Graham McLaren

Mapping genes controlling root morphology and root distribution in a doubled-haploid population of rice

Abstract A deep thick root system has been demonstrated to have a positive effect on yield of upland rice under water stress conditions. Molecular-marker-aided selection could be helpful for the improvement of root morphological traits, which are otherwise difficult to score. We studied a doubled-haploid population of 105 lines derived from an indica×japonica cross and mapped the genes controlling root morphology and distribution (root thickness, maximum root length, total root weight, deep root weight, deep root weight per tiller, and deep root to shoot ratio). Most putative QTL activity was concentrated in fairly compact regions on chromosomes 1, 2, 3, 6, 7, 8 and 9, but was widely spread on chromosome 5 and largely absent on chromosomes 4, 10, 11 and 12. Between three and six QTLs were identified on different chromosomes for each trait. Individual QTLs accounted for between 4 and 22% of the variation in the traits. Multiple QTL models accounted for between 14 and 49%. The main QTLs were common between traits, showing that it should be possible to modify several aspects of root morphology simultaneously. There was evidence of interaction between marker locations in determining QTL expression. Interacting locations were mostly on different chromosomes and showed antagonistic effects with magnitudes large enough to mask QTL detection. The comparison of QTL locations with another population showed that one to three common QTLs per trait were recovered, among which the most significant was in one or other population. These results will allow the derivation of isogenic lines introgressed with these common segments, separately in the indica and japonica backgrounds.

A nonlinear model for crop development as a function of temperature

The Beta function, commonly used as a skewed probability density function in statistics, was introduced to describe the effect of temperature on the rate of crop development. The framework is set by three cardinal temperatures, namely the base (Tb), the optimum (To) and the ceiling (Tc) temperature. The model parameters Tb and Tc and three other coefficients μ, α and β can be used to derive the value of To and the maximum development rate. Parameter α also characterizes the curvature of the relationship with temperatures between Tb and To, and parameter β describes the curvature between To and Tc. The model has one parameter less than the Rice Clock Model (RCM); and in contrast to the RCM, it ensures that the maximum development rate occurs exactly at To. The model accurately described the response to temperature of several developmental processes, and was superior to two widely used thermal time approaches in predicting rice flowering time.

Identification of QTL for growth- and grain yield-related traits in rice across nine locations of Asia

Abstract. Rice double-haploid (DH) lines of an indica and japonica cross were grown at nine different locations across four countries in Asia. Genotype-by-environment (G × E) interaction analysis for 11 growth- and grain yield-related traits in nine locations was estimated by AMMI analysis. Maximum G × E interaction was exhibited for fertility percentage number of spikelets and grain yield. Plant height was least affected by environment, and the AMMI model explained a total of 76.2% of the interaction effect. Mean environment was computed by averaging the nine environments and subsequently analyzed with other environments to map quantitative trait loci (QTL). QTL controlling the 11 traits were detected by interval analysis using mapmaker/qtl. A threshold LOD of ≥3.20 was used to identify significant QTL. A total of 126 QTL were identified for the 11 traits across nine locations. Thirty-four QTL common in more than one environment were identified on ten chromosomes. A maximum of 44 QTL were detected for panicle length, and the maximum number of common QTL were detected for days to heading detected. A single locus for plant height (RZ730-RG810) had QTL common in all ten environments, confirming AMMI results that QTL for plant height were affected the least by environment, indicating the stability of the trait. Two QTL were detected for grain yield and 19 for thousand-grain weight in all DH lines. The number of QTL per trait per location ranged from zero to four. Clustering of the QTL for different traits at the same marker intervals was observed for plant height, panicle number, panicle length and spikelet number suggesting that pleiotropism and or tight linkage of different traits could be the possible reason for the congruence of several QTL. The many QTL detected by the same marker interval across environments indicate that QTL for most traits are stable and not essentially affected by environmental factors.

Mapping QTLs associated with drought avoidance in upland rice

The identification of molecular markers linked to genes controlling drought resistance factors in rice is a necessary step to improve breeding efficiency for this complex trait. QTLs controlling drought avoidance mechanisms were analyzed in a doubled-haploid population of rice. Three trials with different drought stress intensities were carried out in two sites. Leaf rolling, leaf drying, relative water content of leaves and relative growth rate under water stress were measured on 105 doubled haploid lines in two trials and on a sub-sample of 85 lines in the third one. Using composite interval mapping with a LOD threshold of 2.5, the total number of QTLs detected in all trials combined was 11 for leaf rolling, 10 for leaf drying, 11 for relative water content and 10 for relative growth rate under stress. Some of these QTLs were common across traits. Among the eleven possible QTLs for leaf rolling, three QTLs (on chromosomes 1, 5 and 9) were common across the three trials and four additional QTLs (on chromosomes 3, 4 and 9) were common across two trials. One QTL on chromosome 4 for leaf drying and one QTL on chromosome 1 for relative water content were common across two trials while no common QTL was identified for relative growth rate under stress. Some of the QTLs detected for leaf rolling, leaf drying and relative water content mapped in the same places as QTLs controlling root morphology, which were identified in a previous study involving the same population. Some QTL identified here were also located similarly with other QTLs for leaf rolling as reported from other populations. This study may help to chose the best segments for introgression into rice varieties and improvement of their drought resistance.

Bridging the phenotypic and genetic data useful for integrated breeding through a data annotation using the Crop Ontology developed by the crop communities of practice

The Crop Ontology (CO) of the Generation Challenge Program (GCP) (http://cropontology.org/) is developed for the Integrated Breeding Platform (IBP) (http://www.integratedbreeding.net/) by several centers of The Consultative Group on International Agricultural Research (CGIAR): bioversity, CIMMYT, CIP, ICRISAT, IITA, and IRRI. Integrated breeding necessitates that breeders access genotypic and phenotypic data related to a given trait. The CO provides validated trait names used by the crop communities of practice (CoP) for harmonizing the annotation of phenotypic and genotypic data and thus supporting data accessibility and discovery through web queries. The trait information is completed by the description of the measurement methods and scales, and images. The trait dictionaries used to produce the Integrated Breeding (IB) fieldbooks are synchronized with the CO terms for an automatic annotation of the phenotypic data measured in the field. The IB fieldbook provides breeders with direct access to the CO to get additional descriptive information on the traits. Ontologies and trait dictionaries are online for cassava, chickpea, common bean, groundnut, maize, Musa, potato, rice, sorghum, and wheat. Online curation and annotation tools facilitate (http://cropontology.org) direct maintenance of the trait information and production of trait dictionaries by the crop communities. An important feature is the cross referencing of CO terms with the Crop database trait ID and with their synonyms in Plant Ontology (PO) and Trait Ontology (TO). Web links between cross referenced terms in CO provide online access to data annotated with similar ontological terms, particularly the genetic data in Gramene (University of Cornell) or the evaluation and climatic data in the Global Repository of evaluation trials of the Climate Change, Agriculture and Food Security programme (CCAFS). Cross-referencing and annotation will be further applied in the IBP.

Fostering molecular breeding in developing countries

Molecular breeding (MB) increases genetic gain per crop cycle, stacks favourable alleles at target loci and reduces the number of selection cycles. In the last decade, the private sector has benefitted immensely from MB, which demonstrates its efficacy. In contrast, MB adoption is still limited in the public sector, and it is hardly used in developing countries. Major bottlenecks in these countries include shortage of well-trained personnel, inadequate high-throughput capacity, poor phenotyping infrastructure, lack of information systems or adapted analysis tools or simply resource-limited breeding programmes. The emerging virtual platforms aided by the information and communication technology revolution will help to overcome some of these limitations by providing breeders with better access to genomic resources, advanced laboratory services and robust analytical and data management tools. Apart from some advanced national agricultural research systems (NARS), the implementation of large-scale molecular breeding programmes in developing countries will take time. However, the exponential development of genomic resources, including for less-studied crops, the ever-decreasing cost of marker technologies and the emergence of platforms for accessing MB tools and support services, plus the increasing public–private partnerships and needs-driven demand for improved varieties to counter the global food crisis, are all grounds to predict that MB will have a significant impact on crop breeding in developing countries. These predictions are supported by some preliminary successful examples presented in this paper.

Multifunctional crop trait ontology for breeders' data: field book, annotation, data discovery and semantic enrichment of the literature

The ‘Crop Ontology’ database we describe provides a controlled vocabulary for several economically important crops. It facilitates data integration and discovery from global databases and digital literature. This allows researchers to exploit comparative phenotypic and genotypic information of crops to elucidate functional aspects of traits.

The generation challenge programme platform: semantic standards and workbench for crop science.

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.

International crop information system for germplasm data management.

Passport and phenotypic data on germplasm and breeding lines are available from worldwide sources in various electronic formats. These data can be collated into a single database format to enable strategic interrogation to make the best use of data for effective germplasm use and enhancement. The International Crop Information System (http://www.icis.cgiar.org) is an open-source project under development by a global community of crop researchers and includes applications designed to achieve the storage and interrogation of pedigree and phenotypic data.