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

Area of Science:

• Agricultural Science
• Bioinformatics
• Molecular Biology

Background:

• Advances in DNA sequencing technologies necessitate efficient data management for high-throughput genotyping.
• Automated genotyping processes generate large volumes of data requiring robust tracking and quality control systems.
• Standardized protocols and data annotation are crucial for good laboratory practice in molecular genotyping.

Purpose of the Study:

• To design and implement a Laboratory Information Management System (LIMS) for a molecular genotyping facility.
• To address the need for a software system to manage high-throughput genotypic data and track samples.
• To standardize workflows and ensure accurate data capture in genotyping processes.

Main Methods:

• Development and implementation of a modular Laboratory Information Management System (LIMS).
• System designed to guide users through experimental steps, from initiation to data storage.
• Data entry facilitated through forms and file uploads, with auto-binning of alleles for genotype detection.

Main Results:

• A functional LIMS was implemented at ICRISAT for moderately high-throughput molecular genotyping.
• The system effectively tracks DNA samples and associated data, ensuring identical handling and comprehensive capture.
• LIMS enables tracing genotypic data back to electrophoresis files or sample sources and facilitates experiment repetition.

Conclusions:

• The developed LIMS is effective for managing microsatellite genotype data in high-throughput laboratories.
• The application promotes standardized protocols and accurate data management in molecular genotyping.
• The LIMS software, including source code, is freely available to academic users.