No abstract

The Baluchi breed is the most common native breed of Iran adapted to harsh environments in the eastern parts of the country. The data used in the present study, collected from two research flocks at the Abbasabad sheep breeding station in north-east Iran, included 20 534 animals descended from 363 sires, 5992 dams, 282 maternal grandsires, and 2865 maternal granddams during the period 1966 to 1989. The traits recorded were: birth weight (BW), weaning weight (WW), weight at 6 months (W6), weight at 12 months (YW), pre-weaning gain (WG), postweaning gain (PWG), lamb fleece weight (LFW), ewe fleece weight sheared before first joining (FW1) and adult ewe fleece weight (FW). Genetic parameters, estimated with restricted maximum likelihood and a two-trait animal model, were similar in the two flocks. Direct heritabilities for the various body weight traits were moderate and varied between 0-13 and 0-32, while the maternal heritabilities were low and varied between 0-01 and 0-12. Direct and maternal genetic correlations between WW and weights at later ages were moderate to high (0-59 to 0-96). Direct heritabilities of weight gain measures varied between 0-12 and 0-19, while no significant maternal influence on either of these weight gain measures could be detected. The estimates of direct genetic correlation between WG and PWG were positive and varied between 0-54 and 0-74, while negative maternal genetic correlation (-0-17 on average) between WG and PWG was detected. For LFW, direct heritability was low and no maternal heritability could be shown. For FW1, both direct and maternal genetic influences were demonstrated (0-07 to 0-26). Direct genetic correlation between LFW and FW1 was very low and close to zero, while maternal genetic correlation was positive and relatively high (0-72 on average). The relative contributions to phenotypic variance from variance components due to common environmental effects ranged from 0-01 to 0-15 for all traits. The repeatability of FW was low (0-03 to 0-12).

Due to computational demand, elements of genetic correlation matrices may have been estimated separately and then combined together into a single correlation matrix at a later stage. Because these matrices should be positive definite (PD) a statistical method commonly known as "bending" is used to make them positive definite. The conventional bending method ignores the reliability of different correlations and may subject any of them to change in order to make a positive definite correlation matrix. A simple method to obtain a weighted bended matrix to be used in animal breeding applications is proposed, and the implementation of the method is demonstrated by an example.

The effect of selection for high phenotypic value in the presence of a genotype by environment interaction (G ✕ E, i.e. genetic variation for environmental sensitivity) and an improving environment was studied in a simulation. Environmental sensitivity was evaluated by using reaction norms, which describe the phenotype expressed by a genotype as a function of the environment. Three types of reaction norms (linear, quadratic and sigmoid), and two selection schemes (mass selection and progeny test selection) were studied. Environmental sensitivity was measured as the weighted average of the absolute value of the first derivative of the reaction norm function. Results showed that environmental sensitivity increased in response to selection for high phenotypic value in the presence of G ✕ E and an improving environment when reaction norms were linear or quadratic. For sigmoid reaction norms, approximating threshold characters, environmental sensitivity increased within the environmental range encompassing the threshold. With mass selection and/or non-linear reaction norms, environmental sensitivity increased even without environmental change.

BackgroundIn recent years, the use of genomic information in livestock species for genetic improvement, association studies and many other fields has become routine. In order to accommodate different market requirements in terms of genotyping cost, manufacturers of single nucleotide polymorphism (SNP) arrays, private companies and international consortia have developed a large number of arrays with different content and different SNP density. The number of currently available SNP arrays differs among species: ranging from one for goats to more than ten for cattle, and the number of arrays available is increasing rapidly. However, there is limited or no effort to standardize and integrate array- specific (e.g. SNP IDs, allele coding) and species-specific (i.e. past and current assemblies) SNP information.ResultsHere we present SNPchiMp v.3, a solution to these issues for the six major livestock species (cow, pig, horse, sheep, goat and chicken). Original data was collected directly from SNP array producers and specific international genome consortia, and stored in a MySQL database. The database was then linked to an open-access web tool and to public databases. SNPchiMp v.3 ensures fast access to the database (retrieving within/across SNP array data) and the possibility of annotating SNP array data in a user-friendly fashion.ConclusionsThis platform allows easy integration and standardization, and it is aimed at both industry and research. It also enables users to easily link the information available from the array producer with data in public databases, without the need of additional bioinformatics tools or pipelines. In recognition of the open-access use of Ensembl resources, SNPchiMp v.3 was officially credited as an Ensembl E!mpowered tool. Availability at http://bioinformatics.tecnoparco.org/SNPchimp.