Impact of a cis-associated gene expression SNP on chromosome 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance.

BackgroundBipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain.AimsWe sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL.MethodTo detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance (n = 342) among healthy individuals.ResultsIntegrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85×10(-5)). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P = 3.54×10(-8)). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals.ConclusionsOur findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder.

Rare genomic structural variants in complex disease: lessons from the replication of associations with obesity.

The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the 'missing heritability'. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10(-4) (95% confidence interval [9.6×10(-5)-3.1×10(-4)]); accounts overall for 0.5% [0.19%-0.82%] of severe childhood obesity cases (P = 3.8×10(-10); odds ratio = 25.0 [9.9-60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m(-2) [1.8-10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the identification of variants making an appreciable contribution to complex disease.

Structured RNAs in the ENCODE selected regions of the human genome.

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

Genomic determinants of the efficiency of internal ribosomal entry sites of viral and cellular origin

Summary : Internal ribosome entry sites (IRES) are used by viruses as a strategy to bypass inhibition of cap-dependent translation that commonly results from viral infection. IRES are also used in eukaryotic cells to control mRNA translation under conditions of cellular stress (apoptosis, heat shock) or during the G2 phase of the cell cycle when general protein synthesis is inhibited. Variation in cellular expression levels has been shown to be inherited. Expression is controlled, among others, by transcriptional factors and by the efficiency of cap-mediated translation and ribosome activity. We aimed at identifying genomic determinants of variability in IRES-mediated translation of two representative IRES [Encephalomyocarditis virus (EMCV) and X-linked Inhibitor-of-Apoptosis (XIAP) IRES]. We used bicistronic lentiviral constructions expressing two fluorescent reporter transgenes. Lentiviruses were used to transduce seven different laboratory cell lines and B lymphoblastoid cell lines from the Centre d'Etude du Polymorphisme Humain (CEPH; 15 pedigrees; n=209); representing an in vitro approach to family structure allowing genome scan analyses. The relative expression of the two markers was assessed by FACS. IRES efficiency varies according to cellular background, but also varies, for a same cell type, among individuals. The control of IRES activity presents an inherited component (h2) of 0.47 and 0.36 for EMCV and XIAP IRES, respectively. A genome scan identified a suggestive Quantitative Trait Loci (LOD 2.35) involved in the control of XIAP IRES activity. Résumé : Les sites internes d'entrée des ribosomes (IRES = internal ribosome entry sites) sont utilisés par les virus comme une stratégie afin d'outrepasser l'inhibition de traduction qui résulte communément d'une infection virale. Les IRES sont également utilisés par les cellules eucaryotes pour contrôler la traduction de l'ARN messager dans des conditions de stress cellulaire (apoptose, choc thermique) ou durant la phase G2 du cycle cellulaire, situations durant lesquelles la synthèse générale des protéines est inhibée. La variation des niveaux d'expression cellulaire de transcription est un caractère héréditaire. L'expression des gènes est contrôlée entre autre par les facteurs de transcription et par l'efficacité de la traduction initiée par la coiffe ainsi que par l'activité des ribosomes. Durant cette étude nous avons eu pour but d'identifier les déterminants génomiques responsables de la variabilité de la traduction contrôlée par l'IRES. Ceci a été effectué en étudiant deux IRES représentatifs : l'IRES du virus de l'encéphalomyocardite (EMCV) et l'IRES de l'inhibiteur de l'apoptose XIAP (X-linked Inhibitor-of-Apoptosis). Nous avons utilisés des lentivirus délivrant un transgène bicistronique codant pour deux gènes rapporteurs fluorescents. Ces lentivirus ont été utilisés pour transduire sept différentes lignées cellulaires de laboratoire et des lignées cellulaires lymphoblastoïdes B du Centre d'Etude du Polymorphisme Humain (CEPH; 15 pedigrees; n=209) qui représentent une approche in vitro de la structure familiale et qui permettent des analyses par balayage du génome. L'expression relative des deux marqueurs fluorescents a été analysée par FACS. Nos résultats montrent que l'efficacité des IRES varie en fonction du type de cellules. Il varie aussi, pour le même type de cellules, selon les individus. Le contrôle de l'activité de l'IRES est un caractère héritable (héritabilité h2) de 0.47 et 0.36 pour les IRES de EMCV et XIAP respectivement. Le balayage du génome a permis l'identification d'un locus à effets quantitatifs [QTL Quantitative Trait Loci (LOD 2.35)] impliqué dans le contôle de l'activité de l'IRES de XIAP.

Detecting epistasis with restricted response patterns in pairs of biallelic loci.

Well-established examples of genetic epistasis between a pair of loci typically show characteristic patterns of phenotypic distributions in joint genotype tables. However, inferring epistasis given such data is difficult due to the lack of power in commonly used approaches, which decompose the epistatic patterns into main plus interaction effects followed by testing the interaction term. Testing additive-only or all terms may have more power, but they are sensitive to nonepistatic patterns. Alternatively, the epistatic patterns of interest can be enumerated and the best matching one is found by searching through the possibilities. Although this approach requires multiple testing correction over possible patterns, each pattern can be fitted with a regression model with just one degree of freedom and thus the overall power can still be high, if the number of possible patterns is limited. Here we compare the power of the linear decomposition and pattern search methods, by applying them to simulated data generated under several patterns of joint genotype effects with simple biological interpretations. Interaction-only tests are the least powerful; while pattern search approach is the most powerful if the range of possibilities is restricted, but still includes the true pattern.

Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies.

To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P = 5.4 × 10&#8315;&#8310;&#8304;) and 9q31.2 (P = 2.2 × 10&#8315;³³), we identified 30 new menarche loci (all P < 5 × 10&#8315;&#8312;) and found suggestive evidence for a further 10 loci (P < 1.9 × 10&#8315;&#8310;). The new loci included four previously associated with body mass index (in or near FTO, SEC16B, TRA2B and TMEM18), three in or near other genes implicated in energy homeostasis (BSX, CRTC1 and MCHR2) and three in or near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and gene-set enrichment pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing.

A genome-wide association study of early menopause and the combined impact of identified variants.

Early menopause (EM) affects up to 10% of the female population, reducing reproductive lifespan considerably. Currently, it constitutes the leading cause of infertility in the western world, affecting mainly those women who postpone their first pregnancy beyond the age of 30 years. The genetic aetiology of EM is largely unknown in the majority of cases. We have undertaken a meta-analysis of genome-wide association studies (GWASs) in 3493 EM cases and 13 598 controls from 10 independent studies. No novel genetic variants were discovered, but the 17 variants previously associated with normal age at natural menopause as a quantitative trait (QT) were also associated with EM and primary ovarian insufficiency (POI). Thus, EM has a genetic aetiology which overlaps variation in normal age at menopause and is at least partly explained by the additive effects of the same polygenic variants. The combined effect of the common variants captured by the single nucleotide polymorphism arrays was estimated to account for &#8764;30% of the variance in EM. The association between the combined 17 variants and the risk of EM was greater than the best validated non-genetic risk factor, smoking.

Genome-wide association analysis identifies 20 loci that influence adult height.

Adult height is a model polygenic trait, but there has been limited success in identifying the genes underlying its normal variation. To identify genetic variants influencing adult human height, we used genome-wide association data from 13,665 individuals and genotyped 39 variants in an additional 16,482 samples. We identified 20 variants associated with adult height (P &lt; 5 x 10(-7), with 10 reaching P &lt; 1 x 10(-10)). Combined, the 20 SNPs explain approximately 3% of height variation, with a approximately 5 cm difference between the 6.2% of people with 17 or fewer 'tall' alleles compared to the 5.5% with 27 or more 'tall' alleles. The loci we identified implicate genes in Hedgehog signaling (IHH, HHIP, PTCH1), extracellular matrix (EFEMP1, ADAMTSL3, ACAN) and cancer (CDK6, HMGA2, DLEU7) pathways, and provide new insights into human growth and developmental processes. Finally, our results provide insights into the genetic architecture of a classic quantitative trait.

Variants in MTNR1B influence fasting glucose levels.

To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 x 10(-50)) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 x 10(-15)). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 x 10(-7)) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 x 10(-57)) and GCK (rs4607517, P = 1.0 x 10(-25)) loci.

A multilevel approach to understanding circadian rhythmicity : social and sleep-dependent effects in ants and mice

Résumé françaisLa majorité des organismes vivants sont soumis à l'alternance du jour et de la nuit, conséquence de la rotation de la terre autour de son axe. Ils ont développé un système interne de mesure du temps, appelé horloge circadienne, leur permettant de s'adapter et de synchroniser leur comportement et leur physiologie aux cycles de lumière. Cette dernière est considérée comme étant le signal majeur entraînant l'horloge interne et. par conséquent, les rythmes journaliers d'éveil et de sommeil. Outre sa régulation circadienne, le sommeil est contrôlé par un processus homéostatique qui détermine son besoin. La contribution de ces deux processus dans le fonctionnement cellulaire du cerveau n'a pas encore été investiguée. La mesure de l'amplitude ainsi que de la prévalence des ondes delta de l'EEG (activité delta) constitue un index très fiable du besoin de sommeil. Il a été démontré que cette activité est génétiquement déterminée et associée à un locus de trait quantitatif situé sur le chromosome 13 de la souris.Grâce à des expériences de privation de sommeil et d'analyses de transcriptome du cerveau dans trois souches de souris présentant diverses réponses à la privation de sommeil, nous avons trouvé que Homerla, localisé dans la région d'intérêt du chromosome 13, est le meilleur marqueur du besoin de sommeil. Homerla est impliqué dans la récupération de l'hyperactivité neuronale induite par le glutamate, grâce à son effet tampon sur le calcium intracellulaire. Une fonction fondamentale du sommeil pourrait donc être de protéger le cerveau et de lui permettre de récupérer après une hyperactivité neuronale imposée par une veille prolongée.De plus, nous avons montré que 2032 transcrits sont exprimés rythmiqueraent dans le cerveau de la souris, parmi lesquels seulement 391 le restent après que les animaux aient été privés de sommeil à différents moments au cours des 24 heures. Cette observation montre clairement que la plupart des changements rythmiques au niveau du transcriptome dépendent du sommeil et non de l'horloge circadienne et souligne ainsi l'importance du sommeil dans la physiologie des mammifères.La plupart des expériences concernant les rythmes circadiens ont été réalisées sur des individus isolés en négligeant l'effet du contexte social sur les comportements circadiens. Les espèces sociales, telles que les fourmis, se caractérisent par une division du travail où une répartition des tâches s'effectue entre ses membres. De plus, certaines d'entre elles doivent être pratiquées en continu comme les soins au couvain tandis que d'autres requièrent une activité rythmique comme le fourragement. Ainsi la fourmi est un excellent modèle pour l'étude de 1 influence du contexte social sur les rythmes circadiens.A ces fins, nous avons décidé d'étudier les rythmes circadiens chez une espèce de fourmi Camponotus fellah et de caractériser au niveau moléculaire son horloge circadienne. Nous avons ainsi développé un système vidéo permettant de suivre l'activité locomotrice de tous les individus d'une colonie. Nos résultats montrent que, bien que la plupart des fourmis soient arythmiques à l'intérieur de la colonie, elles développent d'amples rythmes d'activité en isolation. De plus, ces rythmes disparaissent presque aussitôt que la fourmi est réintroduite dans la colonie. Cette rythmicité observée en isolation semble être générée par l'horloge circadienne car elle persiste en condition constante (obscurité totale). Nous avons ensuite regardé si cette apparente arythmie observée dans la colonie résultait d'un effet masquant des interactions sociales sur les rythmes circadiens d'activité. Nos résultats suggèrent que l'horloge interne est fonctionnelle dans la colonie mais que l'expression de ses rythmes au niveau comportemental est inhibée par les interactions sociales. Les analyses moléculaires du statut de l'horloge dans différents contextes sociaux sont actuellement en cours. Le contexte social semble donc un déterminant majeur du comportement circadien chez la fourmi.AbstractAlmost all living organisms on earth are subjected to the alternance of day and night re-sulting from the rotation of the earth around its axis. They have evolved with an internal timing system, termed the circadian clock, enabling them to adapt and synchronize their behavior and physiology to the daily changes in light and related environmental parame¬ters. Light is thought to be the major cue entraining the circadian clock and consequently the rhythms of rest/activity. In addition to its circadian dependent timing, sleep is reg¬ulated by a homeostatic process that determines its need. The contribution of these two processes in the cellular functioning of the brain has not yet been considered. A highly reliable index of the homeostatic process of sleep is the measure of the amplitude and prevalence of the EEG delta waves (delta activity). It has been shown that sleep need, measured by delta activity, is genetically determined and associated with a Quantitative Trait Locus (QTL) located on the mouse chromosome 13. By using sleep deprivation and brain transcriptome profiling in three inbred mouse strains showing different responses to sleep loss, we found that Homerla, localized within this QTL region is the best transcrip¬tional marker of sleep need. Interestingly Homerla is primarily involved in the recovery from glutamate-induced neuronal hyperactivity by its buffering effect on intracellular cal¬cium. A fundamental function of sleep may therefore reside in the protection and recovery of the brain from a neuronal hyperactivity imposed by prolonged wakefulness.Moreover, time course gene expression experiments showed that 2032 brain tran¬scripts present a rhythmic variation, but only 391 of those remain rhythmic when mice are sleep deprived at four time points around the clock. This finding clearly suggests that most changes in gene transcription over the day are sleep-wake dependent rather than clock dependent and underlines the importance of sleep in mammalian physiology.In the second part of this PhD, I was interested in the social influence on circadian behavior. Most experiments done in the circadian field have been performed on isolated individuals and have therefore ignored the effect of the social context on circadian behav-ior. Eusocial insect species such as ants are characterized by a division of labor: colony tasks are distributed among individuals, some of them requiring continuous activity such as nursing or rhythmic ones such as foraging. Thus ants represent a suitable model to study the influence of the social context on the circadian clock and its output rhythms.The aim of this part was to address the effect of social context on circadian rhythms in the ant species Camponotus fellah and to characterize its circadian clock at the molecu¬lar level. We therefore developed a video tracking system to follow the locomotor activity of all individuals in a colony. Our results show that most ants are arrhythmic within the colony, but develop, when subjected to social isolation, strong rhythms of activity that intriguingly disappear when individuals are reintroduced into the colony. The rhythmicity observed in isolated ants seems to be driven by the circadian clock as it persists under constant conditions (complete darkness). We then tested whether the apparent arrhyth- micity in the colony stemmed from a masking effect of social interactions on circadian rhythms. Indeed, we found that circadian clocks of ants in the colony are functional but their expression at the behavioral level is inhibited by social interactions. The molecular assessment of the circadian clock functional state in the different social context is still under investigation. Our results suggest that social context is a major determinant of circadian behavior in ants.

Genomic and proteomic approaches towards an understanding of sleep.

The basic functions of sleep are still unclear, however, recent advances in genomics and proteomics have begun to contribute to our understanding of both normal and pathological sleep. In this review, we focus primarily on normal sleep and wake that have been studied in model organisms such as mice. Mice have been especially valuable since many different inbred strains exist that differ in sleep-related traits, and genes can be altered by either mutagenesis or targeted approaches. Advances in QTL (Quantitative Trait Loci) analysis have also helped to identify important sleep related genes, and several other QTLs have been mapped as a first step toward finding the genes that underlie basic sleep traits. In addition to more traditional genetic approaches, the abundance of different mRNAs across sleep and wake can now be studied and compared in different brain regions much more thoroughly using microarray methods. Progress at the protein level has been more difficult, but a few studies have begun to investigate changes in proteins during sleep and wake, and we present some of our own preliminary data in this area. A knowledge of which genes and proteins control or respond to changes in sleep will not only help answer fundamental questions, but may also suggest novel drug targets for improving multiple aspects of sleep and wake.

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Although it has long been known that genetic factors play a major role in shaping the electroencephalogram (EEG), progress on identifying the underlying genes has, until recently, been limited. Using quantitative trait loci (QTL) analyses several genomic loci affecting the sleep EEG could be mapped in the mouse. For three of these QTLs the responsible genes were identified leading to the implication of novel signaling pathways affecting EEG traits. Moreover, the insight that in the mouse the sleep-wake dependent dynamics in the expression of EEG slow waves during sleep is under strong genetic control has paved the way for candidate gene studies in humans investigating the contribution of specific polymorphism to the trait-like inter-individual differences in the susceptibility to sleep loss. Candidate gene studies in the mouse were also instrumental in establishing an alternative, noncircadian function for clock genes in the homeostatic regulation of sleep and modulating rhythmic EEG activity of thalamocortical origin. Future efforts should combine system genetics approaches in the mouse and genome-wide association studies in humans to facilitate uncovering the molecular pathways that shape brain activity.

Genetic basis of adaptation in Arabidopsis thaliana: local adaptation at the seed dormancy QTL DOG1.

Local adaptation provides an opportunity to study the genetic basis of adaptation and investigate the allelic architecture of adaptive genes. We study delay of germination 1 (DOG1), a gene controlling natural variation in seed dormancy in Arabidopsis thaliana and investigate evolution of dormancy in 41 populations distributed in four regions separated by natural barriers. Using F(ST) and Q(ST) comparisons, we compare variation at DOG1 with neutral markers and quantitative variation in seed dormancy. Patterns of genetic differentiation among populations suggest that the gene DOG1 contributes to local adaptation. Although Q(ST) for seed dormancy is not different from F(ST) for neutral markers, a correlation with variation in summer precipitation supports that seed dormancy is adaptive. We characterize dormancy variation in several F(2) -populations and show that a series of functionally distinct alleles segregate at the DOG1 locus. Theoretical models have shown that the number and effect of alleles segregatin at quantitative trait loci (QTL) have important consequences for adaptation. Our results provide support to models postulating a large number of alleles at quantitative trait loci involved in adaptation.

Comprehensive analysis of Arabidopsis expression level polymorphisms with simple inheritance.

In Arabidopsis thaliana, gene expression level polymorphisms (ELPs) between natural accessions that exhibit simple, single locus inheritance are promising quantitative trait locus (QTL) candidates to explain phenotypic variability. It is assumed that such ELPs overwhelmingly represent regulatory element polymorphisms. However, comprehensive genome-wide analyses linking expression level, regulatory sequence and gene structure variation are missing, preventing definite verification of this assumption. Here, we analyzed ELPs observed between the Eil-0 and Lc-0 accessions. Compared with non-variable controls, 5' regulatory sequence variation in the corresponding genes is indeed increased. However, approximately 42% of all the ELP genes also carry major transcription unit deletions in one parent as revealed by genome tiling arrays, representing a &amp;gt;4-fold enrichment over controls. Within the subset of ELPs with simple inheritance, this proportion is even higher and deletions are generally more severe. Similar results were obtained from analyses of the Bay-0 and Sha accessions, using alternative technical approaches. Collectively, our results suggest that drastic structural changes are a major cause for ELPs with simple inheritance, corroborating experimentally observed indel preponderance in cloned Arabidopsis QTL.

Natural genetic variation of root system architecture from Arabidopsis to Brachypodium: towards adaptive value.

Root system architecture is a trait that displays considerable plasticity because of its sensitivity to environmental stimuli. Nevertheless, to a significant degree it is genetically constrained as suggested by surveys of its natural genetic variation. A few regulators of root system architecture have been isolated as quantitative trait loci through the natural variation approach in the dicotyledon model, Arabidopsis. This provides proof of principle that allelic variation for root system architecture traits exists, is genetically tractable, and might be exploited for crop breeding. Beyond Arabidopsis, Brachypodium could serve as both a credible and experimentally accessible model for root system architecture variation in monocotyledons, as suggested by first glimpses of the different root morphologies of Brachypodium accessions. Whether a direct knowledge transfer gained from molecular model system studies will work in practice remains unclear however, because of a lack of comprehensive understanding of root system physiology in the native context. For instance, apart from a few notable exceptions, the adaptive value of genetic variation in root system modulators is unknown. Future studies should thus aim at comprehensive characterization of the role of genetic players in root system architecture variation by taking into account the native environmental conditions, in particular soil characteristics.