Gene co-expression network analysis identifies molecular regulators for improving stress tolerance traits in papaya and rice

R-A. ZAINAL-ABIDIN, M. M. SAAD, N. A. BAKAR, S. Y. SHIN, M.S.F.A. RAZAK, M.A. HASSAN

Biotechnology & Nanotechnology Research Centre, Malaysian Agricultural Research and Development Institute (MARDI), 43400 Serdang, Malaysia

Horticulture Research Centre, MARDI, 43400 Serdang, Malaysia

Discovering molecular mechanisms that govern traits that boost crop productivity under environmental stress, including pathogen attack is an urgent need. Gene co-expression network (GCN) analysis has been widely used to reveal hub genes and key pathways from gene expression datasets. To understand the molecular mechanism of disease progression in papaya dieback disease (PDD) and prioritise hub genes for increasing antioxidant content in pigmented rice, we performed GCN analysis from RNA-seq datasets. A modified Markov Cluster (MCL) algorithm was used to identify co-expression modules and hub genes within these modules in the rice and papaya. The papaya GCN consisted of 53 modules that defined the papaya-pathogen (Erwinia mallotivora) interaction network. The modules revealed not only classical disease resistance-related pathways, such as pattern recognition receptors (PRR) and pathogenesis-related (PR) genes but also new molecular regulators that could be prioritised for further validation and papaya breeding programme. The pigmented rice GCN identified three established functional modules related to flavonoid and terpenoid biosynthesis as well as transcriptional regulators that modulate these pathways in the rice seed. The rice and papaya breeding programmes in Malaysia will use the information generated here as a foundation for marker-assisted breeding or gene editing, for improving crop productivity.