Exploring gene regulation and biological processes in insects: Insights from omics data using gene regulatory network models.

Gene regulatory network (GRN) comprises complicated yet intertwined gene-regulator relationships. Understanding the GRN dynamics will unravel the complexity behind the observed gene expressions. Insect gene regulation is often complicated due to their complex life cycles and diverse ecological adaptations. The main interest of this review is to have an update on the current mathematical modelling methods of GRNs to explain insect science. Several popular GRN architecture models are discussed, together with examples of applications in insect science. In the last part of this review, each model is compared from different aspects, including network scalability, computation complexity, robustness to noise and biological relevancy.

Gene Co-Expression Network Analysis Reveals Key Regulatory Genes in Metisa plana Hormone Pathways.

Metisa plana Walker (Lepidoptera: Psychidae) is a major oil palm pest species distributed across Southeast Asia. M. plana outbreaks are regarded as serious ongoing threats to the oil palm industry due to their ability to significantly reduce fruit yield and subsequent productivity. Currently, conventional pesticide overuses may harm non-target organisms and severely pollute the environment. This study aims to identify key regulatory genes involved in hormone pathways during the third instar larvae stage of M. plana gene co-expression network analysis. A weighted gene co-expression network analysis (WGCNA) was conducted on the M. plana transcriptomes to construct a gene co-expression network. The transcriptome datasets were obtained from different development stages of M. plana, i.e., egg, third instar larvae, pupa, and adult. The network was clustered using the DPClusO algorithm and validated using Fisher's exact test and receiver operating characteristic (ROC) analysis. The clustering analysis was performed on the network and 20 potential regulatory genes (such as MTA1-like, Nub, Grn, and Usp) were identified from ten top-most significant clusters. Pathway enrichment analysis was performed to identify hormone signalling pathways and these pathways were identified, i.e., hormone-mediated signalling, steroid hormone-mediated signalling, and intracellular steroid hormone receptor signalling as well as six regulatory genes Hnf4, Hr4, MED14, Usp, Tai, and Trr. These key regulatory genes have a potential as important targets in future upstream applications and validation studies in the development of biorational pesticides against M. plana and the RNA interference (RNAi) gene silencing method.

Escherichia coli strain INF32/16/A: Dataset of raw reads and assembled draft genome.

Escherichia coli strain INF32/16/A is a gram-negative bacteria which is an extended-spectrum beta-lactamases (ESBL). ESBL is an enzyme that is produced by bacteria to become resistant to existing antibiotic such as extended-spectrum penicillin, cephalosporins, and have been threatening the ability to treat an infection. Therefore, genome analysis will provide an insight of how this bacteria able to evolve and the information obtained will able to facilitate in designing new antibiotics. The genome of E. coli strain was sequenced using Illumina MiSeq and raw genome sequence have been submitted into NCBI SRA database (SRR15334628) under Bioproject accession number PRJNA726861.

Draft genome assembly dataset of the Basidiomycete pathogenic fungus, Ganoderma boninense.

Ganoderma boninense is a soil-borne Basidiomycete pathogenic fungus that eminent as the key causal of devastating disease in oil palm, named basal stem rot. Being a threat to sustainable palm oil production, it is essential to comprehend the fundamental view of this fungus. However, there is gap of information due to its limited number of genome sequence that is available for this pathogenic fungus. This implies the hitches in performing biological research to unravel the mechanism underlying the pathogen attack in oil palm. Therefore, here we report a dataset of draft genome of G. boninense that was sequenced using Illumina Hiseq 2000. The raw reads were deposited into NCBI database (SRX7136614 and SRX7136615) and can be accessed via Bioproject accession number PRJNA503786.

Transcriptomic data of mature oil palm basal trunk tissue infected with Ganoderma boninense.

To date, Ganoderma boninense is known to be the causal agent of basal stem rot (BSR) disease in oil palm (Elaeis guineensis). This disease causes rotting in the roots, basal and upper stem of oil palm. Infection causes progressive destruction of the basal tissues at the oil palm trunk and internal dry rotting, particularly at the intersection between the bole and trunk. Molecular responses of oil palm during infection are not well study although this information is crucial to strategize effective measures to control or eliminate BSR. Here we report three sets of transcriptome data from samples of near-rot section of basal stem tissue of oil palm tree infected with G. boninense (IPIT), healthy section of basal stem tissue of the same G. boninense infected palm (IPHT) and the healthy section of basal stem tissue of the healthy palm (HPHT). The raw reads were deposited into NCBI database and can be accessed via BioProject accession number PRJNA530030.

The Glaciozyma antarctica genome reveals an array of systems that provide sustained responses towards temperature variations in a persistently cold habitat.

Extremely low temperatures present various challenges to life that include ice formation and effects on metabolic capacity. Psyhcrophilic microorganisms typically have an array of mechanisms to enable survival in cold temperatures. In this study, we sequenced and analysed the genome of a psychrophilic yeast isolated in the Antarctic region, Glaciozyma antarctica. The genome annotation identified 7857 protein coding sequences. From the genome sequence analysis we were able to identify genes that encoded for proteins known to be associated with cold survival, in addition to annotating genes that are unique to G. antarctica. For genes that are known to be involved in cold adaptation such as anti-freeze proteins (AFPs), our gene expression analysis revealed that they were differentially transcribed over time and in response to different temperatures. This indicated the presence of an array of adaptation systems that can respond to a changing but persistent cold environment. We were also able to validate the activity of all the AFPs annotated where the recombinant AFPs demonstrated anti-freeze capacity. This work is an important foundation for further collective exploration into psychrophilic microbiology where among other potential, the genes unique to this species may represent a pool of novel mechanisms for cold survival.

Identification of sRNA mediated responses to nutrient depletion in Burkholderia pseudomallei.

The Burkholderia genus includes many species that are known to survive in diverse environmental conditions including low nutrient environments. One species, Burkholderia pseudomallei is a versatile pathogen that can survive in a wide range of hosts and environmental conditions. In this study, we investigated how a nutrient depleted growth environment evokes sRNA mediated responses by B. pseudomallei. Computationally predicted B. pseudomallei D286 sRNAs were mapped to RNA-sequencing data for cultures grown under two conditions: (1) BHIB as a nutrient rich media reference environment and (2) M9 media as a nutrient depleted stress environment. The sRNAs were further selected to identify potentially cis-encoded systems by investigating their possible interactions with their flanking genes. The mappings of predicted sRNA genes and interactions analysis to their flanking genes identified 12 sRNA candidates that may possibly have cis-acting regulatory roles that are associated to a nutrient depleted growth environment. Our approach can be used for identifying novel sRNA genes and their possible role as cis-mediated regulatory systems.