Prospects of breeding high-quality rice using post-genomic tools

Evaluation of Cooked Rice for Eating Quality and Its Components in Geng Rice

At present, ''eating well" is increasingly desired by people instead of merely ''being full". Rice provides the majority of daily caloric needs for half of the global human population. However, eating quality is difficult to objectively evaluate in rice breeding programs. This study was carried out to objectively quantify and predict eating quality in Geng rice. First, eating quality and its components were identified by trained panels. Analysis of variance and broad-sense heritability showed that variation among varieties was significant for all traits except hardness. Among them, viscosity, taste, and appearance were significantly correlated with eating quality. We established an image acquisition and processing system to quantify cooked rice appearance and optimized the process of measuring cooked rice viscosity with a texture analyzer. The results show that yellow areas of the images were significantly correlated with appearance, and adhesiveness was significantly correlated with viscosity. Based on these results, multiple regression analysis was used to predict eating quality: eating quality = 0.37 × adhesiveness - 0.71 × yellow area + 0.89 × taste - 0.34, R2 = 0.85. The correlation coefficient between the predicted and actual values was 0.86. We anticipate that this predictive model will be useful in future breeding programs for high-eating-quality rice.

Gradual daylength sensing coupled with optimum cropping modes enhances multi-latitude adaptation of rice and maize

To expand crop planting areas, reestablishment of crop latitude adaptation based on genetic variation in photoperiodic genes can be performed, but it is quite time consuming. By contrast, a crop variety that already exhibits multi-latitude adaptation has the potential to increase its planting areas to be more widely and quickly available. However, the importance and potential of multi-latitude adaptation of crop varieties have not been systematically described. Here, combining daylength-sensing data with the cropping system of elite rice and maize varieties, we found that varieties with gradual daylength sensing coupled with optimum cropping modes have an enhanced capacity for multi-latitude adaptation in China. Furthermore, this multi-latitude adaptation expanded their planting areas and indirectly improved China's nationwide rice and maize unit yield. Thus, coupling the daylength-sensing process with optimum cropping modes to enhance latitude adaptability of excellent varieties represents an exciting approach for deploying crop varieties with the potential to expand their planting areas and quickly improve nationwide crop unit yield in developing countries.

Post-genomics revolution in the design of premium quality rice in a high-yielding background to meet consumer demands in the 21st century

The eating and cooking quality (ECQ) of rice is critical for determining its economic value in the marketplace and promoting consumer acceptance. It has therefore been of paramount importance in rice breeding programs. Here, we highlight advances in genetic studies of ECQ and discuss prospects for further enhancement of ECQ in rice. Innovations in gene- and genome-editing techniques have enabled improvements in rice ECQ. Significant genes and quantitative trait loci (QTLs) have been shown to regulate starch composition, thereby affecting amylose content and thermal and pasting properties. A limited number of genes/QTLs have been identified for other ECQ properties such as protein content and aroma. Marker-assisted breeding has identified rare alleles in diverse genetic resources that are associated with superior ECQ properties. The post-genomics-driven information summarized in this review is relevant for augmenting current breeding strategies to meet consumer preferences and growing population demands.

Integrated Metabolomics and Transcriptomics Analyses Reveal the Metabolic Differences and Molecular Basis of Nutritional Quality in Landraces and Cultivated Rice

Rice (Oryza sativa L.) is one of the most globally important crops, nutritionally and economically. Therefore, analyzing the genetic basis of its nutritional quality is a paramount prerequisite for cultivating new varieties with increased nutritional health. To systematically compare the nutritional quality differences between landraces and cultivated rice, and to mine key genes that determine the specific nutritional traits of landraces, a seed metabolome database of 985 nutritional metabolites covering amino acids, flavonoids, anthocyanins, and vitamins by a widely targeted metabolomic approach with 114 rice varieties (35 landraces and 79 cultivars) was established. To further reveal the molecular mechanism of the metabolic differences in landrace and cultivated rice seeds, four cultivars and six landrace seeds were selected for transcriptome and metabolome analysis during germination, respectively. The integrated analysis compared the metabolic profiles and transcriptomes of different types of rice, identifying 358 differentially accumulated metabolites (DAMs) and 1982 differentially expressed genes (DEGs), establishing a metabolite–gene correlation network. A PCA revealed anthocyanins, flavonoids, and lipids as the central differential nutritional metabolites between landraces and cultivated rice. The metabolite–gene correlation network was used to screen out 20 candidate genes postulated to be involved in the structural modification of anthocyanins. Five glycosyltransferases were verified to catalyze the glycosylation of anthocyanins by in vitro enzyme activity experiments. At the same time, the different mechanisms of the anthocyanin synthesis pathway and structural diversity in landrace and cultivated rice were systematically analyzed, providing new insights for the improvement and utilization of the nutritional quality of rice landrace varieties.

Deploying viscosity and starch polymer properties to predict cooking and eating quality models: A novel breeding tool to predict texture

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Multivariate analysis was used to develop twelve cooking and eating quality classes.

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Two-layered random forest model was used to predict rice classification.

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High classification accuracy of cooking and eating quality ideotypes were obtained.

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Mismatches from IRRI-released and consumer-preferred lines was capture by the model.

Acceptance of new rice genotypes demanded by rice value chain depends on premium value of varieties that match consumer demands of regional preferences. High throughput prediction tools are not available to breeders to classify cooking and eating quality (CEQ) ideotypes and to capture texture of varieties. The pasting properties in combination with starch properties were used to develop two layered models in order to classify the rice varieties into twelve distinct CEQ ideotypes with unique sensory profiles. Classification models developed using random forest method depicted the overall accuracy of 96 %. These CEQ models were found to be robust to predict ideotypes in both Indica and Japonica diversity panels grown under dry and wet seasons and across the years. We conducted random forest modeling using 1.8 million high density SNPs and identified top 1000 SNP features which explained CEQ model classification with the accuracy of 0.81. Furthermore these CEQ models were found to be valuable to predict textural preferences of IRRI breeding lines released during 1960–2013 and mega varieties preferred in South and South East Asia.

Compositional Variation in Trans-Ferulic, p-coumaric, and Diferulic Acids Levels Among Kernels of Modern and Traditional Maize (Zea mays L.) Hybrids

Maize is one of the most heterogenous cereals worldwide in terms of yield, physical characteristics, and biochemical composition due to its natural diversity. Nowadays the use of maize hybrids is extensive, while the use of landraces is mostly local. Both have become an important genetic resource useful to identify or generate varieties with desirable characteristics to overcome challenges of agronomic performance, nutritional quality, and functionality. In terms of functionality, one of the most studied families of compounds are phenolic acids. These compounds have been associated with the improvement of human health because of their antioxidant capacity. To evaluate the diversity of phenolic compounds in maize, two collections, the Nested Association Mapping (NAM) founders and 24 landraces, were crossed with B73. Phenolic compounds were extracted and quantified by HPLC-PDA. Soluble and cell wall phenolic acids were identified and significant differences between and within the NAM and Landrace collections were assessed. Soluble p-coumaric acid quantification of B73 × NAM hybrids presented high variation as the range went from 14.45 to 132.34 μg/ g dw. In the case of B73 × Landrace hybrids, wide variation was also found, ranging 25.77-120.80 μg/g dw. For trans-ferulic acid, significant variation was found in both hybrid groups: B73 × NAM presented an average of 157.44 μg/g dw (61.02-411.13 μg/g dw) whereas the B73 × Landrace hybrids average was 138.02 μg/g dw (49.32-476.28 μg/g dw). In cell wall p-coumaric acid, a range from 30.93 to 83.69 μg/g dw and 45.06 to 94.98 μg/g dw was found for landrace and NAM hybrids, respectively. For cell wall trans-ferulic acid, a range from 1,641.47 to 2,737.38 μg/g dw and 826.07 to 2,536.40 μg/g dw was observed for landrace and NAM hybrids, respectively. Significant differences between hybrid groups were found in p-coumaric acid, for both soluble and cell wall-bounded. Therefore, maize hybrids produced by conventional techniques using both modern and traditional varieties showed a high diversity in terms of phenolic compounds, denoting the role of these compounds in the maize ability to endure different environment conditions. This study provides a platform of comparison through the unveiling of maize phenolic compounds for future breeding efforts.

Dissection of the genetic basis of oil content in Chinese peanut cultivars through association mapping

Background

Peanut is one of the primary sources for vegetable oil worldwide, and enhancing oil content is the main objective in several peanut breeding programs of the world. Tightly linked markers are required for faster development of high oil content peanut varieties through genomics-assisted breeding (GAB), and association mapping is one of the promising approaches for discovery of such associated markers.

Results

An association mapping panel consisting of 292 peanut varieties extensively distributed in China was phenotyped for oil content and genotyped with 583 polymorphic SSR markers. These markers amplified 3663 alleles with an average of 6.28 alleles per locus. The structure, phylogenetic relationship, and principal component analysis (PCA) indicated two subgroups majorly differentiating based on geographic regions. Genome-wide association analysis identified 12 associated markers including one (AGGS1014_2) highly stable association controlling up to 9.94% phenotypic variance explained (PVE) across multiple environments. Interestingly, the frequency of the favorable alleles for 12 associated markers showed a geographic difference. Two associated markers (AGGS1014_2 and AHGS0798) with 6.90–9.94% PVE were verified to enhance oil content in an independent RIL population and also indicated selection during the breeding program.

Conclusion

This study provided insights into the genetic basis of oil content in peanut and verified highly associated two SSR markers to facilitate marker-assisted selection for developing high-oil content breeding peanut varieties.

Rice quality: How is it defined by consumers, industry, food scientists, and geneticists?

BACKGROUND

Quality is a powerful engine in rice value chain upgrading. However, there is no consensus on how "rice quality" should be defined and measured in the rice sector.

SCOPE AND APPROACH

We adopt a Lancasterian definition of rice quality as a bundle of intrinsic and extrinsic attributes. We then review how rice quality is (i) perceived and defined by consumers and industry stakeholders in rice value chains in Southeast and South Asia; (ii) measured and defined by food technologists; and (iii) predicted through genetics.

KEY FINDINGS AND CONCLUSIONS

Consumers are heterogeneous with respect to their perceived differentiation of rice quality among regions, countries, cities, and urbanization levels. Premium quality is defined by nutritional benefits, softness and aroma in Southeast Asia, and by the physical appearance of the grains (uniformity, whiteness, slenderness), satiety, and aroma in South Asia. These trends are found to be consistent with industry perceptions and have important implications for regional and national breeding programs in terms of tailoring germplasm to regions and rice varieties to specific local market segments. Because rice is traded internationally, there is a need to standardize definitions of rice quality. However, food technologists have not reached unanimity on quality classes and measurement; routine indicators need to be complemented by descriptive profiles elicited through sensory evaluation panels. Finally, because rice quality is controlled by multiple interacting genes expressed through environmental conditions, predicting grain quality requires associating genetic information with grain quality phenotypes in different environments.

Multi-Dimensional Cooking Quality Classification Using Routine Quality Evaluation Methods

A battery of assays to characterize the cooking and eating attributes of rice have been in routine use for several decades. The classification system to group rice varieties into different quality types are often based on cooking and eating attributes defined based on amylose content, rather than being considered a set of attributes contributing to an overall quality type based on multi-dimensional approach. In this chapter, the methods developed to measure the cooking quality attributes of rice are described. Instead of considering each attribute on its own, the authors employ multidimensional data generated from the estimation of amylose content, gel consistency, gelatinization temperature, Rapid Visco-Analyzer parameters to classify rice into distinct cooking quality ideotypes. If used universally, such an approach can improve prediction of cooking quality classifications of rice varieties in the breeding programs.

Endosperm enzyme activity is responsible for texture and eating quality of cooked rice grains in Japanese cultivars

Eating quality of cooked rice grains is an important determinant of its market price and consumer acceptance. To comprehensively assess the variation of eating-quality traits in 152 Japanese rice cultivars, we evaluated activities of eight endosperm enzymes related to degradation of starch and cell-wall polysaccharides. Endosperm enzyme activities showed a wide range of variations and were lower in recently developed cultivars than in landraces and old improved cultivars. Activities of most endosperm enzymes correlated significantly with the eating-quality score and surface texture of cooked rice grains. Principal component analysis revealed that rice cultivars with high eating-quality scores had high stickiness of the grain surface and low levels of endosperm enzyme activities. These results suggest that endosperm enzyme activities control texture and eating quality of cooked rice grains in Japanese rice cultivars.

Measuring Head Rice Recovery in Rice

Head rice recovery (HRR) is a milling quality attribute that is highly influential toward the market price of rice. It is defined as the proportion of paddy rice that retains 75% of its length after milling. For a new rice variety to be accepted and adopted by farmers, the new variety's HRR should satisfy consumer requirements of at least 55% or above. Hence, HRR is a crucial attribute by which new varieties are selected for release. Although the amount of head rice recovered depends on the genetic background of a rice variety, HRR is also highly affected by postharvest processing conditions that the variety goes through. To determine the maximum HRR, therefore, one must ensure that the processing conditions are as optimal as possible. This book chapter outlines how paddy rice is processed into head rice and how HRR is measured. It also proposes an improved laboratory-scale means for postharvest drying to minimize head rice losses.

Re-sequencing Resources to Improve Starch and Grain Quality in Rice

Next-generation sequencing can identify differences in the rice genome that explain the genetic basis of grain quality variation. Differences in rice grain quality are mainly associated with differences in the major component of the grain, starch. Association of rice quality variation with rice genome variation can be conducted at the gene or whole-genome level. Re-sequencing of specific genes or whole genomes can be used depending on the extent to which candidate genes for the traits of interest are known. Amplicon sequencing of genes involved in starch metabolism can help in targeted discovery of the molecular genetic basis of differences in starch related quality attributes. Whole-genome re-sequencing can complement this, when the genetic basis of the trait is expected to be outside the coding region of starch metabolism genes. These approaches have been used successfully to understand the rice genome at specific loci and over the whole genome.

Deciphering the Genetic Architecture of Cooked Rice Texture

The textural attributes of cooked rice determine palatability and consumer acceptance. Henceforth, understanding the underlying genetic basis is pivotal for the genetic improvement of preferred textural attributes in breeding programs. We characterized diverse set of 236 Indica accessions from 37 countries for textural attributes, which includes adhesiveness (ADH), hardness (HRD), springiness (SPR), and cohesiveness (COH) as well as amylose content (AC). A set of 147,692 high quality SNPs resulting from genotyping data of 700K high Density Rice Array (HDRA) derived from the Indica diversity panels of 218 lines were retained for marker-trait associations of textural attributes using single-locus (SL) genome wide association studies (GWAS) which resulted in identifying hotspot on chromosome 6 for AC and ADH attributes. Four independent multi-locus approaches (ML-GWAS) including FASTmrEMMA, pLARmEB, mrMLM, and ISIS_EM-BLASSO were implemented to dissect additional loci of major/minor effects influencing the rice texture and to overcome limitations of SL-based GWAS approach. In total 224 significant quantitative trait nucleotide (QTNs) were identified using ML-GWAS, of which 97 were validated with at least two out of the four multi-locus methods. The GWAS results were in accordance with the very significant negative correlation (r = -0.83) observed between AC and ADH, and the significant correlation exhibited by AC (r < 0.4) with HRD, SPR, and COH. The novel haplotypes and putative candidate genes influencing textural properties beyond AC will be a useful resource for deployment into the marker assisted program to capture consumer preferences influencing rice texture and palatability.

Wheat seed transcriptome reveals genes controlling key traits for human preference and crop adaptation

Analysis of the transcriptome of the developing wheat grain has associated expression of genes with traits involving production (e.g. yield) and quality (e.g. bread quality). Photosynthesis in the grain may be important in retaining carbon that would be lost in respiration during grain filling and may contribute to yield in the late stages of seed formation under warm and dry environments. A small number of genes have been identified as having been selected by humans to optimize the performance of wheat for foods such as bread. Genes determining flour yield in milling have been discovered. Hardness is explained by variations in expression of pin genes. Knowledge of these genes should dramatically improve the efficiency of breeding better climate adapted wheat genotypes.

Down-Regulation of SSSII-2 Gene Expression Results in Novel Low-Amylose Rice with Soft, Transparent Grains

Although soft rice, with low amylose content (AC), has high eating and cooking quality (ECQ), its appearance is poor due to the opaque endosperm. Here, a novel soft rice with low AC but a transparent appearance was generated by knocking-down the expression of SSSII-2, a gene encoding one isoform of soluble starch synthase (SSS). The physicochemical properties of the SSSII-2 RNAi rice are quite different from the control but more like the popular soft rice "Nanjing 46". The taste value assay further demonstrated that the ECQ of SSSII-2 RNAi rice was as high as "Nanjing 46", but only SSSII-2 RNAi rice retained the transparent endosperm under low moisture conditions. Further examination showed that the different morphologies and fine structures of the starch granules may contribute to the specific properties of SSSII-2 RNAi rice. Therefore, SSSII-2 has potential application in future high quality rice breeding programs.

Diversity analysis and genome-wide association studies of grain shape and eating quality traits in rice (Oryza sativa L.) using DArT markers

Microarray-based markers such as Diversity Arrays Technology (DArT) have become the genetic markers of choice for construction of high-density maps, quantitative trait loci (QTL) mapping and genetic diversity analysis based on their efficiency and low cost. More recently, the DArT technology was further developed in combination with high-throughput next-generation sequencing (NGS) technologies to generate the DArTseq platform representing a new sequencing tool of complexity-reduced representations. In this study, we used DArTseq markers to investigate genetic diversity and genome-wide association studies (GWAS) of grain quality traits in rice (Oryza sativa L.). The study was performed using 59 rice genotypes with 525 SNPs derived from DArTseq platform. Population structure analysis revealed only two distinct genetic clusters where genotypes were grouped based on environmental adaptation and pedigree information. Analysis of molecular variance indicated a low degree of differentiation among populations suggesting the need for broadening the genetic base of the current germplasm collection. GWAS revealed 22 significant associations between DArTseq-derived SNP markers and rice grain quality traits in the test genotypes. In general, 2 of the 22 significant associations were in chromosomal regions where the QTLs associated with the given traits had previously been reported, the other 20 significant SNP marker loci were indicative of the likelihood discovery of novel alleles associated with rice grain quality traits. DArTseq-derived SNP markers that include SNP12_100006178, SNP13_3052560 and SNP14_3057360 individually co-localised with two functional gene groups that were associated with QTLs for grain width and grain length to width ratio on chromosome 3, indicating trait dependency or pleiotropic-effect loci. This study demonstrated that DArTseq markers were useful genomic resources for genome-wide association studies of rice grain quality traits to accelerate varietal development and release.

Variations in agronomic and grain quality traits of rice grown under irrigated lowland conditions in West Africa

Rice breeding in West Africa has been largely skewed toward yield enhancement and stress tolerance. This has led to the variable grain quality of locally produced rice in the region. This study sought to assess variations in the agronomic and grain quality traits of some rice varieties grown in this region, with a view to identifying sources of high grain yield and quality that could serve as potential donors in their breeding programs. Forty-five varieties were grown under irrigated conditions in Benin and Senegal with two trials in each country. There were wide variations in agronomic and grain quality traits among the varieties across the trials. Cluster analysis using paddy yield, head rice yield, and chalkiness revealed that 68% of the total variation could be explained by five varietal groupings. One group comprising seven varieties (Afrihikari, BG90-2, IR64, Sahel 108, WAT311-WAS-B-B-23-7-1, WAT339-TGR-5-2, and WITA 10) had high head rice yield and low chalkiness. Of the varieties in this group, Sahel 108 had the highest paddy yield in three of the four trials. IR64 and Afrihikari had intermediate and low amylose content, respectively, with the rest being high-amylose varieties. Another group of varieties consisting of B6144F-MR-6-0-0, C74, IR31851-96-2-3-2-1, ITA222, Jaya, Sahel 305, WITA 1, and WITA 2 had high paddy yield but poor head rice yield and chalkiness. The use of materials from these two groups of varieties could accelerate breeding for high yielding rice varieties with better grain quality for local production in West Africa.

Rice Soluble Starch Synthase I: Allelic Variation, Expression, Function, and Interaction With Waxy

Starch, which is composed of amylose and amylopectin, is the key determinant of rice quality. Amylose is regulated by the Waxy (Wx) gene, whereas amylopectin is coordinated by various enzymes including eight soluble starch synthases (SSSs), of which SSSI accounts for ∼70% of the total SSS activity in cereal endosperm. Although great progress has been made in understanding SSSI gene expression and function, allelic variation and its effects on gene expression, rice physicochemical properties and qualities, and interactions with the Wx gene remain unclear. Herein, SSSI nucleotide polymorphisms were analyzed in 165 rice varieties using five distinct molecular markers, three of which reside in an SSSI promoter and might account for a higher expression of the SSSIⁱ allele in indica ssp. than of the SSSI^j allele in japonica ssp. The results of SSSI promoter-Beta-Glucuronidase (β-GUS) analysis were consistent with the expression results. Moreover, analysis of near isogenic lines (NILs) in the Nipponbare (Nip) background showed that Nip (SSSIⁱ ) and Nip (SSSI^j ) differed in their thermal properties, gel consistency (GC), and granule crystal structure. Knockdown of SSSI expression using the SSSI-RNA interference (RNAi) construct in both japonica and indica backgrounds caused consistent changes in most tested physicochemical characteristics except GC. Moreover, taste value analysis (TVA) showed that introduction of the SSSI allele in indica or knockdown of SSSI expression in japonica cultivars significantly reduced the comprehensive taste value, which was consistent with the superior taste of japonica against indica. Furthermore, to test the potential interaction between SSSI and different Wx alleles, three NILs within the Wx locus were generated in the indica cv. Longtefu (LTF) background, which were designated as LTF (Wx^a ), LTF (Wx^b ), and LTF (wx). The SSSI-RNAi construct was also introduced into these three NILs, and physiochemical analysis confirmed that the knockdown of SSSI significantly increased the rice apparent amylose content (AAC) only in the Wx^a and Wx^b background and caused different changes in GC in the NILs. Therefore, the effect of SSSI variation on rice quality also depends on its crosstalk with other factors, especially the Wx gene. These findings provide fundamental knowledge for future breeding of rice with premium eating and cooking qualities.

Whole genome sequencing-based association study to unravel genetic architecture of cooked grain width and length traits in rice

In this study, we used 2.9 million single nucleotide polymorphisms (SNP) and 393,429 indels derived from whole genome sequences of 591 rice landraces to determine the genetic basis of cooked and raw grain length, width and shape using genome-wide association study (GWAS). We identified a unique fine-mapped genetic region GWi7.1 significantly associated with cooked and raw grain width. Additionally, GWi7.2 that harbors GL7/GW7 a cloned gene for grain dimension was found. Novel regions in chromosomes 10 and 11 were also found to be associated with cooked grain shape and raw grain width, respectively. The indel-based GWAS identified fine-mapped genetic regions GL3.1 and GWi5.1 that matched synteny breakpoints between indica and japonica. GL3.1 was positioned a few kilobases away from GS3, a cloned gene for cooked and raw grain lengths in indica. GWi5.1 found to be significantly associated with cooked and raw grain width. It anchors upstream of cloned gene GW5, which varied between indica and japonica accessions. GWi11.1 is present inside the 3'-UTR of a functional gene in indica that corresponds to a syntenic break in chromosome 11 of japonica. Our results identified novel allelic structural variants and haplotypes confirmed using single locus and multilocus SNP and indel-based GWAS.

Whole genome sequencing-based association study to unravel genetic architecture of cooked grain width and length traits in rice

In this study, we used 2.9 million single nucleotide polymorphisms (SNP) and 393,429 indels derived from whole genome sequences of 591 rice landraces to determine the genetic basis of cooked and raw grain length, width and shape using genome-wide association study (GWAS). We identified a unique fine-mapped genetic region GWi7.1 significantly associated with cooked and raw grain width. Additionally, GWi7.2 that harbors GL7/GW7 a cloned gene for grain dimension was found. Novel regions in chromosomes 10 and 11 were also found to be associated with cooked grain shape and raw grain width, respectively. The indel-based GWAS identified fine-mapped genetic regions GL3.1 and GWi5.1 that matched synteny breakpoints between indica and japonica. GL3.1 was positioned a few kilobases away from GS3, a cloned gene for cooked and raw grain lengths in indica. GWi5.1 found to be significantly associated with cooked and raw grain width. It anchors upstream of cloned gene GW5, which varied between indica and japonica accessions. GWi11.1 is present inside the 3'-UTR of a functional gene in indica that corresponds to a syntenic break in chromosome 11 of japonica. Our results identified novel allelic structural variants and haplotypes confirmed using single locus and multilocus SNP and indel-based GWAS.

Sequencing of Australian wild rice genomes reveals ancestral relationships with domesticated rice

The related A genome species of the Oryza genus are the effective gene pool for rice. Here, we report draft genomes for two Australian wild A genome taxa: O. rufipogon-like population, referred to as Taxon A, and O. meridionalis-like population, referred to as Taxon B. These two taxa were sequenced and assembled by integration of short- and long-read next-generation sequencing (NGS) data to create a genomic platform for a wider rice gene pool. Here, we report that, despite the distinct chloroplast genome, the nuclear genome of the Australian Taxon A has a sequence that is much closer to that of domesticated rice (O. sativa) than to the other Australian wild populations. Analysis of 4643 genes in the A genome clade showed that the Australian annual, O. meridionalis, and related perennial taxa have the most divergent (around 3 million years) genome sequences relative to domesticated rice. A test for admixture showed possible introgression into the Australian Taxon A (diverged around 1.6 million years ago) especially from the wild indica/O. nivara clade in Asia. These results demonstrate that northern Australia may be the centre of diversity of the A genome Oryza and suggest the possibility that this might also be the centre of origin of this group and represent an important resource for rice improvement.

Enhancing genetic gain in the era of molecular breeding

As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as the amount of increase in performance that is achieved annually through artificial selection. To develop pro ducts that meet the increasing demand of mankind, especially for food and feed, in addition to various industrial uses, breeders are challenged to enhance the potential of genetic gain continuously, at ever higher rates, while they close the gaps that remain between the yield potential in breeders' demonstration trials and the actual yield in farmers' fields. Factors affecting genetic gain include genetic variation available in breeding materials, heritability for traits of interest, selection intensity, and the time required to complete a breeding cycle. Genetic gain can be improved through enhancing the potential and closing the gaps, which has been evolving and complemented with modern breeding techniques and platforms, mainly driven by molecular and genomic tools, combined with improved agronomic practice. Several key strategies are reviewed in this article. Favorable genetic variation can be unlocked and created through molecular and genomic approaches including mutation, gene mapping and discovery, and transgene and genome editing. Estimation of heritability can be improved by refining field experiments through well-controlled and precisely assayed environmental factors or envirotyping, particularly for understanding and controlling spatial heterogeneity at the field level. Selection intensity can be significantly heightened through improvements in the scale and precision of genotyping and phenotyping. The breeding cycle time can be shortened by accelerating breeding procedures through integrated breeding approaches such as marker-assisted selection and doubled haploid development. All the strategies can be integrated with other widely used conventional approaches in breeding programs to enhance genetic gain. More transdisciplinary approaches, team breeding, will be required to address the challenge of maintaining a plentiful and safe food supply for future generations. New opportunities for enhancing genetic gain, a high efficiency breeding pipeline, and broad-sense genetic gain are also discussed prospectively.

Functional cereals for production in new and variable climates

Adaptation of cereal crops to variable or changing climates requires that essential quality attributes are maintained to deliver food that will be acceptable to human consumers. Advances in cereal genomics are delivering insights into the molecular basis of nutritional and functional quality traits in cereals and defining new genetic resources. Understanding the influence of the environment on expression of these traits will support the retention of these essential functional properties during climate adaptation. New cereals for use as whole grain or ground to flour for other food products may be based upon the traditional species such as rice and wheat currently used in these food applications but may also include new options exploiting genomics tools to allow accelerated domestication of new species.

Variation in cooking and eating quality traits in Japanese rice germplasm accessions

The eating quality of cooked rice is important and determines its market price and consumer acceptance. To comprehensively describe the variation of eating quality in 183 rice germplasm accessions, we evaluated 33 eating-quality traits including amylose and protein contents, pasting properties of rice flour, and texture of cooked rice grains. All eating-quality traits varied widely in the germplasm accessions. Principal-components analysis (PCA) revealed that allelic differences in the Wx gene explained the largest proportion of phenotypic variation of the eating-quality traits. In 146 accessions of non-glutinous temperate japonica rice, PCA revealed that protein content and surface texture of the cooked rice grains significantly explained phenotypic variations of the eating-quality traits. An allelic difference based on simple sequence repeats, which was located near a quantitative trait locus (QTL) on the short arm of chromosome 3, was associated with differences in the eating quality of non-glutinous temperate japonica rice. These results suggest that eating quality is controlled by genetic factors, including the Wx gene and the QTL on chromosome 3, in Japanese rice accessions. These genetic factors have been consciously selected for eating quality during rice breeding programs in Japan.