Identification of several small main-effect QTLs and a large number of epistatic QTLs for drought tolerance related traits in groundnut (Arachis hypogaea L.).

Cultivated groundnut or peanut (Arachis hypogaea L.), an allotetraploid (2n = 4x = 40), is a self pollinated and widely grown crop in the semi-arid regions of the world. Improvement of drought tolerance is an important area of research for groundnut breeding programmes. Therefore, for the identification of candidate QTLs for drought tolerance, a comprehensive and refined genetic map containing 191 SSR loci based on a single mapping population (TAG 24 x ICGV 86031), segregating for drought and surrogate traits was developed. Genotyping data and phenotyping data collected for more than ten drought related traits in 2-3 seasons were analyzed in detail for identification of main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs) using QTL Cartographer, QTLNetwork and Genotype Matrix Mapping (GMM) programmes. A total of 105 M-QTLs with 3.48-33.36% phenotypic variation explained (PVE) were identified using QTL Cartographer, while only 65 M-QTLs with 1.3-15.01% PVE were identified using QTLNetwork. A total of 53 M-QTLs were such which were identified using both programmes. On the other hand, GMM identified 186 (8.54-44.72% PVE) and 63 (7.11-21.13% PVE), three and two loci interactions, whereas only 8 E-QTL interactions with 1.7-8.34% PVE were identified through QTLNetwork. Interestingly a number of co-localized QTLs controlling 2-9 traits were also identified. The identification of few major, many minor M-QTLs and QTL × QTL interactions during the present study confirmed the complex and quantitative nature of drought tolerance in groundnut. This study suggests deployment of modern approaches like marker-assisted recurrent selection or genomic selection instead of marker-assisted backcrossing approach for breeding for drought tolerance in groundnut.

Fine mapping of the sunflower resistance locus Pl(ARG) introduced from the wild species Helianthus argophyllus.

Downy mildew, caused by Plasmopara halstedii, is one of the most destructive diseases in cultivated sunflower (Helianthus annuus L.). The dominant resistance locus Pl(ARG) originates from silverleaf sunflower (H. argophyllus Torrey and Gray) and confers resistance to all known races of P. halstedii. We mapped Pl(ARG) on linkage group (LG) 1 of (cms)HA342 × ARG1575-2, a population consisting of 2,145 F(2) individuals. Further, we identified resistance gene candidates (RGCs) that cosegregated with Pl(ARG) as well as closely linked flanking markers. Markers from the target region were mapped with higher resolution in NDBLOS(sel) × KWS04, a population consisting of 2,780 F(2) individuals that does not segregate for Pl(ARG). A large-insert sunflower bacterial artificial chromosome (BAC) library was screened with overgo probes designed for markers RGC52 and RGC151, which cosegregated with Pl(ARG). Two RGC-containing BAC contigs were anchored to the Pl(ARG) region on LG 1.

Identifying quantitative trait loci for resistance to Sclerotinia head rot in two USDA sunflower germplasms.

Sclerotinia head rot is a major disease of sunflower in the world, and quantitative trait loci (QTL) mapping could facilitate understanding of the genetic basis of head rot resistance and breeding in sunflower. One hundred twenty-three F2:3 and F2:4 families from a cross between HA 441 and RHA 439 were studied. The mapping population was evaluated for disease resistance in three field experiments in a randomized complete block design with two replicates. Disease incidence (DI) and disease severity (DS) were assessed. A genetic map with 180 target region amplification polymorphism, 32 simple sequence repeats, 11 insertion-deletion, and 2 morphological markers was constructed. Nine DI and seven DS QTL were identified with each QTL explaining 8.4 to 34.5% of phenotypic variance, suggesting the polygenic basis of the resistance to head rot. Five of these QTL were identified in more than one experiment, and each QTL explained more than 12.9% of phenotypic variance. These QTL could be useful in sunflower breeding. Although a positive correlation existed between the two disease indices, most of the respective QTL were located in different chromosomal regions, suggesting a different genetic basis for the two indices.

Using molecular markers to estimate quantitative trait locus parameters: power and genetic variances for unreplicated and replicated progeny.

Many of the progeny types used to estimate quantitative trait locus (QTL) parameters can be replicated, e.g., recombinant inbred, doubled haploid, and F3 lines. These parameters are estimated using molecular markers or QTL genotypes estimated from molecular markers as independent variables. Experiment designs for replicated progeny are functions of the number of replications per line (r) and the number of replications per QTL genotype (n). The value of n is determined by the size of the progeny population (N), the progeny type, and the number of simultaneously estimated QTL parameters (q - 1). Power for testing hypotheses about means of QTL genotypes is increased by increasing r and n, but the effects of these factors have not been quantified. In this paper, we describe how power is affected by r, n, and other factors. The genetic variance between lines nested in QTL genotypes (sigma 2n:q) is the fraction of the genetic variance between lines (sigma 2n) which is not explained by simultaneously estimated intralocus and interlocus QTL parameters (phi 2Q); thus, sigma 2n:q = sigma 2n - phi 2Q. If sigma 2n:q not equal to 0, then power is not efficiently increased by increasing r and is maximized by maximizing n and using r = 1; however, if sigma 2n:q = 0, then r and n affect power equally and power is efficiently increased by increasing r and is maximized by maximizing N.r. Increasing n efficiently increases power for a wide range of values of sigma 2n:q.sigma 2n:q = 0 when the genetic variance between lines is fully explained by QTL parameters (sigma 2n = phi 2Q).(ABSTRACT TRUNCATED AT 250 WORDS)

Nonparametric confidence interval estimators for heritability and expected selection response.

Statistical methods have not been described for comparing estimates of family-mean heritability (H) or expected selection response (R), nor have consistently valid methods been described for estimating R intervals. Nonparametric methods, e.g., delete-one jackknifing, may be used to estimate variances, intervals, and hypothesis test statistics in estimation problems where parametric methods are unsuitable, nonrobust, or undefinable. Our objective was to evaluate normal-approximation jackknife interval estimators for H and R using Monte Carlo simulation. Simulations were done using normally distributed within-family effects and normally, uniformly, and exponentially distributed between-family effects. Realized coverage probabilities for jackknife interval (2) and parametric interval (5) for H were not significantly different from stated probabilities when between-family effects were normally distributed. Coverages for jackknife intervals (3) and (4) for R were not significantly different from stated coverages when between-family effects were normally distributed. Coverages for interval (3) for R were occasionally significantly less than stated when between-family effects were uniformly or exponentially distributed. Coverages for interval (2) for H were occasionally significantly less than stated when between-family effects were exponentially distributed. Thus, intervals (3) and (4) for R and (2) for H were robust. Means of analysis of variance estimates of R were often significantly less than parametric values when the number of families evaluated was 60 or less. Means of analysis of variance estimates of H were consistently significantly less than parametric values. Means of jackknife estimates of H calculated from log transformed point estimates and R calculated from untransformed or log transformed point estimates were not significantly different from parametric values. Thus, jackknife estimators of H and R were unbiased. Delete-one jackknifing is a robust, versatile, and effective statistical method when applied to estimation problems involving variance functions. Jackknifing is especially valuable in hypothesis test estimation problems where the objective is comparing estimates from different populations.

Quantitative resistance to Phytophthora infestans in potato: a case study for QTL mapping in an allogamous plant species.

Phytophthora infestans is the most important fungal pathogen in the cultivated potato (Solanum tuberosum). Dominant, race-specific resistance alleles and quantitative resistance--the latter being more important for potato breeding--are found in the germplasm of cultivated and wild potato species. Quantitative trait loci (QTLs) for resistance to two races of P. infestans have been mapped in an F1 progeny of a cross between non-inbred diploid potato parents with multiple alleles. Interval mapping methods based on highly informative restriction fragment length polymorphism markers revealed 11 chromosome segments on 9 potato chromosomes showing significant contrasts between marker genotypic classes. Whereas phenotypically no difference in quantitative resistance response was observed between the two fungal races, QTL mapping identified at least one race specific QT locus. Two QT regions coincided with two small segments on chromosomes V and XII to which the dominant alleles R1, conferring race specific resistance to P. infestans, Rx1 and Rx2, both inducing extreme resistance to potato virus X, have been allocated in independent mapping experiments. Some minor QTLs were correlated with genetic loci for specific proteins related to pathogenesis, the expression of which is induced after infection with P. infestans.

The development of a genetic map for meadowfoam comprised of amplified fragment length polymorphisms.

Limnanthes alba Benth. (meadowfoam), a diploid ( x=5) winter annual, produces novel very long-chain seed oils (C(20) and C(22)) with less than 2% saturated fatty acids. The first genetic map of meadowfoam, a recently domesticated species, is described herein. Two phenotypically diverse inbred lines, OMF40-11 ( L. alba ssp. alba) and OMF64 ( L. alba ssp. versicolor), were screened for amplified fragment length polymorphisms (AFLPs) using 16 primer combinations. Twenty three percent of the AFLP bands (415 out of 1,801) were polymorphic between OMF40-11 and OMF64. One hundred (OMF40-11xOMF64)xOMF64 BC(1) progeny were genotyped for 107 polymorphic AFLP markers produced by nine AFLP primer combinations. One hundred and three AFLP loci amalgamated into five linkage groups with 14 to 28 loci per linkage group (four loci segregated independently). The map was 698.5-cM long with a mean interlocus spacing of 6.7 cM and no dense clustering of loci. The segregation ratios for 25 loci (23.2%) were significantly distorted. Twenty one of the distorted loci (84%) had an excess of L. alba ssp. versicolor (recurrent parent) alleles. The distorted loci, apart from one locus on linkage group 4, were distally clustered on both ends of linkage groups 1, 4 and 5. The development of the map was facilitated by the small chromosome number, an abundance of restriction site polymorphisms between the two subspecies (23%), and a high multiplex ratio of the AFLP markers (112 per primer combination).

Stearoyl-ACP and oleoyl-PC desaturase genes cosegregate with quantitative trait loci underlying high stearic and high oleic acid mutant phenotypes in sunflower.

The genetic control of the synthesis of stearic acid (C18:0) and oleic acid (C18:1) in the seed oil of sunflower was studied through candidate-gene and QTL analysis. Two F(2) mapping populations were developed using the high C18:0 mutant CAS-3 crossed to either HA-89 (standard, high linoleic fatty acid profile), or HAOL-9 (high C18:1 version of HA-89). A stearoyl-ACP desaturase locus (SAD17A), and an oleoyl-PC de-saturase locus (OLD7) were found to cosegregate with the previously described Es1 and Ol genes controlling the high C18:0 and the high C18:1 traits, respectively. Using linkage maps constructed from AFLP and RFLP markers, these loci mapped to LG1 (SAD17A) and to LG14 (OLD7) and were found to underlie the major QTLs affecting the concentrations of C18:0 and C18:1, explaining around 80% and 56% of the phenotypic variance of these fatty acids, respectively. These QTLs pleiotropically affected the levels of other primary fatty acids in the seed storage lipids. A minor QTL affecting both C18:0 and C18:1 levels was identified on LG8 in the HAOL-9xCAS-3 F(2). This QTL showed a significant epistatic interaction for C18:1 with the QTL at the OLD7 locus, and was hypothesized to be a modifier of Ol. Two additional minor C18:0 QTLs were also detected on LG7 and LG3 in the HA-89xCAS-3 and the HAOL-9xCAS-3 F(2) populations, respectively. No association between a mapped FatB thioesterase locus and fatty acid concentration was found. These results provide strong support about the role of fatty acid desaturase genes in determining fatty acid composition in the seed oil of sunflower.

Incineration and monitoring of low-level 3H and 14C wastes at a biological research institution.

Low-level radioactive waste containing liquid scintillation fluid and known amounts of 14C and 3H has been incinerated in a modified pathological incinerator with the incinerator effluent, refractory surface and ash being monitored. The study relates the activity monitored to that incinerated and discusses how this relation was affected by a modification of the incinerator and monitoring conditions. No significant activity was found to be associated with the ash, particulates or the refractory surface. These data suggest that most of the activity is released as tritiated water vapor and 14C-labeled carbon dioxide. However, incomplete oxidation may occur for short periods of time depending on the amount of liquid scintillation fluid incinerated, with the possible release of 14C-labeled carbon monoxide.

Considerations for ethical practice in managed care.

How does one maintain an ethical practice while facing the requirements and limits of a health care system that is dominated by managed care? Psychologists are increasingly raising such questions about ethical issues when working in or contracting with managed care organizations. The authors review the process involved in ethical decision making and problem solving and focus on 4 areas in which ethical dilemmas most commonly arise in a managed care context: informed consent, confidentiality, abandonment, and utilization management-utilization review. The need for sustained and organized advocacy efforts to ensure patient access to quality health care is discussed, as is the impact of managed care's competitive marketplace on professional relationships. Hypothetical examples of typical dilemmas psychologists face in the current practice environment are provided to illustrate systematic ethical decision making.

Quantitative trait locus analysis and construction of consensus genetic map for foliar disease resistance based on two recombinant inbred line populations in cultivated groundnut (Arachis hypogaea L.).

Late leaf spot (LLS) and rust have the greatest impact on yield losses worldwide in groundnut (Arachis hypogaea L.). With the objective of identifying tightly linked markers to these diseases, a total of 3,097 simple sequence repeats (SSRs) were screened on the parents of two recombinant inbred line (RIL) populations, namely TAG 24 × GPBD 4 (RIL-4) and TG 26 × GPBD 4 (RIL-5), and segregation data were obtained for 209 marker loci for each of the mapping populations. Linkage map analysis of the 209 loci resulted in the mapping of 188 and 181 loci in RIL-4 and RIL-5 respectively. Using 143 markers common to the two maps, a consensus map with 225 SSR loci and total map distance of 1,152.9 cM was developed. Comprehensive quantitative trait locus (QTL) analysis detected a total of 28 QTL for LLS and 15 QTL for rust. A major QTL for LLS, namely QTL(LLS)01 (GM1573/GM1009-pPGPseq8D09), with 10.27-62.34% phenotypic variance explained (PVE) was detected in all the six environments in the RIL-4 population. In the case of rust resistance, in addition to marker IPAHM103 identified earlier, four new markers (GM2009, GM1536, GM2301 and GM2079) showed significant association with the major QTL (82.96% PVE). Localization of 42 QTL for LLS and rust on the consensus map identified two candidate genomic regions conferring resistance to LLS and rust. One region present on linkage group AhXV contained three QTL each for LLS (up to 67.98% PVE) and rust (up to 82.96% PVE). The second candidate genomic region contained the major QTL with up to 62.34% PVE for LLS. Molecular markers associated with the major QTL for resistance to LLS and rust can be deployed in molecular breeding for developing groundnut varieties with enhanced resistance to foliar diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11032-011-9661-z) contains supplementary material, which is available to authorized users.

Quantitative trait locus analysis and construction of consensus genetic map for drought tolerance traits based on three recombinant inbred line populations in cultivated groundnut (Arachis hypogaea L.).

Groundnut (Arachis hypogaea L.) is an important food and cash crop grown mainly in semi-arid tropics (SAT) regions of the world where drought is the major constraint on productivity. With the aim of understanding the genetic basis and identification of quantitative trait loci (QTL) for drought tolerance, two new recombinant inbred line (RIL) mapping populations, namely ICGS 76 × CSMG 84-1 (RIL-2) and ICGS 44 × ICGS 76 (RIL-3), were used. After screening of 3,215 simple sequence repeat (SSR) markers on the parental genotypes of these populations, two new genetic maps were developed with 119 (RIL-2) and 82 (RIL-3) SSR loci. Together with these maps and the reference map with 191 SSR loci based on TAG 24 × ICGV 86031 (RIL-1), a consensus map was constructed with 293 SSR loci distributed over 20 linkage groups, spanning 2,840.8 cM. As all these three populations segregate for drought-tolerance-related traits, a comprehensive QTL analysis identified 153 main effect QTL (M-QTL) and 25 epistatic QTL (E-QTL) for drought-tolerance-related traits. Localization of these QTL on the consensus map provided 16 genomic regions that contained 125 QTL. A few key genomic regions were selected on the basis of the QTL identified in each region, and their expected role in drought adaptation is also discussed. Given that no major QTL for drought adaptation were identified, novel breeding approaches such as marker-assisted recurrent selection (MARS) and genomic selection (GS) approaches are likely to be the preferred approaches for introgression of a larger number of QTL in order to breed drought-tolerant groundnut genotypes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11032-011-9660-0) contains supplementary material, which is available to authorized users.

Selection for low erucic acid and genetic mapping of loci affecting the accumulation of very long-chain fatty acids in meadowfoam seed storage lipids.

Erucic acid (22:1(13)) has been identified as an anti-nutritional compound in meadowfoam (Limnanthes alba) and other oilseeds in the Brassicales, a classification which has necessitated the development of low erucic acid cultivars for human consumption. The erucic acid concentrations of meadowfoam wild types (8%-24%) surpass industry standards for human consumption (

The first SSR-based genetic linkage map for cultivated groundnut (Arachis hypogaea L.).

Molecular markers and genetic linkage maps are pre-requisites for molecular breeding in any crop species. In case of peanut or groundnut (Arachis hypogaea L.), an amphidiploid (4X) species, not a single genetic map is, however, available based on a mapping population derived from cultivated genotypes. In order to develop a genetic linkage map for tetraploid cultivated groundnut, a total of 1,145 microsatellite or simple sequence repeat (SSR) markers available in public domain as well as unpublished markers from several sources were screened on two genotypes, TAG 24 and ICGV 86031 that are parents of a recombinant inbred line mapping population. As a result, 144 (12.6%) polymorphic markers were identified and these amplified a total of 150 loci. A total of 135 SSR loci could be mapped into 22 linkage groups (LGs). While six LGs had only two SSR loci, the other LGs contained 3 (LG_AhXV) to 15 (LG_AhVIII) loci. As the mapping population used for developing the genetic map segregates for drought tolerance traits, phenotyping data obtained for transpiration, transpiration efficiency, specific leaf area and SPAD chlorophyll meter reading (SCMR) for 2 years were analyzed together with genotyping data. Although, 2-5 QTLs for each trait mentioned above were identified, the phenotypic variation explained by these QTLs was in the range of 3.5-14.1%. In addition, alignment of two linkage groups (LGs) (LG_AhIII and LG_AhVI) of the developed genetic map was shown with available genetic maps of AA diploid genome of groundnut and Lotus and Medicago. The present study reports the construction of the first genetic map for cultivated groundnut and demonstrates its utility for molecular mapping of QTLs controlling drought tolerance related traits as well as establishing relationships with diploid AA genome of groundnut and model legume genome species. Therefore, the map should be useful for the community for a variety of applications.

Identification and validation of QTL for Sclerotinia midstalk rot resistance in sunflower by selective genotyping.

Midstalk rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in sunflower (Helianthus annuus L.). Objectives of this study were to: (1) estimate the number, genomic positions and genetic effects of quantitative trait loci (QTL) for resistance to midstalk rot in line TUB-5-3234, derived from an interspecific cross; (2) determine congruency of QTL between this line and other sources of resistance; and (3) make inferences about the efficiency of selective genotyping (SG) in detecting QTL conferring midstalk rot resistance in sunflower. Phenotypic data for three resistance (stem lesion, leaf lesion and speed of fungal growth) and two morphological (leaf length and leaf length with petiole) traits were obtained from 434 F3 families from cross CM625 (susceptible) x TUB-5-3234 (resistant) under artificial infection in field experiments across two environments. The SG was applied by choosing the 60 most resistant and the 60 most susceptible F3 families for stem lesion. For genotyping of the respective F2 plants, 78 simple sequence repeat markers were used. Genotypic variances were highly significant for all traits. Heritabilities and genotypic correlations between reMidstalk rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in sunflower (Helianthus annuus L.). Objectives of this study were to: (1) estimate the number, genomic positions and genetic effects of quantitative trait loci (QTL) for resistance to midstalk rot in line TUB-5-3234, derived from an interspecific cross; (2) determine congruency of QTL between this line and other sources of resistance; and (3) make inferences about the efficiency of selective genotyping (SG) in detecting QTL conferring midstalk rot resistance in sunflower. Phenotypic data for three resistance (stem lesion, leaf lesion and speed of fungal growth) and two morphological (leaf length and leaf length with petiole) traits were obtained from 434 F3 families from cross CM625 (susceptible) x TUB-5-3234 (resistant) under artificial infection in field experiments across two environments. The SG was applied by choosing the 60 most resistant and the 60 most susceptible F3 families for stem lesion. For genotyping of the respective F2 plants, 78 simple sequence repeat markers were used. Genotypic variances were highly significant for all traits. Heritabilities and genotypic correlations between resistance traits were moderate to high. Three to four putative QTL were detected for each resistance trait explaining between 40.8% and 72.7% of the genotypic variance (PTS). Two QTL for stem lesion showed large genetic effects and corroborated earlier findings from the cross NDBLOSsel (resistant) x CM625 (susceptible). Our results suggest that SG can be efficiently used for QTL detection and the analysis of congruency for resistance genes across populations.

Identification and mapping of SNPs from ESTs in sunflower.

More than 67,000 expressed sequence tags (ESTs) have recently been generated for sunflower (Helianthus), including 44,000 from cultivated confectionery (RHA280) and oilseed (RHA801) lines of Helianthus annuus and 23,000 from drought- and salt-tolerant wild sunflowers, H. argophyllus and H. paradoxus, respectively. To create a transcript map for sunflower, we identified 605 ESTs that displayed small insertion-deletion polymorphism (SNP) variation in silico, had apparent tissue-specific expression patterns, and/or were ESTs with candidate functions in traits such as development, cell transport, metabolism, plant defense, and tolerance to abiotic stress. Primer pairs for 535 of the loci were designed from the ESTs and screened for polymorphism in recombinant inbred lines derived from a cross between the same cultivars (RHA280 x RHA801) employed for sequencing. In total, 273 of the loci amplified polymorphic products, of which 243 mapped to the 17 linkage groups previously identified for sunflower. Comparisons with previously mapped QTL revealed some cases where ESTs with putatively related functions mapped near QTLs identified in other crosses for salt tolerance and for domestication traits such as stem diameter, shattering, flowering time, and achene size.

Using molecular markers to map multiple quantitative trait loci: models for backcross, recombinant inbred, and doubled haploid progeny.

To maximize parameter estimation efficiency and statistical power and to estimate epistasis, the parameters of multiple quantitative trait loci (QTLs) must be simultaneously estimated. If multiple QTL affect a trait, then estimates of means of QTL genotypes from individual locus models are statistically biased. In this paper, I describe methods for estimating means of QTL genotypes and recombination frequencies between marker and quantitative trait loci using multilocus backcross, doubled haploid, recombinant inbred, and testcross progeny models. Expected values of marker genotype means were defined using no double or multiple crossover frequencies and flanking markers for linked and unlinked quantitative trait loci. The expected values for a particular model comprise a system of nonlinear equations that can be solved using an interative algorithm, e.g., the Gauss-Newton algorithm. The solutions are maximum likelihood estimates when the errors are normally distributed. A linear model for estimating the parameters of unlinked quantitative trait loci was found by transforming the nonlinear model. Recombination frequency estimators were defined using this linear model. Certain means of linked QTLs are less efficiently estimated than means of unlinked QTLs.

Confidence intervals for heritability for two-factor mating design single environment linear models.

Precision measurement is an essential part of heritability estimate interpretation. Approximate standard errors are commonly used as measures of precision for heritability on a progeny mean basis (H). Their derivation, however, is not inferred from the distribution theory for H. F-distribution based exact confidence intervals have been derived for some onefactor mating design H estimators. Extension of the confidence interval results from one-factor to twofactor mating designs is reported in this paper. Functions of heritability on a full-sib or half-sib progeny mean basis from nested or factorial mating design parameters were distributed according to the F-distribution. Exact confidence intervals were derived for heritability on a full-sib progeny mean basis. Exact confidence intervals for heritability on a half-sib progeny basis were adapted from previous results. Maize (Zea mays L.) data were used to estimate confidence intervals. Complete equations were given for interpolation in F-tables.

Mating systems of Cuphea laminuligera and Cuphea lutea.

In this paper, the mating systems of experimental populations of C. laminuligera and C. lutea are described. Outcrossing rates (t) were estimated for four populations of C. laminuligera and three populations of C. lutea using allozyme phenotypes of open-pollinated individual plant families. Populations were grown at densities of 1.0 × 1.0 m (low) and 0.04 × 0.3 m (high). Pollen and ovule frequencies and single locus and multilocus outcrossing rates were estimated for each population using the mixed-mating model. Multilocus estimates of t ranged from 0.83 to 0.98 and 1.00 to 1.01 for low and high density populations of C. laminuligera, respectively, and 0.17 to 0.26 and 0.36 to 0.54 for low and high density populations of C. lutea, respectively. C. laminuligera is predominantly allogamous; however, selfing rates as great as 17% were observed for this species. C. lutea is predominantly autogamous, but outcrossing rates as great as 54% were observed for this species. Outcrossing rates increased as density increased within C. lutea populations.

Parametric and jackknife confidence interval estimators for two-factor mating design genetic variance ratios.

Confidence interval estimators have not been defined for dominance to additive genetic variance (θ) and average degree of dominance (δ) for the nested, factorial, and backcross mating designs. The objective of this paper was to describe interval estimators for these parameters. Approximate F random variables were defined for expected mean square (EMS) ratios for linear models with one environmental effect. Approximate 1-α parametric interval estimators were defined for θ and δ using these random variables. Random variables defined for linear models with no environmental effects are not approximately distributed as F random variables because common EMS are involved in the numerators and denominators of the EMS ratios. Delete-one jackknife (jackknife) interval estimators were defined for θ and δ for linear models with zero or one environmental effect(s); In transformed analysis of variance point estimates were used in pseudovalue estimators.