Computer aided data acquisition tool for high-throughput phenotyping of plant populations

BackgroundThe data generated during a course of a biological experiment/study can be sometimes be massive and its management becomes quite critical for the success of the investigation undertaken. The accumulation and analysis of such large datasets often becomes tedious for biologists and lab technicians. Most of the current phenotype data acquisition management systems do not cater to the specialized needs of large-scale data analysis. The successful application of genomic tools/strategies to introduce desired traits in plants requires extensive and precise phenotyping of plant populations or gene bank material, thus necessitating an efficient data acquisition system.ResultsHere we describe newly developed software "PHENOME" for high-throughput phenotyping, which allows researchers to accumulate, categorize, and manage large volume of phenotypic data. In this study, a large number of individual tomato plants were phenotyped with the "PHENOME" application using a Personal Digital Assistant (PDA) with built-in barcode scanner in concert with customized database specific for handling large populations.ConclusionThe phenotyping of large population of plants both in the laboratory and in the field is very efficiently managed using PDA. The data is transferred to a specialized database(s) where it can be further analyzed and catalogued. The "PHENOME" aids collection and analysis of data obtained in large-scale mutagenesis, assessing quantitative trait loci (QTLs), raising mapping population, sampling of several individuals in one or more ecological niches etc.

[1]  Robert Rieger,et al.  Using mobile computing to enhance field study , 1997, CSCL.

[2]  Leakha Henry,et al.  RGMIMS: a web-based Laboratory Information Management System for plant functional genomics research , 2008, Molecular Breeding.

[3]  Rogers Hall,et al.  Proceedings of CSCL '97 : The Second International Conference on Computer Support for Collaborative Learning, December 10-14, 1997, University of Toronto, Toronto, Ontario, Canada , 1997 .

[4]  Y. Lussier,et al.  Computational approaches to phenotyping: high-throughput phenomics. , 2007, Proceedings of the American Thoracic Society.

[5]  Wilhelm Gruissem,et al.  PlantDB – a versatile database for managing plant research , 2008, Plant Methods.

[6]  S. Henikoff,et al.  Targeting induced local lesions IN genomes (TILLING) for plant functional genomics. , 2000, Plant physiology.

[7]  Yong-Hwan Lee,et al.  'PACLIMS': A component LIM system for high-throughput functional genomic analysis , 2005, BMC Bioinformatics.

[8]  D. Bouchez,et al.  Arabidopsis gene knockout: phenotypes wanted. , 2001, Current opinion in plant biology.

[9]  Steven Henikoff,et al.  Targeted screening for induced mutations , 2000, Nature Biotechnology.

[10]  Joachim Selbig,et al.  A plant resource and experiment management system based on the Golm Plant Database as a basic tool for omics research , 2008, Plant Methods.

[11]  Naama Menda,et al.  In silico screening of a saturated mutation library of tomato. , 2004, The Plant journal : for cell and molecular biology.

[12]  M. Kumagai,et al.  Development of Electronic Barcodes for use in Plant Pathology and Functional Genomics , 2006, Plant Molecular Biology.