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For genetic studies and genomics-assisted breeding, particularly of minor crops, a genotyping system that does not require a priori genomic information is preferable. Here, we demonstrated the potential of a novel array-based genotyping system for the rapid construction of high-density linkage map and quantitative trait loci (QTL) mapping. By using the system, we successfully constructed an accurate, high-density linkage map for common buckwheat (Fagopyrum esculentum Moench); the map was composed of 756 loci and included 8,884 markers. The number of linkage groups converged to eight, which is the basic number of chromosomes in common buckwheat. The sizes of the linkage groups of the P1 and P2 maps were 773.8 and 800.4 cM, respectively. The average interval between adjacent loci was 2.13 cM. The linkage map constructed here will be useful for the analysis of other common buckwheat populations. We also performed QTL mapping for main stem length and detected four QTL. It took 37 days to process 178 samples from DNA extraction to genotyping, indicating the system enables genotyping of genome-wide markers for a few hundred buckwheat plants before the plants mature. The novel system will be useful for genomics-assisted breeding in minor crops without a priori genomic information.

Understanding the genetic bases of local adaptation in dominant conifer species is critical in predicting the impacts of rapid climate change on forest ecosystems. However, the genetic basis of adaptation is not yet fully understood due to the huge and complex genomes of conifers and the unavailability to date of suitable crossing material. In this study, we constructed a linkage map for Abies sachalinensis (2n = 24) and investigated quantitative trait loci (QTLs) associated with local adaptation along an altitudinal gradient. A segregating population of 239 seedlings was produced from a cross between two F1 hybrids (high-altitude × low-altitude genotypes). QTL mapping of phenological and growth traits was performed using a pseudo-testcross strategy with linkage maps based on 1251 single-nucleotide polymorphism (SNP) and three simple sequence repeat (SSR) markers. Two maps consisting of 12 linkage groups with an average marker interval of ca. 3 cM were constructed for each parent. The total lengths of the maps were 1861 and 1949 cM. A permutation test identified four significant QTLs and 11 additional suggestive QTLs, with high logarithm of odds (LOD) scores (> 3.0). This is the first highly saturated linkage map produced for Abies taxa. Our results suggest that spring bud phenology is controlled by several QTLs with moderate effects. The use of the mapping population created by crossing two hybrids (high × low altitude genotypes) and numerous SNP markers enabled us to investigate the genetic basis of adaptive traits in conifer species.

Novel genomics-based approaches such as genome-wide association studies (GWAS) and genomic selection (GS) are expected to be useful in fruit tree breeding, which requires much time from the cross to the release of a cultivar because of the long generation time. In this study, a citrus parental population (111 varieties) and a breeding population (676 individuals from 35 full-sib families) were genotyped for 1,841 single nucleotide polymorphisms (SNPs) and phenotyped for 17 fruit quality traits. GWAS power and prediction accuracy were increased by combining the parental and breeding populations. A multi-kernel model considering both additive and dominance effects improved prediction accuracy for acidity and juiciness, implying that the effects of both types are important for these traits. Genomic best linear unbiased prediction (GBLUP) with linear ridge kernel regression (RR) was more robust and accurate than GBLUP with non-linear Gaussian kernel regression (GAUSS) in the tails of the phenotypic distribution. The results of this study suggest that both GWAS and GS are effective for genetic improvement of citrus fruit traits. Furthermore, the data collected from breeding populations are beneficial for increasing the detection power of GWAS and the prediction accuracy of GS.

The molecular chaperone protein HSP90 has been proposed to modulate genotype-phenotype relationship in a broad range of organisms. We explore the proposed genetic modifier effect of HSP90 through a genomewide analysis. Here, we show that HSP90 functions as a genetic modifier of genital morphology in Drosophila melanogaster. We identified a large number of single-nucleotide polymorphisms (SNPs) with an HSP90-dependent effect by using genome wide association analysis. We classified the SNPs into the ones under capacitance effect (smaller allelic effect under HSP90 inhibition) or the ones under potentiation effect (larger allelic effect under HSP90 inhibition). Although the majority of SNPs are under capacitance, there are a large number of SNPs under potentiation. This observation provides support for a model in which Hsp90 is not described exclusively as a "genetic capacitor," but is described more broadly as a "genetic modifier." Because the majority of the candidate genes estimated from SNPs with an HSP90-dependent effect in the current study has never been reported to interact with HSP90 directly, the global genetic modifier effect of HSP90 may be exhibited through epistatic interactions in gene regulatory networks.

The grain traits of Yamadanishiki, an excellent sake-brewing rice cultivar in Japan, are governed by multiple QTLs, namely, a total of 42 QTLs including six major QTLs. Japanese rice wine (sake) is produced using brewing rice (Oryza sativa L.) that carries traits desirable for sake-brewing, such as a larger grain size and higher white-core expression rate (WCE) compared to cooking rice cultivars. However, the genetic basis for these traits in brewing rice cultivars is still unclear. We performed analyses of quantitative trait locus (QTL) of grain and days to heading over 3 years on populations derived from crosses between Koshihikari, a cooking rice, and Yamadanishiki, an excellent sake-brewing rice. A total of 42 QTLs were detected for the grain traits, and the Yamadanishiki alleles at 16 QTLs contributed to larger grain size. Two major QTLs essential for regulating both 100-grain weight (GWt) and grain width (GWh) were harbored in the same regions on chromosomes 5 and 10. An interaction was noted between the environment and the QTL associated with WCE on chromosome 6, which was detected in two of 3 years. In addition, two QTLs for WCE on chromosomes 3 and 10 overlapped with the QTLs for GWt and GWh, suggesting that QTLs associated with grain size also play an important role in the formation of white-core. Despite differences in the rate of grain growth in both Koshihikari and Yamadanishiki across 2 years, the WCE in Yamadanishiki remained consistent, thus demonstrating that the formation of white-core does not depend on grain filling speed. These data can be informative for programs involved in breeding better cooking and brewing rice cultivars.

Since apple fruit skin reddens poorly under warmer climates, new apple cultivars are desired that are adapted to global warming in terms of bearing well-reddened fruit. We developed a simple sequence repeat marker, Mdo.chr9.4, which is suitable for red skin color selection. It amplified four alleles (Mdo.chr9.4-R-0, Mdo.chr9.4-Y-3, Mdo.chr9.4-Y-9, and Mdo.chr9.4-Y-15) distinguished by length. Mdo. chr9.4-R-0 associated with MdMYB1-1 which confers red fruit skin. The presence of Mdo. chr9.4-R-0 was consistent with empirical skin color in all 160 tested accessions. Mdo. chr9.4 was identified as the only significant marker that contributed to red skin color intensity by a genome wide association study (GWAS), and it accounted for 52.0% of phenotypic variation, confirming that MdMYB1 was the major and principal determinant of fruit skin color in apples. Individuals with a homozygous state of Mdo.chr9.4-R-0 (dose 2) were significantly redder than those showing a heterozygote state (dose 1) in both the accession set and full-sib families, indicating a partially dominant effect of MdMYB1-1. Therefore, the selection of dose 2 individuals would target individuals with intensive red skin. We applied Mdo.chr9.4 to several application populations using a time and cost-efficient genotyping system developed in the present study. This system, along with Mdo.chr9.4, provide advanced marker-assisted breeding for intensive red skin color apples adapted to a global warming climate.

Seed shape is an important agronomic trait with continuous variation among genotypes. Therefore, the quantitative evaluation of this variation is highly important. Among geometric morphometrics methods, elliptic Fourier analysis and semi-landmark analysis are often used for the quantification of biological shape variations. Elliptic Fourier analysis is an approximation method to treat contours as a waveform. Semi-landmark analysis is a method of superimposed points in which the differences of multiple contour positions are minimized. However, no detailed comparison of these methods has been undertaken. Moreover, these shape descriptors vary when the scale and direction of the contour and the starting point of the contour trace change. Thus, these methods should be compared with respect to the standardization of the scale and direction of the contour and the starting point of the contour trace. In the present study, we evaluated seed shape variations in a sorghum (Sorghum bicolor Moench) germplasm collection to analyze the association between shape variations and genome-wide single-nucleotide polymorphisms by genomic prediction (GP) and genome-wide association studies (GWAS). In our analysis, we used all possible combinations of three shape description methods and eight standardization procedures for the scale and direction of the contour as well as the starting point of the contour trace; these combinations were compared in terms of GP accuracy and the GWAS results. We compared the shape description methods (elliptic Fourier descriptors and the coordinates of superposed pseudo-landmark points) and found that principal component analysis of their quantitative descriptors yielded similar results. Different scaling and direction standardization procedures caused differences in the principal component scores, average shape, and the results of GP and GWAS.

Although the potential of marker-assisted selection (MAS) in fruit tree breeding has been reported, bi-parental QTL mapping before MAS has hindered the introduction of MAS to fruit tree breeding programs. Genome-wide association studies (GWAS) are an alternative to bi-parental QTL mapping in long-lived perennials. Selection based on genomic predictions of breeding values (genomic selection: GS) is another alternative for MAS. This study examined the potential of GWAS and GS in pear breeding with 76 Japanese pear cultivars to detect significant associations of 162 markers with nine agronomic traits. We applied multilocus Bayesian models accounting for ordinal categorical phenotypes for GWAS and GS model training. Significant associations were detected at harvest time, black spot resistance and the number of spurs and two of the associations were closely linked to known loci. Genome-wide predictions for GS were accurate at the highest level (0.75) in harvest time, at medium levels (0.38–0.61) in resistance to black spot, firmness of flesh, fruit shape in longitudinal section, fruit size, acid content and number of spurs and at low levels (

Genome-wide regression using a number of genome-wide markers as predictors is now widely used for genome-wide association mapping and genomic prediction. We developed novel software for genome-wide regression which we named VIGoR (variational Bayesian inference for genome-wide regression). Variational Bayesian inference is computationally much faster than widely used Markov chain Monte Carlo algorithms. VIGoR implements seven regression methods, and is provided as a command line program package for Linux/Mac, and as a cross-platform R package. In addition to model fitting, cross-validation and hyperparameter tuning using cross-validation can be automatically performed by modifying a single argument. VIGoR is available at https://github.com/Onogi/VIGoR. The R package is also available at https://cran.r-project.org/web/packages/VIGoR/index.html.

A method based on a multi-task Gaussian process using self-measuring similarity gave increased accuracy for imputing missing phenotypic data in multi-trait and multi-environment trials. Multi-environmental trial (MET) data often encounter the problem of missing data. Accurate imputation of missing data makes subsequent analysis more effective and the results easier to understand. Moreover, accurate imputation may help to reduce the cost of phenotyping for thinned-out lines tested in METs. METs are generally performed for multiple traits that are correlated to each other. Correlation among traits can be useful information for imputation, but single-trait-based methods cannot utilize information shared by traits that are correlated. In this paper, we propose imputation methods based on a multi-task Gaussian process (MTGP) using self-measuring similarity kernels reflecting relationships among traits, genotypes, and environments. This framework allows us to use genetic correlation among multi-trait multi-environment data and also to combine MET data and marker genotype data. We compared the accuracy of three MTGP methods and iterative regularized PCA using rice MET data. Two scenarios for the generation of missing data at various missing rates were considered. The MTGP performed a better imputation accuracy than regularized PCA, especially at high missing rates. Under the ‘uniform’ scenario, in which missing data arise randomly, inclusion of marker genotype data in the imputation increased the imputation accuracy at high missing rates. Under the ‘fiber’ scenario, in which missing data arise in all traits for some combinations between genotypes and environments, the inclusion of marker genotype data decreased the imputation accuracy for most traits while increasing the accuracy in a few traits remarkably. The proposed methods will be useful for solving the missing data problem in MET data.

This study was carried out with the aim of developing the methodology to determine elemental composition in wheat and identify the best germplasm for further research. Orphan and genetically diverse Afghan wheat landraces were chosen and EDXRF was used to measure the content of some of the elements to establish elemental composition in grains of 266 landraces using 10 reference lines. Four elements, K, Mg, P, and Fe, were measured by standardizing sample preparation. The results of hierarchical cluster analysis using elemental composition data sets indicated that the Fe content has an opposite pattern to the other elements, especially that of K. By systematic analysis the best wheat germplasms for P content and Fe content were identified. In order to compare the sensitivity of EDXRF, the ICP method was also used and the similar results obtained confirmed the EDXRF methodology. The sampling method for measurement using EDXRF was optimized resulting in high-throughput profiling of elemental composition in wheat grains at low cost. Using this method, we have characterized the Afghan wheat landraces and isolated the best genotypes that have high-elemental content and have the potential to be used in crop improvement.

In human mitochondria, the AUA codon encodes methionine via a mitochondrial transfer RNA for methionine (mt-tRNA(Met)) that contains 5-formylcytidine (f(5)C) at the first position of the anticodon (position 34). f(5)C34 is required for deciphering the AUA codon during protein synthesis. Until now, the biogenesis and physiological role of f(5)C34 were unknown. We demonstrate that biogenesis of f(5)C34 is initiated by S-adenosylmethionine (AdoMet)-dependent methylation catalyzed by NSUN3, a putative methyltransferase in mitochondria. NSUN3-knockout cells showed strong reduction in mitochondrial protein synthesis and reduced oxygen consumption, leading to deficient mitochondrial activity. We reconstituted formation of 5-methylcytidine (m(5)C) at position 34 (m(5)C34) on mt-tRNA(Met) with recombinant NSUN3 in the presence of AdoMet, demonstrating that NSUN3-mediated m(5)C34 formation initiates f(5)C34 biogenesis. We also found two disease-associated point mutations in mt-tRNA(Met) that impaired m(5)C34 formation by NSUN3, indicating that a lack of f(5)C34 has pathological consequences.

It has become increasingly important to understand the factors controlling the abundance of male strobili in Cryptomeria japonica since allergic reactions to the species’ pollen have become prevalent in Japan. There is considerable inter-annual variation in the abundance of male strobili, so it is important to investigate and validate quantitative trait loci (QTL) for strobili abundance across different years. Data on third generation families derived from an individual that produces abundant male strobili were studied using Kruskal–Wallis tests and Bayesian regression analysis, resulting in the detection of a single major QTL that was observed over multiple years. This QTL explained between 10.4 and 26.5 % of the phenotypic variation in male strobilus abundance. The consistency and significance of this QTL’s effects suggest that it has a major role in male strobilus production in C. japonica, although we also detected other QTLs, indicating that strobilus production is subject to complex and multifactorial regulation. These QTL may also affect precocity because we were unable to separate their effects from the genetic variability in male strobilus production. The major QTL that we detected occurs in a region homologous to a QTL detected in a previous study examining trees with a different genetic heritage following artificial induction of male strobilus production. This result further supports the importance of the QTL detected in the present study. Identifying the important genes in this QTL will therefore significantly increase our understanding of the genetic mechanisms of pollen production in C. japonica.

Mating processes of local demes and spatial genetic structure of island populations at the self-incompatibility (S-) locus under negative frequency-dependent selection (NFDS) were evaluated in Prunus lannesiana var. speciosa in comparison with nuclear simple sequence repeat (SSR) loci that seemed to be evolutionarily neutral. Our observations of local mating patterns indicated that male-female pair fecundity was influenced by not only self-incompatibility, but also various factors, such as kinship, pollen production and flowering synchrony. In spite of the mating bias caused by these factors, the NFDS effect on changes in allele frequencies from potential mates to mating pollen was detected at the S-locus but not at the SSR loci, although the changes from adult to juvenile cohorts were not apparent at any loci. Genetic differentiation and isolation-by-distance over various spatial scales were smaller at the S-locus than at the SSR loci, as expected under the NFDS. Allele-sharing distributions among the populations also had a unimodal pattern at the S-locus, indicating the NFDS effect except for alleles unique to individual populations probably due to isolation among islands, although this pattern was not exhibited by the SSR loci. Our results suggest that the NFDS at the S-locus has an impact on both the mating patterns and the genetic structure in the P. lannesiana populations studied.

Genomic selection (GS) is a promising tool for plant and animal breeding that uses genomewide molecular marker data to capture small and large effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, we compared phenotypic and marker-based prediction accuracy of genetic value for nine different grain quality traits within two biparental soft winter wheat (Triticum aestivum L.) populations. We used a cross-validation approach that trained and validated prediction accuracy across years to evaluate effects of model training population size, training population replication, and marker density. Results showed that prediction accuracy was signifi cantly greater using GS versus MAS for all traits studied and that accuracy for GS reached a plateau at low marker densities (128–256).The average ratio of GS accuracy to phenotypic selection accuracy was 0.66, 0.54, and 0.42 for training population sizes of 96, 48, and 24, respectively. These results provide further empirical evidence that GS could produce greater genetic gain per unit time and cost than both phenotypic selection and conventional MAS in plant breeding with use of year-round nurseries and inexpensive, high-throughput genotyping technology.

To evaluate the effects of pollen contamination from outside of Cryptomeria japonica seed orchard on the growth performance (height and diameter at breast height, DBH) and morphological traits (stem straightness and basal stem straightness), paternity testing using seven microsatellite markers was performed in a progeny test. In the studied progeny test, high rates of inconsistency were found between the observed and expected genotypes. The average rates of pollen contamination from outside the orchard and self-fertilization were 58.47% and 0.65%, respectively. We divided the individuals of the studied progeny test into two groups based on their genotype data, for which: (1) both parents were elite trees and (2) only the mother trees were elite trees, and then compared them with respect to the growth performance and morphological traits of progenies using data at 20 and 30 years old. Significant adverse effects of contaminating pollen were detected in relation to straightness, but not tree height and DBH. The results suggest that the genetic gains for straightness generally show higher narrow-sense heritability than growth traits, which should be increased by reduction of pollen contamination. Breeding with paternal analysis (BWPA) is an effective approach for evaluating breeding materials based on maternal and paternal information revealed by DNA markers. The use of BWPA in progeny test allows effective forward- and backward selection without laborious and time-consuming tasks. In this study, we also suggest that the significant pollen contamination and paternal deviation found in the open-pollinated progeny test are serious impediments for BWPA.

Genomic selection (GS) can be a powerful technology in conifer breeding because conifers have long generation intervals, protracted evaluation times, and high costs of breeding inputs. To elucidate the potential of GS for conifer breeding, we simulated 60-year breeding programs in Cryptomeria japonica with and without GS. In conifers, the rapid decay of linkage disequilibrium (LD) can constitute a severe barrier to application of GS. For overcoming that barrier, we proposed an idea to leverage a seed orchard system, which has been used commonly in conifers, because some degree of LD exists in progenies derived from the limited number of elite trees in a seed orchard. The base population used for simulations consisted of progenies from 25 elite trees. Results show that GS breeding (GSB) done without model updating outperformed phenotypic selection breeding (PSB) during the first 30 years, but the genetic gain achieved over the 60 years was smaller in GSB than in PSB. However, GSB with model updating outperformed PSB over the 60 years. The genetic gain achieved over the 60 years of GSB with model updating was nearly twice that of PSB. Advantages of GSB over PSB prevailed, even for a low heritability polygenic trait. The number of markers necessary for efficient GS was a realistic level (e.g., one in every 1 cM), although higher marker density engendered higher accuracy of selection. These results suggest that GS can be useful in C. japonica breeding. Updating of the prediction model was, however, indispensable for attaining the large genetic gain.

Recombinant inbred lines (RILs) are created by a cross between inbred lines followed by repeated selfing or sib-mating, which include many different types of new inbred lines with many recombination events on the genome. The phenotype of each RIL can be assessed based on multiple individuals within the same line to reduce non-genetic variability. Therefore, RILs are useful tools for QTL mapping allowing effective detection and fine localization of QTL. Usually only two inbred lines are involved to create RILs. In such two-way RILs, however, there are at most two different alleles at QTL and only QTL segregating between two parental lines can be detected. Recently a new crossing design using multiple founders for creating RILs was proposed in Arabidopsis thaliana and mice, where the genome of each RIL is a mosaic of the genomes from multiple parents. Such multi-way RILs are more useful to improve the efficiency in QTL detection than two-way RILs because of the increased chance of QTL segregation among multiple lines, leading to the successful detection of many QTL. In this paper, we propose a Bayesian method for mapping multiple QTL simultaneously in four-way RILs allowing the inference about the equivalence relationship among the four possible alleles descended from the four founder lines as well as the estimation of QTL locations and effects via a MCMC algorithm. Simulation experiments show that our method has the practical ability to detect QTL and to provide the information of equivalence relationship among alleles at detected QTL using four-way RILs.

Photoperiod sensitivity is an important trait related to crop adaptation and ecological breeding in common buckwheat (Fagopyrum esculentum Moench). Although photoperiod sensitivity in this species is thought to be controlled by quantitative trait loci (QTLs), no genes or regions related to photoperiod sensitivity had been identified until now. Here, we identified QTLs controlling photoperiod sensitivity by QTL analysis in a segregating F(4) population (n = 100) derived from a cross of two autogamous lines, 02AL113(Kyukei SC2)LH.self and C0408-0 RP. The F(4) progenies were genotyped with three markers for photoperiod-sensitivity candidate genes, which were identified based on homology to photoperiod-sensitivity genes in Arabidopsis and 76 expressed sequence tag markers. Among the three photoperiod-sensitivity candidate genes (FeCCA1, FeELF3 and FeCOL3) identified in common buckwheat, FeELF3 was associated with photoperiod sensitivity. Two EST regions, Fest_L0606_4 and Fest_L0337_6, were associated with photoperiod sensitivity and explained 20.0% and 14.2% of the phenotypic variation, respectively. For both EST regions, the allele from 02AL113(Kyukei SC2)LH.self led to early flowering. An epistatic interaction was also confirmed between Fest_L0606_4 and Fest_L0337_6. These results demonstrate that photoperiod sensitivity in common buckwheat is controlled by a pathway consisting of photoperiod-sensitivity candidate genes as well as multiple gene action.

Japanese chestnut (Castanea crenata Sieb. et Zucc.) has a long juvenile phase, so breeders have to wait many years to evaluate nut traits. Molecular markers associated with genes of interest would accelerate selection in chestnut breeding programs. We evaluated five nut traits (nut harvest date, nut weight, pericarp splitting, insect infestation, and specific gravity) in 99 Japanese chestnut cultivars and selections. A wide range of phenotypic variation was observed for each of the traits, suggesting that the collection harbored sufficient genetic diversity for breeding. A Bayesian genome-wide association study was conducted using 162 simple sequence repeat markers and 741 single nucleotide polymorphism markers. To evaluate the potential of marker-assisted selection, we examined 12 molecular markers found to be associated with nut traits: 4 for nut harvest date, 4 for nut weight, 1 for pericarp splitting, and 3 for insect infestation. The percentages of phenotypic variance explained ranged from 4.8 to 37.1%. Although insect infestation showed only medium heritability (0.672), we obtained two quantitative trait loci (QTLs) with extremely high posterior probabilities (0.93 and 1.00). Out of the 12 molecular markers, 3 of the 4 markers for nut harvest time could be validated in a breeding population. Accuracies of genomic selection were extremely high for nut harvest date (0.841) and moderate for insect infestation (0.604), suggesting that genomic selection based on Bayesian regression would reduce the cost of phenotypic evaluation of these traits and possibly others.

We evaluated a strategy in which the scores of markers untyped in a low-density experimental panel were imputed on the basis of data from a high-density reference panel, in its application to whole-genome genotyping of barley (Hordeum vulgare L.) breeding lines. Using a barley core set consisting of 98 lines genotyped with 3205 markers (high-density reference panel), we imputed marker scores untyped in 863 barley breeding lines genotyped with 1330 common markers (low-density experimental panel). In repeated analyses, the scores of one common marker were masked in the experimental panel, and then imputed as an untyped marker. Imputation accuracy was evaluated by comparing imputed scores with true ones. The correct imputation rate was >0.9 in 92% of markers. The square of correlation coefficient between true genotypes and mean imputed genotypes was >0.6 in 90% of the markers. Factors affecting imputation accuracy were minor allele frequency, linkage disequilibrium with neighbor common markers, minimum distance to the closest common marker, and degree of differentiation among subpopulations. Actual quantitative trait loci (QTL) would be unobserved in both reference and experimental panels. Markers masked in both panels to mimic this situation sometimes showed larger correlation to imputed markers than to typed common markers, indicating that imputation can sometimes capture the variation of unknown QTL better than the genotypes of common markers.

To reveal the sequence diversity and population structure of Asian rice (Oryza sativa L.) cultivars, we surveyed genome-wide single-nucleotide polymorphisms (SNPs) in 140 diverse accessions. We identified 4357 SNPs distributed on the 12 chromosomes by sequencing PCR amplicons from the exons and introns of anonymous rice genes. We detected 4.87 SNPs per 1 kb genome-wide. By classifying the 140 accessions on the basis of these SNPs, we identified seven cultivar groups that reflected the geographical distribution of the accessions. Three cultivar groups were defined from tropical japonica that corresponded to previous categories, and three indica cultivar groups were also defined within indica. The linkage disequilibrium (LD) distance between SNPs was approximately 250 kb, except for a longer LD detected in the Indica I cultivar group (corresponding to the previously identified aus group). The allele frequency of the SNPs varied among cultivar groups, reflecting the level of genetic diversity in each group. These SNPs for the diverse accessions enhance our understanding of natural variation in rice.

Although grain shape is an important cereal breeding target, it has only been evaluated using simple measurements, e.g., the length:width ratio. We used elliptic Fourier analysis to evaluate grain shape variation and conducted whole genome association mapping of grain shape using a germplasm collection of Asian cultivated rice. The first principal component of elliptic Fourier descriptors, accounting for over 90% of the total variation, was associated with the length:width ratio of brown rice. That component was the most significant among the first ten components: the length:width ratio is the major genetic variation of rice grain shape. Bayesian multilocus association mapping detected five significant markers for this component; three might be linked to previously reported quantitative trait loci. Allelic effects of significant markers were visualized using inverse Fourier transformation, showing that the allele of a Japonica variety “Nipponbare” produced plumper grains in four of five significant markers. For the second to tenth principal components, varietal effects were significant (P < 0.001), although most accounted for less than 1% of the total variation in elliptic Fourier descriptors. Association mapping detected at least one quantitative trait locus in six of these nine components: breeding programs can improve the heritable shape characteristics associated with these components. For association mapping, elliptic Fourier analysis’ accuracy and high throughput are suitable; it is readily applicable to cereal crops because it is not based on rice-specific morphological characteristics but rather on universal shape descriptors that can delineate any closed contour.

Association mapping can be a powerful tool for detecting quantitative trait loci (QTLs) without requiring line-crossing experiments. We previously proposed a Bayesian approach for simultaneously mapping multiple QTLs by a regression method that directly incorporates estimates of the population structure. In the present study, we extended our method to analyze ordinal and censored traits, since both types of traits are common in the evaluation of germplasm collections. Ordinal-probit and tobit models were employed to analyze ordinal and censored traits, respectively. In both models, we postulated the existence of a latent continuous variable associated with the observable data, and we used a Markov-chain Monte Carlo algorithm to sample the latent variable and determine the model parameters. We evaluated the efficiency of our approach by using simulated- and real-trait analyses of a rice germplasm collection. Simulation analyses based on real marker data showed that our models could reduce both false-positive and false-negative rates in detecting QTLs to reasonable levels. Simulation analyses based on highly polymorphic marker data, which were generated by coalescent simulations, showed that our models could be applied to genotype data based on highly polymorphic marker systems, like simple sequence repeats. For the real traits, we analyzed heading date as a censored trait and amylose content and the shape of milled rice grains as ordinal traits. We found significant markers that may be linked to previously reported QTLs. Our approach will be useful for whole-genome association mapping of ordinal and censored traits in rice germplasm collections.

Association or linkage disequilibrium mapping is alternative to identify QTLs in plants. In this study we used SSR based sorghum diversity research set (SDRS) of 107 sorghum accessions. The representative set included a geographically diverse collection of accessions from 27 countries in Asia and Africa. For association analysis 98 sorghum SSR markers were selected from three previously published linkage maps. Phenotypic data was recorded for 26 morphological traits. Different association models were used to identify QTLs controlling major agronomic traits including both single QTL approaches as well as a multiple QTL approach. All models revealed loci having different strength of association with morphological traits. A total of 14 common significant SSR loci were identified by three different models of association analysis namely, single-QTL models with the effects of population structure, single-QTL models with the effects of population structure and familial relatedness, and multiple-QTL model with the effects of population structure. These loci were associated with 12 different morphological traits including days to heading, days to flowering, culm length, number of tillers, number of panicles and panicle length. Comparing results from different models may be an efficient way to detect reliable associations in the genome-wide association studies.

In order to clarify the origin of weedy rice (Oryza sativa L.) in Okayama Prefecture, Japan, we used a set of 15 sequence-tagged site primers to analyze polymorphisms among 27 weedy rice accessions and 88 cultivated rice varieties accessions including common rice varieties from Okayama. The band patterns indicated that 13 of the japonica weedy accessions corresponded exactly with one of the japonica cultivated rice varieties. Furthermore, with the exception of a strong shattering habit, these japonica weedy accessions closely resembled each corresponding rice variety in morphophysiological characteristics. Consequently, in view of the close genetic homology and high morphophysiological resemblance between weedy rice and cultivated rice varieties in Okayama, we conclude that weedy rice originated from cultivated rice varieties as an “off-type” caused by genetic mutation accompanied by the development of a strong shattering habit.

To find out an efficient and accurate way to estimate the genetic relationship among cultivars having within-variety genetic variation by using different types of approaches, we compared among-varieties genetic similarity estimated based on individual samples and also on bulked population samples of six Japanese turnip (Brassica rapa ssp. rapa) cultivars using RAPD and ISSR markers. In both individual- and bulked-samples-based approaches, 37 individuals were sampled from each cultivar, amplified individually and also as bulked DNA, respectively. Genetic similarity matrices among six cultivars were estimated based on four similarity measures estimated with 125 or 124 polymorphic bands scored in the individual- or bulked-samples-based approach, respectively, and the correlations between the similarity matrices were calculated to evaluate the degree of agreement between matrices. Correlations between similarity matrices calculated based on individuals on the one hand and those calculated based on bulked samples on the other were also high and significant in all combinations of the four similarity measures. Use of computational analysis indicated that 6 to 8 individuals per cultivar were enough to accurately estimate similarity with the individual-based approach.

Comparative genomic hybridization (CGH) was performed with nine strains of Bradyrhizobium japonicum (a symbiotic nitrogen-fixing bacterium associated with soybean) and eight other members of the Bradyrhizobiaceae by DNA macroarray of B. japonicum USDA110. CGH clearly discriminated genomic variations in B. japonicum strains, but similar CGH patterns were observed in other members of the Bradyrhizobiaceae. The most variable regions were 14 genomic islands (4-97 kb) and low G+C regions on the USDA110 genome, some of which were missing in several strains of B. japonicum and other members of the Bradyrhizobiaceae. The CGH profiles of B. japonicum were classified into three genome types: 110, 122 and 6. Analysis of DNA sequences around the boundary regions showed that at least seven genomic islands were missing in genome type 122 as compared with type 110. Phylogenetic analysis for internal transcribed sequences revealed that strains belonging to genome types 110 and 122 formed separate clades. Thus genomic islands were horizontally inserted into the ancestor genome of type 110 after divergence of the type 110 and 122 strains. To search for functional relationships of variable genomic islands, we conducted linear models of the correlation between the existence of genomic regions and the parameters associated with symbiotic nitrogen fixation in soybean. Variable genomic regions including genomic islands were associated with the enhancement of symbiotic nitrogen fixation in B. japonicum USDA110.

In the conservation and management practices of natural forests, sound reproduction and regeneration form the basis of the maintenance and viability of the tree populations. To obtain and serve biological information for sustainable forest management, we investigated reproductive biology and inbreeding depression in seeds of an important dipterocarp tree species, Shorea acuminata (Dipterocarpaceae), by both field and laboratory experiments. Results of parental analysis of immature and mature seeds showed that selfing rates varied greatly, from 7.6 to 88.4% among eight mother trees, and the mean overall selfing rate was 38.3%. Observed outcrossing events within a 40-ha study plot were predominantly (76.5%) short-distance events with a mating distance (md) ≤ 100 m. Since the selfing rate sharply decreased with increase in the number of flowering conspecifics (i.e., individuals of the same species) within a 100-m radius from the mother trees, the local density of flowering conspecifics appears to be the key factor determining the outcrossing rate in S. acuminata. However, the extremely high selfing rate (88.4%) observed for one tree could not be simply explained by the low local density of flowering conspecifics. Instead, differences in its flowering phenology (its flowering peaked ca. a week earlier than most of the other examined individuals) may have severely limited its receipt of pollen from other conspecifics, and thus promoted selfing. Since there were no significant differences in the proportion of selfed progeny between immature and mature seed stages, there was no evidence of selective abortion of selfed seeds during seed development. However, the seed mass of outcrossed progeny was heavier than that of selfed progeny, and heavier seeds showed higher success rates at germination and seedling establishment. These results suggest that inbreeding depression resulted in reductions in seed mass and may reduce the fitness of selfed seeds in S. acuminata. In addition, the outcrossing rate of S. acuminata was more sensitive to low local conspecific flowering-tree densities than that of a sympatric bee-pollinated dipterocarp species with greater pollination distances. These results suggest that the management of local adult-tree densities is important for avoiding selfing and inbreeding depression in future generations, especially in a species like S. acuminata with predominantly short-distance pollination.

We investigated the influence of male flower production, floral synchrony and inter-tree distances on male reproductive success in a miniature seed orchard of Cryptomeria japonica. We used six microsatellite markers to determine the paternity of each seed. In the seed orchard, the average pollen contamination and clonal self-fertilization rates were 38.7% and 1.7%, respectively. The level of male reproductive success of constituent clones varied from 0.0 to 15.7%. Five clones showing the highest male reproductive success contributed ca. 30% of all analyzed seeds as a pollen donor after excluding contamination by external sources of pollen. The statistical analyses showed that male reproductive success was strongly influenced by male flower production of each clone and, possibly, by their distance to the mother trees. The linear regression which included male flower production and floral synchrony as independent variables, however, accounted for only 14.7% of variation of male reproductive success, suggesting that other factors such as pollen competition might also influence male reproductive success. Since we found no significant correlation between male reproductive and female reproductive successes, it may be better to equalize male and female reproductive successes independently

Chalkiness is a major concern in rice ( Oryza sativa L.) breeding because it is one of the key factors in determining quality and price. Evalu-ation of chalkiness is traditionally performed by human visual inspection, and there is no stan-dard objective method to effectively classify chalky grains into different categories. In this study, we evaluated the effectiveness of image information processing with an inexpensive personal computer and a digital image scan-ner to measure and categorize chalkiness and assessed the method’s viability as an alternative to human visual assessment. A support vector machine based on the image data generated an accuracy rate of 90.2% in discriminating the level of chalkiness, and principal-components analy-sis of the image data provided new quantitative variables related to the location and degree of chalkiness with much greater accuracy than was previously possible. These results indicate that image processing may be a useful tool for evaluating the chalkiness of rice in scientifi c research and breeding programs.Y. Yoshioka, Graduate School of Life and Environmental Sciences, Univ. of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan, present address: National Institute of Vegetable and Tea Science, National Agricul-ture and Food Research Organization, Tsu, Mie 514-2392, Japan; R. Ohsawa, Graduate School of Life and Environmental Sciences, Univ. of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan; H. Iwata and S. Ninomiya, National Agricultural Research Center, National Agriculture and Food Research Organization, Tsukuba, Ibaraki 305-8666, Japan; M. Tabata, Plant Biotechnology Institute, Ibaraki Agricultural Center, Mito, Ibaraki 311-4203, Japan. Received 3 Oct. 2006. *Corresponding author (osawaryo@sakura.cc.tsukuba.ac.jp).

We investigated 29 natural populations of Cryptomeria japonica using 148 cleaved amplified polymorphic sequence markers to elucidate their genetic structure and identify candidate adaptive genes of this species. In accordance with the inferred evolutionary history of the species during and after the last glacial episode, the genetic diversity was higher in western populations than in northern populations. The results of phylogenetic and genetic structure analyses suggest that populations of the two main varieties of the species have clearly diverged from each other and that two of the examined loci are strongly associated with the differentiation between the two varieties. Using a coalescent simulation based on FST and He values, we detected five genes that had higher, and two that had lower, values than the respective 99% confidence intervals (C.I.s) that are theoretically expected intervals under a neutral infinite-island model. We also detected 13 outlier loci using a coalescent simulation based on the assumption that the 2 varieties originated from the splitting of an ancestral population. Four of these loci were detected by both methods, two of which were detected in a genetic structure analysis as loci associated with differentiation between the two varieties of the species, and are strong candidates for genes that have been subject to selection.

The petal shape of Primula sieboldii E. Morren (Primulaceae) is diverse in wild populations. In this study, we investigated population differentiation in the petal shape of P. sieboldii using image analysis. Flowers were sampled from 160 genets from eight wild populations in the western to north-eastern parts of the Japanese archipelago. Principal component (PC) analysis of 40 coefficients of elliptic Fourier descriptors (EFDs) detected three major characteristics of petal shape variation: the ratio of length to width (PC1), the depth of the head notch (PC2) and the position of the center of gravity (PC3). To test the association between divergence in petal shape and geographical and genetic distances, we calculated two types of pairwise population distances for petal shape: Mahalanobis distances for the 40 EFD coefficients and for the first three PCs. The existence of an association between neutral genetic markers and petal shape was revealed by the Mahalanobis distances based on the 40 EFD coefficients, suggesting that evolutionary forces, such as founder effect and isolation by distance effect, are probably the main causes of differentiation in petal shape. In contrast, we found no association between Mahalanobis distances for the first three PCs and geographical and genetic distances. The discrepancy between the two petal shape distances indicated that the population differentiation promoted by the founder effects and isolation by distance effect appears mainly as subtle changes in petal shape rather than in major characteristics of petal shape variation.

Transgenic rice plants overexpressing a mutant rice gene for anthranilate synthase alpha subunit (OASA1D) accumulate large amounts of free tryptophan (Trp) with few adverse effects on the phenotype, except for poor germination and weak seedling growth. Metabolic profiling of 8-d-old seedlings of Nipponbare and two high-Trp lines, HW1 and HW5, by high performance liquid chromatography-photo diode array (HPLC-PDA) confirmed that, relative to Nipponbare, only the peak attributed to Trp was significantly changed in the profiles of the OASA1D lines. More detailed and targeted analysis using HPLC coupled with tandem mass spectrometry revealed that the OASA1D lines had higher levels of anthranilate, tryptamine, and serotonin than Nipponbare, but these metabolites were at much lower levels than free Trp. The levels of phenylalanine (Phe) and tyrosine (Tyr) were not affected by the overproduction of Trp. Transcriptomic analysis by microarray validated by quantitative Real-Time PCR (qRT-PCR) revealed that at least 12 out of 21 500 genes showed significant differential expression among genotypes. Except for the OASA1D transgene and a putative IAA beta-glucosyltransferase, these were not related to Trp metabolism. Most importantly, the overexpression of the OASA1D and the consequent accumulation of Trp in these lines had little effect on the overall transcriptome, consistent with the minimal effects on growth and the metabolome. Integrated analysis of the metabolome and transcriptome of these OASA1D transgenic lines indicates that the over-accumulation of free Trp may be partly due to the low activity of Trp decarboxylase or other metabolic genes that directly utilize Trp as a substrate.

One way to use a crop germplasm collection directly to map QTLs without using line-crossing experiments is the whole genome association mapping. A major problem with association mapping is the presence of population structure, which can lead to both false positives and failure to detect genuine associations (i.e., false negatives). Particularly in highly selfing species such as Asian cultivated rice, high levels of population structure are expected and therefore the efficiency of association mapping remains almost unknown. Here, we propose an approach that combines a Bayesian method for mapping multiple QTLs with a regression method that directly incorporates estimates of population structure. That is, the effects due to both multiple QTLs and population structure were included in our statistical model. We evaluated the efficiency of our approach in simulated- and real-trait analyses of a rice germplasm collection. Simulation analyses based on real marker data showed that our model could suppress both false-positive and false-negative rates and the error of estimation of genetic effects over single QTL models, indicating that our model has statistically desirable attributes over single QTL models. As real traits, we analyzed the size and shape of milled rice grains and found significant markers that may be linked to QTLs reported previously. Association mapping should have good prospects in highly selfing species such as rice if proper methods are adopted. Our approach will be useful for the whole genome association mapping of various selfing crop species.

BACKGROUND AND AIMS: Flower shapes are important visual cues for pollinators. However, the ability of pollinators to discriminate between flower shapes under natural conditions is poorly understood. This study focused on the diversity of flower shape in Primula sieboldii and investigated the ability of bumblebees to discriminate between flowers by combining computer graphics with a traditional behavioural experiment. METHODS: Elliptic Fourier descriptors described shapes by transforming coordinate information for the contours into coefficients, and principal components analysis summarized these coefficients. Using these methods, artificial flowers were created based on the natural diversity of petal shape in P. sieboldii. Dual-choice tests were then performed to investigate the ability of the bumblebees to detect differences in the aspect ratio of petals and the depth of their head notch. KEY RESULTS: The insects showed no significant ability to detect differences in the aspect ratio of the petals under natural conditions unless the morphological distance increased to an unrealistic level. These results suggest the existence of a perception threshold for distances in this parameter. The bumblebees showed a significant preference for narrow petals even after training using flowers with wide petals. The bumblebees showed a significant ability to discriminate based on the depth of the petal head notch after training using artificial flowers with a deep head notch. However, they showed no discrimination in tests with training using extreme distances between flowers in this parameter. CONCLUSIONS: A new type of behavioural experiment was demonstrated using real variation in flower corolla shape in P. sieboldii. If the range in aspect ratios of petals expands much further, bumblebees may learn to exhibit selective behaviour. However, because discrimination by bumblebees under natural conditions was low, there may be no strong selective behaviour based on innate or learned preferences under natural conditions.

Recent advancements in genomic analysis technologies have opened up new avenues to promote the efficiency of plant breeding. Novel genomics-based approaches for plant breeding and genetics research, such as genome-wide association studies (GWAS) and genomic selection (GS), are useful, especially in fruit tree breeding. The breeding of fruit trees is hindered by their long generation time, large plant size, long juvenile phase, and the necessity to wait for the physiological maturity of the plant to assess the marketable product (fruit). In this article, we describe the potential of genomics-assisted breeding, which uses these novel genomics-based approaches, to break through these barriers in conventional fruit tree breeding. We first introduce the molecular marker systems and whole-genome sequence data that are available for fruit tree breeding. Next we introduce the statistical methods for biparental linkage and quantitative trait locus (QTL) mapping as well as GWAS and GS. We then review QTL mapping, GWAS, and GS studies conducted on fruit trees. We also review novel technologies for rapid generation advancement. Finally, we note the future prospects of genomics-assisted fruit tree breeding and problems that need to be overcome in the breeding.

It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in the prediction of phenotypes of plants.

Because fatty acid composition influences the flavor and texture of meat, controlling it is particularly important for cattle breeds such as the Japanese Black, characterized by high meat quality. We evaluated the predictive ability of single-step genomic best linear unbiased prediction (ssGBLUP) in fatty acid composition of Japanese Black cattle by assessing the composition of seven fatty acids in 3088 cattle, of which 952 had genome-wide marker genotypes. All sires of the genotyped animals were genotyped, but their dams were not. Cross-validation was conducted for the 952 animals. The prediction accuracy was higher with ssGBLUP than with best linear unbiased prediction (BLUP) for all traits, and in an empirical investigation, the gain in accuracy of using ssGBLUP over BLUP increased as the deviations in phenotypic values of the animals increased. In addition, the superior accuracy of ssGBLUP tended to be more evident in animals whose maternal grandsire was genotyped than in other animals, although the effect was small.

Trees are important sources of food, fibre, fodder, fuel, and timber. Fruit and forest trees provide habitat for wildlife, sequester carbon, and protect soil and water resources. Despite a very long history of domestication of some fruit tree species, such as apple, domestication and breeding of many tree species is still in their early stages. The domestication of trees can be accelerated by modern tree breeding practices. Advances in genomic technologies are providing valuable tools to tree breeders. Breeders can be more efficient in improving the traits of interest to increase productivity, and develop genetic resources that can adapt to changing environment and have resistance to disease and pests. In this chapter, we first briefly examined the current status of major forest (conifers, eucalypts) and fruit trees (apple, peach, pear) breeding across the world. We then described the breeding strategies employed to improve the populations. A summary of genomic resources available for major tree species is also covered. The challenges and opportunities of genomic selection applications are finally summarized.

Flower appearance is an important target for improvement in garden pansy (Viola × wittrockiana Gams). Flowers of this species consist of three petal types: inferior, lateral, and superior. By means of principal-components (PC) analysis of elliptic Fourier descriptors (EFDs), we estimated the general and specific combining abilities (GCA and SCA) of the floral characteristics of F1 progeny derived from diallel crosses of four inbred lines. The greatest variation in petal shape was explained by the aspect ratio (the first PC) in each petal type. The second or third PC of each petal type was associated with the curvatures of the various parts of the petal. The highly significant GCA effects indicate the importance of additive genetic variance in the transmission of parental petal characteristics to the progeny. The fact that the SCA mean squares were not significant for aspect ratio and petal area indicates that these characteristics of a single-cross progeny can be sufficiently predicted on the basis of GCA. Significant SCA effects were observed in the curvatures of the distal and proximal parts of lateral and superior petals. Correlation analyses indicated several associations between the shape elements of lateral and superior petals, suggesting that genes for these shape elements may be associated, linked, or pleiotropic in the parents used in this study. We successfully demonstrated the use of EFD–PCA to evaluate the petal shape of garden pansy, and of analyzing combining ability and correlations based on the PC scores of EFDs.