Selection of test locations for regional trials of barley

Summary Three sets of regional six-row barley (Hordeum vulgare L.) trial data, representing cultivar x location x year, were grouped for locations based on the similarity of genotype x environment (GE) interaction. Locations were selected from each group (cluster) so that the structure of the GE interaction generated by the subsets of the locations would be approximately similar to that of the whole set (all locations). The purpose of this paper is to determine the number of locations where the GE interaction structure generated by these selected locations would be fairly consistent over years. Two statistics were used to measure the success of the selected locations: (1) the ratio of GE mean square (MS) associated with the selected location set relative to that associated with the best set (which gives the highest GE interaction MS) and (2) the rank correlation between the cultivar means averaged over the selected locations and those based on the entire data set. The results show that, for eastern Canada, 10–13 locations based on the cluster method can achieve a fairly consistent GE interaction structure over years.Contribution no. R-078 from Research Program Service, Agriculture Canada, and contribution no. 1352 from Plant Research Centre, Central Experimental Farm     

Comparison of unpredictable environmental variation generated by year and by seeding-time factors for measuring type 4 stability

Summary Type 4 stability has been proposed to measure a cultivar's homeostatic property to resist unpredictable environmental variation. The requirement for calculating this stability is that the experiment must contain a time factor in addition to the cultivar x location factors. Of the two time factors, year and seeding-time, the latter is less attractive biologically because it represents only a part of the broader context of unpredictable variation represented by years, but it is attractive in terms of shortening the test period. Investigation of historical data from the Eastern Cooperative trials and the Ontario Production trials in Canada indicates that the unpredictable variation generated by seeding-time was about half that generated by year. Although type 4 stability measured by both factors appears to be the same, the stability measured by seeding-time is more prone to variation. The implication is that complete substitution of the year factor by seeding-time is not appropriate, but use of both factors in combination may be sensible.Contribution No. C-055 from the Engineering and Statistical Research Centre, Research Branch, Agriculture Canada, Ottawa, K1A 0C6, Canada     

A method of analyzing cultivar x location x year experiments: a new stability parameter

Summary Assessment of cultivar performance in a cultivar x location x year experiment is often difficult because of the presence of a location x year interaction. Our objective is to demonstrate a method on separation of environment effects (location x year) into predictable and unpredictabel components. The analysis consists of two parts: (1) a regression analysis based on location effects (averaged over years), assuming that the location means represent predictable environmental variation; and (2) the estimation of stability (denoted type 4) based on the years within location mean squares, assuming that years within location represent unpredictable environmental variation. From the regression analysis in (1), a breeder can determine the optimum range of locations in which a cultivar is well suited, and from (2) he can choose the most stable cultivars. The advantage of type 4 stability is that it is independent of the other cultivars included in the test and of the regression coefficient estimated for predictable variation. Three sets of published data are used to illustrate the analysis. Type 4 stability is compared with type 3 stability (deviation mean square from regression on environmental index) for genetic consistency. The analyses suggest that type 4 stability is consistent and is therefore a potential genetic parameter, but type 3 stability is not.Contribution No. I-806 from Engineering and Statistical Research Centre, Research Branch, Agriculture Canada, Ottawa, K1A OC6, Canada     

Comparing test cultivars using reliability functions of test-check differences from on-farm trials

An approach to selection is proposed that is based on the probabilities that a test cultivar outperforms a check by more than an amount d in a future environment. The function that gives these probabilities for all possible values of d is called the reliability function. When d=0, the value of the reliability function is the probability that the test cultivar outperforms the check. The method is illustrated using data from on-farm maize (Zea mays L.) strip test trials grown cooperatively by Pioneer Hi-bred International and farmers. Results indicate that reliability functions are useful for evaluating how test cultivars perform relative to a check across a range of environments since the location, slope and shape of the reliability function may be used to describe a test cultivar's performance, similarity to the check and stability, and identify environments where the test cultivar has performance problems.Contribution from the Agric Res Div, Univ Nebraska, Lincoln, Neb. Paper No. 9913.     

Expected utility maximization and selection of stable plant cultivars

Summary In most plant breeding programs, selection of the best commercially suitable cultivars for a target group of environments is based on information obtained from evaluation trials cultivated in a sample of environments. Information on the performance of cultivars collected in a sample of environments can only be approximate and, consequently, selection of the best cultivar involves choosing among cultivars that respond uncertainly in many environments. The agronomic and/or economic value of a cultivar across environments may be considered the general or overall utility of the cultivar. Data from a sample of environments therefore provides only an estimate of any cultivar's overall utility, with the overall goal of selection among all cultivars being the maximization of the expected utility. Within this frame-work, expected utility maximization, an approach to decision making that has been well developed in the disciplines of economics and statistics, can assist the plant breeder in making such decisions. This research was initiated (1) to determine how expected utility maximization might be used to develop indices that are useful for selecting broadly adapted plant cultivars, and (2) to determine how the breeder's preferences might affect choice of the best cultivar. The data used in this research were from USDA Regional Soybean Tests. The results indicated that expected utility maximization, which explicitly incorporates into the selection rule the plant breeder's preferences regarding stability, can be a useful aid in the selection of stable plant cultivars.     

Grouping genotypes by a cluster method directly related to genotype-environment interaction mean square

Summary To facilitate the interpretation of data from a genotype by environment (GE) experiment when the GE interaction is large, a cluster method is proposed to group genotypics according to their response to the environments. The dissimilarity index between a pair of genotypes is defined in terms of distance adjusted for the average effects of genotypes, and Sokal and Michener's (1958) unweighted pair-group method is used in the clustering algorithm. The new index, constructed in each cluster cycle for any group, is shown to be equivalent to within group GE interaction mean square under 2-way ANOVA. Thus, if the F-value is used as an empirical stopping criterion for clustering, there will be no significant GE interaction within groups and the genotypes within the groups can be compared by their average effects. The method of analysis is illustrated by an example.Contribution no. I-348 from the Engineering and Statistical Research Institute     

Generalized Exponential Distribution in Flood Frequency Analysis for Polish Rivers

Many distributions have been used in flood frequency analysis (FFA) for fitting the flood extremes data. However, as shown in the paper, the scatter of Polish data plotted on the moment ratio diagram shows that there is still room for a new model. In the paper, we study the usefulness of the generalized exponential (GE) distribution in flood frequency analysis for Polish Rivers. We investigate the fit of GE distribution to the Polish data of the maximum flows in comparison with the inverse Gaussian (IG) distribution, which in our previous studies showed the best fitting among several models commonly used in FFA. Since the use of a discrimination procedure without the knowledge of its performance for the considered probability density functions may lead to erroneous conclusions, we compare the probability of correct selection for the GE and IG distributions along with the analysis of the asymptotic model error in respect to the upper quantile values. As an application, both GE and IG distributions are alternatively assumed for describing the annual peak flows for several gauging stations of Polish Rivers. To find the best fitting model, four discrimination procedures are used. In turn, they are based on the maximized logarithm of the likelihood function (K procedure), on the density function of the scale transformation maximal invariant (QK procedure), on the Kolmogorov-Smirnov statistics (KS procedure) and the fourth procedure based on the differences between the ML estimate of 1% quantile and its value assessed by the method of moments and linear moments, in sequence (R procedure). Due to the uncertainty of choosing the best model, the method of aggregation is applied to estimate of the maximum flow quantiles.     

An integrated approach to oilseed rape cultivar selection using phenotypic stability

Summary Various methods of evaluating phenotypic stability have been proposed; however, no single method can adequately describe cultivar performance. The objectives of this study were to integrate a number of methods of evaluating stability and to use this approach for cultivar selection. These objectives were considered in the context of the broad-based oilseed rape cultivar (Brassica napus spp. oleifera) evaluation system currently used in western Canada. Regression analysis was used to assess cultivar response to environments. Cluster analysis was used to assemble cultivars into groups with similar regression coefficients (b _i ) and mean yield. Three parametric stability parameters, years within locations mean square (MS; Y/L), Shukla's stability variance ( _i ² ), and Francis and Kannenberg's coefficient of variability (CV _i ), were compared to determine which method would be most suitable for selection of oilseed rape cultivars from within clustered groups. Yield data from three cultivars and six breeding lines that had been tested for 2 years at 26 locations in the Western Canola Cooperative Test A were used for all calculations. The cluster analysis was successful in identifying commercially acceptable breeding lines. The parameter MS _i Y/L was considered to be more appropriate than either CV _i or _i ² , because it measured only the unpredictable portion of the genotype x environment interaction and was independent of the other cultivars in the test. The use of cluster analysis to group entries with similar b _i values and mean yields, followed by selection for stability within groups, was advocated.Contribution No. 846 of the Plant Science Department, University of Manitoba     

Multiattribute evaluation of regional cotton variety trials

Summary The Australian Cotton Cultivar Trials (ACCT) are designed to investigate various cotton [Gossypium hirsutum (L.)] lines in several locations in New South Wales and Queensland each year. If these lines are to be assessed by the simultaneous use of yield and lint quality data, then a multivariate technique applicable to three-way data is desirable. Two such techniques, the mixture maximum likelihood method of clustering and three-mode principal component analysis, are described and used to analyze these data. Applied together, the methods enhance each other's usefulness in interpreting the information on the line response patterns across the locations. The methods provide a good integration of the responses across environments of the entries for the different attributes in the trials. For instance, using yield as the sole criterion, the excellence of the namcala and coker group for quality is overlooked. The analyses point to a decision in favor of either high yields of moderate to good quality lint or moderate yield but superior lint quality. The decisions indicated by the methods confirmed the selections made by the plant breeders. The procedures provide a less subjective, relatively easy to apply and interpret analytical method of describing the patterns of performance and associations in complex multiattribute and multilocation trials. This should lead to more efficient selection among lines in such trials.     

Assessing the correlations and selection criteria between different traits in wheat salt-tolerant genotypes

Salinity is one of the largest stresses blocking horizontal and vertical expansion in agricultural lands. Establishing salt-tolerant genotypes is a promising method to benefit from poor water quality and salinized lands. An integrated method was developed for accomplishing reliable and effective evaluation of traits stability of salt-tolerant wheat. The study aims were to estimate the genetic relationships between explanatory traits and shoot dry matter (SDM), and determine the traits stability under three salinity levels. Morphophysiological and biochemical traits were evaluated as selection criteria for SDM improvement in wheat for salinity tolerance. Three cultivars and three high-yielding doubled haploid lines (DHLs) were used. Three salt (NaCl) levels (control (washed sand), 7 and 14 dS m⁻¹) were applied for 45 days (at the first signs of death in the sensitive genotypes). All morphophysiological traits gradually decreased as salinity levels increased, excluding the number of roots. Decreases were more visible in sensitive genotypes than in tolerant genotypes. All biochemical traits increased as salinity levels increased. Variance inflation factors (VIFs) and condition number exhibited multicollinearity for membrane stability index and polyphenol oxidase activity. After their removal, all VIFs were <10, thereby increasing path coefficient accuracy. Total chlorophyll content (CHL) and catalase (CAT) provided significant direct effects regarding genetic and phenotypic correlations for the three salinity levels and their interactions in path analysis on SDM, indicating their stability. CHL and CAT had high heritability (>0.60%) and genetic gain (>20%) and highly significant genetic correlation, co-heritability, and selection efficiencies for SDM. CHL and CAT could be used as selection criteria for salinity tolerance in wheat-breeding programs. The tolerated line (DHL21) with the check cultivar (Sakha 93) can be also recommended as novel genetic resource for improving salinity tolerance of wheat.     

A comparative evaluation of two methods of selecting locations used for testing spring wheat cultivars

Summary One of the considerations of regional cultivar evaluation programs is to optimize the number of locations used for testing. Although optimization of numbers of locations using cluster analysis has been previously attempted, no objective comparison of methods has yet been made. A new clustering method that uses the pairwise contribution of locations to the cultivar x location mean square as the distance measure (LB) was compared to another method that employs diallel correlations as the distance measure (CL). Data from six spring wheat (Triticum aestivum L. em Thell) cultivars grown at 13 locations for five years were used in the initial cluster analysis. Another set of data, from a separate year, consisting of yields of the original 6 cultivars and a set of 12 independent cultivars was then used to check the validity of the original groupings and to compare the two methods. When the 6 original cultivars were considered, the LB technique was found to be superior to the CL. When the 12 independent cultivars were used, neither method was considered to be superior. Because of the lack of flexibility on the part of the LB method, neither technique could be deemed as fully adequate.Contribution Number 842 of the Department of Plant Science, University of Manitoba, Winnipeg, Manitoba, Canada     

Efficiency robust tests for survival or ordered categorical data

The selection of a single method of analysis is problematic when the data could have been generated by one of several possible models. We examine the properties of two tests designed to have high power over a range of models. The first one, the maximum efficiency robust test (MERT), uses the linear combination of the optimal statistics for each model that maximizes the minimum efficiency. The second procedure, called the MX, uses the maximum of the optimal statistics. Both approaches yield efficiency robust procedures for survival analysis and ordinal categorical data. Guidelines for choosing between them are provided.     

Mating schemes for optimum contribution selection with constrained rates of inbreeding

The effect of non-random mating on genetic response was compared for populations with discrete generations. Mating followed a selection step where the average coancestry of selected animals was constrained, while genetic response was maximised. Minimum coancestry (MC), Minimum coancestry with a maximum of one offspring per mating pair (MC1) and Minimum variance of the relationships of offspring (MVRO) mating schemes resulted in a delay in inbreeding of about two generations compared with Random, Random factorial and Compensatory mating. In these breeding schemes where selection constrains the rate of inbreeding, ΔF, the improved family structure due to non-random mating increased genetic response. For schemes with ΔF constrained to 1.0% and 100 selection candidates, genetic response was 22% higher for the MC1 and MVRO schemes compared with Random mating schemes. For schemes with a less stringent constraint on ΔF or more selection candidates, the superiority of the MC1 and MVRO schemes was smaller (5–6%). In general, MC1 seemed to be the preferred mating method, since it almost always yielded the highest genetic response. MC1 mainly achieved these high genetic responses by avoiding extreme relationships among the offspring, i.e. fullsib offspring are avoided, and by making the contributions of ancestors to offspring more equal by mating least related animals.     

A nonparametric method for classification trees using grouped covariates

A group of variables are commonly seen in diagnostic medicine when multiple prognostic factors are aggregated into a composite score to represent the risk profile. A model selection method considers these covariates as all-in or all-out types. Model selection procedures for grouped covariates and their applications have thrived in recent years, in part because of the development of genetic research in which gene–gene or gene–environment interactions and regulatory network pathways are considered groups of individual variables. However, little has been discussed on how to utilize grouped covariates to grow a classification tree. In this paper, we propose a nonparametric method to address the selection of split variables for grouped covariates and their following selection of split points. Comprehensive simulations were implemented to show the superiority of our procedures compared to a commonly used recursive partition algorithm. The practical use of our method is demonstrated through a real data analysis that uses a group of prognostic factors to classify the successful mobilization of peripheral blood stem cells.     

High‐dimensional data analysis: Selection of variables,data compression and graphics – Application to gene expression

The paper presents effective and mathematically exact procedures for selection of variables which are applicable in cases with a very high dimension as, for example, in gene expression analysis. Choosing sets of variables is an important method to increase the power of the statistical conclusions and to facilitate the biological interpretation. For the construction of sets, each single variable is considered as the centre of potential sets of variables. Testing for significance is carried out by means of the Westfall‐Young principle based on resampling or by the parametric method of spherical tests. The particular requirements for statistical stability are taken into account; each kind of overfitting is avoided. Thus, high power is attained and the familywise type I error can be kept in spite of the large dimension. To obtain graphical representations by heat maps and curves, a specific data compression technique is applied. Gene expression data from B‐cell lymphoma patients serve for the demonstration of the procedures.     

Potential of promotion of alleles by genome editing to improve quantitative traits in livestock breeding programs

Background

Genome editing (GE) is a method that enables specific nucleotides in the genome of an individual to be changed. To date, use of GE in livestock has focussed on simple traits that are controlled by a few quantitative trait nucleotides (QTN) with large effects. The aim of this study was to evaluate the potential of GE to improve quantitative traits that are controlled by many QTN, referred to here as promotion of alleles by genome editing (PAGE).

Methods

Multiple scenarios were simulated to test alternative PAGE strategies for a quantitative trait. They differed in (i) the number of edits per sire (0 to 100), (ii) the number of edits per generation (0 to 500), and (iii) the extent of use of PAGE (i.e. editing all sires or only a proportion of them). The base line scenario involved selecting individuals on true breeding values (i.e., genomic selection only (GS only)-genomic selection with perfect accuracy) for several generations. Alternative scenarios complemented this base line scenario with PAGE (GS + PAGE). The effect of different PAGE strategies was quantified by comparing response to selection, changes in allele frequencies, the number of distinct QTN edited, the sum of absolute effects of the edited QTN per generation, and inbreeding.

Results

Response to selection after 20 generations was between 1.08 and 4.12 times higher with GS + PAGE than with GS only. Increases in response to selection were larger with more edits per sire and more sires edited. When the total resources for PAGE were limited, editing a few sires for many QTN resulted in greater response to selection and inbreeding compared to editing many sires for a few QTN. Between the scenarios GS only and GS + PAGE, there was little difference in the average change in QTN allele frequencies, but there was a major difference for the QTN with the largest effects. The sum of the effects of the edited QTN decreased across generations.

Conclusions

This study showed that PAGE has great potential for application in livestock breeding programs, but inbreeding needs to be managed.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0135-3) contains supplementary material, which is available to authorized users.     

Regression analysis of yield stability is strongly affected by companion test varieties and locations — examples from a study of Nordic barley lines

The suitability of regression analysis for studying the phenotypic stability of grain yield was investigated using a collection of 220 Nordic barley lines. Linear regression explained 26–52% of the genotype x environment (GE) interactions in different groupings of the material. The regression coefficient, b _i , measures the yield response of the i-th genotype to improved environmental conditions. Deviations from regression, S _di ² , have been used to estimate Tai's stability parameter, _i , which is a measure of the phenotypic yield stability in the agronomic sense. Repeatability of b _i , _i , and grain yield was studied by means of correlations between estimates obtained in each experimental year. Yield had the highest repeatability, with correlations between years ranging from 0.57 to 0.85. In this study, regression coefficients and _i -values were not repeatable, i.e. genotypes reacted differentially to the yearly climatic variations. Six-rowed (6r) barleys had higher responsiveness, but lower mean yields, than two-rowed (2r) barleys. This is partly due to the history of selection of 6r-barleys, which mainly originate from regions with low potential yield levels, i.e. Finland and Norway. In general, responsiveness and stability were not correlated with yield. The highest-yielding lines had b _i 1. The response pattern of the different types of barleys used in this study show that responsiveness can be changed by recombination.     

OVERCOMING STATISTICAL BIAS TO ESTIMATE GENETIC MATING SYSTEMS IN OPEN POPULATIONS: A COMPARISON OF BATEMAN'S PRINCIPLES BETWEEN THE SEXES IN A SEX‐ROLE‐REVERSED PIPEFISH

The genetic mating system is a key component of the sexual selection process, yet methods for the quantification of mating systems remain controversial. One approach involves metrics derived from Bateman's principles, which are based on variances in mating and reproductive success and the relationship between them. However, these measures are extremely difficult to measure for both sexes in open populations, because missing data can result in biased estimates. Here, we develop a novel approach for the estimation of mating system metrics based on Bateman's principles and apply it to a microsatellite‐based parentage analysis of a natural population of the dusky pipefish, Syngnathus floridae. Our results show that both male and female dusky pipefish have significantly positive Bateman gradients. However, females exhibit larger values of the opportunity for sexual selection and the opportunity for selection compared to males. These differences translate into a maximum intensity of sexual selection () for females three times larger than that for males. Overall, this study identifies a critical source of bias that affects studies of mating systems in open populations, presents a novel method for overcoming this bias, and applies this method for the first time in a sex‐role‐reversed pipefish.     

仙客来(Cyclamen persicum Mill.)的种质资源RAPD分析

利用RAPD技术对20个现今栽培的名优仙客来品种的分类和亲缘关系进行研究,从100个随机引物中筛选出18个用于PCR反应,共在153个位点上扩增出条带,平均每个引物扩增位点8.5个,多态性位点144个,占总带数的94.1%。这种多肽性可以进行品种的鉴定,聚类分析将各品种材料分为4个类群。提出仙客来除目前的观赏性状分类以外,还应具有更科学的以遗传基础为基准的分类方法。也从分子水平揭示了目前栽培的仙客来品种的遗传基础的狭窄性。对RAPD技术在仙客来育种的进一步应用也作了相应的探讨。     

Circadian Variation in the Gastric-Emptying Response to Eating in Rats Previously Fed Once or Twice Daily

Four experiments dealt with circadian variation in the gastric emptying (GE) response to eating, among rats accustomed to eating once (1X) or twice daily (2x). In measuring GE response, a test meal [10 g accustomed diet per (kg body weight)^3/4] was fed close to a scheduled eating time or after a delay of up to 24 h. GE response was the fraction of the ingested test meal emptied per hr, up to a known degree of emptying, e.g., 50-58% of the test meal. Animals accustomed to the prescribed eating patterns ate promptly and at similarly rapid rates at all times of day. GE response, as plotted against time of response, fit a 24-h cosine model. Acrophase (time of maximum GE response of the fitted model) was similar, being 1.5 and 2.1 h, respectively, after the starting time of the accustomed dark-span meal for 1X and 2x rats, while amplitude (1/2 the maximum-to-minimum difference) was 41 and 24% of the MESOR (rhythm-adjusted mean). Characteristics of the GE rhythm appeared to be unchanged among 1X rats, severely versus minimally restricted in food intake during a final 9 days.