Ultraconserved yet informative for species delimitation: Ultraconserved elements resolve long-standing systematic enigma in Central European bees.

Accurate and testable species hypotheses are essential for measuring, surveying and managing biodiversity. Taxonomists often rely on mitochondrial DNA barcoding to complement morphological species delimitations. Although COI-barcoding has largely proven successful in assisting identifications for most animal taxa, there are nevertheless numerous cases where mitochondrial barcodes do not reflect species hypotheses. For instance, what is regarded as a single species can be associated with two distinct DNA barcodes, which can point either to cryptic diversity or to within-species mitochondrial divergences without reproductive isolation. In contrast, two or more species can share barcodes, for instance due to mitochondrial introgression. These intrinsic limitations of DNA barcoding are commonly addressed with nuclear genomic markers, which are expensive, may have low repeatability and often require high-quality DNA. To overcome these limitations, we examined the use of ultraconserved elements (UCEs) as a quick and robust genomic approach to address such problematic cases of species delimitation in bees. This genomic method was assessed using six different species complexes suspected to harbour cryptic diversity, mitochondrial introgression or mitochondrial paraphyly. The sequencing of UCEs recovered between 686 and 1,860 homologous nuclear loci and provided explicit species delimitation in all investigated species complexes. These results provide strong evidence for the suitability of UCEs as a fast method for species delimitation even in recently diverged lineages. Furthermore, we provide the first evidence for both mitochondrial introgression among distinct bee species, and mitochondrial paraphyly within a single bee species.

Evaluating next-generation sequencing (NGS) methods for routine monitoring of wild bees: Metabarcoding, mitogenomics or NGS barcoding.

Implementing cost-effective monitoring programs for wild bees remains challenging due to the high costs of sampling and specimen identification. To reduce costs, next-generation sequencing (NGS)-based methods have lately been suggested as alternatives to morphology-based identifications. To provide a comprehensive presentation of the advantages and weaknesses of different NGS-based identification methods, we assessed three of the most promising ones, namely metabarcoding, mitogenomics and NGS barcoding. Using a regular monitoring data set (723 specimens identified using morphology), we found that NGS barcoding performed best for both species presence/absence and abundance data, producing only few false positives (3.4%) and no false negatives. In contrast, the proportion of false positives and false negatives was higher using metabarcoding and mitogenomics. Although strong correlations were found between biomass and read numbers, abundance estimates significantly skewed the communities' composition in these two techniques. NGS barcoding recovered the same ecological patterns as morphology. Ecological conclusions based on metabarcoding and mitogenomics were similar to those based on morphology when using presence/absence data, but different when using abundance data. In terms of workload and cost, we show that metabarcoding and NGS barcoding can compete with morphology, but not mitogenomics which was consistently more expensive. Based on these results, we advocate that NGS barcoding is currently the seemliest NGS method for monitoring of wild bees. Furthermore, this method has the advantage of potentially linking DNA sequences with preserved voucher specimens, which enable morphological re-examination and will thus produce verifiable records which can be fed into faunistic databases.

Global Transcriptomic Effects of Environmentally Relevant Concentrations of the Neonicotinoids Clothianidin, Imidacloprid, and Thiamethoxam in the Brain of Honey Bees ( Apis mellifera).

Neonicotinoids are implicated in the decline of honey bees, but the molecular basis underlying adverse effects is poorly known. Here we describe global transcriptomic profiles in the brain of honey bee workers exposed for 48 h at one environmentally realistic and one sublethal concentration of 0.3 and 3.0 ng/bee clothianidin and imidacloprid, respectively, and 0.1 and 1.0 ng/bee thiamethoxam (1-30 ng/mL sucrose solution) by high-throughput RNA-sequencing (RNA-seq). All neonicotinoids led to significant alteration (mainly down-regulation) of gene expression, generally with a concentration-dependent effect. Among many others, genes related to metabolism and detoxification were differently expressed. Gene ontology (GO) enrichment analysis of biological processes revealed catabolic carbohydrate metabolism (regulation of enzyme activities such as amylase), lipid metabolism, and transport mechanisms as shared terms between all neonicotinoids at high concentrations. KEGG pathway analysis indicated that at least two neonicotinoids induced changes in expression of various metabolic pathways: pentose phosphate pathways, starch and sucrose metabolism, and sulfur metabolism, in which glucose 1-dehydrogenase and alpha-amylase were down-regulated and 3'(2'), 5'-bisphosphate nucleotidase was up-regulated. RT-qPCR analysis confirmed the down-regulation of major royal jelly proteins, hbg3, and cyp9e2 found by RNA-seq. Our study highlights the comparative molecular effects of neonicotinoid exposure to bees. Further studies should link these effects with physiological outcomes for a better understanding of effects of neonicotinoids.

Comparative Genomics of Completely Sequenced Lactobacillus helveticus Genomes Provides Insights into Strain-Specific Genes and Resolves Metagenomics Data Down to the Strain Level.

Although complete genome sequences hold particular value for an accurate description of core genomes, the identification of strain-specific genes, and as the optimal basis for functional genomics studies, they are still largely underrepresented in public repositories. Based on an assessment of the genome assembly complexity for all lactobacilli, we used Pacific Biosciences' long read technology to sequence and de novo assemble the genomes of three Lactobacillus helveticus starter strains, raising the number of completely sequenced strains to 12. The first comparative genomics study for L. helveticus-to our knowledge-identified a core genome of 988 genes and sets of unique, strain-specific genes ranging from about 30 to more than 200 genes. Importantly, the comparison of MiSeq- and PacBio-based assemblies uncovered that not only accessory but also core genes can be missed in incomplete genome assemblies based on short reads. Analysis of the three genomes revealed that a large number of pseudogenes were enriched for functional Gene Ontology categories such as amino acid transmembrane transport and carbohydrate metabolism, which is in line with a reductive genome evolution in the rich natural habitat of L. helveticus. Notably, the functional Clusters of Orthologous Groups of proteins categories "cell wall/membrane biogenesis" and "defense mechanisms" were found to be enriched among the strain-specific genes. A genome mining effort uncovered examples where an experimentally observed phenotype could be linked to the underlying genotype, such as for cell envelope proteinase PrtH3 of strain FAM8627. Another possible link identified for peptidoglycan hydrolases will require further experiments. Of note, strain FAM22155 did not harbor a CRISPR/Cas system; its loss was also observed in other L. helveticus strains and lactobacillus species, thus questioning the value of the CRISPR/Cas system for diagnostic purposes. Importantly, the complete genome sequences proved to be very useful for the analysis of natural whey starter cultures with metagenomics, as a larger percentage of the sequenced reads of these complex mixtures could be unambiguously assigned down to the strain level.

An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics.

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae, Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote.

Improved prediction of peptide detectability for targeted proteomics using a rank-based algorithm and organism-specific data.

The in silico prediction of the best-observable "proteotypic" peptides in mass spectrometry-based workflows is a challenging problem. Being able to accurately predict such peptides would enable the informed selection of proteotypic peptides for targeted quantification of previously observed and non-observed proteins for any organism, with a significant impact for clinical proteomics and systems biology studies. Current prediction algorithms rely on physicochemical parameters in combination with positive and negative training sets to identify those peptide properties that most profoundly affect their general detectability. Here we present PeptideRank, an approach that uses learning to rank algorithm for peptide detectability prediction from shotgun proteomics data, and that eliminates the need to select a negative dataset for the training step. A large number of different peptide properties are used to train ranking models in order to predict a ranking of the best-observable peptides within a protein. Empirical evaluation with rank accuracy metrics showed that PeptideRank complements existing prediction algorithms. Our results indicate that the best performance is achieved when it is trained on organism-specific shotgun proteomics data, and that PeptideRank is most accurate for short to medium-sized and abundant proteins, without any loss in prediction accuracy for the important class of membrane proteins. BIOLOGICAL SIGNIFICANCE: Targeted proteomics approaches have been gaining a lot of momentum and hold immense potential for systems biology studies and clinical proteomics. However, since only very few complete proteomes have been reported to date, for a considerable fraction of a proteome there is no experimental proteomics evidence that would allow to guide the selection of the best-suited proteotypic peptides (PTPs), i.e. peptides that are specific to a given proteoform and that are repeatedly observed in a mass spectrometer. We describe a novel, rank-based approach for the prediction of the best-suited PTPs for targeted proteomics applications. By building on methods developed in the field of information retrieval (e.g. web search engines like Google's PageRank), we circumvent the delicate step of selecting positive and negative training sets and at the same time also more closely reflect the experimentalist´s need for selecting e.g. the 5 most promising peptides for targeting a protein of interest. This approach allows to predict PTPs for not yet observed proteins or for organisms without prior experimental proteomics data such as many non-model organisms.

Developing diagnostic SNP panels for the identification of true fruit flies (Diptera: Tephritidae) within the limits of COI-based species delimitation.

BACKGROUND: Rapid and reliable identification of quarantine pests is essential for plant inspection services to prevent introduction of invasive species. For insects, this may be a serious problem when dealing with morphologically similar cryptic species complexes and early developmental stages that lack distinctive characters useful for taxonomic identification. DNA based barcoding could solve many of these problems. The standard barcode fragment, an approx. 650 base pairs long sequence of the 5'end of the mitochondrial cytochrome oxidase I (COI), enables differentiation of a very wide range of arthropods. However, problems remain in some taxa, such as Tephritidae, where recent genetic differentiation among some of the described species hinders accurate molecular discrimination. RESULTS: In order to explore the full species discrimination potential of COI, we sequenced the barcoding region of the COI gene of a range of economically important Tephritid species and complemented these data with all GenBank and BOLD entries for the systematic group available as of January 2012. We explored the limits of species delimitation of this barcode fragment among 193 putative Tephritid species and established operational taxonomic units (OTUs), between which discrimination is reliably possible. Furthermore, to enable future development of rapid diagnostic assays based on this sequence information, we characterized all single nucleotide polymorphisms (SNPs) and established "near-minimal" sets of SNPs that differentiate among all included OTUs with at least three and four SNPs, respectively. CONCLUSIONS: We found that although several species cannot be differentiated based on the genetic diversity observed in COI and hence form composite OTUs, 85% of all OTUs correspond to described species. Because our SNP panels are developed based on all currently available sequence information and rely on a minimal pairwise difference of three SNPs, they are highly reliable and hence represent an important resource for developing taxon-specific diagnostic assays. For selected cases, possible explanations that may cause composite OTUs are discussed.

Rapid detection and species identification of Mycobacterium spp. using real-time PCR and DNA-microarray.

Infections with mycobacteria are an important issue in public health care. Here we present a "proof-of-principle" concept for the identification of 37 different Mycobacterium species using 5' exonuclease real-time PCR and DNA microarray based on the region upstream of the 65 kDa heat shock protein. With our two PCR probes, one complementary to all mycobacteria species, the other specific for the M. tbc-complex, 34 species were properly classified by real-time PCR. After reamplification and hybridization to a DNA microarray, all species showed a specific pattern. All 10 blindly tested positive cultures revealed a positive real-time PCR signal with the genus probe. After reamplification and hybridization, six samples could unambiguously be identified. One sample showed a mixture of presumably three species-specific patterns and sequencing the 16S rRNA confirmed the presence of a mixture. The hybridization results of three specimens could not be interpreted because the signal to background ratio was not sufficient. Two samples considered as negative controls (LAL Reagent Water (Cambrex) and DNA of Candida albicans) gave neither a genus nor a M. tbc-complex positive PCR signal. Based on these results we consider our method to be a promising tool for the rapid identification of different mycobacteria species, with the advantage of possible identification of mixed infections or contaminations.

Quantitative assessment of heteroplasmy levels in Senecio vulgaris chloroplast DNA.

Heteroplasmy in coding chloroplast DNA was only recently shown to occur and was so far not quantitatively assessed. We present a quantitative analysis of cpDNA heteroplasmy levels at a triazine-resistance determining site within and between individual Senecio vulgaris plants. Detectable levels of heteroplasmic haplotypes were observed in all tested plants. As expected, the levels of heteroplasmy vary greatly between plants. However, even within individual plants, the fraction of one haplotype may cover a range from below 1% to well over 90%. Our results suggest that heteroplasmy may be a common phenomenon in S. vulgaris. Possible consequences for molecular diagnostics of chloroplast encoded traits as well as evolutionary consequences of chloroplast heteroplasmy are discussed.

Dissociation analysis in polymerase chain reaction and 1X SSC buffer as a prerequisite for selection of 13mer microarray probe sets with uniform hybridization behavior.

Homogeneous probe hybridization is a prerequisite for the robust design of microarrays. Elaborate algorithms were developed to select for probe sets with uniform melting temperatures (Tm). However, at least short oligonucleotides (< 20 bp) show large variation in the on-chip hybridization efficiency even if designed with state-of-the-art algorithms. This variation can be explained by steric effects and interferences on the solid surface as well as by chemical conditions that may deviate from conditions used to develop the algorithms. We designed 412 random 13mer duplexes to study the differences between the Tm of nearest-neighbor algorithms and the Tm values measured by dissociation analysis in polymerase chain reaction (PCR) and 1X SSC buffer. We tested the effects of theoretical vs empirical Tm values on the hybridization variation of 40 duplexes on-chip. Although the empirical approach resulted in a slightly better prediction of hybridization efficiency, less than one-fifth (17%) of the observed variation could be explained by the factor Tm alone. We conclude that state-of-the-art algorithms can be used for a first selection of short oligonucleotide probes, but that it is then necessary to perform an on-chip selection to obtain a probe set with a uniform hybridization behavior.

Origin of intra-individual variation in PCR-amplified mitochondrial cytochrome oxidase I of Thrips tabaci (Thysanoptera: Thripidae): mitochondrial heteroplasmy or nuclear integration?

The mitochondrial genome is increasingly being used as a species diagnostic marker in insects. Typically, genomic DNA is PCR amplified and then analysed by restriction analyses or sequencing. This analysis system may cause some serious problems for molecular diagnosis. Besides the errors introduced by the PCR process, mtDNA sequence variation of amplified fragments may originate from mtDNA heteroplasmy or from nuclear integrations of mtDNA fragments, both of which have been shown to occur in insects. Here we document abundant variation in PCR-amplified sequences of the mitochondrial cytochrome oxidase I gene of Thrips tabaci. We confirm that the most common haplotype is of mitochondrial origin. Some of the observed mutations were introduced by the amplification process. However, the occurrence of some haplotypes at elevated frequencies indicates that within-individual variation of the respective fragment exists at low levels in T. tabaci. The frequencies of these sequences are too low to negatively affect mtDNA-based molecular diagnosis of T. tabaci. The possible origin of these variant haplotypes is discussed.