Lessons from eQTL mapping studies: non-coding regions and their role behind natural phenotypic variation in plants

Advancements in genetic techniques and functional genomics for enhancing crop traits and agricultural sustainability

Genetic variability is essential for the development of new crop varieties with economically beneficial traits. The traits can be inherited from wild relatives or induced through mutagenesis. Novel genetic elements can then be identified and new gene functions can be predicted. In this study, forward and reverse genetics approaches were described, in addition to their applications in modern crop improvement programs and functional genomics. By using heritable phenotypes and linked genetic markers, forward genetics searches for genes by using traditional genetic mapping and allele frequency estimation. Despite recent advances in sequencing technology, omics and computation, genetic redundancy remains a major challenge in forward genetics. By analyzing close-related genes, we will be able to dissect their functional redundancy and predict possible traits and gene activity patterns. In addition to these predictions, sophisticated reverse gene editing tools can be used to verify them, including TILLING, targeted insertional mutagenesis, gene silencing, gene targeting and genome editing. By using gene knock-down, knock-up and knock-out strategies, these tools are able to detect genetic changes in cells. In addition, epigenome analysis and editing enable the development of novel traits in existing crop cultivars without affecting their genetic makeup by increasing epiallelic variants. Our understanding of gene functions and molecular dynamics of various biological phenomena has been revised by all of these findings. The study also identifies novel genetic targets in crop species to improve yields and stress tolerances through conventional and non-conventional methods. In this article, genetic techniques and functional genomics are specifically discussed and assessed for their potential in crop improvement.

Allelic variations of WAK106-E2Fa-DPb1-UGT74E2 module regulate fibre properties in Populus tomentosa

Wood formation, intricately linked to the carbohydrate metabolism pathway, underpins the capacity of trees to produce renewable resources and offer vital ecosystem services. Despite their importance, the genetic regulatory mechanisms governing wood fibre properties in woody plants remain enigmatic. In this study, we identified a pivotal module comprising 158 high-priority core genes implicated in wood formation, drawing upon tissue-specific gene expression profiles from 22 Populus samples. Initially, we conducted a module-based association study in a natural population of 435 Populus tomentosa, pinpointing PtoDPb1 as the key gene contributing to wood formation through the carbohydrate metabolic pathway. Overexpressing PtoDPb1 led to a 52.91% surge in cellulose content, a reduction of 14.34% in fibre length, and an increment of 38.21% in fibre width in transgenic poplar. Moreover, by integrating co-expression patterns, RNA-sequencing analysis, and expression quantitative trait nucleotide (eQTN) mapping, we identified a PtoDPb1-mediated genetic module of PtoWAK106-PtoDPb1-PtoE2Fa-PtoUGT74E2 responsible for fibre properties in Populus. Additionally, we discovered the two PtoDPb1 haplotypes that influenced protein interaction efficiency between PtoE2Fa-PtoDPb1 and PtoDPb1-PtoWAK106, respectively. The transcriptional activation activity of the PtoE2Fa-PtoDPb1 haplotype-1 complex on the promoter of PtoUGT74E2 surpassed that of the PtoE2Fa-PtoDPb1 haplotype-2 complex. Taken together, our findings provide novel insights into the regulatory mechanisms of fibre properties in Populus, orchestrated by PtoDPb1, and offer a practical module for expediting genetic breeding in woody plants via molecular design.

Multi-omics-driven advances in the understanding of triacylglycerol biosynthesis in oil seeds

Vegetable oils are rich sources of polyunsaturated fatty acids and energy as well as valuable sources of human food, animal feed, and bioenergy. Triacylglycerols, which are comprised of three fatty acids attached to a glycerol backbone, are the main component of vegetable oils. Here, we review the development and application of multiple-level omics in major oilseeds and emphasize the progress in the analysis of the biological roles of key genes underlying seed oil content and quality in major oilseeds. Finally, we discuss future research directions in functional genomics research based on current omics and oil metabolic engineering strategies that aim to enhance seed oil content and quality, and specific fatty acids components according to either human health needs or industrial requirements.

Gene editing of non-coding regulatory DNA and its application in crop improvement

The development of the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas) system has provided precise and efficient strategies to edit target genes and generate transgene-free crops. Significant progress has been made in the editing of protein-coding genes; however, studies on the editing of non-coding DNA with regulatory roles lags far behind. Non-coding regulatory DNAs, including those which can be transcribed into long non-coding RNAs (lncRNAs), and miRNAs, together with cis-regulatory elements (CREs), play crucial roles in regulating plant growth and development. Therefore, the combination of CRISPR/Cas technology and non-coding regulatory DNA has great potential to generate novel alleles that affect various agronomic traits of crops, thus providing valuable genetic resources for crop breeding. Herein, we review recent advances in the roles of non-coding regulatory DNA, attempts to edit non-coding regulatory DNA for crop improvement, and potential application of novel editing tools in modulating non-coding regulatory DNA. Finally, the existing problems, possible solutions, and future applications of gene editing of non-coding regulatory DNA in modern crop breeding practice are also discussed.

Expression quantitative trait loci mapping identified PtrXB38 as a key hub gene in adventitious root development in Populus

Plant establishment requires the formation and development of an extensive root system with architecture modulated by complex genetic networks. Here, we report the identification of the PtrXB38 gene as an expression quantitative trait loci (eQTL) hotspot, mapped using 390 leaf and 444 xylem Populus trichocarpa transcriptomes. Among predicted targets of this trans-eQTL were genes involved in plant hormone responses and root development. Overexpression of PtrXB38 in Populus led to significant increases in callusing and formation of both stem-born roots and base-born adventitious roots. Omics studies revealed that genes and proteins controlling auxin transport and signaling were involved in PtrXB38-mediated adventitious root formation. Protein-protein interaction assays indicated that PtrXB38 interacts with components of endosomal sorting complexes required for transport machinery, implying that PtrXB38-regulated root development may be mediated by regulating endocytosis pathway. Taken together, this work identified a crucial root development regulator and sheds light on the discovery of other plant developmental regulators through combining eQTL mapping and omics approaches.

Allelic variation in transcription factor PtoWRKY68 contributes to drought tolerance in Populus

Drought stress limits woody species productivity and influences tree distribution. However, dissecting the molecular mechanisms that underpin drought responses in forest trees can be challenging due to trait complexity. Here, using a panel of 300 Chinese white poplar (Populus tomentosa) accessions collected from different geographical climatic regions in China, we performed a genome-wide association study (GWAS) on seven drought-related traits and identified PtoWRKY68 as a candidate gene involved in the response to drought stress. A 12-bp insertion and/or deletion and three nonsynonymous variants in the PtoWRKY68 coding sequence categorized natural populations of P. tomentosa into two haplotype groups, PtoWRKY68hap1 and PtoWRKY68hap2. The allelic variation in these two PtoWRKY68 haplotypes conferred differential transcriptional regulatory activities and binding to the promoters of downstream abscisic acid (ABA) efflux and signaling genes. Overexpression of PtoWRKY68hap1 and PtoWRKY68hap2 in Arabidopsis (Arabidopsis thaliana) ameliorated the drought tolerance of two transgenic lines and increased ABA content by 42.7% and 14.3% compared to wild-type plants, respectively. Notably, PtoWRKY68hap1 (associated with drought tolerance) is ubiquitous in accessions in water-deficient environments, whereas the drought-sensitive allele PtoWRKY68hap2 is widely distributed in well-watered regions, consistent with the trends in local precipitation, suggesting that these alleles correspond to geographical adaptation in Populus. Moreover, quantitative trait loci analysis and an electrophoretic mobility shift assay showed that SHORT VEGETATIVE PHASE (PtoSVP.3) positively regulates the expression of PtoWRKY68 under drought stress. We propose a drought tolerance regulatory module in which PtoWRKY68 modulates ABA signaling and accumulation, providing insight into the genetic basis of drought tolerance in trees. Our findings will facilitate molecular breeding to improve the drought tolerance of forest trees.

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.

Thorough Characterization of ETHQB3.5, a QTL Involved in Melon Fruit Climacteric Behavior and Aroma Volatile Composition

The effect of the QTL involved in climacteric ripening ETHQB3.5 on the fruit VOC composition was studied using a set of Near-Isogenic Lines (NILs) containing overlapping introgressions from the Korean accession PI 16375 on the chromosome 3 in the climacteric 'Piel de Sapo' (PS) genetic background. ETHQB3.5 was mapped in an interval of 1.24 Mb that contained a NAC transcription factor. NIL fruits also showed differences in VOC composition belonging to acetate esters, non-acetate esters, and sulfur-derived families. Cosegregation of VOC composition (23 out of 48 total QTLs were mapped) and climacteric ripening was observed, suggesting a pleiotropic effect of ETHQB3.5. On the other hand, other VOCs (mainly alkanes, aldehydes, and ketones) showed a pattern of variation independent of ETHQB3.5 effects, indicating the presence of other genes controlling non-climacteric ripening VOCs. Network correlation analysis and hierarchical clustering found groups of highly correlated compounds and confirmed the involvement of the climacteric differences in compound classes and VOC differences. The modification of melon VOCs may be achieved with or without interfering with its physiological behavior, but it is likely that high relative concentrations of some type of ethylene-dependent esters could be achieved in climacteric cultivars.

Combined population transcriptomic and genomic analysis reveals cis-regulatory differentiation of non-coding RNAs in maize

Long intergenic non-coding RNA (lincRNA), cis-acting expression quantitative trait locus (cis-eQTL), maize, regulatory evolution. The law of genetic variation during domestication explains the evolutionary mechanism and provides a theoretical basis for improving existing varieties of maize. Previous studies focused on exploiting regulatory variations controlling the expression of protein-coding genes rather than of non-protein-coding genes. Here, we examined the genetic and evolutionary features of long non-coding RNAs from intergenic regions (long intergenic non-coding RNAs, lincRNAs) using population-scale transcriptome data and identified 1168 lincRNAs with cis-acting expression quantitative trait loci (cis-eQTLs). We found that lincRNAs are more likely to be regulated by cis-eQTLs, which exert stronger effects than the protein-coding genes. During maize domestication and improvement, upregulated alleles of lincRNAs, which originated from both standing variation and new mutation, accumulate more frequently and show larger effect sizes than the coding genes. A stronger signature of genetic differentiation was observed in their regulatory regions compared to those of randomly sampled lincRNAs. In addition, we found that cis-regulatory differentiation of lincRNAs is related to the sequence conservation of lincRNA transcripts. Non-conserved lincRNAs more tend to gain upregulated alleles and show a stronger relationship with selected traits than conserved lincRNAs between maize and its wild relatives. Our findings in maize improve the understanding of cis-regulatory variation in lincRNA genes during domestication and improvement and provide an effective approach for prioritizing candidates for further investigation.

eQTLs play critical roles in regulating gene expression and identifying key regulators in rice

The regulation of gene expression plays an essential role in both the phenotype and adaptation of plants. Transcriptome sequencing enables simultaneous identification of exonic variants and quantification of gene expression. Here, we sequenced the leaf transcriptomes of 287 rice accessions from around the world and obtained a total of 177 853 high-quality single nucleotide polymorphisms after filtering. Genome-wide association study identified 44 354 expression quantitative trait loci (eQTLs), which regulate the expression of 13 201 genes, as well as 17 local eQTL hotspots and 96 distant eQTL hotspots. Furthermore, a transcriptome-wide association study screened 21 candidate genes for starch content in the flag leaves at the heading stage. HS002 was identified as a significant distant eQTL hotspot with five downstream genes enriched for diterpene antitoxin synthesis. Co-expression analysis, eQTL analysis, and linkage mapping together demonstrated that bHLH026 acts as a key regulator to activate the expression of downstream genes. The transgenic assay revealed that bHLH026 is an important regulator of diterpenoid antitoxin synthesis and enhances the disease resistance of rice. These findings improve our knowledge of the regulatory mechanisms of gene expression variation and complex regulatory networks of the rice genome and will facilitate genetic improvement of cultivated rice varieties.

Integrating Phenotypic and Gene Expression Linkage Mapping to Dissect Rust Resistance in Chickling Pea

Rusts are among the most important foliar biotrophic fungal diseases in legumes. Lathyrus cicera crop can be severely damaged by Uromyces pisi, to which partial resistance has been identified. Nevertheless, the underlying genetic basis and molecular mechanisms of this resistance are poorly understood in L. cicera. To prioritise the causative variants controlling partial resistance to rust in L. cicera, a recombinant inbred line (RIL) population, segregating for response to this pathogen, was used to combine the detection of related phenotypic- and expression-quantitative trait loci (pQTLs and eQTLs, respectively). RILs' U. pisi disease severity (DS) was recorded in three independent screenings at seedling (growth chamber) and in one season of exploratory screening at adult plant stage (semi-controlled field conditions). A continuous DS range was observed in both conditions and used for pQTL mapping. Different pQTLs were identified under the growth chamber and semi-controlled field conditions, indicating a distinct genetic basis depending on the plant developmental stage and/or the environment. Additionally, the expression of nine genes related to U. pisi resistance in L. cicera was quantified for each RIL individual and used for eQTL mapping. One cis-eQTL and one trans-eQTL were identified controlling the expression variation of one gene related to rust resistance - a member of glycosyl hydrolase family 17. Integrating phenotyping, gene expression and linkage mapping allowed prioritising four candidate genes relevant for disease-resistance precision breeding involved in adaptation to biotic stress, cellular, and organelle homeostasis, and proteins directly involved in plant defence.

Genetic architecture of the metabolic pathway of salicylic acid biosynthesis in Populus

Salicylic acid (SA) is a vital hormone for adaptive responses to biotic and abiotic stresses, which facilitates growth-immunity trade-offs in plants. However, the genetic regulatory networks underlying the metabolic pathway of SA biosynthesis in perennial species remain unclear. Here, we integrated genome-wide association study (GWAS) with metabolite and expression profiling methodologies to dissect the genetic architecture of SA biosynthesis in Populus. First, we quantified nine intermediate metabolites of SA biosynthesis in 300 unrelated Populus tomentosa Carr. individuals. Then, we used a systematic genetic strategy to identify candidate genes for constructing the genetic regulatory network of SA biosynthesis. We focused on WRKY70, an efficient transcription factor, as the key causal gene in the regulatory network, and combined the novel genes coordinating the accumulation of SA. Finally, we identified eight GWAS signals and eight expression quantitative trait loci situated in a selective sweep, and showed the presence of large allele frequency differences among the three geographic populations, revealing that candidate genes subject to selection were involved in SA biosynthesis. This study provides an integrated strategy for dissecting the genetic architecture of the metabolic pathway of SA biosynthesis in Populus, thereby enhancing our understanding of genetic regulation of SA biosynthesis in trees, and accelerating marker-assisted breeding efforts toward high-resistance elite varieties of Populus.

VipariNama: RNA viral vectors to rapidly elucidate the relationship between gene expression and phenotype

Synthetic transcription factors have great promise as tools to help elucidate relationships between gene expression and phenotype by allowing tunable alterations of gene expression without genomic alterations of the loci being studied. However, the years-long timescales, high cost, and technical skill associated with plant transformation have limited their use. In this work, we developed a technology called VipariNama (ViN) in which vectors based on the tobacco rattle virus are used to rapidly deploy Cas9-based synthetic transcription factors and reprogram gene expression in planta. We demonstrate that ViN vectors can implement activation or repression of multiple genes systemically and persistently over several weeks in Nicotiana benthamiana, Arabidopsis (Arabidopsis thaliana), and tomato (Solanum lycopersicum). By exploring strategies including RNA scaffolding, viral vector ensembles, and viral engineering, we describe how the flexibility and efficacy of regulation can be improved. We also show how this transcriptional reprogramming can create predictable changes to metabolic phenotypes, such as gibberellin biosynthesis in N. benthamiana and anthocyanin accumulation in Arabidopsis, as well as developmental phenotypes, such as plant size in N. benthamiana, Arabidopsis, and tomato. These results demonstrate how ViN vector-based reprogramming of different aspects of gibberellin signaling can be used to engineer plant size in a range of plant species in a matter of weeks. In summary, ViN accelerates the timeline for generating phenotypes from over a year to just a few weeks, providing an attractive alternative to transgenesis for synthetic transcription factor-enabled hypothesis testing and crop engineering.

Identification of Distant Regulatory Elements Using Expression Quantitative Trait Loci Mapping for Heat-Responsive Genes in Oysters

Many marine ectotherms, especially those inhabiting highly variable intertidal zones, develop high phenotypic plasticity in response to rapid climate change by modulating gene expression levels. Herein, we examined the regulatory architecture of heat-responsive gene expression plasticity in oysters using expression quantitative trait loci (eQTL) analysis. Using a backcross family of Crassostrea gigas and its sister species Crassostrea angulata under acute stress, 56 distant regulatory regions accounting for 6–26.6% of the gene expression variation were identified for 19 heat-responsive genes. In total, 831 genes and 164 single nucleotide polymorphisms (SNPs) that could potentially regulate expression of the target genes were screened in the eQTL region. The association between three SNPs and the corresponding target genes was verified in an independent family. Specifically, Marker13973 was identified for heat shock protein (HSP) family A member 9 (HspA9). Ribosomal protein L10a (RPL10A) was detected approximately 2 kb downstream of the distant regulatory SNP. Further, Marker14346-48 and Marker14346-85 were in complete linkage disequilibrium and identified for autophagy-related gene 7 (ATG7). Nuclear respiratory factor 1 (NRF1) was detected approximately 3 kb upstream of the two SNPs. These results suggested regulatory relationships between RPL10A and HSPA9 and between NRF1 and ATG7. Our findings indicate that distant regulatory mutations play an important role in the regulation of gene expression plasticity by altering upstream regulatory factors in response to heat stress. The identified eQTLs provide candidate biomarkers for predicting the persistence of oysters under future climate change scenarios.

Cis- and Trans-Regulatory Variations in the Domestication of the Chili Pepper Fruit

The process of domestication requires the rapid transformation of the wild morphology into the cultivated forms that humans select for. This process often takes place through changes in the regulation of genes, yet, there is no definite pattern on the role of cis- and trans-acting regulatory variations in the domestication of the fruit among crops. Using allele-specific expression and network analyses, we characterized the regulatory patterns and the inheritance of gene expression in wild and cultivated accessions of chili pepper, a crop with remarkable fruit morphological variation. We propose that gene expression differences associated to the cultivated form are best explained by cis-regulatory hubs acting through trans-regulatory cascades. We show that in cultivated chili, the expression of genes associated with fruit morphology is partially recessive with respect to those in the wild relative, consistent with the hybrid fruit phenotype. Decreased expression of fruit maturation and growth genes in cultivated chili suggest that selection for loss-of-function took place in its domestication. Trans-regulatory changes underlie the majority of the genes showing regulatory divergence and had larger effect sizes on gene expression than cis-regulatory variants. Network analysis of selected cis-regulated genes, including ARP9 and MED25, indicated their interaction with many transcription factors involved in organ growth and fruit ripening. Differentially expressed genes linked to cis-regulatory variants and their interactions with downstream trans-acting genes have the potential to drive the morphological differences observed between wild and cultivated fruits and provide an attractive mechanism of morphological transformation during the domestication of the chili pepper.

Polymorphisms in cis-elements confer SAUR26 gene expression difference for thermo-response natural variation in Arabidopsis

The SAUR26 subfamily genes play an important role in conferring variations of thermo-responsiveness of growth architecture among natural accessions of Arabidopsis thaliana. The expression variations are critical for their activity variations, but how expression variations are generated is unknown. We identified genetic loci for gene expression variations through expression genome-wide association study (eGWAS) and investigated their mechanisms through molecular analyses. We found that cis elements are the major determinants for expression variations of SAUR26, SAUR27, and SAUR28. Polymorphisms in the promoter region likely impact PIF4 regulation while those at the 3'UTR affect mRNA stability to generate variations in SAUR26 expression levels. These polymorphisms also differentially affect the mRNA stability of SAUR26 at two temperatures. This study reveals two mechanisms involving cis elements in generating gene expression diversity, which is likely important for local adaptations in Arabidopsis natural accessions.

Identification of miRNA-eQTLs in maize mature leaf by GWAS

Background

MiRNAs play essential roles in plant development and response to biotic and abiotic stresses through interaction with their target genes. The expression level of miRNAs shows great variations among different plant accessions, developmental stages, and tissues. Little is known about the content within the plant genome contributing to the variations in plants. This study aims to identify miRNA expression-related quantitative trait loci (miR-QTLs) in the maize genome.

Results

The miRNA expression level from next generation sequencing (NGS) small RNA libraries derived from mature leaf samples of the maize panel (200 maize lines) was estimated as phenotypes, and maize Hapmap v3.2.1 was chosen as the genotype for the genome-wide association study (GWAS). A total of four significant miR-eQTLs were identified contributing to miR156k-5p, miR159a-3p, miR390a-5p and miR396e-5p, and all of them are trans-eQTLs. In addition, a strong positive coexpression of miRNA was found among five miRNA families. Investigation of the effects of these miRNAs on the expression levels and target genes provided evidence that miRNAs control the expression of their targets by suppression and enhancement.

Conclusions

These identified significant miR-eQTLs contribute to the diversity of miRNA expression in the maize penal at the developmental stages of mature leaves in maize, and the positive and negative regulation between miRNA and its target genes has also been uncovered.

Genome-wide expression quantitative trait locus studies facilitate isolation of causal genes controlling panicle structure

The morphology of rice (Oryza sativa L.) panicles is an important determinant of grain yield, and elucidation of the genetic control of panicle structure is very important for fulfilling the demand for high yield in breeding programs. In a quantitative trait locus (QTL) study using 82 backcross inbred lines (BILs) derived from Koshihikari and Habataki, 68 QTLs for 25 panicle morphological traits were identified. Gene expression profiling from inflorescence meristems of BILs was obtained. A combination of phenotypic QTL (pQTL) and expression QTL (eQTL) analysis revealed co-localization between pQTLs and eQTLs, consistent with significant correlations between phenotypic traits and gene expression levels. By combining pQTL and eQTL data, two genes were identified as controlling panicle structure: OsMADS18 modulates the average length of the primary rachis and OsFTL1 has pleiotropic effects on the total number of secondary rachides, number of grains per panicle, plant height and the length of flag leaves. Phenotypes were confirmed in RNA interference knocked-down plants and overexpressor lines. The combination of pQTL and eQTL analysis could facilitate identification of genes involved in rice panicle formation.

Genetic dissection of the gene coexpression network underlying photosynthesis in Populus

Photosynthesis is a key reaction that ultimately generates the carbohydrates needed to form woody tissues in trees. However, the genetic regulatory network of protein-encoding genes (PEGs) and regulatory noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), underlying the photosynthetic pathway is unknown. Here, we integrated data from coexpression analysis, association studies (additive, dominance and epistasis), and expression quantitative trait nucleotide (eQTN) mapping to dissect the causal variants and genetic interaction network underlying photosynthesis in Populus. We initially used 30 PEGs, 6 miRNAs and 12 lncRNAs to construct a coexpression network based on the tissue-specific gene expression profiles of 15 Populus samples. Then, we performed association studies using a natural population of 435 unrelated Populus tomentosa individuals, and identified 72 significant associations (P ≤ 0.001, q ≤ 0.05) with diverse additive and dominance patterns underlying photosynthesis-related traits. Analysis of epistasis and eQTNs revealed that the complex genetic interactions in the coexpression network contribute to phenotypes at various levels. Finally, we demonstrated that heterologously expressing the most highly linked gene (PtoPsbX1) in this network significantly improved photosynthesis in Arabidopsis thaliana, pointing to the functional role of PtoPsbX1 in the photosynthetic pathway. This study provides an integrated strategy for dissecting a complex genetic interaction network, which should accelerate marker-assisted breeding efforts to genetically improve woody plants.

Challenges of Translating Gene Regulatory Information into Agronomic Improvements

Improvement of agricultural species has exploited the genetic variation responsible for complex quantitative traits. Much of the functional variation is regulatory, in cis-regulatory elements and trans-acting factors that ultimately contribute to gene expression differences. However, the identification of gene regulatory network components that, when modulated, will increase plant productivity or resilience, is challenging, yet essential to provide increased predictive power for genome engineering approaches that are likely to benefit useful traits. Here, we discuss the opportunities and limitations of using data obtained from gene coexpression, transcription factor binding, and genome-wide association mapping analyses to predict regulatory interactions that impact crop improvement. It is apparent that a combination of information from these data types is necessary for the reliable identification and utilization of important regulatory interactions that underlie complex agronomic traits.

Compensatory trans-regulatory alleles minimizing variation in TDH3 expression are common within Saccharomyces cerevisiae

Heritable variation in gene expression is common within species. Much of this variation is due to genetic differences outside of the gene with altered expression and is trans-acting. This trans-regulatory variation is often polygenic, with individual variants typically having small effects, making the genetic architecture and evolution of trans-regulatory variation challenging to study. Consequently, key questions about trans-regulatory variation remain, including the variability of trans-regulatory variation within a species, how selection affects trans-regulatory variation, and how trans-regulatory variants are distributed throughout the genome and within a species. To address these questions, we isolated and measured trans-regulatory differences affecting TDH3 promoter activity among 56 strains of Saccharomyces cerevisiae, finding that trans-regulatory backgrounds varied approximately twofold in their effects on TDH3 promoter activity. Comparing this variation to neutral models of trans-regulatory evolution based on empirical measures of mutational effects revealed that despite this variability in the effects of trans-regulatory backgrounds, stabilizing selection has constrained trans-regulatory differences within this species. Using a powerful quantitative trait locus mapping method, we identified ∼100 trans-acting expression quantitative trait locus in each of three crosses to a common reference strain, indicating that regulatory variation is more polygenic than previous studies have suggested. Loci altering expression were located throughout the genome, and many loci were strain specific. This distribution and prevalence of alleles is consistent with recent theories about the genetic architecture of complex traits. In all mapping experiments, the nonreference strain alleles increased and decreased TDH3 promoter activity with similar frequencies, suggesting that stabilizing selection maintained many trans-acting variants with opposing effects. This variation may provide the raw material for compensatory evolution and larger scale regulatory rewiring observed in developmental systems drift among species.

Next-Generation Sequencing Accelerates Crop Gene Discovery

The identification and isolation of genes underlying quantitative trait loci (QTLs) associated with agronomic traits in crops have been recently accelerated thanks to next-generation sequencing (NGS)-based technologies combined with plant genetics. With NGS, various revisited genetic approaches, which benefited from higher marker density, have been elaborated. These approaches improved resolution in QTL position and assisted in determining functional causative variations in genes. Examples of QTLs/genes associated with agronomic traits in crops and identified using different strategies based on whole-genome sequencing (WGS)/whole-genome resequencing (WGR) or RNA-seq are presented and discussed in this review. More specifically, we summarize and illustrate how NGS boosted bulk-segregant analysis (BSA), expression profiling, and the construction of polymorphism databases to facilitate the detection of QTLs and causative genes.

Allele-specific expression and genetic determinants of transcriptomic variations in response to mild water deficit in tomato

Characterizing the natural diversity of gene expression across environments is an important step in understanding how genotype-by-environment interactions shape phenotypes. Here, we analyzed the impact of water deficit onto gene expression levels in tomato at the genome-wide scale. We sequenced the transcriptome of growing leaves and fruit pericarps at cell expansion stage in a cherry and a large fruited accession and their F₁ hybrid grown under two watering regimes. Gene expression levels were steadily affected by the genotype and the watering regime. Whereas phenotypes showed mostly additive inheritance, ~80% of the genes displayed non-additive inheritance. By comparing allele-specific expression (ASE) in the F₁ hybrid to the allelic expression in both parental lines, respectively, 3005 genes in leaf and 2857 genes in fruit deviated from 1:1 ratio independently of the watering regime. Among these genes, ~55% were controlled by cis factors, ~25% by trans factors and ~20% by a combination of both types of factors. A total of 328 genes in leaf and 113 in fruit exhibited significant ASE-by-watering regime interaction, among which ~80% presented trans-by-watering regime interaction, suggesting a response to water deficit mediated through a majority of trans-acting loci in tomato. We cross-validated the expression levels of 274 transcripts in fruit and leaves of 124 recombinant inbred lines (RILs) and identified 163 expression quantitative trait loci (eQTLs) mostly confirming the divergences identified by ASE. Combining phenotypic and expression data, we observed a complex network of variation between genes encoding enzymes involved in the sugar metabolism.

GWAS with Heterogeneous Data: Estimating the Fraction of Phenotypic Variation Mediated by Gene Expression Data

Intermediate phenotypes such as gene expression values can be used to elucidate the mechanisms by which genetic variation causes phenotypic variation, but jointly analyzing such heterogeneous data are far from trivial. Here we extend a so-called mediation model to handle the confounding effects of genetic background, and use it to analyze flowering time variation in Arabidopsis thaliana, focusing in particular on the central role played by the key regulator FLOWERING TIME LOCUS C (FLC). FLC polymorphism and FLC expression are both strongly correlated with flowering time variation, but the effect of the former is only partly mediated through the latter. Furthermore, the latter also reflects genetic background effects. We demonstrate that it is possible to partition these effects, shedding light on the complex regulatory network that underlies flowering time variation.

QTLs and eQTLs mapping related to citrandarins' resistance to citrus gummosis disease

Background

Phytophthora nicotianae Breda de Haan (Phytophthora parasitica Dastur) causes severe damage to citrus crops worldwide. A population of citrandarins was created from the cross between the susceptible parent Citrus sunki Hort. Ex Tan. and the resistant parent Poncirus trifoliata (L.) Raf. cv. Rubidoux, both parents and two reference rootstocks (Rangpur lime and Swingle citrumelo) were grafted in a greenhouse on Rangpur lime. Inoculations were performed at 10 cm and 15 cm above the grafting region and the resulting lesions were evaluated by measuring the lesion length 60 days after inoculation. As control, non-inoculated plants of each genotype were used. In addition, we evaluated the expression of 19 candidate genes involved in citrus defense response 48 h after pathogen infection by quantitative Real-Time PCR (qPCR). We mapped genomic regions of Quantitative Trait Loci (QTLs) and Expression Quantitative Trait Loci (eQTLs) associated with resistance to P. parasitica in the linkage groups (LGs) of the previously constructed maps of C. sunki and P. trifoliata.

Results

We found disease severity differences among the generated hybrids, with lesion lengths varying from 1.15 to 11.13 mm. The heritability of the character was 65%. These results indicate that there is a great possibility of success in the selection of resistant hybrids within this experiment. The analysis of gene expression profile demonstrated a great variation of responses regarding the activation of plant defense pathways, indicating that citrandarins have several defense strategies to control oomycete infection. The information of the phenotypic and gene expression data made possible to detect genomic regions associated with resistance. Three QTLs and 84 eQTLs were detected in the linkage map of P. trifoliata, while one QTL and 110 eQTLs were detected in C. sunki.

Conclusions

This is the first study to use eQTLs mapping in the Phytophthora-citrus interaction. Our results from the QTLs and eQTLs mapping allow us to conclude that the resistance of some citrandarins to the infection by P. parasitica is due to a favorable combination of QTLs and eQTLs transmitted by both parents.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4888-2) contains supplementary material, which is available to authorized users.

GPD1 and ADH3 Natural Variants Underlie Glycerol Yield Differences in Wine Fermentation

Glycerol is one of the most important by-products of alcohol fermentation, and depending on its concentration it can contribute to wine flavor intensity and aroma volatility. Here, we evaluated the potential of utilizing the natural genetic variation of non-coding regions in budding yeast to identify allelic variants that could modulate glycerol phenotype during wine fermentation. For this we utilized four Saccharomyces cerevisiae strains (WE - Wine/European, SA – Sake, NA – North American, and WA – West African), which were previously profiled for genome-wide Allele Specific Expression (ASE) levels. The glycerol yields under Synthetic Wine Must (SWM) fermentations differed significantly between strains; WA produced the highest glycerol yields while SA produced the lowest yields. Subsequently, from our ASE database, we identified two candidate genes involved in alcoholic fermentation pathways, ADH3 and GPD1, exhibiting significant expression differences between strains. A reciprocal hemizygosity assay demonstrated that hemizygotes expressing GPD1^WA, GPD1^SA, ADH3^WA and ADH3^SA alleles had significantly greater glycerol yields compared to GPD1^WE and ADH3^WE. We further analyzed the gene expression profiles for each GPD1 variant under SWM, demonstrating that the expression of GPD1^WE occurred earlier and was greater compared to the other alleles. This result indicates that the level, timing, and condition of expression differ between regulatory regions in the various genetic backgrounds. Furthermore, promoter allele swapping demonstrated that these allele expression patterns were transposable across genetic backgrounds; however, glycerol yields did not differ between wild type and modified strains, suggesting a strong trans effect on GPD1 gene expression. In this line, Gpd1 protein levels in parental strains, particularly Gpd1p^WE, did not necessarily correlate with gene expression differences, but rather with glycerol yield where low Gpd1p^WE levels were detected. This suggests that GPD1^WE is influenced by recessive negative post-transcriptional regulation which is absent in the other genetic backgrounds. This dissection of regulatory mechanisms in GPD1 allelic variants demonstrates the potential to exploit natural alleles to improve glycerol production in wine fermentation and highlights the difficulties of trait improvement due to alternative trans-regulation and gene-gene interactions in the different genetic background.

Deciphering genetic factors that determine melon fruit-quality traits using RNA-Seq-based high-resolution QTL and eQTL mapping

Combined quantitative trait loci (QTL) and expression-QTL (eQTL) mapping analysis was performed to identify genetic factors affecting melon (Cucumis melo) fruit quality, by linking genotypic, metabolic and transcriptomic data from a melon recombinant inbred line (RIL) population. RNA sequencing (RNA-Seq) of fruit from 96 RILs yielded a highly saturated collection of > 58 000 single-nucleotide polymorphisms, identifying 6636 recombination events that separated the genome into 3663 genomic bins. Bin-based QTL analysis of 79 RILs and 129 fruit-quality traits affecting taste, aroma and color resulted in the mapping of 241 QTL. Thiol acyltransferase (CmThAT1) gene was identified within the QTL interval of its product, S-methyl-thioacetate, a key component of melon fruit aroma. Metabolic activity of CmThAT1-encoded protein was validated in bacteria and in vitro. QTL analysis of flesh color intensity identified a candidate white-flesh gene (CmPPR1), one of two major loci determining fruit flesh color in melon. CmPPR1 encodes a member of the pentatricopeptide protein family, involved in processing of RNA in plastids, where carotenoid and chlorophyll pigments accumulate. Network analysis of > 12 000 eQTL mapped for > 8000 differentially expressed fruit genes supported the role of CmPPR1 in determining the expression level of plastid targeted genes. We highlight the potential of RNA-Seq-based QTL analysis of small to moderate size, advanced RIL populations for precise marker-assisted breeding and gene discovery. We provide the following resources: a RIL population genotyped with a unique set of SNP markers, confined genomic segments that harbor QTL governing 129 traits and a saturated set of melon eQTLs.

Genome-wide Analysis of Transcriptional Variability in a Large Maize-Teosinte Population

Gene expression regulation plays an important role in controlling plant phenotypes and adaptation. Here, we report a comprehensive assessment of gene expression variation through the transcriptome analyses of a large maize-teosinte experimental population. Genome-wide mapping identified 25 660 expression quantitative trait loci (eQTL) for 17 311 genes, capturing an unprecedented range of expression variation. We found that local eQTL were more frequently mapped to adjacent genes, displaying a mode of expression piggybacking, which consequently created co-regulated gene clusters. Genes within the co-regulated gene clusters tend to have relevant functions and shared chromatin modifications. Distant eQTL formed 125 significant distant eQTL hotspots with their targets significantly enriched in specific functional categories. By integrating different sources of information, we identified putative trans- regulators for a variety of metabolic pathways. We demonstrated that the bHLH transcription factor R1 and hexokinase HEX9 might act as crucial regulators for flavonoid biosynthesis and glycolysis, respectively. Moreover, we showed that domestication or improvement has significantly affected global gene expression, with many genes targeted by selection. Of particular interest, the Bx genes for benzoxazinoid biosynthesis may have undergone coordinated cis-regulatory divergence between maize and teosinte, and a transposon insertion that inactivates Bx12 was under strong selection as maize spread into temperate environments with a distinct herbivore community.

Genetic basis of mycotoxin susceptibility differences between budding yeast isolates

Micophenolic acid (MPA) is an immunosuppressant mycotoxin which impairs yeast cell growth to variable degrees depending on the genetic background. Such variation could have emerged from several phenomena, including MPA gene resistance mutations and variations in copy number and localisation of resistance genes. To test this, we evaluated MPA susceptibility in four S. cerevisiae isolates and genetically dissected variation through the identification of Quantitative Trait Loci. Via linkage analysis we identified six QTLs, majority of which were located within subtelomeres and co-localised with IMD2, an inosine monophosphate dehydrogenase previously identified underlying MPA drug resistance in yeast cells. From chromosome end disruption and bioinformatics analysis, it was found that the subtelomere localisation of IMD2 within chromosome ends is variable depending on the strain, demonstrating the influence of IMD2 on the natural variation in yeast MPA susceptibility. Furthermore, GxE gene expression analysis of strains exhibiting opposite phenotypes indicated that ribosome biogenesis, RNA transport, and purine biosynthesis were impaired in strains most susceptible to MPA toxicity. Our results demonstrate that natural variation can be exploited to better understand the molecular mechanisms underlying mycotoxin susceptibility in eukaryote cells and demonstrate the role of subtelomeric regions in mediating interactions with the environment.

Constraints on eQTL Fine Mapping in the Presence of Multisite Local Regulation of Gene Expression

Expression quantitative trait locus (eQTL) detection has emerged as an important tool for unraveling of the relationship between genetic risk factors and disease or clinical phenotypes. Most studies use single marker linear regression to discover primary signals, followed by sequential conditional modeling to detect secondary genetic variants affecting gene expression. However, this approach assumes that functional variants are sparsely distributed and that close linkage between them has little impact on estimation of their precise location and the magnitude of effects. We describe a series of simulation studies designed to evaluate the impact of linkage disequilibrium (LD) on the fine mapping of causal variants with typical eQTL effect sizes. In the presence of multisite regulation, even though between 80 and 90% of modeled eSNPs associate with normally distributed traits, up to 10% of all secondary signals could be statistical artifacts, and at least 5% but up to one-quarter of credible intervals of SNPs within r² > 0.8 of the peak may not even include a causal site. The Bayesian methods eCAVIAR and DAP (Deterministic Approximation of Posteriors) provide only modest improvement in resolution. Given the strong empirical evidence that gene expression is commonly regulated by more than one variant, we conclude that the fine mapping of causal variants needs to be adjusted for multisite influences, as conditional estimates can be highly biased by interference among linked sites, but ultimately experimental verification of individual effects is needed. Presumably similar conclusions apply not just to eQTL mapping, but to multisite influences on fine mapping of most types of quantitative trait.

Regulatory Architecture of Gene Expression Variation in the Threespine Stickleback Gasterosteus aculeatus

Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats.

eQTLs Regulating Transcript Variations Associated with Rapid Internode Elongation in Deepwater Rice

To avoid low oxygen, oxygen deficiency or oxygen deprivation, deepwater rice cultivated in flood planes can develop elongated internodes in response to submergence. Knowledge of the gene regulatory networks underlying rapid internode elongation is important for an understanding of the evolution and adaptation of major crops in response to flooding. To elucidate the genetic and molecular basis controlling their deepwater response we used microarrays and performed expression quantitative trait loci (eQTL) and phenotypic QTL (phQTL) analyses of internode samples of 85 recombinant inbred line (RIL) populations of non-deepwater (Taichung 65)- and deepwater rice (Bhadua). After evaluating the phenotypic response of the RILs exposed to submergence, confirming the genotypes of the populations, and generating 188 genetic markers, we identified 10,047 significant eQTLs comprised of 2,902 cis-eQTLs and 7,145 trans-eQTLs and three significant eQTL hotspots on chromosomes 1, 4, and 12 that affect the expression of many genes. The hotspots on chromosomes 1 and 4 located at different position from phQTLs detected in this study and other previous studies. We then regarded the eQTL hotspots as key regulatory points to infer causal regulatory networks of deepwater response including rapid internode elongation. Our results suggest that the downstream regulation of the eQTL hotspots on chromosomes 1 and 4 is independent, and that the target genes are partially regulated by SNORKEL1 and SNORKEL2 genes (SK1/2), key ethylene response factors. Subsequent bioinformatic analyses, including gene ontology-based annotation and functional enrichment analysis and promoter enrichment analysis, contribute to enhance our understanding of SK1/2-dependent and independent pathways. One remarkable observation is that the functional categories related to photosynthesis and light signaling are significantly over-represented in the candidate target genes of SK1/2. The combined results of these investigations together with genetical genomics approaches using structured populations with a deepwater response are also discussed in the context of current molecular models concerning the rapid internode elongation in deepwater rice. This study provides new insights into the underlying genetic architecture of gene expression regulating the response to flooding in deepwater rice and will be an important community resource for analyses on the genetic basis of deepwater responses.

Evaluation of the utility of gene expression and metabolic information for genomic prediction in maize

Predictive ability derived from gene expression and metabolic information was evaluated using genomic prediction methods based on datasets from a public maize panel. With the rapid development of high throughput biological technologies, information from gene expression and metabolites has received growing attention in plant genetics and breeding. In this study, we evaluated the utility of gene expression and metabolic information for genomic prediction using data obtained from a maize diversity panel. Our results show that, when used as predictor variables, gene expression levels and metabolite abundances provided reasonable predictive abilities relative to those based on genetic markers, although these values were not as large as those with genetic markers. Integrating gene expression levels and metabolite abundances with genetic markers significantly improved predictive abilities in comparison to the benchmark genomic best linear unbiased prediction model using genome-wide markers only. Predictive abilities based on gene expression and metabolites were trait-specific and were affected by the time of measurement and tissue samples as well as the number of genes and metabolites included in the model. In general, our results suggest that, rather than being conventionally used as intermediate phenotypes, gene expression and metabolic information can be used as predictors for genomic prediction and help improve genetic gains for complex traits in breeding programs.

Natural gene expression variation studies in yeast

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

A Catalog of Regulatory Sequences for Trait Gene for the Genome Editing of Wheat

Wheat has been cultivated for 10000 years and ever since the origin of hexaploid wheat it has been exempt from natural selection. Instead, it was under the constant selective pressure of human agriculture from harvest to sowing during every year, producing a vast array of varieties. Wheat has been adopted globally, accumulating variation for genes involved in yield traits, environmental adaptation and resistance. However, one small but important part of the wheat genome has hardly changed: the regulatory regions of both the x- and y-type high molecular weight glutenin subunit (HMW-GS) genes, which are alone responsible for approximately 12% of the grain protein content. The phylogeny of the HMW-GS regulatory regions of the Triticeae demonstrates that a genetic bottleneck may have led to its decreased diversity during domestication and the subsequent cultivation. It has also highlighted the fact that the wild relatives of wheat may offer an unexploited genetic resource for the regulatory region of these genes. Significant research efforts have been made in the public sector and by international agencies, using wild crosses to exploit the available genetic variation, and as a result synthetic hexaploids are now being utilized by a number of breeding companies. However, a newly emerging tool of genome editing provides significantly improved efficiency in exploiting the natural variation in HMW-GS genes and incorporating this into elite cultivars and breeding lines. Recent advancement in the understanding of the regulation of these genes underlines the needs for an overview of the regulatory elements for genome editing purposes.

Exploiting budding yeast natural variation for industrial processes

For the last two decades, the natural variation of the yeast Saccharomyces cerevisiae has been massively exploited with the aim of understanding ecological and evolutionary processes. As a result, many new genetic variants have been uncovered, providing a large catalogue of alleles underlying complex traits. These alleles represent a rich genetic resource with the potential to provide new strains that can cope with the growing demands of industrial fermentation processes. When surveyed in detail, several of these variants have proven useful in wine and beer industries by improving nitrogen utilisation, fermentation kinetics, ethanol production, sulphite resistance and aroma production. Here, I illustrate how allele-specific expression and polymorphisms within the coding region of GDB1 underlie fermentation kinetic differences in synthetic wine must. Nevertheless, the genetic basis of how GDB1 variants and other natural alleles interact in foreign genetic backgrounds remains unclear. Further studies in large sets of strains, recombinant hybrids and multiple parental pairs will broaden our knowledge of the molecular and genetic basis of trait adaptation for utilisation in applied and industrial processes.

Targeted Proteomics Approach for Precision Plant Breeding

Selected reaction monitoring (SRM) is a targeted mass spectrometry technique that enables precise quantitation of hundreds of peptides in a single run. This technique provides new opportunities for multiplexed protein biomarker measurements. For precision plant breeding, DNA-based markers have been used extensively, but the potential of protein biomarkers has not been exploited. In this work, we developed an SRM marker panel with assays for 104 potato (Solanum tuberosum) peptides selected using univariate and multivariate statistics. Thereafter, using random forest classification, the prediction markers were identified for Phytopthora infestans resistance in leaves, P. infestans resistance in tubers, and plant yield in potato leaf secretome samples. The results suggest that the marker panel has the predictive potential for three traits, two of which have no commercial DNA markers so far. Furthermore, the marker panel was also tested and found to be applicable to potato clones not used during the marker development. The proposed workflow is thus a proof-of-concept for targeted proteomics as an efficient readout in accelerated breeding for complex and agronomically important traits.

Learning from Co-expression Networks: Possibilities and Challenges

Plants are fascinating and complex organisms. A comprehensive understanding of the organization, function and evolution of plant genes is essential to disentangle important biological processes and to advance crop engineering and breeding strategies. The ultimate aim in deciphering complex biological processes is the discovery of causal genes and regulatory mechanisms controlling these processes. The recent surge of omics data has opened the door to a system-wide understanding of the flow of biological information underlying complex traits. However, dealing with the corresponding large data sets represents a challenging endeavor that calls for the development of powerful bioinformatics methods. A popular approach is the construction and analysis of gene networks. Such networks are often used for genome-wide representation of the complex functional organization of biological systems. Network based on similarity in gene expression are called (gene) co-expression networks. One of the major application of gene co-expression networks is the functional annotation of unknown genes. Constructing co-expression networks is generally straightforward. In contrast, the resulting network of connected genes can become very complex, which limits its biological interpretation. Several strategies can be employed to enhance the interpretation of the networks. A strategy in coherence with the biological question addressed needs to be established to infer reliable networks. Additional benefits can be gained from network-based strategies using prior knowledge and data integration to further enhance the elucidation of gene regulatory relationships. As a result, biological networks provide many more applications beyond the simple visualization of co-expressed genes. In this study we review the different approaches for co-expression network inference in plants. We analyse integrative genomics strategies used in recent studies that successfully identified candidate genes taking advantage of gene co-expression networks. Additionally, we discuss promising bioinformatics approaches that predict networks for specific purposes.

Whole genome sequences in pulse crops: a global community resource to expedite translational genomics and knowledge-based crop improvement

Unprecedented developments in legume genomics over the last decade have resulted in the acquisition of a wide range of modern genomic resources to underpin genetic improvement of grain legumes. The genome enabled insights direct investigators in various ways that primarily include unearthing novel structural variations, retrieving the lost genetic diversity, introducing novel/exotic alleles from wider gene pools, finely resolving the complex quantitative traits and so forth. To this end, ready availability of cost-efficient and high-density genotyping assays allows genome wide prediction to be increasingly recognized as the key selection criterion in crop breeding. Further, the high-dimensional measurements of agronomically significant phenotypes obtained by using new-generation screening techniques will empower reference based resequencing as well as allele mining and trait mapping methods to comprehensively associate genome diversity with the phenome scale variation. Besides stimulating the forward genetic systems, accessibility to precisely delineated genomic segments reveals novel candidates for reverse genetic techniques like targeted genome editing. The shifting paradigm in plant genomics in turn necessitates optimization of crop breeding strategies to enable the most efficient integration of advanced omics knowledge and tools. We anticipate that the crop improvement schemes will be bolstered remarkably with rational deployment of these genome-guided approaches, ultimately resulting in expanded plant breeding capacities and improved crop performance.

From association to prediction: statistical methods for the dissection and selection of complex traits in plants

Quantification of genotype-to-phenotype associations is central to many scientific investigations, yet the ability to obtain consistent results may be thwarted without appropriate statistical analyses. Models for association can consider confounding effects in the materials and complex genetic interactions. Selecting optimal models enables accurate evaluation of associations between marker loci and numerous phenotypes including gene expression. Significant improvements in QTL discovery via association mapping and acceleration of breeding cycles through genomic selection are two successful applications of models using genome-wide markers. Given recent advances in genotyping and phenotyping technologies, further refinement of these approaches is needed to model genetic architecture more accurately and run analyses in a computationally efficient manner, all while accounting for false positives and maximizing statistical power.

Extensive cis-regulatory variation robust to environmental perturbation in Arabidopsis

cis- and trans-acting factors affect gene expression and responses to environmental conditions. However, for most plant systems, we lack a comprehensive map of these factors and their interaction with environmental variation. Here, we examined allele-specific expression (ASE) in an F1 hybrid to study how alleles from two Arabidopsis thaliana accessions affect gene expression. To investigate the effect of the environment, we used drought stress and developed a variance component model to estimate the combined genetic contributions of cis- and trans-regulatory polymorphisms, environmental factors, and their interactions. We quantified ASE for 11,003 genes, identifying 3318 genes with consistent ASE in control and stress conditions, demonstrating that cis-acting genetic effects are essentially robust to changes in the environment. Moreover, we found 1618 genes with genotype x environment (GxE) interactions, mostly cis x E interactions with magnitude changes in ASE. We found fewer trans x E interactions, but these effects were relatively less robust across conditions, showing more changes in the direction of the effect between environments; this confirms that trans-regulation plays an important role in the response to environmental conditions. Our data provide a detailed map of cis- and trans-regulation and GxE interactions in A. thaliana, laying the ground for mechanistic investigations and studies in other plants and environments.

A network perspective on nitrogen metabolism from model to crop plants using integrated 'omics' approaches

Nitrogen (N), as an essential element in amino acids, nucleotides, and proteins, is a key factor in plant growth and development. Omics approaches such as metabolomics and transcriptomics have become a promising way to inspect complex network interactions in N metabolism and can be used for monitoring the uptake and regulation, translocation, and remobilization of N. In this review, the authors highlight recent progress in omics approaches, including transcript profiling using microarrays and deep sequencing, and show recent technical developments in metabolite profiling for N studies. Further, network analysis studies including network inference methods with correlations, information-theoretic measures, and a network concept to examine gene expression clusters in relation to N regulatory systems in plants are introduced, and integrating network inference methods and integrated networks using multiple omics data are discussed. Finally, this review summarizes recent omics application examples using metabolite and/or transcript profiling analysis to elucidate the regulation of N metabolism and signalling and the coordination of N and carbon metabolism in model plants (Arabidopsis and rice), crops (tomato, maize, and legumes), and trees (Populus).

Elucidating the molecular responses of apple rootstock resistant to ARD pathogens: challenges and opportunities for development of genomics-assisted breeding tools

Apple replant disease (ARD) is a major limitation to the establishment of economically viable orchards on replant sites due to the buildup and long-term survival of pathogen inoculum. Several soilborne necrotrophic fungi and oomycetes are primarily responsible for ARD, and symptoms range from serious inhibition of growth to the death of young trees. Chemical fumigation has been the primary method used for control of ARD, and manipulating soil microbial ecology to reduce pathogen density and aggressiveness is being investigated. To date, innate resistance of apple rootstocks as a means to control this disease has not been carefully explored, partly due to the complex etiology and the difficulty in phenotyping the disease resistance. Molecular defense responses of plant roots to soilborne necrotrophic pathogens are largely elusive, although considerable progress has been achieved using foliar disease systems. Plant defense responses to necrotrophic pathogens consist of several interacting modules and operate as a network. Upon pathogen detection by plants, cellular signals such as the oscillation of Ca(2+) concentration, reactive oxygen species (ROS) burst and protein kinase activity, lead to plant hormone biosynthesis and signaling. Jasmonic acid (JA) and ethylene (ET) are known to be fundamental to the induction and regulation of defense mechanisms toward invading necrotrophic pathogens. Complicated hormone crosstalk modulates the fine-tuning of transcriptional reprogramming and metabolic redirection, resulting in production of antimicrobial metabolites, enzyme inhibitors and cell wall refortification to restrict further pathogenesis. Transcriptome profiling of apple roots in response to inoculation with Pythium ultimum demonstrated that there is a high degree of conservation regarding the molecular framework of defense responses compared with those observed with foliar tissues. It is conceivable that the timing and intensity of genotype-specific defense responses may lead to different outcomes between rootstocks in response to invasion by necrotrophic pathogens. Elucidation of host defense mechanisms is critical in developing molecular tools for genomics-assisted breeding of resistant apple rootstocks. Due to their perennial nature, use of resistant rootstocks as a component for disease management might offer a durable and cost-effective benefit to tree performance than the standard practice of soil fumigation for control of ARD.

Exome resequencing reveals signatures of demographic and adaptive processes across the genome and range of black cottonwood (Populus trichocarpa)

Extant variation in temperate and boreal plant species has been influenced by both demographic histories associated with Pleistocene glacial cycles and adaptation to local climate. We used sequence capture to investigate the role of these neutral and adaptive processes in shaping diversity in black cottonwood (Populus trichocarpa). Nucleotide diversity and Tajima's D were lowest at replacement sites and highest at intergenic sites, while LD showed the opposite pattern. With samples grouped into three populations arrayed latitudinally, effective population size was highest in the north, followed by south and centre, and LD was highest in the south followed by the north and centre, suggesting a possible northern glacial refuge. FST outlier analysis revealed that promoter, 5'-UTR and intronic sites were enriched for outliers compared with coding regions, while no outliers were found among intergenic sites. Codon usage bias was evident, and genes with synonymous outliers had 30% higher average expression compared with genes containing replacement outliers. These results suggest divergent selection related to regulation of gene expression is important to local adaptation in P. trichocarpa. Finally, within-population selective sweeps were much more pronounced in the central population than in putative northern and southern refugia, which may reflect the different demographic histories of the populations and concomitant effects on signatures of genetic hitchhiking from standing variation.

Genetical and comparative genomics of Brassica under altered Ca supply identifies Arabidopsis Ca-transporter orthologs

Although Ca transport in plants is highly complex, the overexpression of vacuolar Ca(2+) transporters in crops is a promising new technology to improve dietary Ca supplies through biofortification. Here, we sought to identify novel targets for increasing plant Ca accumulation using genetical and comparative genomics. Expression quantitative trait locus (eQTL) mapping to 1895 cis- and 8015 trans-loci were identified in shoots of an inbred mapping population of Brassica rapa (IMB211 × R500); 23 cis- and 948 trans-eQTLs responded specifically to altered Ca supply. eQTLs were screened for functional significance using a large database of shoot Ca concentration phenotypes of Arabidopsis thaliana. From 31 Arabidopsis gene identifiers tagged to robust shoot Ca concentration phenotypes, 21 mapped to 27 B. rapa eQTLs, including orthologs of the Ca(2+) transporters At-CAX1 and At-ACA8. Two of three independent missense mutants of BraA.cax1a, isolated previously by targeting induced local lesions in genomes, have allele-specific shoot Ca concentration phenotypes compared with their segregating wild types. BraA.CAX1a is a promising target for altering the Ca composition of Brassica, consistent with prior knowledge from Arabidopsis. We conclude that multiple-environment eQTL analysis of complex crop genomes combined with comparative genomics is a powerful technique for novel gene identification/prioritization.

Natural occurring epialleles determine vitamin E accumulation in tomato fruits

Vitamin E (VTE) content is a low heritability nutritional trait for which the genetic determinants are poorly understood. Here, we focus on a previously detected major tomato VTE quantitative trait loci (QTL; mQTL(9-2-6)) and identify the causal gene as one encoding a 2-methyl-6-phytylquinol methyltransferase (namely VTE3(1)) that catalyses one of the final steps in the biosynthesis of γ- and α-tocopherols, which are the main forms of VTE. By reverse genetic approaches, expression analyses, siRNA profiling and DNA methylation assays, we demonstrate that mQTL(9-2-6) is an expression QTL associated with differential methylation of a SINE retrotransposon located in the promoter region of VTE3(1). Promoter DNA methylation can be spontaneously reverted leading to different epialleles affecting VTE3(1) expression and VTE content in fruits. These findings indicate therefore that naturally occurring epialleles are responsible for regulation of a nutritionally important metabolic QTL and provide direct evidence of a role for epigenetics in the determination of agronomic traits.

Sustainable harvest: managing plasticity for resilient crops

Maintaining crop production to feed a growing world population is a major challenge for this period of rapid global climate change. No consistent conceptual or experimental framework for crop plants integrates information at the levels of genome regulation, metabolism, physiology and response to growing environment. An important role for plasticity in plants is assisting in homeostasis in response to variable environmental conditions. Here, we outline how plant plasticity is facilitated by epigenetic processes that modulate chromatin through dynamic changes in DNA methylation, histone variants, small RNAs and transposable elements. We present examples of plant plasticity in the context of epigenetic regulation of developmental phases and transitions and map these onto the key stages of crop establishment, growth, floral initiation, pollination, seed set and maturation of harvestable product. In particular, we consider how feedback loops of environmental signals and plant nutrition affect plant ontogeny. Recent advances in understanding epigenetic processes enable us to take a fresh look at the crosstalk between regulatory systems that confer plasticity in the context of crop development. We propose that these insights into genotype × environment (G × E) interaction should underpin development of new crop management strategies, both in terms of information-led agronomy and in recognizing the role of epigenetic variation in crop breeding.