Genotype X environment interaction and simultaneous selection for high yield and stability in soybeans (Glycine max (L.) Merr.)

Eighteen genotypes of soybean were grown in five locations in Nigeria. The heritability estimates for seed yield were generally low, ranging from 22.6% to 45.3%. Joint regression analysis indicated the presence of genotype x environment, although a large proportion was non-linear. The genotypes responded differently to environments, highlighting the possibility of breeding for specific environments. The correlation of regression coefficients with mean yield indicated that high yielding genotypes were responsive to changing environments. The simultaneous selection parameters Pi, S³ and rank-sums gave somewhat similar results but Pi produced higher yielding genotypes than others. The correlation between Pi and rank-sum indicated that either of the techniques could be employed during selection.     

Estimation of heritability from varietal trials data

We present the estimation of heritabilities of an observed trait in situations where evaluation of several pure breeding lines is performed in a trial at a single location and in trials from several locations. For the single location situation, we evaluate exact confidence intervals, the probability of invalid estimates, and the percentage points of the distribution of heritability. Simulations were performed to numerically verify the results. Additionally, approximations to the bias and standard error of the estimate were obtained and are presented along with their simulated values and coefficients of skewness and kurtosis. For trials in several locations, explicit expressions for exact values of confidence limits are not available. Further, one would require knowledge of one more parameter, represented by the ratio of genotype x environment (G x E) interaction variance to error variance, in addition to the number of genotypes, replication and true heritability value. Approximations were made for bias and the standard error of estimates of heritability. The evaluation of the distribution of heritability and its moments was recognized as a problem of the linear function of an independent chi-square. The methods have been illustrated by data from experiments on grain and straw yield of 64 barley genotypes evaluated at three locations.     

Environmental conditions and host genotype direct genetic diversity of Venturia ditricha,a fungal endophyte of birch trees

We investigated whether genetic variation of a common foliar endophyte of birch trees, Venturia ditricha, is affected by environmental conditions or host genotype. Fungal samples were collected from 10 half-sibling families of mountain birch (Betula pubescens ssp. czerepanovii) grown in two environmental conditions with different daily average temperatures: a forested river valley and an adjacent open tundra (altitudinal difference 180 m). Genetic analysis of V. ditricha isolates was done using random amplified microsatellite polymerase chain reaction. We found that host genotypes, along with prevailing environmental conditions, influence the probability of infection by particular endophyte genotypes. The most susceptible host genotypes were highly infected with genetically similar endophyte genotypes, whereas the most resistant trees were poorly infected and they were infected by genetically dissimilar endophytes. Our results also showed environment-host genotype interactions, suggesting that the susceptibility of the host to a particular endophyte genotype may change in natural environments when environmental conditions are changed. It appears that a particular endophyte genotype needs to find the right host genotype for a successful infection. There are many host genotypes in natural stands; this means, from the point of view of the fungus, the environment is heterogeneous. Thus, under the influence of birch tree genotypes, genetically differentiated subgroups of the endophytic fungus may be formed in different environments.     

Heritability estimates in contrasting environments as influenced by the adaptation level of barley germ plasm

Low heritability estimates in marginal or stress environments have often been used as one of the main justification for conducting selection work in environments with optimum or near‐optimum conditions for plant growth and grain yield. In this study, we have examined the relationships between grain yield and broad‐sense heritability in four groups of recombinant inbred lines (RILs) obtained from four barley crosses derived from parents differing in adaptation to stress. The RILs and the parents were grown in 13 combinations of years and locations (environments) in Syria and Jordan. Grain yields ranged from about 30 kg ha^?1 to nearly 4000 kg ha^?1 and genotype × environment interactions explained about half of the total variance for environmentally standardised data. Broad‐sense heritability in the individual year–location combinations varied from 0 to 0.68 and both the simple correlation and the rank correlation coefficients between grain yield and heritability were not significant. Genotype × years within individual locations, which measures the repeatability of a location in discriminating between genotypes, was also independent from the yield level, confirming that low‐yielding locations can be reliable selection environments. Also, there was no relationship between the type of cross and the magnitude of heritability in the various environments, but, as expected, the magnitude of heritability was significantly associated with the genetic distance between the parents. It is concluded that, holding all other factors affecting response to selection constant, concerns about the magnitude of heritability at low‐yielding locations are not justified and should not prevent them from being used as selection sites.     

Environmental response patterns in commercial classes of common bean (Phaseolus vulgaris L.)

Summary The yield data of 39 cultivars of diverse commercial classes of beans (Phaseolus vulgaris L.) planted in seven locations in Michigan were subjected to cluster and canonical variate analyses. The essential findings and conclusions can be summarized as follows: (1) Cluster analysis classified the cultivars into sub-sets or clusters almost identically coinciding with their commercial class designation. Canonical variate analysis completely confirmed the sub-groupings. Within class similarities were attributed to a narrow genetic base resulting from a common genetic relationship, or at least sharing of a common gene pool. (2) It was found that two clusters could possess almost identical mean (cluster mean) yields, and deviate in opposite directions over the same range of environments. (3) When total genotype × environmental interaction variance was partitioned into between and within clusters, the cluster × environment portion constituted 80% of the total. (4) These results imply that if the behavior of a given cultivar across a series of environments is known, the behavior of all other members of the class across a similar range of environments would be predictable.Journal Article No. 10329 of the Michigan Agricultural Experiment Station     

基因型和环境对小麦主要品质性状参数的影响

利用8个冬小麦品种（系）于2002年种植在8个不同地点的试验结果,分析了品种（系）、环境以及品种（系）与环境的互作对谷蛋白大聚合体（GMP）及其组成、面团揉混仪参数及烘烤品质等主要品质性状的影响。结果表明,基因型对GMP、高、低分子量谷蛋白亚基有显著影响,说明GMP及其组成主要受基因型控制;沉淀值、峰值时间（MPT）、8min带宽（8TW）受环境影响程度比基因型小;而品种、环境及其互作对面包体积都有显著影响。小麦品质性状间的相关系数受环境条件的影响,不同地点品质性状问的相关系数不同。品种（系）和地点的互作效应在同一品种不同地点间是不同的,即使在不利的环境下,也有表现好的品种（系）。综合考虑对烘烤品质的影响,烟台点和济麦20表现最好。因此,进行品质评价时,不同地点间不仅考虑蛋白质含量的变化,还要考虑蛋白质质量、GMP及其组成、沉淀值、中线峰值时间以及8min带宽的变化规律。     

Genetic properties of four types of stability parameter

Summary The genetic properties of four types of stability parameter for individual genotypes were investigated using a set of diallel cross data (28 genotypes x four locations x 3 years). The specific parameters studied were: the variance of a genotype across environments (T1); the genotype x environment (GE) interaction effect for a genotype, squared and summed across all environments (T2); the residual mean square (MS) of deviations from the regression of a genotype on an environmental index (T3); and years within locations MS for a genotype, averaged over all locations (T4). Each stability statistic was fitted to the additive model, based on the assumption that if the stability parameter is heritable, stability of F₁ is most likely to be the average stability of its parents. The results showed that T1 and T4 were additive, but T2 and T3 were not. A study of the consistency of stability rankings between two seeding rates over the same set of environments showed a similar pattern. It appears that stability parameters of types 1 and 4 are heritable, and thus useful for selection, while those of types 2 and 3 are nonheritable, and thus not useful.Contribution No. R-029     

Microsatellite DNA markers: evaluating their potential for estimating the proportion of hatchery-reared offspring in a stock enhancement programme

We describe a statistical method for estimating the effectiveness of a stock enhancement programme using nuclear DNA loci. It is based on knowing the population allele frequencies and the genotypes of the hatchery parents (mother only, or mother and father), and on determining the probability that a wild-born animal will by chance have a genotype consistent with hatchery origin. We show how to estimate the proportion of released animals in the wild population, and its standard error. The method is applied to a data set of eight microsatellite loci in brown tiger prawns (Penaeus esculentus), prior to the start of a possible enhancement programme. We conclude that, for this particular data set, the effectiveness of such an enhancement programme could be quantified accurately if both maternal and paternal genotypes are known, but not if maternal genotypes only are known. Full paternal genotyping would require offspring genotyping and thus would be expensive, but a partly typed paternal genotype from a mass homogenate of offspring would be almost as effective and much cheaper. The experiment would become feasible based on maternal genotypes alone, if a further three typical microsatellite loci could be found to add to the existing panel of eight. The methods detailed should be of interest to any enhancement project that relies on nuclear DNA markers to provide tags.     

Population genetics from an information perspective

Some basic effects of population genetics are derived governing the occurrences of alleles A(i)and genotypes A(i)A(j)among its members. A principle of extreme physical information (EPI) is used. These effects are (1) the equation of genetic change, (2) Fisher's theorem of partial change, (3) a new uncertainty principle, and (4) the monotonic decrease of Fisher information with time, indicating increased disorder for the population. General conditions of population change are allowed: fitness coefficients w(ij)generally changing with time [except in effect (2)], population randomly or non-randomly mating, and a general number of loci present within each chromosome. EPI is a practical tool for deriving probability laws. It is an outgrowth of a physical process that occurs during any act of measurement. Here the measurement is the random observation of a genotype A(i)A(j). This observation is to be used to estimate the time of the observation, called "evolutionary time". The measurement activity incurs errors in the estimated observation time and fitness value of the observed genotype. By the Cramer-Rao inequality, the product of the two uncertainties must exceed unity [effect (3)]. The Fisher information I in data space is postulated to originate in the space of the genotype where it had some generally larger value J. The EPI principle extremizes the loss of information (I--J) with I=1/2 J. The solution gives rise to effects (1) and (2). Finally, it is shown that effect (4) holds when the population approaches an equilibrium state, e.g. for time values greater than a threshold if fitness coefficients w(ij)are constant. EPI provides a common framework for deriving physical laws and laws of population genetics. The new effects (3) and (4) are confirmed through computer simulation.     

Assessing three methods for identification of desirable genotypes in white cabbage (Brassica oleracea L. var. capitata)

Summary A desirable genotype is a genotype performing well in a chosen set of environments. Three methods for identification of desirable genotypes were assessed in two cabbage data sets: regression analysis, multidimensional scaling of dissimilarity matrices, and biplot of deviation matrices. Using the regression approach is not recommended mainly for two reasons: (1) it is difficult to identify the desirable genotypes since one has to unify three parameters into one decision; (2) the regression method failed to identify the most desirable genotypes in one of the data sets. Multidimensional scaling and the biplot method were in accordance with each other and with the mean tables when different subsets where compared. Consequently, they were considered more adequate for identifying desirable genotypes. In cases where rank 2 approximation of the analysed matrix was justified, the biplot revealed more information in one display and was, therefore, considered particularly useful in plant breeding for larger target areas.     

Genotype identity has a more important influence than genotype diversity on shoot biomass productivity in willow short‐rotation coppices

Willow (Salix spp.) short‐rotation coppice is commercially grown to produce lignocellulosic biomass to meet renewable bioenergy demands. Most commercial willow coppices are grown in stands of a single genotype, but biomass productivity may be greater in mixed communities, and the productivity in mixed communities may depend on the specific genotypes involved. We assessed the biomass production of four different Salix genotypes (“Björn,” “Jorr,” “Loden,” “Tora”) grown without additional nutrient fertilization during one cutting cycle at three locations in Europe (Uppsala in Sweden, Rostock and Freiburg in Germany) in plots of pure and mixed communities. We evaluated (i) the effect of genotype diversity on shoot biomass productivity, including the evidence for complementarity and selection effects; (ii) the influence of individual genotypes on mixed community productivity; and (iii) the productivity of individual genotypes in response to pure vs. mixed culture. Mean shoot biomass production after the first cutting cycle decreased in the order Rostock (8.7 Mg ha^?1) > Freiburg (6.9 Mg ha^?1) > Uppsala (5.7 Mg ha^?1), with values similar to those for other nonfertilized willow stands after the first growth cycle. Consistently across all three locations, increasing genotype diversity did not significantly affect shoot biomass production. Using Bayesian statistics, the addition of the genotypes “Jorr” and “Loden” was predicted to enhance shoot biomass production, while “Tora” and “Björn” are more likely to reduce shoot biomass production in mixed communities. In addition, we found evidence for a negative selection effect due to the genotype “Tora” performing better in mixed than in pure communities in two of the sites (Freiburg, Uppsala). In conclusion, our results imply that increasing genetic richness has no negative effect on productivity and that there is a potential to design site‐specific genotype mixtures of short‐rotation coppice promoting both high genetic diversity and high biomass production.     

A competition model for viral inhibition of host cell proliferation

Some viruses encode proteins that promote cell proliferation while others, such as the human immunodeficiency virus (HIV), encode proteins that prevent cell division. It has been hypothesized that the selective advantage determining which strategy evolves depends on the ability of the virus to induce a cellular environment which maximizes both virus production and cell life span. In HIV, the protein that causes cell cycle arrest is Vpr. In this paper, we develop a mathematical model, based on difference equations, to study the competition between two genotypes of HIV - one that encodes this protein (Vpr+) and one that does not (Vpr-). In particular, we are interested in parameters that could be different between the in vitro condition, where the Vpr- genotype dominates, and the in vivo condition, where the Vpr+ genotype dominates. Our model indicates that the infected cell death-rate, the viral half-life, and the dynamics of the target cell population all effect the competition dynamics between the Vpr+ and Vpr- viral genotypes. Perturbing any of these parameters from the in vitro estimates while holding the others fixed has no affect on the competition outcome, i. e., the Vpr- genotype dominates. Perturbing the infected cell death-rate and the target cell source causes a switch in competitive outcome, although not necessarily at values, which represent the in vivo condition. Adding a perturbation in the viral half-life from in vitro to in vivo condition results in a switch of the competitive advantage from the Vpr- genotype to the Vpr+ genotype with parameters for all three mechanisms set to estimated in vivo values.     

Genotype x environment interaction of crossover type: detecting its presence and estimating the crossover point

Genotype-environment interaction (GEI) introduces inconsistency in the relative rating of genotypes across environments and plays a key role in formulating strategies for crop improvement. GEI can be either qualitative (i.e., crossover type) or only quantitative (i.e., non-crossover type). Since the presence of crossover-type interaction has a strong implication for breeding for specific adaptation, it is important to assess the frequency of crossover interactions. This paper presents a test for detecting the presence of crossover-type interaction using the response-environment relationship and enumerates the frequency of crossovers and estimation of the crossover point (CP) on the environment axis, which serves as a cut-off point for the two environments groups where different/specific selections can be made. Sixty-four barley lines with various selection histories were grown in northern Syria and Lebanon giving a total of 21 environments (location-year combinations). Linear regression of the genotypic response on the environmental index represented a satisfactory model, and heterogeneity among regressions was significant. At a 5% level of significance, 38% and 19% of the pairs showed crossover interactions when the error variances were considered heterogeneous and homogeneous, respectively, implying that an appreciable number of crossovers took place in the case of barley lines responding to their environments. The CP of 1.64 t/ha, obtained as the CP of regression lines between the genotype numbers 19 and 31, provided maximum genotype x environment-group interaction. Across all environments, genotype nos. 59 and 12 stood first and second for high yield, respectively. The changes in the ranks of genotypes under the groups of environments can be used for selecting specifically adapted genotypes. Received: 25 January 1999 / Accepted: 16 March 1999     

Yield Results and Stability Analysis from the Sorghum Regional Biomass Feedstock Trial

Sorghum [Sorghum bicolor (L.) Moench] is one of four herbaceous dedicated bioenergy crops the U.S. Department of Energy identified as critical to annually produce one billion tons of dry biomass. Of these four crops, sorghum is unique as it is a drought-tolerant, annual crop established from seed that is readily tractable to genetic improvement. The purpose of this study was to assess the yield potential and stability of sorghums grown across diverse production environments in the USA. For this study, six sorghum genotypes (one cultivar, five hybrids) were grown in yield trials in seven locations in six states for 5 years (2008–2012). Variation in dry and fresh yield was attributable to not only genotypes, but also to the effects of year, location, and year × location. Even with the highest yielding genotype, environmental conditions were a major factor in determining the yield in a given year. This variability affects the consistency of the biomass supply for ethanol production. In general, the southeastern USA had the highest mean yields for fresh weight and dry weight, indicating that this area may be the most reliable for biomass production. A significant variation was detected among genotypes for fresh weight, dry weight, moisture content, and brix, revealing that sufficient variation within sorghum exists for continued improvement and that certain hybrids are more tractable for biomass/bioenergy production. With dedicated bioenergy sorghum germplasm and proper production environments, sorghum will be a valuable tool in the goal of the sustainable production of one billion tons of dry biomass each year in the USA.     

Coherent synthesis of genomic associations with phenotypes and home environments

Local adaptation is often studied via (i) multiple common garden experiments comparing performance of genotypes in different environments and (ii) sequencing genotypes from multiple locations and characterizing geographic patterns in allele frequency. Both approaches aim to characterize the same pattern (local adaptation), yet the complementary information from each has not yet been coherently integrated. Here, we develop a genome‐wide association model of genotype interactions with continuous environmental gradients (G × E), that is reaction norms. We present an approach to impute relative fitness, allowing us to coherently synthesize evidence from common garden and genome–environment associations. Our approach identifies loci exhibiting environmental clines where alleles are associated with higher fitness in home environments. Simulations show our approach can increase power to detect loci causing local adaptation. In a case study on Arabidopsis thaliana, most identified SNPs exhibited home allele advantage and fitness trade‐offs along climate gradients, suggesting selective gradients can maintain allelic clines. SNPs exhibiting G × E associations with fitness were enriched in genic regions, putative partial selective sweeps and associations with an adaptive phenotype (flowering time plasticity). We discuss extensions for situations where only adaptive phenotypes other than fitness are available. Many types of data may point towards the loci underlying G × E and local adaptation; coherent models of diverse data provide a principled basis for synthesis.     

Stability analysis of grain yield in barley (Hordeum vulgare) in the US mid-Atlantic Region

Stability of grain yield performance is an important characteristic in the selection of new crop cultivars. Information from cultivar trials, however, is seldom fully analysed for genotype by environment interactions and, therefore, information on stability of current crop cultivars is lacking. The objectives of this study were to investigate the stability of agronomic traits among genotypes of barley (Hordeum vulgare) across 17 environments (location‐years) in Maryland (USA) from 1994 through 1997 and to examine the effect of locations and years of testing on grain yield performance in this region. Significant differences were observed among barley cultivars and experimental lines for grain yield, plant height, and heading date. Grain yield was positively correlated with plant height and negatively correlated with heading date. Genotype x environment interactions measured through regression analysis were significant for grain yield, heading date and plant height, with the environmental component having the largest effect. Most barley genotypes tested (90%) had regression slopes for grain yield that did not differ from 1.0, indicating good potential for yield response under improving environmental conditions. The most widely grown cultivar in the mid‐Atlantic region, ‘Nomini’, had a regression slope that was higher than 1.0 for grain yield. This indicates that it tends to respond with increasingly higher yields under favorable conditions. In this study, the slope and the standard error of the slope were moderately correlated with grain yield. The genotype's coefficient of variation was not a good indicator of stability for this region. Grain yields of genotype entries common to all years and locations were correlated with corresponding yields at each of the locations and years to assess the relative performance of each location and year. Correlation coefficients across locations were relatively high (r=0.64) within each year of testing. Correlations between years for the same and across locations were generally much lower. The data presented here supports a testing program over more years rather than increased locations to fully characterise the performance of new cultivars.     

Spatial distribution of Rhodopseudomonas palustris ecotypes on a local scale

The number, spatial distribution, and significance of genetically distinguishable ecotypes of prokaryotes in the environment are poorly understood. Oda et al. (Y. Oda, B. Star, L. A. Huisman, J. C. Gottschal, and L. J. Forney, Appl. Environ. Microbiol. 69:xxx-xxx, 2003) have shown that Rhodopseudomonas palustris ecotypes were lognormally distributed along a 10-m transect and that multiple strains of the species could coexist in 0.5-g sediment samples. To extend these observations, we investigated the clonal diversity of R. palustris in 0.5-g samples taken from the corners and center of a 1-m square. A total of 35 or 36 clones were recovered by direct plating from each sample and were characterized by BOX A1R repetitive element-PCR genomic DNA fingerprinting. Isolates with fingerprint images that were >/=80% similar to each other were defined as the same genotype. Among the 178 isolates studied, 32 genotypes were identified, and each genotype contained between 1 and 40 isolates. These clusters were consistent with minor variations found in 16S rRNA gene sequences. The Shannon indices of the genotypic diversity within each location ranged from 1.08 (5 genotypes) to 2.18 (13 genotypes). Comparison of the rank abundance of genotypes found in pairs of locations showed that strains from three locations were similar to each other, with Morisita-Horn similarity coefficients ranging from 0.59 to 0.71. All comparisons involving the remaining two locations resulted in coefficients between 0 and 0.12. From these results we inferred that the patterns of ecotype diversity at the sampling site are patchy at a 1-m scale and postulated that factors such as mixing, competitive interactions, and microhabitat variability are likely to be responsible for the maintenance of the similarities between some locations and the differences between others.     

Repeatability of stability estimators for downy mildew incidence in pearl millet

Summary Repeatability of mean downy mildew (Sclerospora graminicola (Sacc.) Schroet.) incidence, regression coefficients and deviation mean squares were investigated for 25 pearl millet (Pennisetum typhoides (Burm.) Stapf. & Hubb.) genotypes in 20 environments by correlating arrays of these stability parameters over subsets of the 20 environments arranged according to the year-wise, random, stratified and extreme methods of environmental division. Correlation coefficients between arrays of mean downy mildew incidence from different pairs of subsets ranged from 0.57 to 0.98 and those of deviation mean squares from 0.58 to 0.96 indicating good repeatability of these parameters. Arrays of regression coefficients from different subsets, on the other hand, showed correlation coefficients that ranged from –0.58 to 0.96. Apparently, the regression index of stability was not repeatable for the genotypes and environments studied. Therefore, in order to identify a widely adapted genotype, testing is required to be carried out over a wider range of environments.     

Yield in spring barley at contrasting sites in England and Scotland

The yield and yield components of tall and short genotypes derived from the cross between two spring barley cultivars, Ark Royal and Golden Promise were examined. The genotypes were grown at two locations in England and two in Scotland. The highest yields were observed at two English sites (in East Anglia) rather than, as expected, in Scotland (East Lothian). Higher yield at the English sites was related to the greater means recorded for all the components of yield. The tall genotypes produced higher yields than the short genotypes, particularly at sites affected by drought. There were significant interactions between genotypes and environments for plot yield. Selection for increased yield would have been possible within either tall or short lines.     

Searching for weeds – how to search where the weeds are?

Sampling for rare events, such as a new weed incursion, is not easy. At most of the sample points the species of interest is absent and only occasionally the species is recorded. Very often surveillance and monitoring for rare events (e.g. new weed incursions) is done using local knowledge and a statistical sampling design is not used. The stated reason for this approach is usually because the biodiversity managers knew where to look and didn’t need statistics. Adaptive, unequal probability survey designs can be used in these situations, ensuring both sample effort is focused on locations where there is a high likelihood of a weed being present. Time in the field is spent within locations where weeds are present and minimal time spent where weeds are absent. Any relevant information on where weeds are likely to be found (e.g. local knowledge and expertise) can be used to target survey effort in unequal probability survey designs. The advantage of an adaptive, unequal probability survey design is that not only can field effort be focused on areas where the weeds are thought to be. In addition, important weed parameters can be estimated and reported along with estimates of uncertainty. Weed parameters include the proportion of the total area that weeds are present, the diversity of weed species, the total abundance of weeds, and the total area covered by weeds. With reliable and consistent estimates of these weed parameters (e.g. weed cover or abundance) the efficacy of weed management can be tracked. Over time, with regular reporting of weed cover or abundance, the success (or otherwise) of weed management strategies can be measured.