RNA-seq of eight different poplar clones reveals conserved up-regulation of gene expression in response to insect herbivory

Multi-omics analysis of Populus simonii × P. nigra leaves under Hyphantria cunea stress

Poplar is an important greening and timber tree species in China, which has great economic and ecological values. However, the spread of Hyphantria cunea has become increasingly serious in recent years, resulting in huge economic loss of poplar production. Exploring the molecular mechanism of poplar reponse to H. cunea stress has significant implications for future development of new insect-resistant poplar varieties using genetic engineering technology. In this study, a total of 1039 differentially expressed genes (DEGs), 106 differentially expressed proteins (DEPs) and 212 differentially expressed metabolites (DEMs) were screened from Populus simonii × P. nigra leaves under H. cunea stress by transcriptome, proteomics and metabolomics analysis, respectively. GO and KEGG analysis showed that the DEGs and DEPs are associated with endopeptidase inhibitor activity, stress response, α-linolenic acid metabolism, phenylpropanoid biosynthesis and metabolic pathways, cysteine and methionine metabolism pathways and MAKP signaling pathway. Metabolomics analysis showed the most of DEMs were lipids and lipid molecules, and the pathways associated with transcriptome mainly include plant hormone signal transduction, α-linolenic acid metabolic pathway, amino sugar and nucleotide sugar metabolism, and phenylpropanoid biosynthesis. In particular, multi-omics analysis showed that several pathways such as α-linolenic acid metabolic, phenylpropanoid biosynthesis and metabolic pathway and cysteine and methionine metabolic pathway were significantly enriched in the three omics, which may play an important role in the resistance to pests in poplar.

Transcriptome analysis reveals the potential mechanism of the response to scale insects in Camellia sasanqua Thunb

BACKGROUND

Camellia sasanqua Thunb. is an essential woody ornamental plant. Our continuous observation found that scale insects often infest C. sasanqua all year round in Kunming, China, resulting in poor growth. Scientifically preventing and controlling the infestation of scale insects should be paid attention to, and the mechanism of scale insects influencing C. sasanqua should be used as the research basis.

RESULTS

The scale insect was identified as Pseudaulacaspis sasakawai Takagi. We analyzed transcriptome sequencing data from leaves of C. sasanqua infested with scale insects. A total of 1320 genes were either up-regulated or down-regulated and differed significantly in response to scale insects. GO (Gene Ontology) annotation analysis showed that the pathway of catalytic activity, binding, membrane part, cell part, and cellular process were affected. KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis showed that most DEGs (differentially expressed genes) involved in plant hormone signal transduction, MAPK signaling pathway, flavonoid biosynthesis, tropane, piperidine and pyridine alkaloid biosynthesis. We also observed that the expression of galactose metabolism and carotenoid biosynthesis were significantly influenced. In addition, qRT-PCR (quantitative real-time PCR) validated the expression patterns of DEGs, which showed an excellent agreement with the transcriptome sequencing.

CONCLUSIONS

Our transcriptomic analysis revealed that the C. sasanqua had an intricate resistance strategy to cope with scale insect attacks. After sensing the attack signal of scale insects, C. sasanqua activated the early signal MAPK (mitogen-activated protein kinase) to activate further transcription factors and Auxin, ET, JA, ABA, and other plant hormone signaling pathways, ultimately leading to the accumulation of lignin, scopolin, flavonoids and other secondary metabolites, produces direct and indirect resistance to scale insects. Our results suggested that it provided some potential resources of defense genes that would benefit the following resistance breeding in C. sasanqua to scale insects.

Advanced Breeding for Biotic Stress Resistance in Poplar

Poplar is one of the most important forest trees because of its high economic value. Thanks to the fast-growing rate, easy vegetative propagation and transformation, and availability of genomic resources, poplar has been considered the model species for forest genetics, genomics, and breeding. Being a field-growing tree, poplar is exposed to environmental threats, including biotic stresses that are becoming more intense and diffused because of global warming. Current poplar farming is mainly based on monocultures of a few elite clones and the expensive and long-term conventional breeding programmes of perennial tree species cannot face current climate-change challenges. Consequently, new tools and methods are necessary to reduce the limits of traditional breeding related to the long generation time and to discover new sources of resistance. Recent advances in genomics, marker-assisted selection, genomic prediction, and genome editing offer powerful tools to efficiently exploit the Populus genetic diversity and allow enabling molecular breeding to support accurate early selection, increasing the efficiency, and reducing the time and costs of poplar breeding, that, in turn, will improve our capacity to face or prevent the emergence of new diseases or pests.

Genotype-Specific Expression and NLR Repertoire Contribute to Phenotypic Resistance Diversity in Plantago lanceolata

High levels of phenotypic variation in resistance appears to be nearly ubiquitous across natural host populations. Molecular processes contributing to this variation in nature are still poorly known, although theory predicts resistance to evolve at specific loci driven by pathogen-imposed selection. Nucleotide-binding leucine-rich repeat (NLR) genes play an important role in pathogen recognition, downstream defense responses and defense signaling. Identifying the natural variation in NLRs has the potential to increase our understanding of how NLR diversity is generated and maintained, and how to manage disease resistance. Here, we sequenced the transcriptomes of five different Plantago lanceolata genotypes when inoculated by the same strain of obligate fungal pathogen Podosphaera plantaginis. A de novo transcriptome assembly of RNA-sequencing data yielded 24,332 gene models with N50 value of 1,329 base pairs and gene space completeness of 66.5%. The gene expression data showed highly varying responses where each plant genotype demonstrated a unique expression profile in response to the pathogen, regardless of the resistance phenotype. Analysis on the conserved NB-ARC domain demonstrated a diverse NLR repertoire in P. lanceolata consistent with the high phenotypic resistance diversity in this species. We find evidence of selection generating diversity at some of the NLR loci. Jointly, our results demonstrate that phenotypic resistance diversity results from a crosstalk between different defense mechanisms. In conclusion, characterizing the architecture of resistance in natural host populations may shed unprecedented light on the potential of evolution to generate variation.