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Journal articles 2006

Documents

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Development of a composite collection for mining germplasm possessing allelic variation for beneficial traits in chickpea Development of a composite collection for mining germplasm possessing allelic variation for beneficial traits in chickpea

Upadhyaya HD, Furman BJ, Dwivedi SL, Udupa SM, Gowda CLL, Baum M, Crouch JH, Buhariwalla HK, and Sube Singh (2006). Development of a composite collection for mining germplasm possessing allelic variation for beneficial traits in chickpea. Plant Genetic Resources 4(1):13–19. (DOI: http://dx.doi.org/10.1079/PGR2005101). Not open access: view abstract

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Mapping QTLs and QTL-environment interaction for CIMMYT maize drought stress program using factorial regression and partial least squares methods Mapping QTLs and QTL-environment interaction for CIMMYT maize drought stress program using factorial regression and partial least squares methods

Vargas M, van Eeuwijk F, Crossa J and Ribaut J-M (2006). Mapping QTLs and QTL-environment interaction for CIMMYT maize drought stress program using factorial regression and partial least squares methods. Theoretical and Applied Genetics 112(6):1009–1023. (DOI: 10.1007/s00122-005-0204-z). Not open access: view abstract

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Fenotipagem para tolerância à seca visando o melhoramento genético do trigo no cerrado Fenotipagem para tolerância à seca visando o melhoramento genético do trigo no cerrado

Ribeiro Júnior WQ, Ramos MLG, Vasconcelos U, Trindade MG, Ferreira FM, Siqueira MMH, da Silva HLM, Rodrigues GC, Guerra AF, Rocha OC, Amábile RF, Albuquerque AC, Só e Silva M, Albrecht JC and Durães FOM (2006). Fenotipagem para tolerância à seca visando o melhoramento genético do trigo no cerrado. Circular Técnica Online Embrapa Trigo 21. In Portuguese. Available online.

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Sequencing multiple and diverse rice varieties: Connecting whole-genome variation with phenotypes 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.

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Gene expression microarrays and their application in drought stress research Gene expression microarrays and their application in drought stress research

Kathiresan A, Lafitte HR, Chen J, Mansueto L, Bruskiewich R, Bennett J (2006). Gene expression microarrays and their application in drought stress research.  Field Crops Research 97(1):101–110. (DOI: 10.1016/j.fcr.2005.08.021). Not open access: view abstract

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Genetic variation in the sensitivity of anther dehiscence to drought stress in rice 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

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The Generation Challenge Programme (GCP): Standards for crop data The Generation Challenge Programme (GCP): Standards for crop data

Bruskiewich R, Davenport G, Hazekamp T, Metz T, Ruiz M, Simon R, Takeya M, Lee J, Senger M, McLaren G, and van Hintum T (2006). The Generation Challenge Programme (GCP): Standards for crop data. OMICS: A Journal of Integrative Biology. 10(2):215–219.

The Generation Challenge Programme (GCP) is an international research consortium striving to apply molecular biological advances to crop improvement for developing countries. Central to its activities is the creation of a next generation global crop information platform and network to share genetic resources, genomics, and crop improvement information. This system is being designed based on a comprehensive scientific domain object model and associated shared ontology. This model covers germplasm, genotype, phenotype, functional genomics, and geographical information data types needed in GCP research. This paper provides an overview of this modelling effort.

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Microsatellite marker diversity in common bean (Phaseolus vulgaris L.) 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

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Laboratory Information Management Software for genotyping workflows: applications in high throughput crop genotyping 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.

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Relationship between carbon isotope discrimination, ash content and grain yield in wheat in the Peninsular Zone of India Relationship between carbon isotope discrimination, ash content and grain yield in wheat in the Peninsular Zone of India

Misra SC, Randive R, Rao VS, Sheshshayee MS, Serraj R and Monneveux P (2006). Relationship between carbon isotope discrimination, ash content and grain yield in wheat in the Peninsular Zone of India. Journal of Agronomy and Crop Science 192(5):352–362. (DOI: 10.1111/j.1439-037X.2006.00225.x). Not open access: view abstract

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