A primary assembly of a bovine haplotype block map based on a 15,036-single-nucleotide polymorphism panel genotyped in holstein-friesian cattle

Genome-wide mining of diversity and evolutionary signatures revealed selective hotspots in Indian Sahiwal cattle

The Sahiwal cattle breed is the best indigenous dairy cattle breed, and it plays a pivotal role in the Indian dairy industry. This is due to its exceptional milk-producing potential, adaptability to local tropical conditions, and its resilience to ticks and diseases. The study aimed to identify selective sweeps and estimate intrapopulation genetic diversity parameters in Sahiwal cattle using ddRAD sequencing-based genotyping data from 82 individuals. After applying filtering criteria, 78,193 high-quality SNPs remained for further analysis. The population exhibited an average minor allele frequency of 0.221 ± 0.119. Genetic diversity metrics, including observed (0.597 ± 0.196) and expected heterozygosity (0.433 ± 0.096), nucleotide diversity (0.327 ± 0.114), the proportion of polymorphic SNPs (0.726), and allelic richness (1.323 ± 0.134), indicated ample genomic diversity within the breed. Furthermore, an effective population size of 74 was observed in the most recent generation. The overall mean linkage disequilibrium (r2) for pairwise SNPs was 0.269 ± 0.057. Moreover, a greater proportion of short Runs of Homozygosity (ROH) segments were observed suggesting that there may be low levels of recent inbreeding in this population. The genomic inbreeding coefficients, computed using different inbreeding estimates (FHOM, FUNI, FROH, and FGROM), ranged from -0.0289 to 0.0725. Subsequently, we found 146 regions undergoing selective sweeps using five distinct statistical tests: Tajima's D, CLR, |iHS|, |iHH12|, and ROH. These regions, located in non-overlapping 500 kb windows, were mapped and revealed various protein-coding genes associated with enhanced immune systems and disease resistance (IFNL3, IRF8, BLK), as well as production traits (NRXN1, PLCE1, GHR). Notably, we identified interleukin 2 (IL2) on Chr17: 35217075-35223276 as a gene linked to tick resistance and uncovered a cluster of genes (HSPA8, UBASH3B, ADAMTS18, CRTAM) associated with heat stress. These findings indicate the evolutionary impact of natural and artificial selection on the environmental adaptation of the Sahiwal cattle population.

Multiple haplotype-based analyses provide genetic and evolutionary insights into tomato fruit weight and composition

Improving fruit quality traits such as metabolic composition remains a challenge for tomato breeders. To better understand the genetic architecture of these traits and decipher the demographic history of the loci controlling tomato quality traits, we applied an innovative approach using multiple haplotype-based analyses, aiming to test the potentials of haplotype based study in association and genomic prediction studies. We performed and compared haplotype vs SNP-based associations (hapQTL) with multi-locus mixed model (MLMM), focusing on tomato fruit weight and metabolite contents (i.e. sugars, organic acids and amino acids). Using a panel of 163 tomato accessions genotyped with 5995 SNPs, we detected a total of 784 haplotype blocks, with an average size of haplotype blocks ~58 kb. A total of 108 significant associations for 26 traits were detected thanks to Haplotype/SNP-based Bayes models. Haplotype-based Bayes model (97 associations) outperformed SNP-based Bayes model (50 associations) and MLMM (53 associations) in identifying marker-trait associations as well as in genomic prediction (especially for those traits with moderate to low heritability). To decipher the demographic history, we identified 24 positive selective sweeps using the integrated haplotype score (iHS). Most of the significant associations for tomato quality traits were located within selective sweeps (54.63% and 71.7% in hapQTL and MLMM models, respectively). Promising candidate genes were identified controlling tomato fruit weight and metabolite contents. We thus demonstrated the benefits of using haplotypes for evolutionary and genetic studies, providing novel insights into tomato quality improvement and breeding history.

Haplotype-Based Single-Step GWAS for Yearling Temperament in American Angus Cattle

Behavior is a complex trait and, therefore, understanding its genetic architecture is paramount for the development of effective breeding strategies. The objective of this study was to perform traditional and weighted single-step genome-wide association studies (ssGWAS and WssGWAS, respectively) for yearling temperament (YT) in North American Angus cattle using haplotypes. Approximately 266 K YT records and 70 K animals genotyped using a 50 K single nucleotide polymorphisms (SNP) panel were used. Linkage disequilibrium thresholds (LD) of 0.15, 0.50, and 0.80 were used to create the haploblocks, and the inclusion of non-LD-clustered SNPs (NCSNP) with the haplotypes in the genomic models was also evaluated. WssGWAS did not perform better than ssGWAS. Cattle YT was found to be a highly polygenic trait, with genes and quantitative trait loci (QTL) broadly distributed across the whole genome. Association studies using LD-based haplotypes should include NCSNPs and different LD thresholds to increase the likelihood of finding the relevant genomic regions affecting the trait of interest. The main candidate genes identified, i.e., ATXN10, ADAM10, VAX2, ATP6V1B1, CRISPLD1, CAPRIN1, FA2H, SPEF2, PLXNA1, and CACNA2D3, are involved in important biological processes and metabolic pathways related to behavioral traits, social interactions, and aggressiveness in cattle. Future studies should further investigate the role of these candidate genes.

Genetic Variability of Methane Production and Concentration Measured in the Breath of Polish Holstein-Friesian Cattle

The genetic architecture of methane (CH₄) production remains largely unknown. We aimed to estimate its heritability and to perform genome-wide association studies (GWAS) for the identification of candidate genes associated with two phenotypes: CH₄ in parts per million/day (CH₄ ppm/d) and CH₄ in grams/day (CH₄ g/d). We studied 483 Polish Holstein-Friesian cows kept on two commercial farms in Poland. Measurements of CH₄ and carbon dioxide (CO₂) concentrations exhaled by cows during milking were obtained using gas analyzers installed in the automated milking system on the farms. Genomic analyses were performed using a single-step BLUP approach. The percentage of genetic variance explained by SNPs was calculated for each SNP separately and then for the windows of neighbouring SNPs. The heritability of CH₄ ppm/d ranged from 0 to 0.14, with an average of 0.085. The heritability of CH₄ g/d ranged from 0.13 to 0.26, with an average of 0.22. The GWAS detected potential candidate SNPs on BTA 14 which explained ~0.9% of genetic variance for CH₄ ppm/d and ~1% of genetic variance for CH₄ g/d. All identified SNPs were located in the TRPS1 gene. We showed that methane traits are partially controlled by genes; however, the detected SNPs explained only a small part of genetic variation-implying that both CH₄ ppm/d and CH₄ g/d are highly polygenic traits.

Graduate Student Literature Review: Understanding the genetic mechanisms underlying mastitis

Mastitis is the costliest disease facing dairy producers today; consequently, it has been the subject of substantial research focus. Efforts have evolved from an initial focus on understanding the etiology of intramammary infections to the application of preventative measures, including attempts to breed cows that are resistant to infection. However, breeding for resistance to infection has proven difficult, given the complexity of the disease and the high expense associated with assembling high-quality genotypes and phenotypes. This review provides a brief background on mastitis; illustrates current understanding of the genetics influencing mastitis and the application of this knowledge; and discusses challenges and limitations in understanding these mechanisms and applying these findings to genetic improvement strategies.

Haplotype-Based Genome-Wide Association Study and Identification of Candidate Genes Associated with Carcass Traits in Hanwoo Cattle

Hanwoo, is the most popular native beef cattle in South Korea. Due to its extensive popularity, research is ongoing to enhance its carcass quality and marbling traits. In this study we conducted a haplotype-based genome-wide association study (GWAS) by constructing haplotype blocks by three methods: number of single nucleotide polymorphisms (SNPs) in a haplotype block (nsnp), length of genomic region in kb (Len) and linkage disequilibrium (LD). Significant haplotype blocks and genes associated with them were identified for carcass traits such as BFT (back fat thickness), EMA (eye Muscle area), CWT (carcass weight) and MS (marbling score). Gene-set enrichment analysis and functional annotation of genes in the significantly-associated loci revealed candidate genes, including PLCB1 and PLCB4 present on BTA13, coding for phospholipases, which might be important candidates for increasing fat deposition due to their role in lipid metabolism and adipogenesis. CEL (carboxyl ester lipase), a bile-salt activated lipase, responsible for lipid catabolic process was also identified within the significantly-associated haplotype block on BTA11. The results were validated in a different Hanwoo population. The genes and pathways identified in this study may serve as good candidates for improving carcass traits in Hanwoo cattle.

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.

Haplotype-based genome-wide association study identifies loci and candidate genes for milk yield in Holsteins

Since milk yield is a highly important economic trait in dairy cattle, the genome-wide association study (GWAS) is vital to explain the genetic architecture underlying milk yield and to perform marker-assisted selection (MAS). In this study, we adopted a haplotype-based empirical Bayesian GWAS to identify the loci and candidate genes for milk yield. A total of 1 092 Holstein cows were sequenced by using the genotyping by genome reducing and sequencing (GGRS) method. After filtering, 164 312 high-confidence SNPs and 13 476 haplotype blocks were identified to use for GWAS. The results indicated that 17 blocks were significantly associated with milk yield. We further identified the nearest gene of each haplotype block and annotated the genes with milk-associated quantitative trait locus (QTL) intervals and ingenuity pathway analysis (IPA) networks. Our analysis showed that four genes, DLGAP1, AP2B1, ITPR2 and THBS4, have relationships with milk yield, while another three, ARHGEF4, TDRD1 and KIF19, were inferred to have potential relationships. Additionally, a network derived from the IPA containing one inferred (ARHGEF4) and all four confirmed genes likely regulates milk yield. Our findings add to the understanding of identifying the causal genes underlying milk production traits and could guide follow up studies for further confirmation of the associated genes, pathways and biological networks.

Genome-wide scan for commons SNPs affecting bovine leukemia virus infection level in dairy cattle

BACKGROUND

Bovine leukemia virus (BLV) infection is omnipresent in dairy herds causing direct economic losses due to trade restrictions and lymphosarcoma-related deaths. Milk production drops and increase in the culling rate are also relevant and usually neglected. The BLV provirus persists throughout a lifetime and an inter-individual variation is observed in the level of infection (LI) in vivo. High LI is strongly correlated with disease progression and BLV transmission among herd mates. In a context of high prevalence, classical control strategies are economically prohibitive. Alternatively, host genomics studies aiming to dissect loci associated with LI are potentially useful tools for genetic selection programs tending to abrogate the viral spreading. The LI was measured through the proviral load (PVL) set-point and white blood cells (WBC) counts. The goals of this work were to gain insight into the contribution of SNPs (bovine 50KSNP panel) on LI variability and to identify genomics regions underlying this trait.

RESULTS

We quantified anti-p24 response and total leukocytes count in peripheral blood from 1800 cows and used these to select 800 individuals with extreme phenotypes in WBCs and PVL. Two case-control genomic association studies using linear mixed models (LMMs) considering population stratification were performed. The proportion of the variance captured by all QC-passed SNPs represented 0.63 (SE ± 0.14) of the phenotypic variance for PVL and 0.56 (SE ± 0.15) for WBCs. Overall, significant associations (Bonferroni's corrected -log10p > 5.94) were shared for both phenotypes by 24 SNPs within the Bovine MHC. Founder haplotypes were used to measure the linkage disequilibrium (LD) extent (r2 = 0.22 ± 0.27 at inter-SNP distance of 25-50 kb). The SNPs and LD blocks indicated genes potentially associated with LI in infected cows: i.e. relevant immune response related genes (DQA1, DRB3, BOLA-A, LTA, LTB, TNF, IER3, GRP111, CRISP1), several genes involved in cell cytoskeletal reorganization (CD2AP, PKHD1, FLOT1, TUBB5) and modelling of the extracellular matrix (TRAM2, TNXB). Host transcription factors (TFs) were also highlighted (TFAP2D; ABT1, GCM1, PRRC2A).

CONCLUSIONS

Data obtained represent a step forward to understand the biology of BLV-bovine interaction, and provide genetic information potentially applicable to selective breeding programs.

Estimation of linkage disequilibrium and analysis of genetic diversity in Korean chicken lines

The development of genetic markers for animal breeding is an effective strategy to reduce the time and cost required to improve economically important traits. To implement genomic selection in the multibreed chicken population of Korea, an understanding of the linkage disequilibrium (LD) status of the target population is essential. In this study, we performed population genetic analyses to investigate LD decay, the effective population size, and breed diversity using 600K high-density single nucleotide polymorphism genotypes of 189 native chickens in 14 lines (including Korean native chicken, imported and adapted purebred and commercial chickens). The results indicated that commercial native chickens have less calculated LD (average, r2 = 0.13-0.26) and purebred native chickens have more calculated LD (average, r2 = 0.24-0.37) across the entire genome. The effective population sizes of the examined lines showed patterns opposite to those of population LD. The phylogeny and admixture analyses showed that commercial and purebred chickens were well distinguished, except for Rhode Island Red (RIR) purebred lines of NC (NIAS_RIR_C) and ND (NIAS_RIR_D). These lines are difficult to distinguish clearly because they originated from the same respective breeds. The results of this study may provide important information for the development of genetic markers that can be used in breeding to improve the economic traits of native chickens.

Genetic parameters and genome-wide associations of twinning rate in a local breed, the Maremmana cattle

This study seeks to verify the feasibility of increasing twinning in a herd of the Italian autochtonous Maremmana breed. The data set included 1260 individuals born from 1963 to 2014, 527 males and 733 females, 402 of them calving at least once from 1983 through 2015. Breeding values for twinning were estimated by a single-trait linear animal model. However, since twinning is a dichotomous trait and the frequency of twins is far smaller than the frequency of single births, breeding values were also estimated by a single-trait animal threshold model. Heritability of twinning was 0.014±0.018 and 0.062±0.093 for the linear and the threshold models, respectively. Repeatability was 0.071±0.004 and 0.286± 0.012, respectively, for the two models. Genotyping with the Illumina BovineSNP54 BeadChip was performed for cows living on farm in 2012 (119 cows) and a genome-wide association analysis was performed on the corrected phenotype of all calving during the lifespan of each cow, using the GenABEL package in R and a three step GRAMMAR-GC approach. Genomic heritability, calculated from the genomic kinship matrix estimated through genomic marker data, was 0.29±0.021. The most significant detected single nucleotide polymorphisms (Hapmap22923-BTA-129564) was located in proximity of two genes, ARHGAP8 and TMEM200C, which might be potential functional candidates for twinning rate in cattle.

Genomic Selection in Dairy Cattle: The USDA Experience

Genomic selection has revolutionized dairy cattle breeding. Since 2000, assays have been developed to genotype large numbers of single-nucleotide polymorphisms (SNPs) at relatively low cost. The first commercial SNP genotyping chip was released with a set of 54,001 SNPs in December 2007. Over 15,000 genotypes were used to determine which SNPs should be used in genomic evaluation of US dairy cattle. Official USDA genomic evaluations were first released in January 2009 for Holsteins and Jerseys, in August 2009 for Brown Swiss, in April 2013 for Ayrshires, and in April 2016 for Guernseys. Producers have accepted genomic evaluations as accurate indications of a bull's eventual daughter-based evaluation. The integration of DNA marker technology and genomics into the traditional evaluation system has doubled the rate of genetic progress for traits of economic importance, decreased generation interval, increased selection accuracy, reduced previous costs of progeny testing, and allowed identification of recessive lethals.

Genomic scan for identifying candidate genes for paratuberculosis resistance in sheep

Breeding objectives relating to health, functional traits and welfare need to receive priority in the research programs and selection schemes, but very few reports are available on natural resistant genotypes in livestock, where some important diseases cause severe economic losses and pose serious zoonotic threats. In this study, diagnosis of paratuberculosis was performed on 759 adult sheep, from a single flock, with the serum antibody enzyme-linked immunosorbent assay; 100 sheep were selected among the extreme divergent animals for the S/P ratio obtained from the test, and were genotyped on the Illumina Ovine SNP50K BeadChip. A genome-wide scan was then performed on the individual marker genotypes, in the attempt to identify genomic regions associated with disease resistance in sheep. For each marker, the allelic substitution effect was calculated by regressing the S/P value on the number of copies of the reference allele. The position on the OARv3.1 Genome Assembly was searched for 32 markers, which showed a statistically significant allelic substitution effect (Raw P < 0.0006 and FDR P < 0.09). All markers were located within, or close to, annotated genes. Five of these genes, SEMA3, CD109, PCP4, PRDM2 and ITFG2 are referred in literature to play a role in either disease resistance or cell-mediated immune response.

Targeted Analysis Reveals an Important Role of JAK-STAT-SOCS Genes for Milk Production Traits in Australian Dairy Cattle

The Janus kinase and signal transducer and activator of transcription (JAK-STAT) pathway genes along with suppressors of cytokine signalling (SOCS) family genes play a crucial role in controlling cytokine signals in the mammary gland and thus mammary gland development. Mammary gene expression studies showed differential expression patterns for all the JAK-STAT pathway genes. Gene expression studies using qRT-PCR revealed differential expression of SOCS2, SOCS4, and SOCS5 genes across the lactation cycle in dairy cows. Using genotypes from 1,546 Australian Holstein-Friesian bulls, a statistical model for an association analysis based on SNPs within 500 kb of JAK-STAT pathway genes, and SOCS genes alone was constructed. The analysis suggested that these genes and pathways make a significant contribution to the Australian milk production traits. There were 24 SNPs close to SOCS1, SOCS3, SOCS5, SOCS7, and CISH genes that were significantly associated with Australian Profit Ranking (APR), Australian Selection Index (ASI), and protein yield (PY). This study supports the view that there may be some merit in choosing SNPs around functionally relevant genes for the selection and genetic improvement schemes for dairy production traits.

Genomic population structure and prevalence of copy number variations in South African Nguni cattle

Background

Copy number variations (CNVs) are modifications in DNA structure comprising of deletions, duplications, insertions and complex multi-site variants. Although CNVs are proven to be involved in a variety of phenotypic discrepancies, the full extent and consequence of CNVs is yet to be understood. To date, no such genomic characterization has been performed in indigenous South African Nguni cattle. Nguni cattle are recognized for their ability to sustain harsh environmental conditions while exhibiting enhanced resistance to disease and parasites and are thought to comprise of up to nine different ecotypes.

Methods

Illumina BovineSNP50 Beadchip data was utilized to investigate genomic population structure and the prevalence of CNVs in 492 South African Nguni cattle. PLINK, ADMIXTURE, R, gPLINK and Haploview software was utilized for quality control, population structure and haplotype block determination. PennCNV hidden Markov model identified CNVs and genes contained within and 10 Mb downstream from reported CNVs. PANTHER and Ensembl databases were subsequently utilized for gene annotation analyses.

Results

Population structure analyses on Nguni cattle revealed 5 sub-populations with a possible sub-structure evident at K equal to 8. Four hundred and thirty three CNVs that formed 334 CNVRs ranging from 30 kb to 1 Mb in size are reported. Only 231 of the 492 animals demonstrated CNVRs. Two hundred and eighty nine genes were observed within CNVRs identified. Of these 149, 28, 44, 2 and 14 genes were unique to sub-populations A, B, C, D and E respectively. Gene ontology analyses demonstrated a number of pathways to be represented by respective genes, including immune response, response to abiotic stress and biological regulation processess.

Conclusions

CNVs may explain part of the phenotypic diversity and the enhanced adaptation evident in Nguni cattle. Genes involved in a number of cellular components, biological processes and molecular functions are reported within CNVRs identified. The significance of such CNVRs and the possible effect thereof needs to be ascertained and may hold interesting insight into the functional and adaptive consequence of CNVs in cattle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2122-z) contains supplementary material, which is available to authorized users.

Linkage disequilibrium and haplotype block structure in a composite beef cattle breed

Background

The development of linkage disequilibrium (LD) maps and the characterization of haplotype block structure at the population level are useful parameters for guiding genome wide association (GWA) studies, and for understanding the nature of non-linear association between phenotypes and genes. The elucidation of haplotype block structure can reduce the information of several single nucleotide polymorphisms (SNP) into the information of a haplotype block, reducing the number of SNPs in a coherent way for consideration in GWA and genomic selection studies.

Results

The maximum average LD, measured by r² varied between 0.33 to 0.40 at a distance of < 2.5 kb, and the minimum average values of r² varied between 0.05 to 0.07 at distances ranging from 400 to 500 kb, clearly showing that the average r² reduced with the increase in SNP pair distances. The persistence of LD phase showed higher values at shorter genomic distances, decreasing with the increase in physical distance, varying from 0.96 at a distance of < 2.5 kb to 0.66 at a distance from 400 to 500 kb. A total of 78% of all SNPs were clustered into haplotype blocks, covering 1,57 Mb of the total autosomal genome size.

Conclusions

This study presented the first high density linkage disequilibrium map and haplotype block structure for a composite beef cattle population, and indicates that the high density SNP panel over 700 k can be used for genomic selection implementation and GWA studies for Canchim beef cattle.

Impact of whole-genome amplification on the reliability of pre-transfer cattle embryo breeding value estimates

Background

Genome-wide profiling of single-nucleotide polymorphisms is receiving increasing attention as a method of pre-implantation genetic diagnosis in humans and of commercial genotyping of pre-transfer embryos in cattle. However, the very small quantity of genomic DNA in biopsy material from early embryos poses daunting technical challenges. A reliable whole-genome amplification (WGA) procedure would greatly facilitate the procedure.

Results

Several PCR-based and non-PCR based WGA technologies, namely multiple displacement amplification, quasi-random primed library synthesis followed by PCR, ligation-mediated PCR, and single-primer isothermal amplification were tested in combination with different DNA extractions protocols for various quantities of genomic DNA inputs. The efficiency of each method was evaluated by comparing the genotypes obtained from 15 cultured cells (representative of an embryonic biopsy) to unamplified reference gDNA. The gDNA input, gDNA extraction method and amplification technology were all found to be critical for successful genome-wide genotyping. The selected WGA platform was then tested on embryo biopsies (n = 226), comparing their results to that of biopsies collected after birth. Although WGA inevitably leads to a random loss of information and to the introduction of erroneous genotypes, following genomic imputation the resulting genetic index of both sources of DNA were highly correlated (r = 0.99, P<0.001).

Conclusion

It is possible to generate high-quality DNA in sufficient quantities for successful genome-wide genotyping starting from an early embryo biopsy. However, imputation from parental and population genotypes is a requirement for completing and correcting genotypic data. Judicious selection of the WGA platform, careful handling of the samples and genomic imputation together, make it possible to perform extremely reliable genomic evaluations for pre-transfer embryos.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-889) contains supplementary material, which is available to authorized users.

Genetic characterization of a herd of the endangered Danish Jutland cattle

In this paper we present results from a genetic characterization of a herd of the Danish Jutland cattle breed named the Kortegaard herd (n = 135; 57 males and 78 females). The herd is genotyped on the Bovine HD BeadChip microarray with 697,548 evenly spaced SNP across the bovine genome. The aim of the study was to characterize the genetic profile of the Kortegaard herd, which has been closed for several generations, by quantifying the degree of genetic homogeneity within the herd and to compare its genetic profile to that of other cattle breeds. A total of 868 animals from the Angus, Belgian Blue, Charolais, Friesian, Hereford, Holstein, Holstein-Friesian crosses, Limousin, and Simmental breeds was used for genetic profile comparisons. The level of genetic variation within the breeds were quantified by the expected heterozygosity (H(E)), observed heterozygosity (H(O)), average minor allele frequency (MAF), the degree of polymorphism, and runs of homozygosity (ROH), which are contiguous lengths of homozygous genotypes of varying length. Interestingly, the Kortegaard herd had the lowest within-breed genetic variation (lowest H(E), H(O), and MAF), showed moderate levels of short ROH (<5 Mb), and had the highest mean long ROH (>5 Mb) compared to all the other breeds. This is possibly due to recent consanguineous matings, a strong founder effect, and a lack of gene flow from other herds and breeds. We further examined whether the observed genetic patterns in the Kortegaard herd can be used to design breeding strategies for the preservation of the genetic pool by focusing on a subset of SNP outside homozygote regions. By calculating the pairwise identical-by-state between all possible matings, we designed a breeding plan that maximized heterozygosity in the short term. The benefits and limitations of such a breeding strategy are discussed.

Genome-wide linkage disequilibrium in the Blonde d'Aquitaine cattle breed

We present here the first genome-wide characterization of linkage disequilibrium (LD) in the French Blonde d'Aquitaine (BLA) breed, a well-muscled breed renowned for producing high-yielding beef carcasses. To assess the pattern and extent of LD, we used a sample of 30 unrelated bulls and 36 923 single nucleotide polymorphisms (SNPs) covering all cattle autosomes. The squared correlation of the alleles at two loci (r(2) ) was used as a measure of LD. The analysis of adjacent marker pairs revealed that the level of LD decreases rapidly with physical distance between SNPs. Overall mean r(2) was 0.205 (±0.262). Strong LD (r(2)  > 0.8) and useful LD (measured as r(2 ) > 0.2) were observed within genomic regions of up to 720 and 724 kb, respectively. We analysed the genetic structure of the BLA population and found stratification. The observed genetic sub-structuring is consistent with the known recent demographic history that occurred during BLA breed formation. Our results indicate that LD mapping of phenotypic traits in the BLA population is feasible; however, because of this sub-structuring, special care is needed to reduce the likelihood of false-positive associations between marker loci and traits of interest.

On the way to functional agro biodiversity: coat colour gene variability in goats

Functional agro biodiversity defines the exploitation of biodiversity to provide ecosystem services, support sustainable agricultural production and benefit the regional and global environment and the public at large (ELN-FAB, 2009; www.eln_fab.eu). Tracking of animal products back to the breed of origin based on their genetic make-up undoubtedly falls in this category. The aim of this paper was to identify and validate a set of single nucleotide polymorphisms (SNPs) in goat coat colour genes, most of which have not been investigated before, to trace five goat populations of the Italian Alps and their product. Several regions of 28 genes influencing coat colour pathways were amplified in eight animals (two per breed). Sequence comparison revealed 48 SNPs and three INDEL (INsertion DELetion). No breed-specific alleles were detected; however, several SNPs showed an uneven frequency distribution between breeds. In BIO, the genotype frequency distribution of a non-synonymous SNP suggested a possible role of TYRP1 in brown eumelanic goat coat colour. A total of 29 independent SNPs in 20 genes were selected and used to allocate 159 minimally related goat samples using STRUCTURE 2.2 and GeneClass 2 software. STRUCTURE 2.2 assigns 99% of individuals to the correct breed considering the prior information on putative breed of origin for each sample and 81% using only the genotypic data. The three algorithms available in GeneClass 2 performed with nearly equal efficiency, with 86% and 87% correct allocations. All the methods yielded an average probability of assignment >0.92 and a specificity index >0.86. Despite their coat colour variability, individuals belonging to ORO were fully assigned, showing that, in the absence of a breed-specific allele tied to coat colour, the best assignment resulted for the most genetically distinct breed. The lowest rate of correct assignment was observed in Verzaschese (73%), not ascertained in the breed panel used in the SNP discovery phase.

Population parameters incorporated into genome-wide tagSNP selection

Single nucleotide polymorphisms (SNPs) are the most widespread source of variation in genomes. While the very large number of SNPs allows for a very precise description of genetic variation, it impedes data processing and significantly increases analysis time. Many of the SNPs located close to each other frequently carry the same or similar information. This problem can be solved by selecting the most informative SNPs (tagSNPs) using linkage disequilibrium information by identifying a set of tagSNPs representative for a chromosome fragment. The goal of this study is to check whether the genetic structure of a population, expressed by relationship and inbreeding coefficients, affects tagSNP selection. Six subsets of 450 bulls are selected out of the 1228 Polish Holstein-Friesian bulls genotyped by the Illumina BovineSNP50 Bead Chip. TagSNPs are selected for each of the subsets, as well as for the whole data set. The average reduction of the SNP number is 77.2% and is very similar in each sub-population. Differences in tagSNP selection between sub-populations are small. On average, 93.88% of the tagSNPs overlap between subsets. The study showed that differences in the genetic structure of the reference population have little influence on tagSNP selection.

Strategies and utility of imputed SNP genotypes for genomic analysis in dairy cattle

Background

We investigated strategies and factors affecting accuracy of imputing genotypes from lower-density SNP panels (Illumina 3K, 7K, Affymetrix 15K and 25K, and evenly spaced subsets) up to one medium (Illumina 50K) and one high-density (Illumina 800K) SNP panel. We also evaluated the utility of imputed genotypes on the accuracy of genomic selection using Australian Holstein-Friesian cattle data from 2727 and 845 animals genotyped with 50K and 800K SNP chip, respectively. Animals were divided into reference and test sets (genotyped with higher and lower density SNP panels, respectively) for evaluating the accuracies of imputation. For the accuracy of genomic selection, a comparison of direct genetic values (DGV) was made by dividing the data into training and validation sets under a range of imputation scenarios.

Results

Of the three methods compared for imputation, IMPUTE2 outperformed Beagle and fastPhase for almost all scenarios. Higher SNP densities in the test animals, larger reference sets and higher relatedness between test and reference animals increased the accuracy of imputation. 50K specific genotypes were imputed with moderate allelic error rates from 15K (2.85%) and 25K (2.75%) genotypes. Using IMPUTE2, SNP genotypes up to 800K were imputed with low allelic error rate (0.79% genome-wide) from 50K genotypes, and with moderate error rate from 3K (4.78%) and 7K (2.00%) genotypes. The error rate of imputing up to 800K from 3K or 7K was further reduced when an additional middle tier of 50K genotypes was incorporated in a 3-tiered framework. Accuracies of DGV for five production traits using imputed 50K genotypes were close to those obtained with the actual 50K genotypes and higher compared to using 3K or 7K genotypes. The loss in accuracy of DGV was small when most of the training animals also had imputed (50K) genotypes. Additional gains in DGV accuracies were small when SNP densities increased from 50K to imputed 800K.

Conclusion

Population-based genotype imputation can be used to predict and combine genotypes from different low, medium and high-density SNP chips with a high level of accuracy. Imputing genotypes from low-density SNP panels to at least 50K SNP density increases the accuracy of genomic selection.

Tracing cattle breeds with principal components analysis ancestry informative SNPs

The recent release of the Bovine HapMap dataset represents the most detailed survey of bovine genetic diversity to date, providing an important resource for the design and development of livestock production. We studied this dataset, comprising more than 30,000 Single Nucleotide Polymorphisms (SNPs) for 19 breeds (13 taurine, three zebu, and three hybrid breeds), seeking to identify small panels of genetic markers that can be used to trace the breed of unknown cattle samples. Taking advantage of the power of Principal Components Analysis and algorithms that we have recently described for the selection of Ancestry Informative Markers from genomewide datasets, we present a decision-tree which can be used to accurately infer the origin of individual cattle. In doing so, we present a thorough examination of population genetic structure in modern bovine breeds. Performing extensive cross-validation experiments, we demonstrate that 250-500 carefully selected SNPs suffice in order to achieve close to 100% prediction accuracy of individual ancestry, when this particular set of 19 breeds is considered. Our methods, coupled with the dense genotypic data that is becoming increasingly available, have the potential to become a valuable tool and have considerable impact in worldwide livestock production. They can be used to inform the design of studies of the genetic basis of economically important traits in cattle, as well as breeding programs and efforts to conserve biodiversity. Furthermore, the SNPs that we have identified can provide a reliable solution for the traceability of breed-specific branded products.

Mapping of a milk production quantitative trait locus to a 1.056 Mb region on bovine chromosome 5 in the Fleckvieh dual purpose cattle breed

BACKGROUND

In a previous study in the Fleckvieh dual purpose cattle breed, we mapped a quantitative trait locus (QTL) affecting milk yield (MY1), milk protein yield (PY1) and milk fat yield (FY1) during first lactation to the distal part of bovine chromosome 5 (BTA5), but the confidence interval was too large for positional cloning of the causal gene. Our objective here was to refine the position of this QTL and to define the candidate region for high-throughput sequencing.

METHODS

In addition to those previously studied, new Fleckvieh families were genotyped, in order to increase the number of recombination events. Twelve new microsatellites and 240 SNP markers covering the most likely QTL region on BTA5 were analysed. Based on haplotype analysis performed in this complex pedigree, families segregating for the low frequency allele of this QTL (minor allele) were selected. Single- and multiple-QTL analyses using combined linkage and linkage disequilibrium methods were performed.

RESULTS

Single nucleotide polymorphism haplotype analyses on representative family sires and their ancestors revealed that the haplotype carrying the minor QTL allele is rare and most probably originates from a unique ancestor in the mapping population. Analyses of different subsets of families, created according to the results of haplotype analysis and availability of SNP and microsatellite data, refined the previously detected QTL affecting MY1 and PY1 to a region ranging from 117.962 Mb to 119.018 Mb (1.056 Mb) on BTA5. However, the possibility of a second QTL affecting only PY1 at 122.115 Mb was not ruled out.

CONCLUSION

This study demonstrates that targeting families segregating for a less frequent QTL allele is a useful method. It improves the mapping resolution of the QTL, which is due to the division of the mapping population based on the results of the haplotype analysis and to the increased frequency of the minor allele in the families. Consequently, we succeeded in refining the region containing the previously detected QTL to 1 Mb on BTA5. This candidate region contains 27 genes with unknown or partially known function(s) and is small enough for high-throughput sequencing, which will allow future detailed analyses of candidate genes.

Assignment of chromosomal locations for unassigned SNPs/scaffolds based on pair-wise linkage disequilibrium estimates

Background

Recent developments of high-density SNP chips across a number of species require accurate genetic maps. Despite rapid advances in genome sequence assembly and availability of a number of tools for creating genetic maps, the exact genome location for a number of SNPs from these SNP chips still remains unknown. We have developed a locus ordering procedure based on linkage disequilibrium (LODE) which provides estimation of the chromosomal positions of unaligned SNPs and scaffolds. It also provides an alternative means for verification of genetic maps. We exemplified LODE in cattle.

Results

The utility of the LODE procedure was demonstrated using data from 1,943 bulls genotyped for 73,569 SNPs across three different SNP chips. First, the utility of the procedure was tested by analysing the masked positions of 1,500 randomly-chosen SNPs with known locations (50 from each chromosome), representing three classes of minor allele frequencies (MAF), namely >0.05, 0.01<MAF ≤ 0.05 and 0.001<MAF ≤ 0.01. The efficiency (percentage of masked SNPs that could be assigned a location) was 96.7%, 30.6% and 2.0%; with an accuracy (the percentage of SNPs assigned correctly) of 99.9%, 98.9% and 33.3% in the three classes of MAF, respectively. The average precision for placement of the SNPs was 914, 3,137 and 6,853 kb, respectively. Secondly, 4,688 of 5,314 SNPs unpositioned in the Btau4.0 assembly were positioned using the LODE procedure. Based on these results, the positions of 485 unordered scaffolds were determined. The procedure was also used to validate the genome positions of 53,068 SNPs placed on Btau4.0 bovine assembly, resulting in identification of problem areas in the assembly. Finally, the accuracy of the LODE procedure was independently validated by comparative mapping on the hg18 human assembly.

Conclusion

The LODE procedure described in this study is an efficient and accurate method for positioning SNPs (MAF>0.05), for validating and checking the quality of a genome assembly, and offers a means for positioning of unordered scaffolds containing SNPs. The LODE procedure will be helpful in refining genome sequence assemblies, especially those being created from next-generation sequencing where high-throughput SNP discovery and genotyping platforms are integrated components of genome analysis.

The pattern of linkage disequilibrium in German Holstein cattle

This study presents a second generation of linkage disequilibrium (LD) map statistics for the whole genome of the Holstein-Friesian population, which has a four times higher resolution compared with that of the maps available so far. We used DNA samples of 810 German Holstein-Friesian cattle genotyped by the Illumina Bovine SNP50K BeadChip to analyse LD structure. A panel of 40 854 (75.6%) markers was included in the final analysis. The pairwise r(2) statistic of SNPs up to 5 Mb apart across the genome was estimated. A mean value of r(2) = 0.30 +/- 0.32 was observed in pairwise distances of <25 kb and it dropped to 0.20 +/- 0.24 at 50-75 kb, which is nearly the average inter-marker space in this study. The proportion of SNPs in useful LD (r(2) > or = 0.25) was 26% for the distance of 50 and 75 kb between SNPs. We found a lower level of LD for SNP pairs at the distance < or =100 kb than previously thought. Analysis revealed 712 haplo-blocks spanning 4.7% of the genome and containing 8.0% of all SNPs. Mean and median block length were estimated as 164 +/- 117 kb and 144 kb respectively. Allele frequencies of the SNPs have a considerable and systematic impact on the estimate of r(2). It is shown that minimizing the allele frequency difference between SNPs reduces the influence of frequency on r(2) estimates. Analysis of past effective population size based on the direct estimates of recombination rates from SNP data showed a decline in effective population size to N(e) = 103 up to approximately 4 generations ago. Systematic effects of marker density and effective population size on observed LD and haplotype structure are discussed.

A comparison of five methods to predict genomic breeding values of dairy bulls from genome-wide SNP markers

Background

Genomic selection (GS) uses molecular breeding values (MBV) derived from dense markers across the entire genome for selection of young animals. The accuracy of MBV prediction is important for a successful application of GS. Recently, several methods have been proposed to estimate MBV. Initial simulation studies have shown that these methods can accurately predict MBV. In this study we compared the accuracies and possible bias of five different regression methods in an empirical application in dairy cattle.

Methods

Genotypes of 7,372 SNP and highly accurate EBV of 1,945 dairy bulls were used to predict MBV for protein percentage (PPT) and a profit index (Australian Selection Index, ASI). Marker effects were estimated by least squares regression (FR-LS), Bayesian regression (Bayes-R), random regression best linear unbiased prediction (RR-BLUP), partial least squares regression (PLSR) and nonparametric support vector regression (SVR) in a training set of 1,239 bulls. Accuracy and bias of MBV prediction were calculated from cross-validation of the training set and tested against a test team of 706 young bulls.

Results

For both traits, FR-LS using a subset of SNP was significantly less accurate than all other methods which used all SNP. Accuracies obtained by Bayes-R, RR-BLUP, PLSR and SVR were very similar for ASI (0.39-0.45) and for PPT (0.55-0.61). Overall, SVR gave the highest accuracy.

All methods resulted in biased MBV predictions for ASI, for PPT only RR-BLUP and SVR predictions were unbiased. A significant decrease in accuracy of prediction of ASI was seen in young test cohorts of bulls compared to the accuracy derived from cross-validation of the training set. This reduction was not apparent for PPT. Combining MBV predictions with pedigree based predictions gave 1.05 - 1.34 times higher accuracies compared to predictions based on pedigree alone. Some methods have largely different computational requirements, with PLSR and RR-BLUP requiring the least computing time.

Conclusions

The four methods which use information from all SNP namely RR-BLUP, Bayes-R, PLSR and SVR generate similar accuracies of MBV prediction for genomic selection, and their use in the selection of immediate future generations in dairy cattle will be comparable. The use of FR-LS in genomic selection is not recommended.

Depauperate genetic variability detected in the American and European bison using genomic techniques

A total of 929 polymorphic SNPs in EB (out of 54, 000 SNPs screened using a BovineSNP50 Illumina Genotyping BeadChip), and 1, 524 and 1, 403 polymorphic SNPs in WB and PB, respectively, were analysed. EB, WB and PB have all undergone recent drastic reductions in population size. Accordingly, they exhibited extremely depauperate genomes, deviations from genetic equilibrium and a genome organization consisting of a mosaic of haplotype blocks: regions with low haplotype diversity and high levels of linkage disequilibrium. No evidence for positive or stabilizing selection was found in EB, WB and PB, likely reflecting drift overwhelming selection. We suggest that utilization of genome-wide screening technologies, followed by utilization of less expensive techniques (e.g. VeraCode and Fluidigm EP1), holds large potential for genetic monitoring of populations. Additionally, these techniques will allow radical improvements of breeding practices in captive or managed populations, otherwise hampered by the limited availability of polymorphic markers. This result in improved possibilities for 1) estimating genetic relationships among individuals and 2) designing breeding strategies which attempt to preserve or reduce polymorphism in ecologically relevant genes and/or entire blocks.

Reviewers

This article was reviewed by: Fyodor Kondrashov and Shamil Sunyaev

Discovery, validation and characterization of 1039 cattle single nucleotide polymorphisms

We identified approximately 13 000 putative single nucleotide polymorphisms (SNPs) by comparison of repeat-masked BAC-end sequences from the cattle RPCI-42 BAC library with whole-genome shotgun contigs of cattle genome assembly Btau 1.0. Genotyping of a subset of these SNPs was performed on a panel containing 186 DNA samples from 18 cattle breeds including 43 trios. Of 1039 SNPs confirmed as polymorphic in the panel, 998 had minor allele frequency > or =0.25 among unrelated individuals of at least one breed. When Btau 4.0 became available, 974 of these validated SNPs were assigned in silico to known cattle chromosomes, while 41 SNPs were mapped to unassigned sequence scaffolds, yielding one SNP every approximately 3 Mbp on average. Twenty-four SNPs identified in Btau 1.0 were not mapped to Btau 4.0. Of the 1015 SNPs mapped to Btau 4.0, 959 SNPs had nucleotide bases identical in Btau 4.0 and Btau 1.0 contigs, whereas 56 bases were changed, resulting in the loss of the in silico SNP in Btau 4.0. Because these 1039 SNPs were all directly confirmed by genotyping on the multi-breed panel, it is likely that the original polymorphisms were correctly identified. The 1039 validated SNPs identified in this study represent a new and useful resource for genome-wide association studies and applications in animal breeding.

Discovery of novel genetic networks associated with 19 economically important traits in beef cattle

Quantitative or complex traits are determined by the combined effects of many loci, and are affected by genetic networks or molecular pathways. In the present study, we genotyped a total of 138 mutations, mainly single nucleotide polymorphisms derived from 71 functional genes on a Wagyu x Limousin reference population. Two hundred forty six F₂ animals were measured for 5 carcass, 6 eating quality and 8 fatty acid composition traits. A total of 2,280 single marker-trait association runs with 120 tagged mutations selected based on the HAPLOVIEW analysis revealed 144 significant associations (P < 0.05), but 50 of them were removed from the analysis due to the small number of animals (≤ 9) in one genotype group or absence of one genotype among three genotypes. The remaining 94 single-trait associations were then placed into three groups of quantitative trait modes (QTMs) with additive, dominant and overdominant effects. All significant markers and their QTMs associated with each of these 19 traits were involved in a linear regression model analysis, which confirmed single-gene associations for 4 traits, but revealed two-gene networks for 8 traits and three-gene networks for 5 traits. Such genetic networks involving both genotypes and QTMs resulted in high correlations between predicted and actual values of performance, thus providing evidence that the classical Mendelian principles of inheritance can be applied in understanding genetic complexity of complex phenotypes. Our present study also indicated that carcass, eating quality and fatty acid composition traits rarely share genetic networks. Therefore, marker-assisted selection for improvement of one category of these traits would not interfere with improvement of another.

Two-stage genome-wide association study identifies integrin beta 5 as having potential role in bull fertility

Background

Fertility is one of the most critical factors controlling biological and financial performance of animal production systems and genetic improvement of lines. The objective of this study was to identify molecular defects in the sperm that are responsible for uncompensable fertility in Holstein bulls. We performed a comprehensive genome wide analysis of single nucleotide polymorphisms (SNP) for bull fertility followed by a second-stage replication in additional bulls for a restricted set of markers.

Results

In the Phase I association study, we genotyped the genomic sperm DNA of 10 low-fertility and 10 high-fertility bulls using Bovine SNP Gene Chips containing approximately 10,000 random SNP markers. In these animals, 8,207 markers were found to be polymorphic, 97 of which were significantly associated with fertility (p < 0.01). In the Phase II study, we tested the four most significant SNP from the Phase I study in 101 low-fertility and 100 high-fertility bulls, with two SNPs (rs29024867 and rs41257187) significantly replicated. Rs29024867 corresponds to a nucleotide change of C → G 2,190 bp 3' of the collagen type I alpha 2 gene on chromosome 4, while the rs41257187 (C → T) is in the coding region of integrin beta 5 gene on chromosome 1. The SNP rs41257187 induces a synonymous (Proline → Proline), suggesting disequilibrium with the true causative locus (i), but we found that the incubation of bull spermatozoa with integrin beta 5 antibodies significantly decreased the ability to fertilize oocytes. Our findings suggest that the bovine sperm integrin beta 5 protein plays a role during fertilization and could serve as a positional or functional marker of bull fertility.

Conclusion

We have identified molecular markers associated with bull fertility and established that at least one of the genes harboring such variation has a role in fertility. The findings are important in understanding mechanisms of uncompensatory infertility in bulls, and in other male mammals. The findings set the stage for more hypothesis-driven research aimed at discovering the role of variation in the genome that affect fertility and that can be used to identify molecular mechanisms of development.

High-resolution haplotype block structure in the cattle genome

Background

The Bovine HapMap Consortium has generated assay panels to genotype ~30,000 single nucleotide polymorphisms (SNPs) from 501 animals sampled from 19 worldwide taurine and indicine breeds, plus two outgroup species (Anoa and Water Buffalo). Within the larger set of SNPs we targeted 101 high density regions spanning up to 7.6 Mb with an average density of approximately one SNP per 4 kb, and characterized the linkage disequilibrium (LD) and haplotype block structure within individual breeds and groups of breeds in relation to their geographic origin and use.

Results

From the 101 targeted high-density regions on bovine chromosomes 6, 14, and 25, between 57 and 95% of the SNPs were informative in the individual breeds. The regions of high LD extend up to ~100 kb and the size of haplotype blocks ranges between 30 bases and 75 kb (10.3 kb average). On the scale from 1–100 kb the extent of LD and haplotype block structure in cattle has high similarity to humans. The estimation of effective population sizes over the previous 10,000 generations conforms to two main events in cattle history: the initiation of cattle domestication (~12,000 years ago), and the intensification of population isolation and current population bottleneck that breeds have experienced worldwide within the last ~700 years. Haplotype block density correlation, block boundary discordances, and haplotype sharing analyses were consistent in revealing unexpected similarities between some beef and dairy breeds, making them non-differentiable. Clustering techniques permitted grouping of breeds into different clades given their similarities and dissimilarities in genetic structure.

Conclusion

This work presents the first high-resolution analysis of haplotype block structure in worldwide cattle samples. Several novel results were obtained. First, cattle and human share a high similarity in LD and haplotype block structure on the scale of 1–100 kb. Second, unexpected similarities in haplotype block structure between dairy and beef breeds make them non-differentiable. Finally, our findings suggest that ~30,000 uniformly distributed SNPs would be necessary to construct a complete genome LD map in Bos taurus breeds, and ~580,000 SNPs would be necessary to characterize the haplotype block structure across the complete cattle genome.

A high density linkage map of the bovine genome

BACKGROUND

Recent technological advances have made it possible to efficiently genotype large numbers of single nucleotide polymorphisms (SNPs) in livestock species, allowing the production of high-density linkage maps. Such maps can be used for quality control of other SNPs and for fine mapping of quantitative trait loci (QTL) via linkage disequilibrium (LD).

RESULTS

A high-density bovine linkage map was constructed using three types of markers. The genotypic information was obtained from 294 microsatellites, three milk protein haplotypes and 6769 SNPs. The map was constructed by combining genetic (linkage) and physical information in an iterative mapping process. Markers were mapped to 3,155 unique positions; the 6,924 autosomal markers were mapped to 3,078 unique positions and the 123 non-pseudoautosomal and 19 pseudoautosomal sex chromosome markers were mapped to 62 and 15 unique positions, respectively. The linkage map had a total length of 3,249 cM. For the autosomes the average genetic distance between adjacent markers was 0.449 cM, the genetic distance between unique map positions was 1.01 cM and the average genetic distance (cM) per Mb was 1.25.

CONCLUSION

There is a high concordance between the order of the SNPs in our linkage map and their physical positions on the most recent bovine genome sequence assembly (Btau 4.0). The linkage maps provide support for fine mapping projects and LD studies in bovine populations. Additionally, the linkage map may help to resolve positions of unassigned portions of the bovine genome.

Linkage disequilibrium in the North American Holstein population

Linkage disequilibrium was estimated using 7119 single nucleotide polymorphism markers across the genome and 200 animals from the North American Holstein cattle population. The analysis of maternally inherited haplotypes revealed strong linkage disequilibrium (r(2) > 0.8) in genomic regions of approximately 50 kb or less. While linkage disequilibrium decays as a function of genomic distance, genomic regions within genes showed greater linkage disequilibrium and greater variation in linkage disequilibrium compared with intergenic regions. Identification of haplotype blocks could characterize the most common haplotypes. Although maximum haplotype block size was over 1 Mb, mean block size was 26-113 kb by various definitions, which was larger than that observed in humans ( approximately 10 kb). Effective population size of the dairy cattle population was estimated from linkage disequilibrium between single nucleotide polymorphism marker pairs in various haplotype ranges. Rapid reduction of effective population size of dairy cattle was inferred from linkage disequilibrium in recent generations. This result implies a loss of genetic diversity because of the high rate of inbreeding and high selection intensity in dairy cattle. The pattern observed in this study indicated linkage disequilibrium in the current dairy cattle population could be exploited to refine mapping resolution. Changes in effective population size during past generations imply a necessity of plans to maintain polymorphism in the Holstein population.

The combined effect of SNP-marker and phenotype attributes in genome-wide association studies

The last decade has seen rapid improvements in high-throughput single nucleotide polymorphism (SNP) genotyping technologies that have consequently made genome-wide association studies (GWAS) possible. With tens to hundreds of thousands of SNP markers being tested simultaneously in GWAS, it is imperative to appropriately pre-process, or filter out, those SNPs that may lead to false associations. This paper explores the relationships between various SNP genotype and phenotype attributes and their effects on false associations. We show that (i) uniformly distributed ordinal data as well as binary data are more easily influenced, though not necessarily negatively, by differences in various SNP attributes compared with normally distributed data; (ii) filtering SNPs on minor allele frequency (MAF) and extent of Hardy–Weinberg equilibrium (HWE) deviation has little effect on the overall false positive rate; (iii) in some cases, filtering on MAF only serves to exclude SNPs from the analysis without reduction of the overall proportion of false associations; and (iv) HWE, MAF and heterozygosity are all dependent on minor genotype frequency, a newly proposed measure for genotype integrity.

The concordance test emerges as a powerful tool for identifying quantitative trait nucleotides: lessons from BTA6 milk yield QTL

The lack of conventions for confirming the discovery of quantitative trait nucleotides in livestock was evidenced by the proposals of mutations in two different genes (SPP1 and ABCG2) as the underlying functional mutation for a major quantitative trait locus (QTL) for milk concentration on bovine chromosome 6 (BTA6). Of these conflicting candidates, SPP1 was excluded by follow-up studies and by the data described here. A simple test for concordance of the zygosity state between QTL segregation status and the candidate polymorphism was shown, in this case, to be a critical step towards establishing the proof. If a given sample effectively represents the genetic variation across the QTL region, haplotype-based concordance may further enhance the functionality and resolution power of this test, allowing identification of the causative gene.

Gene mapping in the wild with SNPs: guidelines and future directions

One of the biggest challenges facing evolutionary biologists is to identify and understand loci that explain fitness variation in natural populations. This review describes how genetic (linkage) mapping with single nucleotide polymorphism (SNP) markers can lead to great progress in this area. Strategies for SNP discovery and SNP genotyping are described and an overview of how to model SNP genotype information in mapping studies is presented. Finally, the opportunity afforded by new generation sequencing and typing technologies to map fitness genes by genome-wide association studies is discussed.

Linkage disequilibrium and signatures of selection on chromosomes 19 and 29 in beef and dairy cattle

The objective of this study was to quantify the extent of linkage disequilibrium (LD) on bovine chromosomes 19 and 29 and to study the pattern of selection signatures in beef and dairy breeds (Angus and Holstein) of Bos taurus. The extent of LD was estimated for 370 and 186 single nucleotide polymorphism markers on BTA19 and 29 respectively using the square of the correlation coefficient (r(2)) among alleles at pairs of loci. A comparison of the extent of LD found that the decline of LD followed a similar pattern in both breeds. We observed long-range LD and found that LD dissipates to background levels at a locus separation of about 20 Mb on both chromosomes. Along each chromosome, patterns of LD were variable in both breeds. We find that a minimum of 30 000 informative and evenly spaced markers would be required for whole-genome association studies in cattle. In addition, we have identified chromosomal regions that show some evidence of selection for economically important traits in Angus and Holstein cattle. The results of this study are of importance for the design and application of association studies.