Systems genetics reveals a transcriptional network associated with susceptibility in the maize-grey leaf spot pathosystem

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach

Expression of quantitative disease resistance in many host-pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Phytophthora sojae pathosystem, incorporating expression quantitative trait loci (eQTL) mapping and gene co-expression network analysis to identify the genes putatively regulating transcriptional changes in response to inoculation. These findings were compared to previously mapped phenotypic (phQTL) to identify the molecular mechanisms contributing to the expression of this resistance. A subset of 93 recombinant inbred lines (RILs) from a Conrad × Sloan population were inoculated with P. sojae isolate 1.S.1.1 using the tray-test method; RNA was extracted, sequenced, and the normalized read counts were genetically mapped from tissue collected at the inoculation site 24 h after inoculation from both mock and inoculated samples. In total, more than 100,000 eQTLs were mapped. There was a switch from predominantly cis-eQTLs in the mock treatment to an almost entirely nonoverlapping set of predominantly trans-eQTLs in the inoculated treatment, where greater than 100-fold more eQTLs were mapped relative to mock, indicating vast transcriptional reprogramming due to P. sojae infection occurred. The eQTLs were organized into 36 hotspots, with the four largest hotspots from the inoculated treatment corresponding to more than 70% of the eQTLs, each enriched for genes within plant-pathogen interaction pathways. Genetic regulation of trans-eQTLs in response to the pathogen was predicted to occur through transcription factors and signaling molecules involved in plant-pathogen interactions, plant hormone signal transduction, and MAPK pathways. Network analysis identified three co-expression modules that were correlated with susceptibility to P. sojae and associated with three eQTL hotspots. Among the eQTLs co-localized with phQTLs, two cis-eQTLs with putative functions in the regulation of root architecture or jasmonic acid, as well as the putative master regulators of an eQTL hotspot nearby a phQTL, represent candidates potentially underpinning the molecular control of these phQTLs for resistance.

Polygenic pathogen networks influence transcriptional plasticity in the Arabidopsis-Botrytis pathosystem

Bidirectional flow of information shapes the outcome of the host-pathogen interactions and depends on the genetics of each organism. Recent work has begun to use co-transcriptomic studies to shed light on this bidirectional flow, but it is unclear how plastic the co-transcriptome is in response to genetic variation in both the host and pathogen. To study co-transcriptome plasticity, we conducted transcriptomics using natural genetic variation in the pathogen, Botrytis cinerea, and large-effect genetic variation abolishing defense signaling pathways within the host, Arabidopsis thaliana. We show that genetic variation in the pathogen has a greater influence on the co-transcriptome than mutations that abolish defense signaling pathways in the host. Genome-wide association mapping using the pathogens' genetic variation and both organisms' transcriptomes allowed an assessment of how the pathogen modulates plasticity in response to the host. This showed that the differences in both organism's responses were linked to trans-expression quantitative trait loci (eQTL) hotspots within the pathogen's genome. These hotspots control gene sets in either the host or pathogen and show differential allele sensitivity to the host's genetic variation rather than qualitative host specificity. Interestingly, nearly all the trans-eQTL hotspots were unique to the host or pathogen transcriptomes. In this system of differential plasticity, the pathogen mediates the shift in the co-transcriptome more than the host.

The maize ZmVPS23-like protein relocates the nucleotide-binding leucine-rich repeat protein Rp1-D21 to endosomes and suppresses the defense response

Plants often utilize nucleotide-binding leucine-rich repeat (NLR) proteins to perceive pathogen infections and trigger a hypersensitive response (HR). The endosomal sorting complex required for transport (ESCRT) machinery is a conserved multisubunit complex that is essential for the biogenesis of multivesicular bodies and cargo protein sorting. VPS23 is a key component of ESCRT-I and plays important roles in plant development and abiotic stresses. ZmVPS23L, a homolog of VPS23-like in maize (Zea mays), was previously identified as a candidate gene in modulating HR mediated by the autoactive NLR protein Rp1-D21 in different maize populations. Here, we demonstrate that ZmVPS23L suppresses Rp1-D21-mediated HR in maize and Nicotiana benthamiana. Variation in the suppressive effect of HR by different ZmVPS23L alleles was correlated with variation in their expression levels. ZmVPS23 also suppressed Rp1-D21-mediated HR. ZmVPS23L and ZmVPS23 predominantly localized to endosomes, and they physically interacted with the coiled-coil domain of Rp1-D21 and mediated the relocation of Rp1-D21 from the nucleo-cytoplasm to endosomes. In summary, we demonstrate that ZmVPS23L and ZmVPS23 are negative regulators of Rp1-D21-mediated HR, likely by sequestrating Rp1-D21 in endosomes via physical interaction. Our findings reveal the role of ESCRT components in controlling plant NLR-mediated defense responses.

Goss's Wilt Resistance in Corn Is Mediated via Salicylic Acid and Programmed Cell Death but Not Jasmonic Acid Pathways

A highly aggressive strain (CMN14-5-1) of Clavibacter nebraskensis bacteria, which causes Goss's wilt in corn, induced severe symptoms in a susceptible corn line (CO447), resulting in water-soaked lesions followed by necrosis within a few days. A tolerant line (CO450) inoculated with the same strain exhibited only mild symptoms such as chlorosis, freckling, and necrosis that did not progress after the first six days following infection. Both lesion length and disease severity were measured using the area under the disease progression curve (AUDPC), and significant differences were found between treatments. We analyzed the expression of key genes related to plant defense in both corn lines challenged with the CMN14-5-1 strain. Allene oxide synthase (ZmAOS), a gene responsible for the production of jasmonic acid (JA), was induced in the CO447 line in response to CMN14-5-1. Following inoculation with CMN14-5-1, the CO450 line demonstrated a higher expression of salicylic acid (SA)-related genes, ZmPAL and ZmPR-1, compared to the CO447 line. In the CO450 line, four genes related to programmed cell death (PCD) were upregulated: respiratory burst oxidase homolog protein D (ZmrbohD), polyphenol oxidase (ZmPPO1), ras-related protein 7 (ZmRab7), and peptidyl-prolyl cis-trans isomerase (ZmPPI). The differential gene expression in response to CMN14-5-1 between the two corn lines provided an indication that SA and PCD are involved in the regulation of corn defense responses against Goss's wilt disease, whereas JA may be contributing to disease susceptibility.

A role for heritable transcriptomic variation in maize adaptation to temperate environments

Background

Transcription bridges genetic information and phenotypes. Here, we evaluated how changes in transcriptional regulation enable maize (Zea mays), a crop originally domesticated in the tropics, to adapt to temperate environments.

Result

We generated 572 unique RNA-seq datasets from the roots of 340 maize genotypes. Genes involved in core processes such as cell division, chromosome organization and cytoskeleton organization showed lower heritability of gene expression, while genes involved in anti-oxidation activity exhibited higher expression heritability. An expression genome-wide association study (eGWAS) identified 19,602 expression quantitative trait loci (eQTLs) associated with the expression of 11,444 genes. A GWAS for alternative splicing identified 49,897 splicing QTLs (sQTLs) for 7614 genes. Genes harboring both cis-eQTLs and cis-sQTLs in linkage disequilibrium were disproportionately likely to encode transcription factors or were annotated as responding to one or more stresses. Independent component analysis of gene expression data identified loci regulating co-expression modules involved in oxidation reduction, response to water deprivation, plastid biogenesis, protein biogenesis, and plant-pathogen interaction. Several genes involved in cell proliferation, flower development, DNA replication, and gene silencing showed lower gene expression variation explained by genetic factors between temperate and tropical maize lines. A GWAS of 27 previously published phenotypes identified several candidate genes overlapping with genomic intervals showing signatures of selection during adaptation to temperate environments.

Conclusion

Our results illustrate how maize transcriptional regulatory networks enable changes in transcriptional regulation to adapt to temperate regions.

Supplementary information

The online version contains supplementary material available at 10.1186/s13059-023-02891-3.

Identification of Key Gene Network Modules and Hub Genes Associated with Wheat Response to Biotic Stress Using Combined Microarray Meta-analysis and WGCN Analysis

Wheat (Triticum aestivum) is one of the major crops worldwide and a primary source of calories for human food. Biotic stresses such as fungi, bacteria, and diseases limit wheat production. Although plant breeding and genetic engineering for biotic stress resistance have been suggested as promising solutions to handle losses caused by biotic stress factors, a comprehensive understanding of molecular mechanisms and identifying key genes is a critical step to obtaining success. Here, a network-based meta-analysis approach based on two main statistical methods was used to identify key genes and molecular mechanisms of the wheat response to biotic stress. A total of 163 samples (21,792 genes) from 10 datasets were analyzed. Fisher Z test based on the p-value and REM method based on effect size resulted in 533 differentially expressed genes (p < 0.001 and FDR < 0.001). WGCNA analysis using a dynamic tree-cutting algorithm was used to construct a co-expression network and three significant modules were detected. The modules were significantly enriched by 16 BP terms and 4 KEGG pathways (Benjamini-Hochberg FDR < 0.001). A total of nine hub genes (a top 1.5% of genes with the highest degree) were identified from the constructed network. The identification of DE genes, gene-gene co-expressing network, and hub genes may contribute to uncovering the molecular mechanisms of the wheat response to biotic stress.

Network organization of the plant immune system: from pathogen perception to robust defense induction

The plant immune system has been explored essentially through the study of qualitative resistance, a simple form of immunity, and from a reductionist point of view. The recent identification of genes conferring quantitative disease resistance revealed a large array of functions, suggesting more complex mechanisms. In addition, thanks to the advent of high-throughput analyses and system approaches, our view of the immune system has become more integrative, revealing that plant immunity should rather be seen as a distributed and highly connected molecular network including diverse functions to optimize expression of plant defenses to pathogens. Here, we review the recent progress made to understand the network complexity of regulatory pathways leading to plant immunity, from pathogen perception, through signaling pathways and finally to immune responses. We also analyze the topological organization of these networks and their emergent properties, crucial to predict novel immune functions and test them experimentally. Finally, we report how these networks might be regulated by environmental clues. Although system approaches remain extremely scarce in this area of research, a growing body of evidence indicates that the plant response to combined biotic and abiotic stresses cannot be inferred from responses to individual stresses. A view of possible research avenues in this nascent biology domain is finally proposed.

qtlXplorer: an online systems genetics browser in the Eucalyptus Genome Integrative Explorer (EucGenIE)

BACKGROUND

Affordable high-throughput DNA and RNA sequencing technologies are allowing genomic analysis of plant and animal populations and as a result empowering new systems genetics approaches to study complex traits. The availability of intuitive tools to browse and analyze the resulting large-scale genetic and genomic datasets remain a significant challenge. Furthermore, these integrative genomics approaches require innovative methods to dissect the flow and interconnectedness of biological information underlying complex trait variation. The Plant Genome Integrative Explorer (PlantGenIE.org) is a multi-species database and domain that houses online tools for model and woody plant species including Eucalyptus. Since the Eucalyptus Genome Integrative Explorer (EucGenIE) is integrated within PlantGenIE, it shares genome and expression analysis tools previously implemented within the various subdomains (ConGenIE, PopGenIE and AtGenIE). Despite the success in setting up integrative genomics databases, online tools for systems genetics modelling and high-resolution dissection of complex trait variation in plant populations have been lacking.

RESULTS

We have developed qtlXplorer ( https://eucgenie.org/QTLXplorer ) for visualizing and exploring systems genetics data from genome-wide association studies including quantitative trait loci (QTLs) and expression-based QTL (eQTL) associations. This module allows users to, for example, find co-located QTLs and eQTLs using an interactive version of Circos, or explore underlying genes using JBrowse. It provides users with a means to build systems genetics models and generate hypotheses from large-scale population genomics data. We also substantially upgraded the EucGenIE resource and show how it enables users to combine genomics and systems genetics approaches to discover candidate genes involved in biotic stress responses and wood formation by focusing on two multigene families, laccases and peroxidases.

CONCLUSIONS

qtlXplorer adds a new dimension, population genomics, to the EucGenIE and PlantGenIE environment. The resource will be of interest to researchers and molecular breeders working in Eucalyptus and other woody plant species. It provides an example of how systems genetics data can be integrated with functional genetics data to provide biological insight and formulate hypotheses. Importantly, integration within PlantGenIE enables novel comparative genomics analyses to be performed from population-scale data.

Transcriptomic analysis of Pinellia ternata (Thunb.) Breit T2 plus line provides insights in host responses resist Pectobacterium carotovorum infection

Transcriptome is used to determine the induction response of Pinellia ternata (Thunb.) Breit T2 plus line (abbreviated as PT2P line) infected with Pectobacterium carotovorum. The main objective of the study was to deal with the transcriptome database of PT2P line resistance to soft rot pathogens to provide a new perspective for identifying the resistance-related genes and understanding the molecular mechanism. Results indicated that water soaking and tissue collapse started at 20 h after PT2P line was infected by P. carotovorum. A total of 1360 and 5768 differentially expressed genes (DEGs) were identified at 0 h and 20 h, respectively. After 20 h of infection, growth and development-related pathways were inhibited. Meanwhile, DEGs were promoted the colonization of P. carotovorum pathogens in specific cell wall modification processes at the early infected stage. A shift to a defensive response was triggered at 0 h. A large number of DEGs were mainly up-controlled at 20 h and were substantially used in the pathogen recognition and the introduction of signal transformation cascades, secondary metabolites biosynthesis, pathogenic proteins activation, transcription aspects and numerous transporters. Furthermore, our data provided novel insights into the transcript reprogramming of PT2P line in response to P. carotovorum infestation.

A systems genetics approach reveals PbrNSC as a regulator of lignin and cellulose biosynthesis in stone cells of pear fruit

BACKGROUND

Stone cells in fruits of pear (Pyrus pyrifolia) negatively influence fruit quality because their lignified cell walls impart a coarse and granular texture to the fruit flesh.

RESULTS

We generate RNA-seq data from the developing fruits of 206 pear cultivars with a wide range of stone cell contents and use a systems genetics approach to integrate co-expression networks and expression quantitative trait loci (eQTLs) to characterize the regulatory mechanisms controlling lignocellulose formation in the stone cells of pear fruits. Our data with a total of 35,897 expressed genes and 974,404 SNPs support the identification of seven stone cell formation modules and the detection of 139,515 eQTLs for 3229 genes in these modules. Focusing on regulatory factors and using a co-expression network comprising 39 structural genes, we identify PbrNSC as a candidate regulator of stone cell formation. We then verify the function of PbrNSC in regulating lignocellulose formation using both pear fruit and Arabidopsis plants and further show that PbrNSC can transcriptionally activate multiple target genes involved in secondary cell wall formation.

CONCLUSIONS

This study generates a large resource for studying stone cell formation and provides insights into gene regulatory networks controlling the formation of stone cell and lignocellulose.

Status and advances in mining for blackleg (Leptosphaeria maculans) quantitative resistance (QR) in oilseed rape (Brassica napus)

KEY MESSAGE

Quantitative resistance (QR) loci discovered through genetic and genomic analyses are abundant in the Brassica napus genome, providing an opportunity for their utilization in enhancing blackleg resistance. Quantitative resistance (QR) has long been utilized to manage blackleg in Brassica napus (canola, oilseed rape), even before major resistance genes (R-genes) were extensively explored in breeding programmes. In contrast to R-gene-mediated qualitative resistance, QR reduces blackleg symptoms rather than completely eliminating the disease. As a polygenic trait, QR is controlled by numerous genes with modest effects, which exerts less pressure on the pathogen to evolve; hence, its effectiveness is more durable compared to R-gene-mediated resistance. Furthermore, combining QR with major R-genes has been shown to enhance resistance against diseases in important crops, including oilseed rape. For these reasons, there has been a renewed interest among breeders in utilizing QR in crop improvement. However, the mechanisms governing QR are largely unknown, limiting its deployment. Advances in genomics are facilitating the dissection of the genetic and molecular underpinnings of QR, resulting in the discovery of several loci and genes that can be potentially deployed to enhance blackleg resistance. Here, we summarize the efforts undertaken to identify blackleg QR loci in oilseed rape using linkage and association analysis. We update the knowledge on the possible mechanisms governing QR and the advances in searching for the underlying genes. Lastly, we lay out strategies to accelerate the genetic improvement of blackleg QR in oilseed rape using improved phenotyping approaches and genomic prediction tools.

A forward genetics approach integrating genome-wide association study and expression quantitative trait locus mapping to dissect leaf development in maize (Zea mays)

The characterization of the genetic basis of maize (Zea mays) leaf development may support breeding efforts to obtain plants with higher vigor and productivity. In this study, a mapping panel of 197 biparental and multiparental maize recombinant inbred lines (RILs) was analyzed for multiple leaf traits at the seedling stage. RNA sequencing was used to estimate the transcription levels of 29 573 gene models in RILs and to derive 373 769 single nucleotide polymorphisms (SNPs), and a forward genetics approach combining these data was used to pinpoint candidate genes involved in leaf development. First, leaf traits were correlated with gene expression levels to identify transcript-trait correlations. Then, leaf traits were associated with SNPs in a genome-wide association (GWA) study. An expression quantitative trait locus mapping approach was followed to associate SNPs with gene expression levels, prioritizing candidate genes identified based on transcript-trait correlations and GWAs. Finally, a network analysis was conducted to cluster all transcripts in 38 co-expression modules. By integrating forward genetics approaches, we identified 25 candidate genes highly enriched for specific functional categories, providing evidence supporting the role of vacuolar proton pumps, cell wall effectors, and vesicular traffic controllers in leaf growth. These results tackle the complexity of leaf trait determination and may support precision breeding in maize.

The utility of metabolomics as a tool to inform maize biology

With the rise of high-throughput omics tools and the importance of maize and its products as food and bioethanol, maize metabolism has been extensively explored. Modern maize is still rich in genetic and phenotypic variation, yielding a wide range of structurally and functionally diverse metabolites. The maize metabolome is also incredibly dynamic in terms of topology and subcellular compartmentalization. In this review, we examine a broad range of studies that cover recent developments in maize metabolism. Particular attention is given to current methodologies and to the use of metabolomics as a tool to define biosynthetic pathways and address biological questions. We also touch upon the use of metabolomics to understand maize natural variation and evolution, with a special focus on research that has used metabolite-based genome-wide association studies (mGWASs).

Bioactive diterpenoids impact the composition of the root-associated microbiome in maize (Zea mays)

Plants deploy both primary and species-specific, specialized metabolites to communicate with other organisms and adapt to environmental challenges, including interactions with soil-dwelling microbial communities. However, the role of specialized metabolites in modulating plant-microbiome interactions often remains elusive. In this study, we report that maize (Zea mays) diterpenoid metabolites with known antifungal bioactivities also influence rhizosphere bacterial communities. Metabolite profiling showed that dolabralexins, antibiotic diterpenoids that are highly abundant in roots of some maize varieties, can be exuded from the roots. Comparative 16S rRNA gene sequencing determined the bacterial community composition of the maize mutant Zman2 (anther ear 2), which is deficient in dolabralexins and closely related bioactive kauralexin diterpenoids. The Zman2 rhizosphere microbiome differed significantly from the wild-type sibling with the most significant changes observed for Alphaproteobacteria of the order Sphingomonadales. Metabolomics analyses support that these differences are attributed to the diterpenoid deficiency of the Zman2 mutant, rather than other large-scale metabolome alterations. Together, these findings support physiological functions of maize diterpenoids beyond known chemical defenses, including the assembly of the rhizosphere microbiome.

Benefits of maize resistance breeding and chemical control against northern leaf blight in smallholder farms in South Africa

Maize underpins food security in South Africa. An annual production of more than 10 million tons is a combination of the output of large-scale commercial farms plus an estimated 250 000 ha cultivated by smallholder farmers. Maize leaves are a rich source of nutrients for fungal pathogens. Farmers must limit leaf blighting by fungi to prevent sugars captured by photosynthesis being ‘stolen’ instead of filling the grain. This study aimed to fill the knowledge gap on the prevalence and impact of fungal foliar diseases in local smallholder maize fields. A survey with 1124 plant observations from diverse maize hybrids was conducted over three seasons from 2015 to 2017 in five farming communities in KwaZulu-Natal Province (Hlanganani, Ntabamhlophe, KwaNxamalala) and Eastern Cape Province (Bizana, Tabankulu). Northern leaf blight (NLB), common rust, Phaeosphaeria leaf spot, and grey leaf spot had overall disease incidences of 75%, 77%, 68% and 56%, respectively, indicating high disease pressure in smallholder farming environments. NLB had the highest disease severity (LSD test, p<0.05). A yield trial focused on NLB in KwaZulu-Natal showed that this disease reduced yields in the three most susceptible maize hybrids by 36%, 71% and 72%, respectively. Eighteen other hybrids in this trial did not show significant yield reductions due to NLB, which illustrates the progress made by local maize breeders in disease resistance breeding. This work highlights the risk to smallholder farmers of planting disease-susceptible varieties, and makes recommendations on how to exploit the advances of hybrid maize disease resistance breeding to develop farmer-preferred varieties for smallholder production.

A systems genetics approach reveals environment-dependent associations between SNPs, protein coexpression, and drought-related traits in maize

The effect of drought on maize yield is of particular concern in the context of climate change and human population growth. However, the complexity of drought-response mechanisms makes the design of new drought-tolerant varieties a difficult task that would greatly benefit from a better understanding of the genotype–phenotype relationship. To provide novel insight into this relationship, we applied a systems genetics approach integrating high-throughput phenotypic, proteomic, and genomic data acquired from 254 maize hybrids grown under two watering conditions. Using association genetics and protein coexpression analysis, we detected more than 22,000 pQTLs across the two conditions and confidently identified 15 loci with potential pleiotropic effects on the proteome. We showed that even mild water deficit induced a profound remodeling of the proteome, which affected the structure of the protein coexpression network, and a reprogramming of the genetic control of the abundance of many proteins, including those involved in stress response. Colocalizations between pQTLs and QTLs for ecophysiological traits, found mostly in the water deficit condition, indicated that this reprogramming may also affect the phenotypic level. Finally, we identified several candidate genes that are potentially responsible for both the coexpression of stress response proteins and the variations of ecophysiological traits under water deficit. Taken together, our findings provide novel insights into the molecular mechanisms of drought tolerance and suggest some pathways for further research and breeding.

Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits

BACKGROUND

Genetic analysis of gene expression level is a promising approach for characterizing candidate genes that are involved in complex economic traits such as meat quality. In the present study, we conducted expression quantitative trait loci (eQTL) and allele-specific expression (ASE) analyses based on RNA-sequencing (RNAseq) data from the longissimus muscle of 189 Duroc × Luchuan crossed pigs in order to identify some candidate genes for meat quality traits.

RESULTS

Using a genome-wide association study based on a mixed linear model, we identified 7192 cis-eQTL corresponding to 2098 cis-genes (p ≤ 1.33e-3, FDR ≤ 0.05) and 6400 trans-eQTL corresponding to 863 trans-genes (p ≤ 1.13e-6, FDR ≤ 0.05). ASE analysis using RNAseq SNPs identified 9815 significant ASE-SNPs in 2253 unique genes. Integrative analysis between the cis-eQTL and ASE target genes identified 540 common genes, including 33 genes with expression levels that were correlated with at least one meat quality trait. Among these 540 common genes, 63 have been reported previously as candidate genes for meat quality traits, such as PHKG1 (q-value = 1.67e-6 for the leading SNP in the cis-eQTL analysis), NUDT7 (q-value = 5.67e-13), FADS2 (q-value = 8.44e-5), and DGAT2 (q-value = 1.24e-3).

CONCLUSIONS

The present study confirmed several previously published candidate genes and identified some novel candidate genes for meat quality traits via eQTL and ASE analyses, which will be useful to prioritize candidate genes in further studies.

Pathogen Genetic Control of Transcriptome Variation in the Arabidopsis thaliana - Botrytis cinerea Pathosystem

In plant-pathogen relations, disease symptoms arise from the interaction of the host and pathogen genomes. Host-pathogen functional gene interactions are well described, whereas little is known about how the pathogen genetic variation modulates both organisms' transcriptomes. To model and generate hypotheses on a generalist pathogen control of gene expression regulation, we used the Arabidopsis thaliana-Botrytis cinerea pathosystem and the genetic diversity of a collection of 96 B. cinerea isolates. We performed expression-based genome-wide association (eGWA) for each of 23,947 measurable transcripts in Arabidopsis (host), and 9267 measurable transcripts in B. cinerea (pathogen). Unlike other eGWA studies, we detected a relative absence of locally acting expression quantitative trait loci (cis-eQTL), partly caused by structural variants and allelic heterogeneity hindering their identification. This study identified several distantly acting trans-eQTL linked to eQTL hotspots dispersed across Botrytis genome that altered only Botrytis transcripts, only Arabidopsis transcripts, or transcripts from both species. Gene membership in the trans-eQTL hotspots suggests links between gene expression regulation and both known and novel virulence mechanisms in this pathosystem. Genes annotated to these hotspots provide potential targets for blocking manipulation of the host response by this ubiquitous generalist necrotrophic pathogen.

De novo Assembly of Transcriptomes From a B73 Maize Line Introgressed With a QTL for Resistance to Gray Leaf Spot Disease Reveals a Candidate Allele of a Lectin Receptor-Like Kinase

Gray leaf spot (GLS) disease in maize, caused by the fungus Cercospora zeina, is a threat to maize production globally. Understanding the molecular basis for quantitative resistance to GLS is therefore important for food security. We developed a de novo assembly pipeline to identify candidate maize resistance genes. Near-isogenic maize lines with and without a QTL for GLS resistance on chromosome 10 from inbred CML444 were produced in the inbred B73 background. The B73-QTL line showed a 20% reduction in GLS disease symptoms compared to B73 in the field (p = 0.01). B73-QTL leaf samples from this field experiment conducted under GLS disease pressure were RNA sequenced. The reads that did not map to the B73 or C. zeina genomes were expected to contain novel defense genes and were de novo assembled. A total of 141 protein-coding sequences with B73-like or plant annotations were identified from the B73-QTL plants exposed to C. zeina. To determine whether candidate gene expression was induced by C. zeina, the RNAseq reads from C. zeina-challenged and control leaves were mapped to a master assembly of all of the B73-QTL reads, and differential gene expression analysis was conducted. Combining results from both bioinformatics approaches led to the identification of a likely candidate gene, which was a novel allele of a lectin receptor-like kinase named L-RLK-CML that (i) was induced by C. zeina, (ii) was positioned in the QTL region, and (iii) had functional domains for pathogen perception and defense signal transduction. The 817AA L-RLK-CML protein had 53 amino acid differences from its 818AA counterpart in B73. A second "B73-like" allele of L-RLK was expressed at a low level in B73-QTL. Gene copy-specific RT-qPCR confirmed that the l-rlk-cml transcript was the major product induced four-fold by C. zeina. Several other expressed defense-related candidates were identified, including a wall-associated kinase, two glutathione s-transferases, a chitinase, a glucan beta-glucosidase, a plasmodesmata callose-binding protein, several other receptor-like kinases, and components of calcium signaling, vesicular trafficking, and ethylene biosynthesis. This work presents a bioinformatics protocol for gene discovery from de novo assembled transcriptomes and identifies candidate quantitative resistance genes.

Genome-Wide Association and Gene Co-expression Network Analyses Reveal Complex Genetics of Resistance to Goss's Wilt of Maize

Goss’s bacterial wilt and leaf blight is a disease of maize caused by the gram positive bacterium Clavibacter michiganensis subsp. nebraskensis (Cmn). First discovered in Nebraska, Goss’s wilt has now spread to major maize growing states in the United States and three provinces in Canada. Previous studies conducted using elite maize inbred lines and their hybrids have shown that resistance to Goss’s wilt is a quantitative trait. The objective of this study was to further our understanding of the genetic basis of resistance to Goss’s wilt by using a combined approach of genome-wide association mapping and gene co-expression network analysis. Genome-wide association analysis was accomplished using a diversity panel consisting of 555 maize inbred lines and a set of 450 recombinant inbred lines (RILs) from three bi-parental mapping populations, providing the most comprehensive screening of Goss’s wilt resistance to date. Three SNPs in the diversity panel and 10 SNPs in the combined dataset, including the diversity panel and RILs, were found to be significantly associated with Goss’s wilt resistance. Each significant SNP explained 1–5% of the phenotypic variation for Goss’s wilt (total of 8–11%). To augment the results of genome-wide association mapping and help identify candidate genes, a time course RNA sequencing experiment was conducted using resistant (N551) and susceptible (B14A) maize inbred lines. Gene co-expression network analysis of this time course experiment identified one module of 141 correlated genes that showed differential regulation in response to Cmn inoculations in both resistant and susceptible lines. SNPs inside and flanking these genes explained 13.3% of the phenotypic variation. Among 1,000 random samples of genes, only 8% of samples explained more phenotypic variance for Goss’s wilt resistance than those implicated by the co-expression network analysis. While a statistically significant enrichment was not observed (P < 0.05), these results suggest a possible role for these genes in quantitative resistance at the field level and warrant more research on combining gene co-expression network analysis with quantitative genetic analyses to dissect complex disease resistance traits. The results of the GWAS and co-expression analysis both support the complex nature of resistance to this important disease of maize.

A systems genetics analysis in Eucalyptus reveals coordination of metabolic pathways associated with xylan modification in wood-forming tissues

Acetyl- and methylglucuronic acid decorations of xylan, the dominant hemicellulose in secondary cell walls (SCWs) of woody dicots, affect its interaction with cellulose and lignin to determine SCW structure and extractability. Genes and pathways involved in these modifications may be targets for genetic engineering; however, little is known about the regulation of xylan modifications in woody plants. To address this, we assessed genetic and gene expression variation associated with xylan modification in developing xylem of Eucalyptus grandis × Eucalyptus urophylla interspecific hybrids. Expression quantitative trait locus (eQTL) mapping identified potential regulatory polymorphisms affecting gene expression modules associated with xylan modification. We identified 14 putative xylan modification genes that are members of five expression modules sharing seven trans-eQTL hotspots. The xylan modification genes are prevalent in two expression modules. The first comprises nucleotide sugar interconversion pathways supplying the essential precursors for cellulose and xylan biosynthesis. The second contains genes responsible for phenylalanine biosynthesis and S-adenosylmethionine biosynthesis required for glucuronic acid and monolignol methylation. Co-expression and co-regulation analyses also identified four metabolic sources of acetyl coenxyme A that appear to be transcriptionally coordinated with xylan modification. Our systems genetics analysis may provide new avenues for metabolic engineering to alter wood SCW biology for enhanced biomass processability.

Durability of Quantitative Resistance in Crops: Greater Than We Know?

Quantitative resistance (QR) to crop diseases has usually been much more durable than major-gene, effector-triggered resistance. It has been observed that the effectiveness of some QR has eroded as pathogens adapt to it, especially when deployment is extensive and epidemics occur regularly, but it generally declines more slowly than effector-triggered resistance. Changes in aggressiveness and specificity of diverse pathogens on cultivars with QR have been recorded, along with experimental data on fitness costs of pathogen adaptation to QR, but there is little information about molecular mechanisms of adaptation. Some QR has correlated or antagonistic effects on multiple diseases. Longitudinal data on cultivars' disease ratings in trials over several years can be used to assess the significance of QR for durable resistance in crops. It is argued that published data likely underreport the durability of QR, owing to publication bias. The implications of research on QR for plant breeding are discussed.

Meta-analysis of drought-tolerant genotypes in Oryza sativa: A network-based approach

BACKGROUND

Drought is a severe environmental stress. It is estimated that about 50% of the world rice production is affected mainly by drought. Apart from conventional breeding strategies to develop drought-tolerant crops, innovative computational approaches may provide insights into the underlying molecular mechanisms of stress response and identify drought-responsive markers. Here we propose a network-based computational approach involving a meta-analytic study of seven drought-tolerant rice genotypes under drought stress.

RESULTS

Co-expression networks enable large-scale analysis of gene-pair associations and tightly coupled clusters that may represent coordinated biological processes. Considering differentially expressed genes in the co-expressed modules and supplementing external information such as resistance/tolerance QTLs, transcription factors, network-based topological measures, we identify and prioritize drought-adaptive co-expressed gene modules and potential candidate genes. Using the candidate genes that are well-represented across the datasets as 'seed' genes, two drought-specific protein-protein interaction networks (PPINs) are constructed with up- and down-regulated genes. Cluster analysis of the up-regulated PPIN revealed ABA signalling pathway as a central process in drought response with a probable crosstalk with energy metabolic processes. Tightly coupled gene clusters representing up-regulation of core cellular respiratory processes and enhanced degradation of branched chain amino acids and cell wall metabolism are identified. Cluster analysis of down-regulated PPIN provides a snapshot of major processes associated with photosynthesis, growth, development and protein synthesis, most of which are shut down during drought. Differential regulation of phytohormones, e.g., jasmonic acid, cell wall metabolism, signalling and posttranslational modifications associated with biotic stress are elucidated. Functional characterization of topologically important, drought-responsive uncharacterized genes that may play a role in important processes such as ABA signalling, calcium signalling, photosynthesis and cell wall metabolism is discussed. Further transgenic studies on these genes may help in elucidating their biological role under stress conditions.

CONCLUSION

Currently, a large number of resources for rice functional genomics exist which are mostly underutilized by the scientific community. In this study, a computational approach integrating information from various resources such as gene co-expression networks, protein-protein interactions and pathway-level information is proposed to provide a systems-level view of complex drought-responsive processes across the drought-tolerant genotypes.

Xylan in the Middle: Understanding Xylan Biosynthesis and Its Metabolic Dependencies Toward Improving Wood Fiber for Industrial Processing

Lignocellulosic biomass, encompassing cellulose, lignin and hemicellulose in plant secondary cell walls (SCWs), is the most abundant source of renewable materials on earth. Currently, fast-growing woody dicots such as Eucalyptus and Populus trees are major lignocellulosic (wood fiber) feedstocks for bioproducts such as pulp, paper, cellulose, textiles, bioplastics and other biomaterials. Processing wood for these products entails separating the biomass into its three main components as efficiently as possible without compromising yield. Glucuronoxylan (xylan), the main hemicellulose present in the SCWs of hardwood trees carries chemical modifications that are associated with SCW composition and ultrastructure, and affect the recalcitrance of woody biomass to industrial processing. In this review we highlight the importance of xylan properties for industrial wood fiber processing and how gaining a greater understanding of xylan biosynthesis, specifically xylan modification, could yield novel biotechnology approaches to reduce recalcitrance or introduce novel processing traits. Altering xylan modification patterns has recently become a focus of plant SCW studies due to early findings that altered modification patterns can yield beneficial biomass processing traits. Additionally, it has been noted that plants with altered xylan composition display metabolic differences linked to changes in precursor usage. We explore the possibility of using systems biology and systems genetics approaches to gain insight into the coordination of SCW formation with other interdependent biological processes. Acetyl-CoA, s-adenosylmethionine and nucleotide sugars are precursors needed for xylan modification, however, the pathways which produce metabolic pools during different stages of fiber cell wall formation still have to be identified and their co-regulation during SCW formation elucidated. The crucial dependence on precursor metabolism provides an opportunity to alter xylan modification patterns through metabolic engineering of one or more of these interdependent pathways. The complexity of xylan biosynthesis and modification is currently a stumbling point, but it may provide new avenues for woody biomass engineering that are not possible for other biopolymers.

Transcriptome analysis reveals the molecular mechanisms of the defense response to gray leaf spot disease in maize

BACKGROUND

Gray leaf spot (GLS), which is caused by the necrotrophic fungi Cercospora zeae-maydis and Cercospora zeina, is one of the most impactful diseases in maize worldwide. The aim of the present study is to identify the resistance genes and understand the molecular mechanisms for GLS resistance.

RESULTS

Two cultivars, 'Yayu889' and 'Zhenghong532,' which are distinguished as resistant and susceptible cultivars, respectively, were challenged with the GLS disease and a RNA-seq experiment was conducted on infected plants at 81, 89, 91, and 93 days post planting (dap). Compared with the beginning stage at 81 dap, 4666, 1733, and 1166 differentially expressed genes (DEGs) were identified at 89, 91, and 93 dap, respectively, in 'Yayu889,' while relatively fewer, i.e., 4713, 881, and 722 DEGs, were identified in 'Zhenghong532.' Multiple pathways involved in the response of maize to GLS, including 'response to salicylic acid,' 'protein phosphorylation,' 'oxidation-reduction process,' and 'carotenoid biosynthetic process,' were enriched by combining differential expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). The expression of 12 candidate resistance proteins in these pathways were quantified by the multiple reaction monitoring (MRM) method. This approach identified two candidate resistance proteins, a calmodulin-like protein and a leucine-rich repeat receptor-like protein kinase with SNPs that were located in QTL regions for GLS resistance. Metabolic analysis showed that, compared with 'Zhenghong532,' the amount of salicylic acid (SA) and total carotenoids in 'Yayu889' increased, while peroxidase activity decreased during the early infection stages, suggesting that increased levels of SA, carotenoids, and reactive oxygen species (ROS) may enhance the defense response of 'Yayu889' to GLS.

CONCLUSION

By combining transcriptome and proteome analyses with comparisons of resistance QTL regions, calmodulin-like protein and leucine-rich repeat receptor-like protein kinase were identified as candidate GLS resistance proteins. Moreover, we found that the metabolic pathways for ROS, SA, and carotenoids are especially active in the resistant cultivar. These findings could lead to a better understanding of the GLS resistance mechanisms and facilitate the breeding of GLS-resistant maize cultivars.

RNA-Seq analysis of resistant and susceptible sub-tropical maize lines reveals a role for kauralexins in resistance to grey leaf spot disease, caused by Cercospora zeina

BACKGROUND

Cercospora zeina is a foliar pathogen responsible for maize grey leaf spot in southern Africa that negatively impacts maize production. Plants use a variety of chemical and structural mechanisms to defend themselves against invading pathogens such as C. zeina, including the production of secondary metabolites with antimicrobial properties. In maize, a variety of biotic and abiotic stressors induce the accumulation of the terpenoid phytoalexins, zealexins and kauralexins.

RESULTS

C. zeina-susceptible line displayed pervasive rectangular grey leaf spot lesions, running parallel with the leaf veins in contrast to C. zeina-resistant line that had restricted disease symptoms. Analysis of the transcriptome of both lines indicated that genes involved in primary and secondary metabolism were up-regualted, and although different pathways were prioritized in each line, production of terpenoid compounds were common to both. Targeted phytoalexin analysis revealed that C. zeina-inoculated leaves accumulated zealexins and kauralexins. The resistant line shows a propensity toward accumulation of the kauralexin B series metabolites in response to infection, which contrasts with the susceptible line that preferentially accumulates the kauralexin A series. Kauralexin accumulation was correlated to expression of the kauralexin biosynthetic gene, ZmAn2 and a candidate biosynthetic gene, ZmKSL2. We report the expression of a putative copalyl diphosphate synthase gene that is induced by C. zeina in the resistant line exclusively.

DISCUSSION

This study shows that zealexins and kauralexins, and expression of their biosynthetic genes, are induced by C. zeina in both resistant and susceptible germplasm adapted to the southern African climate. The data presented here indicates that different forms of kauralexins accumulate in the resistant and susceptible maize lines in response to C. zeina, with the accumulation of kauralexin B compounds in a resistant maize line and kauralexin A compounds accumulating in the susceptible line.

Complementation of CTB7 in the Maize Pathogen Cercospora zeina Overcomes the Lack of In Vitro Cercosporin Production

Gray leaf spot (GLS), caused by the sibling species Cercospora zeina or Cercospora zeae-maydis, is cited as one of the most important diseases threatening global maize production. C. zeina fails to produce cercosporin in vitro and, in most cases, causes large coalescing lesions during maize infection, a symptom generally absent from cercosporin-deficient mutants in other Cercospora spp. Here, we describe the C. zeina cercosporin toxin biosynthetic (CTB) gene cluster. The oxidoreductase gene CTB7 contained several insertions and deletions as compared with the C. zeae-maydis ortholog. We set out to determine whether complementing the defective CTB7 gene with the full-length gene from C. zeae-maydis could confer in vitro cercosporin production. C. zeina transformants containing C. zeae-maydis CTB7 were generated by Agrobacterium tumefaciens-mediated transformation and were evaluated for in vitro cercosporin production. When grown on nitrogen-limited medium in the light-conditions conducive to cercosporin production in other Cercospora spp.-one transformant accumulated a red pigment that was confirmed to be cercosporin by the KOH assay, thin-layer chromatography, and ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry. Our results indicated that C. zeina has a defective CTB7, but all other necessary machinery required for synthesizing cercosporin-like molecules and, thus, C. zeina may produce a structural variant of cercosporin during maize infection.