Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits

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.

Flavonoids Modulate the Accumulation of Toxins From Aspergillus flavus in Maize Kernels

Aspergillus flavus is an opportunistic fungal pathogen capable of producing aflatoxins, potent carcinogenic toxins that accumulate in maize kernels after infection. To better understand the molecular mechanisms of maize resistance to A. flavus growth and aflatoxin accumulation, we performed a high-throughput transcriptomic study in situ using maize kernels infected with A. flavus strain 3357. Three maize lines were evaluated: aflatoxin-contamination resistant line TZAR102, semi-resistant MI82, and susceptible line Va35. A modified genotype-environment association method (GEA) used to detect loci under selection via redundancy analysis (RDA) was used with the transcriptomic data to detect genes significantly influenced by maize line, fungal treatment, and duration of infection. Gene ontology enrichment analysis of genes highly expressed in infected kernels identified molecular pathways associated with defense responses to fungi and other microbes such as production of pathogenesis-related (PR) proteins and lipid bilayer formation. To further identify novel genes of interest, we incorporated genomic and phenotypic field data from a genome wide association analysis with gene expression data, allowing us to detect significantly expressed quantitative trait loci (eQTL). These results identified significant association between flavonoid biosynthetic pathway genes and infection by A. flavus. In planta fungal infections showed that the resistant line, TZAR102, has a higher fold increase of the metabolites naringenin and luteolin than the susceptible line, Va35, when comparing untreated and fungal infected plants. These results suggest flavonoids contribute to plant resistance mechanisms against aflatoxin contamination through modulation of toxin accumulation in maize kernels.

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.

RIL-StEp: epistasis analysis of rice recombinant inbred lines reveals candidate interacting genes that control seed hull color and leaf chlorophyll content

Characterizing epistatic gene interactions is fundamental for understanding the genetic architecture of complex traits. However, due to the large number of potential gene combinations, detecting epistatic gene interactions is computationally demanding. A simple, easy-to-perform method for sensitive detection of epistasis is required. Due to their homozygous nature, use of recombinant inbred lines excludes the dominance effect of alleles and interactions involving heterozygous genotypes, thereby allowing detection of epistasis in a simple and interpretable model. Here, we present an approach called RIL-StEp (recombinant inbred lines stepwise epistasis detection) to detect epistasis using single-nucleotide polymorphisms in the genome. We applied the method to reveal epistasis affecting rice (Oryza sativa) seed hull color and leaf chlorophyll content and successfully identified pairs of genomic regions that presumably control these phenotypes. This method has the potential to improve our understanding of the genetic architecture of various traits of crops and other organisms.

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.

A systems biology approach uncovers a gene co-expression network associated with cell wall degradability in maize

Understanding the mechanisms triggering variation of cell wall degradability is a prerequisite to improving the energy value of lignocellulosic biomass for animal feed or biorefinery. Here, we implemented a multiscale systems approach to shed light on the genetic basis of cell wall degradability in maize. We demonstrated that allele replacement in two pairs of near-isogenic lines at a region encompassing a major quantitative trait locus (QTL) for cell wall degradability led to phenotypic variation of a similar magnitude and sign to that expected from a QTL analysis of cell wall degradability in the F271 × F288 recombinant inbred line progeny. Using DNA sequences within the QTL interval of both F271 and F288 inbred lines and Illumina RNA sequencing datasets from internodes of the selected near-isogenic lines, we annotated the genes present in the QTL interval and provided evidence that allelic variation at the introgressed QTL region gives rise to coordinated changes in gene expression. The identification of a gene co-expression network associated with cell wall-related trait variation revealed that the favorable F288 alleles exploit biological processes related to oxidation-reduction, regulation of hydrogen peroxide metabolism, protein folding and hormone responses. Nested in modules of co-expressed genes, potential new cell-wall regulators were identified, including two transcription factors of the group VII ethylene response factor family, that could be exploited to fine-tune cell wall degradability. Overall, these findings provide new insights into the regulatory mechanisms by which a major locus influences cell wall degradability, paving the way for its map-based cloning in maize.

Molecular and physiological control of adventitious rooting in cuttings: phytohormone action meets resource allocation

BACKGROUND

Adventitious root (AR) formation in excised plant parts is a bottleneck for survival of isolated plant fragments. AR formation plays an important ecological role and is a critical process in cuttings for the clonal propagation of horticultural and forestry crops. Therefore, understanding the regulation of excision-induced AR formation is essential for sustainable and efficient utilization of plant genetic resources.

SCOPE

Recent studies of plant transcriptomes, proteomes and metabolomes, and the use of mutants and transgenic lines have significantly expanded our knowledge concerning excision-induced AR formation. Here, we integrate new findings regarding AR formation in the cuttings of diverse plant species. These findings support a new system-oriented concept that the phytohormone-controlled reprogramming and differentiation of particular responsive cells in the cutting base interacts with a co-ordinated reallocation of plant resources within the whole cutting to initiate and drive excision-induced AR formation. Master control by auxin involves diverse transcription factors and mechanically sensitive microtubules, and is further linked to ethylene, jasmonates, cytokinins and strigolactones. Hormone functions seem to involve epigenetic factors and cross-talk with metabolic signals, reflecting the nutrient status of the cutting. By affecting distinct physiological units in the cutting, environmental factors such as light, nitrogen and iron modify the implementation of the genetically controlled root developmental programme.

CONCLUSION

Despite advanced research in the last decade, important questions remain open for future investigations on excision-induced AR formation. These concern the distinct roles and interactions of certain molecular, hormonal and metabolic factors, as well as the functional equilibrium of the whole cutting in a complex environment. Starting from model plants, cell type- and phase-specific monitoring of controlling processes and modification of gene expression are promising methodologies that, however, need to be integrated into a coherent model of the whole system, before research findings can be translated to other crops.

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.

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.

Exploring the involvement of Tac2 in the mouse hippocampal stress response through gene networking

Tachykinin 2 (Tac2) is expressed in a number of areas throughout the brain, including the hippocampus. However, knowledge about its function has been only well explored in the hypothalamus in the context of reproductive health. In this study, we identified and validated increased hippocampal Tac2 mRNA expression in response to chronic mild stress in mice. Expression quantitative trait locus (eQTL) analysis showed Tac2 is cis-regulated in the hippocampus. Using a systems genetics approach, we constructed a Tac2 co-expression network to better understand the relationship between Tac2 and the hippocampal stress response. Our network identified 69 total genes associated with Tac2, several of which encode major neuropeptides involved in hippocampal stress signaling as well as critical genes for producing neural plasticity, indicating that Tac2 is involved in these processes. Pathway analysis for the member of Tac2 gene network revealed a strong connection between Tac2 and neuroactive ligand-receptor interaction, calcium signaling pathway, as well as cardiac muscle contraction. In addition, we also identified 46 stress-related phenotypes, specifically fear conditioning response, that were significantly correlated with Tac2 expression. Our results provide evidence for Tac2 as a strong candidate gene who likely plays a role in hippocampal stress processing and neural plasticity.

Systems and Synthetic Biology of Forest Trees: A Bioengineering Paradigm for Woody Biomass Feedstocks

Fast-growing forest plantations are sustainable feedstocks of plant biomass that can serve as alternatives to fossil carbon resources for materials, chemicals, and energy. Their ability to efficiently harvest light energy and carbon from the atmosphere and sequester this into metabolic precursors for lignocellulosic biopolymers and a wide range of plant specialized metabolites make them excellent biochemical production platforms and living biorefineries. Their large sizes have facilitated multi-omics analyses and systems modeling of key biological processes such as lignin biosynthesis in trees. High-throughput 'omics' approaches have also been applied in segregating tree populations where genetic variation creates abundant genetic perturbations of system components allowing construction of systems genetics models linking genes and pathways to complex trait variation. With this information in hand, it is now possible to start using synthetic biology and genome editing techniques in a bioengineering approach based on a deeper understanding and rational design of biological parts, devices, and integrated systems. However, the complexity of the biology and interacting components will require investment in big data informatics, machine learning, and intuitive visualization to fully explore multi-dimensional patterns and identify emergent properties of biological systems. Predictive systems models could be tested rapidly through high-throughput synthetic biology approaches and multigene editing. Such a bioengineering paradigm, together with accelerated genomic breeding, will be crucial for the development of a new generation of woody biorefinery crops.

Genome-Wide Association Studies to Improve Wood Properties: Challenges and Prospects

Wood formation is an excellent model system for quantitative trait analysis due to the strong associations between the transcriptional and metabolic traits that contribute to this complex process. Investigating the genetic architecture and regulatory mechanisms underlying wood formation will enhance our understanding of the quantitative genetics and genomics of complex phenotypic variation. Genome-wide association studies (GWASs) represent an ideal statistical strategy for dissecting the genetic basis of complex quantitative traits. However, elucidating the molecular mechanisms underlying many favorable loci that contribute to wood formation and optimizing GWAS design remain challenging in this omics era. In this review, we summarize the recent progress in GWAS-based functional genomics of wood property traits in major timber species such as Eucalyptus, Populus, and various coniferous species. We discuss several appropriate experimental designs for extensive GWAS in a given undomesticated tree population, such as omics-wide association studies and high-throughput phenotyping technologies. We also explain why more attention should be paid to rare allelic and major structural variation. Finally, we explore the potential use of GWAS for the molecular breeding of trees. Such studies will help provide an integrated understanding of complex quantitative traits and should enable the molecular design of new cultivars.

Co-expression network of transcription factors reveal ethylene-responsive element-binding factor as key regulator of wood phenotype in Eucalyptus tereticornis

Suitability of wood biomass for pulp production is dependent on the cellular architecture and composition of secondary cell wall. Presently, systems genetics approach is being employed to understand the molecular basis of trait variation and co-expression network analysis has enabled holistic understanding of complex trait such as secondary development. Transcription factors (TFs) are reported as key regulators of meristematic growth and wood formation. The hierarchical TF network is a multi-layered system which interacts with downstream structural genes involved in biosynthesis of cellulose, hemicelluloses and lignin. Several TFs have been associated with wood formation in tree species such as Populus, Eucalyptus, Picea and Pinus. However, TF-specific co-expression networks to understand the interaction between these regulators are not reported. In the present study, co-expression network was developed for TFs expressed during wood formation in Eucalyptus tereticornis and ethylene-responsive element-binding factor, EtERF2, was identified as the major hub transcript which co-expressed with other secondary cell wall biogenesis-specific TFs such as EtSND2, EtVND1, EtVND4, EtVND6, EtMYB70, EtGRAS and EtSCL8. This study reveals a probable role of ethylene in determining natural variation in wood properties in Eucalyptus species. Understanding this transcriptional regulation underpinning the complex bio-processing trait of wood biomass will complement the Eucalyptus breeding program through selection of industrially suitable phenotypes by marker-assisted selection.

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

Modularity Facilitates Flexible Tuning of Plastic and Evolutionary Gene Expression Responses during Early Divergence

Gene expression changes have been recognized as important drivers of adaptation to changing environmental conditions. Little is known about the relative roles of plastic and evolutionary responses in complex gene expression networks during the early stages of divergence. Large gene expression data sets coupled with in silico methods for identifying coexpressed modules now enable systems genetics approaches also in nonmodel species for better understanding of gene expression responses during early divergence. Here, we combined gene coexpression analyses with population genetics to separate plastic and population (evolutionary) effects in expression networks using small salmonid populations as a model system. We show that plastic and population effects were highly variable among the six identified modules and that the plastic effects explained larger proportion of the total eigengene expression than population effects. A more detailed analysis of the population effects using a QST - FST comparison across 16,622 annotated transcripts revealed that gene expression followed neutral expectations within modules and at the global level. Furthermore, two modules showed enrichment for genes coding for early developmental traits that have been previously identified as important phenotypic traits in thermal responses in the same model system indicating that coexpression analysis can capture expression patterns underlying ecologically important traits. We suggest that module-specific responses may facilitate the flexible tuning of expression levels to local thermal conditions. Overall, our study indicates that plasticity and neutral evolution are the main drivers of gene expression variance in the early stages of thermal adaptation in this system.

Differential expression of a WRKY gene between wild and cultivated soybeans correlates to seed size

Soybean (Glycine max) probably originated from the wild soybean (Glycine soja). Glycine max has a significantly larger seed size, but the underlying genomic changes are largely unknown. Candidate regulatory genes were preliminarily proposed by data co-localizing RNA sequencing with the quantitative loci (QTLs) for seed size. The soybean gene locus SoyWRKY15a and its orthologous genes from G. max (GmWRKY15a) and G. soja (GsWRKY15a) were analyzed in detail. The coding sequences were nearly identical between the two orthologs, but GmWRKY15a was significantly more highly expressed than GsWRKY15a. Four haplotypes (H1-H4) were found and they varied in the size of a CT-core microsatellite locus in the 5'-untranslated region of this gene. H1 (with six CT-repeats) was the only allelic version found in G. max, while H3 (with five CT-repeats) was the dominant G. soja allele. Differential expression of this gene in soybean pods was correlated with CT-repeat variation, and manipulation of the CT copy number altered the reporter gene expression, suggesting a regulatory role for the simple sequence repeats. Seed weight of wild soybeans harboring H1 was significantly greater than that of soybeans having haplotypes H2, H3, or H4, and seed weight was correlated with gene expression, suggesting the influence of GsWRKY15a in controlling seed size. However, the seed size might be refractory to increased SoyWRKY15a expression in cultivated soybeans. The evolutionary significance of SoyWRKY15a variation in soybean seed domestication is discussed.

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

We used a systems genetics approach to elucidate the molecular mechanisms of the responses of maize to grey leaf spot (GLS) disease caused by Cercospora zeina, a threat to maize production globally. Expression analysis of earleaf samples in a subtropical maize recombinant inbred line population (CML444 × SC Malawi) subjected in the field to C. zeina infection allowed detection of 20 206 expression quantitative trait loci (eQTLs). Four trans-eQTL hotspots coincided with GLS disease QTLs mapped in the same field experiment. Co-expression network analysis identified three expression modules correlated with GLS disease scores. The module (GY-s) most highly correlated with susceptibility (r = 0.71; 179 genes) was enriched for the glyoxylate pathway, lipid metabolism, diterpenoid biosynthesis and responses to pathogen molecules such as chitin. The GY-s module was enriched for genes with trans-eQTLs in hotspots on chromosomes 9 and 10, which also coincided with phenotypic QTLs for susceptibility to GLS. This transcriptional network has significant overlap with the GLS susceptibility response of maize line B73, and may reflect pathogen manipulation for nutrient acquisition and/or unsuccessful defence responses, such as kauralexin production by the diterpenoid biosynthesis pathway. The co-expression module that correlated best with resistance (TQ-r; 1498 genes) was enriched for genes with trans-eQTLs in hotspots coinciding with GLS resistance QTLs on chromosome 9. Jasmonate responses were implicated in resistance to GLS through co-expression of COI1 and enrichment of genes with the Gene Ontology term 'cullin-RING ubiquitin ligase complex' in the TQ-r module. Consistent with this, JAZ repressor expression was highly correlated with the severity of GLS disease in the GY-s susceptibility network.

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. A more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.

Systems genetics of wood formation

In woody plants, xylogenesis is an exceptionally strong carbon sink requiring robust transcriptional control and dynamic coordination of cellular and metabolic processes directing carbon allocation and partitioning into secondary cell wall biosynthesis. As a biological process, wood formation is an excellent candidate for systems modeling due to the strong correlation patterns and interconnectedness observed for transcriptional and metabolic component traits contributing to complex phenotypes such as cell wall chemistry and ultrastructure. Genetic variation in undomesticated tree populations provides abundant perturbation of systems components, adding another dimension to plant systems biology (besides spatial and temporal variation). High-throughput analysis of molecular component traits in adult trees has provided the first insights into the systems genetics of wood, an important renewable feedstock for biomaterials and bioenergy.

Frequency of alcohol consumption in humans; the role of metabotropic glutamate receptors and downstream signaling pathways

Rodent models implicate metabotropic glutamate receptors (mGluRs) and downstream signaling pathways in addictive behaviors through metaplasticity. One way mGluRs can influence synaptic plasticity is by regulating the local translation of AMPA receptor trafficking proteins via eukaryotic elongation factor 2 (eEF2). However, genetic variation in this pathway has not been examined with human alcohol use phenotypes. Among a sample of adults living in Detroit, Michigan (Detroit Neighborhood Health Study; n = 788; 83% African American), 206 genetic variants across the mGluR-eEF2-AMPAR pathway (including GRM1, GRM5, HOMER1, HOMER2, EEF2K, MTOR, EIF4E, EEF2, CAMK2A, ARC, GRIA1 and GRIA4) were found to predict number of drinking days per month (corrected P-value < 0.01) when considered as a set (set-based linear regression conducted in PLINK). In addition, a CpG site located in the 3'-untranslated region on the north shore of EEF2 (cg12255298) was hypermethylated in those who drank more frequently (P < 0.05). Importantly, the association between several genetic variants within the mGluR-eEF2-AMPAR pathway and alcohol use behavior (i.e., consumption and alcohol-related problems) replicated in the Grady Trauma Project (GTP), an independent sample of adults living in Atlanta, Georgia (n = 1034; 95% African American), including individual variants in GRM1, GRM5, EEF2, MTOR, GRIA1, GRIA4 and HOMER2 (P < 0.05). Gene-based analyses conducted in the GTP indicated that GRM1 (empirical P < 0.05) and EEF2 (empirical P < 0.01) withstood multiple test corrections and predicted increased alcohol consumption and related problems. In conclusion, insights from rodent studies enabled the identification of novel human alcohol candidate genes within the mGluR-eEF2-AMPAR pathway.

The crop QTLome comes of age

Recent progress in genomics and phenomics allows for a more accurate and comprehensive characterization of the Quantitative Trait Loci (QTLs)—hereafter defined 'QTLome' as a whole—that govern the variation targeted in breeding programs. High-density genotyping now provides unambiguous identification of QTL alleles, and for several traits beneficial alleles at major QTLs have already been deployed in marker-assisted breeding. However, the amount of QTLome information is enormous and approaches to distill and translate this information to breeders remain to be refined. Improved QTL meta-analyses, better estimation of QTL effects, improved crop modelling and full sharing of raw QTL data will enable a more effective exploitation of the QTLome.

Genetic Addiction Risk Score (GARS): molecular neurogenetic evidence for predisposition to Reward Deficiency Syndrome (RDS)

We have published extensively on the neurogenetics of brain reward systems with reference to the genes related to dopaminergic function in particular. In 1996, we coined “Reward Deficiency Syndrome” (RDS), to portray behaviors found to have gene-based association with hypodopaminergic function. RDS as a useful concept has been embraced in many subsequent studies, to increase our understanding of Substance Use Disorder (SUD), addictions, and other obsessive, compulsive, and impulsive behaviors. Interestingly, albeit others, in one published study, we were able to describe lifetime RDS behaviors in a recovering addict (17 years sober) blindly by assessing resultant Genetic Addiction Risk Score (GARS™) data only. We hypothesize that genetic testing at an early age may be an effective preventive strategy to reduce or eliminate pathological substance and behavioral seeking activity. Here, we consider a select number of genes, their polymorphisms, and associated risks for RDS whereby, utilizing GWAS, there is evidence for convergence to reward candidate genes. The evidence presented serves as a plausible brain-print providing relevant genetic information that will reinforce targeted therapies, to improve recovery and prevent relapse on an individualized basis. The primary driver of RDS is a hypodopaminergic trait (genes) as well as epigenetic states (methylation and deacetylation on chromatin structure). We now have entered a new era in addiction medicine that embraces the neuroscience of addiction and RDS as a pathological condition in brain reward circuitry that calls for appropriate evidence-based therapy and early genetic diagnosis and that requires further intensive investigation.