Agrigenomics
Codon Genomics is actively involved in the commercial and collaborative research on the genomics of agricultural crops, such as oil palm, rubber, cocoa and rice. We offer and apply latest technology to assist in agrigenomics research and crop improvement projects, such as:
What we do
Assembly and annotation of plant genomes and transcriptomes using the latest cutting-edge technology provide a rich reservoir to discover novel genes for many downstream applications, such as identification of oil-yield controlling SHELL gene in oil palm for accurate genotyping and selection of palms with desired fruit form with a higher oil yield before planting.
Direct high-throughput genetic analysis of massive microbial genomes present in an plant-environmental sample, bypassing the resources-intensive isolation and subculture of individual microbes, and problem of high percentage of unculturable microbes.
With this technology, disease-suppressive bacteria beneficial to agricultural plants can be identified, such as members of the Pseudomonadaceae capable in the suppression of fungal infection in host plants such as rice, potato and sugar beet.
In addition, viral and pathogen metagenomics can act as diagnostic tools in plant virology, allowing quick detection of plant disease without prior knowledge of the host or pathogen and enabling preventive measures to be taken.
Dual-RNA Sequencing: deciphering the molecular interactions between agricultural plants and microbes
Simultaneous capture of both plant and pathogen transcriptomes during the infection stage, and uses in silico analysis to distinguish species-specific transcripts
The information on molecular interactions between host and pathogen enables the identification of defence pathways and disease-related genes in plants, enabling future genetic engineering, molecular breeding and selection of high-disease resistant plants.
Genotyping By Sequencing (GBS) enables plant researcher to discover SNPs for genotyping studies such as GWAS.
Genome-Wide Association Studies (GWAS) enables plant researchers to identify and map QTL underlying commercially important quantitative traits, such cocoa butter content in cocoa and yield traits in rice.
Genomic Selection (GS) enables plant breeders to predict complex, polygenic agronomy traits (or breeding values) in a breeding population by a statistical model constructed from entire genome marker data
Our achievements
Ithnin, M., Xu, Y., Marjuni, M., Serdari, N.M., Amiruddin, M.D., Low, E.T.L., Tan, Y.C., Yap, S.J., Ooi, L.C.L., Nookiah, R. and Singh, R., 2017. Multiple locus genome-wide association studies for important economic traits of oil palm. Tree Genetics & Genomes, 13(5), p.103.
Ho, C.L., Tan, Y.C., Yeoh, K.A., Ghazali, A.K., Yee, W.Y. and Hoh, C.C., 2016. De novo transcriptome analyses of host-fungal interactions in oil palm (Elaeis guineensis Jacq.). BMC genomics, 17(1), p.66.
Ho, C.L. and Yee, W.Y. 2017. RNA-seq analysis in plant-fungus interactions. In Crop Improvement (pp. 1-25). Springer, Cham.
Chow, K.S., Ghazali, A.K., Hoh, C.C. and Mohd-Zainuddin, Z., 2014. RNA sequencing read depth requirement for optimal transcriptome coverage in Hevea brasiliensis. BMC research notes, 7(1), p.69.