Seed shape and size are among the most important agronomic traits because they affect yield and market price. To obtain accurate seed size data, a large number of measurements are needed because there is little difference in size among seeds from one plant. To promote genetic analysis and selection for seed shape in plant breeding, efficient, reliable, high-throughput seed phenotyping methods are required. We developed SmartGrain software for high-throughput measurement of seed shape. This software uses a new image analysis method to reduce the time taken in the preparation of seeds and in image capture. Outlines of seeds are automatically recognized from digital images, and several shape parameters, such as seed length, width, area, and perimeter length, are calculated. To validate the software, we performed a quantitative trait locus (QTL) analysis for rice (Oryza sativa) seed shape using backcrossed inbred lines derived from a cross between japonica cultivars Koshihikari and Nipponbare, which showed small differences in seed shape. SmartGrain removed areas of awns and pedicels automatically, and several QTLs were detected for six shape parameters. The allelic effect of a QTL for seed length detected on chromosome 11 was confirmed in advanced backcross progeny; the cv Nipponbare allele increased seed length and, thus, seed weight. High-throughput measurement with SmartGrain reduced sampling error and made it possible to distinguish between lines with small differences in seed shape. SmartGrain could accurately recognize seed not only of rice but also of several other species, including Arabidopsis (Arabidopsis thaliana). The software is free to researchers.

BackgroundTo create useful gene combinations in crop breeding, it is necessary to clarify the dynamics of the genome composition created by breeding practices. A large quantity of single-nucleotide polymorphism (SNP) data is required to permit discrimination of chromosome segments among modern cultivars, which are genetically related. Here, we used a high-throughput sequencer to conduct whole-genome sequencing of an elite Japanese rice cultivar, Koshihikari, which is closely related to Nipponbare, whose genome sequencing has been completed. Then we designed a high-throughput typing array based on the SNP information by comparison of the two sequences. Finally, we applied this array to analyze historical representative rice cultivars to understand the dynamics of their genome composition.ResultsThe total 5.89-Gb sequence for Koshihikari, equivalent to 15.7× the entire rice genome, was mapped using the Pseudomolecules 4.0 database for Nipponbare. The resultant Koshihikari genome sequence corresponded to 80.1% of the Nipponbare sequence and led to the identification of 67 051 SNPs. A high-throughput typing array consisting of 1917 SNP sites distributed throughout the genome was designed to genotype 151 representative Japanese cultivars that have been grown during the past 150 years. We could identify the ancestral origin of the pedigree haplotypes in 60.9% of the Koshihikari genome and 18 consensus haplotype blocks which are inherited from traditional landraces to current improved varieties. Moreover, it was predicted that modern breeding practices have generally decreased genetic diversityConclusionsDetection of genome-wide SNPs by both high-throughput sequencer and typing array made it possible to evaluate genomic composition of genetically related rice varieties. With the aid of their pedigree information, we clarified the dynamics of chromosome recombination during the historical rice breeding process. We also found several genomic regions decreasing genetic diversity which might be caused by a recent human selection in rice breeding. The definition of pedigree haplotypes by means of genome-wide SNPs will facilitate next-generation breeding of rice and other crops.

Grain shape is an important trait for improving rice yield. A number of quantitative trait loci (QTLs) for this trait have been identified by using primary F2 mapping populations and recombinant inbred lines, in which QTLs with a small effect are harder to detect than they would be in advanced generations. In this study, we developed two advanced mapping populations (chromosome segment substitution lines [CSSLs] and BC4F2 lines consisting of more than 2000 individuals) in the genetic backgrounds of two improved cultivars: a japonica cultivar (Koshihikari) with short, round grains, and an indica cultivar (IR64) with long, slender grains. We compared the ability of these materials to reveal QTLs for grain shape with that of an F2 population. Only 8 QTLs for grain length or grain width were detected in the F2 population, versus 47 in the CSSL population and 65 in the BC4F2 population. These results strongly suggest that advanced mapping populations can reveal QTLs for agronomic traits under complicated genetic control, and that DNA markers linked with the QTLs are useful for choosing superior allelic combinations to enhance grain shape in the Koshihikari and IR64 genetic backgrounds.

To dissect the genetic factors controlling naturally occurring variation of heading date in Asian rice cultivars, we performed QTL analyses using F2 populations derived from crosses between a japonica cultivar, Koshihikari, and each of 12 cultivars originating from various regions in Asia. These 12 diverse cultivars varied in heading date under natural field conditions in Tsukuba, Japan. Transgressive segregation was observed in 10 F2 combinations. QTL analyses using multiple crosses revealed a comprehensive series of loci involved in natural variation in flowering time. One to four QTLs were detected in each cross combination, and some QTLs were shared among combinations. The chromosomal locations of these QTLs corresponded well with those detected in other studies. The allelic effects of the QTLs varied among the cross combinations. Sequence analysis of several previously cloned genes controlling heading date, including Hd1, Hd3a, Hd6, RFT1, and Ghd7, identified several functional polymorphisms, indicating that allelic variation at these loci probably contributes to variation in heading date. Taken together, the QTL and sequencing results indicate that a large portion of the phenotypic variation in heading date in Asian rice cultivars could be generated by combinations of different alleles (possibly both loss- and gain-of-function) of the QTLs detected in this study.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-010-1524-1) contains supplementary material, which is available to authorized users.

To analyze genetic features in the Japanese rice population, which is mainly composed of closely related accessions, a core set of single-nucleotide polymorphisms (SNPs) was selected from SNP resources based on Japanese rice cultivars. A total of 25,199 SNPs were newly detected from the comparison of genomic sequences between two cultivars (Eiko and Rikuu132) and Nipponbare as a reference. A total of 81,499 nonredundant SNPs, including 67,051 SNPs of Koshihikari detected in a previous study, were used as candidates to select the core SNPs. Across the entire genome, 3379 SNPs were selected based on the chromosomal position of each SNP and were investigated each allele of 92 Japanese rice accessions and 3 from outside of Japan. As a result, 2551 SNPs were found to be informative for at least 91 cultivars for reducing the potential risks of genotyping error. The Japanese rice accessions were classified into three groups (upland, lowland Hokkaido, and other lowland) using all 2551 SNPs. In addition, a core set of 768 SNPs was selected to provide an even distribution among the chromosomes. Comparison of dendrograms generated by all 2551 SNPs and the core set of 768 SNPs demonstrated that the core SNPs could be used efficiently and reliably in the classification of the Japanese rice population. The core SNPs can be used for diversity analysis and for genetic analysis of the biparental populations of Japanese rice accessions.