Biomedical subjects

Norbert Reinsch

Publications and source records attributed to Norbert Reinsch.

9 recordsLinked to original sources

PubMed2004

Multiple quantitative trait loci mapping with cofactors and application of alternative variants of the false discovery rate in an enlarged granddaughter design.

The experimental power of a granddaughter design to detect quantitative trait loci (QTL) in dairy cattle is often limited by the availability of progeny-tested sires, by the ignoring of already identified QTL in the statistical analysis, and by the application of stringent experimentwise significance levels. This study describes an experiment that addressed these points. A large granddaughter design was set up that included sires from two countries (Germany and France), resulting in almost 2000 sires. The animals were genotyped for markers on nine different chromosomes. The QTL analysis was done for six traits separately using a multimarker regression that included putative QTL on other chromosomes as cofactors in the model. Different variants of the false discovery rate (FDR) were applied. Two of them accounted for the proportion of truly null hypotheses, which were estimated to be 0.28 and 0.3, respectively, and were therefore tailored to the experiment. A total of 25 QTL could be mapped when cofactors were included in the model-7 more than without cofactors. Controlling the FDR at 0.05 revealed 31 QTL for the two FDR methods that accounted for the proportion of truly null hypotheses. The relatively high power of this study can be attributed to the size of the experiment, to the QTL analysis with cofactors, and to the application of an appropriate FDR.

Animals↗

PubMed2004

[QTL mapping for ear shape based on a commercial pig population].

A commercial pig population, including 19 hybrid boars [Piétrain x (Piétrain x Hampshire), 52 hybrid sows [Leicoma x (Large White x Landrace)] and their 332 offspring, was used to construct a reference pedigree, with which a linkage map of whole genome was created using 172 microsatellite markers and three type-1 markers (RYR1, PRKAG3, PIT1). The average of the notes of ear shape (pricky ear shape noted by 1; middle ear shape noted by 0; floppy ear noted by -1) detected by a trained technician is 0.23 and the variation 0.82. QTL mapping for ear shape was carried out with the least square regression method. The result showed that only one QTL for ear shape was detected at 1% genomewise level at the end (between Sw1881 and Sw322) of the chromosome 6 and no QTL was found on the other chromosomes even at 10% chromosome-wise level.

Animals↗

PubMed2004

[Amplification of pig microsatellite markers using multiplex PCR].

In order to rapidly amplify pig microsatellite markers and save materials,multiplex PCR was used and its reaction condition was optimized. Forty-six combinations of multiplex PCR with good effects were obtained. Thirty of them are duplex-PCRs, sixteen are triplex-PCRs. The results of multiplexes showed that the concentration of primers varied among 0.06 approximately 0.3 micromol/L, the Mg(2+) concentration among 1.5 approximately 3.0 mmol/L; 0.2 approximately 0.4 U of Taq polymerase and 1.0-, 1.2-, 1.4-, 1.6-fold buffer were used, the annealing temperature and the cycle number varied among 52 approximately 60 degrees and 32 approximately 50 degrees, respectively. All multiplexes were further combined into 17 sets for the electrophoresis on ABI 377 sequencer.

Animals↗

PubMed2004

[Comparison between the female- and male-linkage maps in pigs].

The difference between the length of female- and male-linkage map, which was created with a reference pedigree based on a commercial porcine population and using 163 microsatellite markers as well as 3 type-I markers (RYR1, PRKAG3, PIT1), was statistic analyzed. The results showed that the total length of female linkage map of autosomes is 2625.9 cm and the total length of the male linkage map is 2259.7 cm; the ratio between the total length of the female- and male-linkage maps is 1.16 : 1; except for the chromosomes 1 and 14, the female linkage maps of the other chromosomes are longer than the male linkage maps. The difference between the length of female- and male-linkage maps of chromosomes 1, 3, 5, 6, 7, 8, 10, 11, 12, 13, 14, 16, 17 and 18 is very significant (P<0.01) and the difference of chromosome 9 is significant (P<0.05); but there is no significance on chromosomes 2, 4, 12 and 15.

Animals↗

PubMed2003

[A porcine linkage map of microsatellite markers using a commercial population as a reference].

A commercial population created with 19 hybrid boars [Piétrain x (Piétrain x Hampshire)], 52 hybrid sows [Leicoma x (Large White x Landrace)] and their 332 offspring was used to construct a whole genome porcine linkage map. The genetic markers used in this study include 172 microsatellite markers and 3 type- I markers (RYR1, PIT1 and PRKAG3). All microsatellite markers were genotyped using multiplex PCR reactions and visualized on ABI 377 sequencer. Three type I markers were assayed using PCR-RFLP technique. CRIMAP (2.4) analysis revealed a total length of the sex-averaged map for SSC1-SSC18 by 2449.2 cM and the length of SSCX by 143.1 cM. The average interval distance accounts to 16.3 cM. The heterozygosity of the parents at the microsatellite loci averaged 0.70. This map will play an important role in screening of QTL for growth, carcass and meat quality and reproduction in commercial populations.

Animals↗

PubMed2002

Improved confidence intervals in quantitative trait loci mapping by permutation bootstrapping.

The nonparametric bootstrap approach is known to be suitable for calculating central confidence intervals for the locations of quantitative trait loci (QTL). However, the distribution of the bootstrap QTL position estimates along the chromosome is peaked at the positions of the markers and is not tailed equally. This results in conservativeness and large width of the confidence intervals. In this study three modified methods are proposed to calculate nonparametric bootstrap confidence intervals for QTL locations, which compute noncentral confidence intervals (uncorrected method I), correct for the impact of the markers (weighted method I), or both (weighted method II). Noncentral confidence intervals were computed with an analog of the highest posterior density method. The correction for the markers is based on the distribution of QTL estimates along the chromosome when the QTL is not linked with any marker, and it can be obtained with a permutation approach. In a simulation study the three methods were compared with the original bootstrap method. The results showed that it is useful, first, to compute noncentral confidence intervals and, second, to correct the bootstrap distribution of the QTL estimates for the impact of the markers. The weighted method II, combining these two properties, produced the shortest and less biased confidence intervals in a large number of simulated configurations.

Chromosome Mapping↗

PubMed2002

A general likelihood approach to trait-based multipoint linkage analysis in large groups of half-sibs and super sisters.

The idea of trait-based linkage analysis in half-sibs is extended by comparing the frequency of parental marker haplotypes in animals with different phenotypes. This article first presents the likelihood of observing different classes of paternal haplotypes in a half-sib family, where only family members of a certain phenotype (e.g., affected) are genotyped and are fully informative. The likelihood function is then generalized to multiple phenotypic categories. A linear predictor allows for discontinuous as well as for continuous phenotypes and other explanatory variables. Finally, how to incorporate not fully informative offspring and how to analyze super sister families are shown. Maximum-likelihood estimates of all parameters can be found by a Newton-Raphson algorithm, which mimics an iteratively weighted least-squares procedure. The method allows for any multilocus feasible mapping function and, among others, for situations with selective or nonselective genotyping, single or multiple traits, and continuous or categorical traits. No parameters are required to describe the mode of inheritance and the method copes with virtually any family size. Fields of applications are therefore mapping experiments in species with a high reproductive capacity, such as cattle, pigs, horses, honey bees, trees, and fish.

Animals↗

PubMedDate not supplied

Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle.

A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data were exchanged in a coded and standardised form. The combined data set (JOINT-design) consisted of on average 231 sires per grandsire. Genetic maps were calculated for 133 markers distributed over nine chromosomes. QTL analyses were performed separately for each design and each trait. The results revealed QTL for milk production on chromosome 14, for milk yield on chromosome 5, and for fat content on chromosome 19 in both the ADR- and the Inra-design (confirmed within this study). Some QTL could only be mapped in either the ADR- or in the Inra-design (not confirmed within this study). Additional QTL previously undetected in the single designs were mapped in the JOINT-design for fat yield (chromosome 19 and 26), protein yield (chromosome 26), protein content (chromosome 5), and somatic cell score (chromosome 2 and 19) with genomewide significance. This study demonstrated the potential benefits of a combined analysis of data from different granddaughter designs.

Animals↗

PubMedDate not supplied

Identification of gametes and treatment of linear dependencies in the gametic QTL-relationship matrix and its inverse.

The estimation of gametic effects via marker-assisted BLUP requires the inverse of the conditional gametic relationship matrix G. Both gametes of each animal can either be identified (distinguished) by markers or by parental origin. By example, it was shown that the conditional gametic relationship matrix is not unique but depends on the mode of gamete identification. The sum of both gametic effects of each animal--and therefore its estimated breeding value--remains however unaffected. A previously known algorithm for setting up the inverse of G was generalized in order to eliminate the dependencies between columns and rows of G. In the presence of dependencies the rank of G also depends on the mode of gamete identification. A unique transformation of estimates of QTL genotypic effects into QTL gametic effects was proven to be impossible. The properties of both modes of gamete identification in the fields of application are discussed.

Algorithms↗