Journal articles 2006
Documents
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
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
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
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
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
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.
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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
Identification of quantitative trait loci for resistance to Southern Leaf Blight and days to anthesis in a maize recombinant inbred line population
Balint-Kurti PJ, Krakowsky MD, Jines MP, Robertson LA, Molnár TL, Goodman MM and Holland JB (2006). Identification of quantitative trait loci for resistance to Southern Leaf Blight and days to anthesis in a maize recombinant inbred line population. Phytopathology 96:1067–1071. (DOI: 10.1094/PHYTO-96-1067).
A recombinant inbred line population derived from a cross between the maize lines NC300 (resistant) and B104 (susceptible) was evaluated for resistance to southern leaf blight (SLB) disease caused by Cochliobolus heterostrophus race O and for days to anthesis in four environments (Clayton, NC, and Tifton, GA, in both 2004 and 2005). Entry mean and average genetic correlations between disease ratings in different environments were high (0.78 to 0.89 and 0.9, respectively) and the overall entry mean heritability for SLB resistance was 0.89. When weighted mean disease ratings were fitted to a model using multiple interval mapping, seven potential quantitative trait loci (QTL) were identified, the two strongest being on chromosomes 3 (bin 3.04) and 9 (bin 9.03-9.04). These QTL explained a combined 80% of the phenotypic variation for SLB resistance. Some time-point-specific SLB resistance QTL were also identified. There was no significant correlation between disease resistance and days to anthesis. Six putative QTL for time to anthesis were identified, none of which coincided with any SLB resistance QTL.
Balint-Kurti PJ, Krakowsky MD, Jines MP, Robertson LA, Molnár TL, Goodman MM and Holland JB (2006). Identification of quantitative trait loci for resistance to Southern Leaf Blight and days to anthesis in a maize recombinant inbred line population. Phytopathology 96:1067–1071. (DOI: 10.1094/PHYTO-96-1067).
A recombinant inbred line population derived from a cross between the maize lines NC300 (resistant) and B104 (susceptible) was evaluated for resistance to southern leaf blight (SLB) disease caused by Cochliobolus heterostrophus race O and for days to anthesis in four environments (Clayton, NC, and Tifton, GA, in both 2004 and 2005). Entry mean and average genetic correlations between disease ratings in different environments were high (0.78 to 0.89 and 0.9, respectively) and the overall entry mean heritability for SLB resistance was 0.89. When weighted mean disease ratings were fitted to a model using multiple interval mapping, seven potential quantitative trait loci (QTL) were identified, the two strongest being on chromosomes 3 (bin 3.04) and 9 (bin 9.03-9.04). These QTL explained a combined 80% of the phenotypic variation for SLB resistance. Some time-point-specific SLB resistance QTL were also identified. There was no significant correlation between disease resistance and days to anthesis. Six putative QTL for time to anthesis were identified, none of which coincided with any SLB resistance QTL.
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
Genetic diversity in salt tolerant rice (O. sativa)
Islam MR, Faruquei MAB and Salam MA (2006). Genetic diversity in salt tolerant rice (O. sativa). Bangladesh Journal of Plant Breeding Genetics 19(1):35–40. (Articles before 2007 were not archived for this journal; photocopied version of article in PDF).
Genetic diversity of 36 genotypes of salt tolerant coastal rice collected from IRRI (Philippines), BRRI (bangladesh), China and Sri Lanka were studied through Mahalanobis D2 statistics to identify the most genetically distant parental genotypes for improving salt tolerant rice varieties.The genotypes were grouped into five clusters. The cluster II and cluster V contained the highest and the lowest number of genotypes, respectively. The highest intra-cluster distance was noticed for the cluster I and the lowest for the cluster V.
Islam MR, Faruquei MAB and Salam MA (2006). Genetic diversity in salt tolerant rice (O. sativa). Bangladesh Journal of Plant Breeding Genetics 19(1):35–40. (Articles before 2007 were not archived for this journal; photocopied version of article in PDF).
Genetic diversity of 36 genotypes of salt tolerant coastal rice collected from IRRI (Philippines), BRRI (bangladesh), China and Sri Lanka were studied through Mahalanobis D2 statistics to identify the most genetically distant parental genotypes for improving salt tolerant rice varieties.The genotypes were grouped into five clusters. The cluster II and cluster V contained the highest and the lowest number of genotypes, respectively. The highest intra-cluster distance was noticed for the cluster I and the lowest for the cluster V.
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
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
