Fully in vitro iterative construction of a 24 kb-long artificial DNA sequence to store digital information.

In the absence of a DNA template, the ab initio production of long double-stranded DNA molecules of predefined sequences is particularly challenging. The DNA synthesis step remains a bottleneck for many applications such as functional assessment of ancestral genes, analysis of alternative splicing or DNA-based data storage. In this report we propose a fully in vitro protocol to generate very long double-stranded DNA molecules starting from commercially available short DNA blocks in less than 3 days using Golden Gate assembly. This innovative application allowed us to streamline the process to produce a 24 kb-long DNA molecule storing part of the Declaration of the Rights of Man and of the Citizen of 1789 . The DNA molecule produced can be readily cloned into a suitable host/vector system for amplification and selection.

The genomic basis of the Streptococcus thermophilus health-promoting properties.

BACKGROUND: Streptococcus thermophilus is a Gram-positive bacterium widely used as starter in the dairy industry as well as in many traditional fermented products. In addition to its technological importance, it has also gained interest in recent years as beneficial bacterium due to human health-promoting functionalities. The objective of this study was to inventory the main health-promoting properties of S. thermophilus and to study their intra-species diversity at the genomic and genetic level within a collection of representative strains. RESULTS: In this study various health-related functions were analyzed at the genome level from 79 genome sequences of strains isolated over a long time period from diverse products and different geographic locations. While some functions are widely conserved among isolates (e.g., degradation of lactose, folate production) suggesting their central physiological and ecological role for the species, others including the tagatose-6-phosphate pathway involved in the catabolism of galactose, and the production of bioactive peptides and gamma-aminobutyric acid are strain-specific. Most of these strain-specific health-promoting properties seems to have been acquired via horizontal gene transfer events. The genetic basis for the phenotypic diversity between strains for some health related traits have also been investigated. For instance, substitutions in the galK promoter region correlate with the ability of some strains to catabolize galactose via the Leloir pathway. Finally, the low occurrence in S. thermophilus genomes of genes coding for biogenic amine production and antibiotic resistance is also a contributing factor to its safety status. CONCLUSIONS: The natural intra-species diversity of S. thermophilus, therefore, represents an interesting source for innovation in the field of fermented products enriched for healthy components that can be exploited to improve human health. A better knowledge of the health-promoting properties and their genomic and genetic diversity within the species may facilitate the selection and application of strains for specific biotechnological and human health-promoting purpose. Moreover, by pointing out that a substantial part of its functional potential still defies us, our work opens the way to uncover additional health-related functions through the intra-species diversity exploration of S. thermophilus by comparative genomics approaches.

Finding and Characterizing Repeats in Plant Genomes.

Plant genomes contain a particularly high proportion of repeated structures of various types. This chapter proposes a guided tour of the available software that can help biologists to scan automatically for these repeats in sequence data or check hypothetical models intended to characterize their structures. Since transposable elements (TEs) are a major source of repeats in plants, many methods have been used or developed for this broad class of sequences. They are representative of the range of tools available for other classes of repeats and we have provided two sections on this topic (for the analysis of genomes or directly of sequenced reads), as well as a selection of the main existing software. It may be hard to keep up with the profusion of proposals in this dynamic field and the rest of the chapter is devoted to the foundations of an efficient search for repeats and more complex patterns. We first introduce the key concepts of the art of indexing and mapping or querying sequences. We end the chapter with the more prospective issue of building models of repeat families. We present the Machine Learning approach first, seeking to build predictors automatically for some families of ET, from a set of sequences known to belong to this family. A second approach, the linguistic (or syntactic) approach, allows biologists to describe themselves and check the validity of models of their favorite repeat family.

Identification of isolated or mixed strains from long reads: a challenge met on Streptococcus thermophilus using a MinION sequencer.

This study aimed to provide efficient recognition of bacterial strains on personal computers from MinION (Nanopore) long read data. Thanks to the fall in sequencing costs, the identification of bacteria can now proceed by whole genome sequencing. MinION is a fast, but highly error-prone sequencing device and it is a challenge to successfully identify the strain content of unknown simple or complex microbial samples. It is heavily constrained by memory management and fast access to the read and genome fragments. Our strategy involves three steps: indexing of known genomic sequences for a given or several bacterial species; a request process to assign a read to a strain by matching it to the closest reference genomes; and a final step looking for a minimum set of strains that best explains the observed reads. We have applied our method, called ORI, on 77 strains of Streptococcus thermophilus. We worked on several genomic distances and obtained a detailed classification of the strains, together with a criterion that allows merging of what we termed 'sibling' strains, only separated by a few mutations. Overall, isolated strains can be safely recognized from MinION data. For mixtures of several non-sibling strains, results depend on strain abundance.

Sequencing DNA with nanopores: Troubles and biases.

Oxford Nanopore Technologies' (ONT) long read sequencers offer access to longer DNA fragments than previous sequencer generations, at the cost of a higher error rate. While many papers have studied read correction methods, few have addressed the detailed characterization of observed errors, a task complicated by frequent changes in chemistry and software in ONT technology. The MinION sequencer is now more stable and this paper proposes an up-to-date view of its error landscape, using the most mature flowcell and basecaller. We studied Nanopore sequencing error biases on both bacterial and human DNA reads. We found that, although Nanopore sequencing is expected not to suffer from GC bias, it is a crucial parameter with respect to errors. In particular, low-GC reads have fewer errors than high-GC reads (about 6% and 8% respectively). The error profile for homopolymeric regions or regions with short repeats, the source of about half of all sequencing errors, also depends on the GC rate and mainly shows deletions, although there are some reads with long insertions. Another interesting finding is that the quality measure, although over-estimated, offers valuable information to predict the error rate as well as the abundance of reads. We supplemented this study with an analysis of a rapeseed RNA read set and shown a higher level of errors with a higher level of deletion in these data. Finally, we have implemented an open source pipeline for long-term monitoring of the error profile, which enables users to easily compute various analysis presented in this work, including for future developments of the sequencing device. Overall, we hope this work will provide a basis for the design of better error-correction methods.

Inferring Biochemical Reactions and Metabolite Structures to Understand Metabolic Pathway Drift.

Inferring genome-scale metabolic networks in emerging model organisms is challenged by incomplete biochemical knowledge and partial conservation of biochemical pathways during evolution. Therefore, specific bioinformatic tools are necessary to infer biochemical reactions and metabolic structures that can be checked experimentally. Using an integrative approach combining genomic and metabolomic data in the red algal model Chondrus crispus, we show that, even metabolic pathways considered as conserved, like sterols or mycosporine-like amino acid synthesis pathways, undergo substantial turnover. This phenomenon, here formally defined as "metabolic pathway drift," is consistent with findings from other areas of evolutionary biology, indicating that a given phenotype can be conserved even if the underlying molecular mechanisms are changing. We present a proof of concept with a methodological approach to formalize the logical reasoning necessary to infer reactions and molecular structures, abstracting molecular transformations based on previous biochemical knowledge.

Formalizing and enriching phenotype signatures using Boolean networks.

In order to predict the behavior of a biological system, one common approach is to perform a simulation on a dynamic model. Boolean networks allow to analyze the qualitative aspects of the model by identifying its steady states and attractors. Each of them, when possible, is associated with a phenotype which conveys a biological interpretation. Phenotypes are characterized by their signatures, provided by domain experts. The number of steady states tends to increase with the network size and the number of simulation conditions, which makes the biological interpretation difficult. As a first step, we explore the use of Formal Concept Analysis as a symbolic bi-clustering technics to classify and sort the steady states of a Boolean network according to biological signatures based on the hierarchy of the roles the network components play in the phenotypes. FCA generates a lattice structure describing the dependencies between proteins in the signature and steady-states of the Boolean network. We use this lattice (i) to enrich the biological signatures according to the dependencies carried by the network dynamics, (ii) to identify variants to the phenotypes and (iii) to characterize hybrid phenotypes. We applied our approach on a T helper lymphocyte (Th) differentiation network with a set of signatures corresponding to the sub-types of Th. Our method generated the same classification as a manual analysis performed by experts in the field, and was also able to work under extended simulation conditions. This led to the identification and prediction of a new hybrid sub-type later confirmed by the literature.

De novo clustering of long reads by gene from transcriptomics data.

Long-read sequencing currently provides sequences of several thousand base pairs. It is therefore possible to obtain complete transcripts, offering an unprecedented vision of the cellular transcriptome. However the literature lacks tools for de novo clustering of such data, in particular for Oxford Nanopore Technologies reads, because of the inherent high error rate compared to short reads. Our goal is to process reads from whole transcriptome sequencing data accurately and without a reference genome in order to reliably group reads coming from the same gene. This de novo approach is therefore particularly suitable for non-model species, but can also serve as a useful pre-processing step to improve read mapping. Our contribution both proposes a new algorithm adapted to clustering of reads by gene and a practical and free access tool that allows to scale the complete processing of eukaryotic transcriptomes. We sequenced a mouse RNA sample using the MinION device. This dataset is used to compare our solution to other algorithms used in the context of biological clustering. We demonstrate that it is the best approach for transcriptomics long reads. When a reference is available to enable mapping, we show that it stands as an alternative method that predicts complementary clusters.

Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks.

BACKGROUND: The emergence of functions in biological systems is a long-standing issue that can now be addressed at the cell level with the emergence of high throughput technologies for genome sequencing and phenotyping. The reconstruction of complete metabolic networks for various organisms is a key outcome of the analysis of these data, giving access to a global view of cell functioning. The analysis of metabolic networks may be carried out by simply considering the architecture of the reaction network or by taking into account the stoichiometry of reactions. In both approaches, this analysis is generally centered on the outcome of the network and considers all metabolic compounds to be equivalent in this respect. As in the case of genes and reactions, about which the concept of essentiality has been developed, it seems, however, that some metabolites play crucial roles in system responses, due to the cell structure or the internal wiring of the metabolic network. RESULTS: We propose a classification of metabolic compounds according to their capacity to influence the activation of targeted functions (generally the growth phenotype) in a cell. We generalize the concept of essentiality to metabolites and introduce the concept of the phenotypic essential metabolite (PEM) which influences the growth phenotype according to sustainability, producibility or optimal-efficiency criteria. We have developed and made available a tool, Conquests, which implements a method combining graph-based and flux-based analysis, two approaches that are usually considered separately. The identification of PEMs is made effective by using a logical programming approach. CONCLUSION: The exhaustive study of phenotypic essential metabolites in six genome-scale metabolic models suggests that the combination and the comparison of graph, stoichiometry and optimal flux-based criteria allows some features of the metabolic network functionality to be deciphered by focusing on a small number of compounds. By considering the best combination of both graph-based and flux-based techniques, the Conquests python package advocates for a broader use of these compounds both to facilitate network curation and to promote a precise understanding of metabolic phenotype.

3D-front-face fluorescence spectroscopy and independent components analysis: A new way to monitor bread dough development.

Following bread dough development can be a hard task as no reliable method exists to give the optimal mixing time. Dough development is linked to the evolution of gluten proteins, carbohydrates and lipids which can result in modifications in the spectral properties of the various fluorophores naturally present in the system. In this paper, we propose to use 3-D-front-face-fluorescence (3D-FFF) spectroscopy in the 250-550nm domain to follow the dough development as influenced by formulation (addition or not of glucose, glucose oxidase and ferulic acid in the dough recipe) and mixing time (2, 4, 6 and 8min). In all the 32 dough samples as well as in flour, three regions of maximum fluorescence intensities have been observed at 320nm after excitation at 295nm (Region 1), at 420nm after excitation at 360nm (Region 2) and 450nm after excitation at 390nm (Region 3). The principal components analysis (PCA) of the evolution of these maxima shows that the formulations with and without ferulic acid are clearly separated since the presence of ferulic acid induces a decrease of fluorescence in Region 1 and an increase in Regions 2 and 3. In addition, a kinetic effect of the mixing time can be observed (decrease of fluorescence in the Regions 1 and 2) mainly in the absence of ferulic acid. The analysis of variance (ANOVA) on these maximum values statistically confirms these observations. Independent components analysis (ICA) is also applied to the complete 3-D-FFF spectra in order to extract interpretable signals from spectral data which reflect the complex contribution of several fluorophores as influenced by their environment. In all cases, 3 signals can be clearly separated matching the 3 regions of maximal fluorescence. The signals corresponding to regions 1 and 2 can be ascribed to proteins and ferulic acid respectively, whereas the fluorophores associated with the 3rd signal (corresponding to region 3) remain unidentified. Good correlations are obtained between the IC score values of the 3 signals and the fluorescence intensities in Region 1, Region 2 and Region 3. Ferulic acid addition increases fluorescence in Region 2 and decreases fluorescence in Region 1, probably via a reabsorption of the protein fluorescence by ferulic acid. These phenomena are less pronounced when glucose oxidase is present. The enzymatic oxidation of ferulic acid by the glucose oxidase-peroxidase association could explain some of these effects.

Finding and Characterizing Repeats in Plant Genomes.

Plant genomes contain a particularly high proportion of repeated structures of various types. This chapter proposes a guided tour of available software that can help biologists to look for these repeats and check some hypothetical models intended to characterize their structures. Since transposable elements are a major source of repeats in plants, many methods have been used or developed for this large class of sequences. They are representative of the range of tools available for other classes of repeats and we have provided a whole section on this topic as well as a selection of the main existing software. In order to better understand how they work and how repeats may be efficiently found in genomes, it is necessary to look at the technical issues involved in the large-scale search of these structures. Indeed, it may be hard to keep up with the profusion of proposals in this dynamic field and the rest of the chapter is devoted to the foundations of the search for repeats and more complex patterns. The second section introduces the key concepts that are useful for understanding the current state of the art in playing with words, applied to genomic sequences. This can be seen as the first stage of a very general approach called linguistic analysis that is interested in the analysis of natural or artificial texts. Words, the lexical level, correspond to simple repeated entities in texts or strings. In fact, biologists need to represent more complex entities where a repeat family is built on more abstract structures, including direct or inverted small repeats, motifs, composition constraints as well as ordering and distance constraints between these elementary blocks. In terms of linguistics, this corresponds to the syntactic level of a language. The last section introduces concepts and practical tools that can be used to reach this syntactic level in biological sequence analysis.

Use of ESR and HPLC to follow the anaerobic reaction catalysed by lipoxygenases.

The measurement of the 4-hydroxy-2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPOL) consumption by using ESR allows to follow the anaerobic reaction between linoleic acid (LH) and its 13-hydroperoxide (LOOH) catalysed by lipoxygenase. During this reaction, two types of radicals are initially obtained, alkyl (L) and alkoxyl (LO) radicals which formed two types of adducts (LT and OLT) with TEMPOL as characterised by HPLC. The stoichiometry of the adduct formation is two mole of TEMPOL consumed for one mole of LH and one mole of LOOH. Using ESR, the kinetic parameters and the mechanism of the anaerobic reaction have been determined at pH 6.5 for three different lipoxygenases, soybean, horse bean and wheat and compared to the values obtained at pH 9 for soybean lipoxygenase. Wheat lipoxygenase is very weakly active compared to the other enzymes. An uncompetitive inhibition of the anaerobic reaction catalysed by soybean and horse bean lipoxygenases was observed with 2,6-di-tert-butyl-4-methylphenol (BHT).

An extended network of genomic maintenance in the archaeon Pyrococcus abyssi highlights unexpected associations between eucaryotic homologs.

In Archaea, the proteins involved in the genetic information processing pathways, including DNA replication, transcription, and translation, share strong similarities with those of eukaryotes. Characterizations of components of the eukaryotic-type replication machinery complex provided many interesting insights into DNA replication in both domains. In contrast, DNA repair processes of hyperthermophilic archaea are less well understood and very little is known about the intertwining between DNA synthesis, repair and recombination pathways. The development of genetic system in hyperthermophilic archaea is still at a modest stage hampering the use of complementary approaches of reverse genetics and biochemistry to elucidate the function of new candidate DNA repair gene. To gain insights into genomic maintenance processes in hyperthermophilic archaea, a protein-interaction network centred on informational processes of Pyrococcus abyssi was generated by affinity purification coupled with mass spectrometry. The network consists of 132 interactions linking 87 proteins. These interactions give insights into the connections of DNA replication with recombination and repair, leading to the discovery of new archaeal components and of associations between eucaryotic homologs. Although this approach did not allow us to clearly delineate new DNA pathways, it provided numerous clues towards the function of new molecular complexes with the potential to better understand genomic maintenance processes in hyperthermophilic archaea. Among others, we found new potential partners of the replication clamp and demonstrated that the single strand DNA binding protein, Replication Protein A, enhances the transcription rate, in vitro, of RNA polymerase. This interaction map provides a valuable tool to explore new aspects of genome integrity in Archaea and also potentially in Eucaryotes.

The bread dough stability improving effect of pyranose oxidase from trametes multicolor and glucose oxidase from Aspergillus niger: unraveling the molecular mechanism.

Glucose oxidase (GO) and pyranose oxidase (P2O) improve dough stability and bread quality. We here studied whether their mode of action resides in cross-linking of proteins and/or arabinoxylan (AX) molecules through the production of H2O2. Evidence for both was deduced from a decrease in extractability of protein and AX from dough made with P2O, GO, or H2O2, using sodium dodecyl sulfate containing buffer and water, respectively. The addition of H2O2, P2O, or GO to a glutathione solution sharply decreased its sulfhydryl (SH) content. P2O or GO can trigger protein cross-linking through the formation of disulfide (SS) bonds. As a result thereof, SH/SS interchange reactions between low molecular mass SH containing compounds and gluten proteins can be hampered. Furthermore, a decrease in the level of monomeric ferulic acid (FA) esterified to AX in dough points to a role of FA bridges in cross-linking of AX molecules. Our results indicate that the molecular mechanism of dough and bread improvement by P2O and GO resides in cross-linking of gluten proteins and AX by formation of H2O2. They furthermore show that the extent of cross-linking upon addition of P2O or GO strongly depends on the concentration (and production rate) of H2O2.

Modelling the interactions between free phenols, L-ascorbic acid, apple polyphenoloxidase and oxygen during a thermal treatment.

The kinetics of degradation of chlorogenic acid (CG), (-) epicatechin (EPI), L-ascorbic acid (AA) and polyphenoloxidase (PPO) activity from Marie-Ménard apple in pH 3.8 solutions at 20 and 50°C were investigated to provide information on the impact of the presence of CG, EPI and/or AA on PPO thermostability. The effect of the heat treatment on their degradation by enzymatic and/or nonenzymatic ways was also studied. Stoechiokinetic reactions on the basis of experimental data and literature and determination of the kinetic constants (k) at 20 and 50°C were elaborated before modelling the interaction among reactants, by fitting the reaction curves to predictive model. Apple PPO was thermolabile, denaturing after 10min at 70°C. Losses of PPO activity were favoured by the presence of EPI in model solutions, compared with CG, due to the formation of o-quinones of EPI (QEPI) lowering PPO stability. Temperature quickened both enzymatic phenol oxidations before PPO deteriorated and the whole set of the chemical reactions, including the production of secondary oxidation products and CG or EPI regeneration. Results also confirmed that AA in excess induced a fast regeneration of CG and EPI from the corresponding o-quinones formed enzymatically via redox chemical reactions.

Evaluation of an electronic nose for the early detection of organic overload of anaerobic digesters.

This study aimed at analysing the utilization of an electronic nose (e-nose) to serve as a specific monitoring tool for anaerobic digestion process, especially for detecting organic overload. An array of non specific metal oxide semiconductor gas sensors were used to detect process faults due to organic overload events in twelve 1.8-L anaerobic semi-continuous reactors. Three different load strategies were followed: (1) a cautious organic load (1.3 gVS L(-1) day(-1)); (2) an increasing load strategy (1.3-5.3 gVS L(-1) day(-1)) and (3) a cautious organic load with load pulses of up to 12 gVS L(-1) day(-1). A first monitoring campaign was conducted with three different substrates: sucrose, maize oil and a mix of sucrose/oil during 60 days. The second campaign was run with dry sugar beet pulp for 45 days. Hotelling's T(2) value and upper control limit to a reference set of digesters fed with a cautious OLR (1.3 gVS L(-1) day(-1)) was used as indirect state variable of the reactors. Overload situations were identified by the e-nose apparatus with Hotelling's T(2) values at least four times higher in magnitude than the upper control limit of 23.7. These results confirmed that the e-nose technology appeared promising for online detection of process imbalances in the domain of anaerobic digestion.

To detect and analyze sequence repeats whatever be their origin.

The development of numerous programs for the identification of mobile elements raises the issue of the founding concepts that are shared in their design. This is necessary for at least three reasons. First, the cost of designing, developing, debugging, and maintaining software could present a danger of distracting biologists from their main bioanalysis tasks that require a lot of energy. Some key concepts on exact repeats are always underlying the search for genomic repeats and we recall the most important ones. All along the chapter, we try to select practical tools that may help the design of new identification pipelines. Second, the huge increase of sequence production capacities requires to use the most efficient data structures and algorithms to scale up tools in front of the data deluge. This paper provides an up-to-date glimpse on the art of string indexing and string matching. Third, there exists a growing knowledge on the architecture of mobile elements built from literature and the analysis of results generated by these pipelines. Besides data management which has led to the discovery of new families or new elements of a family, the community has an increasing need in knowledge management tools in order to compare, validate, or simply keep trace of mobile element models. We end the paper with first considerations on what could help the near future of such research on models.

Apple polyphenoloxidase inactivation during heating in the presence of ascorbic acid and chlorogenic acid.

It was recently reported that during osmotic dehydration of ascorbic acid (AA)-treated apple cubes, losses in AA and phenolics could partly arise from enzymatic oxidation, provided polyphenoloxidase (PPO) was still active under the processing conditions. To determine the impact of dehydration temperatures on PPO action, as well as chemical and enzymatic oxidation reactions, apple PPO inactivation alone or with AA (1mM) and/or chlorogenic acid (CG, 3mM), as well as AA and CG levels evolution, during heating of the model solutions at 45 and 60°C were investigated. At pH 3.8, PPO was still functional, keeping 61 and 4% residual activity after 2h of heating at 45 and 60°C, respectively. The combined treatment of heating and AA was more effective in reducing PPO activity, while incubation at 60°C with AA and CG minimised the losses of PPO activity. CG remained stable during heating, even in the presence of AA which, in turn, was more affected by heating. Thus, during heating, provided PPO remained active with enough available O2 in the model systems, CG oxidation and coupled oxidoreduction with AA could readily develop.

ModuleOrganizer: detecting modules in families of transposable elements.

BACKGROUND: Most known eukaryotic genomes contain mobile copied elements called transposable elements. In some species, these elements account for the majority of the genome sequence. They have been subject to many mutations and other genomic events (copies, deletions, captures) during transposition. The identification of these transformations remains a difficult issue. The study of families of transposable elements is generally founded on a multiple alignment of their sequences, a critical step that is adapted to transposons containing mostly localized nucleotide mutations. Many transposons that have lost their protein-coding capacity have undergone more complex rearrangements, needing the development of more complex methods in order to characterize the architecture of sequence variations. RESULTS: In this study, we introduce the concept of a transposable element module, a flexible motif present in at least two sequences of a family of transposable elements and built on a succession of maximal repeats. The paper proposes an assembly method working on a set of exact maximal repeats of a set of sequences to create such modules. It results in a graphical view of sequences segmented into modules, a representation that allows a flexible analysis of the transformations that have occurred between them. We have chosen as a demonstration data set in depth analysis of the transposable element Foldback in Drosophila melanogaster. Comparison with multiple alignment methods shows that our method is more sensitive for highly variable sequences. The study of this family and the two other families AtREP21 and SIDER2 reveals new copies of very different sizes and various combinations of modules which show the potential of our method. CONCLUSIONS: ModuleOrganizer is available on the Genouest bioinformatics center at http://moduleorganizer.genouest.org.

Bioinformatic prediction, deep sequencing of microRNAs and expression analysis during phenotypic plasticity in the pea aphid, Acyrthosiphon pisum.

BACKGROUND: Post-transcriptional regulation in eukaryotes can be operated through microRNA (miRNAs) mediated gene silencing. MiRNAs are small (18-25 nucleotides) non-coding RNAs that play crucial role in regulation of gene expression in eukaryotes. In insects, miRNAs have been shown to be involved in multiple mechanisms such as embryonic development, tissue differentiation, metamorphosis or circadian rhythm. Insect miRNAs have been identified in different species belonging to five orders: Coleoptera, Diptera, Hymenoptera, Lepidoptera and Orthoptera. RESULTS: We developed high throughput Solexa sequencing and bioinformatic analyses of the genome of the pea aphid Acyrthosiphon pisum in order to identify the first miRNAs from a hemipteran insect. By combining these methods we identified 149 miRNAs including 55 conserved and 94 new miRNAs. Moreover, we investigated the regulation of these miRNAs in different alternative morphs of the pea aphid by analysing the expression of miRNAs across the switch of reproduction mode. Pea aphid microRNA sequences have been posted to miRBase: http://microrna.sanger.ac.uk/sequences/. CONCLUSIONS: Our study has identified candidates as putative regulators involved in reproductive polyphenism in aphids and opens new avenues for further functional analyses.