A De Novo-Assembly Based Data Analysis Pipeline for Plant Obligate Parasite Metatranscriptomic Studies

Advancement of Metatranscriptomics towards Productive Agriculture and Sustainable Environment: A Review

While chemical fertilisers and pesticides indeed enhance agricultural productivity, their excessive usage has been detrimental to environmental health. In addressing this matter, the use of environmental microbiomes has been greatly favoured as a ‘greener’ alternative to these inorganic chemicals’ application. Challenged by a significant proportion of unidentified microbiomes with unknown ecological functions, advanced high throughput metatranscriptomics is prudent to overcome the technological limitations in unfolding the previously undiscovered functional profiles of the beneficial microbiomes. Under this context, this review begins by summarising (1) the evolution of next-generation sequencing and metatranscriptomics in leveraging the microbiome transcriptome profiles through whole gene expression profiling. Next, the current environmental metatranscriptomics studies are reviewed, with the discussion centred on (2) the emerging application of the beneficial microbiomes in developing fertile soils and (3) the development of disease-suppressive soils as greener alternatives against biotic stress. As sustainable agriculture focuses not only on crop productivity but also long-term environmental sustainability, the second half of the review highlights the metatranscriptomics’ contribution in (4) revolutionising the pollution monitoring systems via specific bioindicators. Overall, growing knowledge on the complex microbiome functional profiles is imperative to unlock the unlimited potential of agricultural microbiome-based practices, which we believe hold the key to productive agriculture and sustainable environment.

Genome Sequencing and Transcriptome Analysis of the Hop Downy Mildew Pathogen Pseudoperonospora humuli Reveal Species-Specific Genes for Molecular Detection

Pseudoperonospora humuli is an obligate oomycete pathogen of hop (Humulus lupulus) that causes downy mildew, an important disease in most production regions in the Northern Hemisphere. The pathogen can cause a systemic infection in hop, overwinter in the root system, and infect propagation material. Substantial yield loss may occur owing to P. humuli infection of strobiles (seed cones), shoots, and cone-bearing branches. Fungicide application and cultural practices are the primary methods to manage hop downy mildew. However, effective, sustainable, and cost-effective management of downy mildew can be improved by developing early detection systems to inform on disease risk and timely fungicide application. However, no species-specific diagnostic assays or genomic resources are available for P. humuli. The genome of the P. humuli OR502AA isolate was partially sequenced using Illumina technology and assembled with ABySS. The assembly had a minimum scaffold length of 500 bp and an N50 (median scaffold length of the assembled genome) of 19.2 kbp. A total number of 18,656 genes were identified using MAKER standard gene predictions. Additionally, transcriptome assemblies were generated using RNA-seq and Trinity for seven additional P. humuli isolates. Bioinformatics analyses of next generation sequencing reads of P. humuli and P. cubensis (a closely related sister species) identified 242 candidate species-specific P. humuli genes that could be used as diagnostic molecular markers. These candidate genes were validated using polymerase chain reaction against a diverse collection of isolates from P. humuli, P. cubensis, and other oomycetes. Overall, four diagnostic markers were found to be uniquely present in P. humuli. These candidate markers identified through comparative genomics can be used for pathogen diagnostics in propagation material, such as rhizomes and vegetative cuttings, or adapted for biosurveillance of airborne sporangia, an important source of inoculum in hop downy mildew epidemics.

Population structure, genetic diversity and downy mildew resistance among Ocimum species germplasm

BACKGROUND

The basil (Ocimum spp.) genus maintains a rich diversity of phenotypes and aromatic volatiles through natural and artificial outcrossing. Characterization of population structure and genetic diversity among a representative sample of this genus is severely lacking. Absence of such information has slowed breeding efforts and the development of sweet basil (Ocimum basilicum L.) with resistance to the worldwide downy mildew epidemic, caused by the obligate oomycete Peronospora belbahrii. In an effort to improve classification of relationships 20 EST-SSR markers with species-level transferability were developed and used to resolve relationships among a diverse panel of 180 Ocimum spp. accessions with varying response to downy mildew.

RESULTS

Results obtained from nested Bayesian model-based clustering, analysis of molecular variance and unweighted pair group method using arithmetic average (UPGMA) analyses were synergized to provide an updated phylogeny of the Ocimum genus. Three (major) and seven (sub) population (cluster) models were identified and well-supported (P < 0.001) by PhiPT (Φ_PT) values of 0.433 and 0.344, respectively. Allelic frequency among clusters supported previously developed hypotheses of allopolyploid genome structure. Evidence of cryptic population structure was demonstrated for the k1 O. basilicum cluster suggesting prevalence of gene flow. UPGMA analysis provided best resolution for the 36-accession, DM resistant k3 cluster with consistently strong bootstrap support. Although the k3 cluster is a rich source of DM resistance introgression of resistance into the commercially important k1 accessions is impeded by reproductive barriers as demonstrated by multiple sterile F1 hybrids. The k2 cluster located between k1 and k3, represents a source of transferrable tolerance evidenced by fertile backcross progeny. The 90-accession k1 cluster was largely susceptible to downy mildew with accession 'MRI' representing the only source of DM resistance.

CONCLUSIONS

High levels of genetic diversity support the observed phenotypic diversity among Ocimum spp. accessions. EST-SSRs provided a robust evaluation of molecular diversity and can be used for additional studies to increase resolution of genetic relationships in the Ocimum genus. Elucidation of population structure and genetic relationships among Ocimum spp. germplasm provide the foundation for improved DM resistance breeding strategies and more rapid response to future disease outbreaks.

Characterization of viral RNA splicing using whole-transcriptome datasets from host species

RNA alternative splicing (AS) is an important post-transcriptional mechanism enabling single genes to produce multiple proteins. It has been well demonstrated that viruses deploy host AS machinery for viral protein productions. However, knowledge on viral AS is limited to a few disease-causing viruses in model species. Here we report a novel approach to characterizing viral AS using whole transcriptome dataset from host species. Two insect transcriptomes (Acheta domesticus and Planococcus citri) generated in the 1,000 Insect Transcriptome Evolution (1KITE) project were used as a proof of concept using the new pipeline. Two closely related densoviruses (Acheta domesticus densovirus, AdDNV, and Planococcus citri densovirus, PcDNV, Ambidensovirus, Densovirinae, Parvoviridae) were detected and analyzed for AS patterns. The results suggested that although the two viruses shared major AS features, dramatic AS divergences were observed. Detailed analysis of the splicing junctions showed clusters of AS events occurred in two regions of the virus genome, demonstrating that transcriptome analysis could gain valuable insights into viral splicing. When applied to large-scale transcriptomics projects with diverse taxonomic sampling, our new method is expected to rapidly expand our knowledge on RNA splicing mechanisms for a wide range of viruses.

A first linkage map and downy mildew resistance QTL discovery for sweet basil (Ocimum basilicum) facilitated by double digestion restriction site associated DNA sequencing (ddRADseq)

Limited understanding of sweet basil (Ocimum basilicum L.) genetics and genome structure has reduced efficiency of breeding strategies. This is evidenced by the rapid, worldwide dissemination of basil downy mildew (Peronospora belbahrii) in the absence of resistant cultivars. In an effort to improve available genetic resources, expressed sequence tag simple sequence repeat (EST-SSR) and single nucleotide polymorphism (SNP) markers were developed and used to genotype the MRI x SB22 F2 mapping population, which segregates for response to downy mildew. SNP markers were generated from genomic sequences derived from double digestion restriction site associated DNA sequencing (ddRADseq). Disomic segregation was observed in both SNP and EST-SSR markers providing evidence of an O. basilicum allotetraploid genome structure and allowing for subsequent analysis of the mapping population as a diploid intercross. A dense linkage map was constructed using 42 EST-SSR and 1,847 SNP markers spanning 3,030.9 cM. Multiple quantitative trait loci (QTL) model (MQM) analysis identified three QTL that explained 37-55% of phenotypic variance associated with downy mildew response across three environments. A single major QTL, dm11.1 explained 21-28% of phenotypic variance and demonstrated dominant gene action. Two minor QTL dm9.1 and dm14.1 explained 5-16% and 4-18% of phenotypic variance, respectively. Evidence is provided for an additive effect between the two minor QTL and the major QTL dm11.1 increasing downy mildew susceptibility. Results indicate that ddRADseq-facilitated SNP and SSR marker genotyping is an effective approach for mapping the sweet basil genome.