Secale cereale L.) improvement programs depends on the availability of high-density molecular linkage maps. However, the number of sequence-specific PCR-based markers available for the species is limited. Diversity Arrays Technology (DArT) is a microarray-based method allowing for detection of DNA polymorphism at several thousand loci in a single assay without relying on DNA sequence information. The objective of this study was the development and application of Diversity Arrays technology for rye.Implementation of molecular breeding in rye  were placed on a genetic linkage map of the cross L318 × L9, providing an average density of one unique marker every 2.68 cM. This is the most saturated rye linkage map based solely on transferable markers available at the moment, providing rye breeders and researches with a better choice of markers and a higher probability of finding polymorphic markers in the region of interest.Using the The Diversity Arrays Technology can be efficiently and effectively used for rye genome analyses - assessment of genetic similarity and linkage mapping. The 11520-clone rye genotyping panel with several thousand markers with determined chromosomal location and accessible through an inexpensive genotyping service is a valuable resource for studies on rye genome organization and in molecular breeding of the species. Secale cereale L.) is an important cereal crop in Central, Eastern and Northern Europe, mainly due to its exceptional ability to thrive and to produce high yields in adverse environmental conditions. Nutrient efficiency and tolerance of diseases exhibited by rye, allowing for a reduced usage of pesticides and fertilizers during production, increase its attractiveness for farmers and consumers. The recently better recognized dietary value of rye contributed to the noticeable growth of consumers' interest in rye products. Breeding progress in rye, however, is rather slow, as the traditional breeding is hampered by the outcrossing nature of this crop, self-incompatibility and occurrence of inbreeding depression.Winter rye   were printed onto microarrays. Targets prepared from DNA samples of 10 rye ILs and 16 varieties were hybridized to those microarrays in the manner described above.For testing the applicability of eat DNA [, http://The DArTsoft generated 0-1 scores were used to calculate a pair-wise genetic similarity matrix on the basis of the Jaccard's coefficient  using thMarker scores obtained after hybridizations of RILs and the parental lines L9 and L318 to the rye genotyping array 1.0 and the rye genotyping array 2.0 were combined and DArT markers with P values from both experiments greater than 80% and additionally markers with P value from one experiment above 85% were chosen for map construction. The scores of polymorphic DArT markers were converted into genotype codes according to the scores of the parents. RECORD  was usedhttp://wheat.pw.usda.gov/GG2/index.shtml and they can be retrieved using the link: http://wheat.pw.usda.gov/cgi-bin/graingenes/browse.cgi?class=allele;query=DArT*All DArT marker scores reported in this paper were deposited in the GrainGenes database Employees of DArT P/L co-authoring this paper  may benefit financially from this work.HBB participated in molecular analyses, genetic mapping and the design of the study, performed hierarchical clustering and ordination analysis and drafted the manuscript, KHU participated in molecular and DArTsoft analyses, PW participated in genetic mapping, GU participated in DArTsoft data analyses and downstream processing, AK participated in the design and coordination of the study, guided array development and data production and helped to draft the manuscript, MRT conceived of the study, participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.


A. thaliana mutant glu1-2 knocked-down in the expression of Fd-GOGAT1 , one of the two genes of A. thaliana encoding ferredoxin-dependent glutamate synthase.Glutamate plays a central position in the synthesis of a variety of organic molecules in plants and is synthesised from nitrate through a series of enzymatic reactions. Glutamate synthases catalyse the last step in this pathway and two types are present in plants: NADH- or ferredoxin-dependent. Here we report a genome wide microarray analysis of the transcriptional reprogramming that occurs in leaves and roots of the glu1-2 revealed extensive changes with the expression of more than 5500 genes significantly affected in leaves and nearly 700 in roots. Both genes involved in glutamate biosynthesis and transformation are affected, leading to changes in amino acid compositions as revealed by NMR metabolome analysis. An elevated glutamine level in the glu1-2 mutant was the most prominent of these changes. An unbiased analysis of the gene expression datasets allowed us to identify the pathways that constitute the secondary response of an FdGOGAT1/GLU1 knock-down. Among the most significantly affected pathways, photosynthesis, photorespiratory cycle and chlorophyll biosynthesis show an overall downregulation in glu1-2 leaves. This is in accordance with their slight chlorotic phenotype. Another characteristic of the glu1-2 transcriptional profile is the activation of multiple stress responses, mimicking cold, heat, drought and oxidative stress. The change in expression of genes involved in flavonoid biosynthesis is also revealed. The expression of a substantial number of genes encoding stress-related transcription factors, cytochrome P450 monooxygenases, glutathione S-transferases and UDP-glycosyltransferases is affected in the glu1-2 mutant. This may indicate an induction of the detoxification of secondary metabolites in the mutant.Transcriptional profiling of glu1-2 transcriptome reveals extensive changes in gene expression profiles revealing the importance of Fd-GOGAT1, and indirectly the central role of glutamate, in plant development. Besides the effect on genes involved in glutamate synthesis and transformation, the glu1-2 mutant transcriptome was characterised by an extensive secondary response including the downregulation of photosynthesis-related pathways and the induction of genes and pathways involved in the plant response to a multitude of stresses.Analysis of the  Nitrogen is an important nutrient for plants and a limiting factor in plant development. It is mainly in the form of nitrate through nitrate transporters that nitrogen is taken up by plants. Nitrate is first reduced to nitrite and subsequently to ammonium through the action of nitrate reductase EC 1.7.1.1) and nitrite reductase (EC 1.7.7.1), respectively. Glutamine synthetase (EC 6.3.2.1) catalyses the incorporation of this ammonium into glutamate and thereby producing glutamine. Subsequently, glutamate synthase transfers the amide amino group of glutamine to 2-oxoglutarate, yielding two molecules of glutamate. Production of glutamate is a key point in the synthesis of a variety of organic molecules, such as nucleic acids, amino acids and secondary metabolites  catalysed by RuBP carboxylase/oxygenase [Besides the function in primary nitrogen assimilation, the GS/GOGAT pathway plays a central role in the reassimilation of ammonium produced by photorespiration (for review: ). Photorxygenase .Arabidopsis thaliana, NADH-GOGAT is encoded by a single gene (At5g53460) whereas Fd-GOGAT is encoded by two genes, previously called GLU1  and GLU2 [A. thaliana show contrasting patterns of expression, with Fd-GOGAT1 expression being highest in leaves, whereas Fd-GOGAT2 is mostly expressed in roots [A. thaliana is to a very large extent due to ferredoxin-dependent glutamate synthase, Fd-GOGAT1 contributing most [Fd-GOGAT1 and Fd-GOGAT2 expression is also regulated differently: light causes a dramatic increase in Fd-GOGAT1 whereas Fd-GOGAT2 expression is not or only slightly affected. Similarly, Fd-GOGAT1 but not Fd-GOGAT2 expression is induced by sucrose [Plants possess two forms of glutamate synthase, which are both localized in plastids. One uses NADH as electron donor and is commonly called NADH-GOGAT . The other one uses ferredoxin as electron donor and is called Fd-GOGAT EC 1.4.7.1) and to relate this to metabolic and phenotypic changes observed for this mutant.The aim of the study was to characterise the transcriptional reprogramming that occurs in an in vitro grown glu1-2 mutant plantlets. These analyses identified substantial reprogramming of several pathways and processes in the mutant. These include primary and secondary nitrogen assimilation, leading to changes in the levels of certain amino acid, and photosynthesis related processes. The mutant was also affected in flavonoid biosynthesis and exhibited extensive transcriptional changes indicating the induction of multiple stress responses.We report here the genome wide transcriptional analysis by microarray and the metabolic profiling by NMR spectroscopy of A. thaliana mutant presenting a T-DNA insertion in the Fd-GOGAT1  gene was used in the present study. This mutant will hence be referred to as glu1-2 mutant hereafter. Under the in vitro growth conditions that were used in the present study, glu1-2 mutant plants exhibited a moderate chlorotic phenotype and reduced growth compared to wild-type Col-0 plants . When comparing the change fold in expression between the glu1-2 mutant and the wild-type, the log2 ratio of affected genes in leaves varied between 6.41 and -5.73 whereas that in roots was much more moderate with a variation between 1.71 and -2.61  in leaves versus 687 genes in roots, there was an 8-fold difference in the number of affected genes between the two organs  induced genes were exclusively affected in this tissue  induced genes and 199 out of 303 (over 65%) repressed genes were exclusively affected in this tissue. Among the remaining genes, which were also affected in leaves, the induced ones were more prevalent than the repressed ones, irrespective of whether they were up-or down-regulated in leaves.In e Figure . The 92 glu1-2 mutant, notably the leaves, which indicates that a profound transcriptional reprogramming takes place. The schematic representation by Mapman [glu1-2 mutant  genes in glu1-2 roots. Analysis on glu1-2 root-induced and -repressed genes separately identifies 34 and 0 overrepresented GO_biological_process terms, respectively. When combining expression patterns from leaves and roots 2 GO_biological_process terms are overrepresented among affected genes, while the subset of genes downregulated in leaves and upregulated in roots reveals three additional overrepresented GO_biological_processes. Two terms are overrepresented among genes induced in both organs of the glu1-2 mutant  that are overrepresented in the glu1-2 mutant versus wild-type, using the Cytoscape [glu1-2 mutant leaves  and the affected GO-terms  is more highly expressed in leaves than in roots  of 18 day old in vitro grown A. thaliana wild type plants (Col-0 ecotype)  was downregulated in the glu1-2 mutant (Table 2 ratio of -5.74 between the expression levels of Fd-GOGAT1 in leaves of wild type and the mutant. In roots the difference was more moderate with a reduction in expression of log2 = -0.54 (only significant at P = 0.05). It should however be noted that residual levels of transcripts for Fd-GOGAT1 are still detectable on the microarrays from the glu1-2 mutant, and that these are similar in roots and leaves.Comparison of expression levels in our microarray assays indicates that 1 GLU1;Atg04140 isGLU2 (At2g41220) encoding Fd-GOGAT2, the second A. thaliana Fd-dependent glutamate synthase, is upregulated (log2 = 1.07) in leaves but not affected in roots of the glu1-2 mutant. The NADH-GOGAT (EC1.4.1.14) encoding gene At5g53460 is also slightly upregulated (log2 = 0.71) in glu1-2 leaves but not affected in roots  using ATP. Of the five putative A. thaliana genes encoding the cytoplasmic glutamine synthetase 1 (GS1), two were upregulated (At5g37600/GLN1.1 and At3g17820/GLN1.3) whereas one (At5g16570/GLN1.4) was slightly downregulated in glu1-2 leaves. The gene At5g35630 encoding glutamine synthetase 2 (GS2), which is dual-targeted to the plastid and mitochondria [glu1-2 mutant.Glutamine is the substrate of GOGATs for the synthesis of glutamate Figure  and glutchondria , was notglu1-2 mutant  and nitrite reductase , are upregulated in activity .A. thaliana genes encoding asparagine synthases, two were downregulated in glu1-2 leaves but none was affected in roots (Table ASN1 (At3g47340) is one of the ten most downregulated genes in the glu1-2 mutant leaves. It has been shown that ASN1 is induced by dark and reduced by light (or sucrose) while ASN2, which is moderately downregulated, is induced by light. These two genes also respond differently to asparagine, glutamine and glutamate with ASN1 expression being induced and ASN2 expression being reduced (for review: ). Of thereduced  encoding ASPs [glu1-2 leaves. Aspartate is a precursor of asparagine and the aspartate family of amino acids such as lysine, threonine and methionine  catalyse the transfer of the α-amino group of glutamate to oxaloacetate to form aspartate and 2-oxoglutarate. In ing ASPs  are upree Figure . From thA. thaliana [glu1-2 mutant (Table glu1-2 roots (Table GGAT2 (At1g70580) is reduced in glu1-2 leaves. The further conversion of glycine to serine involves the glycine decarboxylase complex (GDC) and serine hydroxymethyltransferase . The glycine decarboxylase complex is composed of four mitochondrial proteins  encoded by a total of eight genes in A. thaliana [A. thaliana genes putatively encoding serine hydroxymethyltransferases, four show a changed expression in glu1-2 leaves (Table SHM1 (At4g37930) encoding the mitochondrial SHMT1 is downregulated. Interestingly, the knock-out mutant shm1-1 also displays a lethal photorespiratory phenotype [glu1-2 roots  which comprise four members, subdivided into two groups, in thaliana . The firnt Table . Glyoxylthaliana . The genthaliana . Of the henotype  and a ph2 At1g7050 is reduglu1-2 mutant leaves , which catalyses the conversion of 2,3-dihydroxy-3-isovalerate to α-ketoisovalerate, is also induced in glu1-2 leaves. Branched-chain aminotransferases  catalyse the subsequent and last step in the synthesis of valine from α-ketoisovalerate, which is accompanied by the conversion of glutamate to 2-oxoglutarate. However none of the BCAT-encoding genes  implicated in this step is affected in the glu1-2 mutant. Hence, a few of the genes encoding biosynthetic enzymes involved in valine biosynthesis are induced, indicating possibly a slight activation of the valine biosynthetic pathway.Valine biosynthesis starts with the condensation of two molecules of pyruvate by acetohydroxyacid synthase , also known as acetolactate synthase . NeitherAt4g23100) and GSH2 (At5g27380) are upregulated in glu1-2 mutant leaves .Glutamate is used for the synthesis of glutathione in a two-reaction pathway Figure  catalysehenotype . UpregulGAD1 (At5g17330) and GAD2 (At1g65960) initially identified in A. thaliana [glu1-2 mutant. Of the three additional genes encoding putative GADs that have recently been identified based on homology [glu1-2 mutant leaves (Table At3g22200), the γ-aminobutyric acid transaminase that catalyses the conversion of GABA into succinic semialdehyde (SSA), simultaneously producing alanine from pyruvate, is also induced in leaves. The conversion of SSA to succinate by succinic semialdehyde dehydrogensase (SSADH) is also upregulated in glu1-2 leaves (Table Under certain conditions glutamate may be converted to gamma-aminobutyrate (GABA) in a cytosolic reaction catalysed by glutamate decarboxylase . The two GAD-encoding genes thaliana ,36 are nhomology , GAD3 anA. thaliana [GDH2 (At5g07440), encoding the β-subunit, is affected in the glu1-2 mutant, showing surprisingly an increased expression in mutant leaves  Figure , a mitocthaliana . Only GDproposed . The the2 At5g074, encodinproposed  proposedproposed .A. thaliana, glutamate is one of the predominant amino acids found in the phloem sap and xylem exudates [A. thaliana amino acid permease (AAP) family have been shown to catalyse the low affinity influx of a broad range of amino acids, including glutamate [AAP1 (At1g58360), AAP4 (At5g63850) and AAP6 (At5g49630) were moderately downregulated, whereas AAP5 (At1g44100) was induced in glu1-2 leaves  was affected in roots, with a lower expression in the mutant than in the wild-type.Amino acids can be exported from their site of synthesis and transported via the vascular tissue to newly developed tissues. In exudates . Memberslutamate . Of thesAAP5 At1g100 was iLHT1 (At5g40780) gene which appears to encode a high-affinity glutamate influx system [glu1-2 roots but not affected in glu1-2 leaves. A role for LHT1 in root uptake of certain amino acids was also recently proposed, but its role in glutamate uptake may be limited as this was not affected in an lht1 mutant [The related x system  was also1 mutant .At2g01170 encoding the recently identified bidirectional amino acid transporter BAT1 capable of import and export of glutamate and potentially involved in amino acid export from phloem to sink tissue [glu1-2 leaves and not affected in roots.The gene k tissue  is moderThe synthesis of glutamate by NADH- and Fd-GOGATs necessitates 2-oxoglutarate, which is thus situated at the interface between C and N metabolism. As it is possible to affect the glutamate pool by feeding 2-oxoglutarate to plants, the supply of 2-oxoglutarate may be a key regulator of glutamate levels .glu1-2 leaves  of the 2-oxoglutarate dehydrogenase system. On the other hand, the genes At2g47510/At5g50950 encoding fumarate hydratases  were downregulated in glu1-2 leaves. Interestingly, none of the TCA cycle-implicated genes mentioned above were significantly affected in glu1-2 roots. These data indicate an overall induction of the TCA cycle in glu1-2 leaves potentially leading to an increase in 2-oxoglutarate production. Higher levels of 2-oxoglutarate have been observed in Fd-GOGAT deficient tobacco plants [2-oxoglutarate is produced through the TCA cycle (for review: ) and sevs Figure . These is Figure . This inactivity . Recentlactivity  have shoo plants .glu1-2 leaves  and two genes putatively encoding cytosolic NADP-dependent isocitrate dehydrogenases  are upregulated in Fd-GOGAT1 is a key enzyme in the primary assimilation of nitrogen and knocking it down was expected to change the transcriptional level of genes involved in nitrogen uptake and transport Table .A. thaliana, five were induced in glu1-2 leaves. Of these, NRT1.1 (At1g12110) has been implicated in stomatal aperture and drought stress [- sensing role in root architecture was recently described [At1g32450) and NRT 1.7 (At1g69870) are less well characterised but have been shown to transport nitrate in a heterologous system [glu1-2 roots. On the other hand, eight genes encoding putative NRT1 family members, such as the NRT1.3/NTP3  was moderately induced in glu1-2 leaves , are doNRT3.1/NAR2.1 (At5g50200) encoding this protein is induced in glu1-2 leaves  proteins, which are encoded by six genes in nt roots . The genrecently .At5g40890 is down-regulated in glu1-2 leaves  is downregulated in glu1-2 leaves, whereas AtTIP2;3 (At5g47450) is downregulated in glu1-2 roots  have been proposed to be responsible for NHthaliana . AtTIP2;gluS/gls mutants did not seem to be impaired in primary nitrogen assimilation [Fd-GOGAT1/GLU1 indeed plays a role in primary nitrogen metabolism [Fd-GOGAT1 in the glu1-2 mutant affected several genes involved in primary nitrogen assimilation but the effects at the transcriptional level were more moderate than expected. Metabolite analysis by NMR spectroscopy of glu1-2 mutant tissue was performed to assess metabolic changes in the mutant.Although the Fd-GOGAT deficient milation , it was tabolism . As descglu1-2 mutant were revealed . This is not surprising considering the close interaction between C and N metabolism through the GS/GOGAT cycle. Differences in the contents of sucrose and glucose were not observed by NMR spectroscopy of glu1-2 leaves and roots (data not shown). This is consistent with results from tobacco plants with reduced Fd-GOGAT activity [Analysis with PathExpress identified starch and sucrose metabolism as being downregulated in leaves and roots of the activity .glu1-2 leaves  upregulated. The photosynthesis related bins of the MapMan software .Several genes involved in the Calvin cycle are thus affected in the s Figure . The mos2 is consumed in the plastid and CO2 and ammonium are released in the mitochondria. The released ammonium is reassimilated by the GS/GOGAT pathway in the plastid  and glycerate kinase  of plastids and mitochondrial serine hydroxymethyltransferase . Knock-out mutants of these genes exhibit a conditional lethal photorespiratory phenotype [At1g68010 encoding the peroxisomal NADH-dependent hydroxypyruvate reductase HPR1 is downregulated in glu1-2 leaves with no concomitant change of At1g79870 encoding the cytosolic isoform HPR2 that provides a cytosolic bypass to the photorespiratory cycle [glu1-2 leaves. Its role is yet unclear, although the homolog DiT2.1 has been identified as a glutamate/malate translocator with an essential role in photorespiration [At2g22500 encoding one of the three recently characterised mitochondrial dicarboxylate carriers (DIC1-3) that are able to transport malate and oxaloacetate among other substrates [glu1-2 roots the expression of a smaller number of genes involved in photorespiration is affected by the glu1-2 mutation, and all these are upregulated  by RuBP carboxylase/oxygenase . This ox review: ). The es review: . Transcrs Figure ; Table 4henotype ,64,65. Try cycle . The geneviously  showed tDue to the dual-targeting of glutamine synthetase 2 (GS2) to the plastid and mitochondria , other sAt1g03630 and At5g54190) encoding protochlorophyllide reductases that catalyse the last step leading to the synthesis of chlorophyllide a  encoding transcription factors belonging to different families, such as the zinc finger proteins , MYBs and bHLHs -deficient plants [The C2H2-type zinc finger transcription factor ZAT12 plays an important role in oxidative and abiotic stress response -73 and it plants . ZAT12 et plants  and showAt1g01060) and CCA1 (At2g46830), which are associated with the circadian clock and act as negative regulators of the periodic flowering pathway [glu1-2 leaves respectively. A role of LHY and CCA1 in the response to abiotic stresses has also been proposed [The genes encoding the two MYB-related transcription factors LHY  has not been described yet, it is phylogenetically closely linked to BHLH039 , and induced by salicylic acid (SA) [glu1-2 roots.Five genes (putatively) encoding bHLH transcription factors were among the 5% most repressed genes in 3g56980; ) which icid (SA)  and ironcid (SA) . It shouDREB2C/DREB2H  are highly upregulated AP2/ERF transcription factors in glu1-2 leaves. DREB2C has been described as being heat and drought inducible and overexpression confers thermotolerance to the plants. Analysis of these plants lead the authors to hypothesise that DREB2C is a late regulator of genes under heat stress [t stress .Flavonoids, which were revealed as affected in the gene sets, are a class of compounds that act for example as protection against abiotic and biotic stresses and their concentrations increase in response to these .glu1-2 mutant the phenylalanine metabolism was identified as being negatively affected whereas flavonoid biosynthesis was identified as being positively affected on the transcriptional level  and 3-dehydroquinate dehydratase (DHQD) are slightly induced in glu1-2 leaves but do not constitute important regulatory steps [At2g38400) is downregulated in glu1-2 leaves. Prephenate aminotransferase transfers the amino group from glutamate or aspartate for the synthesis of arogenate. Genes putatively encoding arogenate dehydratase that catalyses the last step of the shikimate pathway leading to the formation of phenylalanine, were either induced, repressed or unaffected in glu1-2 leaves  complex [glu1-2 leaves have not yet been described, although the contribution of AtMRP12 in detoxification seems to be marginal [The multidrug resistance-related protein (MRP)-type ABC transporters have been implicated in the vacuolar sequestration of phenolic compounds such as flavonoids and anthocyanins, and flavonoids have been suggested as negative regulators of MDR-type members (for review: ). A long complex . The rolmarginal  and AtMRmarginal . Based omarginal  speculatA. thaliana have not yet been identified, and it is therefore impossible to attribute most of these to particular pathways. Cytochrome P450s are categorised into the gene ontology term GO:0006118 (electron transport), which was revealed as being overrepresented (together with its parent GO:0006091) by GOstat analysis  and defense compounds . A large number of cytochrome P450s are responsive to hormones, signaling molecules and environmental stresses (for review: ). The fuglu1-2 mutant cytochrome P450 were especially frequent among the most upregulated and downregulated genes in roots. In total 22 and 39 genes annotated as encoding cytochrome P450 are affected in roots and leaves respectively  are among the 10% most highly induced genes and all but one are specifically affected in roots. On the other hand, the genes encoding the cytochrome P450s CYP71A12, CYP82C4 and CYP81F2 were among the 10% most highly repressed genes in glu1-2 roots. The function of CYP71A12and CYP82C4 has not yet been described. It was however shown that CYP71A12 expression responded in a similar way to aphid infestation than CYP71B15, which is involved in synthesis of the defence compound camalexin [glu1-2 mutant these three genes are repressed in roots while they are induced in leaves. The genes encoding three cytochrome P450  involved in the biosynthesis of glucosinolates are on the other hand induced in glu1-2 roots.Of the 22 genes affected in roots, 9 are repressed and 13 are induced  and At4g37370 (CYP81D8). These genes, together with At3g14660 (CYP72A13), were among the 30 genes upregulated by cis-jasmone treatment [CYP81D8 is also among the eight genes induced early on by imidazolinone treatment, a herbicide inhibiting acetohydroxyacid synthase  catalysing the first step of valine, isoleucine and leucine synthesis  GSTs belonging to the tau (GSTU), phi (GSTF) and zeta (GSTZ) classes are affected, 20 of these being induced and 6 being repressed. In glu1-2 roots, four glutathione S-transferases are induced and two are repressed , the most highly induced of them, was reported to be induced by herbicide treatment, xenobiotic exposure and in the catalase 2 deficient mutant . It was hypothesised that AtGSTU24 could be involved in the conjugation of stress-induced catabolites  are responsive to cold and heat stress, oxidative damage and metal exposure [AtGSTF2 has also been shown to be responsive to several stimuli and the protein interacts with flavonoids in vitro [Glutathione S-transferases , also known as glutathione transferases (GTs), are involved in the second phase of detoxification processes. These enzymes catalyse the conjunction of glutathione (GSH-tripeptide) with electrophilic compounds, to form non toxic derivatives that are ready to be compartimentalised in vacuoles. In addition, GSTs can serve as peroxidases, isomerases and thiol transferases or have non-catalytic functions such as ligand binding and modulation of signalling processes (for review: ). Severabolites  use UDP-activated sugars as donor to catalyse the glycosylation of various metabolites and are hence implicated in a series of mechanisms and pathways, including phase II of the detoxification mechanism.glu1-2 mutant leaves 45 UGT-encoding genes are affected, which represents a third of the approximately 120 UGT-encoding genes that have been identified in the A. thaliana genome  showed that it was able to glycosylate both the 3-OH and the 4-OH position of the benzoate derivative 3,4-dihydroxybenzoic acid [At1g05560) is associated with the callose synthase complex [UGT84A3 (At4g15490) may be involved in sinapate ester metabolism in plants [glu1-2 leaves: UGT73C1 (At2g36750), UGT85A1 (At1g22400) and UGT76C1 (At5g05870). Recombinant UGT73C1 is also able to conjugate transformation products of the explosive 2,4,6-trinitrotoluene [At4g15550 is also upregulated in glu1-2 leaves. UGT74F2 (At2g34820) has been described as a salicylic acid glucosyltransferase [In  review: ). Thirtyoic acid . UGT75B1 complex  and is h complex . UGT84A3n plants . Three gn plants  were alsotoluene . UGT84B1otoluene  and the nsferase ,113 and nsferase .glu1-2 leaves have been shown to be stress responsive. Recently, UGT74E2 (At1g05680) was identified as one of eight genes that were rapidly and highly induced upon treatment with the herbicide imidazolinone [glu1-2 leaves. UGT73B1, UGT73B2 and UGT73B3 have been implicated in the response to oxidative stress and a role in stress response and resistance to Pseudomonas syringae was shown for UGT73B3 and UGT73B5 [Several of the UGT-encoding genes that are highly upregulated in zolinone . This ge UGT73B5 ,116.A. thaliana are induced and five are repressed in glu1-2 leaves , AtDTX3 (At2g04050) and AtDTX4 (At2g04070). AtDTX1 serves as an efflux carrier for plant derived alkaloids [Phase III of xenobiotic detoxification in plants consists of storage of the compounds produced by the mechanisms of two first phases. The multidrug and toxic compound extrusion (MATE) efflux carriers may function in this process, although the transport activities and exact roles of most of these have not yet been described . Fourteelkaloids . To our lkaloids .glu1-2 mutant. It is beyond the scope of the present article to describe these in detail. This can however be exemplified by the striking overlap between the genes induced in leaves of the glu1-2 mutant and those described by Vanderauwera et al. [glu1-2 mutant leaves . The Fd-GOGAT1 deficient A. thaliana mutants described previously display a lethal phenotype [glu1-2 mutant used here, did not prevent plants from showing a chlorotic phenotype, although less severe than in previously published studies.Knocking down the expression of the gene henotype ,7,9. It Fd-GOGAT1 expression is much higher in leaves than in roots of A. thaliana at the steady state  was identified in the SALK T-DNA insertion mutant collection [glu1-2) were obtained. The T-DNA insertion was checked by PCR amplification using a T-DNA primer and a Fd-GOGAT1 specific primer, and subsequent sequencing of the amplicon. A. thaliana ecotype Col-0 was used as wild-type control in all described assays.The llection , seeds wllection  and homoglu1-2 seeds were surface sterilised and sown on solid in vitro cultivation medium consisting of 1x Murashige and Skoog basal salt mixture, 3% sucrose, 0.75% phytoagar (w/v), pH5.7. This medium contains 1650 mg ammonium nitrate/L. Seeds were stratified for 3 days at 4°C before being transferred to a controlled growth chamber under a 16 hour photoperiod (light intensity: 75 μmol.m-2.sec-1) at 21-23°C.Wild-type Col-0 and mutant glu1-2 mutant plants, four biological replicates of each were processed simultaneously through the following procedure. Leaves and roots of 18 day old in vitro grown plantlets were harvested separately and immediately flash-frozen in liquid N2. Harvesting of tissue was performed two hours after onset of the 16 hour light period. The harvested tissue was stored at -80°C until further processing. Total RNA was extracted from plant tissue  using the RNeasy Plant Midi kit  following the supplier's instructions. RNasin  was added to the RNA to the final concentration of 1 U/μl. RNA quality was assessed by standard denaturing agarose gel electrophoresis and RNA concentration was measured with a NanoDrop ND-1000 . To prepare the samples for microarray experiments the "GeneChip Expression Analysis" procedure of Affymetrix  was followed. Briefly, 10 μg total RNA was processed through a one-cycle cDNA synthesis procedure, the resulting double-stranded cDNA was cleaned up and submitted to the synthesis of biotin-labelled cRNA. This biotin-labelled cRNA was then cleaned up, quantified and fragmented before being hybridized to Affymetrix GeneChip Arabidopsis ATH1 genome arrays. After 16 hours of hybridization the arrays were processed through the washing and staining procedures, before being scanned and analysed. Microarray data files have been deposited in the Gene Expression Omnibus (GEO accession number: GSE20493).For microarray experiments of wild-type and The microarray data were preprocessed using the Robust Multichip Average (RMA) package  as impleGenome annotation as given in the tables originates from Affymetrix . This was supplemented/updated by information provided by The Arabidopsis Information Service  and theBiochemical pathways were assessed according to published data (see referred articles at the respective places in the text) and information provided by the AraCyc database , the KyoClassification into GO terms were taken over from the software in question  but AmiGO  and the 2PO4 buffer  in D2O containing 0.05% TSP  and methanol-d4 (1:1). The extract was vortexed for 30s, centrifuged at 4500 rpm for 10 min and filtered through glass wool. Five hundred microliters of the supernatant were taken for NMR spectroscopy analysis.Total metabolites were extracted from freeze-dried plant material according to Liang et al.  with som1H-NMR spectra were recorded with presaturation of the residual water resonance in the interscan delay using a standard Bruker pulse sequence (zgpr). A 90° excitation pulse was used to record 256 FID's with a spectral width of 8389 Hz averaged into 32 k data points with an acquisition time of 3.91 s. The interscan delay was 3 s. 1H, 1H-COSY NMR spectra with the same spectral width as the 1D spectra were recorded with 2048x512 data points in the F2xF1 directions. Presaturation of the residual water resonance was done in the interscan delay using a standard Bruker pulse sequence (cosyqfpr). 16 FID's were recorded for each increment in the F1 direction. A square sine bell window function was applied in both directions and zero filling in the F1 direction was applied to give the processed spectrum a resolution of 2048x2048 data points.NMR spectroscopy was performed at 25°C on a Bruker DRX 600 spectrometer  resonating at 600.13 MHz fitted with a 5 mm BBO probe. The frequency lock was done on MeOD. 1D The NMR spectra were exported from TOPSPIN and imported into R  where thRK, PW, TSJ, DHTT, TRS and AMB drafted the manuscript. RK and PW analysed the transcriptional data. TSJ performed statistical analysis of the transcriptional data. TRS performed NMR spectroscopy and analysed NMR results. TC performed the verification of the T-DNA insertion mutant and a preliminary microarray characterisation on a home-made 2K chip. PW, DHTT and AMB designed the study and AMB coordinated the study. All authors read and approved the final manuscript.glu1-2Transcriptional data of . Detailed lists of genes whose expression is affected in leaves and roots of 18 day old glu1-2 mutant plantsClick here for fileglu1-2 transcriptional dataGOstat analysis of . GO_biological_process terms identified by GOstat [glu1-2 mutant leaves and roots.y GOstat  as beingClick here for fileglu1-2 transcriptional dataPathExpress analysis of . Identification by PathExpress [glu1-2 mutant.hExpress  of affecClick here for fileGeneBins analysis of glu1-2 transcriptional data. BINs identified by GeneBins [glu1-2 organs compared to wild type.GeneBins  as beingClick here for file2-oxoglutarate synthesis and TCA cycle. Genes whose expression is affected in glu1-2 mutant leaves and that encode enzymes involved in 2-oxoglutarate synthesis and the TCA cycle.Click here for filePhotosynthesis and related pathways. Genes whose expression is affected in glu1-2 mutant leaves and roots and that encode enzymes involved in photosynthesis related GO categories and bins as identified by GOstat [y GOstat , AmiGO [y GOstat  and MapMy GOstat  respectiClick here for fileTranscription factors. Genes encoding WRKY, C2H2, CCCH, MYB, bHLH or AP2/ERF transcription factors and that show different expression in the glu1-2 mutant.Click here for fileShikimate pathway and flavonoid biosynthesis. Genes implicated in the shikimate pathway and flavonoid biosynthesis, and that show different expression in the glu1-2 mutant.Click here for fileABC transporters. Genes whose expression is affected in the glu1-2 mutant and that encode ABC transporters.Click here for fileCytochrome P450 monooxygenases. Cytochrome P450-encoding genes whose expression is affected in the glu1-2 mutant.Click here for fileGlutathione S-transferases. Genes encoding glutathione S-transferases (GSTs) and that show different expression in the glu1-2 mutant.Click here for fileUDP-glycosyltransferases. Genes encoding UDP-glycosyltransferases (UGTs) and that show different expression in the glu1-2 mutant.Click here for fileMATE efflux family proteins. Genes coding for multidrug and toxic compound extrusion (MATE) efflux carriers and that show different expression in the glu1-2 mutant.Click here for fileComparison with catalase 2 deficient plants. Comparison of induced transcriptional responses in catalase 2 deficient plants CAT2HP1 and glu1-2 mutant leaves.Click here for file


Objective. Attention-deficit hyperactivity disorder (ADHD) is a developmental disorder characterized by a long-standing pattern of impulsive behavior, hyperkinesia, and inattention. Psychostimulants, for example, methylphenidate, are the treatment of choice for ADHD both in children, adolescents, and adults. Method. The effect of methylphenidate on sleep structure is not well known. We studied the effect of long-acting methylphenidate on sleep in adult ADHD patients, in a naturalistic treatment setting, using actigraphic and polysomnographic recordings. Results. One of our patients experienced manic episode after starting methylphenidate. A wrist-worn accelerometer recording demonstrated a decrease in the duration and quality of sleep. After discontinuation of methylphenidate treatment, the patient's symptoms subsided and there was no need for hospital admission. Actigraphic recording showed a decrease in the amount and quality of the patient's sleep as triggering factor for the manic symptoms. Conclusions. Disruptions of the sleep-wake cycle are probably important etiologic factors in mood disorders, especially bipolar disorder. The changes in length and quality of sleep described in this case report bear close resemblance to those of patients with a manic episode, although these symptoms were induced by methylphenidate. Attention-deficit hyperactivity disorder (ADHD) is a developmental disorder characterized by impulsive behavior, hyperkinesia and inattention. Recent studies suggest that there is a range of abnormalities in neurotransmission in ADHD patients . PsychiaSevere ADHD symptoms are often treated with medication. Psychostimulants are effective in all symptom domains of ADHD. Stimulants such as dextroamphetamine and methylphenidate are used in the treatment of ADHD both in children and adults. A common adverse effect of methylphenidate is a sleep disturbance. In children, even short-acting methylphenidate thrice daily increases sleep onset latency . HoweverOne of the study participants, a 40-year-old man with no prior history of bipolar disorder, experienced a manic episode after the treatment with methylphenidate was started. His switch from euthymia into mania was recorded with a wrist-worn accelerometer. We present herein, for the first time, actigraphic recording data on a switch from euthymia into mania induced by methylphenidate.The diagnosis of ADHD was assessed with the Conners' Adult ADHD Diagnostic Interview for DSM-IV  using muThe patient's response to methylphenidate was clinically rated as good. In addition to alleviation of his ADHD symptoms, his bruxism and nail-biting activities were reduced. However, he became increasingly more talkative and excited during the treatment with methylphenidate. He reported that his subjective quality of sleep was decreased, which was confirmed in the actigraphic recordings . After dInsomnia is known to be a potential adverse effect of psychostimulants and may trigger manic episodes , 9. PatiClinical experience is that disruptions in sleep often predict onset of mood episodes, both mania and depression. Here, methylphenidate disrupted sleep and induced mania-like symptoms in an adult patient with ADHD, but no underlying mood disorder. His reaction seemed to be clearly dose-related and dependent also on the use of long-acting methylphenidate.


Recent studies have not paid a great deal of attention to comorbid attention-deficit/hyperactivity disorder (ADHD) symptoms in autistic children even though it is well known that almost half of children with autism spectrum disorder (ASD) suffer from hyperactivity, inattention and impulsivity. The goal of this study was to evaluate and compare executive functioning (EF) profiles in children with ADHD and in children with ASD with and without comorbid ADHD.Children aged 6 to 18 years old with ADHD (n = 20) or ASD (High-Functioning autism or Asperger syndrome) with (n = 20) and without (n = 20) comorbid ADHD and a typically developing group (n = 20) were compared on a battery of EF tasks comprising inhibition, flexibility, working memory and planning tasks. A MANOVA, effect sizes as well as correlations between ADHD-symptomatology and EF performance were calculated. Age- and IQ-corrected z scores were used.There was a significant effect for the factor group . Post-hoc analysis revealed significant differences between the ADHD and the TD group on the inhibition task for false alarms (p = .01) and between the ADHD group, the ASD+ group (p = .03), the ASD- group (p = .02) and the TD group (p = .01) for omissions. Effect sizes showed clear deficits of ADHD children in inhibition and working memory tasks. Participants with ASD were impaired in planning and flexibility abilities. The ASD+ group showed compared to the ASD- group more problems in inhibitory performance but not in the working memory task.Our findings replicate previous results reporting impairment of ADHD children in inhibition and working memory tasks and of ASD children in planning and flexibility abilities. The ASD + group showed similarities to the ADHD group with regard to inhibitory but not to working memory deficits. Nevertheless the heterogeneity of these and previous results shows that EF assessment is not useful for differential diagnosis between ADHD and ASD. It might be useful for evaluating strengths and weaknesses in individual children. Autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD) are childhood-onset neurodevelopmental disorders affecting key fronto-striatal and fronto-parietal circuits that are important for executive functions ,2. The tSeveral authors have proposed that symptoms of ADHD arise from a primary deficit in a specific EF domain such as response inhibition, working memory, or a more general weakness in executive control ,6. This There are also many empirical reports of executive impairments in individuals with autism spectrum disorders across wide age ranges and functioning levels ,11. HillEFs have been examined in neuropsychological studies that were carried out in direct comparison of children and adolescents with ASD or ADHD. To date six studies have compared EF in ASD and ADHD.Two studies were conducted independently in the year 1999 by Ozonoff et al. and Nyden et al. ,13. OzonGeurts et al. extended the aforementioned studies by examining a broader spectrum of EFs in patients with ADHD and high-functioning autism (HFA) with the aim of distinguishing between the two disorders . The ASDGoldberg et al. report no differences between ADHD and ASD children on response inhibition, planning and flexibility tasks . Both grHappé et al. compared age- and IQ-matched groups with ASD and ADHD and found greater inhibitory problems in the ADHD group on a Go/NoGo, planning and working memory task, while the ASD group was solely worse on a response selection task .A study by Johnson et al. tested children with HFA and ADHD on a Sustained Attention to Response Task (SART) and report of clear deficits in response inhibition and sustained attention in the ADHD group. The HFA group showed dissociation in response inhibition performance .The results of the studies differed partly. A reason for that might be the differences in the age ranges within the sample and the different types of tasks that were applied, whereas mean age and IQ were similar. Table ADHD is still an exclusion criterion for Pervasive Developmental Disorders in ICD-10 and DSM-IV-TR even though there is preliminary evidence of genetic linkage in both disorders at chromosomal locations 2q24 and 16p13, 16p1, 17p11 and 5p13 as well as 15q -22. FurtTo date, studies dealing with the topic of EF deficits in both ASD and ADHD have not devoted a great deal of attention to comorbid ADHD symptoms in the autistic participants, although several authors have described that almost half of the autistic children suffer from comorbid hyperactivity, impulsivity and inattention ,19. In tThe present study aimed to assess the impact of comorbid ADHD-symptoms in children with HFA or Asperger syndrome on the ability on EF tasks. For this purpose, we compared autistic children with and without comorbid ADHD symptoms, children with ADHD and normal healthy children on four EF tasks: inhibition, planning, spatial working memory and flexibility. To the authors' knowledge this is compared to previous studies comparing ADHD and ASD samples the first study including both a pure ASD group AND an ASD with comorbid ADHD group.We predicted that profile differences might exist, with ADHD children being more impaired in inhibition and working memory and children with ASD showing greater difficulties in flexibility and planning referring to the above mentioned studies by Nigg and Hill ,3. With Additionally it was hypothesized that the ASD group with comorbid ADHD symptoms performs worse by an order equivalent to the addition of each disorder individually (additivity hypothesis) and not worse than the combination of the two disorders (over-additivity hypothesis) or similarly to either of the disorders on its own (under-additivity hypothesis) .The total sample of this study consisted of four subgroups. The ASD with comorbid ADHD symptoms group (ASD+) comprised 19 boys and one girl with a diagnosis of either HFA (n = 5) or an Asperger syndrome (n = 15), the ASD without comorbid ADHD symptoms group (ASD-) comprised 16 boys and 4 girls with a high-functioning diagnosis (n = 5) or an Asperger diagnosis (n = 15). The ADHD group consisted of 19 boys and one girl. Also children with a diagnosis of predominantly inattentive type were included. The typically developing (TD) comparison group comprised 14 boys and 6 girls that were recruited through schools, family friends of participants in the clinical groups or personal contacts. Children were not included if they had any psychiatric diagnosis or family history of social or attention related problems.The participants were required not to be taking any central nervous system active medication except for methylphenidate. All were required to be off medication for at least 24 hours prior to the administration of the experimental tasks. This period is described to be sufficient to ensure full wash-out . More paFurthermore the participants were required to have an IQ ≥ 80. Comorbid Oppositional Defiant Disorder (ODD) was allowed in both clinical groups. This inclusion was because findings from studies suggest that ADHD associated with conduct disorder (CD) may be a distinct subtype, but this does not appear to be the case for ADHD associated with ODD . ParticiTable The participants were recruited from our inpatient and outpatient department of child and adolescent psychiatry, while the healthy control group consisted of healthy siblings of the patients or were other children interested in taking part. All new referrals with suspected ADHD or ASD underwent an extensive child psychiatric examination, which was conducted by an experienced child and adolescent psychiatrist according to DSM-IV-TR criteria. Additionally standardized psychopathological measures were used (see diagnostic measures section). IQ was measured using the Culture Fair Intelligence Test, a non-verbal one-dimensional IQ-test . The diaInformed parental consent was obtained for all participants, and the study was approved by the Medical Ethical Committee of the University of Cologne. All children were tested individually in the Department of Child & Adolescent Psychiatry in a quiet room by one of the two researchers. The person testing was blind with regard to the ADHD diagnosis of the autistic participants. Testing was carried out within a larger study that comprised a two-hour session. EF tasks were presented in a fixed order  approximately after the implementation of the first half of the test. Due to the small simple size we decided not to counterbalance the order of the test. Participants were informed that they could discontinue testing at any time and were given positive comments throughout the testing. The parents or caregivers were sent detailed reports on their child's performance on the tests.Autism-Diagnostic Interview-Revised  and the Autism Diagnostic Observation Scale , 12 (Module 2), 10 (Module 3+4)) [Diagnostic Checklist for Pervasive Developmental disorders (DCL-TES) was applied, mainly to exclude ASD in the ADHD children and to differentiate between HFA and Asperger syndrome within the ASD group [Diagnostic Checklist for Oppositional Defiant or Conduct disorders (DCL-SSV) was used to have a dimensional description of ODD-symptoms in both the ASD and the ADHD group.The diagnosis of autistic disorder was made using the le 3+4)) -32. FurtSD group . AdditioDiagnostic Checklist for Hyperkinetic Disorders/ADHD (DCL-HKS). Similar rating scales have been developed in the United States, based solely on DSM-IV criteria for ADHD [The diagnosis of attention deficit/hyperactivity disorder was made using the for ADHD . The numfor ADHD . The chefor ADHD . The cutThe groups ASD + and ADHD show an equal profile without statistically significant differences in the DCL-HKS scores with regard to the criteria of hyperactivity, inattention and impulsivity. Scores of the DCL-TES were as expected high for both ASD groups and low for the ADHD and the TD group. The scores are illustrated in Figure Kiddie-SADS – Lifetime-Version (K-SADS-PL) [Additional comorbid disorders  were assessed using the SADS-PL) . No releThe inhibition (Go/NoGo) task was administered from the "Test for Attentional Performance" (TAP) . In a GoFlexibility, working memory, and planning functions were assessed using sub-tests from the "Cambridge Neuropsychological Automated Test Battery" (CANTAB). This test battery has been employed internationally for 15 years. This battery has already been used by investigators to assess EF in children with normal development, as well as with developmental disorders including autism and ADHD -41. We cThis task measures the ability to attend to specific attributes of compound stimuli, shifting attention from one attribute to another when required. Participants are presented with a series of multidimensional stimuli, consisting of shapes and lines. In stages 1 through 5 of the task, the discrimination and learning stages, participants learn through trial and error to respond selectively to one specific shape, ignoring the other shape and the lines. In stage 6, the intradimensional shift, new shapes and lines, are introduced, but shape continues to be the salient response dimension. In stage 7 the intradimensional reversal, the previously nonreinforced shape now becomes the correct response. At stage 8, during the critical extradimensional shift, however, the correct rule now changes to the other dimension  that has been irrelevant for the preceding dozens of trials. Finally in stage 9, the extradimensional reversal, participants must respond to the previously non reinforced line. The dependent measures were the number of errors committed and the number of trials taken to achieve criterion on stages 6 through 9. When participants failed to achieve criterion (six consecutive correct responses) at a given stage, the test was failed and the maximum number of errors (25) was recorded for all subsequent stages not administered.In this test a trial begins with a number of coloured squares being shown on the screen. The overall aim is that the participant should find a blue "counter" in each of the squares and use them to fill up an empty column on the right hand side of the screen. The child must touch each box in turn until one opens with a blue "counter" inside (a search). Returning to an empty box already sampled on this search is an "between-search error". A "Strategy score" is estimated from the number of searches that start from the same location. The dependent measures were the number of between-search errors, strategies and test duration.This is a computerized test of spatial planning based upon the "Tower of London" Test. The participant is shown displays containing three coloured balls. The displays can easily be perceived as stacks of coloured balls  held in stockings or socks suspended from a beam. The participant must use the balls in the lower display to copy the pattern shown in the upper one. The dependent measures were the number of problems solved in the minimum number of moves, mean of the mean initial thinking time, mean of the subsequent thinking time and test duration.The statistical analysis was carried out using the SPSS for Windows Program Version 14.0.In order to examine group differences between the groups a MANOVA with all EF parameters of the four paradigms as the dependent measures and the group as the between-subject variable and additional post hoc Scheffé tests were calculated. Due to the small sample sizes effect sizes, according to Cohen, were calculated in order to examine group differences between the four groups for the EF parameters of the four paradigms . Since aNext, Pearson correlations were carried out between the different executive variables and the values of the DISYPS ADHD scales  and the DISYPS ASD scales  for the four diagnostic groups.It might be assumed that neuropsychological performances probably improve due to physiological brain maturation. Also IQ deficits are described as being associated with neuropsychological performance ,44. TherBecause of these results, we calculated group differences between the four diagnostic groups using a MANOVA with post-hoc Scheffé tests with age and IQ as the dependent variable and group as the between-subject variable. There was a significant group effect for age  as well as for IQ . Post-hoc tests revealed a significant effect for age between the groups ASD+ vs. ASD- (p = .01) and for IQ between the groups ADHD vs. ASD- (p = .01) as well as the TD group (p = .01).Table On the inhibition task the ADHD group appeared more impaired than and the TD group on all variables with high effect sizes . But also compared to the ASD+ group  and the ASD- group  they performed significantly worse. However the ASD+ group performed less well than the TD (more errors of omission: d = 0.7 and fewer hits: d = 0.7) and the ASD- group (more errors of omission: d = 0.6).Significant group differences were found for the variable false alarms  and omissions  with post hoc group differences between the ADHD and the TD group for false alarms (p = .01) and between the ADHD group, the ASD+ group (p = .03), the ASD- group (p = .02) and the TD group (p = .01) for omissions.The flexibility task was more difficult for participants with ASD and comorbid ADHD symptoms. They made more errors and needed more time for the task compared to the ASD- group (d = 0.6) and the TD group (d = 0.6), but completed more stages compared to the TD group (d = 0.6). The best performance was shown by the ASD- group. Test duration was also longer for the ADHD group with a small effect size (d = 0.4).No statistically significant differences could be found between any of the groups.Participants of the ADHD group performed significantly worse making more errors than the TD group (d = 1.0) as well as needing more strategies than healthy control children (d = 0.7) and autistic children with comorbid ADHD symptoms (d = 0.7). Also the ASD- group made more errors than the TD group (d = 0.6). Furthermore, the ASD+ and the ADHD group needed longer to perform the whole task compared to the ASD- (d = 0.4) and the TD group (d = 0.4). There were no significant group differences on the basis of the MANOVA.There was a medium effect size between the groups ASD- and ADHD (d = 0.6). All clinical groups needed more time between the subtasks. There was a high effect size between the groups ASD- and the control group (d = 0.6). Participants of the ASD+ group had a longer test duration than those of the TD group (d = 0.6).There were no significant group differences for any of the tasks.The Z score plots with medium and high effect sizes between the four groups are shown in Fig. In addition, Pearson product-moment correlations separated for the two groups affected by ADHD-symptoms were used to examine the relationship between all dependent measures of the neuropsychological paradigms and the clinically observed ADHD symptoms  measured with the DCL-HKS.The ADHD group showed only small, but significant correlations for the variable "flexibility errors" with inattention  and for the variable "flexibility test duration" with inattention . In the ASD+ group, the variable "inhibition median" correlated significantly with the total score ADHD  and impulsivity , the variable "inhibition hits" with inattention , the variable "inhibition false alarms" with hyperactivity  and the total score ADHD  as well as the variable "inhibition omissions" with inattention .Furthermore the ASD+ group showed small, but significant correlations for the variable "flexibility errors" with inattention  and the variable "working memory test duration" and the total score ADHD .There were no significant correlations between different executive variables and the values of the ADHD scales in the ASD- and in the TD group.In contrast to the ADHD symptomatology, we tested the relationship between EF and autistic symptoms  with the help of Pearson product-moment correlations for the four groups. We found significant correlations in the ASD – group for the variable "inhibition hits" with impairment of social interaction  and ASD total score , for the variable "inhibition omissions" and all ASD subscale scores  as well as for the variable "flexibility test duration" and "flexibility stages" with stereotype behaviour .The ASD+ group showed significant correlations for the variable "flexibility test duration" and "flexibility stages" with stereotype behaviour .In the ADHD group we found significant correlations for the inhibition paradigm .There were no significant correlations in the TD group.The aims of this study were twofold: to investigate profiles of EF  in ADHD and ASD with special regard to the comorbidity of ADHD in ASD children and to investigate whether ADHD and ASD symptoms are associated with the applied EF tasks in the four diagnostic groups.With regard to the first aim, we found clear deficits in inhibition and working memory tasks in the ADHD group, whereas the ASD children showed deficits in flexibility and in planning tasks. ASD+ children were compared to those of the ASD- group particularly impaired in inhibitory performance and flexibility as well as test duration on all the tasks. How do these results fit in with our predictions based on the literature?The expectation that the ADHD children would be more impaired in inhibitory control, especially with regard to errors of omission and commission, was confirmed for the Go/NoGo-task for all variables. Our initial prediction that ASD+ children would show inhibition deficits according to an additivity hypothesis was partly confirmed, as these children showed worse performance making more errors of omission and less hits compared to the healthy control children. Our results are partly in line with findings of previous studies. Ozonoff and Happé found more deficits in response inhibition for ADHD children than for autistic children comparing ADHD and ASD groups, whereas the Nyden, Johnson and partly the Geurts study revealed also deficits for ASD children -17. HoweAn interesting finding of our study is that comorbid ADHD symptoms seem to worsen inhibition performance in ASD children with comorbid ADHD, as pure ASD children performed rather well in comparison to the pure ADHD group in our study. Previous studies including comorbid ADHD symptoms couldn't find differences between ASD and ADHD children and vice versa. This underlines the importance of taking into account severe inattention and hyperactivity problems warranting an ADHD diagnosis in ASD children when interpreting inhibition data. If comorbid ADHD symptoms are not statistically referred to individual inhibition problems of children with ASD might not be detected due to a too large heterogeneity of the samples.The results for the flexibility task show differences on the basis of effect sizes. The ASD- group made less errors than the control group. As also discussed by Happé one reason for the absence of differences between the ASD and the TD group might be the high proportion of participants with Asperger syndrome . With reEven though both groups affected by ADHD needed more time to perform the working memory task, especially in the ADHD-group medium to high effect sizes are apparent with poorer performances in comparison to the control group, whereas pure autistic children also made more errors than the healthy children. Happé et al. also describe deficits on the same working memory task for the ADHD group but not for the ASD group, whereas Goldberg et al. found deficits for both groups with poorer performance of the autistic children ,16. One As we found only small problems of working memory in both ASD groups, comorbid ADHD symptoms don't seem to play the key role in working memory performance. One could argue that there were no effects in the ASD groups due to a wide age range in our study (6–18 years) as age-related improvement for the working memory task was described in particular for ASD children in an analysis of developmental age . This diWith regard to the performance in the planning task, our results are difficult to interpret. Even effect sizes revealed only medium effects for the ASD+ group concerning duration of the task and medium effects for the mean initial thinking time and the mean subsequent thinking time especially for the ASD- group. ASD+ children also showed deficits on these variables. These results are partly in line with a study by Ozonoff et al., who applied the CANTAB planning task in a large sample of 79 autistic individuals, finding no differences for the mean initial thinking time, but for the mean subsequent thinking time . The numOur second aim was to examine relationships between EF and clinical symptoms of ADHD and ASD. In our study clinically observed ADHD symptoms don't correlate with EF deficits in ADHD children, whereas inhibition performance shows an interaction of comorbid ADHD symptoms in ASD children on all measures, especially with the symptom of inattention. Also test duration seems to be influenced by ADHD symptoms in this group.Interestingly even though there were low ASD scores in the ADHD sample, inhibitory parameters are associated with ASD symptoms in the ADHD group. Correlations of ASD symptoms and EF don't seem to follow a fixed pattern in the ASD groups.These results underline the difficulty of bringing together clinically observed behaviour and neuropsychologically measured EF functions. This indicates a need for caution when attempting to transfer laboratory outcomes to daily life.Due to the small sample size, this investigation can only be seen as a descriptive attempt to approach the problem of influence of attention disorders and increased impulsivity and hyperactivity as postulated for example by Geurts et al. . HoweverFinally the characteristics of our study sample  limit the comparability of these findings with respect to other research reports with differently characterized samples.One reason for our decision to control for IQ, well knowing that there is a current controversy about this topic, was the fact that we partly wanted to avoid issues concerning late maturation of the frontal lobes and the close overlap between the constructs of EF and fluid intelligence ,51. ThusThis is the first study investigating specifically the impact of comorbid ADHD-symptoms in children with high-functioning ASD on EF performance. To the authors knowledge this is the first study using a four-sample design including two ASD groups (with and without comorbid ADHD symptoms). Our hypothesis that ADHD children are more impaired in inhibition and working memory tasks whereas ASD children show more deficits in planning and flexibility abilities were confirmed. The hypothesis concerning flexibility was partly confirmed as only ASD children with comorbid ADHD had deficits in this task.The additivity hypothesis (see Introduction section) saying that the ASD+ group performs worse by an order equivalent to the addition of each disorder individually was partly confirmed with clear deficits in inhibitory performance of these children compared to the ASD- group. However this effect could not be found for the working memory task. The hypothesis was confirmed as in planning and flexibility abilities there were no additional deficits than those presented by the autistic children themselves.Furthermore the study showed that individuals with ASD and comorbid ADHD have more of a speed than a comprehension problem in planning, working memory or flexibility tasks.In conclusion the paper shows that ASD related studies should take symptoms of ADHD into account as the dimensional overlap in EF functions in ADHD and ASD with comorbid inattention and hyperactivity symptoms might be used to describe an endophenotype. As also stated by Verté et al. "dimensional (or even multivariate) approaches should be employed in order to understand the relationship between multiple overlapping endophenotypes in more depth" . GeneticThe author(s) declare that they have no competing interests.JS participated in the design and coordination of the study, performed the statistical analysis and wrote the manuscript.DM and NB carried out the recruiting and neuropsychological assessment of the participants and contributed to the interpretation of the data.MS revised the manuscript.GL has been involved in designing the study and revising the manuscript. He gave final approval of the final version to be published.All authors read and approved the final the final manuscript


Low birth weight (LBW) is considered as a major multifaceted public health concern. Seventy-two percent of LBW infants are born in Asia. An estimation of 8% LBW infants has been reported for Eastern Mediterranean region including Iran. This study investigated contributory factors of LBW in singleton term births in Tehran, Iran. Tehran is a multicultural metropolitan area and a sample from the general population in Tehran could be regarded as a representative sample of urban population in Iran.This was a retrospective study using data from 15 university maternity hospitals in Tehran, Iran. Data on all singleton term births in these hospitals were extracted from case records during a one calendar year. Study variables included: maternal age, maternal educational level, history of LBW deliveries, history of preterm labor, cigarette smoking during pregnancy, number of parities, chronic diseases and residential area (Tehran versus suburbs of Tehran). In order to examine the relationship between LBW and demographic and reproductive variables the adjusted logistic regression analysis was performed.In all, data for 3734 term pregnancies were extracted. The mean age of women was 25.7 (SD = 5.3) years and 5.2% of term births were LBW. In addition to association between LBW and maternal age, significant risk factors for LBW were: history of LBW deliveries , smoking during pregnancy  and chronic diseases .The findings indicate that in addition to maternal age, history of LBW deliveries; smoking during pregnancy and chronic diseases are significant determinants of LBW in this population. This is consistent with national and international findings indicating that maternal variables and risk behaviors during pregnancy play important roles on LBW. Low birth weight (LBW) is a reliable indicator in monitoring and evaluating the success of maternal and child health programs and has been defined as a birth weight less than 2500 gr . It is eA baby's low weight at birth is either the result of preterm birth or of intrauterine growth retardation (IUGR) . The latThe evidence suggests preterm birth as a main cause of newborn mortality and morbidity . Indeed,This study investigated the contribution of socio-demographic and reproductive-obstetrical risk factors on LBW in all singleton term births that referred from Tehran and its suburbs to the main general and teaching hospitals in Tehran during a one calendar year (2005).A retrospective study was conducted in 15 maternity wards of the main general and teaching hospitals in Tehran, Iran. The ethics committee of Tehran University of Medical Sciences approved the study. Using hospital records, data on all singleton term births  of married pregnant women in these hospitals during year 2005 were extracted. Studied variables included maternal age, maternal education, number of parities, history of LBW deliveries (HLBW), history of preterm labor (HPL), cigarette smoking during pregnancy, chronic diseases and residential area (Tehran versus suburbs of Tehran). Mothers' chronic diseases were considered as categorical variable: 1) none (no report of any disease in case notes), 2) hypertension (most reported condition) and 3) others. The latter included renal, heart, respiratory, arthritis and several other chronic diseases. There were no other LBW related data available. Birth outcome was defined as LBW and covered IUGR as well. All term LBW babies had been examined by a gynecologist. According to sonography results and weight chart for gestational ages, the diagnosis of IUGR was established.The regression analysis was performed to calculate crude and adjusted odds ratios and to examine the predictive effect of variables studied on risk for LBW. LBW was considered as dependent variable and was categorized into two groups: <2500 gr. and ≥2500 gr. Other variables were entered into the model as key independent variables and except "maternal age and number of deliveries"; all other variables were entered into the model as categorical data.In all, 3734 pregnant women were studied. The mean age of mothers and the mean duration of pregnancy were 25.7 (SD = 5.3) years and 39.03 SD = 1.36) weeks respectively. Overall, 5.2% of term births were LBW and of these 4% had been recognized as IUGR babies. The mean birth weight was 3.2 (SD = 0.47) Kg. Self-reported cigarette smoking was 1.2% (n = 45). Table .36 weeksThe findings of regression analysis for crude and adjusted odds ratios (OR) of LBW and its determinants are shown in table Maternal education did not show a significant relation with LBW, but increased risk was observed for less educated mothers (OR = 3.22) and those with secondary educational level (OR = 3.44). Although residential area (Tehran versus suburbs of Tehran) was not significant, an increased risk (OR = 1.24) was observed for women referred from suburbs of Tehran.This paper evaluated the LBW contributions in a representative sample of singleton term births in the university hospitals in Tehran, Iran during 2005. The findings showed that most of the term LBW babies are recognized as IUGR (4% of 5.2%). Evidence suggests in developing countries most of LBW infants are due to IUGR . In a siBased on adjusted logistic regression analysis, maternal age was a protective factor for LBW and one year age increase, showed a 4% risk reduction Table . A studyThe present study indicated that obstetric history of previous LBW deliveries was a significant risk factor for LBW (OR = 2.53). The findings from this study with a relatively large sample of singleton term births in Tehran, Iran compares well to the findings from other studies. A large study by Kramer indicated risk of delivering an IUGR infant was 2.75 times greater for women with one or more previous LBW infants than for women with no history of LBW deliveries . AnotherWe did not find a significant relationship between LBW and number of parities (p = 0.84). Studies on the topic have shown primiparous women have a greater risk of IUGR than multiparous women .Also, cigarette smoking was found as a risk factor for LBW (OR = 4.64), although it was self-reported. Evidence suggests the strong effect of cigarette smoking during pregnancy on LBW even after controlling for other variables -19. PoliMaternal history of chronic diseases including hypertension and other chronic conditions increased the risk of giving birth to a LBW infant by 3.70 and 2.04 folds respectively. Documented research has confirmed that maternal diseases increase the risk of delivering LBW infants ,21.Although, maternal educational level in illiterate-primary and secondary-high school grades increased the risk of LBW (OR = 3.32 & 3.44 respectively), there was not a significant association. Well established studies have indicated that mothers with lower educational level give birth more to LBW neonates ,11,22.Finally, residential area (Tehran versus suburbs of Tehran) in adjusted analysis did not show a statistical significant relationship with LBW, but an increased risk OR = 1.24) was observed for pregnant women from suburbs of Tehran. Investigating quality of primary care may explain the region differences in LBW. Studies on LBW have suggested significant associations with socioeconomic indicators and area deprivation. Women with lower socio-economic status and those living in deprived areas give birth more to LBW infants ,23,24. was obseThis study provided data on several risk factors for LBW and IUGR in Tehran, Iran. As LBW would induce complications during infancy period and life course, prevention and control of its determinant factors should be considered in primary health care settings in order to improve mother and child health.LBW: Low Birth Weight; IUGR: Intra Uterine Growth Retardation; SGA: Small for Gestational Age; HLBWD: History of LBW Deliveries; HPD: History of Preterm Labor; OR: Odds Ratio; CI: Confidence Interval.The author(s) declare that they have no competing interests.MV and ST designed and conducted the study. MV and AM analyzed the data and wrote the paper. All authors read and approved the manuscript.The pre-publication history for this paper can be accessed here: