More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.

https://link.springer.com/content/pdf/10.1007%2Fs00122-013-2066-0.pdf

Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement

Epidemiological studies suggested that the low incidence of certain chronic diseases in rice-consuming regions of the world might be associated with the antioxidant compound contents of rice. The molecules with antioxidant activity contained in rice include phenolic acids, flavonoids, anthocyanins, proanthocyanidins, tocopherols, tocotrienols, γ-oryzanol, and phytic acid. This review provides information on the contents of these compounds in rice using a food composition database built from compiling data from 316 papers. The database provides access to information that would have otherwise remained hidden in the literature. For example, among the four types of rice ranked by color, black rice varieties emerged as those exhibiting the highest antioxidant activities, followed by purple, red, and brown rice varieties. Furthermore, insoluble compounds appear to constitute the major fraction of phenolic acids and proanthocyanidins in rice, but not of flavonoids and anthocyanins. It is clear that to maximize the intake of antioxidant compounds, rice should be preferentially consumed in the form of bran or as whole grain. With respect to breeding, japonica rice varieties were found to be richer in antioxidant compounds compared with indica rice varieties. Overall, rice grain fractions appear to be rich sources of antioxidant compounds. However, on a whole grain basis and with the exception of γ-oryzanol and anthocyanins, the contents of antioxidants in other cereals appear to be higher than those in rice.

/pdf/rice-antioxidants-phenolic-acids-flavonoids-anthocyanins-1ybtlk419j.pdf

Rice antioxidants: phenolic acids, flavonoids, anthocyanins, proanthocyanidins, tocopherols, tocotrienols, γ-oryzanol, and phytic acid

Physicochemical and antioxidative properties of red and black rice varieties from Thailand, China and Sri Lanka

Soluble and insoluble-bound phenolic extracts of several varieties of millet (kodo, finger, foxtail, proso, pearl, and little millets) whole grains were evaluated for their phenolic contents and antioxidative efficacy using trolox equivalent antioxidant capacity (TEAC), reducing power (RP), and beta-carotene-linoleate model system as well as ferrous chelating activity. In addition, ferulic and p-coumaric acids were present in soluble and bound phenolic fractions of millets, and their contents were determined using high-performance liquid chromatography (HPLC) and HPLC-mass spectrometry (MS). Kodo millet had the highest total phenolic content, whereas proso millet possessed the least. All millet varieties showed high antioxidant activities, although the order of their efficacy was assay dependent. HPLC analysis of millet phenolic extracts demonstrated that the bound fractions contained more ferulic and p-coumaric acids compared to their soluble counterparts. The results of this study showed that soluble as well as bound fractions of millet grains are rich sources of phenolic compounds with antioxidant, metal chelating, and reducing power. The potential of whole millets as natural sources of antioxidants depends on the variety used. The importance of the insoluble bound fraction of millet as a source of ferulic acid and p-coumaric acid was established, and their contribution to the total phenolic content must be taken into account in the assessment of the antioxidant activity of millets.

Content of insoluble bound phenolics in millets and their contribution to antioxidant capacity.

The use of molecular markers has revolutionized the pace and precision of plant genetic analysis which in turn facilitated the implementation of molecular breeding of crops. The last three decades have seen tremendous advances in the evolution of marker systems and the respective detection platforms. Markers based on single nucleotide polymorphisms (SNPs) have rapidly gained the center stage of molecular genetics during the recent years due to their abundance in the genomes and their amenability for high-throughput detection formats and platforms. Computational approaches dominate SNP discovery methods due to the ever-increasing sequence information in public databases; however, complex genomes pose special challenges in the identification of informative SNPs warranting alternative strategies in those crops. Many genotyping platforms and chemistries have become available making the use of SNPs even more attractive and efficient. This paper provides a review of historical and current efforts in the development, validation, and application of SNP markers in QTL/gene discovery and plant breeding by discussing key experimental strategies and cases exemplifying their impact.

https://downloads.hindawi.com/archive/2012/728398.pdf

SNP markers and their impact on plant breeding.

Total phenolics, flavonoids, antioxidant capacity in rice grain and their relations to grain color, size and weight

Germplasm diversity is the mainstay for crop improvement and genetic dissection of complex traits. Understanding genetic diversity, population structure, and the level and distribution of linkage disequilibrium (LD) in target populations is of great importance and a prerequisite for association mapping. In this study, 100 genome-wide simple sequence repeat (SSR) markers were used to assess genetic diversity, population structure, and LD of 416 rice accessions including landraces, cultivars and breeding lines collected mostly in China. A model-based population structure analysis divided the rice materials into seven subpopulations. 63% of the SSR pairs in these accessions were in LD, which was mostly due to an overall population structure, since the number of locus pairs in LD was reduced sharply within each subpopulation, with the SSR pairs in LD ranging from 5.9 to 22.9%. Among those SSR pairs showing significant LD, the intrachromosomal LD had an average of 25-50 cM in different subpopulations. Analysis of the phenotypic diversity of 25 traits showed that the population structure accounted for an average of 22.4% of phenotypic variation. An example association mapping for starch quality traits using both the candidate gene mapping and genome-wide mapping strategies based on the estimated population structure was conducted. Candidate gene mapping confirmed that the Wx and starch synthase IIa (SSIIa) genes could be identified as strongly associated with apparent amylose content (AAC) and pasting temperature (PT), respectively. More importantly, we revealed that the Wx gene was also strongly associated with PT. In addition to the major genes, we found five and seven SSRs were associated with AAC and PT, respectively, some of which have not been detected in previous linkage mapping studies. The results suggested that the population may be useful for the genome-wide marker-trait association mapping. This new association population has the potential to identify quantitative trait loci (QTL) with small effects, which will aid in dissecting complex traits and in exploiting the rich diversity present in rice germplasm.

Genetic diversity and population structure of a diverse set of rice germplasm for association mapping

Molecular marker assisted selection for improvement of the eating, cooking and sensory quality of rice (Oryza sativa L.)

Phytochemicals such as phenolics and flavonoids, which are present in rice grains, are associated with reduced risk of developing chronic diseases such as cardiovascular disease, type 2 diabetes, and certain cancers. The phenolic and flavonoid compounds in rice grains also contribute to the antioxidant activity. Biofortification of rice grain by conventional breeding is one way to improve nutritional quality to combat nutritional deficiency. For improvement of the phenolics, flavonoids, and antioxidant capacity, we must understand the genetic bases of the related traits. In the present study, mapping of quantitative trait locus (QTL) for five color parameters, phenolics, flavonoids, and antioxidant capacity was completed using a composite interval mapping approach using a doubled haploid (DH) population. Correlation analysis showed that the five color parameters lightness (L*), redness (a*), yellowness (b*), chroma (C), and hue angle (H°) were intercorrelated. The phenolic content was positively ...

Yan Lu

Papers

Total phenolics, flavonoids, antioxidant capacity in rice grain and their relations to grain color, size and weight

Genetic diversity and population structure of a diverse set of rice germplasm for association mapping

Molecular marker assisted selection for improvement of the eating, cooking and sensory quality of rice (Oryza sativa L.)

Quantitative Trait Loci for Brown Rice Color, Phenolics, Flavonoid Contents, and Antioxidant Capacity in Rice Grain

Development of new markers to genotype the functional SNPs of SSIIa, a gene responsible for gelatinization temperature of rice starch