学会抄録

A description of the results of the cross platform (385 K CGH and SNP50 chip) verification of CNV regions [72, 73]. (PDF 8 kb

Genomic selection and scan for major genes for a new lamb survival trait for the New Zealand sheep industry

Lambing percentage is one of the most significant factors affecting profitability on New Zealand sheep farms. Since the early 1990s, lambing percentage has increased at about 1% per year from a relatively stable level of approximately 100%, and top performing sheep farms are now consistently achieving 150% or more. As lambing percentage increases, the proportion of ewes bearing twins and triplets increases accordingly. Lamb mortality rate in these multiples is higher than in singles, with triplets being particularly susceptible. Consequently, lamb survival has become increasingly important to the New Zealand sheep industry. Sheep Improvement Ltd. (SIL, New Zealand’s national sheep genetic evaluation system owned by Beef + Lamb NZ) records lamb survival to weaning but genetic improvement has been limited due to the low heritability of the trait and the current method of recording. To address those issues, we have developed an improved survival to weaning trait for industry implementation, which is more accurate and more heritable than the current SIL trait. This poster will present results of applying genome-enabled prediction procedures to the new trait to obtain molecular breeding values. It will also describe results from a genome wide association study using the new trait

Derivation of a new lamb survival trait for the New Zealand sheep industry

Previous research identified that a review of the current industry New Zealand lamb survival trait was necessary as its recording accuracy was reliant on farmers notifying their Sheep Improvement Limited bureau of lamb deaths. This paper reports the decision rules and genetic parameters for a new lamb survival trait for the New Zealand sheep industry. These rules define the new lamb survival trait (NEWSUR) using lamb birth fate (BFATE) codes and the presence/absence of lamb weight measurements. Six univariate animal models were tested and used to estimate variance or covariance components and the resulting direct and maternal heritabilities for NEWSUR. The models differed in the way they adjust for the effect of day of birth, the exclusion or inclusion of a litter (dam/year of birth) random effect and the application or not of a logit transformation of the phenotypes. For both the linear and logistic methods, models including the random effect of litter provided the best fit for NEWSUR according to log-likelihood values. Log-likelihoods for the linear and logistic models cannot be compared, therefore a cross-validation method was used to assess whether the logit transformation was appropriate by analyzing the predictive ability of the models. The mean square errors were slightly lower for the linear compared to the logistic model and therefore the linear model was recommended for industry use. The heritability attributed to direct effects ranged from 2 to 5.5%. A direct heritability of 5.5% resulted from a linear model without litter effect and omitting the effect of day of birth on survival, whereas a direct heritability of 2% resulted from the logistic model fitting a random litter effect. The heritability attributed to maternal genetic effects ranged from 1.9 to 7.7%. A maternal genetic heritability of 7.7% resulted from the logistic model omitting the litter effect, whereas a maternal genetic heritability of 1.9% resulted from the linear model fitting a random litter effect. The addition of the litter random effect decreased the maternal heritabilities substantially in all cases and was recommended for industry use to avoid overestimation of the maternal genetic variance. SIL has implemented NEWSUR and the associated genetic evaluation model based on information described in this paper. Industry wide implementation will enable sheep breeders to produce more accurate genetic evaluations to their commercial clients

Derivation of a new lamb survival trait for implementation in the New Zealand sheep industry

Lambing percentage is one of the most significant factors affecting profitability on New Zealand sheep farms. Since the early 1990s, lambing percentage has increased at about 1% per year from a relatively stable level of approximately 100%, and top performing sheep farms are now consistently achieving 150% or more. As lambing percentage increases, the proportion of ewes bearing twins and triplets increases accordingly. Lamb mortality rate in these multiples is higher than in singles, with triplets being particularly susceptible. Consequently, lamb survival has become increasingly important to the New Zealand sheep industry. Sheep Improvement Ltd (SIL, New Zealand's national sheep genetic evaluation system provided by Beef & Lamb NZ) records lamb survival to weaning but genetic improvement has been limited due to the low heritability of the trait and the current method of recording

Additional file 3: of Genomic prediction and genome-wide association study for dagginess and host internal parasite resistance in New Zealand sheep

Output of protein domain matches from InterProScan 5 search of the 100kbp window around SNP s22390 located at OAR15: 40210579 on OARv3.1. (CSV 110 kb

Copy number variants in the sheep genome detected using multiple approaches

Background: Copy number variants (CNVs) are a type of polymorphism found to underlie phenotypic variation, both in humans and livestock. Most surveys of CNV in livestock have been conducted in the cattle genome, and often utilise only a single approach for the detection of copy number differences. Here we performed a study of CNV in sheep, using multiple methods to identify and characterise copy number changes. Comprehensive information from small pedigrees (trios) was collected using multiple platforms (array CGH, SNP chip and whole genome sequence data), with these data then analysed via multiple approaches to identify and verify CNVs. Results: In total, 3,488 autosomal CNV regions (CNVRs) were identified in this study, which substantially builds on an initial survey of the sheep genome that identified 135 CNVRs. The average length of the identified CNVRs was 19kb (range of 1kb to 3.6Mb), with shorter CNVRs being more frequent than longer CNVRs. The total length of all CNVRs was 67.6Mbps, which equates to 2.7% of the sheep autosomes. For individuals this value ranged from 0.24 to 0.55%, and the majority of CNVRs were identified in single animals. Rather than being uniformly distributed throughout the genome, CNVRs tended to be clustered. Application of three independent approaches for CNVR detection facilitated a comparison of validation rates. CNVs identified on the Roche-NimbleGen 2.1M CGH array generally had low validation rates with lower density arrays, while whole genome sequence data had the highest validation rate (>60%). Conclusions: This study represents the first comprehensive survey of the distribution, prevalence and characteristics of CNVR in sheep. Multiple approaches were used to detect CNV regions and it appears that the best method for verifying CNVR on a large scale involves using a combination of detection methodologies. The characteristics of the 3,488 autosomal CNV regions identified in this study are comparable to other CNV regions reported in the literature and provide a valuable and sizeable addition to the small subset of published sheep CNVs

Towards a turbulence characterization in tidal energy sites. First results of THYMOTE project

Tidal turbine will be installed in area with high current and high turbulence level. A characterisation of this last is required. The aim of the project THYMOTE is to characterize and understand the generation of eddies from smaller to several tens of meters. Three technics are used: Numerical modelling, Physical modelling, field measurements. Physical and numerical modelling show clearly the appearance of the eddies close to the bottom in presence of dunes or rocks and their motion towards the free surface