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H P Piepho

Publications and source records attributed to H P Piepho.

17 recordsLinked to original sources
PubMed2006

A comparison of experimental designs for selection in breeding trials with nested treatment structure.

Plant breeders frequently evaluate large numbers of entries in field trials for selection. Generally, the tested entries are related by pedigree. The simplest case is a nested treatment structure, where entries fall into groups or families such that entries within groups are more closely related than between groups. We found that some plant breeders prefer to plant close relatives next to each other in the field. This contrasts with common experimental designs such as the alpha-design, where entries are fully randomized. A third design option is to randomize in such a way that entries of the same group are separated as much as possible. The present paper compares these design options by simulation. Another important consideration is the type of model used for analysis. Most of the common experimental designs were optimized assuming that the model used for analysis has fixed treatment effects. With many entries that are related by pedigree, analysis based on a model with random treatment effects becomes a competitive alternative. In simulations, we therefore study the properties of best linear unbiased predictions (BLUP) of genetic effects based on a nested treatment structure under these design options for a range of genetic parameters. It is concluded that BLUP provides efficient estimates of genetic effects and that resolvable incomplete block designs such as the alpha-design with restricted or unrestricted randomization can be recommended.

Breeding↗
PubMed2006

Combining signals from spotted cDNA microarrays obtained at different scanning intensities.

MOTIVATION: The analysis of spotted cDNA microarrays involves scanning of color signals from fluorescent dyes. A common problem is that a given scanning intensity is not usually optimal for all spotted cDNAs. Specifically, some spots may be at the saturation limit, resulting in poor separation of signals from different tissues or conditions. The problem may be addressed by multiple scans with varying scanning intensities. Multiple scanning intensities raise the question of how to combine different signals from the same spot, particularly when measurement error is not negligible. RESULTS: This paper suggests a non-linear latent regression model for this purpose. It corrects for biases caused by the saturation limit and efficiently combines data from multiple scans. Combining multiple scans also allows reduction of technical error particularly for cDNA spots with low signal. The procedure is exemplified using cDNA expression data from maize. AVAILABILITY: All methods were implemented using standard procedures available in the SAS/STAT module of the SAS System. Programming statements are available from the first author upon request. CONTACT: piepho@uni-hohenheim.de SUPPLEMENTARY INFORMATION: The supplementary data are available at Bioinformatics online.

DNA, Complementary↗
PubMed2006

The effect of feather eating on feed passage in laying hens.

Previous work has demonstrated an association between feather pecking and feather eating in laying hens. This raised the question of the dietary effect of feathers. We hypothesized that feathers, as indigestible components, have similar effects as insoluble fiber, i.e., speeding up feed passage. Twenty-four adult laying hens each of a high (H) and a low (L) feather pecking line were kept in individual cages and fed a commercial pelleted diet ad libitum. One-half of each line was offered downy feathers (HF; LF) of the same genetic line. The other half of the birds were kept as control without access to feathers (H0; L0). After a 6-wk feeding period, 5 birds of each group were selected for determination of feed passage. The HF birds with the highest number of feathers eaten and the LF birds with the lowest number of feathers eaten were used. Selection of L0 and H0 birds was carried out at random. Feed passage was determined over 48 h using titanium dioxide as a marker. The number of feathers eaten was significantly higher in HF birds than in LF birds before (P < 0.001) and during 48 h of marker excretion (P < 0.02). The time when 50% of the plateau level of excretion of the TiO2 was reached differed significantly among all groups; the shortest time was observed for the HF group (P < 0.05). The results clearly show that feathers increase the speed of feed passage and, in this regard, show similar effects as insoluble fiber. The dietary effect of feathers may be a crucial factor in the development of feather pecking and the related damages to the feather cover in laying hens.

Animals↗
PubMed2005

Permutation tests for the correlation among genetic distances and measures of heterosis.

It is often found that heterosis tends to increase with genetic distance of the parents, though the correlation is not usually very close. It is therefore important to test the null hypothesis that the correlation is zero. The present work shows that standard procedures tend to yield too liberal tests, owing to the lack of independence among genetic distances and among heterosis estimates. A valid alternative is to use a permutation test, which was first suggested by Mantel [(1967) Cancer Res 27: 209--220). This test is well-known among plant breeders and geneticists, who often use it to test the correlation among two distance matrices. Its use is not restricted to the comparison of distance matrices. This is demonstrated in the present work, using two published datasets on marker-based genetic distances of maize inbreds or populations and heterosis of their crosses. It is shown that the test is also applicable in the presence of missing data.

Breeding↗
PubMed2005

Statistical tests for QTL and QTL-by-environment effects in segregating populations derived from line crosses.

Quantitative trait locus (QTL) studies in plants frequently employ phenotypic data on a population of lines (doubled haploid lines, recombinant inbred lines, etc.) tested in multiple environments. An important feature of such data is the genetic correlation among observations on the same genotype in different environments. Detection of QTL-by-environment interaction requires tests which take this correlation into account. In this article, a comparison was made of the properties of several such tests by means of simulation. The results indicate that a split-plot analysis of variance (ANOVA), being an approximate method, tends to be too liberal under departures from the Huynh-Feldt condition. A standard two-way ANOVA, which ignores genetic correlation, yields inappropriate tests and should be avoided. In contrast, mixed model approaches as well as univariate and multivariate repeated-measures ANOVA yield valid results. This supports the use of a flexible mixed model framework in more complex settings, which are difficult to tackle by repeated-measures ANOVA. .

Environment↗
PubMed2004

Digesta characteristics of dorsal, middle and ventral rumen of cows fed with different hay qualities and concentrate levels.

The influence of fibre content of hay (H) and concentrate level (C) on local differences in the composition of ruminal digesta (ratio of solid to fluid digesta, DM, NDF, ADF and ADL content), particle size (MPL), specific gravity (SG) and fermentation (pH and concentrations of SCFA and bicarbonate) have been tested on two ruminally cannulated Friesian cows (520 kg BW) which were fed restricted, using individual cows as experimental units. Digesta samples were collected via cannula from three rumen layers: 5 to 10 cm (top) and 25-35 cm beneath the top of the particle mat (middle) and 5-10 cm above the rumen floor (bottom). For a main plot treatment (H x C), repeated samples were collected at four time intervals (1 h before and 2, 5 and 10 h after morning feeding) on each of two days. From top to bottom rumen the share of solid digesta mass (SM), DM and NDF contents of squeezed digesta fluid (SRF) and concentration of SCFA decreased (P < 0.05); pH and bicarbonate concentration increased (P < 0.05), while DM, NDF, ADF and ADL contents in SM, MPL and SG did not differ. Higher NDF content of hay (from 47-62%) increased SM, fibre fractions in SM, MPL, pH and concentration of bicarbonate in ruminal digesta, especially when 50% concentrate was given, while SG decreased. When the concentrate level was enhanced from 20 to 50%, digesta SM, MPL and the content of DM and NDF in SRF increased, while pH, concentrations of SCFA and acetate decreased when low-fibre hay was given. With longer time after feeding the digesta SM was reduced and fibre content in SM increased. The increase of the fibre content of hay reduced the possible negative effect of high concentrate level on the stratification of ruminal digesta. The decrease of the fibre content of hay promised better conditions for fibre digestion in the rumen when concentrate availability is limited.

Animal Feed↗
PubMed2004

Effect of supplementation of xylanase and phospholipase to a wheat-based diet for weanling pigs on nutrient digestibility and concentrations of microbial metabolites in ileal digesta and feces.

The objective of this study was to determine the effect of supplementing a wheat-based diet with xylanase and phospholipase either alone or in combination on the ileal and fecal digestibilities of nutrients and energy in early-weaned pigs. In addition, the concentrations of ammonia, lactate, and VFA were measured in ileal digesta and feces. The experiment was carried out with 16 barrows weaned at the age of 11 d with an average initial BW of 4.1 kg. On d 4 and 5 postweaning, the piglets were fitted with a simple T-cannula at the distal ileum. The experiment was designed as a balanced incomplete block design with three periods. The piglets received the basal diet with or without supplementation of either xylanase or phospholipase or a combination of these. There was a positive (P = 0.005 to 0.018) effect on the digestibility values of GE, OM, CP, crude fiber (CF), and NDF with xylanase supplementation. Apart from lysine, threonine, cysteine, glycine, and proline, the digestibility values of all AA were improved (P = 0.001 to 0.024). Phospholipase supplementation had a positive effect on CP (P = 0.047) and CF (P = 0.002) digestibilities, but no effect on ether extract (EE) digestibility. Supplementation of both enzymes showed the largest response in nutrient digestibilities, except that EE digestibility was not affected. No differences were found in D-/L- lactate, and ammonia concentrations among treatments. Acetate and propionate concentrations tended to increase when xylanase was supplemented and were highest for the combination of both enzymes. Despite the positive effects on ileal nutrient and energy digestibilities, there was no effect of xylanase or the combined enzyme supplementation on the fecal digestibilities of OM, CP, EE, CF, NDF, ADF, or GE, and on fecal concentrations of VFA. Phospholipase alone slightly decreased the total-tract nutrient and energy digestibilities (P < 0.05). In conclusion, the combination of both enzymes generally led to the highest increases in ileal digestibilities, which were of small numerical magnitude (approximately 2%). However, on a relative basis, this increase of 2% represents approximately 13% of the remaining diet that was available for digestion based on the fact that approximately 15% of the diet was not digested in the control pigs. Thus, the potential benefits in the nutrition of weanling pigs from combinations of enzymes should be validated under practical conditions.

Animals↗
PubMed2002

Determining the sample size for co-dominant molecular marker-assisted linkage detection for a monogenic qualitative trait by controlling the type-I and type-II errors in a segregating F2 population.

Tests for linkage are usually performed using the lod score method. A critical question in linkage analyses is the choice of sample size. The appropriate sample size depends on the desired type-I error and power of the test. This paper investigates the exact type-I error and power of the lod score method in a segregating F(2) population with co-dominant markers and a qualitative monogenic dominant-recessive trait. For illustration, a disease-resistance trait is considered, where the susceptible allele is recessive. A procedure is suggested for finding the appropriate sample size. It is shown that recessive plants have about twice the information content of dominant plants, so the former should be preferred for linkage detection. In some cases the exact alpha-values for a given nominal alpha may be rather small due to the discrete nature of the sampling distribution in small samples. We show that a gain in power is possible by using exact methods.

Crosses, Genetic↗
PubMed2001

A quick method for computing approximate thresholds for quantitative trait loci detection.

This article proposes a quick method for computing approximate threshold levels that control the genome-wise type I error rate of tests for quantitative trait locus (QTL) detection in interval mapping (IM) and composite interval mapping (CIM). The procedure is completely general, allowing any population structure to be handled, e.g., BC(1), advanced backcross, F(2), and advanced intercross lines. Its main advantage is applicability in complex situations where no closed form approximate thresholds are available. Extensive simulations demonstrate that the method works well over a range of situations. Moreover, the method is computationally inexpensive and may thus be used as an alternative to permutation procedures. For given values of the likelihood-ratio (LR)-profile, computations involve just a few seconds on a Pentium PC. Computations are simple to perform, requiring only the values of the LR statistics (or LOD scores) of a QTL scan across the genome as input. For CIM, the window size and the position of cofactors are also needed. For the approximation to work well, it is suggested that scans be performed with a relatively small step size between 1 and 2 cM.

Biometry↗
PubMed2001

Marker pair selection for mapping quantitative trait loci.

Mapping of quantitative trait loci (QTL) for backcross and F(2) populations may be set up as a multiple linear regression problem, where marker types are the regressor variables. It has been shown previously that flanking markers absorb all information on isolated QTL. Therefore, selection of pairs of markers flanking QTL is useful as a direct approach to QTL detection. Alternatively, selected pairs of flanking markers can be used as cofactors in composite interval mapping (CIM). Overfitting is a serious problem, especially if the number of regressor variables is large. We suggest a procedure denoted as marker pair selection (MPS) that uses model selection criteria for multiple linear regression. Markers enter the model in pairs, which reduces the number of models to be considered, thus alleviating the problem of overfitting and increasing the chances of detecting QTL. MPS entails an exhaustive search per chromosome to maximize the chance of finding the best-fitting models. A simulation study is conducted to study the merits of different model selection criteria for MPS. On the basis of our results, we recommend the Schwarz Bayesian criterion (SBC) for use in practice.

Chromosome Mapping↗
PubMed2000

Optimal marker density for interval mapping in a backcross population.

An important question in QTL mapping is the optimal choice of marker density. Using analytical results, it is shown for the case of interval mapping in a backcross population, that the power of QTL detection and the standard errors of genetic effect estimates are little affected by an increase of marker density beyond 10 cM. This finding confirms published simulation results by other authors.

Analysis of Variance↗
PubMed2000

Codominant analysis of banding data from a dominant marker system by normal mixtures.

Amplified fragment length polymorphisms (AFLPs) currently are among the most widely used marker systems. In many studies, AFLPs are analyzed on the basis of the presence or absence of a band on an electrophoretic gel. As a result, dominant homozygous individuals are not distinguished from heterozygous individuals, resulting in a considerable loss of information. This article shows how codominant information can be obtained if the amount of PCR products is quantified. Due to measurement variation, genotyping on the basis of such information is not error-free. We propose use of normal mixture distributions to determine the most likely genotype, given the data. The method is exemplified using AFLP data from sugar beet.

Analysis of Variance↗
PubMed2000

A mixed-model approach to mapping quantitative trait loci in barley on the basis of multiple environment data.

In this article, I propose a mixed-model method to detect QTL with significant mean effect across environments and to characterize the stability of effects across multiple environments. I demonstrate the method using the barley dataset by the North American Barley Genome Mapping Project. The analysis raises the need for mixed modeling in two different ways. First, it is reasonable to regard environments as a random sample from a population of target environments. Thus, environmental main effects and QTL-by-environment interaction effects are regarded as random. Second, I expect a genetic correlation among pairs of environments caused by undetected QTL. I show how random QTL-by-environment effects as well as genetic correlations are straightforwardly handled in a mixed-model framework. The main advantage of this method is the ability to assess the stability of QTL effects. Moreover, the method allows valid statistical inferences regarding average QTL effects.

Crosses, Genetic↗
PubMed1999

Fitting a regression model for genotype-by-environment data on heading dates in grasses by methods for nonlinear mixed models.

The analysis of agricultural crop variety trials is usually complicated by the presence of genotype-by-environment interaction. A number of methods and models have been proposed to tackle this problem. One of the most common methods is the regression approach due to Yates and Cochran (1938, Journal of Agricultural Science 28, 556-580), in which performances of genotypes in the environments are regressed onto environmental means. The underlying regression model contains a multiplicative term with two unknown parameters (one for genotypes and one for environments). In the present paper, the model is modified by exchanging the role of genotypes and environments. Various diagnostic plots show that this modified model is adequate for a data set on heading dates in the grass species Dactylis glomerata. If environments are considered as a random factor while genotypes are taken as fixed, the model falls into the class of nonlinear mixed models. Recently, a number of procedures have been suggested for this class of models, which are based on first-order Taylor series expansion. Alternatively, the model can be estimated by maximum likelihood. This paper discusses the application of these methods for estimating parameters of the model.

Agriculture↗