Location of a gene regulating drought-induced abscisic acid production on the long arm of chromosome 5A of wheat

The accumulation of abscisic acid (ABA) by detached and partially dehydrated wheat leaves is known to be inherited in a quantitative manner. The location of genes having a major effect on drought-induced ABA accumulation in wheat was determined using a set of single chromosome substitution lines and populations derived from a cross between a high-ABA- and a low-ABA-producing genotype. Examination of a series of chromosome substitution lines of the high-ABA genotype Ciano 67 into the low-ABA recipient Chinese Spring showed that chromosome 5A carries gene(s) that have a major influence on ABA accumulation in a drought test with detached and partially dehydrated leaves (DLT). A similar DLT was used to examine ABA accumulation in a population of F₂ plants and doubled haploid (DH) lines derived from the cross between Chinese Spring (low-ABA) and SQ1 (high-ABA) in which the F₂ population (139 plants) and DH lines (96 lines) were also mapped partially with molecular markers. Analysis of variance of ABA accumulation between and within marker allele classes in the F₂ confirmed the location of a gene(s) regulating ABA accumulation on the long arm of chromosome 5A. MAPMAKERQTL showed the most likely position for the ABA quantitative trait locus (QTL) to be between the loci Xpsr575 and Xpsr426, about 8 cM from Xpsr426. A similar trend for high ABA accumulation was found in DH lines having the SQ1 allele at marker loci in the same region of chromosome 5AL, but the QTL effect was not significant. The function of the QTL is discussed.     

小麦叶蜂危害的产量损失与防治指标研究

当小麦叶蜂幼虫数量相等时,在较干旱的年份（1988）危害较重;而在气候较湿润的年份（1989）危害较轻。虫量与产量损失成正相关（r=0．9821**）,其中以25头／m2幼虫危害的产量损失突增,达显著水平,可以认定为防治指标。     

Quantitative trait loci influencing protein and starch concentration in the Illinois Long Term Selection maize strains

A study was initiated to determine the number, chromosomal location, and magnitude of effect of QTL (quantitative trait loci or locus depending on context) controlling protein and starch concentration in the maize (Zea mays L.) kernel. Restriction fragment length polymorphism (RFLP) analysis was performed on 100 F₃ families derived from a cross of two strains, Illinois High Protein (IHP), X Illinois Low Protein (ILP), which had been divergently selected for protein concentration for 76 generations as part of the Illinois Long Term Selection Experiment. These families were analyzed for kernel protein and starch in replicated field trials during 1990 and 1991. A series of 90 genomic and cDNA clones distributed throughout the maize genome were chosen for their ability to detect RFLP between IHP and ILP. These clones were hybridized with DNA extracted from the 100 F₃ families, revealing 100 polymorphic loci. Single factor analysis of variance revealed significant QTL associations of many loci with both protein and starch concentration (P < 0.05 level). Twenty-two loci distributed on 10 chromosome arms were significantly associated with protein concentration, 19 loci on 9 chromosome arms were significantly associated with starch concentration. Sixteen of these loci were significant for both protein and starch concentration. Clusters of 3 or more significant loci were detected on chromosome arms 3L, 5S, and 7L for protein concentration, suggesting the presence of QTL with large effects at these locations. A QTL with large additive effects on protein and starch concentration was detected on chromosome arm 3L. RFLP alleles at this QTL were found to be linked with RFLP alleles at the Shrunken-2 (Sh2) locus, a structural gene encoding the major subunit of the starch synthetic enzyme ADP-glucose pyrophosphorylase. A multiple linear regression model consisting of 6 significant RFLP loci on different chromosomes explained over 64 % of the total variation for kernel protein concentration. Similar results were detected for starch concentration. Thus, several chromosomal regions with large effects may be responsible for a significant portion of the changes in kernel protein and starch concentration in the Illinois Long Term Selection Experiment.     

DNA fingerprint bands applied to linkage analysis with quantitative trait loci in chickens

Summary
An efficient approach to detect association between quantitative traits and bands of DNA fingerprint patterns uses intra-family tail analysis, which compares fingerprints of DNA mixes from individuals at the two tails of a phenotypic distribution. In analysis of 67 paternal half-sibs of a meat-type chicken family, of 57 sire bands generated by two probes, one sire-specific band (S6–6) was associated with abdominal fat deposition. The band effect was estimated by a linear model analysis to be 0–88 standard deviations, or about 30% of the family mean. The association between band S6–6 and abdominal fat was further examined by testing progeny of paternal half-sibs of the chickens which were used in the tail analysis, establishing genetic linkage between the DNA marker and a genetic locus affecting abdominal fat deposition.     

The ecosystem wilting point defines drought response and recovery of a Quercus-Carya forest

Soil and atmospheric droughts increasingly threaten plant survival and productivity around the world. Yet, conceptual gaps constrain our ability to predict ecosystem-scale drought impacts under climate change. Here, we introduce the ecosystem wilting point (Ψ_EWP), a property that integrates the drought response of an ecosystem's plant community across the soil–plant–atmosphere continuum. Specifically, Ψ_EWP defines a threshold below which the capacity of the root system to extract soil water and the ability of the leaves to maintain stomatal function are strongly diminished. We combined ecosystem flux and leaf water potential measurements to derive the Ψ_EWP of a Quercus-Carya forest from an “ecosystem pressure–volume (PV) curve,” which is analogous to the tissue-level technique. When community predawn leaf water potential (Ψ_pd) was above Ψ_EWP (=−2.0 MPa), the forest was highly responsive to environmental dynamics. When Ψ_pd fell below Ψ_EWP, the forest became insensitive to environmental variation and was a net source of carbon dioxide for nearly 2 months. Thus, Ψ_EWP is a threshold defining marked shifts in ecosystem functional state. Though there was rainfall-induced recovery of ecosystem gas exchange following soaking rains, a legacy of structural and physiological damage inhibited canopy photosynthetic capacity. Although over 16 growing seasons, only 10% of Ψ_pd observations fell below Ψ_EWP, the forest is commonly only 2–4 weeks of intense drought away from reaching Ψ_EWP, and thus highly reliant on frequent rainfall to replenish the soil water supply. We propose, based on a bottom-up analysis of root density profiles and soil moisture characteristic curves, that soil water acquisition capacity is the major determinant of Ψ_EWP, and species in an ecosystem require compatible leaf-level traits such as turgor loss point so that leaf wilting is coordinated with the inability to extract further water from the soil.     

Design considerations for two-stage enrichment clinical trials

When there is a predictive biomarker, enrichment can focus the clinical trial on a benefiting subpopulation. We describe a two-stage enrichment design, in which the first stage is designed to efficiently estimate a threshold and the second stage is a “phase III-like” trial on the enriched population. The goal of this paper is to explore design issues: sample size in Stages 1 and 2, and re-estimation of the Stage 2 sample size following Stage 1. By treating these as separate trials, we can gain insight into how the predictive nature of the biomarker specifically impacts the sample size. We also show that failure to adequately estimate the threshold can have disastrous consequences in the second stage. While any bivariate model could be used, we assume a continuous outcome and continuous biomarker, described by a bivariate normal model. The correlation coefficient between the outcome and biomarker is the key to understanding the behavior of the design, both for predictive and prognostic biomarkers. Through a series of simulations we illustrate the impact of model misspecification, consequences of poor threshold estimation, and requisite sample sizes that depend on the predictive nature of the biomarker. Such insight should be helpful in understanding and designing enrichment trials.     

MULTIVARIATE ANALYSIS OF SELECTION IN EXPERIMENTAL POPULATIONS DERIVED FROM HYBRIDIZATION OF TWO ECOTYPES OF THE ANNUAL PLANT DIODIA TERES W. (RUBIACEAE)

Morphologically variable F₂ genotypes derived from hybridization of coastal and inland ecotypes of the annual plant Diodia teres were used to identify selection on morphological traits in the natural habitat of each ecotype. These ecotypes occur in very different habitats, and have evolved pronounced morphological differentiation. Selection analysis can suggest whether present patterns of selection can explain morphological differences between ecotypes. F₂ genotypes were characterized morphologically, clonally replicated, and transplanted into the habitat of each ecotype. Selection was measured on six morphological traits. Directional and stabilizing selection occurred on many traits; direction and strength of selection varied sharply at different stages of growth, as revealed by a path-analysis approach that divided selection into a set of independent components. Directional selection favored traits of the native population at the coastal habitat, but less so at the inland habitat. Selection was of sufficient strength to create the observed morphological differences between ecotypes in 25–100 generations, given constant selection and sufficient genetic variation. In effects on fitness, most traits were neither independent nor consistently interactive with other traits. Rather, many traits entered into strong but evanescent interactions affecting particular components of fitness. Observed interactions did not support the hypothesis that the morphology of each ecotype was functionally integrated to a high degree.     

THE INTERACTION PHENOTYPE IN THE DROSOPHILA WILLISTONI–SPIROPLASMA SYMBIOSIS

Both the population and coevolutionary dynamics of hereditary male-lethal endosymbionts, found in a wide range of insect species, depend on host fitness and endosymbiont transmission rates. This paper reports on fitness effects and transmission rates in three lines of Drosophila willistoni infected with either male-lethal spiroplasmas or a spontaneous nonmale-lethal mutant. Overall fitness measures were reduced or unaffected by the infection; however, some infected females produced more offspring in early broods. Maternal transmission rates were high, but imperfect, and varied with a female's age, host line, and spiroplasma type. No evidence for paternal or horizontal transmission was found. If an altered temporal pattern of reproduction is not a factor in countering the loss of spiroplasma hosts through imperfect maternal transmission, persistence of this endoparasitism remains unexplained. Tolerance of the infection and ability to transmit bacteria varied with both host and spiroplasma line. Analysis of the interaction between the spontaneous nonmale-lethal mutant and its host suggests this symbiosis has undergone coevolution under laboratory culture.     

Noncancer Risk Assessment: A Probabilistic Alternative to Current Practice

Based on imperfect data and theory, agencies such as the United States Environmental Protection Agency (USEPA) currently derive “reference doses” (RfDs) to guide risk managers charged with ensuring that human exposures to chemicals are below population thresholds. The RfD for a chemical is typically reported as a single number, even though it is widely acknowledged that there are significant uncertainties inherent in the derivation of this number.

In this article, the authors propose a probabilistic alternative to the EPA's method that expresses the human population threshold as a probability distribution of values (rather than a single RfD value), taking into account the major sources of scientific uncertainty in such estimates. The approach is illustrated using much of the same data that USEPA uses to justify their current RfD procedure.

Like the EPA's approach, our approach recognizes the four key extrapolations that are necessary to define the human population threshold based on animal data: animal to human, human heterogeneity, LOAEL to NOAEL, and subchronic to chronic. Rather than using available data to define point estimates of “uncertainty factors” for these extrapolations, the proposed approach uses available data to define a probability distribution of adjustment factors. These initial characterizations of uncertainty can then be refined when more robust or specific data become available for a particular chemical or class of chemicals.

Quantitative characterization of uncertainty in noncancer risk assessment will be useful to risk managers who face complex trade-offs between control costs and protection of public health. The new approach can help decision-makers understand how much extra control cost must be expended to achieve a specified increase in confidence that the human population threshold is not being exceeded.     

Combined genetic and physiological analysis of a locus contributing to quantitative variation

The natural variation of many traits is controlled by multiple genes, individually referred to as quantitative trait loci (QTL), that interact with the environment to determine the ultimate phenotype of any individual. A QTL has yet to be described molecularly, in part because strategies to systematically identify them are underdeveloped and because the subtle nature of QTLs prevents the application of standard methods of gene identification. Therefore, it will be necessary to develop a systematic approach(es) for the identification of QTLs based upon the numerous positional data now being accumulated through molecular marker analyses. We have characterized a QTL by the following three-step approach: (1) identification of a QTL in complex populations, (2) isolation and genetic mapping of this QTL in near-isogenic lines, and (3) identification of a candidate gene using map position and physiological criteria. Using this approach we have characterized a plant height QTL in maize that maps to chromosome 9 near the centromere. Both map position and physiological criteria suggest the gibberillin biosynthesis gene dwarf3 as a candidate gene for this QTL.