LSGermOPA,a custom OPA of 384 EST-derived SNPs for high-throughput lettuce (<Emphasis Type="Italic">Lactuca sativa</Emphasis> L.) germplasm fingerprinting

To deploy a high-throughput genotyping platform in germplasm management, we designed and tested a custom OPA (Oligo Pool All), LSGermOPA, for assessing the genetic diversity and population structure of the USDA cultivated lettuce (Lactuca sativa L.) germplasm collection using Illumina’s GoldenGate assay. This OPA contains 384 EST (expressed sequence tag)-derived SNP (single nucleotide polymorphism) markers selected from a large set of SNP markers experimentally validated and mapped by the Compositae Genome Project. Used for genotyping were DNA samples prepared from bulked leaves of five randomly-selected seedlings from each of 380 lettuce accessions. High-quality genotype data were obtained from 354 of the 384 SNPs. The reproducibility of automatic genotype calls was 99.8% as calculated from the four pairs of duplicated DNA samples in the assay. An unexpectedly high percentage of heterozygous genotypes at the polymorphic loci for most accessions indicated a high level of heterogeneity within accessions. Only 148 homogenous accessions, collectively comprising all five horticultural types, were used in subsequent analyses to demonstrate the usefulness of LSGermOPA. The results of phylogenetic relationship, population structure and genetic differentiation analyses were consistent with previous reports using other marker systems. This suggests that LSGermOPA is capable of revealing sufficient levels of polymorphism among lettuce cultivars and is appropriate for rapid assessment of genetic diversity and population structure in the lettuce germplasm collection. Challenges and strategies for effective genotyping and managing lettuce germplasm are discussed.     

Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations

Genotyping by sequencing (GBS) is the latest application of next-generation sequencing protocols for the purposes of discovering and genotyping SNPs in a variety of crop species and populations. Unlike other high-density genotyping technologies which have mainly been applied to general interest “reference” genomes, the low cost of GBS makes it an attractive means of saturating mapping and breeding populations with a high density of SNP markers. One barrier to the widespread use of GBS has been the difficulty of the bioinformatics analysis as the approach is accompanied by a high number of erroneous SNP calls which are not easily diagnosed or corrected. In this study, we use a 384-plex GBS protocol to add 30,984 markers to an indica (IR64) × japonica (Azucena) mapping population consisting of 176 recombinant inbred lines of rice (Oryza sativa) and we release our imputation and error correction pipeline to address initial GBS data sparsity and error, and streamline the process of adding SNPs to RIL populations. Using the final imputed and corrected dataset of 30,984 markers, we were able to map recombination hot and cold spots and regions of segregation distortion across the genome with a high degree of accuracy, thus identifying regions of the genome containing putative sterility loci. We mapped QTL for leaf width and aluminum tolerance, and were able to identify additional QTL for both phenotypes when using the full set of 30,984 SNPs that were not identified using a subset of only 1,464 SNPs, including a previously unreported QTL for aluminum tolerance located directly within a recombination hotspot on chromosome 1. These results suggest that adding a high density of SNP markers to a mapping or breeding population through GBS has a great value for numerous applications in rice breeding and genetics research.     

Use of VeraCode 384-plex assays for watermelon diversity analysis and integrated genetic map of watermelon with single nucleotide polymorphisms and simple sequence repeats

Watermelon (Citrullus lanatus var. lanatus) is one of the most important vegetable crops in the world. Molecular markers have become the tools of choice for resolving watermelon taxonomic relationships and evolution. Increased numbers of single nucleotide polymorphism (SNP) markers together with simple sequence repeat (SSR) markers would be useful for phylogenetic analyses of germplasm accessions and for linkage mapping for marker-assisted breeding with quantitative trait loci and single genes. We aimed to construct a genetic map based on SNPs (generated by Illumina Veracode multiplex assays for genotyping) and SSR markers and evaluate relationships inferred from SNP genotypes between 130 watermelon accessions collected throughout the world. We incorporated 282 markers (232 SNPs and 50 SSRs) into the linkage map. The genetic map consisted of 11 linkage groups spanning 924.72 cM with an average distance of 3.28 cM between markers. Because all of the SNP-containing sequences were assembled with the whole-genome sequence draft for watermelon, chromosome numbers could be readily assigned for all the linkage groups. We found that 134 SNPs were polymorphic in 130 watermelon accessions chosen for diversity studies. The current 384-plex SNP set is a powerful tool for characterizing genetic relatedness and for developing medium-resolution genetic maps.     

Highly efficient genotyping of rice biparental populations by GoldenGate assays based on parental resequencing

Key message

A new time- and cost-effective strategy was developed for medium-density SNP genotyping of rice biparental populations, using GoldenGate assays based on parental resequencing.

Abstract

Since the advent of molecular markers, crop researchers and breeders have dedicated huge amounts of effort to detecting quantitative trait loci (QTL) in biparental populations for genetic analysis and marker-assisted selection (MAS). In this study, we developed a new time- and cost-effective strategy for genotyping a population of progeny from a rice cross using medium-density single nucleotide polymorphisms (SNPs). Using this strategy, 728,362 “high quality” SNPs were identified by resequencing Teqing and Lemont, the parents of the population. We selected 384 informative SNPs that were evenly distributed across the genome for genotyping the biparental population using the Illumina GoldenGate assay. 335 (87.2 %) validated SNPs were used for further genetic analyses. After removing segregation distortion markers, 321 SNPs were used for linkage map construction and QTL mapping. This strategy generated SNP markers distributed more evenly across the genome than previous SSR assays. Taking the GW5 gene that controls grain shape as an example, our strategy provided higher accuracy (0.8 Mb) and significance (LOD 5.5 and 10.1) in QTL mapping than SSR analysis. Our study thus provides a rapid and efficient strategy for genetic studies and QTL mapping using SNP genotyping assays.     

Development and application of a set of breeder-friendly SNP markers for genetic analyses and molecular breeding of rice (Oryza sativa L.)

Single nucleotide polymorphisms (SNPs) are the most abundant DNA markers in plant genomes. In this study, based on 54,465 SNPs between the genomes of two Indica varieties, Minghui 63 (MH63) and Zhenshan 97 (ZS97) and additional 20,705 SNPs between the MH63 and Nipponbare genomes, we identified and confirmed 1,633 well-distributed SNPs by PCR and Sanger sequencing. From these, a set of 372 SNPs were further selected to analyze the patterns of genetic diversity in 300 representative rice inbred lines from 22 rice growing countries worldwide. Using this set of SNPs, we were able to uncover the well-known Indica-Japonica subspecific differentiation and geographic differentiations within Indica and Japonica. Furthermore, our SNP results revealed some common and contrasting patterns of the haplotype diversity along different rice chromosomes in the Indica and Japonica accessions, which suggest different evolutionary forces possibly acting in specific regions of the rice genome during domestication and evolution of rice. Our results demonstrated that this set of SNPs can be used as anchor SNPs for large scale genotyping in rice molecular breeding research involving Indica-Japonica and Indica-Indica crosses.     

Distribution and organization of a tandemly repeated 352-bp sequence in the oryzae family

Summary A 352-bp EcoRI fragment from rice DNA was cloned and shown to be a member of a tandem repeat. Sequence determination revealed homologies with human alpha satellite DNA and maize knob heterochromatin specific repeat. This 352-bp sequence is highly specific for the AA genome of rice. However, copy number and sequence organization are variable, depending on the accession analyzed. Several examples of amplification were observed in O. rufipogon and O. longistaminata. Use of resolutive polyacrylamide gel electrophoresis and 4-bp cutter enzymes allowed one to distinguish between the Indica and Japonica subtypes of O. sativa. The same method also discriminates between two groups of O. rufipogon, the presumed ancestor of O. sativa, suggesting that the present day Indica and Japonica subtypes originated independently from two O. rufipogon distinct populations.     

QTL clusters reflect character associations in wild and cultivated rice

The genetic basis of character association related to differentiation found in the primary gene pool of rice was investigated based on the genomic distribution of quantitative trait loci (QTLs). Major evolutionary trends in cultivated rice of Asiatic origin (Oryza sativa) and its wild progenitor (O. rufipogon) are: (1) differentiation from wild to domesticated types (domestication), (2) ecotype differentiation between the perennial and annual types in wild races, and (3) the Indica versus Japonica type differentiation in cultivated races. Using 125 recombinant inbred lines (RILs) derived from a cross between an Indica cultivar of O. sativa and a strain of O. rufipogon carrying some Japonica-like characteristics, we mapped 147 markers, mostly RFLPs, on 12 chromosomes. Thirty-seven morphological and physiological quantitative traits were evaluated, and QTLs for 24 traits were detected. The mapped loci showed a tendency to form clusters that are composed of QTLs of the domestication-related traits as well as Indica/Japonica diagnostic traits. QTLs for perennial/annual type differences did not cluster. This cluster phenomenon could be considered "multifactorial linkages" followed by natural selection favoring co-adapted traits. Further, it is possible that the clustering phenomenon is partly due to pleiotropy of some unknown key factor(s) controlling various traits through diverse metabolic pathways. Chromosomal regions where QTL clusters were found coincided with the regions harboring genes or gene blocks where the frequency of cultivar-derived alleles in RILs is higher than expected. This distortion may be partly due to unconscious selection favoring cultivated plant type during the establishment of RILs.     

High-throughput genotyping in citrus accessions using an SNP genotyping array

We developed a 384 multiplexed SNP array, named CitSGA-1, for the genotyping of Citrus cultivars, and evaluated the performance and reliability of the genotyping. SNPs were surveyed by direct sequence comparison of the sequence tagged site (STS) fragment amplified from genomic DNA of cultivars representing the genetic diversity of citrus breeding in Japan. Among 1497 SNPs candidates, 384 SNPs for a high-throughput genotyping array were selected based on physical parameters of Illumina’s bead array criteria. The assay using CitSGA-1 was applied to a hybrid population of 88 progeny and 103 citrus accessions for breeding in Japan, which resulted in 73,726 SNP calls. A total of 351 SNPs (91 %) could call different genotypes among the DNA samples, resulting in a success rate for the assay comparable to previously reported rates for other plant species. To confirm the reliability of SNP genotype calls, parentage analysis was applied, and it indicated that the number of reliable SNPs and corresponding STSs were 276 and 213, respectively. The multiplexed SNP genotyping array reported here will be useful for the efficient construction of linkage map, for the detection of markers for marker-assisted breeding, and for the identification of cultivars.     

Effects of ascertainment bias and marker number on estimations of barley diversity from high-throughput SNP genotype data

The capability of molecular markers to provide information of genetic structure is influenced by their number and the way they are chosen. This study evaluates the effects of single nucleotide polymorphism (SNP) number and selection strategy on estimates of germplasm diversity and population structure for different types of barley germplasm, namely cultivar and landrace. One hundred and sixty-nine barley landraces from Syria and Jordan and 171 European barley cultivars were genotyped with 1536 SNPs. Different subsets of 384 and 96 SNPs were selected from the 1536 set, based on their ability to detect diversity in landraces or cultivated barley in addition to corresponding randomly chosen subsets. All SNP sets except the landrace-optimised subsets underestimated the diversity present in the landrace germplasm, and all subsets of SNP gave similar estimates for cultivar germplasm. All marker subsets gave qualitatively similar estimates of the population structure in both germplasm sets, but the 96 SNP sets showed much lower data resolution values than the larger SNP sets. From these data we deduce that pre-selecting markers for their diversity in a germplasm set is very worthwhile in terms of the quality of data obtained. Second, we suggest that a properly chosen 384 SNP subset gives a good combination of power and economy for germplasm characterization, whereas the rather modest gain from using 1536 SNPs does not justify the increased cost and 96 markers give unacceptably low performance. Lastly, we propose a specific 384 SNP subset as a standard genotyping tool for middle-eastern landrace barley.     

A pipeline for high throughput detection and mapping of SNPs from EST databases

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic variation that can be used as molecular markers. The SNPs that are hidden in sequence databases can be unlocked using bioinformatic tools. For efficient application of these SNPs, the sequence set should be error-free as much as possible, targeting single loci and suitable for the SNP scoring platform of choice. We have developed a pipeline to effectively mine SNPs from public EST databases with or without quality information using QualitySNP software, select reliable SNP and prepare the loci for analysis on the Illumina GoldenGate genotyping platform. The applicability of the pipeline was demonstrated using publicly available potato EST data, genotyping individuals from two diploid mapping populations and subsequently mapping the SNP markers (putative genes) in both populations. Over 7000 reliable SNPs were identified that met the criteria for genotyping on the GoldenGate platform. Of the 384 SNPs on the SNP array approximately 12% dropped out. For the two potato mapping populations 165 and 185 SNPs segregating SNP loci could be mapped on the respective genetic maps, illustrating the effectiveness of our pipeline for SNP selection and validation.     

Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement

Single nucleotide polymorphism (SNP) data can be obtained using one of the numerous uniplex or multiplex SNP genotyping platforms that combine a variety of chemistries, detection methods, and reaction formats. Kompetitive Allele Specific PCR (KASP) is one of the uniplex SNP genotyping platforms, and has evolved to be a global benchmark technology. However, there are no publications relating either to the technology itself or to its application in crop improvement programs. In this review, we provide an overview of the different aspects of the KASP genotyping platform, discuss its application in crop improvement, and compare it with the chip-based Illumina GoldenGate platform. The International Maize and Wheat Improvement Center routinely uses KASP, generating in excess of a million data points annually for crop improvement purposes. We found that (1) 81 % of the SNPs used in a custom-designed GoldenGate assay were transferable to KASP; (2) using KASP, negative controls (no template) consistently clustered together and rarely produced signals exceeding the threshold values for allele calling, in contrast to the situation observed using GoldenGate assays; (3) KASP’s average genotyping error in positive control DNA samples was 0.7–1.6 %, which is lower than that observed using GoldenGate (2.0–2.4 %); (4) KASP genotyping costs for marker-assisted recurrent selection were 7.9–46.1 % cheaper than those of the BeadXpress and GoldenGate platforms; and (5) KASP offers cost-effective and scalable flexibility in applications that require small to moderate numbers of markers, such as quality control analysis, quantitative trait loci (QTL) mapping in bi-parental populations, marker-assisted recurrent selection, marker-assisted backcrossing, and QTL fine mapping.     

Enigmatic double-stranded RNA in Japonica rice

We have found a linear, 16 kb, double-stranded RNA (dsRNA) in symptomless Japonica rice (Oryza sativa L.) that is not found in Indica rice (Oryza sativa L.). The dsRNA was detected in every tissue and at every developmental stage, and its copy number was approximately constant (about 20 copies/cell). Double-stranded RNA was also detected in two strains of Oryza rufipogon (an ancestor of O. sativa). Hybridization experiments indicated that the dsRNA of O. rufipogon was homologous but not identical to that of O. sativa. The sequence of about 13.2 kb of the dsRNA was determined and two open reading frames (ORFs) were found. The larger ORF (ORF B) was more than 12 351 nucleotides long and encoded more than 4 117 amino acid residues.     

Identification of Quantitative Trait Loci Controlling Drought Tolerance at Seedling Stage in Chinese Dongxiang Common Wild Rice (Oryza rufipogon Griff.)

Common wild rice (Oryza rufipogon Griff.) is the ancestor of cultivated rice (O. sativa L.), which has a greater genetic diversity and important traits that remain to be employed in cultivated rice. In this study, a set of introgression lines (BC₄F₅ and/or BC₄F₆) carrying various introgressed segments from common wild rice, collected from Dongxiang county, Jiangxi Province, China, in the background of an Indica (O. sativa L. ssp. indica) cultivar, Guichao 2, was used. A total of 12 drought-related quantitative trait loci (QTL) were identified by investigating drought tolerance of introgression lines under 30% PEG treatment at the young seedlings stage. Of these QTLs, the alleles of 4 QTLs on chromosome 2, 6 and 12 from Dongxiang common wild rice were responsible for increased drought tolerance of the introgression lines. In particular, a QTL qSDT12-2, near RM17 on chromosome 12, was consistently detected in different replications, and expressed stably under PEG stress throughout the study. It was also found that the QTLs located on different chromosomes might express at different stages.     

Development of species diagnostic SNP markers for quality control genotyping in four rice (<Emphasis Type="Italic">Oryza</Emphasis> L.) species

Species misclassification (misidentification) and handling errors have been frequently reported in various plant species conserved at diverse gene banks, which could restrict use of germplasm for correct purpose. The objectives of the present study were to (i) determine the extent of genotyping error (reproducibility) on DArTseq-based single-nucleotide polymorphisms (SNPs); (ii) determine the proportion of misclassified accessions across 3134 samples representing three African rice species complex (Oryza glaberrima, O. barthii, and O. longistaminata) and an Asian rice (O. sativa), which are conserved at the AfricaRice gene bank; and (iii) develop species- and sub-species (ecotype)-specific diagnostic SNP markers for rapid and low-cost quality control (QC) analysis. Genotyping error estimated from 15 accessions, each replicated from 2 to 16 times, varied from 0.2 to 3.1%, with an overall average of 0.8%. Using a total of 3134 accessions genotyped with 31,739 SNPs, the proportion of misclassified samples was 3.1% (97 of the 3134 accessions). Excluding the 97 misclassified accessions, we identified a total of 332 diagnostic SNPs that clearly discriminated the three indigenous African species complex from Asian rice (156 SNPs), O. longistaminata accessions from both O. barthii and O. glaberrima (131 SNPs), and O. sativa spp. indica from O. sativa spp. japonica (45 SNPs). Using chromosomal position, minor allele frequency, and polymorphic information content as selection criteria, we recommended a subset of 24 to 36 of the 332 diagnostic SNPs for routine QC genotyping, which would be highly useful in determining the genetic identity of each species and correct human errors during routine gene bank operations.     

<Emphasis Type="Bold">A user guide to the</Emphasis><Emphasis Type="BoldItalic">Brassica</Emphasis><Emphasis Type="Bold">60K Illumina Infinium</Emphasis>™ <Emphasis Type="Bold">SNP genotyping array</Emphasis>

The Brassica napus 60K Illumina Infinium? SNP array has had huge international uptake in the rapeseed community due to the revolutionary speed of acquisition and ease of analysis of this high-throughput genotyping data, particularly when coupled with the newly available reference genome sequence. However, further utilization of this valuable resource can be optimized by better understanding the promises and pitfalls of SNP arrays. We outline how best to analyze Brassica SNP marker array data for diverse applications, including linkage and association mapping, genetic diversity and genomic introgression studies. We present data on which SNPs are locus-specific in winter, semi-winter and spring B. napus germplasm pools, rather than amplifying both an A-genome and a C-genome locus or multiple loci. Common issues that arise when analyzing array data will be discussed, particularly those unique to SNP markers and how to deal with these for practical applications in Brassica breeding applications.     

Identification of heterotic loci associated with yield-related traits in Chinese common wild rice (Oryza rufipogon Griff.)

Many rice breeding programs have currently reached yield plateaus as a result of limited genetic variability in parental strains. Dongxiang common wild rice (Oryza rufipogon Griff.) is the progenitor of cultivated rice (Oryza sativa L.) and serves as an important gene pool for the genetic improvement of rice cultivars. In this study, heterotic loci (HLs) associated with six yield-related traits were identified in wild and cultivated rice and investigated using a set of 265 introgression lines (ILs) of O. rufipogon Griff. in the background of the Indica high-yielding cultivar Guichao 2 (O. sativa L.). Forty-two HLs were detected by a single point analysis of mid-parent heterosis values from test cross F₁ offspring, and 30 (71.5%) of these HLs showed significantly positive effects, consistent with the superiority shown by the F₁ test cross population in the six yield-related traits under study. Genetic mapping of hsp11, a locus responsible for the number of spikelets per panicle, confirmed the utility of these HLs. The results indicate that favorable HLs capable of improving agronomic traits are available. The identification of HLs between wild rice and cultivated rice could lead to a new strategy for the application of heterosis in rice breeding.     

SNPs in stress-responsive rice genes: validation, genotyping, functional relevance and population structure

ABSTRACT: BACKGROUND: Single nucleotide polymorphism (SNP) validation and large-scale genotyping are required to maximize the use of DNA sequence variation and determine the functional relevance of candidate genes for complex stress tolerance traits through genetic association in rice. We used the bead array platform-based Illumina GoldenGate assay to validate and genotype SNPs in a select set of stress-responsive genes to understand their functional relevance and study the population structure in rice. RESULTS: Of the 384 putative SNPs assayed, we successfully validated and genotyped 362 (94.3%). Of these 325 (84.6%) showed polymorphism among the 91 rice genotypes examined. Physical distribution, degree of allele sharing, admixtures and introgression, and amino acid replacement of SNPs in 263 abiotic and 62 biotic stress-responsive genes provided clues for identification and targeted mapping of trait-associated genomic regions. We assessed the functional and adaptive significance of validated SNPs in a set of contrasting drought tolerant upland and sensitive lowland rice genotypes by correlating their allelic variation with amino acid sequence alterations in catalytic domains and three-dimensional secondary protein structure encoded by stress-responsive genes. We found a strong genetic association among SNPs in the nine stress-responsive genes with upland and lowland ecological adaptation. Higher nucleotide diversity was observed in indica accessions compared with other rice sub-populations based on different population genetic parameters. The inferred ancestry of 16% among rice genotypes was derived from admixed populations with the maximum between upland aus and wild Oryza species. CONCLUSIONS: SNPs validated in biotic and abiotic stress-responsive rice genes can be used in association analyses to identify candidate genes and develop functional markers for stress tolerance in rice.     

High-throughput genotyping with the GoldenGate assay in the complex genome of soybean

Large numbers of single nucleotide polymorphism (SNP) markers are now available for a number of crop species. However, the high-throughput methods for multiplexing SNP assays are untested in complex genomes, such as soybean, that have a high proportion of paralogous genes. The Illumina GoldenGate assay is capable of multiplexing from 96 to 1,536 SNPs in a single reaction over a 3-day period. We tested the GoldenGate assay in soybean to determine the success rate of converting verified SNPs into working assays. A custom 384-SNP GoldenGate assay was designed using SNPs that had been discovered through the resequencing of five diverse accessions that are the parents of three recombinant inbred line (RIL) mapping populations. The 384 SNPs that were selected for this custom assay were predicted to segregate in one or more of the RIL mapping populations. Allelic data were successfully generated for 89% of the SNP loci (342 of the 384) when it was used in the three RIL mapping populations, indicating that the complex nature of the soybean genome had little impact on conversion of the discovered SNPs into usable assays. In addition, 80% of the 342 mapped SNPs had a minor allele frequency >10% when this assay was used on a diverse sample of Asian landrace germplasm accessions. The high success rate of the GoldenGate assay makes this a useful technique for quickly creating high density genetic maps in species where SNP markers are rapidly becoming available. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. Mention of a trade name, proprietary product, or specific equipment does not constitute a guarantee or warranty by the USDA and does not imply approval of a product to the exclusion of others that may be suitable.     

Inhibitory Effects of Oxygen on the Germination of Oryza sativa L. Seeds

Some workers have reported that the breaking of seed dormancyin rice (O. sativa L.) is usually enhanced by higher oxygentension, whereas others have shown that rice seed dormancy canbe broken by incubation under anaerobic conditions. This articleaims to clarify this paradox. The results show that high oxygentensions inhibit seed germination for a certain period afterharvest in Japonica rice, whereas Indica rice cultivars arenot inhibited by oxygen at any stage. Oxygen inhibition, seed germination, aquatic plants, Japonica rice, Indica rice     

Origin of Oryza sativa in China Inferred by Nucleotide Polymorphisms of Organelle DNA

China is rich of germplasm resources of common wild rice (Oryza rufipogon Griff.) and Asian cultivated rice (O. sativa L.) which consists of two subspecies, indica and japonica. Previous studies have shown that China is one of the domestication centers of O. sativa. However, the geographic origin and the domestication times of O. sativa in China are still under debate. To settle these disputes, six chloroplast loci and four mitochondrial loci were selected to examine the relationships between 50 accessions of Asian cultivated rice and 119 accessions of common wild rice from China based on DNA sequence analysis in the present study. The results indicated that Southern China is the genetic diversity center of O. rufipogon and it might be the primary domestication region of O. sativa. Molecular dating suggested that the two subspecies had diverged 0.1 million years ago, much earlier than the beginning of rice domestication. Genetic differentiations and phylogeography analyses indicated that indica was domesticated from tropical O. rufipogon while japonica was domesticated from O. rufipogon which located in higher latitude. These results provided molecular evidences for the hypotheses of (i) Southern China is the origin center of O. sativa in China and (ii) the two subspecies of O. sativa were domesticated multiple times.