Erwinia mallotivora, the causal agent of papaya dieback disease, is a devastating pathogen that has caused a tremendous decrease in Malaysian papaya export and affected papaya crops in neighbouring countries. A few studies on bacterial species capable of suppressing E. mallotivora have been reported, but the availability of antagonistic fungi remains unknown. In this study, mycelial suspensions from five rhizospheric Trichoderma isolates of Malaysian origin were found to exhibit notable antagonisms against E. mallotivora during co-cultivation. We further characterised three isolates, Trichoderma koningiopsis UKM-M-UW RA5, UKM-M-UW RA6, and UKM-M-UW RA3a, that showed significant growth inhibition zones on plate-based inhibition assays. A study of the genomes of the three strains through a combination of Oxford nanopore and Illumina sequencing technologies highlighted potential secondary metabolite pathways that might underpin their antimicrobial properties. Based on these findings, the fungal isolates are proven to be useful as potential biological control agents against E. mallotivora, and the genomic data opens possibilities to further explore the underlying molecular mechanisms behind their antimicrobial activity, with potential synthetic biology applications.
Transcriptomics has significantly grown as a functional genomics tool for understanding the expression of biological systems. The generated transcriptomics data can be utilised to produce a gene co-expression network that is one of the essential downstream omics data analyses. To date, several gene co-expression network databases that store correlation values, expression profiles, gene names and gene descriptions have been developed. Although these resources remain scattered across the Internet, such databases complement each other and support efficient growth in the functional genomics area. This review presents the features and the most recent gene co-expression network databases in crops and summarises the present status of the tools that are widely used for constructing the gene co-expression network. The highlights of gene co-expression network databases and the tools presented here will pave the way for a robust interpretation of biologically relevant information. With this effort, the researcher would be able to explore and utilise gene co-expression network databases for crops improvement.
The genus Nepenthes (Nepenthaceae) in Peninsular Malaysia includes fourteen species that can be found from the sea-level to over 1000 m in the mountains. Our observation indicated that Nepenthes can be found in five major habitat types: specifically in tropical lowland evergreen rain forest, heath forest, peat swamp forest, montane forest, and limestone forest. Their leaves have several anatomical characters that remain underexplored. There were specific differences between species that could be potential identification characters. The following anatomical characteristics were explored for their diagnostic value and comprised of ten distinct anatomical characteristics in Nepenthes, viz., density and stomatal index (SI), hypodermis cell – cell layers, occurrence of fiber groups mixed with the hypodermis cells, adaxial cuticle thickness, vascular bundle arrangement, midrib outline shape, venation plasticity, druses appearance and appendage/trichome type.
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