Universal gene co-expression network reveals receptor-like protein genes involved in broad-spectrum resistance in pepper (Capsicum annuum L.)

Beyond NGS data sharing for plant ecological resilience and improvement of agronomic traits

Decoding complex plant omics is essential for advancing our understanding of plant biology, evolution, and breeding as well as for practical applications in agriculture, conservation, and biotechnology. The advent of Next-Generation Sequencing (NGS) has revolutionized global plant genomic research, offering high-throughput, cost-effective, and accurate methods for generating genomic data. However, challenges still exist that suggest an entirely unresolved genome characterized by high heterozygosity, extensive repetitive sequences, and complex ploidy features. In addition, individual investigation of genomic information from various genetic resources is essential for omics research, as there are differences in traits within a single breed beyond a species due to the uniqueness of sequence variation. This article provides high-quality genomic and transcriptomic insights targeted at the agronomical background.

The landscape of abiotic and biotic stress-responsive splice variants with deep RNA-seq datasets in hot pepper

Alternative splicing (AS) is a widely observed phenomenon in eukaryotes that plays a critical role in development and stress responses. In plants, the large number of RNA-seq datasets in response to different environmental stressors can provide clues for identification of condition-specific and/or common AS variants for preferred agronomic traits. We report RNA-seq datasets (350.7 Gb) from Capsicum annuum inoculated with one of three bacteria, one virus, or one oomycete and obtained additional existing transcriptome datasets. In this study, we investigated the landscape of AS in response to environmental stressors, signaling molecules, and tissues from 425 total samples comprising 841.49 Gb. In addition, we identified genes that undergo AS under specific and shared stress conditions to obtain potential genes that may be involved in enhancing tolerance to stressors. We uncovered 1,642,007 AS events and identified 4,354 differential alternative splicing genes related to environmental stressors, tissues, and signaling molecules. This information and approach provide useful data for basic-research focused on enhancing tolerance to environmental stressors in hot pepper or establishing breeding programs.

Global co-expression network for key factor selection on environmental stress RNA-seq dataset in Capsicum annuum

Environmental stresses significantly affect plant growth, development, and productivity. Therefore, a deeper understanding of the underlying stress responses at the molecular level is needed. In this study, to identify critical genetic factors associated with environmental stress responses, the entire 737.3 Gb clean RNA-seq dataset across abiotic, biotic stress, and phytohormone conditions in Capsicum annuum was used to perform individual differentially expressed gene analysis and to construct gene co-expression networks for each stress condition. Subsequently, gene networks were reconstructed around transcription factors to identify critical factors involved in the stress responses, including the NLR gene family, previously implicated in resistance. The abiotic and biotic stress networks comprise 233 and 597 hubs respectively, with 10 and 89 NLRs. Each gene within the NLR groups in the network exhibited substantial expression to particular stresses. The integrated analysis strategy of the transcriptome network revealed potential key genes for complex environmental conditions. Together, this could provide important clues to uncover novel key factors using high-throughput transcriptome data in other species as well as plants.

Weighted gene co-expression network analysis of nitrogen (N)-responsive genes and the putative role of G-quadruplexes in N use efficiency (NUE) in rice

Rice is an important target to improve crop nitrogen (N) use efficiency (NUE), and the identification and shortlisting of the candidate genes are still in progress. We analyzed data from 16 published N-responsive transcriptomes/microarrays to identify, eight datasets that contained the maximum number of 3020 common genes, referred to as N-responsive genes. These include different classes of transcription factors, transporters, miRNA targets, kinases and events of post-translational modifications. A Weighted gene co-expression network analysis (WGCNA) with all the 3020 N-responsive genes revealed 15 co-expression modules and their annotated biological roles. Protein-protein interaction network analysis of the main module revealed the hub genes and their functional annotation revealed their involvement in the ubiquitin process. Further, the occurrences of G-quadruplex sequences were examined, which are known to play important roles in epigenetic regulation but are hitherto unknown in N-response/NUE. Out of the 3020 N-responsive genes studied, 2298 contained G-quadruplex sequences. We compared these N-responsive genes containing G-quadruplex sequences with the 3601 genes we previously identified as NUE-related (for being both N-responsive and yield-associated). This analysis revealed 389 (17%) NUE-related genes containing G-quadruplex sequences. These genes may be involved in the epigenetic regulation of NUE, while the rest of the 83% (1811) genes may regulate NUE through genetic mechanisms and/or other epigenetic means besides G-quadruplexes. A few potentially important genes/processes identified as associated with NUE were experimentally validated in a pair of rice genotypes contrasting for NUE. The results from the WGCNA and G4 sequence analysis of N-responsive genes helped identify and shortlist six genes as candidates to improve NUE. Further, the hitherto unavailable segregation of genetic and epigenetic gene targets could aid in informed interventions through genetic and epigenetic means of crop improvement.

Transcriptomic alterations in the sweet orange vasculature correlate with growth repression induced by a variant of citrus tristeza virus

Citrus tristeza virus (CTV, family Closteroviridae) is an economically important pathogen of citrus. CTV resides in the phloem of the infected plants and induces a range of disease phenotypes, including stem pitting and quick decline as well as a number of other deleterious syndromes. To uncover the biological processes underlying the poorly understood damaging symptoms of CTV, we profiled the transcriptome of sweet orange (Citrus sinensis) phloem-rich bark tissues of non-infected, mock-inoculated trees and trees singly infected with two distinct variants of CTV, T36 or T68-1. The T36 and T68-1 variants accumulated in the infected plants at similar titers. With that, young trees infected with T68-1 were markedly repressed in growth, while the growth rate of the trees infected with T36 was comparable to the mock-inoculated trees. Only a small number of differentially expressed genes (DEGs) were identified in the nearly asymptomatic T36-infected trees, whereas almost fourfold the number of DEGs were identified with the growth-restricting T68-1 infection. DEGs were validated using quantitative reverse transcription-PCR. While T36 did not induce many noteworthy changes, T68-1 altered the expression of numerous host mRNAs encoding proteins within significant biological pathways, including immunity and stress response proteins, papain-like cysteine proteases (PLCPs), cell-wall modifying enzymes, vascular development proteins and others. The transcriptomic alterations in the T68-1-infected trees, in particular, the strong and persistent increase in the expression levels of PLCPs, appear to contribute to the observed stem growth repression. On the other hand, analysis of the viral small interfering RNAs revealed that the host RNA silencing-based response to the infection by T36 and that by T68-1 was comparable, and thus, the induction of this antiviral mechanism may not contribute to the difference in the observed symptoms. The DEGs identified in this study promote our understanding of the underlying mechanisms of the yet unexplained growth repression induced by severe CTV isolates in sweet orange trees.

Evolutionary and functional analysis reveals the crucial roles of receptor-like proteins in resistance to Valsa canker in Rosaceae

Rosaceae is an economically important plant family that can be affected by a multitude of pathogenic microbes, some of which can cause dramatic losses in production. As a type of pattern-recognition receptor, receptor-like proteins (RLPs) are considered vital regulators of plant immunity. Based on genome-wide identification, bioinformatic analysis, and functional determination, we investigated the evolutionary characteristics of RLPs, and specifically those that regulate Valsa canker, a devastating fungal disease affecting apple and pear production. A total of 3028 RLPs from the genomes of 19 species, including nine Rosaceae, were divided into 24 subfamilies. Five subfamilies and seven co-expression modules were found to be involved in the responses to Valsa canker signals of the resistant pear rootstock Pyrus betulifolia 'Duli-G03'. Fourteen RLPs were subsequently screened as candidate genes for regulation of resistance. Among these, PbeRP23 (Chr13.g24394) and PbeRP27 (Chr16.g31400) were identified as key resistance genes that rapidly enhance the resistance of 'Duli-G03' and strongly initiate immune responses, and hence they have potential for further functional exploration and breeding applications for resistance to Valsa canker. In addition, as a consequence of this work we have established optimal methods for the classification and screening of disease-resistant RLPs.