data led to a 22% increase in accuracy relative to ∼600K SNP chip data with a Bayesian analysis and a more modest advantage with a BLUP analysis. This advantage increased when causal variants were influenced by negative selection, and accuracy persisted when 10 generations separated reference and validation populations. However, in the reducing Ne population, there was little advantage for sequence even with negative selection. This study demonstrates the joint influence of demography and selection on accuracy of prediction and improves our understanding of how best to exploit sequence for genomic prediction.

Accurate estimation of effective population size in the korean dairy cattle based on linkage disequilibrium corrected by genomic relationship matrix

Linkage disequilibrium between markers or genetic variants underlying interesting traits affects many genomic methodologies. In many genomic methodologies, the effective population size (Ne) is important to assess the genetic diversity of animal populations. In this study, dairy cattle were genotyped using the Illumina BovineHD Genotyping BeadChips for over 777,000 SNPs located across all autosomes, mitochondria and sex chromosomes, and 70,000 autosomal SNPs were selected randomly for the final analysis. We characterized more accurate linkage disequilibrium in a sample of 96 dairy cattle producing milk in Korea. Estimated linkage disequilibrium was relatively high between closely linked markers (>0.6 at 10 kb) and decreased with increasing distance. Using formulae that related the expected linkage disequilibrium to Ne, and assuming a constant actual population size, Ne was estimated to be approximately 122 in this population. Historical Ne, calculated assuming linear population growth, was suggestive of a rapid increase Ne over the past 10 generations, and increased slowly thereafter. Additionally, we corrected the genomic relationship structure per chromosome in calculating r(2) and estimated Ne. The observed Ne based on r(2) corrected by genomics relationship structure can be rationalized using current knowledge of the history of the dairy cattle breeds producing milk in Korea.

Adaptive admixture in the West African bovine hybrid zone: insight from the Borgou population

Understanding the adaptive response to environmental fluctuations represents a central issue in evolutionary biology. Population admixture between divergent ancestries has often been considered as an efficient short-term adaptation strategy. Cattle populations from the West African Bos taurus × Bos indicus hybrid zone represent a valuable resource to characterize the effect of such adaptive admixture at the genome level. We here provide a detailed assessment of the global and local genome ancestries of the Borgou breed, one of the most representative cattle of this hybrid zone. We analysed a large data set consisting of 38,100 SNPs genotyped on 203 Borgou and 591 individuals representative of all the different cattle ancestries. At the global genomic level, we show that Borgou is a stabilized admixed breed whose origin (c. 130 years ago) traces back to the great African rinderpest pandemic, several centuries after the last admixture events, the West African zebus originate from (c. 500 years ago). To identify footprints of adaptive admixture, we combined the identification of signatures of selection and the functional annotation of the underlying genes using systems biology tools. The detection of the SILV coat coloration gene likely under artificial selection may be viewed as a validation of our approach. Overall, our results suggest that the long-term presence of pathogens and the intermediate environmental conditions are the main acting selective pressures. Our analytical framework can be extended to other model or nonmodel species to understand the process that shapes the patterns of genetic variability in hybrid zones.

Recombination locations and rates in beef cattle assessed from parent-offspring pairs

BACKGROUND

Recombination events tend to occur in hotspots and vary in number among individuals. The presence of recombination influences the accuracy of haplotype phasing and the imputation of missing genotypes. Genes that influence genome-wide recombination rate have been discovered in mammals, yeast, and plants. Our aim was to investigate the influence of recombination on haplotype phasing, locate recombination hotspots, scan the genome for Quantitative Trait Loci (QTL) and identify candidate genes that influence recombination, and quantify the impact of recombination on the accuracy of genotype imputation in beef cattle.

METHODS

2775 Angus and 1485 Limousin parent-verified sire/offspring pairs were genotyped with the Illumina BovineSNP50 chip. Haplotype phasing was performed with DAGPHASE and BEAGLE using UMD3.1 assembly SNP (single nucleotide polymorphism) coordinates. Recombination events were detected by comparing the two reconstructed chromosomal haplotypes inherited by each offspring with those of their sires. Expected crossover probabilities were estimated assuming no interference and a binomial distribution for the frequency of crossovers. The BayesB approach for genome-wide association analysis implemented in the GenSel software was used to identify genomic regions harboring QTL with large effects on recombination. BEAGLE was used to impute Angus genotypes from a 7K subset to the 50K chip.

RESULTS

DAGPHASE was superior to BEAGLE in haplotype phasing, which indicates that linkage information from relatives can improve its accuracy. The estimated genetic length of the 29 bovine autosomes was 3097 cM, with a genome-wide recombination distance averaging 1.23 cM/Mb. 427 and 348 windows containing recombination hotspots were detected in Angus and Limousin, respectively, of which 166 were in common. Several significant SNPs and candidate genes, which influence genome-wide recombination were localized in QTL regions detected in the two breeds. High-recombination rates hinder the accuracy of haplotype phasing and genotype imputation.

CONCLUSIONS

Small population sizes, inadequate half-sib family sizes, recombination, gene conversion, genotyping errors, and map errors reduce the accuracy of haplotype phasing and genotype imputation. Candidate regions associated with recombination were identified in both breeds. Recombination analysis may improve the accuracy of haplotype phasing and genotype imputation from low- to high-density SNP panels.

A Genomic Approach for Distinguishing between Recent and Ancient Admixture as Applied to Cattle

Genomic data facilitate opportunities to track complex population histories of divergence and gene flow. We developed a metric, scaled block size (SBS), which uses the nonrecombined block size of introgressed regions of chromosomes to differentiate between recent and ancient types of admixture, and applied it to the reconstruction of admixture in cattle. Cattle are descendants of 2 independently domesticated lineages, taurine and indicine, which diverged more than 200 000 years ago. Several breeds have hybrid ancestry between these divergent lineages. Using 47 506 single-nucleotide polymorphisms, we analyzed the genomic architecture of the ancestry of 1369 individuals. We focused on 4 groups with admixed ancestry, including 2 anciently admixed African breeds (n = 58; n = 43), New World cattle of Spanish origin (n = 51), and known recent hybrids (n = 46). We estimated the ancestry of chromosomal regions for each individual and used the SBS metric to differentiate the timing of admixture among groups and among individuals within groups. By comparing SBS values of test individuals with standards with known recent hybrid ancestry, we were able to differentiate individuals of recent hybrid origin from other admixed cattle. We also estimated ancestry at the chromosomal scale. The X chromosome exhibits reduced indicine ancestry in recent hybrid, New World, and western African cattle, with virtually no evidence of indicine ancestry in New World cattle.

Acceleration of X-chromosome gene order evolution in the cattle lineage

The gene order on the X chromosome of eutherians is generally highly conserved, although an increase in the rate of rearrangement has been reported in the rodent lineage. Conservation of the X chromosome is thought to be caused by selection related to maintenance of dosage compensation. However, we herein reveal that the cattle (Btau4.0) lineage has experienced a strong increase in the rate of X-chromosome rearrangement, much stronger than that previously reported for rodents. We also show that this increase is not matched by a similar increase on the autosomes and cannot be explained by assembly errors. Furthermore, we compared the difference in two cattle genome assemblies: Btau4.0 and Btau6.0 (Bos taurus UMD3.1). The results showed a discrepancy between Btau4.0 and Btau6.0 cattle assembly version data, and we believe that Btau6.0 cattle assembly version data are not more reliable than Btau4.0. [BMB Reports 2013; 46(6): 310-315]