A two step Bayesian approach for genomic prediction of breeding values

<p>Abstract</p> <p>Background</p> <p>In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size <it>p </it>on the posterior distribution of the marker variances will be <it>p </it>df.</p> <p>Methods</p> <p>The simulated data from the 15^thQTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model.</p> <p>Results</p> <p>Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances.</p> <p>Conclusions</p> <p>Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.</p

Number and mode of inheritance of QTL influencing backfat thickness on SSC2p in Sino-European pig pedigrees

<p>Abstract</p> <p>Background</p> <p>In the pig, multiple QTL associated with growth and fatness traits have been mapped to chromosome 2 (SSC2) and among these, at least one shows paternal expression due to the IGF2-intron3-G3072A substitution. Previously published results on the position and imprinting status of this QTL disagree between analyses from French and Dutch F2 crossbred pig populations obtained with the same breeds (Meishan crossed with Large White or Landrace).</p> <p>Methods</p> <p>To study the role of paternal and maternal alleles at the IGF2 locus and to test the hypothesis of a second QTL affecting backfat thickness on the short arm of SSC2 (SSC2p), a QTL mapping analysis was carried out on a combined pedigree including both the French and Dutch F2 populations, on the progeny of F1 males that were heterozygous (A/G) and homozygous (G/G) at the IGF2 locus. Simulations were performed to clarify the relations between the two QTL and to understand to what extent they can explain the discrepancies previously reported.</p> <p>Results</p> <p>The QTL analyses showed the segregation of at least two QTL on chromosome 2 in both pedigrees, i.e. the IGF2 locus and a second QTL segregating at least in the G/G F1 males and located between positions 30 and 51 cM. Statistical analyses highlighted that the maternally inherited allele at the IGF2 locus had a significant effect but simulation studies showed that this is probably a spurious effect due to the segregation of the second QTL.</p> <p>Conclusions</p> <p>Our results show that two QTL on SSC2p affect backfat thickness. Differences in the pedigree structures and in the number of heterozygous females at the IGF2 locus result in different imprinting statuses in the two pedigrees studied. The spurious effect observed when a maternally allele is present at the IGF2 locus, is in fact due to the presence of a second closely located QTL. This work confirms that pig chromosome 2 is a major region associated with fattening traits.</p

Minimising Mortality in Endangered Raptors Due to Power Lines: The Importance of Spatial Aggregation to Optimize the Application of Mitigation Measures

Electrocution by power lines is one of the main causes of non-natural mortality in birds of prey. In an area in central Spain, we surveyed 6304 pylons from 333 power lines to determine electrocution rates, environmental and design factors that may influence electrocution and the efficacy of mitigation measures used to minimise electrocution cases. A total of 952 electrocuted raptors, representing 14 different species, were observed. Electrocuted raptors were concentrated in certain areas and the environmental factors associated with increased electrocution events were: greater numbers of prey animals; greater vegetation cover; and shorter distance to roads. The structural elements associated with electrocutions were shorter strings of insulators, one or more phases over the crossarm, cross-shaped design and pylon function. Of the 952 carcasses found, 148 were eagles, including golden eagle (Aquila chrysaetos), Spanish imperial eagle (Aquila adalberti) and Bonelli's eagle (Aquila fasciata). Electrocuted eagles were clustered in smaller areas than other electrocuted raptors. The factors associated with increased eagle electrocution events were: pylons function, shorter strings of insulators, higher slopes surrounding the pylon, and more numerous potential prey animals. Pylons with increased string of insulators had lower raptor electrocution rates than unimproved pylons, although this technique was unsuccessful for eagles. Pylons with cable insulation showed higher electrocution rates than unimproved pylons, both for raptors and eagles, despite this is the most widely used and recommended mitigation measure in several countries. To optimize the application of mitigation measures, our results recommend the substitution of pin-type insulators to suspended ones and elongating the strings of insulators

Deregressed EBV as the response variable yield more reliable genomic predictions than traditional EBV in pure-bred pigs

<p>Abstract</p> <p>Background</p> <p>Genomic selection can be implemented by a multi-step procedure, which requires a response variable and a statistical method. For pure-bred pigs, it was hypothesised that deregressed estimated breeding values (EBV) with the parent average removed as the response variable generate higher reliabilities of genomic breeding values than EBV, and that the normal, thick-tailed and mixture-distribution models yield similar reliabilities.</p> <p>Methods</p> <p>Reliabilities of genomic breeding values were estimated with EBV and deregressed EBV as response variables and under the three statistical methods, genomic BLUP, Bayesian Lasso and MIXTURE. The methods were examined by splitting data into a reference data set of 1375 genotyped animals that were performance tested before October 2008, and 536 genotyped validation animals that were performance tested after October 2008. The traits examined were daily gain and feed conversion ratio.</p> <p>Results</p> <p>Using deregressed EBV as the response variable yielded 18 to 39% higher reliabilities of the genomic breeding values than using EBV as the response variable. For daily gain, the increase in reliability due to deregression was significant and approximately 35%, whereas for feed conversion ratio it ranged between 18 and 39% and was significant only when MIXTURE was used. Genomic BLUP, Bayesian Lasso and MIXTURE had similar reliabilities.</p> <p>Conclusions</p> <p>Deregressed EBV is the preferred response variable, whereas the choice of statistical method is less critical for pure-bred pigs. The increase of 18 to 39% in reliability is worthwhile, since the reliabilities of the genomic breeding values directly affect the returns from genomic selection.</p

Changing the culture of assessment: the dominance of the summative assessment paradigm

Background Despite growing evidence of the benefits of including assessment for learning strategies within programmes of assessment, practical implementation of these approaches is often problematical. Organisational culture change is often hindered by personal and collective beliefs which encourage adherence to the existing organisational paradigm. We aimed to explore how these beliefs influenced proposals to redesign a summative assessment culture in order to improve students’ use of assessment-related feedback. Methods Using the principles of participatory design, a mixed group comprising medical students, clinical teachers and senior faculty members was challenged to develop radical solutions to improve the use of post-assessment feedback. Follow-up interviews were conducted with individual members of the group to explore their personal beliefs about the proposed redesign. Data were analysed using a socio-cultural lens. Results Proposed changes were dominated by a shared belief in the primacy of the summative assessment paradigm, which prevented radical redesign solutions from being accepted by group members. Participants’ prior assessment experiences strongly influenced proposals for change. As participants had largely only experienced a summative assessment culture, they found it difficult to conceptualise radical change in the assessment culture. Although all group members participated, students were less successful at persuading the group to adopt their ideas. Faculty members and clinical teachers often used indirect techniques to close down discussions. The strength of individual beliefs became more apparent in the follow-up interviews. Conclusions Naïve epistemologies and prior personal experiences were influential in the assessment redesign but were usually not expressed explicitly in a group setting, perhaps because of cultural conventions of politeness. In order to successfully implement a change in assessment culture, firmly-held intuitive beliefs about summative assessment will need to be clearly understood as a first step

Genome-assisted prediction of a quantitative trait measured in parents and progeny: application to food conversion rate in chickens

Accuracy of prediction of yet-to-be observed phenotypes for food conversion rate (FCR) in broilers was studied in a genome-assisted selection context. Data consisted of FCR measured on the progeny of 394 sires with SNP information. A Bayesian regression model (Bayes A) and a semi-parametric approach (Reproducing kernel Hilbert Spaces regression, RKHS) using all available SNPs (p = 3481) were compared with a standard linear model in which future performance was predicted using pedigree indexes in the absence of genomic data. The RKHS regression was also tested on several sets of pre-selected SNPs (p = 400) using alternative measures of the information gain provided by the SNPs. All analyses were performed using 333 genotyped sires as training set, and predictions were made on 61 birds as testing set, which were sons of sires in the training set. Accuracy of prediction was measured as the Spearman correlation (r¯S) between observed and predicted phenotype, with its confidence interval assessed through a bootstrap approach. A large improvement of genome-assisted prediction (up to an almost 4-fold increase in accuracy) was found relative to pedigree index. Bayes A and RKHS regression were equally accurate (r¯S = 0.27) when all 3481 SNPs were included in the model. However, RKHS with 400 pre-selected informative SNPs was more accurate than Bayes A with all SNPs

Mapping carcass and meat quality QTL on Sus Scrofa chromosome 2 in commercial finishing pigs

Quantitative trait loci (QTL) affecting carcass and meat quality located on SSC2 were identified using variance component methods. A large number of traits involved in meat and carcass quality was detected in a commercial crossbred population: 1855 pigs sired by 17 boars from a synthetic line, which where homozygous (A/A) for IGF2. Using combined linkage and linkage disequilibrium mapping (LDLA), several QTL significantly affecting loin muscle mass, ham weight and ham muscles (outer ham and knuckle ham) and meat quality traits, such as Minolta-L* and -b*, ultimate pH and Japanese colour score were detected. These results agreed well with previous QTL-studies involving SSC2. Since our study is carried out on crossbreds, different QTL may be segregating in the parental lines. To address this question, we compared models with a single QTL-variance component with models allowing for separate sire and dam QTL-variance components. The same QTL were identified using a single QTL variance component model compared to a model allowing for separate variances with minor differences with respect to QTL location. However, the variance component method made it possible to detect QTL segregating in the paternal line (e.g. HAMB), the maternal lines (e.g. Ham) or in both (e.g. pHu). Combining association and linkage information among haplotypes improved slightly the significance of the QTL compared to an analysis using linkage information only

Mammary epithelial cell transformation: insights from cell culture and mouse models

Normal human mammary epithelial cells (HMECs) have a finite life span and do not undergo spontaneous immortalization in culture. Critical to oncogenic transformation is the ability of cells to overcome the senescence checkpoints that define their replicative life span and to multiply indefinitely – a phenomenon referred to as immortalization. HMECs can be immortalized by exposing them to chemicals or radiation, or by causing them to overexpress certain cellular genes or viral oncogenes. However, the most efficient and reproducible model of HMEC immortalization remains expression of high-risk human papillomavirus (HPV) oncogenes E6 and E7. Cell culture models have defined the role of tumor suppressor proteins (pRb and p53), inhibitors of cyclin-dependent kinases (p16(INK4a), p21, p27 and p57), p14(ARF), telomerase, and small G proteins Rap, Rho and Ras in immortalization and transformation of HMECs. These cell culture models have also provided evidence that multiple epithelial cell subtypes with distinct patterns of susceptibility to oncogenesis exist in the normal mammary tissue. Coupled with information from distinct molecular portraits of primary breast cancers, these findings suggest that various subtypes of mammary cells may be precursors of different subtypes of breast cancers. Full oncogenic transformation of HMECs in culture requires the expression of multiple gene products, such as SV40 large T and small t, hTERT (catalytic subunit of human telomerase), Raf, phosphatidylinositol 3-kinase, and Ral-GEFs (Ral guanine nucleotide exchange factors). However, when implanted into nude mice these transformed cells typically produce poorly differentiated carcinomas and not adenocarcinomas. On the other hand, transgenic mouse models using ErbB2/neu, Ras, Myc, SV40 T or polyomavirus T develop adenocarcinomas, raising the possibility that the parental normal cell subtype may determine the pathological type of breast tumors. Availability of three-dimensional and mammosphere models has led to the identification of putative stem cells, but more studies are needed to define their biologic role and potential as precursor cells for distinct breast cancers. The combined use of transformation strategies in cell culture and mouse models together with molecular definition of human breast cancer subtypes should help to elucidate the nature of breast cancer diversity and to develop individualized therapies