Natural variations of wheat EARLY FLOWERING 3 highlight their contributions to local adaptation through fine-tuning of heading time.

KEY MESSAGE: We identified a large chromosomal deletion containing TaELF-B3 that confers early flowering in wheat. This allele has been preferred in recent wheat breeding in Japan to adapt to the environment. Heading at the appropriate time in each cultivation region can greatly contribute to stabilizing and maximizing yield. Vrn-1 and Ppd-1 are known as the major genes for vernalization requirement and photoperiod sensitivity in wheat. Genotype combinations of Vrn-1 and Ppd-1 can explain the variation in heading time. However, the genes that can explain the remaining variations in heading time are largely unknown. In this study, we aimed to identify the genes conferring early heading using doubled haploid lines derived from Japanese wheat varieties. Quantitative trait locus (QTL) analysis revealed a significant QTL on the long arm of chromosome 1B in multiple growing seasons. Genome sequencing using Illumina short reads and Pacbio HiFi reads revealed a large deletion of a ~ 500 kb region containing TaELF-B3, an orthologue of Arabidopsis clock gene EARLY FLOWERING 3 (ELF3). Plants with the deleted allele of TaELF-B3 (ΔTaELF-B3 allele) headed earlier only under short-day vernalization conditions. Higher expression levels of clock- and clock-output genes, such as Ppd-1 and TaGI, were observed in plants with the ΔTaELF-B3 allele. These results suggest that the deletion of TaELF-B3 causes early heading. Of the TaELF-3 homoeoalleles conferring early heading, the ΔTaELF-B3 allele showed the greatest effect on the early heading phenotype in Japan. The higher allele frequency of the ΔTaELF-B3 allele in western Japan suggests that the ΔTaELF-B3 allele was preferred during recent breeding to adapt to the environment. TaELF-3 homoeologs will help to expand the cultivated area by fine-tuning the optimal timing of heading in each environment.

Developing core marker sets for effective genomic-assisted selection in wheat and barley breeding programs.

Wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) are widely cultivated temperate crops. In breeding programs with these crops in Japan, effective genomic-assisted selection was performed by selecting core marker sets from thousands of genome-wide amplicon sequencing markers. The core sets consist of 768 and 960 markers for barley and wheat, respectively. These markers are distributed evenly across the genomes and effectively detect widely distributed polymorphisms in the chromosomes. The core set utility was assessed using 1,032 barley and 1,798 wheat accessions across the country. Minor allele frequency and chromosomal distributions showed that the core sets could effectively capture polymorphisms across the entire genome, indicating that the core sets are applicable to highly-related advanced breeding materials. Using the core sets, we also assessed the trait value predictability. As observed via fivefold cross-validation, the prediction accuracies of six barley traits ranged from 0.56-0.74 and 0.62 on average, and the corresponding values for eight wheat traits ranged from 0.44-0.83 and 0.65 on average. These data indicate that the established core marker sets enable breeding processes to be accelerated in a cost-effective manner and provide a strong foundation for further research on genomic selection in crops.

Allelic variations of Vrn-1 and Ppd-1 genes in Japanese wheat varieties reveal the genotype-environment interaction for heading time.

The timing of heading is largely affected by environmental conditions. In wheat, Vrn-1 and Ppd-1 have been identified as the major genes involved in vernalization requirement and photoperiod sensitivity, respectively. To compare the effects of Vrn-1 and Ppd-1 alleles on heading time under different environments, we genotyped Vrn-1 and Ppd-1 homoeologues and measured the heading time at Morioka, Tsukuba and Chikugo in Japan for two growing seasons. A total of 128 Japanese and six foreign varieties, classified into four populations based on the 519 genome-wide SNPs, were used for analysis. Varieties with the spring alleles (Vrn-D1a or Vrn-D1b) at the Vrn-D1 locus and insensitive allele (Hapl-I) at the Ppd-D1 locus were found in earlier heading varieties. The effects of Vrn-D1 and Ppd-D1 on heading time were stronger than those of the other Vrn-1 and Ppd-1 homoeologues. Analysis of variance revealed that heading time was significantly affected by the genotype-environment interactions. Some Vrn-1 and Ppd-1 alleles conferred earlier or later heading in specific environments, indicating that the effect of both alleles on the timing of heading depends on the environment. Information on Vrn-1 and Ppd-1 alleles, together with heading time in various environments, provide useful information for wheat breeding.

Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods.

The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD_2020 has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. We now release in 2021 a new version of the Global Wheat Head Detection dataset, which is bigger, more diverse, and less noisy than the GWHD_2020 version.

Genetic mechanisms determining grain number distribution along the spike and their effect on yield components in wheat.

The number of wheat grains is one of the major determinants of yield. Many quantitative trait loci (QTLs) and some causal genes such as GNI-A1 and WAPO-A1 that are associated with grain number per spike (GNS) have been identified, but the underlying mechanisms remain largely unknown. We analyzed QTLs for grain number and other related traits using 188 doubled haploid lines derived from the Japanese high-yield variety, Kitahonami, as a parent to elucidate the genetic mechanism determining grain number. The major QTLs for grain number at the apical, central, and basal parts of the spike were identified in different chromosomal regions. We considered GNI-A1 and WAPO-A1 as candidate genes controlling grain number at the central and basal parts of the spike, respectively. Kitahonami had the favorable 105Y allele of GNI-A1 and WAPO-A1b allele and unfavorable alleles of QTLs for grain number at the apical part of spikes. Pyramiding the favorable alleles of these QTLs significantly increased GNS without significantly reducing thousand-grain weight (TGW). In contrast, the accumulation of favorable alleles of QTLs for TGW significantly decreased GNS, whereas days to heading positively correlated with GNS. Late heading increased the spikelet number per spike, resulting in a higher GNS. Pyramiding of the QTLs for TGW and days to heading also altered the GNS. In conclusion, GNS is a complex trait controlled by many QTLs, and it is essential for breeding to design. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01255-8.

Global Wheat Head Detection (GWHD) Dataset: A Large and Diverse Dataset of High-Resolution RGB-Labelled Images to Develop and Benchmark Wheat Head Detection Methods.

The detection of wheat heads in plant images is an important task for estimating pertinent wheat traits including head population density and head characteristics such as health, size, maturity stage, and the presence of awns. Several studies have developed methods for wheat head detection from high-resolution RGB imagery based on machine learning algorithms. However, these methods have generally been calibrated and validated on limited datasets. High variability in observational conditions, genotypic differences, development stages, and head orientation makes wheat head detection a challenge for computer vision. Further, possible blurring due to motion or wind and overlap between heads for dense populations make this task even more complex. Through a joint international collaborative effort, we have built a large, diverse, and well-labelled dataset of wheat images, called the Global Wheat Head Detection (GWHD) dataset. It contains 4700 high-resolution RGB images and 190000 labelled wheat heads collected from several countries around the world at different growth stages with a wide range of genotypes. Guidelines for image acquisition, associating minimum metadata to respect FAIR principles, and consistent head labelling methods are proposed when developing new head detection datasets. The GWHD dataset is publicly available at http://www.global-wheat.com/and aimed at developing and benchmarking methods for wheat head detection.

Novel quantitative trait loci for low grain cadmium concentration in common wheat (Triticum aestivum L.).

Cadmium (Cd) is as an extremely toxic metal that can contaminate agricultural soils. To reduce the risk of Cd intake in food cereals, the development of cultivars with low grain Cd concentration (GCC) is an effective countermeasure. We analyzed quantitative trait loci (QTLs) for GCC in a doubled haploid (DH) common wheat (Triticum aestivum L.) population derived from 'Chugoku 165' (low GCC) × 'Chukei 10-22' (high GCC). We found novel loci for low GCC on the short arm of chromosome 4B and on the long arm of chromosome 6B. These QTLs accounted for 9.4%-25.4% (4B) and 9.0%-17.8% (6B) of the phenotypic variance in the DH population. An association analysis with 43 cultivars identified 3 loci at these QTLs: QCdc.4B-kita, QCdc.6B-kita1, and QCdc.6B-kita2. In contrast to durum wheat and barley, no QTL was detected on the chromosomes of homeologous group 5 for heavy metal P1B-type ATPase 3. These results will contribute to marker-assisted selection for low GCC in breeding of common wheat.

Multifamily QTL analysis and comprehensive design of genotypes for high-quality soft wheat.

Milling properties and flour color are essential selection criteria in soft wheat breeding. However, high phenotypic screening costs restrict selection to relatively few breeding lines in late generations. To achieve marker-based selection of these traits in early generations, we performed genetic dissection of quality traits using three doubled haploid populations that shared the high-quality soft wheat variety Kitahonami as the paternal parent. An amplicon sequencing approach allowed effective construction of well-saturated linkage maps of the populations. Marker-based heritability estimates revealed that target quality traits had relatively high values, indicating the possibility of selection in early generations. Taking advantage of Chinese Spring reference sequences, joint linkage maps of the three populations were generated. Based on the maps, multifamily quantitative trait locus (QTL) analysis revealed a total of 86 QTLs for ten traits investigated. In terms of target quality traits, 12 QTLs were detected for flour yield, and 12 were detected for flour redness (a* value). Among these QTLs, six for flour yield and nine for flour a* were segregating in more than two populations. Some relationships among traits were explained by QTL collocations on chromosomes, especially group 7 chromosomes. Ten different ideotypes with various combinations of favorable alleles for the flour yield and flour a* QTLs were generated. Phenotypes of derivatives from these ideotypes were predicted to design ideal genotypes for high-quality wheat. Simulations revealed the possibility of breeding varieties with better quality than Kitahonami.

Development of Genome-Wide SNP Markers for Barley via Reference- Based RNA-Seq Analysis.

Marker-assisted selection of crop plants requires DNA markers that can distinguish between the closely related strains often used in breeding. The availability of reference genome sequence facilitates the generation of markers, by elucidating the genomic positions of new markers as well as of their neighboring sequences. In 2017, a high quality genome sequence was released for the six-row barley (Hordeum vulgare) cultivar Morex. Here, we developed a de novo RNA-Seq-based genotyping procedure for barley strains used in Japanese breeding programs. Using RNA samples from the seedling shoot, seedling root, and immature flower spike, we mapped next-generation sequencing reads onto the transcribed regions, which correspond to ∼590 Mb of the whole ∼4.8-Gbp reference genome sequence. Using 150 samples from 108 strains, we detected 181,567 SNPs and 45,135 indels located in the 28,939 transcribed regions distributed throughout the Morex genome. We evaluated the quality of this polymorphism detection approach by analyzing 387 RNA-Seq-derived SNPs using amplicon sequencing. More than 85% of the RNA-Seq SNPs were validated using the highly redundant reads from the amplicon sequencing, although half of the indels and multiple-allele loci showed different polymorphisms between the platforms. These results demonstrated that our RNA-Seq-based de novo polymorphism detection system generates genome-wide markers, even in the closely related barley genotypes used in breeding programs.

An efficient approach for the development of genome-specific markers in allohexaploid wheat (Triticum aestivum L.) and its application in the construction of high-density linkage maps of the D genome.

In common wheat, the development of genotyping platforms has been hampered by the large size of the genome, its highly repetitive elements and its allohexaploid nature. However, recent advances in sequencing technology provide opportunities to resolve these difficulties. Using next-generation sequencing and gene-targeting sequence capture, 12,551 nucleotide polymorphisms were detected in the common wheat varieties 'Hatsumochi' and 'Kitahonami' and were assigned to chromosome arms using International Wheat Genome Sequencing Consortium survey sequences. Because the number of markers for D genome chromosomes in commercially available wheat single nucleotide polymorphism arrays is insufficient, we developed markers using a genome-specific amplicon sequencing strategy. Approximately 80% of the designed primers successfully amplified D genome-specific products, suggesting that by concentrating on a specific subgenome, we were able to design successful markers as efficiently as could be done in a diploid species. The newly developed markers were uniformly distributed across the D genome and greatly extended the total coverage. Polymorphisms were surveyed in six varieties, and 31,542 polymorphic sites and 5,986 potential marker sites were detected in the D genome. The marker development and genotyping strategies are cost effective, robust and flexible and may enhance multi-sample studies in the post-genomic era in wheat.

A novel compensating wheat-Thinopyrum elongatum Robertsonian translocation line with a positive effect on flour quality.

Wheat flours are used to produce bread, pasta, breakfast cereals, and biscuits; the various properties of these end-products are attributed to the gluten content, produced as seed storage proteins in the wheat endosperm. Thus, genes encoding gluten protein are major targets of wheat breeders aiming to improve the various properties of wheat flour. Here, we describe a novel compensating wheat-Thinopyrum elongatum Robertsonian translocation (T1AS.1EL) line involving the short arm of wheat chromosome 1A (1AS) and the long arm of Th. elongatum chromosome 1E (1EL); we developed this line through centric breakage-fusion. Compared to the common wheat cultivars Chinese Spring and Norin 61, we detected two additional 1EL-derived high-molecular-weight glutenin subunits (HMW-GSs) in the T1AS.1EL plants. Based on the results of an SDS-sedimentation volume to estimate the gluten strength of T1AS.1EL-derived flour, we predict that T1AS.1EL-derived flour is better suited to bread-making than Chinese Spring- and Norin 61-derived flour and that this is because of its greater gluten diversity. Also, we were able to assign 33 of 121 wheat PCR-based Landmark Unique Gene markers to chromosome 1E of Th. elongatum. These markers can now be used for further chromosome engineering of the Th. elongatum segment of T1AS.1EL.

A high-resolution physical map integrating an anchored chromosome with the BAC physical maps of wheat chromosome 6B.

BACKGROUND: A complete genome sequence is an essential tool for the genetic improvement of wheat. Because the wheat genome is large, highly repetitive and complex due to its allohexaploid nature, the International Wheat Genome Sequencing Consortium (IWGSC) chose a strategy that involves constructing bacterial artificial chromosome (BAC)-based physical maps of individual chromosomes and performing BAC-by-BAC sequencing. Here, we report the construction of a physical map of chromosome 6B with the goal of revealing the structural features of the third largest chromosome in wheat. RESULTS: We assembled 689 informative BAC contigs (hereafter reffered to as contigs) representing 91% of the entire physical length of wheat chromosome 6B. The contigs were integrated into a radiation hybrid (RH) map of chromosome 6B, with one linkage group consisting of 448 loci with 653 markers. The order and direction of 480 contigs, corresponding to 87% of the total length of 6B, were determined. We also characterized the contigs that contained a part of the nucleolus organizer region or centromere based on their positions on the RH map and the assembled BAC clone sequences. Analysis of the virtual gene order along 6B using the information collected for the integrated map revealed the presence of several chromosomal rearrangements, indicating evolutionary events that occurred on chromosome 6B. CONCLUSIONS: We constructed a reliable physical map of chromosome 6B, enabling us to analyze its genomic structure and evolutionary progression. More importantly, the physical map should provide a high-quality and map-based reference sequence that will serve as a resource for wheat chromosome 6B.

Association mapping and validation of QTLs for flour yield in the soft winter wheat variety Kitahonami.

The winter wheat variety Kitahonami shows a superior flour yield in comparison to other Japanese soft wheat varieties. To map the quantitative trait loci (QTL) associated with this trait, association mapping was performed using a panel of lines from Kitahonami's pedigree, along with leading Japanese varieties and advanced breeding lines. Using a mixed linear model corrected for kernel types and familial relatedness, 62 marker-trait associations for flour yield were identified and classified into 21 QTLs. In eighteen of these, Kitahonami alleles showed positive effects. Pedigree analysis demonstrated that a continuous pyramiding of QTLs had occurred throughout the breeding history of Kitahonami. Linkage analyses using three sets of doubled haploid populations from crosses in which Kitahonami was used as a parent were performed, leading to the validation of five of the eight QTLs tested. Among these, QTLs on chromosomes 3B and 7A showed highly significant and consistent effects across the three populations. This study shows that pedigree-based association mapping using breeding materials can be a useful method for QTL identification at the early stages of breeding programs.

Fine mapping of a preharvest sprouting QTL interval on chromosome 2B in white wheat.

KEY MESSAGE: Fine mapping by recombinant backcross populations revealed that a preharvest sprouting QTL on 2B contained two QTLs linked in coupling with different effects on the phenotype. Wheat preharvest sprouting (PHS) occurs when grain germinates on the plant before harvest, resulting in reduced grain quality. Previous mapping of quantitative trait locus (QTL) revealed a major PHS QTL, QPhs.cnl-2B.1, located on chromosome 2B significant in 16 environments that explained from 5 to 31 % of the phenotypic variation. The objective of this project was to fine map the QPhs.cnl-2B.1 interval. Fine mapping was carried out in recombinant backcross populations (BC1F4 and BC1F5) that were developed by backcrossing selected doubled haploids to a recurrent parent and self-pollinating the BC1F4 and BC1F5 generations. In each generation, three markers in the QPhs.cnl-2B.1 interval were used to screen for recombinants. Fine mapping revealed that the QPhs.cnl-2B.1 interval contained two PHS QTLs linked in coupling. The distal PHS QTL, located between Wmc453c and Barc55, contributed 8 % of the phenotypic variation and also co-located with a major seed dormancy QTL determined by germination index. The proximal PHS QTL, between Wmc474 and CNL415-rCDPK, contributed 16 % of the variation. Several candidate genes including Mg-chelatase H subunit family protein, GTP-binding protein and calmodulin/Ca(2+)-dependent protein kinase were linked to the PHS QTL. Although many recombinant lines were identified, the lack of polymorphism for markers in the QTL interval prevented the localization of the recombination breakpoints and identification of the gene underlying the phenotype.

Homoeologous relationship of rye chromosome arms as detected with wheat PLUG markers.

Based on the similarity in gene structure between rice and wheat, the polymerase chain reaction (PCR)-based landmark unique gene (PLUG) system enabled us to design primer sets that amplify wheat genic sequences including introns. From the previously reported wheat PLUG markers, we chose 144 markers that are distributed on different chromosomes and in known chromosomal regions (bins) to obtain rye-specific PCR-based markers. We conducted PCR with the 144 primer sets and the template of the Imperial rye genomic DNA and found that 131 (91.0%) primer sets successfully amplified PCR products. Of the 131 PLUG markers, 110 (76.4%) markers showed rye-specific PCR amplification with or without restriction enzyme digestion. We assigned 79 of the 110 markers to seven rye chromosomes (1R to 7R) using seven wheat-rye (cv. Imperial) chromosome addition and substitution lines: 12 to 1R, 8 to 2R, 11 to 3R, 8 to 4R, 16 to 5R, 12 to 6R, and 12 to 7R. Furthermore, we located their positions on the short or long (L) chromosome arm, using 13 Imperial rye telosomic lines of common wheat (except for 3RL). Referring to the chromosome bin locations of the 79 PLUG markers in wheat, we deduced the syntenic relationships between rye and wheat chromosomes. We also discussed chromosomal rearrangements in the rye genome with reference to the cytologically visible chromosomal gaps.

Association mapping for pre-harvest sprouting resistance in white winter wheat.

Association mapping identified quantitative trait loci (QTLs) and the markers linked to pre-harvest sprouting (PHS) resistance in an elite association mapping panel of white winter wheat comprising 198 genotypes. A total of 1,166 marker loci including DArT and SSR markers representing all 21 chromosomes of wheat were used in the analysis. General and mixed linear models were used to analyze PHS data collected over 4 years. Association analysis identified eight QTLs linked with 13 markers mapped on seven chromosomes. A QTL was detected on each arm of chromosome 2B and one each on chromosome arms 1BS, 2DS, 4AL, 6DL, 7BS and 7DS. All except the QTL on 7BS are located in a location similar to previous reports and, if verified, the QTL on 7BS is likely to be novel. Principal components and the kinship matrix were used to account for the presence of population structure but had only a minor effect on the results. Although, none of the QTLs was highly significant across all environments, a QTL on the long arm of chromosome 4A was detected in three different environments and also using the best linear unbiased predictions over years. Although previous reports have identified this as a major QTL, its effects were minor in our biparental mapping populations. The results of this study highlight the benefits of association mapping and the value of using elite material in association mapping for plant breeding programs.

Close linkage of a blast resistance gene, Pias(t), with a bacterial leaf blight resistance gene, Xa1-as(t), in a rice cultivar 'Asominori'.

It has long been known that a bacterial leaf blight-resistant line in rice obtained from a crossing using 'Asominori' as a resistant parent also has resistance to blast, but a blast resistance gene in 'Asominori' has not been investigated in detail. In the present study, a blast resistance gene in 'Asominori', tentatively named Pias(t), was revealed to be located within 162-kb region between DNA markers YX4-3 and NX4-1 on chromosome 4 and to be linked with an 'Asominori' allele of the bacterial leaf blight resistance gene Xa1, tentatively named Xa1-as(t). An 'Asominori' allele of Pias(t) was found to be dominant and difference of disease severity between lines having the 'Asominori' allele of Pias(t) and those without it was 1.2 in disease index from 0 to 10. Pias(t) was also closely linked with the Ph gene controlling phenol reaction, suggesting the possibility of successful selection of blast resistance using the phenol reaction. Since blast-resistant commercial cultivars have been developed using 'Asominori' as a parent, Pias(t) is considered to be a useful gene in rice breeding for blast resistance.

Molecular mapping of the suppressor gene Igc1 to the gametocidal gene Gc3-C1 in common wheat.

Several species of the genus Aegilops, wild relatives of wheat (Triticum aestivum, 2n = 6x = 42, AABBDD) carry gametocidal (Gc) genes. Gc genes kill the gametes without themselves by causing chromosomal breakage during post-meiotic cell divisions, and therefore are strong segregation distorters. The Gc gene Gc3-C1 derived from chromosome 3C of Ae. triuncialis (2n = 4x = 28, CCUU) induces chromosomal breakage in wheat cultivar 'Chinese Spring' (CS) but not in cultivar 'Norin 26' (N26). This cultivar-specific inhibition of Gc function is caused by a suppressor gene Igc1 located on chromosome 3B of N26. Igc1 is presumed to be a modified Gc gene without breakage function because of its homoeology to Gc3-C1. Here we report the results of linkage and physical mapping of Igc1 to help elucidate the molecular mechanisms underlying Gc action. Segregation analysis of the phenotypic data in BC(1)F(1) mapping population of the cross between (CSxN26)F(1) and CS + 3C" showed a 1:1 segregation ratio indicating that Igc1 is a dominant gene. In the linkage analysis, three molecular marker loci Xgwm285, Xgwm376, and Xcfp1886 cosegregated with the Igc1 locus. Bin mapping assigned the loci Xgwm285 and Xcfp1886 to bin C-3BS1-0.33 and Xgwm376 to bin C-3BL2-0.22. Physical mapping using Gc-induced chromosomal deletion lines of chromosome 3B of N26 revealed that the Igc1 locus resides in 52.0% or 2.1% of bins C-3BS1-0.33 and C-3BL2-0.22, respectively. Pericentromeric localization of Igc1 in chromosome 3B of N26 may have a positive effect to keep the two-component system of the Gc action. Map-based cloning approach to isolate the Igc1 may be difficult because recombination is depleted in the pericentromeric region. As is shown in this study, the combination of genetic and physical mapping offers high efficiency to identify the regions where genes are located especially in regions with low levels of recombination.

Localization of anchor loci representing five hundred annotated rice genes to wheat chromosomes using PLUG markers.

PCR-based Landmark Unique Gene (PLUG) markers are EST-PCR markers developed based on the orthologous gene conservation between rice and wheat, and on the intron polymorphisms among the three orthologous genes derived from the A, B and D genomes of wheat. We designed a total of 960 primer sets from wheat ESTs that showed high similarity with 951 single-copy rice genes. When genomic DNA of Chinese Spring wheat was used as a template, 872 primer sets amplified one to five distinct products. Out of these 872 PLUG markers, 531 were assigned to one or more chromosomes by nullisomic-tetrasomic analysis. For each wheat chromosome, the number of loci detected ranged from 32 for chromosome 6A to 73 for chromosome 7D, with an average of 48 loci per chromosome. Several novel synteny perturbations were identified using deletion bin-mapping of markers. Furthermore, we demonstrated that PLUG markers can be used as probes to simultaneously identify BAC clones that contain homoeologous regions from all three genomes.

QTL analysis of seed-flooding tolerance in soybean (Glycine max [L.] Merr.).

In soybean (Glycine max [L.] Merr.), varieties with seed-flooding tolerance at the geminating stage are desirable for breeding in countries with much rainfall at sowing time. Our study revealed great intervarietal variation in seed-flooding tolerance as evaluated by germination rate (GR) and normal seedling rate (NS). Pigmented seed coat and small seed weight tended to give a positive effect on seed-flooding tolerance. Subsequently, QTL analysis of GR and NS were performed and a total of four QTLs were detected. Among them, Sft1 on the linkage group H (LG_H) exhibited a large effect on GR after a 24-h treatment; however, Sft2 near the I locus on LG_A2 involved in seed coat pigmentation exhibited the largest effect on seed-flooding tolerance. Sft1, Sft3 and Sft4 were independent of seed coat color and seed weight. Based on the results, we discussed the physiological effects of genetic factors responsible for seed-flooding tolerance in soybean.