85 research outputs found
A function accounting for training set size and marker density to model the average accuracy of genomic prediction.
No full textPrediction of genomic breeding values is of major practical relevance in dairy cattle breeding. Deterministic equations have been suggested to predict the accuracy of genomic breeding values in a given design which are based on training set size, reliability of phenotypes, and the number of independent chromosome segments ([Formula: see text]). The aim of our study was to find a general deterministic equation for the average accuracy of genomic breeding values that also accounts for marker density and can be fitted empirically. Two data sets of 5'698 Holstein Friesian bulls genotyped with 50 K SNPs and 1'332 Brown Swiss bulls genotyped with 50 K SNPs and imputed to ∼600 K SNPs were available. Different k-fold (k = 2-10, 15, 20) cross-validation scenarios (50 replicates, random assignment) were performed using a genomic BLUP approach. A maximum likelihood approach was used to estimate the parameters of different prediction equations. The highest likelihood was obtained when using a modified form of the deterministic equation of Daetwyler et al. (2010), augmented by a weighting factor (w) based on the assumption that the maximum achievable accuracy is [Formula: see text]. The proportion of genetic variance captured by the complete SNP sets ([Formula: see text]) was 0.76 to 0.82 for Holstein Friesian and 0.72 to 0.75 for Brown Swiss. When modifying the number of SNPs, w was found to be proportional to the log of the marker density up to a limit which is population and trait specific and was found to be reached with ∼20'000 SNPs in the Brown Swiss population studied
Accuracy of direct genomic values for functional traits in Brown Swiss cattle
No full textIn this study, direct genomic values for the functional traits general temperament, milking temperament, aggressiveness, rank order in herd, milking speed, udder depth, position of labia, and days to first heat in Brown Swiss dairy cattle were estimated based on ∼777,000 (777k) single nucleotide polymorphism (SNP) information from 1,126 animals. Accuracy of direct genomic values was assessed by a 5-fold cross-validation with 10 replicates. Correlations between deregressed proofs and direct genomic values were 0.63 for general temperament, 0.73 for milking temperament, 0.69 for aggressiveness, 0.65 for rank order in herd, 0.69 for milking speed, 0.71 for udder depth, 0.66 for position of labia, and 0.74 for days to first heat. Using the information of ∼54,000 (54k) SNP led to only marginal deviations in the observed accuracy. Trying to predict the 20% youngest bulls led to correlations of 0.55, 0.77, 0.73, 0.55, 0.64, 0.59, 0.67, and 0.77, respectively, for the traits listed above. Using a novel method to estimate the accuracy of a direct genomic value (defined as correlation between direct genomic value and true breeding value and accounting for the correlation between direct genomic values and conventional breeding values) revealed accuracies of 0.37, 0.20, 0.19, 0.27, 0.48, 0.45, 0.36, and 0.12, respectively, for the traits listed above. These values are much smaller but probably also more realistic than accuracies based on correlations, given the heritabilities and samples sizes in this study. Annotation of the largest estimated SNP effects revealed 2 candidate genes affecting the traits general temperament and days to first heat
Short communication : Genomic prediction using imputed whole-genome sequence variants in Brown Swiss Cattle
No full textThe accuracy of genomic prediction determines response to selection. It has been hypothesized that accuracy of genomic breeding values can be increased by a higher density of variants. We used imputed whole-genome sequence data and various single nucleotide polymorphism (SNP) selection criteria to estimate genomic breeding values in Brown Swiss cattle. The extreme scenarios were 50K SNP chip data and whole-genome sequence data with intermediate scenarios using linkage disequilibrium-pruned whole-genome sequence variants, only variants predicted to be missense, or the top 50K variants from genome-wide association studies. We estimated genomic breeding values for 3 traits (somatic cell score, nonreturn rate in heifers, and stature) and found differences in accuracy levels between traits. However, among different SNP sets, accuracy was very similar. In our analyses, sequence data led to a marginal increase in accuracy for 1 trait and was lower than 50K for the other traits. We concluded that the inclusion of imputed whole-genome sequence data does not lead to increased accuracy of genomic prediction with the methods
How to Use Fewer Markers in Admixture Studies
No full textSwiss Fleckvieh has been established from 1970 as a composite of Simmental and Red Holstein Friesian cattle. Breed composition is currently reported based on pedigree information. Information on ancestry informative molecular markers potentially provides more accurate information. For the analysis Illumina Bovine SNP50 Beadchip data for 495 bulls were used. Markers were selected based on difference in allele frequencies in the pure populations, using FST as an indicator. Performance of sets with decreasing number of markers was compared. The scope of the study was to see how much we can reduce the number of markers based on FST to get a reliability that is close to that with the full set of markers. On these sets of markers hidden Markov models (HMM) and methods used in genomic selection (BayesB, partial least squares regression, LASSO variable selection) were applied. Correlations of admixture levels were estimated and compared with admixture levels based on pedigree information. FST chosen SNP gave very high correlations with pedigree based admixture. Only when using 96 and 48 SNP with the highest FST, correlations dropped to 0.92 and 0.90, respectively
Genome-wide association studies of fertility and calving traits in Brown Swiss cattle using imputed whole-genome sequences
No full textBACKGROUND:
The detection of quantitative trait loci has accelerated with recent developments in genomics. The introduction of genomic selection in combination with sequencing efforts has made a large amount of genotypic data available. Functional traits such as fertility and calving traits have been included in routine genomic estimation of breeding values making large quantities of phenotypic data available for these traits. This data was used to investigate the genetics underlying fertility and calving traits and to identify potentially causative genomic regions and variants. We performed genome-wide association studies for 13 functional traits related to female fertility as well as for direct and maternal calving ease based on imputed whole-genome sequences. Deregressed breeding values from ~1000-5000 bulls per trait were used to test for associations with approximately 10 million imputed sequence SNPs.
RESULTS:
We identified a QTL on BTA17 associated with non-return rate at 56 days and with interval from first to last insemination. We found two significantly associated non-synonymous SNPs within this QTL region. Two more QTL for fertility traits were identified on BTA25 and 29. A single QTL was identified for maternal calving traits on BTA13 whereas three QTL on BTA19, 21 and 25 were identified for direct calving traits. The QTL on BTA19 co-localizes with the reported BH2 haplotype. The QTL on BTA25 is concordant for fertility and calving traits and co-localizes with a QTL previously reported to influence stature and related traits in Brown Swiss dairy cattle.
CONCLUSION:
The detection of QTL and their causative variants remains challenging. Combining comprehensive phenotypic data with imputed whole genome sequences seems promising. We present a QTL on BTA17 for female fertility in dairy cattle with two significantly associated non-synonymous SNPs, along with five additional QTL for fertility traits and calving traits. For all of these we fine mapped the regions and suggest candidate genes and candidate variants
Optimizing selection of the reference population for genotype imputation from array to sequence variants
No full textImputation of high-density genotypes to whole-genome sequences (WGS) is a cost-effective method to increase the density of available markers within a population. Imputed genotypes have been successfully used for genomic selection and discovery of variants associated with traits of interest for the population. To allow for the use of imputed genotypes for genomic analyses, accuracy of imputation must be high. Accuracy of imputation is influenced by multiple factors, such as size and composition of the reference group, and the allele frequency of variants included. Understanding the use of imputed WGSs prior to the generation of the reference population is important, as accurate imputation might be more focused, for instance, on common or on rare variants. The aim of this study was to present and evaluate new methods to select animals for sequencing relying on a previously genotyped population. The Genetic Diversity Index method optimizes the number of unique haplotypes in the future reference population, while the Highly Segregating Haplotype selection method targets haplotype alleles found throughout the majority of the population of interest. First the WGSs of a dairy cattle population were simulated. The simulated sequences mimicked the linkage disequilibrium level and the variants' frequency distribution observed in currently available Holstein sequences. Then, reference populations of different sizes, in which animals were selected using both novel methods proposed here as well as two other methods presented in previous studies, were created. Finally, accuracies of imputation obtained with different reference populations were compared against each other. The novel methods were found to have overall accuracies of imputation of more than 0.85. Accuracies of imputation of rare variants reached values above 0.50. In conclusion, if imputed sequences are to be used for discovery of novel associations between variants and traits of interest in the population, animals carrying novel information should be selected and, consequently, the Genetic Diversity Index method proposed here may be used. If sequences are to be used to impute the overall genotyped population, a reference population consisting of common haplotypes carriers selected using the proposed Highly Segregating Haplotype method is recommended
Meta-analysis of sequence-based association studies across three cattle breeds reveals 25 QTL for fat and protein percentages in milk at nucleotide resolution
No full textAbstractBackgroundGenotyping and whole-genome sequencing data have been collected in many cattle breeds. The compilation of large reference panels facilitates imputing sequence variant genotypes for animals that have been genotyped using dense genotyping arrays. Association studies with imputed sequence variant genotypes allow characterization of quantitative trait loci (QTL) at nucleotide resolution particularly when individuals from several breeds are included in the mapping populations.ResultsWe imputed genotypes for more than 28 million sequence variants in 17,229 animals of the Braunvieh (BV), Fleckvieh (FV) and Holstein (HOL) cattle breeds in order to generate large mapping populations that are required to identify sequence variants underlying milk production traits. Within-breed association tests between imputed sequence variant genotypes and fat and protein percentages in milk uncovered between six and thirteen QTL (P<1e-8) per breed. Eight of the detected QTL were significant in more than one breed. We combined the association studies across three breeds using meta-analysis and identified 25 QTL including six that were not significant in the within-breed association studies. Closer inspection of the QTL revealed that two well-known causal missense mutations in theABCG2(p.Y581S, rs43702337, P=4.3e-34) andGHR(p.F279Y, rs385640152, P=1.6e-74) genes were the top variants at two QTL on chromosomes 6 and 20. Another true causal missense mutation in theDGAT1gene (p.A232K, rs109326954, P=8.4e-1436) was the second top variant at a QTL on chromosome 14 but its allelic substitution effects were not consistent across three breeds analyzed. It turned out that the conflicting allelic substitution effects resulted from flaws in the imputed genotypes due to the use of a multi-breed reference population for genotype imputation.ConclusionsMany QTL for milk production traits segregate across breeds. Metaanalysis of association studies across breeds has greater power to detect such QTL than within-breed association studies. True causal mutations can be readily detected among the most significantly associated variants at QTL when the accuracy of imputation is high. However, true causal mutations may show conflicting allelic substitution effects across breeds when the imputed sequence variant genotypes contain flaws. Validating the effect of known causal variants is highly recommended in order to assess the ability to detect true causal mutations in association studies with imputed sequence variant genotypes.</jats:sec
Breeding goal traits accounting for feed intake capacity and roughage or concentrate intake separately
No full textCurrent breeding tools aiming to improve feed efficiency use definitions based on total dry matter intake (DMI); for example, residual feed intake or feed saved. This research aimed to define alternative traits using existing data that differentiate between feed intake capacity and roughage or concentrate intake, and to investigate the phenotypic and genetic relationships among these traits. The data set contained 39,017 weekly milk yield, live weight, and DMI records of 3,164 cows. The 4 defined traits were as follows: (1) Feed intake capacity (FIC), defined as the difference between how much a cow ate and how much she was expected to eat based on diet satiety value and status of the cow (parity and lactation stage); (2) feed saved (FS), defined as the difference between the measured and the predicted DMI, based on the regression of DMI on milk components within experiment; (3) residual roughage intake (RRI), defined as the difference between the measured and the predicted roughage intake, based on the regression of roughage intake on milk components and concentrate intake within experiment; and (4) residual concentrate intake (RCI), defined as the difference between the measured and the predicted concentrate intake, based on the regression of concentrate intake on milk components and roughage intake within experiment. The phenotypic correlations were −0.72 between FIC and FS, −0.84 between FS and RRI, and −0.53 between FS and RCI. Heritability of FIC, FS, RRI, and RCI were estimated to be 0.21, 0.12, 0.15, and 0.03, respectively. The genetic correlations were −0.81 between FS and FIC, −0.96 between FS and RRI, and −0.25 between FS and RCI. Concentrate intake and RCI had low heritability. Genetic correlation between DMI and FIC was 0.98. Although the defined traits had moderate phenotypic correlations, the genetic correlations between DMI, FS, FIC, and RRI were above 0.79 (in absolute terms), suggesting that these traits are genetically similar. Therefore, selecting for FIC is expected to simply increase DMI and RRI, and there seems to be little advantage in separating concentrate and roughage intake in the genetic evaluation, because measured concentrate intake was determined by the feeding system in our data and not by the genetics of the cow
Developing communities of practice and research through research informed teaching and learning in cross-cultural groups.
No full textThis conceptual research aims to answer three questions:
• What is the process for learning where teachers and learners research together?
• How can this process be enriched and enhanced, specifically working within an international
and cross-cultural student population?
• How can a co-existence of a pedagogic research informed learning and teaching environment
be embedded with staff and students?
This research looks into the way staff research informs pedagogic practice, and how staff work as
’joint partners’ with students to deliver more ’iterative’ education learning models. The research is aimed at the development of inclusive scholarly knowledge-building communities of practice (see Brew, 2006). The research highlights how staff work with students in an iterative communal process through project-based research activity and collaborative teamwork within cross-cultural groups. It also describes the processes of working with students and how it has helped to directly reinforce the curricula and informed the author’s own learning and teaching strategies. Significantly, this type of open engagement with cultural groups has alerted the author to howtraditional linear ’Western’ forms of academic research within art and design can be influenced by Eastern models of research enquiry. The research describes a coexistence of practice where research and enquiry can be fluidly exchanged between teacher and student.
Changes were made to curricula to develop a more social constructivist form of working (Gredler,
1997) where both the context in which learning occurs and the social contexts that learners bring
to their learning environment were put centre stage. A short film entitled Event digestion, a
pedagogic filmic picnic, where students came together to form a community event, highlighted
this process. This process was also one of cross-disciplinary staff team-working within art and
design where research work is enhanced through creating a more open social experiential learning
environment.
The research methodology is a predominantly qualitative one through problem solving and action
research. It is also situated within a pedagogic research-informed teaching approach where
teaching draws upon enquiry into the teaching and learning process itself (Jenkins & Healey,
2005). Methods incorporated have been cross-cultural international focus groups attended by
students, ’unstructured’ interviews, student case studies and, importantly, practice-based work.
The paper highlights how an active educational model can be developed through learning by
doing (Gibbs, 1998) and thinking (Ramsden, 2003), however, coming from a perspective which
addresses creativity across cultures (Lubart), is cross-disciplinary, and, importantly, by a practicebase collaborative international team project approach. The practical pedagogic findings will be of use to anyone working in design education wishing to develop cross-cultural curricula through practice-based learning and research
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