Journal articles 2006
Documents
The genetic architecture of disease resistance in maize: a synthesis of published studies
Wisser RJ, Balint-Kurti PJ and Nelson RJ (2006). The genetic architecture of disease resistance in maize: a synthesis of published studies. Phytopathology 96(2):120–129. (DOI: 10.1094/PHYTO-96-0120).
Fifty publications on the mapping of maize disease resistance loci were synthesized. These papers reported the locations of 437 quantitative trait loci (QTL) for disease (dQTL), 17 resistance genes (R-genes), and 25 R-gene analogs. A set of rules was devised to enable the placement of these loci on a single consensus map, permitting analysis of the distribution of resistance loci identified across a variety of maize germplasm for a number of different diseases. The confidence intervals of the dQTL were distributed over all 10 chromosomes and covered 89% of the genetic map to which the data were anchored. Visual inspection indicated the presence of clusters of dQTL for multiple diseases. Clustering of dQTL was supported by statistical tests that took into account genome-wide variations in gene density. Several novel clusters of resistance loci were identified. Evidence was also found for the association of dQTL with maturity-related QTL. It was evident from the distinct dQTL distributions for the different diseases that certain breeding schemes may be more suitable for certain diseases. This review provides an up-to-date synthesis of reports on the locations of resistance loci in maize.
Wisser RJ, Balint-Kurti PJ and Nelson RJ (2006). The genetic architecture of disease resistance in maize: a synthesis of published studies. Phytopathology 96(2):120–129. (DOI: 10.1094/PHYTO-96-0120).
Fifty publications on the mapping of maize disease resistance loci were synthesized. These papers reported the locations of 437 quantitative trait loci (QTL) for disease (dQTL), 17 resistance genes (R-genes), and 25 R-gene analogs. A set of rules was devised to enable the placement of these loci on a single consensus map, permitting analysis of the distribution of resistance loci identified across a variety of maize germplasm for a number of different diseases. The confidence intervals of the dQTL were distributed over all 10 chromosomes and covered 89% of the genetic map to which the data were anchored. Visual inspection indicated the presence of clusters of dQTL for multiple diseases. Clustering of dQTL was supported by statistical tests that took into account genome-wide variations in gene density. Several novel clusters of resistance loci were identified. Evidence was also found for the association of dQTL with maturity-related QTL. It was evident from the distinct dQTL distributions for the different diseases that certain breeding schemes may be more suitable for certain diseases. This review provides an up-to-date synthesis of reports on the locations of resistance loci in maize.
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Genetic variation in the sensitivity of anther dehiscence to drought stress in rice
Liu JX, Liao, DQ, Oane R, Estenor L, Yang XE, Li ZC and Bennett J (2006). Genetic variation in the sensitivity of anther dehiscence to drought stress in rice. Field Crops Research 97(1):87–100. (DOI: http://dx.doi.org/10.1016/j.fcr.2005.08.019). Not open access: view abstract
Liu JX, Liao, DQ, Oane R, Estenor L, Yang XE, Li ZC and Bennett J (2006). Genetic variation in the sensitivity of anther dehiscence to drought stress in rice. Field Crops Research 97(1):87–100. (DOI: http://dx.doi.org/10.1016/j.fcr.2005.08.019). Not open access: view abstract
In silico insight into two rice chromosomal regions associated with submergence tolerance and resistance to bacterial leaf blight and gall midge
Kottapalli RK, Sarla N, Kikuchi S (2006). In silico insight into two rice chromosomal regions associated with submergence tolerance and resistance to bacterial leaf blight and gall midge. Biotechnology Advances 24(6):561–589. (http://dx.doi.org/10.1016/j.biotechadv.2006.05.003). Not open access: view abstract
Kottapalli RK, Sarla N, Kikuchi S (2006). In silico insight into two rice chromosomal regions associated with submergence tolerance and resistance to bacterial leaf blight and gall midge. Biotechnology Advances 24(6):561–589. (http://dx.doi.org/10.1016/j.biotechadv.2006.05.003). Not open access: view abstract
Race structure within the Mesoamerican gene pool of common bean (Phaseolus vulgaris L.) as determined by microsatellite markers
Díaz LM, Blair MW (2006). Race structure within the Mesoamerican gene pool of common bean (Phaseolus vulgaris L.) as determined by microsatellite markers. Theoretical and Applied Genetics 114(1):143–154. (DOI: 10.1007/s00122-006-0417-9). Not open access: view abstract
Díaz LM, Blair MW (2006). Race structure within the Mesoamerican gene pool of common bean (Phaseolus vulgaris L.) as determined by microsatellite markers. Theoretical and Applied Genetics 114(1):143–154. (DOI: 10.1007/s00122-006-0417-9). Not open access: view abstract
Microsatellite marker diversity in common bean (Phaseolus vulgaris L.)
Blair MW, Giraldo MC, Buendia HF, Tovar E, Duque MC, Beebe SE (2006). Microsatellite marker diversity in common bean (Phaseolus vulgaris L.). Theoretical and Applied Genetics 113(1):100–109. (DOI: 10.1007/s00122-006-0276-4). Not open access: view abstract
Blair MW, Giraldo MC, Buendia HF, Tovar E, Duque MC, Beebe SE (2006). Microsatellite marker diversity in common bean (Phaseolus vulgaris L.). Theoretical and Applied Genetics 113(1):100–109. (DOI: 10.1007/s00122-006-0276-4). Not open access: view abstract
Models for navigating biological complexity in breeding improved crop plants
Hammer GL, Cooper M, Tardieu F, Welch S, Walsh B, van Eeuwijk F, Chapman SC, and Podlich D (2006). Models for navigating biological complexity in breeding improved crop plants. Trends in Plant Science 11(12):587–593. (DOI: 10.1016/j.tplants.2006.10.006). Not open access: view abstract
Hammer GL, Cooper M, Tardieu F, Welch S, Walsh B, van Eeuwijk F, Chapman SC, and Podlich D (2006). Models for navigating biological complexity in breeding improved crop plants. Trends in Plant Science 11(12):587–593. (DOI: 10.1016/j.tplants.2006.10.006). Not open access: view abstract
Laboratory Information Management Software for genotyping workflows: applications in high throughput crop genotyping
Jayashree B, Reddy PT, Leeladevi Y, Crouch JH, Mahalakshmi V, Hutokshi, K Buhariwalla, Eshwar KE, Mace E, Folkertsma R, Senthilvel S, Varshney RK, Seetha K, Rajalakshmi R, Prasanth VP, Chandra S, Swarupa L, Srikalyani P and Hoisington DA (2006). Laboratory Information Management Software for genotyping workflows: applications in high throughput crop genotyping. BMC Bioinformatics 7:383. (DOI: 10.1186/1471-2105-7-383).
A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics.
Jayashree B, Reddy PT, Leeladevi Y, Crouch JH, Mahalakshmi V, Hutokshi, K Buhariwalla, Eshwar KE, Mace E, Folkertsma R, Senthilvel S, Varshney RK, Seetha K, Rajalakshmi R, Prasanth VP, Chandra S, Swarupa L, Srikalyani P and Hoisington DA (2006). Laboratory Information Management Software for genotyping workflows: applications in high throughput crop genotyping. BMC Bioinformatics 7:383. (DOI: 10.1186/1471-2105-7-383).
A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics.
Sequencing multiple and diverse rice varieties: Connecting whole-genome variation with phenotypes
McNally KL, Bruskiewich R, Mackill D, Leach JE, Buell CR, Leung H (2006). Sequencing multiple and diverse rice varieties: Connecting whole-genome variation with phenotypes. Plant Physiology 141(1):26–31. (DOI: 10.1104/pp.106.077313).
The International Rice Functional Genomics Consortium (IRFGC) has initiated a project to provide the rice research community with access to extensive information on genetic variation present within and between diverse rice cultivars and landraces, as well as the genetic resources to exploit that information. Among crop plants, rice is uniquely positioned to achieve this goal due to the release of a high-quality, whole-genome sequence; advances in the use of high-density arrays to compare complex genomes; and the availability of large collections of genetic materials rich in trait variation. In this project, the international rice research community will collaborate with Perlegen Sciences to identify a large fraction of the single nucleotide polymorphisms (SNPs) present in cultivated rice through whole-genome comparisons of 21 rice genomes, including cultivars, germplasm lines, and landraces.
McNally KL, Bruskiewich R, Mackill D, Leach JE, Buell CR, Leung H (2006). Sequencing multiple and diverse rice varieties: Connecting whole-genome variation with phenotypes. Plant Physiology 141(1):26–31. (DOI: 10.1104/pp.106.077313).
The International Rice Functional Genomics Consortium (IRFGC) has initiated a project to provide the rice research community with access to extensive information on genetic variation present within and between diverse rice cultivars and landraces, as well as the genetic resources to exploit that information. Among crop plants, rice is uniquely positioned to achieve this goal due to the release of a high-quality, whole-genome sequence; advances in the use of high-density arrays to compare complex genomes; and the availability of large collections of genetic materials rich in trait variation. In this project, the international rice research community will collaborate with Perlegen Sciences to identify a large fraction of the single nucleotide polymorphisms (SNPs) present in cultivated rice through whole-genome comparisons of 21 rice genomes, including cultivars, germplasm lines, and landraces.
Low nitrogen tolerance in tropical quality protein maize (Zea mays L.): value of predictive traits
Monneveux P, Cabon G and Sanchez C (2006). Low nitrogen tolerance in tropical quality protein maize (Zea mays L.): value of predictive traits. Cereal Research Communications 34(4):1239–1246. (DOI: 10.1556/CRC.34.2006.4.264). Not open access: view abstract
Monneveux P, Cabon G and Sanchez C (2006). Low nitrogen tolerance in tropical quality protein maize (Zea mays L.): value of predictive traits. Cereal Research Communications 34(4):1239–1246. (DOI: 10.1556/CRC.34.2006.4.264). Not open access: view abstract
Development of a wheat fingerprinting database and assembling an SSR reference kit for wheat genetic diversity analysis
Li GY, Dreisigacker S, Warburton ML, Xianchun X, Zhonghu H and Qixin S (2006). Development of a wheat fingerprinting database and assembling an SSR reference kit for wheat genetic diversity analysis. Acta Agronomica Sinica 32(12):1771–1778. (URL: http://211.155.251.148:8080/zwxb/EN/Y2006/V32/I12/1771). Not open access: viewe abstract
Li GY, Dreisigacker S, Warburton ML, Xianchun X, Zhonghu H and Qixin S (2006). Development of a wheat fingerprinting database and assembling an SSR reference kit for wheat genetic diversity analysis. Acta Agronomica Sinica 32(12):1771–1778. (URL: http://211.155.251.148:8080/zwxb/EN/Y2006/V32/I12/1771). Not open access: viewe abstract
