An integrated approach to bovine oocyte quality: from phenotype to genes

In cattle, early embryonic failure plays a major role in the limitation of reproductive performance and is influenced by genetic effects. Suboptimal oocyte quality, including an inadequate store of maternal factors, is suspected to contribute to this phenomenon. In the present study, 13 Montbeliarde cows were phenotyped on oocyte quality, based on their ability to produce viable embryos after in vitro maturation, fertilisation and culture for 7 days. This discriminated two groups of animals, exhibiting developmental rates below 18.8% or above 40.9% (relative to cleaved embryos). Using microarrays, transcriptomic profiles were compared between oocytes collected in vivo from these two groups of animals. The difference in oocyte development potential was associated with changes in transcripts from 60 genes in immature oocytes and 135 genes in mature oocytes (following Bonferroni 5% correction). Of these, 16 and 32 genes were located in previously identified fertility quantitative trait loci. A subset of differential genes was investigated on distinct samples by reverse transcription-quantitative polymerase chain reaction. For SLC25A16, PPP1R14C, ROBO1, AMDHD1 and MEAF6 transcripts, differential expression was confirmed between high and low oocyte potential animals. Further sequencing and searches for polymorphisms will pave the way for implementing their use in genomic selection.

A comparison of methods for whole-genome QTL mapping using dense markers in four livestock species

Background

With dense genotyping, many choices exist for methods to detect quantitative trait loci (QTL) in livestock populations. However, no across-species study has been conducted on the performance of different methods using real data. We compared three methods that correct for relatedness either implicitly or explicitly: linkage and linkage disequilibrium haplotype-based analysis (LDLA), efficient mixed-model association (EMMA) analysis, and Bayesian whole-genome regression (BayesC). We analyzed one chromosome in each of five datasets (dairy cattle, beef cattle, sheep, horses, and pigs) using real genotypes based on dense single nucleotide polymorphisms and phenotypes. The P values corrected for multiple testing or Bayes factors greater than 150 were considered to be significant. To complete the real data study, we also simulated quantitative trait loci (QTL) for the same datasets based on the real genotypes. Several scenarios were chosen, with different QTL effects and linkage disequilibrium patterns. A pseudo-null statistical distribution was chosen to make the significance thresholds comparable across methods.

Results

For the real data, the three methods generally agreed within 1 or 2 cM for the locations of QTL regions and disagreed when no signals were significant (e.g. in pigs). For certain datasets, LDLA had more significant signals than EMMA or BayesC, but they were concentrated around the same peaks. Therefore, the three methods detected approximately the same number of QTL regions. For the simulated data, LDLA was slightly less powerful and accurate than either EMMA or BayesC but this depended strongly on how thresholds were set in the simulations.

Conclusions

All three methods performed similarly for real and simulated data. No method was clearly superior across all datasets or for any particular dataset. For computational efficiency and ease of interpretation, EMMA is recommended, but using more than one method is suggested.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0087-7) contains supplementary material, which is available to authorized users.

Reproductive technologies and genomic selection in dairy cattle

Genomic tools are now available for most livestock species and are used routinely for genomic selection (GS) in cattle. One of the most important developments resulting from the introduction of genomic testing for dairy cattle is the application of reasonably priced low-density single nucleotide polymorphism technology in the selection of females. In this context, combining genome testing and reproductive biotechnologies in young heifers enables new strategies to generate replacement and elite females in a given period of time. Moreover, multiple markers have been detected in biopsies of preimplantation stage embryos, thus paving the way to develop new strategies based on preimplantation diagnosis and the genetic screening of embryos. Based on recent advances in GS, the present review focuses on new possibilities inherent in reproductive technologies used for commercial purposes and in genetic schemes, possible side effects and beneficial impacts on reproductive efficiency. A particular focus is on the different steps allowing embryo genotyping, including embryo micromanipulation, DNA production and quality assessment.

Diagnosis and treatment of autoimmune pancreatitis types 1 and 2

Background

Autoimmune pancreatitis (AIP) is characterized by diffuse or focal swelling of the pancreas. AIP has been divided into types 1 and 2. The aim of the study was to evaluate and compare the clinicopathological characteristics, therapy and outcome of patients with AIP.

Methods

The medical records of patients diagnosed with AIP between January 2003 and July 2011 were reviewed. Characteristics of patients with AIP types 1 and 2 were compared with those of patients with pancreatic ductal adenocarcinoma (PDAC).

Results

AIP was classified as type 1 in 40 patients and type 2 in 32 according to the HISORt (Histology, Imaging, Serology, Other organ involvement, Response to therapy) criteria. Patients with histologically confirmed AIP type 2 were younger than those with type 1 (P = 0·005). Some 30 of 32 patients with AIP type 2 were found to have a localized tumour-like pancreatic mass and underwent pancreatectomy, compared with only 16 of 40 with type 1 (P < 0·001). Three of 25 patients with AIP type 2 presented with raised serum levels of IgG4 compared with 21 of 38 with type 1 (P < 0·001). There was no difference in symptoms and involvement of other organs between AIP types 1 and 2. Presentation with weight loss was more common among patients with PDAC than those with AIP, but there was no difference in pain or jaundice between the groups. Raised serum carbohydrate antigen 19-9 levels were more prevalent in patients with PDAC.

Conclusion

Patients with AIP type 2 frequently present with abdominal pain and a tumour-like mass. Differentiating AIP from PDAC is difficult, so making the clinical decision regarding operative versus conservative management is challenging.

Concordance analysis for QTL detection in dairy cattle: a case study of leg morphology

BACKGROUND

The present availability of sequence data gives new opportunities to narrow down from QTL (quantitative trait locus) regions to causative mutations. Our objective was to decrease the number of candidate causative mutations in a QTL region. For this, a concordance analysis was applied for a leg conformation trait in dairy cattle. Several QTL were detected for which the QTL status (homozygous or heterozygous for the QTL) was inferred for each individual. Subsequently, the inferred QTL status was used in a concordance analysis to reduce the number of candidate mutations.

METHODS

Twenty QTL for rear leg set side view were mapped using Bayes C. Marker effects estimated during QTL mapping were used to infer the QTL status for each individual. Subsequently, polymorphisms present in the QTL regions were extracted from the whole-genome sequences of 71 Holstein bulls. Only polymorphisms for which the status was concordant with the QTL status were kept as candidate causative mutations.

RESULTS

QTL status could be inferred for 15 of the 20 QTL. The number of concordant polymorphisms differed between QTL and depended on the number of QTL statuses that could be inferred and the linkage disequilibrium in the QTL region. For some QTL, the concordance analysis was efficient and narrowed down to a limited number of candidate mutations located in one or two genes, while for other QTL a large number of genes contained concordant polymorphisms.

CONCLUSIONS

For regions for which the concordance analysis could be performed, we were able to reduce the number of candidate mutations. For part of the QTL, the concordant analyses narrowed QTL regions down to a limited number of genes, of which some are known for their role in limb or skeletal development in humans and mice. Mutations in these genes are good candidates for QTN (quantitative trait nucleotides) influencing rear leg set side view.

Efficiency of multi-breed genomic selection for dairy cattle breeds with different sizes of reference population

Single-breed genomic selection (GS) based on medium single nucleotide polymorphism (SNP) density (~50,000; 50K) is now routinely implemented in several large cattle breeds. However, building large enough reference populations remains a challenge for many medium or small breeds. The high-density BovineHD BeadChip (HD chip; Illumina Inc., San Diego, CA) containing 777,609 SNP developed in 2010 is characterized by short-distance linkage disequilibrium expected to be maintained across breeds. Therefore, combining reference populations can be envisioned. A population of 1,869 influential ancestors from 3 dairy breeds (Holstein, Montbéliarde, and Normande) was genotyped with the HD chip. Using this sample, 50K genotypes were imputed within breed to high-density genotypes, leading to a large HD reference population. This population was used to develop a multi-breed genomic evaluation. The goal of this paper was to investigate the gain of multi-breed genomic evaluation for a small breed. The advantage of using a large breed (Normande in the present study) to mimic a small breed is the large potential validation population to compare alternative genomic selection approaches more reliably. In the Normande breed, 3 training sets were defined with 1,597, 404, and 198 bulls, and a unique validation set included the 394 youngest bulls. For each training set, estimated breeding values (EBV) were computed using pedigree-based BLUP, single-breed BayesC, or multi-breed BayesC for which the reference population was formed by any of the Normande training data sets and 4,989 Holstein and 1,788 Montbéliarde bulls. Phenotypes were standardized by within-breed genetic standard deviation, the proportion of polygenic variance was set to 30%, and the estimated number of SNP with a nonzero effect was about 7,000. The 2 genomic selection (GS) approaches were performed using either the 50K or HD genotypes. The correlations between EBV and observed daughter yield deviations (DYD) were computed for 6 traits and using the different prediction approaches. Compared with pedigree-based BLUP, the average gain in accuracy with GS in small populations was 0.057 for the single-breed and 0.086 for multi-breed approach. This gain was up to 0.193 and 0.209, respectively, with the large reference population. Improvement of EBV prediction due to the multi-breed evaluation was higher for animals not closely related to the reference population. In the case of a breed with a small reference population size, the increase in correlation due to multi-breed GS was 0.141 for bulls without their sire in reference population compared with 0.016 for bulls with their sire in reference population. These results demonstrate that multi-breed GS can contribute to increase genomic evaluation accuracy in small breeds.

High-density marker imputation accuracy in sixteen French cattle breeds

Background

Genotyping with the medium-density Bovine SNP50 BeadChip^® (50K) is now standard in cattle. The high-density BovineHD BeadChip^®, which contains 777 609 single nucleotide polymorphisms (SNPs), was developed in 2010. Increasing marker density increases the level of linkage disequilibrium between quantitative trait loci (QTL) and SNPs and the accuracy of QTL localization and genomic selection. However, re-genotyping all animals with the high-density chip is not economically feasible. An alternative strategy is to genotype part of the animals with the high-density chip and to impute high-density genotypes for animals already genotyped with the 50K chip. Thus, it is necessary to investigate the error rate when imputing from the 50K to the high-density chip.

Methods

Five thousand one hundred and fifty three animals from 16 breeds (89 to 788 per breed) were genotyped with the high-density chip. Imputation error rates from the 50K to the high-density chip were computed for each breed with a validation set that included the 20% youngest animals. Marker genotypes were masked for animals in the validation population in order to mimic 50K genotypes. Imputation was carried out using the Beagle 3.3.0 software.

Results

Mean allele imputation error rates ranged from 0.31% to 2.41% depending on the breed. In total, 1980 SNPs had high imputation error rates in several breeds, which is probably due to genome assembly errors, and we recommend to discard these in future studies. Differences in imputation accuracy between breeds were related to the high-density-genotyped sample size and to the genetic relationship between reference and validation populations, whereas differences in effective population size and level of linkage disequilibrium showed limited effects. Accordingly, imputation accuracy was higher in breeds with large populations and in dairy breeds than in beef breeds. More than 99% of the alleles were correctly imputed if more than 300 animals were genotyped at high-density. No improvement was observed when multi-breed imputation was performed.

Conclusion

In all breeds, imputation accuracy was higher than 97%, which indicates that imputation to the high-density chip was accurate. Imputation accuracy depends mainly on the size of the reference population and the relationship between reference and target populations.

QTL fine mapping with Bayes C(π): a simulation study

BACKGROUND

Accurate QTL mapping is a prerequisite in the search for causative mutations. Bayesian genomic selection models that analyse many markers simultaneously should provide more accurate QTL detection results than single-marker models. Our objectives were to (a) evaluate by simulation the influence of heritability, number of QTL and number of records on the accuracy of QTL mapping with Bayes Cπ and Bayes C; (b) estimate the QTL status (homozygous vs. heterozygous) of the individuals analysed. This study focussed on the ten largest detected QTL, assuming they are candidates for further characterization.

METHODS

Our simulations were based on a true dairy cattle population genotyped for 38,277 phased markers. Some of these markers were considered biallelic QTL and used to generate corresponding phenotypes. Different numbers of records (4387 and 1500), heritability values (0.1, 0.4 and 0.7) and numbers of QTL (10, 100 and 1000) were studied. QTL detection was based on the posterior inclusion probability for individual markers, or on the sum of the posterior inclusion probabilities for consecutive markers, estimated using Bayes C or Bayes Cπ. The QTL status of the individuals was derived from the contrast between the sums of the SNP allelic effects of their chromosomal segments.

RESULTS

The proportion of markers with null effect (π) frequently did not reach convergence, leading to poor results for Bayes Cπ in QTL detection. Fixing π led to better results. Detection of the largest QTL was most accurate for medium to high heritability, for low to moderate numbers of QTL, and with a large number of records. The QTL status was accurately inferred when the distribution of the contrast between chromosomal segment effects was bimodal.

CONCLUSIONS

QTL detection is feasible with Bayes C. For QTL detection, it is recommended to use a large dataset and to focus on highly heritable traits and on the largest QTL. QTL statuses were inferred based on the distribution of the contrast between chromosomal segment effects.

Detection of haplotypes associated with prenatal death in dairy cattle and identification of deleterious mutations in GART, SHBG and SLC37A2

The regular decrease of female fertility over time is a major concern in modern dairy cattle industry. Only half of this decrease is explained by indirect response to selection on milk production, suggesting the existence of other factors such as embryonic lethal genetic defects. Genomic regions harboring recessive deleterious mutations were detected in three dairy cattle breeds by identifying frequent haplotypes (>1%) showing a deficit in homozygotes among Illumina Bovine 50k Beadchip haplotyping data from the French genomic selection database (47,878 Holstein, 16,833 Montbéliarde, and 11,466 Normande animals). Thirty-four candidate haplotypes (p<10(-4)) including previously reported regions associated with Brachyspina, CVM, HH1, and HH3 in Holstein breed were identified. Haplotype length varied from 1 to 4.8 Mb and frequencies from 1.7 up to 9%. A significant negative effect on calving rate, consistent in heifers and in lactating cows, was observed for 9 of these haplotypes in matings between carrier bulls and daughters of carrier sires, confirming their association with embryonic lethal mutations. Eight regions were further investigated using whole genome sequencing data from heterozygous bull carriers and control animals (45 animals in total). Six strong candidate causative mutations including polymorphisms previously reported in FANCI (Brachyspina), SLC35A3 (CVM), APAF1 (HH1) and three novel mutations with very damaging effect on the protein structure, according to SIFT and Polyphen-2, were detected in GART, SHBG and SLC37A2 genes. In conclusion, this study reveals a yet hidden consequence of the important inbreeding rate observed in intensively selected and specialized cattle breeds. Counter-selection of these mutations and management of matings will have positive consequences on female fertility in dairy cattle.

Novel insights into the bovine polled phenotype and horn ontogenesis in Bovidae

Despite massive research efforts, the molecular etiology of bovine polledness and the developmental pathways involved in horn ontogenesis are still poorly understood. In a recent article, we provided evidence for the existence of at least two different alleles at the Polled locus and identified candidate mutations for each of them. None of these mutations was located in known coding or regulatory regions, thus adding to the complexity of understanding the molecular basis of polledness. We confirm previous results here and exhaustively identify the causative mutation for the Celtic allele (P_C) and four candidate mutations for the Friesian allele (P_F). We describe a previously unreported eyelash-and-eyelid phenotype associated with regular polledness, and present unique histological and gene expression data on bovine horn bud differentiation in fetuses affected by three different horn defect syndromes, as well as in wild-type controls. We propose the ectopic expression of a lincRNA in P_C/p horn buds as a probable cause of horn bud agenesis. In addition, we provide evidence for an involvement of OLIG2, FOXL2 and RXFP2 in horn bud differentiation, and draw a first link between bovine, ovine and caprine Polled loci. Our results represent a first and important step in understanding the genetic pathways and key process involved in horn bud differentiation in Bovidae.

Inclusion of cow records in genomic evaluations and impact on bias due to preferential treatment

Background

Today, genomic evaluations are an essential feature of dairy cattle breeding. Initially, genomic evaluation targeted young bulls but recently, a rapidly increasing number of females (both heifers and cows) are being genotyped. A rising issue is whether and how own performance of genotyped cows should be included in genomic evaluations. The purpose of this study was to assess the impact of including yield deviations, i.e. own performance of cows, in genomic evaluations.

Methods

Two different genomic evaluations were performed: one including only reliable daughter yield deviations of proven bulls based on their non-genotyped daughters, and one including both daughter yield deviations for males and own yield deviations for genotyped females. Milk yield, the trait most prone to preferential treatment, and somatic cell count, for which such a bias is very unlikely, were studied. Data consisted of two groups of animals from the three main dairy breeds in France: 11 884 elite females genotyped by breeding companies and 7032 cows genotyped for a research project (and considered as randomly selected from the commercial population).

Results

For several measures that could be related to preferential treatment bias, the elite group presented a different pattern of estimated breeding values for milk yield compared to the other combinations of trait and group: for instance, for milk yield, the average difference between estimated breeding values with or without own yield deviations was significantly different from 0 for this group. Correlations between estimated breeding values with or without yield deviations were lower for elite females than for randomly selected cows for milk yield but were very similar for somatic cell count.

Conclusions

This study demonstrated that including own milk performance of elite females leads to biased (over-estimated) genomic evaluations. Thus, milk production records of elite cows require specific treatment in genomic evaluation.

Cyclooxygenase expression and platelet function in healthy dogs receiving low-dose aspirin

BACKGROUND

Low-dose aspirin is used to prevent thromboembolic complications in dogs, but some animals are nonresponsive to the antiplatelet effects of aspirin ("aspirin resistance").

HYPOTHESIS/OBJECTIVES

That low-dose aspirin would inhibit platelet function, decrease thromboxane synthesis, and alter platelet cyclooxygenase (COX) expression.

ANIMALS

Twenty-four healthy dogs.

METHODS

A repeated measures study. Platelet function (PFA-100 closure time, collagen/epinephrine), platelet COX-1 and COX-2 expression, and urine 11-dehydro-thromboxane B(2) (11-dTXB(2)) were evaluated before and during aspirin administration (1 mg/kg Q24 hours PO, 10 days). Based on prolongation of closure times after aspirin administration, dogs were divided into categories according to aspirin responsiveness: responders, nonresponders, and inconsistent responders.

RESULTS

Low-dose aspirin increased closure times significantly (62% by Day 10, P < .001), with an equal distribution among aspirin responsiveness categories, 8 dogs per group. Platelet COX-1 mean fluorescent intensity (MFI) increased significantly during treatment, 13% on Day 3 (range, -29.7-136.1%) (P = .047) and 72% on Day 10 (range, -0.37-210%) (P < .001). Platelet COX-2 MFI increased significantly by 34% (range, -29.2-270%) on Day 3 (P = .003) and 74% (range, -19.7-226%) on Day 10 (P < .001). Urinary 11-dTXB(2) concentrations significantly (P = .005, P < .001) decreased at both time points. There was no difference between aspirin responsiveness and either platelet COX expression or thromboxane production.

CONCLUSIONS AND CLINICAL IMPORTANCE

Low-dose aspirin consistently inhibits platelet function in approximately one-third of healthy dogs, despite decreased thromboxane synthesis and increased platelet COX expression in most dogs. COX isoform expression before treatment did not predict aspirin resistance.

Short communication: Imputation performances of 3 low-density marker panels in beef and dairy cattle

Low-density chips are appealing alternative tools contributing to the reduction of genotyping costs. Imputation enables researchers to predict missing genotypes to recreate the denser coverage of the standard 50K (∼50,000) genotype. Two alternative in silico chips were defined in this study that included markers selected to optimize minor allele frequency and spacing. The objective of this study was to compare the imputation accuracy of these custom low-density chips with a commercially available 3K chip. Data consisted of genotypes of 4,037 Holstein bulls, 1,219 Montbéliarde bulls, and 991 Blonde d'Aquitaine bulls. Criteria to select markers to include in low-density marker panels are described. To mimic a low-density genotype, all markers except the markers present on the low-density panel were masked in the validation population. Imputation was performed using the Beagle software. Combining the directed acyclic graph obtained with Beagle with the PHASEBOOK algorithm provides fast and accurate imputation that is suitable for routine genomic evaluations based on imputed genotypes. Overall, 95 to 99% of alleles were correctly imputed depending on the breed and the low-density chip used. The alternative low-density chips gave better results than the commercially available 3K chip. A low-density chip with 6,000 markers is a valuable genotyping tool suitable for both dairy and beef breeds. Such a tool could be used for preselection of young animals or large-scale screening of the female population.

Application of Bayesian least absolute shrinkage and selection operator (LASSO) and BayesCπ methods for genomic selection in French Holstein and Montbéliarde breeds

Recently, the amount of available single nucleotide polymorphism (SNP) marker data has considerably increased in dairy cattle breeds, both for research purposes and for application in commercial breeding and selection programs. Bayesian methods are currently used in the genomic evaluation of dairy cattle to handle very large sets of explanatory variables with a limited number of observations. In this study, we applied 2 bayesian methods, BayesCπ and bayesian least absolute shrinkage and selection operator (LASSO), to 2 genotyped and phenotyped reference populations consisting of 3,940 Holstein bulls and 1,172 Montbéliarde bulls with approximately 40,000 polymorphic SNP. We compared the accuracy of the bayesian methods for the prediction of 3 traits (milk yield, fat content, and conception rate) with pedigree-based BLUP, genomic BLUP, partial least squares (PLS) regression, and sparse PLS regression, a variable selection PLS variant. The results showed that the correlations between observed and predicted phenotypes were similar in BayesCπ (including or not pedigree information) and bayesian LASSO for most of the traits and whatever the breed. In the Holstein breed, bayesian methods led to higher correlations than other approaches for fat content and were similar to genomic BLUP for milk yield and to genomic BLUP and PLS regression for the conception rate. In the Montbéliarde breed, no method dominated the others, except BayesCπ for fat content. The better performances of the bayesian methods for fat content in Holstein and Montbéliarde breeds are probably due to the effect of the DGAT1 gene. The SNP identified by the BayesCπ, bayesian LASSO, and sparse PLS regression methods, based on their effect on the different traits of interest, were located at almost the same position on the genome. As the bayesian methods resulted in regressions of direct genomic values on daughter trait deviations closer to 1 than for the other methods tested in this study, bayesian methods are suggested for genomic evaluations of French dairy cattle.

A comparison of partial least squares (PLS) and sparse PLS regressions in genomic selection in French dairy cattle

Genomic selection involves computing a prediction equation from the estimated effects of a large number of DNA markers based on a limited number of genotyped animals with phenotypes. The number of observations is much smaller than the number of independent variables, and the challenge is to find methods that perform well in this context. Partial least squares regression (PLS) and sparse PLS were used with a reference population of 3,940 genotyped and phenotyped French Holstein bulls and 39,738 polymorphic single nucleotide polymorphism markers. Partial least squares regression reduces the number of variables by projecting independent variables onto latent structures. Sparse PLS combines variable selection and modeling in a one-step procedure. Correlations between observed phenotypes and phenotypes predicted by PLS and sparse PLS were similar, but sparse PLS highlighted some genome regions more clearly. Both PLS and sparse PLS were more accurate than pedigree-based BLUP and generally provided lower correlations between observed and predicted phenotypes than did genomic BLUP. Furthermore, PLS and sparse PLS required similar computing time to genomic BLUP for the study of 6 traits.

Fine mapping of copy number variations on two cattle genome assemblies using high density SNP array

Background

Btau_4.0 and UMD3.1 are two distinct cattle reference genome assemblies. In our previous study using the low density BovineSNP50 array, we reported a copy number variation (CNV) analysis on Btau_4.0 with 521 animals of 21 cattle breeds, yielding 682 CNV regions with a total length of 139.8 megabases.

Results

In this study using the high density BovineHD SNP array, we performed high resolution CNV analyses on both Btau_4.0 and UMD3.1 with 674 animals of 27 cattle breeds. We first compared CNV results derived from these two different SNP array platforms on Btau_4.0. With two thirds of the animals shared between studies, on Btau_4.0 we identified 3,346 candidate CNV regions representing 142.7 megabases (~4.70%) of the genome. With a similar total length but 5 times more event counts, the average CNVR length of current Btau_4.0 dataset is significantly shorter than the previous one (42.7 kb vs. 205 kb). Although subsets of these two results overlapped, 64% (91.6 megabases) of current dataset was not present in the previous study. We also performed similar analyses on UMD3.1 using these BovineHD SNP array results. Approximately 50% more and 20% longer CNVs were called on UMD3.1 as compared to those on Btau_4.0. However, a comparable result of CNVRs (3,438 regions with a total length 146.9 megabases) was obtained. We suspect that these results are due to the UMD3.1 assembly's efforts of placing unplaced contigs and removing unmerged alleles. Selected CNVs were further experimentally validated, achieving a 73% PCR validation rate, which is considerably higher than the previous validation rate. About 20-45% of CNV regions overlapped with cattle RefSeq genes and Ensembl genes. Panther and IPA analyses indicated that these genes provide a wide spectrum of biological processes involving immune system, lipid metabolism, cell, organism and system development.

Conclusion

We present a comprehensive result of cattle CNVs at a higher resolution and sensitivity. We identified over 3,000 candidate CNV regions on both Btau_4.0 and UMD3.1, further compared current datasets with previous results, and examined the impacts of genome assemblies on CNV calling.

[Surgical therapy of intraductal papillary mucinous neoplasms of the pancreas]

Intraductal papillary mucinous neoplasms (IPMN) of the pancreas constitute an increasingly recognized entity of cystic pancreatic tumors which are characterized by mucin production and epithelial growth within the pancreatic ducts and show a wide spectrum of morphologic variants. They may arise in the main pancreatic duct, its major side branches or in both (mixed type). Furthermore, IPMNs are considered as precursor lesions to pancreatic adenocarcinoma. However, it is not clear what the time course of such potential neoplastic transformation might be and whether all lesions progress to malignant tumors. As currently no diagnostic test can reliably differentiate between benign and malignant tumors the majority of newly diagnosed IPMNs should be surgically resected. According to current treatment guidelines (Sendai criteria), only asymptomatic side branch IPMNs of less than 3 cm in diameter without suspicious radiologic features, such as nodules, thickness of the cystic wall or size progression, should be treated conservatively without the need for surgical resection. Recently, this approach has become controversial due to a relevant number of reported Sendai negative IPMNs which revealed malignant transformation on final histological examination. The focus of this review is on the surgical treatment of IPMNs with regard to the current state of knowledge.

Design of a bovine low-density SNP array optimized for imputation

The Illumina BovineLD BeadChip was designed to support imputation to higher density genotypes in dairy and beef breeds by including single-nucleotide polymorphisms (SNPs) that had a high minor allele frequency as well as uniform spacing across the genome except at the ends of the chromosome where densities were increased. The chip also includes SNPs on the Y chromosome and mitochondrial DNA loci that are useful for determining subspecies classification and certain paternal and maternal breed lineages. The total number of SNPs was 6,909. Accuracy of imputation to Illumina BovineSNP50 genotypes using the BovineLD chip was over 97% for most dairy and beef populations. The BovineLD imputations were about 3 percentage points more accurate than those from the Illumina GoldenGate Bovine3K BeadChip across multiple populations. The improvement was greatest when neither parent was genotyped. The minor allele frequencies were similar across taurine beef and dairy breeds as was the proportion of SNPs that were polymorphic. The new BovineLD chip should facilitate low-cost genomic selection in taurine beef and dairy cattle.

135 BREEDING VALUES CONCORDANCE BETWEEN EMBRYOS AND CORRESPONDING CALVES

Genomic tools are now available for most livestock species and are used routinely for genomic selection in cattle. Recently, biopsies of pre-implantation-stage embryos were genotyped for multiple markers. This strategy provides the opportunity to estimate breeding values for traits of particular interest and the presence of genetic abnormalities, thus allowing selection of embryos before transfer (Le Bourhis et al. 2011 Reprod. Fertil. Dev. 23, 197 abst). The present work aimed to compare the genotype and the breeding values from biopsied bovine embryos with the corresponding calves. Bovine embryos were obtained after superovulation (8 cows) and flushing at Day 6 or 7. A total of 11 embryos (1 or 2 Grade 1 embryos per flush per cow) were washed and biopsied using a microblade. Biopsies of 5 to 10 cells were transferred individually as dry samples in tubes and frozen before whole genome amplification (WGA). The genomic DNA of each biopsy was amplified using a WGA kit according to the manufacturer's instructions (WGA; QIAGEN REPLI-g® Mini Kit, Qiagen, Valencia, CA, USA). Biopsied embryos were transferred either frozen or fresh to synchronized recipients. At birth a blood sample was taken from the calf for subsequent genotyping. Genotyping was done using the Illumina BovineSNP50TM beadchip. Only embryos with call rate (CR) higher than 80% were selected for breeding values comparisons. Because of allele dropout, heterozygous markers are turned into homozygous makers artificially. Only markers that were still heterozygous in genotypes of an embryo were selected and error rates were calculated with the same markers from the corresponding calf. Imputation was done using Beagle and taking into account the 50 k genotyping results of the parents. Breeding values (milk production and morphological traits) were calculated and compared with those of the 7 corresponding calves. From 11 embryos analysed, only 1 (9%) gave a CR lower than 80% and a higher percentage error with calf genotype (Table 1). These results indicate that, using embryonic DNA after WGA, genotyping errors between embryo and calf are low and correlated with the CR of embryos. For embryos with CR higher than 84, the concordance of genomic values between embryo and calf is very high. More embryo–calf pairs are needed to assess the reliability of this method and to validate the breeding value at the embryo stage. This new technique offers new possibilities in managing breeding schemes by selecting the embryos before transfer. Table 1.Embryo call rate (CR) and genotyping and breeding value concordances between embryos and calves