Hiroyoshi Iwata

Genomic selection in plant breeding: from theory to practice

We intuitively believe that the dramatic drop in the cost of DNA marker information we have experienced should have immediate benefits in accelerating the delivery of crop varieties with improved yield, quality and biotic and abiotic stress tolerance. But these traits are complex and affected by many genes, each with small effect. Traditional marker-assisted selection has been ineffective for such traits. The introduction of genomic selection (GS), however, has shifted that paradigm. Rather than seeking to identify individual loci significantly associated with a trait, GS uses all marker data as predictors of performance and consequently delivers more accurate predictions. Selection can be based on GS predictions, potentially leading to more rapid and lower cost gains from breeding. The objectives of this article are to review essential aspects of GS and summarize the important take-home messages from recent theoretical, simulation and empirical studies. We then look forward and consider research needs surrounding methodological questions and the implications of GS for long-term selection.

Genomic Selection in Plant Breeding: Knowledge and Prospects

Abstract “Genomic selection,” the ability to select for even complex, quantitative traits based on marker data alone, has arisen from the conjunction of new high-throughput marker technologies and new statistical methods needed to analyze the data. This review surveys what is known about these technologies, with sections on population and quantitative genetic background, DNA marker development, statistical methods, reported accuracies of genomic selection (GS) predictions, prediction of nonadditive genetic effects, prediction in the presence of subpopulation structure, and impacts of GS on long-term gain. GS works by estimating the effects of many loci spread across the genome. Marker and observation numbers therefore need to scale with the genetic map length in Morgans and with the effective population size of the population under GS. For typical crops, the requirements range from at least 200 to at most 10,000 markers and observations. With that baseline, GS can greatly accelerate the breeding cycle while also using marker information to maintain genetic diversity and potentially prolong gain beyond what is possible with phenotypic selection. With the costs of marker technologies continuing to decline and the statistical methods becoming more routine, the results reviewed here suggest that GS will play a large role in the plant breeding of the future. Our summary and interpretation should prove useful to breeders as they assess the value of GS in the context of their populations and resources.

Evaluation of variation of root shape of Japanese radish (Raphanus sativus L.) based on image analysis using elliptic Fourier descriptors

Variation was of root shape in Japanese radish, due to genotypes, soil types and growth stages, were quantitatively evaluated by principal components scores based on elliptic Fourier descriptors. Photographic images of sampled roots on 35mm color reversal films were converted into digital images. After image processing, the contour of each root was expressed as chain-code and then described by 77 coefficients of elliptic Fourier descriptors. After normalization about size, rotation, and starting point of the contour, two groups of the coefficients, which are related to the symmetrical and asymmetrical variations of shape, were analyzed separately, since artificially determined direction of curvature of the root may influence the results. Principal component analysis of the coefficients showed that the major part of the symmetrical (A) and asymmetrical (B) variations were summarized by at most 5 components. The cumulative contribution was 95.2% and 97.1%, respectively. Analysis of variance of each component indicated that the variety effect was highly significant for the 1st, 2nd and 3rd principal components derived from group A coefficients, which were related to the aspect ratio, bluntness of the distal part of the root, and swelling of the middle part, respectively. This suggests that these traits are heritable and can be effectively selected through quantified measures based on elliptic Fourier descriptors presented in this report. Direction and degree of curvature of root could be analyzed independently of the symmetrical variation.

Genome Scan to Detect Genetic Structure and Adaptive Genes of Natural Populations of Cryptomeria japonica

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.

Selfing and inbreeding depression in seeds and seedlings of Neobalanocarpus heimii (Dipterocarpaceae).

We evaluated the degree of selfing and inbreeding depression at the seed and seedling stages of a threatened tropical canopy tree, Neobalanocarpus heimii, using microsatellite markers. Selection resulted in an overall decrease in the level of surviving selfed progeny from seeds to established seedlings, indicating inbreeding depression during seedling establishment. Mean seed mass of selfed progeny was lower than that of outcrossed progeny. Since the smaller seeds suffered a fitness disadvantage at germination in N. heimii, the reduced seed mass of selfed progeny would be one of the determinants of the observed inbreeding depression during seedling establishment. High selfing rates in some mother trees could be attributed to low local densities of reproductive individuals, thus maintenance of a sufficiently high density of mature N. heimii should facilitate regeneration and conservation of the species.

Development and characterization of microsatellite markers for Cryptomeria japonica D.Don.

Abstract.Thirty four microsatellite markers for Cryptomeria japonica D. Don were developed by searching three types of library: a database of C. japonica cDNA sequences, a standard non-enriched genomic DNA library and a microsatellite-enriched library using magnetic particles. The enrichment of microsatellite sequences using magnetic particles is very efficient compared to the other two methods both in terms of the numbers of markers generated, and in the polymorphism they detect. The microsatellites developed from the genomic DNA library generally have longer repeat sequences and are more polymorphic than those from cDNA. All the developed microsatellite markers in this study showed polymorphism among 28 plus trees selected from locations scattered throughout Japan. The mean number of alleles per locus (MNA) detected in the 28 plus trees ranged from 2 to 21 with an average of 7.5. The Polymorphism Information Content (PIC) ranged from 0.160 to 0.936 with an average of 0.666. Co-dominant segregation of alleles in a three-generation pedigree of C. japonica was demonstrated at 34 microsatellite loci, and the segregation was not distorted from Mendelian expectation for all loci. In 12 out of 34 loci, a null allele was detected. Key relationships between polymorphic parameters, such as MNA and PIC, and the characteristics of microsatellite sequences, such as the longest repeat number, total repeat number and total number of nucleotides, were investigated using rank correlation coefficients, Kendalls τ. A positive correlation was found between repeat lengths and polymorphisms. The markers provide sufficient resolution for investigating gene flow within forests and seed orchards, and for genome mapping.

AFLP and CAPS linkage maps of Cryptomeria japonica.

Abstract We have used two DNA marker systems, AFLP and CAPS, in a two-way pseudo-testcross strategy applied to an F1 population to construct genetic linkage maps of two local sugi cultivars. The AFLP markers detected about eight polymorphisms per parent per primer combination. Using 38 primer combinations, 612 AFLPs were detected in ’Haara 4’ and ’Kumotooshi’, of which 305 segregated in a 1:1 ratio (P>0.05). A total of 91 markers (83 AFLP and 8 CAPS) in ’Haara 4’ and 132 (123 AFLP and 9 CAPS) in ’Kumotooshi’ were distributed among 19 and 23 linkage groups, respectively, each of which included 2–17 markers. Maps of ’Haara 4’ and ’Kumotooshi’ spanned 1266.1 cM and 1992.3 cM, and covered approximately 50% and 80% of the sugi genome, respectively. Sequences derived from cDNA, which were previously used to construct a sugi linkage map, were also placed on our linkage maps as CAPS markers. Where a ’two-way pseudo-testcross’ is used, more than half of the sugi CAPS developed can be used to construct linkage maps for each parental family. The saturation of mapped markers, and the integration of several linkage maps derived from different mapping populations, is anticipated in the near future.

EM algorithm for Bayesian estimation of genomic breeding values

BackgroundIn genomic selection, a model for prediction of genome-wide breeding value (GBV) is constructed by estimating a large number of SNP effects that are included in a model. Two Bayesian methods based on MCMC algorithm, Bayesian shrinkage regression (BSR) method and stochastic search variable selection (SSVS) method, (which are called BayesA and BayesB, respectively, in some literatures), have been so far proposed for the estimation of SNP effects. However, much computational burden is imposed on the MCMC-based Bayesian methods. A method with both high computing efficiency and prediction accuracy is desired to be developed for practical use of genomic selection.ResultsEM algorithm applicable for BSR is described. Subsequently, we propose a new EM-based Bayesian method, called wBSR (weighted BSR), which is a modification of BSR incorporating a weight for each SNP according to the strength of its association to a trait. Simulation experiments show that the computational time is much reduced with wBSR based on EM algorithm and the accuracy in predicting GBV is improved by wBSR in comparison with BSR based on MCMC algorithm. However, the accuracy of predicted GBV with wBSR is inferior to that with SSVS based on MCMC algorithm which is currently considered to be a method of choice for genomic selection.ConclusionsEM-based wBSR method proposed in this study is much advantageous over MCMC-based Bayesian methods in computational time and can predict GBV more accurately than MCMC-based BSR. Therefore, wBSR is considered a practical method for genomic selection with a large number of SNP markers.

Bayesian association mapping of multiple quantitative trait loci and its application to the analysis of genetic variation among Oryza sativa L. germplasms

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.

Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia

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 (<0.2) in all soluble solid content and vigor of tree. Results suggest the potential of GWAS and GS for use in future breeding programs in Japanese pear.