Prediction of single-cross hybrid performance in maize using haplotype blocks associated with QTL for grain yield

Marker-based prediction of hybrid performance facilitates the identification of untested single-cross hybrids with superior yield performance. Our objectives were to (1) determine the haplotype block structure of experimental germplasm from a hybrid maize breeding program, (2) develop models for hybrid performance prediction based on haplotype blocks, and (3) compare hybrid performance prediction based on haplotype blocks with other approaches, based on single AFLP markers or general combining ability (GCA), under a validation scenario relevant for practical breeding. In total, 270 hybrids were evaluated for grain yield in four Dent × Flint factorial mating experiments. Their parental inbred lines were genotyped with 20 AFLP primer–enzyme combinations. Adjacent marker loci were combined into haplotype blocks. Hybrid performance was predicted on basis of single marker loci and haplotype blocks. Prediction based on variable haplotype block length resulted in an improved prediction of hybrid performance compared with the use of single AFLP markers. Estimates of prediction efficiency (R ² ) ranged from 0.305 to 0.889 for marker-based prediction and from 0.465 to 0.898 for GCA-based prediction. For inter-group hybrids with predominance of general over specific combining ability, the hybrid prediction from GCA effects was efficient in identifying promising hybrids. Considering the advantage of haplotype block approaches over single marker approaches for the prediction of inter-group hybrids, we see a high potential to substantially improve the efficiency of hybrid breeding programs. Tobias A. Schrag and Hans Peter Maurer contributed equally to this work.     

Prediction of maize double-cross hybrids using the best linear unbiased prediction with microsatellite marker information

We examined the usefulness of the best linear unbiased prediction associated with molecular markers for prediction of untested maize double-cross hybrids. Ten single-cross hybrids from different commercial backgrounds were crossed using a complete diallel design. These 10 single-cross hybrids were genotyped with 20 microsatellite markers. The best linear unbiased prediction associated with microsatellite information gave relatively good prediction ability of the double-cross hybrid performance, with correlations between observed phenotypic values and genotypic prediction values varying from 0.27 to 0.54. Taking into account the predictions of specific combing ability, the correlation between observed and predicted specific combining ability varied from 0.50 to 0.88. Based on these results, we infer that it is feasible to predict maize double-cross hybrids with different unbalance degrees without including any prior information about parental inbreed lines or single-cross hybrid performance.     

Prediction of hybrid performance in maize using molecular markers and joint analyses of hybrids and parental inbreds

The identification of superior hybrids is important for the success of a hybrid breeding program. However, field evaluation of all possible crosses among inbred lines requires extremely large resources. Therefore, efforts have been made to predict hybrid performance (HP) by using field data of related genotypes and molecular markers. In the present study, the main objective was to assess the usefulness of pedigree information in combination with the covariance between general combining ability (GCA) and per se performance of parental lines for HP prediction. In addition, we compared the prediction efficiency of AFLP and SSR marker data, estimated marker effects separately for reciprocal allelic configurations (among heterotic groups) of heterozygous marker loci in hybrids, and imputed missing AFLP marker data for marker-based HP prediction. Unbalanced field data of 400 maize dent × flint hybrids from 9 factorials and of 79 inbred parents were subjected to joint analyses with mixed linear models. The inbreds were genotyped with 910 AFLP and 256 SSR markers. Efficiency of prediction (R ²) was estimated by cross-validation for hybrids having no or one parent evaluated in testcrosses. Best linear unbiased prediction of GCA and specific combining ability resulted in the highest efficiencies for HP prediction for both traits (R ² = 0.6–0.9), if pedigree and line per se data were used. However, without such data, HP for grain yield was more efficiently predicted using molecular markers. The additional modifications of the marker-based approaches had no clear effect. Our study showed the high potential of joint analyses of hybrids and parental inbred lines for the prediction of performance of untested hybrids.     

Genome‐wide association analyses reveal the genetic basis of combining ability in rice

Combining ability is a measure for selecting elite parents and predicting hybrid performance in plant breeding. However, the genetic basis of combining ability remains unclear and a global view of combining ability from diverse mating designs is lacking. We developed a North Carolina II (NCII) population of 96 Oryza sativa and four male sterile lines to identify parents of greatest value for hybrid rice production. Statistical analyses indicated that general combining ability (GCA) and specific combining ability (SCA) contributed variously to different agronomic traits. In a genome‐wide association study (GWAS) of agronomic traits, GCA and SCA, we identified 34 significant associations (P < 2.39 × 10^?7). The superior alleles of GCA loci (Ghd8, GS3 and qSSR4) accumulated in parental lines with high GCA and explained 30.03% of GCA variance in grain yield, indicating that molecular breeding of high GCA parental lines is feasible. The distinct distributions of these QTLs contributed to the differentiation of parental GCA in subpopulations. GWAS of SCA identified 12 more loci that showed dominance on corresponding agronomic traits. We conclude that the accumulation of superior GCA and SCA alleles is an important contributor to heterosis and QTLs that greatly contributed to combining ability in our study would accelerate the identification of elite inbred lines and breeding of super hybrids.     

Identification of combining ability loci for five yield-related traits in maize using a set of testcrosses with introgression lines

Combining ability is essential for hybrid breeding in crops. However, the genetic basis of combining ability remains unclear and has been seldom investigated. Identifying molecular markers associated with this complex trait would help to understand its genetic basis and provide useful information for hybrid breeding in maize. In this study, we identified genetic loci of general combining ability (GCA) and specific combining ability (SCA) for five yield-related traits under three environments using a set of testcrosses with introgression lines (ILs). GCA or SCA of the five yield-related traits of the ILs was estimated by the performance of testcrosses with four testers from different heterotic groups. Genetic correlations between GCA of the traits and the corresponding traits per se were not significant or not strong, suggesting that the genetic basis between them is different. A total of 56 significant loci for GCA and 21 loci for SCA were commonly identified in at least two environments, and only 5 loci were simultaneously controlling GCA and SCA, indicating that the genetic basis of GCA and SCA is different. For all of the traits investigated, positive and significant correlations between the number of GCA loci in the ILs and the performance of the corresponding GCA of the ILs were detected, implying that pyramiding GCA loci would have positive effect on the performance of GCA. Results in this study would be useful for maize hybrid breeding.     

Genomewide predictions from maize single-cross data

Maize (Zea mays L.) breeders evaluate many single-cross hybrids each year in multiple environments. Our objective was to determine the usefulness of genomewide predictions, based on marker effects from maize single-cross data, for identifying the best untested single crosses and the best inbreds within a biparental cross. We considered 479 experimental maize single crosses between 59 Iowa Stiff Stalk Synthetic (BSSS) inbreds and 44 non-BSSS inbreds. The single crosses were evaluated in multilocation experiments from 2001 to 2009 and the BSSS and non-BSSS inbreds had genotypic data for 669 single nucleotide polymorphism (SNP) markers. Single-cross performance was predicted by a previous best linear unbiased prediction (BLUP) approach that utilized marker-based relatedness and information on relatives, and from genomewide marker effects calculated by ridge-regression BLUP (RR-BLUP). With BLUP, the mean prediction accuracy (r _MG) of single-cross performance was 0.87 for grain yield, 0.90 for grain moisture, 0.69 for stalk lodging, and 0.84 for root lodging. The BLUP and RR-BLUP models did not lead to r _MG values that differed significantly. We then used the RR-BLUP model, developed from single-cross data, to predict the performance of testcrosses within 14 biparental populations. The r _MG values within each testcross population were generally low and were often negative. These results were obtained despite the above-average level of linkage disequilibrium, i.e., r ² between adjacent markers of 0.35 in the BSSS inbreds and 0.26 in the non-BSSS inbreds. Overall, our results suggested that genomewide marker effects estimated from maize single crosses are not advantageous (compared with BLUP) for predicting single-cross performance and have erratic usefulness for predicting testcross performance within a biparental cross.     

Correlations and comparisons of quantitative trait loci with family per se and testcross performance for grain yield and related traits in maize

Simultaneous improvement in grain yield and related traits in maize hybrids and their parents (inbred lines) requires a better knowledge of genotypic correlations between family per se performance (FP) and testcross performance (TP). Thus, to understand the genetic basis of yield-related traits in both inbred lines and their testcrosses, two F _2:3 populations (including 230 and 235 families, respectively) were evaluated for both FP and TP of eight yield-related traits in three diverse environments. Genotypic correlations between FP and TP, $ \hat{r}_{\text{g}} $ (FP, TP), were low (0–0.16) for grain yield per plant (GYPP) and kernel number per plant (KNPP) in the two populations, but relatively higher (0.32–0.69) for the other six traits with additive effects as the primary gene action. Similar results were demonstrated by the genotypic correlations between observed and predicted TP values based on quantitative trait loci positions and effects for FP, $ \hat{r}_{\text{g}} $ (M _FP, Y _TP). A total of 88 and 35 QTL were detected with FP and TP, respectively, across all eight traits in the two populations. However, the genotypic variances explained by the QTL detected in the cross-validation analysis were much lower than those in the whole data set for all traits. Several common QTL between FP and TP that accounted for large phenotypic variances were clustered in four genomic regions (bin 1.10, 4.05–4.06, 9.02, and 10.04), which are promising candidate loci for further map-based cloning and improvement in grain yield in maize. Compared with publicly available QTL data, these QTL were also detected in a wide range of genetic backgrounds and environments in maize. These results imply that effective selection based on FP to improve TP could be achieved for traits with prevailing additive effects.     

Physiological N response of field-grown maize hybrids (Zea mays L.) with divergent yield potential and grain protein concentration

Fertilizer N availability impacts photosynthesis and crop performance, although cause–effect relationships are not well established, especially for field-grown plants. Our objective was to determine the relationship between N supply and photosynthetic capacity estimated by leaf area index (LAI) and single leaf photosynthesis using genetically diverse field-grown maize (Zea mays L.) hybrids. We compared a high yield potential commercial hybrid (FR1064 x LH185) and an experimental hybrid (FR1064 x IHP) with low yield potential but exceptionally high grain protein concentration. Plant biomass and physiological traits were measured at tassel emergence (VT) and at the grain milk stage (R3) to assess the effects of N supply on photosynthetic source capacity and N uptake, and grain yield and grain N were measured at maturity. Grain yield of FR1064 x LH185 was much greater than FR1064 x IHP even though plant biomass and LAI were larger for FR1064 x IHP, and single leaf photosynthesis was similar for both hybrids. Although photosynthetic capacity was not related to hybrid differences in productivity, increasing N supply led to proportional increases in grain yield, plant biomass, LAI, photosynthesis, and Rubisco and PEP carboxylase activities for both hybrids. Thus, a positive relationship between photosynthetic capacity and yield was revealed by hybrid response to N supply, and the relationship was similar for hybrids with a marked difference in yield potential. For both hybrids the N response of single leaf CER and initial Rubisco activity was negative when expressed per unit of leaf N. In contrast, PEP carboxylase activity per unit leaf N increased in response to N availability, indicating that PEP carboxylase served as a reservoir for excess N accumulation in field-grown maize leaves. The correlation between CER and initial Rubisco activity was highly significant when expressed on a leaf area or a total leaf basis. The results suggest that regardless of genotypic yield potential, maize CER, and potentially grain yield, could be improved by increasing the partitioning of N into Rubisco.     

Heterotic patterns in rapeseed (<Emphasis Type="Italic">Brassica napus</Emphasis> L.): I. Crosses between spring and Chinese semi-winter lines

Chinese semi-winter rapeseed is genetically diverse from Canadian and European spring rapeseed. This study was conducted to evaluate the potential of semi-winter rapeseed for spring rapeseed hybrid breeding, to assess the genetic effects involved, and to estimate the correlation of parental genetic distance (GD) with hybrid performance, heterosis, general combining ability (GCA) and specific combining ability (SCA) in crosses between spring and semi-winter rapeseed lines. Four spring male sterile lines from Germany and Canada as testers were crossed with 13 Chinese semi-winter rapeseed lines to develop 52 hybrids, which were evaluated together with their parents and commercial hybrids for seed yield and oil content in three sets of field trials with 8 environments in Canada and Europe. The Chinese parental lines were not adapted to local environmental conditions as demonstrated by poor seed yields per se. However, the hybrids between the Chinese parents and the adapted spring rapeseed lines exhibited high heterosis for seed yield. The average mid-parent heterosis was 15% and ca. 50% of the hybrids were superior to the respective hybrid control across three sets of field trials. Additive gene effects mainly contributed to hybrid performance since the mean squares of GCA were higher as compared to SCA. The correlation between parental GD and hybrid performance and heterosis was found to be low whereas the correlation between GCA_{(f + m)} and hybrid performance was high and significant in each set of field trials, with an average of r = 0.87 for seed yield and r = 0.89 for oil content, indicating that hybrid performance can be predicted by GCA_{(f + m)}. These results demonstrate that Chinese semi-winter rapeseed germplasm has a great potential to increase seed yield in spring rapeseed hybrid breeding programs in Canada and Europe.     

Prediction of maize hybrid performance using similarity in state and similarity by descent information

We evaluated the efficiency of the best linear unbiased predictor (BLUP) and the influence of the use of similarity in state (SIS) and similarity by descent (SBD) in the prediction of untested maize hybrids. Nine inbred lines of maize were crossed using a randomized complete diallel method. These materials were genotyped with 48 microsatellite markers (SSR) associated with the QTL regions for grain yield. Estimates of four coefficients of SIS and four coefficients of SBD were used to construct the additive genetic and dominance matrices, which were later used in combination with the BLUP for predicting genotypic values and specific combining ability (SCA) in unanalyzed hybrids under simulated unbalance. The values of correlations between the genotypic values predicted and the means observed, depending on the degree of unbalance, ranged from 0.48 to 0.99 for SIS and 0.40 to 0.99 using information from SBD. The results obtained for the SCA ranged from 0.26 to 0.98 using the SIS and 0.001 to 0.990 using the SBD information. It was also observed that the predictions using SBD showed less biased than SIS predictions demonstrating that the predictions obtained by these coefficients (SBD) were closer to the observed value, but were less efficient in the ranking of genotypes. Although the SIS showed a bias due to overestimation of relatedness, this type of coefficient may be used where low values are detected in the SBD in the group of parents because of its greater efficiency in ranking the candidates hybrids.     

Optimum prediction of three-way crosses from single crosses in forage maize (Zea mays L.)

Summary Three-way cross means were predicted with formulae involving linear functions of general (GCA) and specific combining ability (SCA) effects estimated from single-cross factorials between genetically divergent populations. Data from an experiment with 66 single-cross and 66 three-way cross forage maize (Zea mays L.) hybrids was used for comparing the prediction formulae. The genotypic correlation (r) between observed and predicted three-way crosses increased with increasing , the weighting factor of SCA effects, for plant height and ear dry matter (DM) content. It displayed slightly convex curves for total and stover DM yield, ear percentage, and metabolizable energy content of stover. For Jenkins' method B, r was considerably less than 1.0 for all traits, indicating the presence of epistasis. The square root of heritability (h) of the predicted means decreased with increasing , the reduction being small with a greater number of test environments. Using the product r·h as a criterion of efficiency, none of the prediction methods was consistently superior and the differences among them were rather small (< 7.5%) for all traits, irrespective of the number of test environments. We recommend evaluating the GCA of a greater number of lines from each parent population in testcrosses with a small number of elite lines from the opposite population. All possible three-way or double crosses between both sets of lines should be predicted by Jenkins's method C. This procedure allows one to select with a higher intensity among the predicted hybrids and thus should increase the genetic gain.Extended version of a paper (Geiger et al. 1986) read at the sixth meeting of the EUCARPIA Section Biometrics in Plant Breeding held at Birmingham, UK, July 28–August 1, 1986     

The anther-culture response of triticale line x tester progenies

Seven triticale cultivars (Ampiac, Aubrac, Trinidad, Ticino, Lamberto, Pronto and Prado) and their F1 hybrids obtained after crossing in a line x tester scheme were examined with respect to their androgenetic effectiveness. The embryo induction rate (number of embryos per 100 anthers), green plant regeneration rate (number of green plantlets per 100 embryos), plant yield (number of green and albino plantlets per 100 anthers) and green plant yield (number of green plantlets per 100 anthers) were assessed. The multivariate and univariate effects of general (GCA) and specific (SCA) combining abilities for the studied traits were estimated and tested. Significant differences between the genotypes were found for individual traits as well as for all the traits treated jointly. Hybrids generally showed a better response in anther culture than their parental genotypes. Heterosis effects were observed in some hybrids for embryo induction rate and green plant yield. GCA and SCA variances were significant and a dominance of the GCA over the SCA variation was found. Among the examined cultivars, Ticino and Pronto were characterised by positive and significant GCA for embryo induction and green plant yield, and these cultivars may be recommended for the improvement of anther culture responsiveness in triticale.     

Quantitative trait loci for grain moisture at harvest and field grain drying rate in maize (Zea mays, L.)

Hybrids with low grain moisture (GM) at harvest are specially required in mid- to short-season environments. One of the most important factors determining this trait is field grain drying rate (FDR). To produce hybrids with low GM at harvest, inbred lines can be obtained through selection for either GM or FDR. Thus, a single-cross population (181 F _2:3-generation plants) of two divergent inbred lines was evaluated to locate QTL affecting GM at harvest and FDR as a starting point for marker assisted selection (MAS). Moisture measurements were made with a hand-held moisture meter. Detection of QTL was facilitated with interval mapping in one and two dimensions including an interaction term, and a genetic linkage map of 122 SSR loci covering 1,557.8 cM. The markers were arranged in ten linkage groups. QTL mapping was made for the mean trait performance of the F _2:3 population across years. Ten QTL and an interaction were associated with GM. These QTL accounted for 54.8 and 65.2% of the phenotypic and genotypic variation, respectively. Eight QTL and two interactions were associated with FDR accounting for 35.7 and 45.2% of the phenotypic and genotypic variation, respectively. Two regions were in common between traits. The interaction between QTL for GM at harvest had practical implications for MAS. We conclude that MAS per se will not be an efficient method for reducing GM at harvest and/or increasing FDR. A selection index including both molecular marker information and phenotypic values, each appropriately weighted, would be the best selection strategy.     

Associations between quantitative traits and enzyme loci in the F2 population of a maize hybrid

Summary Univariate and multivariate analyses were used to identify associations between eight enzyme marker loci and 11 quantitative traits of maize (Zea mays L.). The material analyzed included inbred lines Wf9 and Pa405, single-cross hybrid Wf9 X Pa405, and the F2 generation of the selfed single-cross hybrid. Each enzyme locus assayed was associated with at least one quantitative trait, and all quantitative traits were associated with genotypes at particular enzyme loci. Significant associations also were found between the level of heterozygosity per individual and nine of 11 quantitative traits. The total contribution to heterosis, for seed yield per plant, of genes linked with the eight enzyme loci, was 27% of the F2 mean and 18% of the difference in mean between the F1 hybrid and the inbred parents. Genes linked with Glu1 accounted for nearly one third of the total dominance effect detected by the eight enzyme loci. The chromosome segments marked by loci with significant effects on seed yield were markedly overdominant. The large heterotic effects of chromosome segments marked by particular loci suggest that enzyme loci could be used to help transfer genes responsible for heterosis to inbred lines. We conclude that analyses of additional inbred lines, F1 hybrids, and F2 populations in more environments will halp identify specific associations between enzyme loci, or chromosome segments which they mark, and important agronomic traits.Cooperative investigations of the USDA, ARS and Dept. of Plant Sciences, South Dakota State Univ. (SDSU), Brookings, Journal Series No. 2039; and the Institute of Animal Resource Ecology, Univ. of British Columbia, Vancouver, B.C. V6T 1W5, Canada     

Molecular marker-based prediction of hybrid performance in maize using unbalanced data from multiple experiments with factorial crosses

In hybrid breeding, the prediction of hybrid performance (HP) is extremely important as it is difficult to evaluate inbred lines in numerous cross combinations. Recent developments such as doubled haploid production and molecular marker technologies have enhanced the prospects of marker-based HP prediction to accelerate the breeding process. Our objectives were to (1) predict HP using a combined analysis of hybrids and parental lines from a breeding program, (2) evaluate the use of molecular markers in addition to phenotypic and pedigree data, (3) evaluate the combination of line per se data with marker-based estimates, (4) study the effect of the number of tested parents, and (5) assess the advantage of haplotype blocks. An unbalanced dataset of 400 hybrids from 9 factorial crosses tested in different experiments and data of 79 inbred parents were subjected to combined analyses with a mixed linear model. Marker data of the inbreds were obtained with 20 AFLP primer–enzyme combinations. Cross-validation was used to assess the performance prediction of hybrids of which no or only one parental line was testcross evaluated. For HP prediction, the highest proportion of explained variance (R ²), 46% for grain yield (GY) and 70% for grain dry matter content (GDMC), was obtained from line per se best linear unbiased prediction (BLUP) estimates plus marker effects associated with mid-parent heterosis (TEAM-LM). Our study demonstrated that HP was efficiently predicted using molecular markers even for GY when testcross data of both parents are not available. This can help in improving greatly the efficiency of commercial hybrid breeding programs.     

Parental Selection of Hybrid Breeding Based On Maternal and Paternal Inheritance of Traits in Rapeseed (Brassica napus L.)

Parental selection is crucial for hybrid breeding, but the methods available for such a selection are not very effective. In this study, a 6×6 incomplete diallel cross was designed using 12 rapeseed germplasms, and a total of 36 hybrids together with their parental lines were planted in 4 environments. Four yield-related traits and seed oil content (OC) were evaluated. Genetic distance (GD) was estimated with 359 simple sequence repeats (SSRs) markers. Heterosis levels, general combining ability (GCA) and specific combining ability (SCA) were evaluated. GD was found to have a significant correlation with better-parent heterosis (BPH) of thousand seed weight (TSW), SCA of seeds per silique (SS), TSW, and seed yield per plant (SY), while SCA showed a statistically significant correlation with heterosis levels of all traits at 1% significance level. Statistically significant correlations were also observed between GCA of maternal or paternal parents and heterosis levels of different traits except for SS. Interestingly, maternal (TSW, SS, and OC) and paternal (siliques per plant (SP) and SY) inheritance of traits was detected using contribution ratio of maternal and paternal GCA variance as well as correlations between GCA and heterosis levels. Phenotype and heterosis levels of all the traits except TSW of hybrids were significantly correlated with the average performance of parents. The correlations between SS and SP, SP and OC, and SY and OC were statistically significant in hybrids but not in parents. Potential applications of parental selection in hybrid breeding were discussed.     

Breeding maize as biogas substrate in Central Europe: II. Quantitative-genetic parameters for inbred lines and correlations with testcross performance

Breeding maize for use as a biogas substrate (biogas maize) has recently gained considerable importance. To optimize hybrid breeding programs, information about line per se performance (LP) of inbreds and its relation to their general combining ability (GCA) is required. The objectives of our research were to (1) estimate variance components and heritability of LP for agronomic and quality traits relevant to biogas production, (2) study correlations among traits as well as between LP and GCA, and (3) discuss implications for breeding of biogas maize. We evaluated 285 diverse dent maize inbred lines in six environments. Data were recorded on agronomic and quality traits, including dry matter yield (DMY), methane fermentation yield (MFY), and their product, methane yield (MY), as the main target trait. In agreement with observations made for GCA in a companion study, variation in MY was mainly determined by DMY. MFY, which showed moderate correlation with lignin but only weak correlation with starch, revealed only low genotypic variation. Thus, our results favor selection of genotypes with high DMY and less focus on ear proportion for biogas maize. Genotypic correlations between LP and GCA [r _g (LP, GCA)] were highest (≥0.94) for maturity traits (days to silking, dry matter concentration) and moderate (≥0.65) for DMY and MY. Multistage selection is recommended. Selection for GCA of maturity traits, plant height, and to some extent also quality traits and DMY on the level of LP looks promising.     

Relative efficiency of the genotypic value and combining ability effects on reciprocal recurrent selection

Reciprocal recurrent selection (RRS) has been successfully applied to maize breeding for more than 60 years. Our objective was to assess the relative efficiency of the genotypic value and the effects of general and specific combining abilities (GCA and SCA) on selection. The GCA effect reflects the number of favorable genes in the parent. The SCA effect primarily reflects the differences in the gene frequencies between the parents. We simulated three traits, three classes of populations, and 10 cycles of half- and full-sib RRS. The RRS is a highly efficient process for intra- and interpopulation breeding, regardless of the trait or the level of divergence among the populations. The RRS increases the heterosis of the interpopulation cross when there is dominance, and it decreases the inbreeding depression in the populations and the genetic variability in the populations and in the hybrid. When there is not dominance and the populations are not divergent, the RRS also determines population differentiation. The half-sib RRS, which is equivalent to selection based on the GCA effect, is more efficient than the full-sib RRS based on the genotypic value, regardless of the trait or the level of improvement of the populations. The full-sib RRS based on the SCA effect is not efficient for intra- and interpopulation breeding.