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Background The Aedes aegypti mosquito is a threat to human health across the globe. The A. aegypti genome was recently re-sequenced and re-assembled. Due to a combination of long-read PacBio and Hi-C sequencing, the AaegL5 assembly is chromosome complete and significantly improves the assembly in key areas such as the M/m sex-determining locus. Release of the updated genome assembly has precipitated the need to reprocess historical functional genomic data sets, including cis-regulatory element (CRE) maps that had previously been generated for A. aegypti. Results We re-processed and re-analyzed the A. aegypti whole embryo FAIRE seq data to create an updated embryonic CRE map for the AaegL5 genome. We validated that the new CRE map recapitulates key features of the original AaegL3 CRE map. Further, we built on the improved assembly in the M/m locus to analyze overlaps of open chromatin regions with genes. To support the validation, we created a new method (PeakMatcher) for matching peaks from the same experimental data set across genome assemblies. Conclusion Use of PeakMatcher software, which is available publicly under an open-source license, facilitated the release of an updated and validated CRE map, which is available through the NIH GEO. These findings demonstrate that PeakMatcher software will be a useful resource for validation and transferring of previous annotations to updated genome assemblies.

Genetic crosses are most powerful for linkage analysis when progeny numbers are high, parental alleles segregate evenly and numbers of inbred progeny are minimized. We previously developed a novel genetic crossing platform for the human malaria parasite Plasmodium falciparum, an obligately sexual, hermaphroditic protozoan, using mice carrying human hepatocytes (the human liver-chimeric FRG NOD huHep mouse) as the vertebrate host. We report on two genetic crosses—(1) an allopatric cross between a laboratory-adapted parasite (NF54) of African origin and a recently patient-derived Asian parasite, and (2) a sympatric cross between two recently patient-derived Asian parasites. We generated 144 unique recombinant clones from the two crosses, doubling the number of unique recombinant progeny generated in the previous 30 years. The allopatric African/Asian cross has minimal levels of inbreeding and extreme segregation distortion, while in the sympatric Asian cross, inbred progeny predominate and parental alleles segregate evenly. Using simulations, we demonstrate that these progeny provide the power to map small-effect mutations and epistatic interactions. The segregation distortion in the allopatric cross slightly erodes power to detect linkage in several genome regions. We greatly increase the power and the precision to map biomedically important traits with these new large progeny panels., Button-Simons et al. report on two different genetic crosses of Plasmodium falciparum derived from Asian and African origin parasites, and generate large numbers of recombinant progeny. These crosses are characterized and have the potential to map biologically important traits across parasite genomes.

Simple Summary Monitoring of resistance alleles is critical to the sustainability of transgenic crops producing insecticidal Cry proteins. Highly sensitive and cost-effective DNA-based methods are needed to improve current bioassay-based resistance screening. Our goal was to evaluate the use of targeted sequencing in detecting known and novel candidate resistance alleles to Cry proteins. As a model, we used field-collected fall armyworm (Spodoptera frugiperda) from Puerto Rico, the first location reporting continued practical field-evolved S. frugiperda resistance to corn producing the Cry1F insecticidal protein, and sequenced the SfABCC2 gene previously identified as critical to Cry1F toxicity. Targeted sequencing of SfABCC2 detected a previously reported Cry1F resistance allele and mutations originally identified in populations from Brazil. Importantly, targeted sequencing also identified nonsynonymous and frameshift mutations as novel candidate resistance alleles. These results advocate for the use of targeted sequencing in screening for resistance alleles to Cry proteins and support potential gene flow, including resistance alleles, between S. frugiperda from Brazil and the Caribbean. Abstract Evolution of practical resistance is the main threat to the sustainability of transgenic crops producing insecticidal proteins from Bacillus thuringiensis (Bt crops). Monitoring of resistance to Cry and Vip3A proteins produced by Bt crops is critical to mitigate the development of resistance. Currently, Cry/Vip3A resistance allele monitoring is based on bioassays with larvae from inbreeding field-collected moths. As an alternative, DNA-based monitoring tools should increase sensitivity and reduce overall costs compared to bioassay-based screening methods. Here, we evaluated targeted sequencing as a method allowing detection of known and novel candidate resistance alleles to Cry proteins. As a model, we sequenced a Cry1F receptor gene (SfABCC2) in fall armyworm (Spodoptera frugiperda) moths from Puerto Rico, a location reporting continued practical field resistance to Cry1F-producing corn. Targeted sequencing detected a previously reported Cry1F resistance allele (SfABCC2mut), in addition to a resistance allele originally described in S. frugiperda populations from Brazil. Moreover, targeted sequencing detected mutations in SfABCC2 as novel candidate resistance alleles. These results support further development of targeted sequencing for monitoring resistance to Bt crops and provide unexpected evidence for common resistance alleles in S. frugiperda from Brazil and Puerto Rico.

As a specific type of structural variation, inversions are enjoying particular traction as a result of their established role in evolution. Using third-generation sequencing technology to predict inversions is growing in interest, but many such methods focus on improving sensitivity, giving rise to either too many false positives or very long running times. In this paper, we propose a new framework for inversion detection based on a combination of two novel theoretical models: rectangle clustering and representative rectangle prediction. This combination can automatically filter out false positive inversion predictions while retaining correct ones, leading to a method that has both high sensitivity and high positive prediction values (PPV). Further, this new framework can run very fast on available data. Our software can be freely obtained at https://github.com/UTbioinf/RigInv .

Background The stable fly, Stomoxys calcitrans, is a major blood-feeding pest of livestock that has near worldwide distribution, causing an annual cost of over $2 billion for control and product loss in the USA alone. Control of these flies has been limited to increased sanitary management practices and insecticide application for suppressing larval stages. Few genetic and molecular resources are available to help in developing novel methods for controlling stable flies. Results This study examines stable fly biology by utilizing a combination of high-quality genome sequencing and RNA-Seq analyses targeting multiple developmental stages and tissues. In conjunction, 1600 genes were manually curated to characterize genetic features related to stable fly reproduction, vector host interactions, host-microbe dynamics, and putative targets for control. Most notable was characterization of genes associated with reproduction and identification of expanded gene families with functional associations to vision, chemosensation, immunity, and metabolic detoxification pathways. Conclusions The combined sequencing, assembly, and curation of the male stable fly genome followed by RNA-Seq and downstream analyses provide insights necessary to understand the biology of this important pest. These resources and new data will provide the groundwork for expanding the tools available to control stable fly infestations. The close relationship of Stomoxys to other blood-feeding (horn flies and Glossina) and non-blood-feeding flies (house flies, medflies, Drosophila) will facilitate understanding of the evolutionary processes associated with development of blood feeding among the Cyclorrhapha.

Most attempts to fit a supervised machine learning (ML) model in bioinformatics try to predict the full range of trait or response values. While such prediction tasks effectively capture the entire phenotypic range of the samples, they are cost prohibitive and can be statistically underpowered for detection of rare variants. In a study design known as extreme phenotype sampling (EPS), samples are selected from the two extremes of the phenotypic distribution. This approach is costcutting, by reducing genotyping/sequencing costs, as well as capable of increasing statistical power. Although combining EPS with ML algorithms has the potential to enhance association studies by improving their computational efficiency, EPS-ML approaches have seen limited use. In this paper we demonstrate an efficient and effective approach to leverage the EPS study design using LASSO regression and random forests, two commonly used ML algorithms within the broader bioinformatics community. We analyze two distinct data sets: leaf expression values generated from black cottonwood and malaria parasite transcriptome data collected from patients. We demonstrate that focusing only on the phenotypic extremes of these sample sets (by forming binary classes) can select more biologically meaningful features than using the full range. This approach will be useful to investigators when examining complex or novel traits. It is particularly well-suited to RNA-seq data where investigators often want to narrow attention to a small number of candidate transcripts out of a large initial pool. Our approach intentionally leverages existing software with efficient implementations to enable future applications of EPS-ML. 1

Background The fall armyworm (Spodoptera frugiperda (J.E. Smith)) is a highly polyphagous agricultural pest with long-distance migratory behavior threatening food security worldwide. This pest has a host range of > 80 plant species, but two host strains are recognized based on their association with corn (C-strain) or rice and smaller grasses (R-strain). The population genomics of the United States (USA) fall armyworm remains poorly characterized to date despite its agricultural threat. Results In this study, the population structure and genetic diversity in 55 S. frugiperda samples from Argentina, Brazil, Kenya, Puerto Rico and USA were surveyed to further our understanding of whole genome nuclear diversity. Comparisons at the genomic level suggest a panmictic S. frugiperda population, with only a minor reduction in gene flow between the two overwintering populations in the continental USA, also corresponding to distinct host strains at the mitochondrial level. Two maternal lines were detected from analysis of mitochondrial genomes. We found members from the Eastern Hemisphere interspersed within both continental USA overwintering subpopulations, suggesting multiple individuals were likely introduced to Africa. Conclusions Our research is the largest diverse collection of United States S. frugiperda whole genome sequences characterized to date, covering eight continental states and a USA territory (Puerto Rico). The genomic resources presented provide foundational information to understand gene flow at the whole genome level among S. frugiperda populations. Based on the genomic similarities found between host strains and laboratory vs. field samples, our findings validate the experimental use of laboratory strains and the host strain differentiation based on mitochondria and sex-linked genetic markers extends to minor genome wide differences with some exceptions showing mixture between host strains is likely occurring in field populations.

When reference genome assemblies are updated, the peaks from DNA enrichment assays such as ChIP-Seq and FAIRE-Seq need to be called again using the new genome assembly. PeakMatcher is an open-source package that aids in validation by matching peaks across two genome assemblies using the alignment of reads or within the same genome. PeakMatcher calculates recall and precision while also outputting lists of peak-to-peak matches. PeakMatcher uses read alignments to match peaks across genome assemblies. PeakMatcher finds all read aligned to one genome that overlap with a given list of peaks. PeakMatcher uses the read names to locate where those reads are aligned against a second genome. Lastly, all peaks called against the second genome that overlap with the aligned reads are found and output. PeakMatcher groups uses the peak-read-peak relationships to discover 1-to-1, 1-to-many, and many-to-many relationships. Overlap queries are performed with interval trees for maximum efficiency. We evaluated PeakMatcher on two data sets. The first data set was FAIRE-Seq (Formaldehyde-Assisted Isolation of Regulatory Elements Sequencing) of DNA isolated embyros of the mosquito Aedes aegypti [2, 4]. We implemented a peak calling pipeline and validated it on the older (highly fragmented) AaegL3 assembly [5]. PeakMatcher matched 92.9% (precision) of the 121,594 previously-called peaks from [2, 4] with 89.4% (recall) of the 124,959 peaks called with our new pipeline. Next, we applied the peak-calling pipeline to call FAIRE peaks using the newer, chromosome-complete AaegL5 assembly [3]. PeakMatcher found matches for 14 of the 16 experimentally-validated AaegL3 FAIRE peaks from [2, 4]. We validated the matches by comparing nearby genes across the genomes. Nearby genes were consistent for 11 of the 14 peaks; inconsistencies for at least two of the remaining peaks were clearly attributable to differences in assemblies. When applied to all of the peaks, Peak-Matcher matched 78.8% (precision) of the 124,959 AaegL3 peaks with 76.7% (recall) of the 128,307 AaegL5 peaks. The second data set was STARR-Seq (Self-Transcribing Active Regulatory Region Sequencing) of Drosophila melanogaster DNA in S2 culture cells [1]. We called STARR peaks against two versions (dm3 and r5.53) of the D. melanogaster genome [6]. PeakMatcher matched 77.4% (precision) of the 4,195 dm3 peaks with 94.8% (recall) of the 3,114 r5.53 peaks. PeakMatcher and associated documentation are available on GitHub (https://github.com/rnowling/peak-matcher) under the open-source Apache Software License v2. PeakMatcher was written in Python 3 using the intervaltree library.

Phlebotomus papatasi sand flies inject their hosts with a myriad of pharmacologically active salivary proteins to assist with blood feeding and to modulate host defenses. In addition, salivary proteins can influence cutaneous leishmaniasis disease outcome, highlighting the potential of the salivary components to be used as a vaccine. Variability of vaccine targets in natural populations influences antigen choice for vaccine development. Therefore, the objective of this study was to investigate the variability in the predicted protein sequences of nine of the most abundantly expressed salivary proteins from field populations, testing the hypothesis that salivary proteins appropriate to target for vaccination strategies will be possible. PpSP12, PpSP14, PpSP28, PpSP29, PpSP30, PpSP32, PpSP36, PpSP42, and PpSP44 mature cDNAs from field collected P. papatasi from three distinct ecotopes in the Middle East and North Africa were amplified, sequenced, and in silico translated to assess the predicted amino acid variability. Two of the predicted sequences, PpSP12 and PpSP14, demonstrated low genetic variability across the three geographic isolated sand fly populations, with conserved multiple predicted MHCII epitope binding sites suggestive of their potential application in vaccination approaches. The other seven predicted salivary proteins revealed greater allelic variation across the same sand fly populations, possibly precluding their use as vaccine targets., Author summary Phlebotomus papatasi sand flies vector Leishmania major parasites, one of the causative agents of cutaneous leishmaniasis (CL). Approximately 0.7–1.2 million cases of CL occur each year. CL produces disfiguring skin lesions for which no vaccine currently exists. Hematophagous arthropods secrete salivary proteins that modulate host inflammation, vasoconstriction, and blood clotting. Salivary proteins from multiple phlebotomine sand fly species have been widely studied and scrutinized to characterize their function in blood feeding as well as their ability to exacerbate or attenuate Leishmania infections. Hence their potential role as vaccine or as a component of vaccination strategies. In such regard, we hypothesize that in order to be successful, sand fly salivary protein-based vaccines must consider, in addition to the human immune responses, the genetic variability and the expression profiles of such salivary antigens from geographically distant sand fly populations. The purpose of this study was to analyze the genetic variability of nine of the most abundant secreted salivary proteins identified in P. papatasi, comparing insects collected from distinct ecotopes in Egypt and Jordan.

The advent of next-generation sequencing has allowed for higher-throughput determination of which species live within a specific location. Here we establish that three analysis methods for estimating diversity within samples&mdash, namely, Operational Taxonomic Units, the newer Amplicon Sequence Variants, and a method commonly found in sequence analysis, minhash&mdash, are affected by various properties of these sequence data. Using simulations we show that the presence of Single Nucleotide Polymorphisms and the depth of coverage from each species affect the correlations between these approaches. Through this analysis, we provide insights which would affect the decisions on the application of each method. Specifically, the presence of sequence read errors and variability in sequence read coverage deferentially affects these processing methods.

Improved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only in highly expressed genes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments from S. cerevisiae, because RFP data is often considered as a “ground truth” for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating translational slowdowns. However, we also show that there is a weak correlation between RFP counts for the same genes originating from independent experiments, even when their experimental conditions are similar. This raises concerns about the efficacy of using current RFP experimental data for estimating translation rates and highlights a potential advantage of using computational models to understand translation rates instead.

BackgroundNew sequencing technologies have lowered financial barriers to whole genome sequencing, but resulting assemblies are often fragmented and far from ‘finished’. Updating multi-scaffold drafts to chromosome-level status can be achieved through experimental mapping or re-sequencing efforts. Avoiding the costs associated with such approaches, comparative genomic analysis of gene order conservation (synteny) to predict scaffold neighbours (adjacencies) offers a potentially useful complementary method for improving draft assemblies.ResultsWe employed three gene synteny-based methods applied to 21 Anopheles mosquito assemblies to produce consensus sets of scaffold adjacencies. For subsets of the assemblies we integrated these with additional supporting data to confirm and complement the synteny-based adjacencies: six with physical mapping data that anchor scaffolds to chromosome locations, 13 with paired-end RNA sequencing (RNAseq) data, and three with new assemblies based on re-scaffolding or Pacific Biosciences long-read data. Our combined analyses produced 20 new superscaffolded assemblies with improved contiguities: seven for which assignments of non-anchored scaffolds to chromosome arms span more than 75% of the assemblies, and a further seven with chromosome anchoring including an 88% anchored Anopheles arabiensis assembly and, respectively, 73% and 84% anchored assemblies with comprehensively updated cytogenetic photomaps for Anopheles funestus and Anopheles stephensi.ConclusionsExperimental data from probe mapping, RNAseq, or long-read technologies, where available, all contribute to successful upgrading of draft assemblies. Our comparisons show that gene synteny-based computational methods represent a valuable alternative or complementary approach. Our improved Anopheles reference assemblies highlight the utility of applying comparative genomics approaches to improve community genomic resources.

Background Malaria is the leading cause of global paediatric mortality in children below 5 years of age. The number of fatalities has reduced significantly due to an expansion of control interventions but the development of new technologies remains necessary in order to achieve elimination. Recent attention has been focused on the release of genetically modified (GM) mosquitoes into natural vector populations as a mechanism of interrupting parasite transmission but despite successful in vivo laboratory studies, a detailed population genetic assessment, which must first precede any proposed field trial, has yet to be undertaken systematically. Here, the genetic structure of Anopheles gambiae populations in north-western Lake Victoria is explored to assess their suitability as candidates for a pilot field study release of GM mosquitoes. Methods 478 Anopheles gambiae mosquitoes were collected from six locations and a subset (N = 96) was selected for restriction site-associated DNA sequencing (RADseq). The resulting single nucleotide polymorphism (SNP) marker set was analysed for effective size (Ne), connectivity and population structure (PCA, FST). Results 5175 high-quality genome-wide SNPs were identified. A principal components analysis (PCA) of the collinear genomic regions illustrated that individuals clustered in concordance with geographic origin with some overlap between sites. Genetic differentiation between populations was varied with inter-island comparisons having the highest values (median FST 0.0480–0.0846). Ne estimates were generally small (124.2–1920.3). Conclusions A reduced-representation SNP marker set for genome-wide An. gambiae genetic analysis in the north-western Lake Victoria basin is reported. Island populations demonstrated low to moderate genetic differentiation and greater structure suggesting some limitation to migration. Smaller estimates of Ne indicate that an introduced effector transgene will be more susceptible to genetic drift but to ensure that it is driven to fixation a robust gene drive mechanism will likely be needed. These findings, together with their favourable location and suitability for frequent monitoring, indicate that the Ssese Islands contain several candidate field locations, which merit further evaluation as potential GM mosquito pilot release sites. Electronic supplementary material The online version of this article (10.1186/s12936-018-2432-0) contains supplementary material, which is available to authorized users.

Although single molecule sequencing is still improving, the lengths of the generated sequences are inevitably an advantage in genome assembly. Prior work that utilizes long reads to conduct genome assembly has mostly focused on correcting sequencing errors and improving contiguity of de novo assemblies. In this paper, we propose a disassembling-reassembling approach for both correcting structural errors in the draft assembly and scaffolding a target assembly based on error-corrected single molecule sequences. In particular, the disassembling stage identifies potential structural errors in the draft assembly and disassembles the draft assembly to remove such erroneous positions, ensuring that the resulting contigs (called validated segments in this paper) are structurally consistent with the new sequence data. The reassembling stage bridges the validated segments to build larger contigs by utilizing the remaining unaligned long reads in the disassembling stage, aiming to improve the contiguity of the final assembly. To achieve this goal, we formulate a maximum alternating path cover problem. We prove that this problem is NP-hard, and solve it by a 2-approximation algorithm. Our experimental results show that our approach can improve the structural correctness of target assemblies in the cost of some contiguity, even with smaller amounts of long reads. Finally, we show that our reassembling process can also serve as a competitive scaffolder using a well-established assembly benchmark.

Most amino acids can be encoded by more than one synonymous codon, but these are rarely used with equal frequency. In many coding sequences the usage patterns of rare versus common synonymous codons is nonrandom and under selection. Moreover, synonymous substitutions that alter these patterns can have a substantial impact on the folding efficiency of the encoded protein. This has ignited broad interest in exploring synonymous codon usage patterns. For many protein chemists, biophysicists and structural biologists, the primary motivation for codon analysis is identifying and preserving usage patterns most likely to impact high-yield production of functional proteins. Here we describe the core functions and new features of %MinMax, a codon usage calculator freely available as a web-based portal and downloadable script (http://www.codons.org). %MinMax evaluates the relative usage frequencies of the synonymous codons used to encode a protein sequence of interest and compares these results to a rigorous null model. Crucially, for analyzing codon usage in common host organisms %MinMax requires only the coding sequence as input; with a user-input codon frequency table, %MinMax can be used to evaluate synonymous codon usage patterns for any coding sequence from any fully sequenced genome. %MinMax makes no assumptions regarding the impact of transfer ribonucleic acid concentrations or other molecular-level interactions on translation rates, yet its output is sufficient to predict the effects of synonymous codon substitutions on cotranslational folding mechanisms. A simple calculation included within %MinMax can be used to harmonize codon usage frequencies for heterologous gene expression.

Concern about elevated disease risk following disasters has been growing with the progression of global trends in urbanization and climate, in part because shifts in socioecological conditions can promote greater human contact with pathogen reservoirs in cities. Remarkably little is known, however, about the diversity and distributions of pathogens carried by commensal reservoirs across disaster-affected urban landscapes. To address this deficit, we characterized the assemblage structure of viruses in the serum of three widespread commensal rodents (Rattus norvegicus, Rattus rattus, and Mus musculus) that were trapped in New Orleans (LA, USA) following Hurricane Katrina. We assessed virus diversity and differentiation according to host species identity, co-occurrence and abundance, as well as prevailing landscape features known to shape urban rodent assemblages. We detected ≥34 viruses in total, including several pathogens of concern, through metagenomic analysis of serum taken from ≥149 individuals of each host species. We found that virus richness as well as assemblage composition and spatial differentiation differed by host species. Notably, we detected associations with host species co-occurrence and abundance, and while we found that assemblage structure varied by study area, we did not detect strong associations with landscape features known to influence rodent hosts. Evidence that virus diversity and assemblage structure reflect host identity more so than other factors indicates that biotic benchmarks might serve as prognostic indicators of post-disaster pathogen exposure risk in cities worldwide.

Background Restriction site associated DNA sequencing (RADseq) has the potential to be a broadly applicable, low-cost approach for high-quality genetic linkage mapping in forest trees lacking a reference genome. The statistical inference of linear order must be as accurate as possible for the correct ordering of sequence scaffolds and contigs to chromosomal locations. Accurate maps also facilitate the discovery of chromosome segments containing allelic variants conferring resistance to the biotic and abiotic stresses that threaten forest trees worldwide. We used ddRADseq for genetic mapping in the tree Quercus rubra, with an approach optimized to produce a high-quality map. Our study design also enabled us to model the results we would have obtained with less depth of coverage. Results Our sequencing design produced a high sequencing depth in the parents (248×) and a moderate sequencing depth (15×) in the progeny. The digital normalization method of generating a de novo reference and the SAMtools SNP variant caller yielded the most SNP calls (78,725). The major drivers of map inflation were multiple SNPs located within the same sequence (77% of SNPs called). The highest quality map was generated with a low level of missing data (5%) and a genome-wide threshold of 0.025 for deviation from Mendelian expectation. The final map included 849 SNP markers (1.8% of the 78,725 SNPs called). Downsampling the individual FASTQ files to model lower depth of coverage revealed that sequencing the progeny using 96 samples per lane would have yielded too few SNP markers to generate a map, even if we had sequenced the parents at depth 248×. Conclusions The ddRADseq technology produced enough high-quality SNP markers to make a moderately dense, high-quality map. The success of this project was due to high depth of coverage of the parents, moderate depth of coverage of the progeny, a good framework map, an optimized bioinformatics pipeline, and rigorous premapping filters. The ddRADseq approach is useful for the construction of high-quality genetic maps in organisms lacking a reference genome if the parents and progeny are sequenced at sufficient depth. Technical improvements in reduced representation sequencing (RRS) approaches are needed to reduce the amount of missing data. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3765-8) contains supplementary material, which is available to authorized users.

Chromosomal inversions are associated with reproductive isolation and adaptation in insects such as Drosophila melanogaster and the malaria vectors Anopheles gambiae and Anopheles coluzzii. While methods based on read alignment have been useful in humans for detecting inversions, these methods are less successful in insects due to long repeated sequences at the breakpoints. Alternatively, inversions can be detected using principal component analysis (PCA) of single nucleotide polymorphisms (SNPs). We apply PCA-based inversion detection to a simulated data set and real data from multiple insect species, which vary in complexity from a single inversion in samples drawn from a single population to analyzing multiple overlapping inversions occurring in closely-related species, samples of which that were generated from multiple geographic locations. We show empirically that proper analysis of these data can be challenging when multiple inversions or populations are present, and that our alternative framework is more robust in these more difficult scenarios.

Motivation Most amino acids are encoded by multiple synonymous codons, some of which are used more rarely than others. Analyses of positions of such rare codons in protein sequences revealed that rare codons can impact co-translational protein folding and that positions of some rare codons are evolutionarily conserved. Analyses of their positions in protein 3-dimensional structures, which are richer in biochemical information than sequences alone, might further explain the role of rare codons in protein folding. Results We model protein structures as networks and use network centrality to measure the structural position of an amino acid. We first validate that amino acids buried within the structural core are network-central, and those on the surface are not. Then, we study potential differences between network centralities and thus structural positions of amino acids encoded by conserved rare, non-conserved rare and commonly used codons. We find that in 84% of proteins, the three codon categories occupy significantly different structural positions. We examine protein groups showing different codon centrality trends, i.e. different relationships between structural positions of the three codon categories. We see several cases of all proteins from our data with some structural or functional property being in the same group. Also, we see a case of all proteins in some group having the same property. Our work shows that codon usage is linked to the final protein structure and thus possibly to co-translational protein folding. Availability and implementation https://nd.edu/∼cone/CodonUsage/. Supplementary information Supplementary data are available at Bioinformatics online.

Arthropods play a dominant role in natural and human-modified terrestrial ecosystem dynamics. Spatially-explicit arthropod population time-series data are crucial for statistical or mathematical models of these dynamics and assessment of their veterinary, medical, agricultural, and ecological impacts. Such data have been collected world-wide for over a century, but remain scattered and largely inaccessible. In particular, with the ever-present and growing threat of arthropod pests and vectors of infectious diseases, there are numerous historical and ongoing surveillance efforts, but the data are not reported in consistent formats and typically lack sufficient metadata to make reuse and re-analysis possible. Here, we present the first-ever minimum information standard for arthropod abundance, Minimum Information for Reusable Arthropod Abundance Data (MIReAD). Developed with broad stakeholder collaboration, it balances sufficiency for reuse with the practicality of preparing the data for submission. It is designed to optimize data (re)usability from the “FAIR,” (Findable, Accessible, Interoperable, and Reusable) principles of public data archiving (PDA). This standard will facilitate data unification across research initiatives and communities dedicated to surveillance for detection and control of vector-borne diseases and pests.

Malaria is transmitted through female Anopheline mosquitoes where gamete fusion and meiosis occurs, and humans where parasites proliferate asexually. We describe a powerful approach to identify the genetic determinants of parasite fitness across both invertebrate and vertebrate life-cycle stages in human malaria parasitePlasmodium falciparumusing bulk segregant analysis (BSA). We combined experimental genetic crosses using humanized mice, with selective whole genome amplification and BSA at multiple developmental stages in both mosquito and vertebrate host to examine parasite competition and identify genomic regions under selection. We generated crosses between artemisinin resistant (ART-R,kelch13-C580Y) and ART-sensitive (ART-S,kelch13-WT) parasite clones recently isolated from Southeast Asian patients. We then quantified genome-wide changes in allele frequency in the parasite progeny population from infected midgut and salivary glands ofAnopheles stephensimosquitoes, infected livers, emerging merozoites and aliquots ofin vitrocultured progeny parasites at intervals over 30 days. Three striking results emerge: we observed (i) a strong skew (>80%) towards alleles from the ART-R parent in the mosquito stage, that dropped to ∼50% in the blood stage as selfed ART-R parasites were selected against; (ii) highly repeatable skews in allele frequencies across the genome in blood stage parasites; (iii) particularly strong selection (selection coefficient (s) ≤ 0.18/asexual cycle) against alleles from the ART-R parent at loci on chromosome 12 containing MRP2 and chromosome 14 containing ARPS10. This approach robustly identifies selected loci and has strong potential for identifying parasite genes that interact with the mosquito vector or compensatory loci involved in drug resistance.

Three common methods, normalization, log transformation, and rarefaction, for handling outliers and erroneous abundances in Operational Taxonomic Unit (OTU) tables are tested for effects in K-means and PCA clustering as well as effects in NMF. We find that of the three methods, log transformation is closest to the unmodified OTUs data, also indicating that when doing specific types of clustering analysis on OTU data, if outliers are to be adjusted within a clustering analysis, a log transformation may be applied.

The advent of next-generation barcode sequencing has allowed for more high-throughput determination of which species live within an area. Relationships, which are a computed distance, are determined by inferred occupancy of the species in one location relative to another. Here we establish that two analysis methods, namely the established Operational Taxonomic Unit approach and a method commonly found in alignment, kmers, are affected by latent effects within real data. We then analyze these latent effects using simulated data and show that the presence of Single Nucleotide Polymorphisms (i.e., SNPs) within the data and the number of sequences obtained from each species affect inferred correlations.

Association tests performed with the Likelihood-Ratio Test (LR Test) can be an alternative to [Formula: see text], which is often used in population genetics to find variants of interest. Because the LR Test has several properties that could make it preferable to [Formula: see text], we propose a novel approach for modeling unknown genotypes in highly-similar species. To show the effectiveness of this LR Test approach, we apply it to single-nucleotide polymorphisms (SNPs) associated with the recent speciation of the malaria vectors Anopheles gambiae and Anopheles coluzzii and compare to [Formula: see text].

The molecular mechanisms and genetic architecture that facilitate adaptive radiation of lineages remain elusive. Polymorphic chromosomal inversions, due to their recombination-reducing effect, are proposed instruments of ecotypic differentiation. Here, we study an ecologically diversifying lineage of Anopheles gambiae, known as the Bamako chromosomal form based on its unique complement of three chromosomal inversions, to explore the impact of these inversions on ecotypic differentiation. We used pooled and individual genome sequencing of Bamako, typical (non-Bamako) An. gambiae and the sister species Anopheles coluzzii to investigate evolutionary relationships and genomewide patterns of nucleotide diversity and differentiation among lineages. Despite extensive shared polymorphism and limited differentiation from the other taxa, Bamako clusters apart from the other taxa, and forms a maximally supported clade in neighbour-joining trees based on whole-genome data (including inversions) or solely on collinear regions. Nevertheless, FST outlier analysis reveals that the majority of differentiated regions between Bamako and typical An. gambiae are located inside chromosomal inversions, consistent with their role in the ecological isolation of Bamako. Exceptionally differentiated genomic regions were enriched for genes implicated in nervous system development and signalling. Candidate genes associated with a selective sweep unique to Bamako contain substitutions not observed in sympatric samples of the other taxa, and several insecticide resistance gene alleles shared between Bamako and other taxa segregate at sharply different frequencies in these samples. Bamako represents a useful window into the initial stages of ecological and genomic differentiation from sympatric populations in this important group of malaria vectors.

Arthropods play a dominant role in natural and human-modified terrestrial ecosystem dynamics. Spatially-explicit population time-series are crucial for statistical or mathematical models of these dynamics and assessment of their veterinary, medical, agricultural, and ecological impacts. Arthropod data have been collected world-wide for over a century, but remain scattered and largely inaccessible. With the ever-present and growing threat of arthropod vectors of infectious diseases and pest species, there are enormous amounts of historical and ongoing surveillance. These data are currently reported in a wide variety of formats, typically lacking sufficient metadata to make reuse and re-analysis possible. We present the first minimum information standard for arthropod abundance. Developed with broad stakeholder collaboration, it balances sufficiency for reuse with the practicality of preparing the data for submission. It is designed to optimize data (re-)usability from the “FAIR,” (Findable, Accessible, Interoperable, and Reusable) principles of public data archiving (PDA). This standard will facilitate data unification across research initiatives and communities dedicated to surveillance for detection and control of vector-borne diseases and pests.

Principal Component Analysis (PCA) of dense single nucleotide polymorphism (SNP) data has wide-ranging applications in populations genetics, including detection of chromosomal inversions. SNPs associated with each PC can be identified through single-SNP association tests performed between SNP genotypes and PC coordinates; this approach has several advantages over thresholding loading factors or sparse PCA methods. Insect vector SNP data often have a high proportion of unknown (uncalled) genotypes, however, that cannot be reliably imputed and prevent the direct usage of association tests. Building on our previous work, we propose a novel method for adjusting the association tests to handle these unknown genotypes. We demonstrate the utility of the method through two applications: detecting chromosomal inversions and characterizing differentiation processed captured by PCA. When applied to SNP data from the 2L and 2R chromosome arms of 34 karyotyped Anopheles gambiae and Anopheles coluzzii mosquitoes, our method clearly identifies the 2La, 2Rb, 2Rc, 2Rj, and 2Ru inversions. Using our method to identify SNP associated with 2L-PC3, we observed one of the two insecticide-resistance variants in the Rdl gene; our results suggests that the PC is capturing differentiation driven by insecticide usage.

Beyond automated classification, supervised machine-learning models can be interpreted to find which features or combination of features distinguish sets of classes. Logistic Regression (LR) is an example of a model well-suited for human interpretation. Unfortunately, results from feature ranking with LR may not be reliable and reproducible for the same dataset. We demonstrate that stability and consistency can be achieved via ensembles (“LR ensembles”). As a specific example of the real-world utility of our associated framework, we apply LR ensembles to single-nucleotide polymorphisms (SNPs) associated with the recent speciation of the malaria vectors Anopheles gambiae and Anopheles coluzzii and compare with the more common univariate metric F ST .

Synonymous rare codons are considered to be sub-optimal for gene expression because they are translated more slowly than common codons. Yet surprisingly, many protein coding sequences include large clusters of synonymous rare codons. Rare codons at the 5’ terminus of coding sequences have been shown to increase translational efficiency. Although a general functional role for synonymous rare codons farther within coding sequences has not yet been established, several recent reports have identified rare-to-common synonymous codon substitutions that impair folding of the encoded protein. Here we test the hypothesis that although the usage frequencies of synonymous codons change from organism to organism, codon rarity will be conserved at specific positions in a set of homologous coding sequences, for example to tune translation rate without altering a protein sequence. Such conservation of rarity–rather than specific codon identity–could coordinate co-translational folding of the encoded protein. We demonstrate that many rare codon cluster positions are indeed conserved within homologous coding sequences across diverse eukaryotic, bacterial, and archaeal species, suggesting they result from positive selection and have a functional role. Most conserved rare codon clusters occur within rather than between conserved protein domains, challenging the view that their primary function is to facilitate co-translational folding after synthesis of an autonomous structural unit. Instead, many conserved rare codon clusters separate smaller protein structural motifs within structural domains. These smaller motifs typically fold faster than an entire domain, on a time scale more consistent with translation rate modulation by synonymous codon usage. While proteins with conserved rare codon clusters are structurally and functionally diverse, they are enriched in functions associated with organism growth and development, suggesting an important role for synonymous codon usage in organism physiology. The identification of conserved rare codon clusters advances our understanding of distinct, functional roles for otherwise synonymous codons and enables experimental testing of the impact of synonymous codon usage on the production of functional proteins., Author summary Proteins are long linear polymers that must fold into complex three-dimensional shapes in order to carry out their cellular functions. Every protein is synthesized by the ribosome, which decodes each trinucleotide codon in an mRNA coding sequence in order to select the amino acid residue that will occupy each position in the protein sequence. Most amino acids can be encoded by more than one codon, but these synonymous codons are not used with equal frequency. Rare codons are associated with generally slower rates for protein synthesis, and for this reason have traditionally been considered mildly deleterious for efficient protein production. However, because synonymous codon substitutions do not change the sequence of the encoded protein, the majority view is that they merely reflect genomic ‘background noise’. To the contrary, here we show that the positions of many synonymous rare codons are conserved in mRNA sequences that encode structurally similar proteins from a diverse range of organisms. These results suggest that rare codons have a functional role related to the production of functional proteins, potentially to regulate the rate of protein synthesis and the earliest steps of protein folding, while synthesis is still underway.

Biomphalaria snails are instrumental in transmission of the human blood fluke Schistosoma mansoni. With the World Health Organization's goal to eliminate schistosomiasis as a global health problem by 2025, there is now renewed emphasis on snail control. Here, we characterize the genome of Biomphalaria glabrata, a lophotrochozoan protostome, and provide timely and important information on snail biology. We describe aspects of phero-perception, stress responses, immune function and regulation of gene expression that support the persistence of B. glabrata in the field and may define this species as a suitable snail host for S. mansoni. We identify several potential targets for developing novel control measures aimed at reducing snail-mediated transmission of schistosomiasis., Biomphalaria glabrata is a fresh water snail that acts as a host for trematode Schistosoma mansoni that causes intestinal infection in human. This work describes the genome and transcriptome analyses from 12 different tissues of B glabrata, and identify genes for snail behavior and evolution.

Determining the genetic basis of fitness is central to understanding evolution and transmission of microbial pathogens. In human malaria parasites (Plasmodium falciparum), most experimental work on fitness has focused on asexual blood stage parasites, because this stage can be easily cultured, although the transmission of malaria requires both female Anopheles mosquitoes and vertebrate hosts. We explore a powerful approach to identify the genetic determinants of parasite fitness across both invertebrate and vertebrate life-cycle stages of P. falciparum. This combines experimental genetic crosses using humanized mice, with selective whole genome amplification and pooled sequencing to determine genome-wide allele frequencies and identify genomic regions under selection across multiple lifecycle stages. We applied this approach to genetic crosses between artemisinin resistant (ART-R, kelch13-C580Y) and ART-sensitive (ART-S, kelch13-WT) parasites, recently isolated from Southeast Asian patients. Two striking results emerge: we observed (i) a strong genome-wide skew (>80%) towards alleles from the ART-R parent in the mosquito stage, that dropped to ~50% in the blood stage as selfed ART-R parasites were selected against; and (ii) repeatable allele specific skews in blood stage parasites with particularly strong selection (selection coefficient (s) ≤ 0.18/asexual cycle) against alleles from the ART-R parent at loci on chromosome 12 containing MRP2 and chromosome 14 containing ARPS10. This approach robustly identifies selected loci and has strong potential for identifying parasite genes that interact with the mosquito vector or compensatory loci involved in drug resistance., Author summary Malaria parasites are transmitted through female mosquitoes where gamete fusion and meiosis occurs, and humans where parasites proliferate asexually. Our work represents the first systematic analysis of malaria (Plasmodium falciparum) parasite fitness cross the complete life cycle, exploiting our ability to conduct genetic crosses in humanized mice. We use parasites recently isolated from Southeast Asia, the epicenter of the evolution and spread of P. falciparum resistance to the front line antimalarial, artemisinin. Our results provide possible insights into additional loci involved in resistance-associated malaria evolution and spread. The approach described here can be directly applied to study multiple selectable traits in the human parasite P. falciparum, such as parasite compatibility with different mosquito vectors, resistance to multiple drugs, and tolerance of temperature increase (fever). We also anticipate that this approach will accelerate genetic studies in other recombining parasites and pathogens.

High-throughput sequencing is continuously generating large volumes of genotype data. Haplotype phasing can be an effective means to deal with large numbers of variants in analyses such as genome-wide association studies (GWAS), but the quality of such phasing is degraded by missing genotypes. Most existing imputation tools rely on reference genotype panels and a linear order of markers in the form of a physical or genetic map. A large number of genomics projects, however, do not have access to these resources. In this paper, we introduce HAPI-Gen, a Highly Accurate Phasing and Imputation tool for Genotype data that does not require reference genotype panels or the global order of markers, thereby filling an important need for improving phasing in less studied organisms. Other major advantages of HAPI-Gen include low runtime, reduced memory consumption, and easy parallelization. We test HAPI-Gen on the malaria parasite Plasmodium falciparum and three plant datasets of grape, apple, and maize. For varying data sizes and proportions of missing genotypes, HAPI-Gen consistently performs better than the leading tools Beagle, IM-PUTE2, and LinkImpute in terms of accuracy, runtime, and memory usage.

Y chromosomes control essential male functions in many species, including sex determination and fertility. However, because of obstacles posed by repeat-rich heterochromatin, knowledge of Y chromosome sequences is limited to a handful of model organisms, constraining our understanding of Y biology across the tree of life. Here, we leverage long single-molecule sequencing to determine the content and structure of the nonrecombining Y chromosome of the primary African malaria mosquito, Anopheles gambiae. We find that the An. gambiae Y consists almost entirely of a few massively amplified, tandemly arrayed repeats, some of which can recombine with similar repeats on the X chromosome. Sex-specific genome resequencing in a recent species radiation, the An. gambiae complex, revealed rapid sequence turnover within An. gambiae and among species. Exploiting 52 sex-specific An. gambiae RNA-Seq datasets representing all developmental stages, we identified a small repertoire of Y-linked genes that lack X gametologs and are not Y-linked in any other species except An. gambiae, with the notable exception of YG2, a candidate male-determining gene. YG2 is the only gene conserved and exclusive to the Y in all species examined, yet sequence similarity to YG2 is not detectable in the genome of a more distant mosquito relative, suggesting rapid evolution of Y chromosome genes in this highly dynamic genus of malaria vectors. The extensive characterization of the An. gambiae Y provides a long-awaited foundation for studying male mosquito biology, and will inform novel mosquito control strategies based on the manipulation of Y chromosomes.

The quantitative prediction of transcriptional activity of genes using promoter sequence is fundamental to the engineering of biological systems for industrial purposes and understanding the natural variation in gene expression. To catalyze the development of new algorithms for this purpose, the Dialogue on Reverse Engineering Assessment and Methods (DREAM) organized a community challenge seeking predictive models of promoter activity given normalized promoter activity data for 90 ribosomal protein promoters driving expression of a fluorescent reporter gene. By developing an unbiased modeling approach that performs an iterative search for predictive DNA sequence features using the frequencies of various k-mers, inferred DNA mechanical properties and spatial positions of promoter sequences, we achieved the best performer status in this challenge. The specific predictive features used in the model included the frequency of the nucleotide G, the length of polymeric tracts of T and TA, the frequencies of 6 distinct trinucleotides and 12 tetranucleotides, and the predicted protein deformability of the DNA sequence. Our method accurately predicted the activity of 20 natural variants of ribosomal protein promoters (Spearman correlation r = 0.73) as compared to 33 laboratory-mutated variants of the promoters (r = 0.57) in a test set that was hidden from participants. Notably, our model differed substantially from the rest in 2 main ways: i) it did not explicitly utilize transcription factor binding information implying that subtle DNA sequence features are highly associated with gene expression, and ii) it was entirely based on features extracted exclusively from the 100 bp region upstream from the translational start site demonstrating that this region encodes much of the overall promoter activity. The findings from this study have important implications for the engineering of predictable gene expression systems and the evolution of gene expression in naturally occurring biological systems.

VectorBase (http://www.vectorbase.org) is a NIAID-supported bioinformatics resource for invertebrate vectors of human pathogens. It hosts data for nine genomes: mosquitoes (three Anopheles gambiae genomes, Aedes aegypti and Culex quinquefasciatus), tick (Ixodes scapularis), body louse (Pediculus humanus), kissing bug (Rhodnius prolixus) and tsetse fly (Glossina morsitans). Hosted data range from genomic features and expression data to population genetics and ontologies. We describe improvements and integration of new data that expand our taxonomic coverage. Releases are bi-monthly and include the delivery of preliminary data for emerging genomes. Frequent updates of the genome browser provide VectorBase users with increasing options for visualizing their own high-throughput data. One major development is a new population biology resource for storing genomic variations, insecticide resistance data and their associated metadata. It takes advantage of improved ontologies and controlled vocabularies. Combined, these new features ensure timely release of multiple types of data in the public domain while helping overcome the bottlenecks of bioinformatics and annotation by engaging with our user community.

Endothelial cells play an essential role in regulating an immune response through promoting leukocyte adhesion and cell migration and production of cytokines such as TNFα. Regulation of endothelial cell immune function is tightly regulated and recent studies suggest that extracellular vesicles (EVs) are prominently involved in this process. However, the importance of EVs in regulating endothelial activation in the context of a bacterial infection is poorly understood. To begin addressing this knowledge gap we characterized the endothelial cell response to EVs released from Mycobacterium tuberculosis (Mtb) infected macrophages. Our result showed increased macrophage migration through the monolayer when endothelial cells were pretreated with EVs isolated from Mtb-infected macrophages. Transcriptome analysis showed a significant upregulation of genes involved in cell adhesion and the inflammatory process in endothelial cells treated with EVs. These results were validated by quantitative PCR and flow cytometry. Pathway analysis of these differentially expressed genes indicated that several immune response-related pathways were up-regulated. Endothelial cells were also treated with EVs isolated from the serum of Mtb-infected mice. Interestingly, EVs isolated 14 days but not 7 or 21 days post-infection showed a similar ability to induce endothelial cell activation suggesting a change in EV function during the course of an Mtb infection. Immunofluorescence microscopy result indicated that NF-κB and the Type 1 interferon pathways were involved in endothelial activation by EVs. In summary, our data suggest that EVs can activate endothelial cells and thus may play an important role in modulating host immune responses during an Mtb infection.

*Summary All above-ground plant organs are derived from shoot apical meristems (SAMs). Global analyses of gene expression were conducted on maize (Zea mays L.) SAMs to identify genes preferentially expressed in the SAM. The SAMs were collected from 14-day-old B73 seedlings via laser capture microdissection (LCM). The RNA samples extracted from LCM-collected SAMs and from seedlings were hybridized to microarrays spotted with 37 660 maize cDNAs. Approximately 30% (10 816) of these cDNAs were prepared as part of this study from manually dissected B73 maize apices. Over 5000 expressed sequence tags (ESTs) (about 13% of the total) were differentially expressed (P < 0.0001) between SAMs and seedlings. Of these, 2783 and 2248 ESTs were up- and down-regulated in the SAM, respectively. The expression in the SAM of several of the differentially expressed ESTs was validated via quantitative RT-PCR and/or in situ hybridization. The up-regulated ESTs included many regulatory genes including transcription factors, chromatin remodeling factors and components of the gene-silencing machinery, as well as about 900 genes with unknown functions. Surprisingly, transcripts that hybridized to 62 retrotransposon-related cDNAs were also substantially up-regulated in the SAM. Complementary DNAs derived from the LCM-collected SAMs were sequenced to identify additional genes that are expressed in the SAM. This generated around 550 000 ESTs (454-SAM ESTs) from two genotypes. Consistent with the microarray results, approximately 14% of the 454-SAM ESTs from B73 were retrotransposon-related. Possible roles of genes that are preferentially expressed in the SAM are discussed.

A massively parallel pyro-sequencing technology commercialized by 454 Life Sciences Corporation was used to sequence the transcriptomes of shoot apical meristems isolated from two inbred lines of maize using laser capture microdissection (LCM). A computational pipeline that uses the POLYBAYES polymorphism detection system was adapted for 454 ESTs and used to detect SNPs (single nucleotide polymorphisms) between the two inbred lines. Putative SNPs were computationally identified using 260 000 and 280 000 454 ESTs from the B73 and Mo17 inbred lines, respectively. Over 36 000 putative SNPs were detected within 9980 unique B73 genomic anchor sequences (MAGIs). Stringent post-processing reduced this number to > 7000 putative SNPs. Over 85% (94/110) of a sample of these putative SNPs were successfully validated by Sanger sequencing. Based on this validation rate, this pilot experiment conservatively identified > 4900 valid SNPs within > 2400 maize genes. These results demonstrate that 454-based transcriptome sequencing is an excellent method for the high-throughput acquisition of gene-associated SNPs.

Background The Phlebotomus papatasi salivary protein PpSP15 was shown to protect mice against Leishmania major, suggesting that incorporation of salivary molecules in multi-component vaccines may be a viable strategy for anti-Leishmania vaccines. Methods Here, we investigated PpSP15 predicted amino acid sequence variability and mRNA profile of P. papatasi field populations from the Middle East. In addition, predicted MHC class II T-cell epitopes were obtained and compared to areas of amino acid sequence variability within the secreted protein. Results The analysis of PpSP15 expression from field populations revealed significant intra- and interpopulation variation.. In spite of the variability detected for P. papatasi populations, common epitopes for MHC class II binding are still present and may potentially be used to boost the response against Le. major infections. Conclusions Conserved epitopes of PpSP15 could potentially be used in the development of a salivary gland antigen-based vaccine. Electronic supplementary material The online version of this article (doi:10.1186/s13071-015-0914-2) contains supplementary material, which is available to authorized users.

Rhodnius prolixus not only has served as a model organism for the study of insect physiology, but also is a major vector of Chagas disease, an illness that affects approximately seven million people worldwide. We sequenced the genome of R. prolixus, generated assembled sequences covering 95% of the genome (∼702 Mb), including 15,456 putative protein-coding genes, and completed comprehensive genomic analyses of this obligate blood-feeding insect. Although immunedeficiency (IMD)-mediated immune responses were observed, R. prolixus putatively lacks key components of the IMD pathway, suggesting a reorganization of the canonical immune signaling network. Although both Toll and IMD effectors controlled intestinal microbiota, neither affected Trypanosoma cruzi, the causal agent of Chagas disease, implying the existence of evasion or tolerance mechanisms. R. prolixus has experienced an extensive loss of selenoprotein genes, with its repertoire reduced to only two proteins, one of which is a selenocysteine-based glutathione peroxidase, the first found in insects. The genome contained actively transcribed, horizontally transferred genes from Wolbachia sp., which showed evidence of codon use evolution toward the insect use pattern. Comparative protein analyses revealed many lineage-specific expansions and putative gene absences in R. prolixus, including tandem expansions of genes related to chemoreception, feeding, and digestion that possibly contributed to the evolution of a blood-feeding lifestyle. The genome assembly and these associated analyses provide critical information on the physiology and evolution of this important vector species and should be instrumental for the development of innovative disease control methods., La lista completa de autores que integran el documento puede consultarse en el archivo, Este documento tiene una corrección (ver documento relacionado)., Centro Regional de Estudios Genómicos, Instituto de Investigaciones Bioquímicas de La Plata

Nature Communications 8: Article number: 15451 (2017); Published 16 May 2017; Updated 23 August 2017 The original version of this Article contained an error in the spelling of the author Leon Di Stefano, which was incorrectly given as Leon di Stephano. This has now been corrected in both the PDF andHTML versions of the Article.

Motivation: RNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression and transcriptional structure. The methods, tools and technologies used to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material and computational infrastructure can minimize the overhead required of life science researchers. Results: RNA-Rocket is a free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides and a user interface designed to enable both novice and experienced users of RNA-Seq data. Availability and implementation: RNA-Rocket is available at rnaseq.pathogenportal.org. Source code for this project can be found at github.com/cidvbi/PathogenPortal. Contact: anwarren@vt.edu Supplementary information: Supplementary materials are available at Bioinformatics online.

High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium’s minimal information (MIxS) and NCBI’s BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant.

Background: Anopheles stephensi is the key vector of malaria throughout the Indian subcontinent and Middle East and an emerging model for molecular and genetic studies of mosquito-parasite interactions. The type form of the species is responsible for the majority of urban malaria transmission across its range. Results: Here, we report the genome sequence and annotation of the Indian strain of the type form of An. stephensi. The 221 Mb genome assembly represents more than 92% of the entire genome and was produced using a combination of 454, Illumina, and PacBio sequencing. Physical mapping assigned 62% of the genome onto chromosomes, enabling chromosome-based analysis. Comparisons between An. stephensi and An. gambiae reveal that the rate of gene order reshuffling on the X chromosome was three times higher than that on the autosomes. An. stephensi has more heterochromatin in pericentric regions but less repetitive DNA in chromosome arms than An. gambiae. We also identify a number of Y-chromosome contigs and BACs. Interspersed repeats constitute 7.1% of the assembled genome while LTR retrotransposons alone comprise more than 49% of the Y contigs. RNA-seq analyses provide new insights into mosquito innate immunity, development, and sexual dimorphism. Conclusions: The genome analysis described in this manuscript provides a resource and platform for fundamental and translational research into a major urban malaria vector. Chromosome-based investigations provide unique perspectives on Anopheles chromosome evolution. RNA-seq analysis and studies of immunity genes offer new insights into mosquito biology and mosquito-parasite interactions., National Science Foundation (U.S.) (Grant CNS-0960081)

Background - The process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly. Results - In Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies. Conclusions - Many current genome assemblers produced useful assemblies, containing a significant representation of their genes, regulatory sequences, and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another., Comment: Additional files available at http://korflab.ucdavis.edu/Datasets/Assemblathon/Assemblathon2/Additional_files/ Major changes 1. Accessions for the 3 read data sets have now been included 2. New file: spreadsheet containing details of all Study, Sample, Run, & Experiment identifiers 3. Made miscellaneous changes to address reviewers comments. DOIs added to GigaDB datasets

We report the imminent completion of a set of reference genome assemblies for 16 species of Anopheles mosquitoes. In addition to providing a generally useful resource for comparative genomic analyses, these genome sequences will greatly facilitate exploration of the capacity exhibited by some Anopheline mosquito species to serve as vectors for malaria parasites. A community analysis project will commence soon to perform a thorough comparative genomic investigation of these newly sequenced genomes. Completion of this project via the use of short next-generation sequence reads required innovation in both the bioinformatic and laboratory realms, and the resulting knowledge gained could prove useful for genome sequencing projects targeting other unconventional genomes., National Human Genome Research Institute (U.S.)

A-Maize-ing Maize is one of our oldest and most important crops, having been domesticated approximately 9000 years ago in central Mexico. Schnable et al. (p. 1112 ; see the cover) present the results of sequencing the B73 inbred maize line. The findings elucidate how maize became diploid after an ancestral doubling of its chromosomes and reveals transposable element movement and activity and recombination. Vielle-Calzada et al. (p. 1078 ) have sequenced the Palomero Toluqueño ( Palomero ) landrace, a highland popcorn from Mexico, which, when compared to the B73 line, reveals multiple loci impacted by domestication. Swanson-Wagner et al. (p. 1118 ) exploit possession of the genome to analyze expression differences occurring between lines. The identification of single nucleotide polymorphisms and copy number variations among lines was used by Gore et al. (p. 1115 ) to generate a Haplotype map of maize. While chromosomal diversity in maize is high, it is likely that recombination is the major force affecting the levels of heterozygosity in maize. The availability of the maize genome will help to guide future agricultural and biofuel applications (see the Perspective by Feuillet and Eversole ).

Background Most animal species exhibit sexually dimorphic behaviors, many of which are linked to reproduction. A number of these behaviors, including blood feeding in female mosquitoes, contribute to the global spread of vector-borne illnesses. However, knowledge concerning the genetic basis of sexually dimorphic traits is limited in any organism, including mosquitoes, especially with respect to differences in the developing nervous system. Methods Custom microarrays were used to examine global differences in female vs. male gene expression in the developing pupal head of the dengue vector mosquito, Aedes aegypti. The spatial expression patterns of a subset of differentially expressed transcripts were examined in the developing female vs. male pupal brain through in situ hybridization experiments. Small interfering RNA (siRNA)-mediated knockdown studies were used to assess the putative role of Doublesex, a terminal component of the sex determination pathway, in the regulation of sex-specific gene expression observed in the developing pupal brain. Results Transcripts (2,527), many of which were linked to proteolysis, the proteasome, metabolism, catabolic, and biosynthetic processes, ion transport, cell growth, and proliferation, were found to be differentially expressed in A. aegypti female vs. male pupal heads. Analysis of the spatial expression patterns for a subset of dimorphically expressed genes in the pupal brain validated the data set and also facilitated the identification of brain regions with dimorphic gene expression. In many cases, dimorphic gene expression localized to the optic lobe. Sex-specific differences in gene expression were also detected in the antennal lobe and mushroom body. siRNA-mediated gene targeting experiments demonstrated that Doublesex, a transcription factor with consensus binding sites located adjacent to many dimorphically expressed transcripts that function in neural development, is required for regulation of sex-specific gene expression in the developing A. aegypti brain. Conclusions These studies revealed sex-specific gene expression profiles in the developing A. aegypti pupal head and identified Doublesex as a key regulator of sexually dimorphic gene expression during mosquito neural development.

Background Knowledge of the origins, distribution, and inheritance of variation in the malaria parasite (Plasmodium falciparum) genome is crucial for understanding its evolution; however the 81% (A+T) genome poses challenges to high-throughput sequencing technologies. We explore the viability of the Roche 454 Genome Sequencer FLX (GS FLX) high throughput sequencing technology for both whole genome sequencing and fine-resolution characterization of genetic exchange in malaria parasites. Results We present a scheme to survey recombination in the haploid stage genomes of two sibling parasite clones, using whole genome pyrosequencing that includes a sliding window approach to predict recombination breakpoints. Whole genome shotgun (WGS) sequencing generated approximately 2 million reads, with an average read length of approximately 300 bp. De novo assembly using a combination of WGS and 3 kb paired end libraries resulted in contigs ≤ 34 kb. More than 8,000 of the 24,599 SNP markers identified between parents were genotyped in the progeny, resulting in a marker density of approximately 1 marker/3.3 kb and allowing for the detection of previously unrecognized crossovers (COs) and many non crossover (NCO) gene conversions throughout the genome. Conclusions By sequencing the 23 Mb genomes of two haploid progeny clones derived from a genetic cross at more than 30× coverage, we captured high resolution information on COs, NCOs and genetic variation within the progeny genomes. This study is the first to resequence progeny clones to examine fine structure of COs and NCOs in malaria parasites.