Optimization of Multi-Generation Multi-location Genomic Prediction Models for Recurrent Genomic Selection in an Upland Rice Population.

Genomic selection is a worthy breeding method to improve genetic gain in recurrent selection breeding schemes. The integration of multi-generation and multi-location information could significantly improve genomic prediction models in the context of shuttle breeding. The Cirad-CIAT upland rice breeding program applies recurrent genomic selection and seeks to optimize the scheme to increase genetic gain while reducing phenotyping efforts. We used a synthetic population (PCT27) of which S0 plants were all genotyped and advanced by selfing and bulk seed harvest to the S0:2, S0:3, and S0:4 generations. The PCT27 was then divided into two sets. The S0:2 and S0:3 progenies for PCT27A and the S0:4 progenies for PCT27B were phenotyped in two locations: Santa Rosa the target selection location, within the upland rice growing area, and Palmira, the surrogate location, far from the upland rice growing area but easier for experimentation. While the calibration used either one of the two sets phenotyped in one or two locations, the validation population was only the PCT27B phenotyped in Santa Rosa. Five scenarios of genomic prediction and 24 models were performed and compared. Training the prediction model with the PCT27B phenotyped in Santa Rosa resulted in predictive abilities ranging from 0.19 for grain zinc concentration to 0.30 for grain yield. Expanding the training set with the inclusion of the PCT27A resulted in greater predictive abilities for all traits but grain yield, with increases from 5% for plant height to 61% for grain zinc concentration. Models with the PCT27B phenotyped in two locations resulted in higher prediction accuracy when the models assumed no genotype-by-environment (G × E) interaction for flowering (0.38) and grain zinc concentration (0.27). For plant height, the model assuming a single G × E variance provided higher accuracy (0.28). The gain in predictive ability for grain yield was the greatest (0.25) when environment-specific variance deviation effect for G × E was considered. While the best scenario was specific to each trait, the results indicated that the gain in predictive ability provided by the multi-location and multi-generation calibration was low. Yet, this approach could lead to increased selection intensity, acceleration of the breeding cycle, and a sizable economic advantage for the program.

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.

Impact of early genomic prediction for recurrent selection in an upland rice synthetic population.

Population breeding through recurrent selection is based on the repetition of evaluation and recombination among best-selected individuals. In this type of breeding strategy, early evaluation of selection candidates combined with genomic prediction could substantially shorten the breeding cycle length, thus increasing the rate of genetic gain. The objective of this study was to optimize early genomic prediction in an upland rice (Oryza sativa L.) synthetic population improved through recurrent selection via shuttle breeding in two sites. To this end, we used genomic prediction on 334 S0 genotypes evaluated with early generation progeny testing (S0:2 and S0:3) across two sites. Four traits were measured (plant height, days to flowering, grain yield, and grain zinc concentration) and the predictive ability was assessed for the target site. For days to flowering and plant height, which correlate well among sites (0.51-0.62), an increase of up to 0.4 in predictive ability was observed when the model was trained using the two sites. For grain zinc concentration, adding the phenotype of the predicted lines in the nontarget site to the model improved the predictive ability (0.51 with two-site and 0.31 with single-site model), whereas for grain yield the gain was less (0.42 with two-site and 0.35 with single-site calibration). Through these results, we found a good opportunity to optimize the genomic recurrent selection scheme and maximize the use of resources by performing early progeny testing in two sites for traits with best expression and/or relevance in each specific environment.

Translocation of a parthenogenesis gene candidate to an alternate carrier chromosome in apomictic Brachiaria humidicola.

BACKGROUND: The apomictic reproductive mode of Brachiaria (syn. Urochloa) forage species allows breeders to faithfully propagate heterozygous genotypes through seed over multiple generations. In Brachiaria, reproductive mode segregates as single dominant locus, the apospory-specific genomic region (ASGR). The AGSR has been mapped to an area of reduced recombination on Brachiaria decumbens chromosome 5. A primer pair designed within ASGR-BABY BOOM-like (BBML), the candidate gene for the parthenogenesis component of apomixis in Pennisetum squamulatum, was diagnostic for reproductive mode in the closely related species B. ruziziensis, B. brizantha, and B. decumbens. In this study, we used a mapping population of the distantly related commercial species B. humidicola to map the ASGR and test for conservation of ASGR-BBML sequences across Brachiaria species. RESULTS: Dense genetic maps were constructed for the maternal and paternal genomes of a hexaploid (2n = 6x = 36) B. humidicola F1 mapping population (n = 102) using genotyping-by-sequencing, simple sequence repeat, amplified fragment length polymorphism, and transcriptome derived single nucleotide polymorphism markers. Comparative genomics with Setaria italica provided confirmation for x = 6 as the base chromosome number of B. humidicola. High resolution molecular karyotyping indicated that the six homologous chromosomes of the sexual female parent paired at random, whereas preferential pairing of subgenomes was observed in the apomictic male parent. Furthermore, evidence for compensated aneuploidy was found in the apomictic parent, with only five homologous linkage groups identified for chromosome 5 and seven homologous linkage groups of chromosome 6. The ASGR mapped to B. humidicola chromosome 1, a region syntenic with chromosomes 1 and 7 of S. italica. The ASGR-BBML specific PCR product cosegregated with the ASGR in the F1 mapping population, despite its location on a different carrier chromosome than B. decumbens. CONCLUSIONS: The first dense molecular maps of B. humidicola provide strong support for cytogenetic evidence indicating a base chromosome number of six in this species. Furthermore, these results show conservation of the ASGR across the Paniceae in different chromosomal backgrounds and support postulation of the ASGR-BBML as candidate genes for the parthenogenesis component of apomixis.

Colombia a Source of Cacao Genetic Diversity As Revealed by the Population Structure Analysis of Germplasm Bank of Theobroma cacao L.

Beans of the species Theobroma cacao L., also known as cacao, are the raw material to produce chocolate. Colombian cacao has been classified as a fine flavor cacao that represents the 5% of cacao world's production. Colombian genetic resources from this species are conserved in ex situ and in-field germplasm banks, since T. cacao has recalcitrant seeds to desication and long-term storage. Currently, the collection of T. cacao of the Colombian Corporation of Agricultural Research (CORPOICA) has approximately 700 germplasm accessions. We conducted a molecular analysis of Corpoica's cacao collection and a morphological characterization of some accessions with the goal to study its genetic diversity and population structure and, to select interesting accessions for the cacao's breeding program. Phenotypic evaluation was performed based on 18 morphological traits and 4 biochemical traits. PCA analysis of morphological traits explained 60.6% of the total variation in seven components and 100% of the total variation of biochemical traits in four components, grouping the collection in 4 clusters for both variables. We explored 565 accessions from Corpoica's germplasm and 252 accessions from reference populations using 96 single nucleotide polymorphism (SNP) molecular markers. Molecular patterns of cacao Corpoica's collection were obtained amplifying specific alleles in a Fluidigm platform that used integrated circuits of fluids. Corpoica's collection showed highest genetic diversity [Expected Heterozygosity (HE = 0.314), Observed Heterozygosity (HO = 0.353)] that is reduced when reference populations were included in the dataset (HE = 0.294, HO = 0.261). The collection was divided into four clusters based on population structure analysis. Cacao accessions from distinct groups showed some taxonomic concordance and reflected their geographic origins. For instance, accessions classified as Criollo were clearly differentiated in one group and we identified two new Colombian genetic groups. Using a number of allelic variations based on 87 SNP markers and 22 different morphological/biochemical traits, a core collection with a total of 232 accessions was selected as a primary genetic resource for cacao breeders.

Correction: Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding.

[This corrects the article DOI: 10.1371/journal.pone.0136594.].

A Parthenogenesis Gene Candidate and Evidence for Segmental Allopolyploidy in Apomictic Brachiaria decumbens.

Apomixis, asexual reproduction through seed, enables breeders to identify and faithfully propagate superior heterozygous genotypes by seed without the disadvantages of vegetative propagation or the expense and complexity of hybrid seed production. The availability of new tools such as genotyping by sequencing and bioinformatics pipelines for species lacking reference genomes now makes the construction of dense maps possible in apomictic species, despite complications including polyploidy, multisomic inheritance, self-incompatibility, and high levels of heterozygosity. In this study, we developed saturated linkage maps for the maternal and paternal genomes of an interspecific Brachiaria ruziziensis (R. Germ. and C. M. Evrard) × B. decumbens Stapf. F1 mapping population in order to identify markers linked to apomixis. High-resolution molecular karyotyping and comparative genomics with Setaria italica (L.) P. Beauv provided conclusive evidence for segmental allopolyploidy in B. decumbens, with strong preferential pairing of homologs across the genome and multisomic segregation relatively more common in chromosome 8. The apospory-specific genomic region (ASGR) was mapped to a region of reduced recombination on B. decumbens chromosome 5. The Pennisetum squamulatum (L.) R.Br. PsASGR-BABY BOOM-like (psASGR-BBML)-specific primer pair p779/p780 was in perfect linkage with the ASGR in the F1 mapping population and diagnostic for reproductive mode in a diversity panel of known sexual and apomict Brachiaria (Trin.) Griseb. and P. maximum Jacq. germplasm accessions and cultivars. These findings indicate that ASGR-BBML gene sequences are highly conserved across the Paniceae and add further support for the postulation of the ASGR-BBML as candidate genes for the apomictic function of parthenogenesis.

Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding.

Genomic selection (GS) is a promising strategy for enhancing genetic gain. We investigated the accuracy of genomic estimated breeding values (GEBV) in four inter-related synthetic populations that underwent several cycles of recurrent selection in an upland rice-breeding program. A total of 343 S2:4 lines extracted from those populations were phenotyped for flowering time, plant height, grain yield and panicle weight, and genotyped with an average density of one marker per 44.8 kb. The relative effect of the linkage disequilibrium (LD) and minor allele frequency (MAF) thresholds for selecting markers, the relative size of the training population (TP) and of the validation population (VP), the selected trait and the genomic prediction models (frequentist and Bayesian) on the accuracy of GEBVs was investigated in 540 cross validation experiments with 100 replicates. The effect of kinship between the training and validation populations was tested in an additional set of 840 cross validation experiments with a single genomic prediction model. LD was high (average r2 = 0.59 at 25 kb) and decreased slowly, distribution of allele frequencies at individual loci was markedly skewed toward unbalanced frequencies (MAF average value 15.2% and median 9.6%), and differentiation between the four synthetic populations was low (FST ≤0.06). The accuracy of GEBV across all cross validation experiments ranged from 0.12 to 0.54 with an average of 0.30. Significant differences in accuracy were observed among the different levels of each factor investigated. Phenotypic traits had the biggest effect, and the size of the incidence matrix had the smallest. Significant first degree interaction was observed for GEBV accuracy between traits and all the other factors studied, and between prediction models and LD, MAF and composition of the TP. The potential of GS to accelerate genetic gain and breeding options to increase the accuracy of predictions are discussed.

Whole genome sequencing of elite rice cultivars as a comprehensive information resource for marker assisted selection.

Current advances in sequencing technologies and bioinformatics revealed the genomic background of rice, a staple food for the poor people, and provided the basis to develop large genomic variation databases for thousands of cultivars. Proper analysis of this massive resource is expected to give novel insights into the structure, function, and evolution of the rice genome, and to aid the development of rice varieties through marker assisted selection or genomic selection. In this work we present sequencing and bioinformatics analyses of 104 rice varieties belonging to the major subspecies of Oryza sativa. We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome. Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas. Based on a reconstruction of the alleles for the gene GBSSI, we could identify novel genetic markers for selection of varieties with high amylose content. We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops.

An integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experiments.

Recent advances in high-throughput sequencing (HTS) technologies and computing capacity have produced unprecedented amounts of genomic data that have unraveled the genetics of phenotypic variability in several species. However, operating and integrating current software tools for data analysis still require important investments in highly skilled personnel. Developing accurate, efficient and user-friendly software packages for HTS data analysis will lead to a more rapid discovery of genomic elements relevant to medical, agricultural and industrial applications. We therefore developed Next-Generation Sequencing Eclipse Plug-in (NGSEP), a new software tool for integrated, efficient and user-friendly detection of single nucleotide variants (SNVs), indels and copy number variants (CNVs). NGSEP includes modules for read alignment, sorting, merging, functional annotation of variants, filtering and quality statistics. Analysis of sequencing experiments in yeast, rice and human samples shows that NGSEP has superior accuracy and efficiency, compared with currently available packages for variants detection. We also show that only a comprehensive and accurate identification of repeat regions and CNVs allows researchers to properly separate SNVs from differences between copies of repeat elements. We expect that NGSEP will become a strong support tool to empower the analysis of sequencing data in a wide range of research projects on different species.

Estabilidad del Diagnostico Psiquiatrico en pacientes de consulta externa / Psychiatry diagnosis in outpatients

El presente estudio es la primera aproximación que se hace en Colombia a la estabilidad del diagnóstico psiquiátrico. Pretende establecer la frecuencia de este fenómeno en un servicio de atención ambulatoria, teniendo en cuenta el tipo de entidad clínica, la edad y el género, como posibles variables que afecten la estabilidad del diagnóstico psiquiátrico. Objetivos: establecer el tiempo que el diagnóstico índice permanece sin cambio en pacientes psiquiátricos de consulta extema. Establecer la probabilidad de cambio de diagnóstico en un grupo de pacientes psiquiátricos ambulatorios. Determinar qué variables influyen en el tiempo que el diagnóstico psiquiátrico permanece sin cambio. Diseño: se realizó un estudio de cohorte retrospectivo con pacientes evaluados durante 1997 en el Servicio de Consulta Externa de Psiquiatría del Hospital San Juan de Dios de Bogotá. Se midió el cambio de diagnóstico índice, tiempo que el diagnóstico índice permanece sin cambio y variables independientes (edad, género, número de consultas, diagnóstico psiquiátrico y comorbilldad). Por último, se realizaron asociaciones divariadas y análisis de sobrevida. Resultados: las características de las variables demográficas y de diagnóstico estudiadas en este grupo corresponden a lo descrito en otros estudios: los trastornos depresivos, ansiosos y adaptativos son más frecuentes en mujeres; los trastornos psicóticos y por uso de sustancias son más frecuentes en hombres; los pacientes con trastornos orgánicos y depresivos tienen mayor edad. El cambio de diagnóstico se presentó en el 11,01 por cientode los casos evaluados, con una tasa de incidencia de 0,039 cambios por mes. La función de riesgo de cambio de diagnóstico tiene distribución Weibull. Se encontró que las variables que favorecen la estabilidad del diagnóstico son: tener enfermedad bipolar, tener psicosis y ser mayor de sesenta años

Factores de riesgo para algunas anomalías congénitas en población colombiana / Risk factors for some congenital anomalies in Colombian population

La frecuencia de las anomalías congénitas varía entre regiones, razas y a través del tiempo. En Colombia el conocimiento de este tema es fragmentario y escaso, así como las causas de estas patologías que pueden ser genéticas, ambientales o una combinación de ambas. Este estudio se realizó con datos recolectados en hospitales de Bogotá, Neiva y Cartagena, entre 1982 y 1993, bajo los lineamientos del ECLAMC-VERACC en recién nacidos, según un diseño de casos y controles. Los posibles factores de riesgo contemplados fueron: antecedentes de malformaciones familiares, edad de la madre, durante la gestación, metrorragia, enfermedades agudas, enfermedades crónicas, ingestión de medicamentos, consumo de alcohol, consumo de cigarrillos, exposición a factores físicos, exposición a inmunización y plaguicidas, únicamente durante el primer trimestre. El análisis de la información se hizo mediante Regresión Logística Multivariada "paso a paso". Se seleccionaron cuatro anomalías, por presentarse en un suficiente número de individuos, mostrar diferencias significativas entre las frecuencias de casos y controles y por ser clínicamente relevantes, estas son: labio leporino con o sin paladar hendido, polidactilia, sindrome de Down y deformidad en Varo. Se identificaron factores de riesgo para cada una de estas anomalías.