Genetic bases of resistance to the rice hoja blanca disease deciphered by a quantitative trait locus approach.

Rice hoja blanca (RHB) is one of the most serious diseases in rice-growing areas in tropical Americas. Its causal agent is RHB virus (RHBV), transmitted by the planthopper Tagosodes orizicolus Müir. Genetic resistance is the most effective and environment-friendly way of controlling the disease. So far, only 1 major quantitative trait locus (QTL) of Oryza sativa ssp. japonica origin, qHBV4.1, that alters the incidence of the virus symptoms in 2 Colombian cultivars has been reported. This resistance has already started to be broken, stressing the urgent need for diversifying the resistance sources. In the present study, we performed a search for new QTLs of O. sativa indica origin associated with RHB resistance. We used 4 F2:3-segregating populations derived from indica-resistant varieties crossed with a highly susceptible japonica pivot parent. Besides the standard method for measuring disease incidence, we developed a new method based on computer-assisted image processing to determine the affected leaf area (ALA) as a measure of symptom severity. Based on the disease severity and incidence scores in the F3 families under greenhouse conditions and SNP genotyping of the F2 individuals, we identified 4 new indica QTLs for RHB resistance on rice chromosomes 4, 6, and 11, namely, qHBV4.2WAS208, qHBV6.1PTB25, qHBV11.1, and qHBV11.2, respectively. We also confirmed the wide-range action of qHBV4.1. Among the 5 QTLs, qHBV4.1 and qHBV11.1 had the largest effects on incidence and severity, respectively. These results provide a more complete understanding of the genetic bases of RHBV resistance in the cultivated rice gene pool and can be used to develop marker-aided breeding strategies to improve RHB resistance. The power of joint- and meta-analyses allowed precise mapping and candidate gene identification, providing the basis for positional cloning of the 2 major QTLs qHBV4.1 and qHBV11.1.

COMPARACIÓN MORFO-AGRONÓMICA Y MOLECULAR DE CATORCE VARIEDADES DE ARROZ (Oryza sativa) CON LAS LÍNEAS QUE DIERON SU ORIGEN / Morpho-agronomic and molecular comparison of fourteen varieties of rice (Oryza sativa) with the lines that gave them the origin

RESUMEN Con el objetivo de determinar las diferencias morfo-agronómicas y de calidad, y la diversidad genética entre 14 variedades de arroz de América Latina con sus respectivas líneas de origen, se estableció un estudio (Bloques completos al azar, con 28 genotipos, tres repeticiones y dos siembras en el tiempo), en el cual se midieron 25 variables morfo-agronómicas y de calidad de grano. El análisis molecular se hizo mediante un arreglo de 96 marcadores tipo SNP de alta capacidad de discriminación para arroces Indica. El análisis estadístico se hizo combinando los datos de las dos siembras porque no hubo diferencias estadísticas entre ellas. Además, se analizaron en conjunto los datos moleculares con los morfo-agronómicos y de calidad, usando el índice de Gower para generar una matriz de similitud. Mediante el programa SAS se analizaron los datos agronómicos y moleculares tanto en forma independiente como en conjunto. Los resultados mostraron que, de las 14 variedades, ocho se agruparon con su línea de origen y hubo una variedad que se agrupó con una línea hermana de su ancestro. Los resultados fueron consistentes cuando el análisis de datos se hizo independientemente o combinado. Dada la amplia diversidad encontrada dentro de las variedades y que ninguna fue homocigota al 100 % no se pudieron establecer los perfiles genéticos distintivos de ellas, por lo que se debe hacer la purificación de las variedades para establecer su huella genética.

ABSTRACT This research aimed to determine the morpho-agronomic, grain quality, and molecular differences between 14 rice varieties and their ancestors. These rice varieties from Latin America were tested for 25 variables in a randomized complete block design with 28 genotypes, two planting dates, and three replications. The molecular analysis was done using an array of 96 SNP markers with a high discrimination capacity for Indica rice. A combined statistical analysis was done because there were no statistical differences between the planting dates. Also, molecular, morpho-agronomic, and grain quality data were analyzed together, using the Gower index to generate a similarity matrix. Agronomic and molecular data were analyzed both, together and independently, through the SAS program. Results showed that eight varieties were grouped with their respective ancestor, and one variety was grouped with a sibling of their ancestor and was consistent in all the analyses. However, given the wide heterozygosity found within the varieties, distinctive genetic profiles could not be established; the varieties must be purified to establish their genetic footprint.

Genetic and phenotypic characterization of rice grain quality traits to define research strategies for improving rice milling, appearance, and cooking qualities in Latin America and the Caribbean.

Rice (Oryza sativa L.)grain quality is a set of complex interrelated traits that include grain milling, appearance, cooking, and edible properties. As consumer preferences in Latin America and the Caribbean evolve, determining what traits best capture regional grain quality preferences is fundamental for breeding and cultivar release. In this study, a genome-wide association study (GWAS), marker-assisted selection (MAS), and genomic selection (GS) were evaluated to help guide the development of new breeding strategies for rice grain quality improvement. For this purpose, 284 rice lines representing over 20 yr of breeding in Latin America and the Caribbean were genotyped and phenotyped for 10 different traits including grain milling, appearance, cooking, and edible quality traits. Genetic correlations among the 10 traits ranged from -0.83 to 0.85. A GWAS identified 19 significant marker/trait combinations associated with eight grain quality traits. Four functional markers, three located in the Waxy and one in the starch synthase IIa genes, were significantly associated with six grain-quality traits. These markers individually explained 51-75% of the phenotypic variance depending on the trait, clearly indicating their potential utility for MAS. Cross-validation studies to evaluate predictive abilities of four different GS models for each of the 10 quality traits were conducted and predictive abilities ranged from 0.3 to 0.72. Overall, the machine learning model random forest had the highest predictive abilities and was especially effective for traits where large effect quantitative trait loci were identified. This study provides the foundation for deploying effective molecular breeding strategies for grain quality in Latin American rice breeding programs.

Concordancia entre analistas de laboratorios de latinoamérica para la determinación de la apariencia de grano de arroz pulido mediante el uso de imágenes digitales

La determinación de la apariencia del grano de arroz es un aspecto clave para evaluar su calidad. Generalmente, este análisis es realizado de manera visual empleando analistas expertos, sin embargo debido a la naturaleza subjetiva de su determinación, los resultados pueden ser divergentes. Con el objetivo de evaluar la concordancia entre analistas de laboratorios latinoamericanos de calidad de arroz en la determinación de la apariencia del grano de arroz pulido con ayuda de imágenes digitalizadas, se realizó un ensayo interlaboratorio con diez analistas e imágenes de 90 granos, capturadas mediante scanner de alta resolución. Los granos fueron clasificados en cuatro categorías incluyendo grano traslúcido, grano yesoso, grano panza blanca y granos dañados. La categorización fue analizada mediante la moda, frecuencia, concordancia relativa y coeficiente de concordancia Kappa. Adicionalmente, se elaboró una galería referencial de imágenes de granos típicos de cada categoría, basada en la frecuencia de modas. Los resultados revelaron un valor de Kappa de 0,49 que corresponde a una reproducibilidad moderada, atribuida a la subjetividad del análisis visual de las imágenes. Los resultados evidencian la necesidad de uniformizar criterios de evaluación entre analistas para mejorar la confiabilidad en la determinación de la apariencia de granos de arroz.

Concordance among analysts from Latin-american laboratories for rice grain appearance determination using a gallery of digital images. The appearance of rice grain is a key aspect in quality determination. Mainly, this analysis is performed by expert analysts through visual observation; however, due to the subjective nature of the analysis, the results may vary among analysts. In order to evaluate the concordance between analysts from Latin-American rice quality laboratories for rice grain appearance through digital images, an inter-laboratory test was performed with ten analysts and images of 90 grains captured with a high resolution scanner. Rice grains were classified in four categories including translucent, chalky, white belly, and damaged grain. Data was categorized using statistic parameters like mode and its frequency, the relative concordance, and the reproducibility parameter kappa. Additionally, a referential image gallery of typical grain for each category was constructed based on mode frequency. Results showed a Kappa value of 0.49, corresponding to a moderate reproducibility, attributable to subjectivity in the visual analysis of grain images. These results reveal the need for standardize the evaluation criteria among analysts to improve the confidence of the determination of rice grain appearance.

The potential of rice to offer solutions for malnutrition and chronic diseases.

It is internationally accepted that malnutrition and chronic diseases in developing countries are key limitations to achieving the Millennium Development Goals. In many developing countries, rice is the primary source of nutrition. In those countries, the major forms of malnutrition are Fe-induced anaemia, Zn deficiency and Vitamin A deficiency, whereas the major chronic disease challenges are Type II diabetes, cardiovascular disease and some cancers. There is a growing corpus of evidence regarding both limitations and opportunities as to how rice could be an effective vehicle by which to tackle key nutrition and health related problems in countries with limited resources. Rice breeding programs are able to focus on developing new varieties carrying enhanced amounts of either Fe, Zn or beta-carotene because of large public investment, and the intuitive link between providing a mineral/vitamin to cure a deficiency in that mineral/vitamin. By contrast, there has been little investment in progressing the development of particular varieties for potential impact on chronic diseases. In this review article we focus on the broad battery of evidence linking rice-related nutritional limitations to their impact on a variety of human health issues. We discuss how rice might offer sometimes even simple solutions to rectifying key problems through targeted biofortification strategies and finally, we draw attention to how recent technological (-omics) developments may facilitate untold new opportunities for more rapidly generating improved rice varieties specifically designed to meet the current and future nutritional needs of a rapidly expanding global population.

[Concordance among analysts from Latin-American laboratories for rice grain appearance determination using a gallery of digital images]. / Concordancia entre analistas de laboratorios de latinoamérica para la determinación de la apariencia de grano de arroz pulido mediante el uso de imágenes digitales.

The appearance of rice grain is a key aspect in quality determination. Mainly, this analysis is performed by expert analysts through visual observation; however, due to the subjective nature of the analysis, the results may vary among analysts. In order to evaluate the concordance between analysts from Latin-American rice quality laboratories for rice grain appearance through digital images, an inter-laboratory test was performed with ten analysts and images of 90 grains captured with a high resolution scanner. Rice grains were classified in four categories including translucent, chalky, white belly, and damaged grain. Data was categorized using statistic parameters like mode and its frequency, the relative concordance, and the reproducibility parameter kappa. Additionally, a referential image gallery of typical grain for each category was constructed based on mode frequency. Results showed a Kappa value of 0.49, corresponding to a moderate reproducibility, attributable to subjectivity in the visual analysis of grain images. These results reveal the need for standardize the evaluation criteria among analysts to improve the confidence of the determination of rice grain appearance.