Formins are multidomain proteins defined by a conserved FH2 (formin homology 2) domain with actin nucleation activity preceded by a proline-rich FH1 (formin homology 1) domain. Formins act as profilin-modulated processive actin nucleators conserved throughout a wide range of eukaryotes.Dictyostelium discoideum. With the exception of ForI and ForC all other formins conform to the domain structure GBD/FH3-FH1-FH2-DAD, where DAD is the Diaphanous autoinhibition domain and GBD/FH3 is the Rho GTPase-binding domain/formin homology 3 domain that we propose to represent a single domain. ForC lacks a FH1 domain, ForI lacks recognizable GBD/FH3 and DAD domains and ForA, E and J have additional unique domains. To establish the relationship between formins of Dictyostelium and other organisms we constructed a phylogenetic tree based on the alignment of FH2 domains. Real-time PCR was used to study the expression pattern of formin genes. Expression of forC, D, I and J increased during transition to multi-cellular stages, while the rest of genes displayed less marked developmental variations. During sexual development, expression of forH and forI displayed a significant increase in fusion competent cells.We present a detailed sequence analysis of the 10 formins (ForA to J) identified in the genome of the social amoeba Dictyostelium formins: all isoforms might display actin nucleation activity and, with the exception of ForI, might also be susceptible to autoinhibition and to regulation by Rho GTPases. The architecture GBD/FH3-FH1-FH2-DAD appears common to almost all Dictyostelium, fungal and metazoan formins, for which we propose the denomination of conventional formins, and implies a common regulatory mechanism.Our analysis allows some preliminary insight into the functionality of  Mice with mutant alleles fail to form proper limbs and kidneys [Diaphanous) [Eukaryotic cells rely on de novo nucleation mechanisms to generate actin filaments in order to elicit spatial and temporal remodeling of their actin cytoskeleton. Besides the Arp2/3 complex, nucleation activity has been recently demonstrated also for formins (reviewed in ). Forminphanous) ,5. Due tphanous) ).The FH2 (formin homology 2) domain is the defining feature of all formins. It is very well conserved and is almost invariably preceded by a proline-rich region, the FH1 (formin homology 1) domain ,7. In viIn most fungal and metazoan formins the FH1-FH2 core is accompanied by a less well conserved N-terminal FH3 (formin homology 3) domain involved in targeting . In planDictyostelium discoideum is an attractive model organism to investigate the components of the actin cytoskeleton and the signaling pathways involved in its regulation [Dictyostelium amoebae are equipped with a complex actin cytoskeleton that endows the cells with motile behavior comparable to that of human leukocytes. In fact, a genome-wide survey revealed that the repertoire of cytoskeletal components of Dictyostelium is more similar to metazoa followed by fungi than to plants . In Dictyostelium, nine formins have been previously identified but only three of them have been characterized to some extent [In vivo experiments with GFP fusions showed that the N-terminal region of ForC targets the protein to places of active actin reorganization, like macropinosomes, phagocytic cups and cell-to-cell contacts [The social amoeba gulation ,19. Dicte extent . Mutantscontacts .Dictyostelium sequencing projects in order to achieve a complete inventory of formin genes. A detailed sequence analysis of the 10 formins identified revealed that, with the exception of ForI and ForC, all other formins conform to the domain structure GBD/FH3-FH1-FH2-DAD present in almost all fungal and metazoan formins, for which we propose the denomination of conventional formins. Our sequence analysis also indicates that the GBD and FH3 domains constitute a single domain also found in two Dictyostelium RasGEFs (guanine nucleotide exchange factors). The expression pattern of formin genes during asexual and sexual development was studied using real-time PCR. Our analysis allows some preliminary insight into the functionality of Dictyostelium formins: all isoforms might display actin nucleation activity and, with the exception of ForI, might also be susceptible to autoinhibition and regulation by Rho GTPases.We have made use of the information released by the Dictyostelium [Dictyostelium we sought to exploit the available databases in order to achieve a complete inventory of formin genes in its entire length. The sequences already reported by Kitayama et al. [Dictyostelium genomic DNA database. This allowed assembly of complete genomic sequence for forA through forI. In order to verify the predicted amino acid sequence for each formin, Blast searches were performed against the Dictyostelium EST database. In cases where no EST sequences were available, like forG and forI, introns were verified after RT-PCR.In a previous publication 9 genes that potentially encode proteins of the formin family were identified in ostelium . For soma et al.  were useforJ, whose genomic sequence was also retrieved and inspected. Recent completion of the assembly of the Dictyostelium genome allowed us to confirm our gene predictions and map each formin gene to its corresponding chromosome locus . Formin genes are dispersed all over the six chromosomes (each chromosome harbors at least one formin gene), and in no case two or more genes are placed adjacent to each other  along with these two intron positions underscore the view that all Dictyostelium formin genes might have arisen from a common ancestor gene. After duplications and divergence from this ancestral formin gene introns were acquired or lost and additional domains and extensions were appended to some genes.Only two intron positions are conserved among es Figs.  and 4. IDictyostelium formins was determined by means of bioinformatics tools and visual inspection. Although formins vary considerably in length (935 residues of ForI versus 2546 of ForJ), with few exceptions they have in common a core of about 1100 residues that harbors a GBD/FH3-FH1-FH2-DAD structure characteristic of most fungal and metazoan formins  have one or more stretches of intervening repetitive sequences of variable length rich in Arg, Gln or Ser. Such repetitive sequences are characteristic of many Dictyostelium genes. The crystal structure of the FH2 domain of two formins, Bni1p and mDia1, has been recently solved [Dictyostelium formins in the context of these two structures. The FH2 domain fold is almost entirely α-helical. It is a stable dimer that forms a closed parallelogram-shaped ring. The structure of this domain can be subdivided into subdomains. At the N-terminus a so-called lasso is connected to a globular knob  but the important methionine residue (Met7) [Dictyostelium formins as well as in members of the FHOD (formin homology domain containing protein) and plant class1 subfamilies.All residues of the sequence motif GNY/FMN participate in dimerization. This motif is also highly conserved in almost all e (Met7)  is preseDictyostelium formins) and Arg5 (substituted by Lys in ForB and ForE). These residues were found mutated in temperature-sensitive yeast mutants [Also very conserved are some residues probably involved in binding to actin, like Ile3 (absolutely conserved) in the N-terminal subdomain and Lys9 in the post region (substituted by Arg in ForB and ForH). Mutation of these residues in Bni1p to Ala and Asp, respectively, abolished actin nucleation and barbed end capping activity of the FH2 domain , and rep mutants ,24, and  mutants .Dictyostelium formins, indicating that all ten formins might be functional actin nucleators.In summary, all essential residues in the FH2 domain revealed by structural and functional studies in metazoan and fungal formins are conserved in Dictyostelium and other organisms and to investigate whether different species share subfamilies of formins, we constructed a phylogenetic tree based on the alignment of complete sets of sequences of FH2 domains from selected organisms, including representatives of fungi, plants, invertebrates and vertebrates. We retrieved sequences of already characterized formins and additionally we made a search of further available sequences through the SMART server with the FH2 domain as query. Appart from the ten sequences of Dictyostelium, we collected a total of 62 sequences, 21 from plants, 5 from yeasts, 6 from D. melanogaster, 6 from C. elegans and 14 from human. Taking into account that some genes might not have been predicted accurately and that predicted proteins not supported by EST sequences were not considered for our analysis, further metazoan formins, especially from human, most probably went unidentified in our search.In order to establish the relationship between formins of C. elegans members are more divergent. The phylogenetic analysis reveals clustering of most formins into well defined classes. Yeast formins form a separate class whereas plant formins significantly group into any of two classes. Metazoan formins do not constitute a single cluster, rather they distribute into a number of subfamilies. The FHOD, Diaphanous and FMNL (formin in leukocytes) subfamilies have representatives in human, D. melanogaster and C. elegans. The Cappuccino/Formin and DAAM (Dishevelled-asssociated activator of morphogenesis) subfamilies, as well as a novel subfamily, is present in human and D. melanogaster, but seems to be absent in C. elegans. Delphilin constitutes a subfamily with a unique member present only in human. Finally, C. elegans has some additional divergent formins apparently unique to this organism.The phylogenetic tree Fig.  supportsDictyostelium formins are 45.5% similar  to each other, with ForC being only slightly more divergent (40.0%/20.4% similarity/identity to the rest of Dictyostelium formins). A comparable degree of similarity (identity) was found to members of several subfamilies of metazoan formins, and ranged between 40% (20%) and 48% (24%). Similarity (identity) to plant and yeast formins was lower: 38% (19%) and 36% (17%) respectively. Dictyostelium ForC and ForG cluster together with the Cappuccino/Formin group (75% bootstraps), whereas ForI very weakly clusters with the FHOD subfamily (53% bootstraps). However, taking into account that the FH2 domain is highly conserved, the position of these three Dictyostelium formins in the tree does not necessarily mean functional relationship with the mammalian counterpart, because other domains are probably responsible for diversity of localization and function. Bootstrapping does not support a significant clustering of the rest of the Dictyostelium formins, and only few members cluster together with a reasonably high number of bootstraps .On average, Dictyostelium, with the notable exception of ForC. The length of the FH1 domains is very variable among formins (10 to >500 amino acids). It constitutes a binding site for the actin monomer binding protein profilin, as well as for SH3 and WW domain containing signaling proteins [Dictyostelium formis have a variable number of these motifs, between 1 in ForD and 8 in ForA , RasGEFs, fungal formins and members of the Diaphanous, DAAM, FMNL and FHOD subfamilies .We constructed a phylogenetic tree based on a multiple alignment of the GBD/FH3 domain of ies Fig. . With feain Fig. . In manyDictyostelium formins revealed a DAD in all members with the exception of ForI  or downstream of the FH2 domain (ForD and ForJ) that might constitute potential protein interaction sites with regulatory or targeting functions.Like metazoan and fungal formins, most nds Fig. . For exaDictyostelium formins have additional recognizable domains at their N-terminus  or gradually increased (forF) or decreased  after the onset of development.The expression patterns observed during asexual development can be classified into two major groups. Expression of forH and forI displayed a significant increase of about 3-fold in fusion competent cells compared to fusion incompetent cells. Cells cultured in light submerged conditions have a reduced sexual fusion competency [forH and forI were enriched in fusion competent compared to light submerged cells, indicating that this enrichment is related to the acquisition of the fusion competence rather than to the submerged condition that was included to induce the fusion competence.When expression was analyzed during sexual development only mpetency ,33. In pDictyostelium, which in this organism comprises 10 genes. A comparison of the domain composition of formins from diverse phyla allows their grouping into four major classes , which includes all fungal and almost all metazoan formins. This is in agreement with a genome wide analysis that places Dictyostelium closer to fungi and metazoa than to plants .We have performed a detailed sequence and expression analysis of the formin family of ses Fig. . In geneWith very few exceptions all formins have in common a FH2 domain immediately preceded by a FH1 domain. The FH1-FH2 combination constitutes the minimal core that is fully functional in terms of actin nucleation and elongation activity . We therefore propose the use of the name conventional formins for those subfamilies with the general structure GBD/FH3-FH1-FH2, although in particular members or in alternatively spliced variants a domain (but never the FH2) might be absent, indicating whether the protein is Rho-regulated where documented experimentally. The name Diaphanous-related formin should be restricted to the metazoan members of the Diaphanous subfamily, like human DRF1 to 3.The designation Diaphanous-related formin has been applied to those formins that interact with activated Rho GTPases . HoweverDictyostelium formins is scarce. Only three isoforms, formins A, B and C have been characterized to some extent. Mutants lacking ForA, ForB or both showed no detectable phenotype, whereas deletion of forC led to formation of aberrant fruiting bodies with short stalks and unlifted sori, suggesting this formin mediates actin remodeling during multicellular stages [Dictyostelium formins are expected to be functional according to their highly conserved FH1-FH2 structure; therefore a certain degree of functional redundancy is expected. However, diversity might arise through specific targeting and activation by Rho GTPases conferred by the GBD/FH3 domain, through interaction of specific SH3-domain containing proteins with the FH1 domain and by virtue of unique additional domains. These issues need to be addressed experimentally in the future.Functional data on r stages . DictyosForC and ForI might be exceptions in terms of regulation. ForC lacks a FH1 domain and consequently does not bind to profilins . AlthougDictyostelium formins have domains at their N-termini that are not found in other formins and might confer unique additional functions or ways of regulation or targeting. The C2 and C1 domains of ForA and ForE, respectively, might regulate activation or targeting of the molecule through interaction with specific lipids [Three c lipids ,30, whilc lipids . In genec lipids ,16 and tforC, D, I and J, displayed an increase in expression during transition to multi-cellular stages. During this phase cells acquire aggregation competence in parallel with maturation of signaling pathways involved in remodeling of the cytoskeleton. At least for forC gene expression data correlate with a developmental role, as mentioned above [rac1b and racF2 was found increased during the analysis of a gamete-enriched cDNA library [Functional diversity might also be related to different patterns of local and temporal gene expression. Our gene expression analyses also suggest specific roles during asexual and sexual development. Four genes in particular, ed above . ForH an library . It is tDictyostelium discoideum expresses 10 formins that with few exceptions conform to the domain structure GBD/FH3-FH1-FH2-DAD. This arhitecture and the high degree of conservation of the FH2 domain allow some preliminary conclusions about the functionality of Dictyostelium formins: all isoforms may display actin nucleation activity and, with the exception of ForI, may also be susceptible to autoinhibition and to regulation by Rho GTPases. Although functional redundancy may be expected to occur to some extent among Dictyostelium formins, specific roles may be conferred by the GBD/FH3 domain, which is less well conserved than the FH2 domain, and by specific patterns of gene expression during asexual and sexual development.The social amoeba Dictyostelium, fungal and most metazoan formins can be grouped within the class of what we designate conventional formins, characterized by the structure GBD/FH3-FH1-FH2-DAD. The GBD and FH3 domains, whose boundaries had not been defined previously, probably constitute a single domain. The architecture shared by conventional formins implies a common regulatory mechanism based on autoinhibition through intramoleculr interaction of the GBD/FH3 and the DAD domains and activation through release of this interaction upon binding of Rho GTPases. Formins of the other classes (plant formins and Delphilin) lack GBD/FH3 and DAD domains and must therefore have other mechanisms of activation.We propose four major classes of formins based on a comparison of the domain composition of proteins from diverse phyla. Note. While our manuscript was under review a phylogenetic analysis of the FH2 domain by H. N Higgs and K. J. Peterson has been published. These authors used a larger set of FH2 domains that includes only three formins from Dictyostelium. The topology of the phylogenetic tree described in that article and that of our tree are essentially coincident, and all seven metazoan groups identified by their authors can be found in our tree, with the novel subfamily INV comprising our HsKIAA1727, DmAE003560 and CeAF106580 sequences. Higgs and Peterson, however, do not recognize the GBD/FH3 region as a domain present in a larger number of formin subfamilies.Dictyostelium formins were used as query for BLAST searches [Dictyostelium genome project databases at The Welcome Trust Sanger Institute, Baylor College of Medicine, The University of Cologne and the Department of Genome Analysis of the Institute of Molecular Biotechnology in Jena. Nearly all of this data was generated at the aforementioned institutes with a small part of it produced at the Institute Pasteur. After assembly of the genome further analyses were performed through the Dictybase server [Dictyostelium formins can be found in Table The amino acid or DNA sequences of searches  of the De server . BLAST se server . AccessiS. cerevisiae Bni1p, P41832; Bnr1p, P40450; S. pombe Fus1, L37838; Cdc12, 786133; For3, AL035247. D. melanogaster Cappuccino, U34258; Diaphanous, U11288; FHOD, AE003554; FMNL, BT003654; DAAM, AAF45601; a novel formin, AE003560. C. elegans FHOD, U88314; Cyk-1, U40187; FMNL, AC024798; novel formins, Z78013, AF106580 and Z22174. H. sapiens Formin 1, AK127078; Formin 2, XM_351329; FHOD1, AF113615; FHOD3/FHOS2, KIAA1695; DRF1, AF05187; DRF2, Y15909; DRF3, BC034952; Delphilin, XM_353725; FMNL1, AF432213; FMNL2/FHOD2, KIAA1902; WBP3/FMNL3, NM_175736; DAAM1, NM_014992; DAAM2, AL833083; a novel formin KIAA1727. Sequences of plant formins were obtained from Cvrčková et al. [Dictyostelium RasGEF-L and RasGEF-V can be accessed at Dictybase [Accession numbers of the sequences retrieved for phylogenetic analyses are as follows. Protein sequences were aligned using the ClustalX  program D. discoideum AX2 strain was grown at 21°C in shaking suspension in axenic HL5 medium [K. aerogenes in BSS either in the darkness or in the light. Cells cultured for 15 hours in the dark become fusion-competent cells. However, cells cultured for 15 hours in the light condition exhibit reduced fusion competency, and are designated light submerged cells. Cells on SM agar plates [5 medium . AX2 cel5 medium . In brier plates  are fusiTotal RNA was purified from both asexually and sexually developing cells with the TRIZOL reagent . Asexually developing cells on phosphate agar plates  were colFor RT-PCR, first strand cDNA synthesis was performed with M-MLV reverse transcriptase  on poly A+ mRNA purified with the Oligotex system  from total RNA. PCR fragments were cloned into the pGEM-T Easy vector system  and sequenced. DNA sequencing was done at the service laboratory of the Center for Molecular Medicine, Cologne, using an automated sequencer .FR conceived the study, performed the assembly of genomic sequences and the sequence alignments and drafted the manuscript. TM and HU carried out the gene expression studies. AKM performed RT-PCR and cloning. CK and TQPU participated in the design of the study and the assembly of genomic sequences. All authors read and approved the final manuscript.


Anxiety and depression co-occur in children and adolescents with anxiety commonly preceding depression. Although there is some evidence to suggest that the association between early anxiety and later depression is explained by a shared genetic aetiology, the contribution of environmental factors is less well examined and it is unknown whether anxiety itself is a phenotypic risk factor for later depression. These explanations of the association between early anxiety and later depression were evaluated.Anxiety and depressive symptoms were assessed longitudinally in a U.K. population-based sample of 676 twins aged 5–17 at baseline. At baseline, anxiety and depression were assessed by parental questionnaire. Depression was assessed three years later by parental and adolescent questionnaire.Shared genetic effects between early anxiety and later depression were found. A model of a phenotypic risk effect from early anxiety on later depression provided a poor fit to the data. However, there were significant genetic effects specific to later depression, showing that early anxiety and later depression do not index entirely the same genetic risk.Anxiety and depression are associated over time because they share a partly common genetic aetiology rather than because the anxiety phenotype leads to later depression. Anxiety and depressive disorders are some of the most common psychiatric diagnoses in children and adolescents respectively. Both are known to be associated with major impairment in childhood and adverse consequences in later life -4. EstimDepression and anxiety co-occur more commonly than would be expected by chance in children and adolescents. This co-occurrence has been identified both in clinical studies of children and adolescents and general population samples that have examined sub-clinical levels of depression and anxiety symptoms ,17. MoreCross-sectional twin studies of children ,29 and aIn the present study, we set out to examine two hypotheses that may explain the observed associations between early anxiety and later depression.1. Early anxiety symptoms and later depression symptoms are associated because of shared risk factors.2. The association between anxiety symptoms and later depression symptoms is mediated by a risk effect of the phenotype of anxiety.Families from a systematically ascertained, population-based register of all twin births between 1980 and 1991 in South Wales, U.K. were invited to participate. This register forms a sub-sample of the Cardiff Study of All-Wales and North West of England Twins (CASTANET). Twins who had emigrated were excluded, as were cases in which one of the twins had died or had a serious illness. At the first wave of data collection in 1997, there were a total of 1109 pairs of twins aged 5–17 years although not all of these individuals were eligible to participate at both time points (see below). Data were collected by postal questionnaire. Families received three reminders and telephone reminders when numbers could be traced. The same methods were used three years later to collect longitudinal data except that families received four reminders. To be invited to participate in the follow-up study, we required that the twins were living together in the same home and were under the age of 18 years. Twins were required to live in the same home in order to minimise heterogeneity of environmental risk factors that can impact on genetic and environmental parameter estimates. The focus of the follow-up study was childhood psychopathology and for that reason young people aged 18 and over were not included. At time 1, there were 986 twin pairs who were within the age range of the study at both time points.In the first wave of the study , 670 families provided questionnaire responses giving a response rate of 61%. Comparison of responders and non-responders using Townsend Scores  which inOf these, 338 families replied, giving a total response rate of 75%. There were no significant socio-demographic differences between responders and non-responders at time 2 . Zygosity was assigned using a twin similarity questionnaire which has been shown to be over 90% accurate in distinguishing identical  from fraternal  twins [At time 1, parents were asked to complete the Children's Revised Manifest Anxiety Scale  which asFor descriptive statistics, (correlations and mean comparisons), the survey commands in the program STATA  were use2 critical value for the number of degrees of freedom gained in the reduced model.Analysing data from twins provides a means of estimating the relative contribution of genetic and environmental effects on individual variation in behaviour. In the basic (ACE) model, variation can arise from three sources: 1) additive genetic effects (A); 2) common environmental effects (C); 3) unique environmental effects (E). Common environmental effects are non-genetic factors that serve to make twins more similar to one another while unique environmental effects are non-genetic factors that uniquely influence one individual within a twin pair and tend to make the individuals in a twin pair different from each other. Model fitting was carried out using the programs Mx  and LISRBivariate analysis allows the covariance of two traits to be partitioned into covariance that is due to additive genetic factors, common environmental factors and unique environmental factors. The covariance parameters for the Cholesky model presented . Qualitative sex differences test whether the set of genes influencing the phenotype differs by gender i.e. different genes , this is done by estimating the genetic correlation for opposite sex DZ pairs and comparing the fit of this model to one that constrained the genetic correlation to 0.5. In addition, a bivariate sex limitation model was tested . This moThere were no significant mean differences on anxiety or depressive symptoms by gender . Age was not associated with anxiety or depressive symptoms . The mean age of children at time 1 was 10.58, range 5.58–17.83, and at time 2, was, 12.64, range 8.75–17.25. Symptoms of early anxiety and later depression were strongly correlated (parent-rated symptoms r = .479. The correlation was slightly lower for symptoms across rater (parent rated anxiety and adolescent rated depression), r = .335.2 = 1.505, Δ df = 3), nor were there qualitative genetic differences . For depression, univariate models for parent-rated and self-rated scores indicated no significant gender effects for the magnitude of genetic effects  nor qualitative gender differences . Finally, for parent rated symptoms, results from the bivariate sex limitation Cholesky model showed no significant gender differences in the covariation between anxiety and depression in that the genetic and environmental covariation could be equated across the genders with no significant deterioration in fit . However, for self-rated symptoms, one parameter, i.e., the non-shared environmental covariation parameter, could not be equated across the genders . Estimates from this model for boys were; Aanx = 50, Canx = 17, Eanx = 32, Ac = 10, Cc = 47, Ec = -11, Adep = 9, Cdep = 5, Edep = 40; and for girls were; Aanx = 47, Canx = 22, Eanx = 30, Ac = 12, Cc = 13, Ec = 8, Adep = 30, Cdep = 12, Edep = 24; χ2 = 30.93, df = 32, AIC = -33.07). These results are presented in addition to those for the combined sample  = 11, p = .001).Table It has been shown that the aetiology of depression varies significantly according to age, with greater common environmental effects in children aged 8–10 than in adolescents aged 11–17 ,46,47. TFollowing this finding of significant common environmental covariation the nature of this latent factor was further examined. Information on a potential common environmental variable, general family functioning  was available. Family functioning was correlated with anxiety symptoms at time 1 . Bivariate analyses controlling for family functioning are shown in table 2 = 48.82, Δ df = 1, p < .001). Thus, it does not appear that anxiety leads to depression through direct phenotypic effects, but that, anxiety and depression symptoms are associated over time because they share aetiological factors in common.Finally, a model that included a direct causal path from anxiety to depression was fitted  a common genetic/environmental aetiology or 2) a phenotypic risk effect of early anxiety. There was significant genetic covariation between anxiety and later depression. . This result is consistent with the association between early anxiety and later depression being due to a common genetic aetiology. However, the genetic overlap between early anxiety and later depression was far from complete in that there were significant, separate genetic effects on anxiety and genetic influences specific to later depression. Thus, in this sample, symptoms of anxiety and depression in children and adolescents share only a partly common genetic aetiology.In addition to genetic covariation, significant shared environmental covariation between anxiety and depression was also observed. It appeared that some of the shared environmental covariation between anxiety and depression observed in parent ratings of anxiety and depression was due to shared rater effects as the common environmental covariation (Cc) was no longer significant when analyses were performed with data across different informants. However, including family adversity as a measured environmental risk factor into a model with data from different informants also resulted in a small decrease in the Cc parameter estimate.The model that included a direct causal path from early anxiety symptoms to later depression symptoms provided a significantly poorer fit than the general bivariate model. These results suggest that anxiety is not an aetiologically distinct phenotype that is in itself a risk factor for future depression symptoms, but rather that the covariation over time arises from the common genetic and environmental architecture. It should be noted though, that some of the common environmental covariation is likely due to shared rater effects, because we found that this path became non significant in cross-informant analyses.The present findings are consistent with those of several other twin studies that have reported strong genetic correlations between symptoms of anxiety and depression in children and adolescents ,29,31 anThe lack of significant univariate and bivariate gender differences in genetic and environmental parameters estimates for parent reports in the present sample is of interest. The results for self reports of depression are less clear, previous analysis of a larger sample, from which the present sample was drawn, did find sex differences for self rated depressive symptoms as measured by the long version of the Mood and Feelings Questionnaire (MFQ) , which wHow do the present findings fit with results from family studies? Several family studies of the offspring of depressed parents have found increased rates of anxiety rather than depressive disorders ,25 and RAs mentioned previously, several groups have shown that the aetiology of depressive symptoms differs between children (8–10) and adolescents (11–17) ,46,47. TAnxiety and depressive symptoms are strongly associated over time. This association does not appear to be due to a phenotypic risk effect of early anxiety. Rather, early anxiety and later depression are associated due to a common aetiology. This was primarily a common genetic aetiology although family functioning and a single informant rating on both sets of symptoms also contributed to this association. Some of the common genetic aetiology may act as indirect genetic effects via behaviour (gene-environment correlation and gene-environment interaction).The author(s) declare that they have no competing interests.AT and FR conceived the paper. FR carried out statistical analysis and wrote the paper. AT and MBM wrote and edited the paper. MBM provided statistical support. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Teaching -- and testing -- students creatively is a challenge, but new public databases and more accessible literature are now helping to develop the critical thinking skills of students The next generation of life scientists are currently undergraduates—and the success of this generation depends upon the quality of the education they receive. It is clear the expectations for undergraduate education are changing . When thEarly in my teaching career, I discussed graduate student preparation with a colleague at MIT. He said new graduate students knew about the different methods, they could even recite fine definitions—but if you asked them which method would be best to answer a particular question, they were uncertain. This reinforced my attitude towards teaching and testing. I realized that teaching science to students should be modeled on the way all scientists learn new information: in the context of an interesting question and on a need-to-know basis. This new style of teaching, “applied education,” would require me to reorganize reading materials for students, since most textbooks are written by someone who already knows all the information and has organized it accordingly. For example, describing membrane structure, protein structure, and signal transduction in Chapters 5, 12, and 15, respectively (spanning 227 pages) is not helpful for most students. It makes more sense to cover these three topics in close succession.www.bio.davidson.edu/courses/Molbio/Publicschedule.html#anchor99574051). So, for example, in my classes students first read the elegant paper by www.bio.davidson.edu/courses/Molbio/molecular.html#2003exams). Based on this success, I have designed my genomics course on the “applied education” principle .Gradually, I converted all my courses over to this “applied education” format in which students were learning new information the same way all other scientists do. I began by asking questions that could be answered by learning the information provided by textbooks or the literature. With time, I realized that published research papers are ideal teaching tools because they cover information in the context of an interesting question and new material is presented as needed. This led me to collect series of related papers to create my own course materials  is a rich repository of and portal to open access articles, BioMed Central  publishes a growing number of open-access journals, and there are a few new open-access education journals such as Cell Biology Education (http://www.cellbioed.org) and the Journal of Undergraduate Neuroscience Education . As the newest player in the open-access arena, PLoS Biology has further enriched the growing espritdes-corps of publishing and has already improved undergraduate education. My students now have equal access to a growing portion of the literature that Nobel laureates and investigators at wealthy institutions enjoy.When I was a graduate student (in the late 1980s and early 1990s), PubMed was restricted to those institutions that could afford the subscription fee; now PubMed is freely available to all who have Internet access. This change in access to PubMed has significantly improved undergraduate training by providing students with the opportunities to do literature searches for their lab reports, papers, seminars, and of course original research. Free access to information in the life sciences has continued to evolve with the newest phenomenon in publishing—open-access journals. PubMed Central  is forced to make difficult choices about which journals we can afford. The number of journal subscriptions goes down in proportion to the rise of subscription costs, but fortunately this loss is being offset by the creation of new open-access journals.http://www.bio.davidson.edu/molecular). Now I use PDF files for students to print and for me to display in class with no loss of information due to reformatting or resolution problems  in which I capitalize on a confluence of two trends in the field: public domain databases and open-access journals (www.bio.davidson.edu/courses/genomics/2003/cain/home.html). But genomics courses are not the only beneficiaries, since other classes at many institutions  require students to mine public domain databases (www.bio.davidson.edu/people/macampbell/Hope/DQ/DQ9.html and www.bio.davidson.edu/people/macampbell/Hope/DQ/DQ10.html). First-year students use Genome Browser and BLAST to determine the molecular causes of cystic fibrosis and Huntington disease, respectively. The benefit of public databases and open-access literature to educators is obvious and immediate. Images can be used in lectures, and papers can be distributed easily and on short notice for class use. There is no need to worry about limited access due to subscription costs nor an obligation to obtain copyright permission from publishers, which is a bothersome and sometimes expensive process for busy faculty members. By reducing nonproductive busy work for faculty, open-access journals have already created an environment that is improving undergraduate education today with long-term benefits in creating research-ready graduate students.During the past three years, I have taught an undergraduate course in genomics . Open-access journals make these two educational goals much more feasible because students can utilize current findings immediately without having to wait for interlibrary loans, which can take up to two weeks, can cost up to $20 per article, and can result in poor-quality black-and-white photocopies.Two common educational goals are to encourage students to become skeptical of unsubstantiated claims and to enable students to evaluate data critically. One way to accomplish these goals is to capitalize on the natural curiosity of students and ask them to compare topics in the popular press to that in the scientific literature . Students were asked to combine what they learned from the paper and the course and choose new proteins . As a result of these professional interactions, students became participants in a community of scholars, interacting with investigators at the University of California, San Francisco, while taking their exams.At the end of their exam, students were given an opportunity for extra credit points (a maximum of three points out of 100 available on the exam) if they provided constructive criticism directly to the database curators. About 70% of the students sent comments, including this one: “In recently using your database, I found it difficult to search the The use of open-access journals for teaching and testing has already improved my courses. I can provide exam questions that are more interesting, more educational, and more current. Furthermore, I accomplish two tasks simultaneously: I keep abreast of new developments in my field and I write exam questions. But what do students think? While I have not formally assessed student attitudes, I have collected information from end-of-semester course evaluations, including the following comments: “One of the best parts of the entire course for me were the exams. The exams really gave me an opportunity to show how I could work through real problems. This class definitely increased my critical thinking skills. Each test presented me with new ideas and problems to work through. I enjoyed the idea that each exam would be a learning experience.”PLoS Biology, my students benefit from free access to published research results. Free access to research literature enhances student learning and helps produce the next generation of graduate students, who are then better trained. Open-access publishing provides the right mix of benefits for educators and students alike.Teaching is a lot like raising children. Like parents, teachers provide learning opportunities in part by modeling the behavior we want our students to learn. By choosing the most current literature as testing material, my students realize that I read the literature to stay current in my field and that there are always new opportunities to learn, analyze, and design experiments, etc. By my choosing open-access papers such as those published in


Saccharomyces cerevisiae genome for fragments conferring a growth-impairment phenotype identified 714 fragments in about 84,000 clones tested.A screen of the  Saccharomyces cerevisiae for fragments that confer a growth-retardation phenotype when overexpressed in a multicopy plasmid with a tetracycline-regulatable (Tet-off) promoter. We selected 714 such fragments with a mean size of 700 base-pairs out of around 84,000 clones tested. These include 493 in-frame open reading frame fragments corresponding to 454 distinct genes (of which 91 are of unknown function), and 162 out-of-frame, antisense and intergenic genomic fragments, representing the largest collection of toxic inserts published so far in yeast.We have screened the genome of  Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana and Schizosaccharomyces pombe, have revealed a large number of novel genes of unknown functions. In S. cerevisiae, for example, around 1,800 genes  encode proteins that so far remain functionally uncharacterized (compilation from Saccharomyces Genome Database (SGD) [S. cerevisiae has been extensively studied, serving as a test case for novel and important developments in functional genomics. Such developments include transposon-mediated gene inactivation and tagging [in situ gene tagging [The complete genome sequences of various eukaryotic model organisms such as se (SGD) , the gen tagging , the ana tagging -6, two-h tagging -9, prote tagging ,11, two- tagging , proteom tagging ) and pro tagging . Even in tagging ,16 . The complete list of inserts is described in Additional file 1 and 2, and results are summarized in Table S. cerevisiae . In our screening, 32 ORFs were found twice, two ORFs were found three times and one ORF (YHR056c in the CUP1 region) was found four times, the cloned fragments being either overlapping (22 ORFs) or non-overlapping (13 ORFs). Mean size of the coding region of inserts is 659 bp. The chosen cloning strategy favors recovery of central-or carboxy-terminal coding parts of the natural yeast genes, whereas the amino-terminal coding regions are rare [The 493 inserts corresponding to in-frame ORF fragments represent 454 distinct annotated ORFs , which are randomly distributed throughout the 16 chromosomes of are rare . In our To find possible common characteristics, we have compared between themselves all the peptides encoded by in-frame ORF fragments. BLASTP analysis was combined with detection of characterized conserved domains, of COG patterns (clusters of predicted orthologous groups of proteins ), and ofAs well as comparing inserts to each other, we also analyzed the totality of the conserved domains present in all peptides encoded by the 493 toxic inserts . Characterized domains are found, at least partially, in a total of 281 inserts . Of a total of 183 distinct domains, 46 are represented more than once. We have compared the frequency of these 46 domains among the toxic inserts versus their frequency among the 5,803 ORF-encoded proteins of the entire genome (Table These 37 domains correspond predominantly to various transporter domains (11 cases), such as amino-acid permeases and mitochondrial carrier protein domains. The toxicity of these domains is probably due to the presence of transmembrane spans. Indeed, 132 out of the 493 toxic peptides contain at least two transmembrane spans, including cases where one span is putative . Among these, 63 contain three or more predicted spans and 26 have five spans or more. Putative spans were also recognized in 84 other ORF fragments  .RNA-and DNA-binding domains (nine cases) involved in replication, transcription or translation functions, such as PUF, KH and rrm, are also much more represented than expected Table . The PUFOther important domains for interactions with polypeptides, phospholipids or small molecules (nine cases) are also over-represented. The WD40 motif, a propeller-like platform for stable or reversible binding of proteins in eukaryotes, has been found in inserts of 12 distinct ORFs . The 12 ORFs code for proteins having interactions with other proteins in complexes related to RNA processing or transcription , and ninThe serine/threonine protein kinase domain (S_TKc) is significantly under-represented in our screen. Among the 10 toxic inserts whose cognate genes code for protein kinases (PK), only four contain this domain . In these four cases, the S_TKc domain is either truncated , or flanked by a coiled-coil region and/or a low-complexity segment. Two other inserts contain the PBD (and PH) domains, and the four remaining inserts contain no characterized domain to date. As it is known that overexpression of some protein kinases is deleterious for cells (see  and refeThe remaining 137 domains (out of 183) were found only once each. Many correspond to functional categories described above, such as transport, metabolism, and interactions with nucleotides, other proteins or other ligands. Seven domains associated with ubiquitination functions were also found . Several of the domains encountered have also been isolated as mammalian genetic suppressor elements (GSEs), which are cDNA fragments that inhibit cell growth . A number of these peptides are highly charged, either negatively or positively . Such charged peptides might interact in an artifactual way with other charged domains of proteins or nucleic acids or with small molecules. Interestingly, the prion-like (Q+N)-rich domain was found in eight of the natural peptides having low-complexity regions.We have seen above that 493/714 toxic inserts are in-frame fragments of protein-coding genes. The complete list of the 454 genes corresponding to these toxic inserts is given in Additional dat file 1 and 2. Their sizes range between 282 bp and 14,733 bp. The mean size of this distribution is 2,401 bp (standard deviation (SD) 1,671 bp), to be compared with a mean size of 1,444 bp  for the entire set of 5,803 ORFs of the yeast genome. The bias towards longer ORFs is expected from our cloning strategy (see above). Note that the 35 ORFs that we found more than once are nearly randomly distributed in various size classes.S. cerevisiae.We examined the distribution of these genes according to different criteria, such as function, subcellular localization, viability and phylogeny Table  and compAmong the 454 ORFs identified, 91 are unclassified, and function is not yet clear for six others . The remaining ORFs represent a variety of functional classes  among the selected ORFs. This is a significantly higher percentage than in the whole genome, where 939/5,803 genes (16.2%) are essential  are ascomycete-specific and 10 (2.2%) are orphan genes. This distribution is significantly different from the distribution among the 5,803 genes of S. cerevisiae, where 64% of protein-coding genes are conserved , we fineas 106 2% are ascNOP4 gene whose disruption is lethal. Six of these genes are singletons; three others have a paralog already known as toxic upon overexpression. Six out of the 13 still have no known function to date , indicating that the toxic effect is not the result of mislocalization of the overexpressed fragment. The gene MSC1 had already been screened [Schizosaccharomyces pombe and has a role in meiotic recombination. The TRM3 gene contains a carboxy-terminal domain responsible for tRNA methyltransferase activity [To compare the phenotypes conferred by overexpression of the entire gene and of the gene fragment, we have cloned the cognate entire genes of 13 in-frame toxic inserts into the vector pCMha191 . One criterion for the choice of the genes was the absence of a mutant phenotype of the corresponding gene disruption at the time this work was started, except for the screened  as a toxactivity , which iactivity .Additional data file 2 analyzes the 221 other toxic inserts which do not correspond to in-frame fragments of annotated ORFs. Sixty-eight inserts correspond to natural ORF fragments cloned in an antiparallel orientation, most of them being entirely included within the ORF sequence (47 cases), the others overlapping the intergenic upstream region of the natural ORF (17 cases) and sometimes the next gene as well (four cases). Their toxicity can result either from the overexpression of an antisense RNA or from the overexpression of a toxic artificial peptide encoded by a fortuitous ORF. Several arguments favor the second hypothesis. First, short ORFs longer than 24 codons (maximum observed 250 codons), and in-frame with the start codon of the cloning vector, are observed in 53 cases . A number of those artificial ORFs are due to the 'mirror' effect produced by codon-biased natural ORFs ,41. But Fifty-three additional inserts correspond to natural ORF fragments cloned out-of-frame with respect to the plasmid-borne ATG codon, of which only 12 code for artificial ORFs longer than 24 codons  reveals no significant similarity. None of these artificial ORFs corresponds to the 137 new annotated yeast genes of Kumar et al. [et al. [et al. [In total, short artificial peptides may be encoded by 92 out of the 162 inserts described above. Comparison of the 92 peptides between themselves reveals several low-complexity sequences , mostly encoded by antiparallel ORF fragments whose direct amino-acid sequence is itself of low complexity. Comparison with the proteins of r et al. , to the  [et al.  or to th [et al. . Even thAmong the 59 remaining inserts, 17 belong to Ty elements, 10 of which are in-frame ORF fragments corresponding to TyB only ), whereas all antisense fragments (three inserts) correspond to TyA. Y' elements, which are present in 20 copies in the genome, are represented by nine inserts, all coding for highly basic or acidic peptides  which contain repeats of amino acids or motifs, and confer a strongly toxic effect . Considering that these inserts are toxic, their observed number is not different from that expected from the size and number of Y' in the genome.REP1, REP2 and FLP1. The seven other inserts are out-of-frame or antisense fragments of FLP1, or fragments of intergenic regions, all (except two) coding for artificial ORFs. Finally, mtDNA is represented by 12 fragments, mostly corresponding to intergenic regions on the minus strand of the chromosome. Artificial peptides highly enriched in the amino acids tyrosine (Y), isoleucine (I), and lysine (K) are encoded by 10 out of the 12 mitochondrial inserts.Four inserts from yeast chromosome XII are fragments of genes coding for 18S or 25S RNA, two inserts being cloned in the sense orientation. The 2 mm plasmid is represented by 17 fragments, 10 of which are in-frame fragments of ORFs coding for The general fitness of living organisms largely depends on a harmonious equilibrium between the various cellular components and on their capacity to maintain homeostasis. The intricate circuitries that regulate gene expression form the basis of these properties, and massive deregulation of single components may result in flagrant phenotypic defects leading to serious growth impairment or even cell death. Our large-scale screening of the yeast genome using random genomic fragments resulted in a collection of several hundreds of inserts showing toxic effects on cell survival or growth when overexpressed. These toxic effects are expected to result from several distinct molecular situations that have been encountered at various frequencies in our experiments. Of the total of 714 toxic inserts studied, a majority (69%) correspond to the overexpression of fragments originating from natural protein-coding genes . But, interestingly, a large minority (23%) correspond to noncoding DNA fragments. The remaining cases  correspond to fragments of Ty or Y' elements, of the 2 μm plasmid or of mtDNA which, after analysis, can be attributed to one of the two previous categories. Toxic fragments of natural gene products are interesting to consider with respect to the functions of the corresponding genes. But the second category may be even more promising in that it offers us a description of DNA sequences that cannot be overexpressed in a cell without a deleterious effect.TOR1 and TOR2 genes, toxicity is specific to a central domain of the proteins distinct from their carboxy-terminal protein kinase domain; overexpression of the entire gene has no effect, and can even cure the negative effect of the overexpressed domain [et al. [TOR1, TOR2, TEL1 and TRA1 - were selected in this work, all represented by inserts of the central region of these proteins , the ZnF C3H1 domain of CTH1 [GCN4 [The toxicity of coding fragments may result from the imbalance between products of tightly controlled genes, or from the titration of active complexes by the presence of truncated proteins and/or isolated domains. In addition, nonspecific effects might also exist, for example, as a result of an abnormal intracellular localization of an artificially overabundant peptide or protein. We did not attempt to distinguish experimentally between these possibilities for all the coding inserts isolated in this work. Taking into account only specific effects, in the limited number of cases in which the entire gene corresponding to a toxic insert was cloned in the overexpression vector (see Results), we verified that toxicity was due, in most cases, to the disruption of the precise dosage of an essential cellular component  and, in some cases, to the titration effect exerted by the incomplete fragment of the natural protein (the entire protein is not toxic when overexpressed). A few examples where the domain responsible for toxicity upon overexpression is known can be found in the literature. In the case of d domain . Alarcon [et al.  have proe effect . In othe of CTH1  and the H1 [GCN4 . All theEven in the absence of precise mapping of the toxic domain present in our clones, we were able to explore the nature of the domains found in each insert. Our experiment has shown a bias towards domains corresponding to transport functions and to various interactions Table . As mentAs our results also showed a bias towards a number of interaction domains, we have examined the known interactions of the proteins encoded by the 454 genes found in this screen . Genetic interactions were also considered, excluding the coexpression results obtained in microarray experiments. It appears that 88.3% of our genes  code for proteins which have known genetic or physical interactions, or are members of complexes . Moreover, for 60% of these (242/401), at least one of their known partners is also found in our screen . Among the 53 genes having no known interactions, 24 correspond to transporter or membrane proteins .S. cerevisiae, which had previously identified a total 231 genes or gene fragments that were toxic when overexpressed [et al. [et al. experiment. Common biases are, however, observed in favor of transcription, cell-cycle and cellular transport genes. Overall, only 33 of our 454 ORFs were previously identified by the previous authors . Twenty-five other genes from the previous screenings not found here are members of paralogous gene families represented in our work . The limited overlap may result from partial genome coverage. However, by screening 84,086 clones , we must have encountered a total of 4,677 ORFs, each being represented 1.6 times as an ORF fragment . We have thus screened for toxicity around 80% of the natural yeast ORFs. But the limited overlap of results may also be explained by the experimental bias introduced by each technique. The previous experiments were mostly based on cDNA cloning, which favors short and highly expressed genes, whereas our genomic library favors large ORFs (mean size 800 ± 557 codons per ORF) and has no expression bias. In addition, the largest previous experiment [The biases we have observed show little overlap with previous screenings of xpressed ,28-30,49S. cerevisiae. A collection of toxic polypeptides, acting as genetic suppressor elements and interfering with major cellular functions, is of interest not only in antifungal research but also as a means of identifying new domains with major physiological roles.The finding of a large minority of toxic inserts corresponding to noncoding DNA is puzzling. Indeed, some of the toxic inserts originate from annotated but questionable ORFs, and some originate from antisense or intergenic fragments which can artificially be translated into small ORFs. None of these peptides has recognizable characterized domains, but many of them are charged, mostly positively  and some have amino-acid sequences of low complexity. It could be proposed that all these small ORFs represent a reservoir of potentially new gene sequences in the genome. In addition, 100 of the in-frame toxic inserts had no characterized domains and sometimes no predicted secondary structure. These inserts do not contain conserved domains, COGs or TMS, and are not biased in amino-acid composition . They may correspond to domains that have not yet been described, or to domains whose structure has diverged, but another possibility would be that some protein domains are perhaps not structured in a permanent way before evolving towards a structurally functional domain. Interestingly, a significant proportion of the expressed peptides we selected are specific to ascomycetes, or are even true orphan genes that have no known homolog in any other species than Finally, given the large number of inserts encoding very short ORFs , we cannot exclude the possibility that some transcripts are toxic through hypothetical mechanisms that may include, for example, nonspecific interactions with other cellular or nuclear complexes or through overloading of some component(s) involved in RNA metabolism.In a large-scale phenotypic screening of overexpressed random DNA fragments, we selected around 470 genes  whose domains inhibit or impair growth when overexpressed. Many functional categories are represented, transporter proteins being especially over-represented, and genes of unknown function represent one-fifth of our selection. Our approach gave access to genes controlling intracellular and membrane structures, as well as to genes whose deficiency is compensated for by genetic redundancy. Comparable approaches, using efficient phenotyping technology  and apprWe have carried out an analysis of toxic protein domains, pointing out the importance of binding domains and of protein-protein interactions correlated to regulation of cell growth and cell division. This provides a large body of data for targeting more specific studies on the modular construction of proteins and the role of interaction domains in multicomponent assembly of physiological complexes. Finally, in some cases, the deleterious effects in our system of inserts that encode very short ORFs may suggest that overexpression of some transcripts is also toxic for cell growth.Mata/α, ura3-52/ura3-52, trp1-Δ63/+, leu2-Δ1/+, his3-Δ200/+) [Matα, ura3-Δ851, trp1-Δ63, leu2-Δ1) [Matα, ura3-Δ851, trp1-Δ63, leu2-Δ1, his3-Δ200, ade2-661)  were used for transformations and growth defect screening. All strains are isogenic derivatives of S288C.Total yeast DNA from strain FY1679 (-Δ200/+)  was a geEscherichia coli DH10B cells .The yeast genomic library was constructed using Yeast cells transformed by pCMha190 recombinants were grown at 30°C on glucose synthetic complete medium lacking uracil (SC - URA) always supplemented with 10 μg/ml doxycycline (Sigma) (uninduced conditions). Phenotypic tests were done on solid medium (12 cm × 12 cm plates) containing 70 ml of SC - URA + 10 μg/ml doxycycline (uninduced conditions) or SC - URA without doxycycline (overexpression conditions). Yeast cells transformed by pCMha191 recombinants were grown at 30°C on SC - tryptophan medium, with or without addition of doxycycline. Plasmid loss was carried out on SC plates containing uracil (50 mg/l) and 0.1% of 5-fluoroorotic acid (5-FOA).URA3  or TRP1 (pCM184) as selection markers [BamHI-NotI fragment was replaced by a synthetic linker with ends compatible with these sites and introducing an ATG codon followed by an in-frame HA-tag, a BamHI cloning site, and stop codons in the three frames  by replacement of the centromere and replication origin with a 2 μm plasmid replication origin. This was PCR-amplified from pCMha190 using primers M1 and M2  using Pfu polymerase (Stratagene), and ligated to the 5,953 bp EcoRI-BglII fragment of pCMha184.Plasmids pCMha184, pCMha189, and pCMha190 were derived from the centromeric  or episomal (pCM190) overexpression vectors, containing a tetracycline-regulatable promoter system and  markers . In the s Figure . The epiMCM1 and AUAI (861 and 285 bp respectively), which are toxic when overexpressed under the control of a GAL1 promoter [MCM1, cloned in the high-copy pCMha190 vector, had a clear and constant toxic effect on yeast growth when overexpressed. We thus decided to build the library into pCMha190 and to choose the MCM1 gene as a control for toxic phenotype in overexpression conditions.The overexpression system was checked by cloning two short genes, promoter . Both geMCM1 control gene were cloned into the BamHI digested plasmid pCMha191 (TRP1 marker). Genes were PCR-amplified from genomic DNA . For each gene, two independent plasmids were transformed into yeast strain FYBL2-5D. In parallel, the same strain was transformed with the plasmids bearing the corresponding toxic inserts.Thirteen complete genes corresponding to 13 selected toxic inserts (see Results) and the YGL039w and YAL062w/GDH3 ORFs, were modified by PCR synthesis , then recloned in vivo into pCMha190 using homologous recombination [Two toxic inserts, 156C1 and 57B6, which are antiparallel fragments of bination  in yeastThe adaptor-based strategy ,54 was uSonicated total yeast DNA fragments from FY1679 ranging in size from 200 to 1,200 bp were treated with mung-bean nuclease, T4 DNA polymerase and Klenow enzyme following the manufacturers' protocols. Blunt ends of DNA fragments were ligated to the following adaptor:5'-pATCCCGGACGAAGGCC-3'3'-GGCCTGCTTCCGG-5'.BamHI and filled in with dGTP by the Vent (exo-) polymerase (New England Biolabs) was ligated to the purified adaptor-DNA inserts . The ligation result is drawn in Figure Excess of unligated adaptors and small adaptor-DNA fragments were eliminated by two consecutive purifications using Chroma spin+TE-400 columns (Clontech). Vector predigested with E. coli DH10B cells were performed with 1.8 μl of ligation mix and plated onto 2YT medium  containing 100 μg/ml ampicillin (four 12 × 12 cm plates per transformation) giving 25,000 to 45,000 clones per transformation.Electroporations of 40 μl of A total of 51 independent transformations were made. This corresponds to 1,888,000 clones. We tested 150 clones for the presence of an insert and observed that more than 85% contained one . Colonies from each transformation were pooled and distinct Qiagen Tip 500 DNA preparations were made and stored separately for yeast transformation. Final concentration of DNA was 300 to 1,300 ng/μl. The detailed protocol of library construction is available on request.Another library had previously been constructed with the same vector ligated to a distinct DNA-adaptor preparation and was partially used, giving rise to 160,000 primary clones. Characteristics of the transformants were the same as described above. Eight pools of plasmid DNA were prepared from this first library.We carried out a total of 28 independent transformations of yeast by the LiAc method : five wiMCM1, respectively) were also inoculated into each microplate. Cultures were grown overnight at 30°C and stored at 4°C before dilutions for phenotypic examination. Screening of the toxic phenotypes after overexpression was done in a two-round selection, using the 'drop test', which allowed us to see even slightly impaired growth effects. Ten-fold serial dilutions in water were made from each 96-well culture microplate with a Beckman Biomek 2000 robot, then manually replicated with the 96-pin Beckman replicator onto SC - URA + doxycycline and SC - URA plates in parallel  or with the Q-Pix robot  for overnight growth. Non-toxic and toxic control clones  and RNA were examined manually for their position relative to the coding sequences.S. cerevisiae annotated ORFs and to the 308,738 sequences of our internal database (see below).Sequences of inserts other than in-frame ORF fragments were systematically translated into amino-acid sequences from the junction with the adaptor up to the first stop codon encountered in the insert. Sequences coding for more than 24 amino acids were internally compared using BLASTP, then compared to the et al. [S. cerevisiae was filtered to eliminate all spurious ORFs or unlikely real genes, as well as Ty, Y' and mitochondrial ORFs, yielding a final list of 5,803 ORFs [Genetic entities corresponding to the toxic inserts were identified by comparison with the DNA sequences of the 16 chromosomes (available in the Comprehensive Yeast Genome Database (CYGD) at MIPS ); with oet al. ; with thet al. ; and witet al. . The set803 ORFs . For all803 ORFs  containi-3 were examined individually before validation.Comparisons among the peptides encoded by in-frame ORF fragments were done using BLASTP . Alignme-4 for most domains, and 10-3 for short domains (60 amino acids or fewer). Domains were considered as present even when represented only partially. In describing genes  were done using TopPredII  implemenS. cerevisiae [Descriptions of selected genes and their products were retrieved from the Yeast Proteome Database   and in protein complexes using three different sources: YPD  files foet al. ; data coet al. , MIPS [3et al.  and unpuPx of encountering any gene x times is described by a Poisson distribution:We consider that our library contains DNA fragments randomly distributed throughout the genome. Out of 84,086 clones tested, 11%  contain a DNA fragment cloned in-frame with the frame of the natural ORF , the others containing noncoding, out-of-frame or antisense DNA fragments. If we use the simplifying assumption that all genes are equally represented among the 9,530 clones (not taking into account the size diversity of genes), each of the 5,803 ORFs will be represented 1.64 times . The probability m, the mean of the distribution, is 1.64. This is used to estimate the fraction of genes not encountered: for x = 0 and probability p = 0.19, the number of non-encountered genes = 1,126. Thus, by screening a total of 84,086 clones, we have encountered a maximum of 4,677 ORFs .where The following additional data are available with the online version of this article. Additional data file Lists and coordinates of the 493 in-frame fragments of annotated ORFs giving toxic phenotypes when overexpressed, and short description of their cognate genesClick here for additional data fileA list and description of the 221 DNA toxic inserts other than in-frame ORF fragmentsClick here for additional data fileA description of the peptides encoded by the 493 toxic ORF fragments, and of the cognate proteinsClick here for additional data fileThe content of the 57 groups of peptide inserts sharing similaritiesClick here for additional data fileA list and description of protein domains found only once among the toxic insertsClick here for additional data fileThe genes selected in this work whose products are members of complexesClick here for additional data fileGenes selected in this work whose products are known as interacting with each otherClick here for additional data fileThe sequences of the oligonucleotides used in this workClick here for additional data fileA figure showing the phenotypes induced by overexpression of antiparallel ORF fragments before and after introduction of a stop codon upstream of the artificial ORFsClick here for additional data file


Health-related quality of life instruments are expected to be of particular value in routine care of people with multiple sclerosis (MS), where they may facilitate the detection of disease aspects that would otherwise go unrecognised, help clinicians appreciate patient priorities particularly in terms of treatment goals, facilitate physician-patient communication, and promote shared decision-making. However, it appears that these instruments are little used routine clinical approaches to people with MS. To address this issue, I performed a bibliographic search of studies that evaluated the efficacy of generic or disease-specific health-related quality of life (HRQOL) instruments in MS clinical practice from clinicians' or patients' perspectives. I found only one cross-sectional study, which compared preferences for three instruments, and assessed acceptability in people with MS.Reasons for lack of transfer of HRQOL measurements to clinical practice may be cultural, methodological, or practical. With regard to MS, the proliferation of instruments seems to constitute a barrier, with no particular instrument having gained wide popularity or consensus. Other barriers are lack of resources for the administration, collection and storage of the data, and inability of clinicians to score, interpret, and use HRQOL instrument to guide clinical care. It is therefore important to refine existing tools, extending clinical validation to wider contexts and cultures. More studies assessing acceptability and clinicians' and patients' preferences for different instruments are also required. Multiple sclerosis (MS) is a demyelinating disease of the central nervous system of unknown etiology and poorly understood pathogenesis. There is a north-south gradient of MS prevalence in the northern hemisphere, with highest levels  in northern regions . It is aInterest in measuring outcomes in MS has increased markedly over the past 20 years. Standardised instruments have been developed, the most-used being the Expanded Disability Status Scale (EDSS)  which isMore recently, the importance of MS outcome assessment from the perspective of the person with the disease has been recognised . After 1HRQOL studies in MS have drawn attention to the multiplicity of domains that may be compromised by the disease, and the effects of this compromise on ability to cope. As expected, people with MS, especially those with a progressive course, report reduced physical functioning compared to the general population ,11,29-31The ultimate aim of measuring HRQOL is to provide a comprehensive assessment of patients' health status, to serve as a baseline from which to tailor interventions, pharmacological or otherwise, and assess their effectiveness, both in the clinical trial setting and in routine care. HRQOL instruments are expected to be of particular value in routine care, where they may improve the detection of disease aspects that would otherwise go unrecognised, help clinicians appreciate patient priorities particularly in terms of treatment goals, facilitate physician-patient communication, and promote shared decision making. In addition HRQOL data from clinical trials can provide information that clinicians can usefully discuss with their patients . UnfortuIt appears that HRQOL instruments are little used in routine clinical approaches to people with MS. To address this issue, I searched MEDLINE (1966–2004), the Cochrane Library  and the Cochrane MS Group trials register (2004) for studies that evaluated the efficacy of generic or MS-specific HRQOL instruments in clinical practice from the clinicians' or MS patients' perspective, also checking study references. Studies considering patient-reported outcomes other than HRQOL, and domain-specific measures were excluded.I found only one study, a cross-sectional postal survey conducted in Canada, published in 2004 . This stThe reasons for lack of transfer of HRQOL assessment into clinical practice may be cultural, practical, or methodological -43. WithPractical considerations be particularly important in clinical settings, where data must be provided promptly and in an understandable manner to be of use. Instruments must be administered, processed, scored, stored and retrieved – all of which have logistic and financial implications . Most HRAnother factor limiting the dissemination of HRQOL tools in MS clinical practice is likely to be that too many instruments are available, and unlike EDSS, none has emerged as clearly superior to any other.Existing HRQOL tools for people with MS should be refined and their clinical validation pursued in the widest possible cultural context. More studies assessing instrument acceptability and preferences of clinicians and people with MS are also needed. It would be useful for example to implement computer-based technology (touch-screens and adaptive administration to reduce respondent burden by selecting pertinent items and omitting inappropriate ones) and other alternatives to traditional paper-and-pencil or interview methods, which should of course be evaluated for acceptability and reliability . The obj


Drosophila serve as a wonderful model for studying aspects of innate immunity, i.e. the physical, cellular, and molecular features that provide the first lines of defense against infections in flies and man Drosophila melanogaster (http://flybase.bio.indiana.edu/). Components in these pathways perform the same biochemical functions and act in the same order in both fruitfly and mammalian cells.Organisms of vastly differing morphologies, ecologies, and behaviors—such as fruit flies and humans—are now known to share a multitude of molecular, cellular, and developmental processes. Not only is there extensive similarity in the sequences of fly and human genes, but in addition, almost all of the proteins and major signal transduction pathways that control cell division and differentiation in mammals are also found in the fruitfly Evolutionary conservation is of considerable practical and theoretical importance to biologists. First, it provides a valuable source of data for the reconstruction of phylogeny . Evoluti“Innate” immunity refers to the variety of physical, cellular, and molecular features that provide the first lines of defense against infections. The relatively quick innate immune responses operate along with slower but more targeted adaptive immune responses that generate antigen-specific mechanisms that eventually lead to the destruction and elimination of the pathogen.In mammals, the skin and the epithelial lining of the mucosal tissues act as the primary nonspecific barriers, impeding infectious agents from entering the body. The mucous membrane barrier traps microorganisms, and the cilia present on the epithelial cells assist in sweeping the microbes towards the external openings of the respiratory and gastrointestinal tracts. If infectious agents gain entry into the body, internal innate immune responses become activated and rapidly eliminate the infection. Internal innate immune agents and responses include (amongst others) low pH of the stomach and vagina, proteolytic enzymes and bile in the small intestine, and phagocytosis.Phagocytosis is a fundamental innate immune mechanism carried out by a number of different cell types, including macrophages. Specific macrophage subpopulations are associated with different tissues . Their main function is to consume microorganisms, other foreign substances, and old, dying cells.Innate immunity is present from birth, and the information for innate immune responses is inherited. Cells in the mammalian innate immune system  detect “microbial nonself” by recognizing pathogen-associated molecular patterns PAMPs; . PAMPs aAdaptive immunity is characterized by greater specificity than innate immunity, as the adaptive immune response can not only distinguish foreign cells from self, but can also distinguish one foreign antigen from another. Another hallmark of adaptive immunity is memory, which enables the body to remember specific adaptive responses in response to specific antigens. Immunological memory allows the body to make a greater and more rapid second response when the body is reinfected by the same pathogen. Immunological memory underlies both immunization and resistance to reinfection, conferring a tremendous evolutionary advantage to vertebrates. The adaptive immune response has nearly infinite flexibility: the T and B lymphocytes of the acquired immune system can rearrange the elements of their immunoglobulin and T-cell receptor genes to create billions of clones with distinct antigen receptors. In organisms where both innate and acquired immune systems are present, there is a clear interdependence between the two systems. For a fully functional immune system, these components must act in synergy.Drosophila melanogaster serves as a wonderful model for studying aspects of the innate immune system that might otherwise be obscured by the actions of the adaptive immune response. Insects defend themselves against parasites and pathogens by invoking a multitude of innate immune responses .Because it lacks an adaptive immune response, esponses . Like huPLoS Biology, Drosophila. The mammalian ortholog of Collier (Early B-cell Factor) is involved in B-cell differentiation in mice.Once within the body cavity, microbes may be consumed by the phagocytic blood cells called plasmatocytes . Larger Drosophila hemolymph also coagulates and participates in host defense and wound healing  make the fly susceptible to fungal or gram-positive bacterial infections. However, Toll does not act as a pattern recognition receptor in the fly; instead its activation depends on the presence of the processed (active) form of the growth-factor-like polypeptide Spätzle. Processing of Spätzle depends on a serpin-controlled proteolytic cascade (The eceptors . Mutatio cascade .Drosophila Toll pathway were identified in earlier genetic screens for developmental mutants, those in the Imd pathway have been the focus of more recent studies, mainly in the context of Drosophila immunity (While components of the immunity . The effimmunity . Using aDrosophila is now guiding scientists to explore the immune system of other insects such as the mosquito, Anopheles gambiae, that spreads human malaria. Immune responses in this mosquito are linked to the elimination of the malarial parasites (Anopheles and Drosophila reveals the presence of the Toll signaling pathway in the mosquito genome, even though there are some differences in genes encoding pathogen recognition and signal transduction molecules (The impressive progress in our understanding of innate immunity in arasites . A compaolecules . A detaiThe homologs of many genes involved in innate immune responses in flies and humans have also been found in mice, sharks, nematodes, and plants e.g., . In spec


The discovery of experience-dependent brain reactivation during both slow-wave (SW) and rapid eye-movement (REM) sleep led to the notion that the consolidation of recently acquired memory traces requires neural replay during sleep. To date, however, several observations continue to undermine this hypothesis. To address some of these objections, we investigated the effects of a transient novel experience on the long-term evolution of ongoing neuronal activity in the rat forebrain. We observed that spatiotemporal patterns of neuronal ensemble activity originally produced by the tactile exploration of novel objects recurred for up to 48 h in the cerebral cortex, hippocampus, putamen, and thalamus. This novelty-induced recurrence was characterized by low but significant correlations values. Nearly identical results were found for neuronal activity sampled when animals were moving between objects without touching them. In contrast, negligible recurrence was observed for neuronal patterns obtained when animals explored a familiar environment. While the reverberation of past patterns of neuronal activity was strongest during SW sleep, waking was correlated with a decrease of neuronal reverberation. REM sleep showed more variable results across animals. In contrast with data from hippocampal place cells, we found no evidence of time compression or expansion of neuronal reverberation in any of the sampled forebrain areas. Our results indicate that persistent experience-dependent neuronal reverberation is a general property of multiple forebrain structures. It does not consist of an exact replay of previous activity, but instead it defines a mild and consistent bias towards salient neural ensemble firing patterns. These results are compatible with a slow and progressive process of memory consolidation, reflecting novelty-related neuronal ensemble relationships that seem to be context- rather than stimulus-specific. Based on our current and previous results, we propose that the two major phases of sleep play distinct and complementary roles in memory consolidation: pretranscriptional recall during SW sleep and transcriptional storage during REM sleep. Rats exposed to novel objects during periods of wakefulness generate neural activity that is correlated with patterns observed in subsequent sleep episodes Sleep is important for the consolidation of newly acquired memories . The disstrictu sensu neuronal reactivation during sleep in mammals has only been investigated in the hippocampocortical loop  representing larger-scale neural rhythms were simultaneously recorded from four different brain regions: HP, primary somatosensory “barrel field” CX, ventral posteromedial thalamic nucleus (TH), and putamen (PU)  and S7. In our studies, neural signals were continuously recorded across the natural sleep–wake cycle for 48–96 h, with a single 1-h exposure to four complex objects placed in the four corners of the recording box C. All obn= five templates per animal). Control templates were selected from epochs of alert WK 24 h or 48 h before novel stimulation , during which familiar tactile stimulation was produced by the contact of whiskers with the smooth walls of the recording box, to which animals had been habituated. Templates were matched against the entire record of neuronal activity using the neuronal ensemble correlation method . This indicates that the neuronal firing patterns concomitant with novel stimulation persisted significantly more during the ensuing time than patterns sampled 24 h or 48 h before novel stimulation, when animals were in the same behavioral state , but without novel objects to explore. The effect was independently observed, to a variable degree, in all the five animals studied . First, we tested whether the neuronal ensemble correlation method could detect any trace of neuronal reverberation lasting at least more than 1 h after exposure to novel stimulation. For this, we examined correlation profiles obtained for all recorded neurons (three to four brain areas pooled together) in each animal. As shown in p values generated by Bonferroni comparisons between post- and prenovelty correlation distributions . This indicates that the neuronal changes associated with exposure to novel stimuli were highly distributed through the neuronal populations sampled. Furthermore, judging by the maximum neuronal ensemble correlations observed . Indeed, experience-dependent changes were not statistically different across different forebrain areas . The temporal evolution of p values (Bonferroni comparison) associated with single-area correlation profiles shows that significant reverberation was present in 16 of 18 recording sites for several hours after exposure to novel stimulation , with SW ratios being significantly higher than those of both WK  and REM . Indeed, significant state-specific differences in post-/prenovelty correlation ratios were individually detected in four of five animals .Single-area results indicate that neuronal ensemble correlations often peak during discrete epochs that last a few hours. We also noticed marked oscillations of the correlation trace in several recorded sites . These observations suggest that some underlying biological process, with slow evolution but with sharp phase transitions, governs the long-term reverberation of neuronal firing patterns. To test whether transitions in the wake–sleep cycle could amount for these effects, we investigated how experience-dependent changes in neuronal correlations varied across the three major rat behavioral states: WK, SW sleep, and REM sleep. A comparison across states of post-/prenovelty correlation ratios calculated from averages of entire recordings indicated a significant state-specific effect . Next, we tested the possibility reported in hippocampal place cells  that expp values can be observed for speed factors 10 times and 20 times faster than normal WK rates, while speed factors near the physiological range (2×–0.5×) show stronger and similar effects. This was the case even in the HP, in contrast with previous findings in hippocampal place cells recorded in highly trained animals performing a spatial navigation task  are substantially less detectable over time.Our results fend off three major objections to the notion that neuronal reverberation during sleep may underlie memory consolidation. First, significant experience-depen-dent changes in neuronal ensemble correlations can be tracked as late as 48 h after the reference novel experience, being therefore compatible with memory impairment effects of sleep deprivation applied hours or days after training . Second,An important result of the present study is the inverse correlation between neuronal correlations and concurrent firing rates. Although all neuronal activity templates were taken from epochs of high arousal WK when firing rates were generally high, their neuronal reverberation during subsequent WK was not very prominent , agreeing with values previously reported for pairwise  or many-A third important point regards the observation that neural activity sampled when animals were aroused, but not touching the objects, yielded neuronal reverberation that was nearly identical to that obtained when animals made sensory contact with the objects. This indicates that the kind of experience-dependent neuronal reverberation detected by the neuronal ensemble correlation method  does notIt has been suggested that the neuronal reverberation of newly acquired synaptic changes during SW sleep may lead to the recall and storage of new memories by way of “calcium-mediated intracellular cascades” capable of opening the “molecular gates to plasticity” . This hyThe fact that neuronal reverberation is sustained for long epochs during SW sleep suggests that unconsolidated synaptic changes may not only be recalled, but also amplified over time during SW sleep. Indeed, a progressive increase of neuronal correlations across single SW sleep episodes was often observed  so as to reach steady-state behavioral activity and baseline wake–sleep cycles. Behaviors were continuously recorded by way of two infrared-sensitive CCD video-cameras; infrared illumination was used to monitor behavior when visible lights were off. Behavioral states were coded as WK, SW sleep, or REM sleep based on a spectral analysis of LFPs and visual inspection of videotaped behaviors, according to previously described criteria  Figure .TM  code running in a computer cluster comprising 32 CPU . Neuronal ensemble correlations were calculated following the method in CxN matrices corresponding to simultaneously recorded spike trains of C neurons binned into N intervals of a certain length. Our results were obtained using 9 s-long templates binned with 250 ms-long bins with as many neurons as were available for the brain areas in question. Hence, each template pattern yielded a Cx36 matrix. Target data comprising 24 h or 48 h were sparsely sampled (every 30 s) and binned into matrices of the same dimensions. For a C×N template data matrix x and a target data matrix y sampled at time t, the ensemble correlation index Ct is obtained by:Data were processed and analyzed by custom-made MATLABwherec, y¯, and σy). and MATLABTM software were used for descriptive statistics and hypothesis testing.Templates were selected by careful scrutiny of behavior recorded on videotapes and of the corresponding spectral characteristics of hippocampal LFPs, so as to assure sampling during alert WK . ParticuFigure S1Four different objects were used to produce CSS.(9.7 MB PPT).Click here for additional data file.Figure S2All animals were highly habituated to the recording box, so that exposure to novel complex objects caused a general increase in the animals' arousal. Four of five animals showed an increase in time spent in WK with respect to SW and REM sleep during CSS (A), as compared to adjacent pre- and postnovelty periods of equal length (60 min). The only exception was rat 1, which showed nevertheless a marked exploratory drive, spending nearly 20% of the exposure period in direct whisker-contact with the objects (B). Individual object preferences were moderately varied, as indicated in (C).(746 KB PPT).Click here for additional data file.Figure S3Teflon-coated tungsten wires  were assembled in multielectrode arrays shaped to fit different neuroanatomical targets.(282 KB PPT).Click here for additional data file.Figure S4Frontal brain sections stained for cresyl-violet were used to determine the sites of electrode placement. Electrode tracks, tissue scars, and reference electrolytic lesions performed a few days before sacrifice were used to delimit the implant sites, indicated in red in the figure below. Numbers on the right represent standard AP coordinates  in milli(6.3 MB PPT).Click here for additional data file.Figure S5To record neuronal activity, differentiated neural signal was preamplified  and digitized at 40 KHz. Up to four neuronal action potentials per recording channel were sorted online  and validated by offline analysis  according to the following cumulative criteria: voltage thresholds greater than two standard deviations of amplitude distributions; signal-to-noise ratio greater than 2.5 (as verified on the oscilloscope screen); less than 1% of interspike intervals smaller than 1.2 ms; and stereotypy of waveform shapes, as determined by a waveform template algorithm and principal component analysis. In order to continuously record individual neurons for up to 96 h, we used an adaptive algorithm  that adjusts waveform templates based on the recent accumulated mean shapes (1% of midline every 20 min). This allows for the same neuron to be tracked across consecutive days, as verified by the superimposition of waveforms acquired thoughout the experiment .(3 MB PPT).Click here for additional data file.Figure S6Up to 159 neurons were recorded from three to four different brain areas.(1.4 MB PPT).Click here for additional data file.Figure S7LFPs were recorded in parallel with spikes from the same electrodes. Neural signals were split, preamplified , and filtered (0.5–400 Hz) by way of a Plexon LFP board. Signals were then fed to the MAP acquisition principal component through a NIDAQ card and digitized at 500 Hz. Behaviors were constantly recorded in videotape by two diametrically opposed infrared-sensitive CCD cameras . A millisecond-precision timer  was used to synchronize the acquisition of spikes, LFPs, and videotape records.Behavioral states were identified by the combined inspection of videotapes and the spectral content (1–20 Hz) of LFPs. Behaviors were classified according to the following criteria: (1) alert WK: active exploration with whisking, plus strong hippocampal θ rhythm; (2) quiet WK: stillness or grooming, with eyes open and low-power hippocampal θ rhythm; (3) SW sleep: stillness with eyes closed, plus large-amplitude hippocampal δ rhythm; (4) REM sleep: overall stillness with intermittent whisking, eyes closed, strong hippocampal θ rhythm.The inspection of videotape records readily separates alert and quiet WK from sleep states, but the separation of SW and REM sleep relies strongly on LFP analysis. Hippocampal LFP is particularly useful to disambiguate SW and REM sleep: SW sleep has a strong δ band (2–4 Hz), while REM sleep shows increased θ band (5–8 Hz). The distinction between alert and quiet WK was used only for template selection . For all other purposes, alert and quiet WK data were combined into a single WK category. The graphs depict the θ/δ hippocampal spectral ratios (mean ± SEM) of the three major behavioral states for rat 5 (entire recording).(2.1 MB PPT).Click here for additional data file.Figure S8The figure shows the effect of using different bin sizes to calculate neuronal ensemble correlations. We observed quantitative differences , but qualitatively the correlations profiles are equivalent, i.e., have very similar shapes.(404 KB PPT).Click here for additional data file.