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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.

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.

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.

Over ten thousand genomes ofEscherichia coliare now available, and this number will continue to grow for this and other important microbial species. The first approach often used to better understand microbes is phylogenetic group analysis followed by pan-genome analysis of highly related genomes. Here, we combine sequence-based features with unsupervised clustering on up to 2,231E. coligenomes and a total of 1,367Clostridium difficilegenomes. We show that Non-negative Matrix Factorization (NMF) can identify “mixed”/cryptic genomes, and can better determine inter-related genome groups and their distinguishing features (genes) relative to prior methods.

Concurrent advances in high-throughput sequencing and assembly have led to the completion of many complex genomes. Even so, these assemblies require substantial computational resources. In this dissertation, we present a massively parallel approach that scales to thousands of processors without duplicating the biological expertise present in conventional assembly software. Additional bioinformatics techniques were required to accurately assemble the maize genome including novel repeat detection, and the resulting framework has been strongly supported by maize experimental data. More recently, this framework has been generalized for fruit fly, sorghum, soybean and environmental sequence assemblies. Questions in plant genome analysis were also addressed. For example, we have discovered an estimated 350 "orphan" maize genes and have shown that approximately 1% of all maize genes were recently duplicated, many of which into at least two functional copies. LCM-454 sequencing is introduced and analyses that indicate this approach can discover rare, potentially tissue-specific transcripts and thousands of SNPs will be presented. This dissertation combines high performance computing, computational biology and high-throughput sequencing for our ongoing work on the maize genome project. We conclude by describing how these contributions can be useful for any species, including non-model organisms that are unlikely to be fully sequenced.

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.

Assembly of large genomes from tens of millions of short genomic fragments is computationally demanding requiring hundreds of gigabytes of memory and tens of thousands of CPU hours. The advent of high throughput sequencing technologies, new gene-enrichment sequencing strategies, and collective sequencing of environmental samples further exacerbate this situation. In this paper, we present the first massively parallel genome assembly framework. The unique features of our approach include space-efficient and on-demand algorithms that consume only linear space, and strategies to reduce the number of expensive pairwise sequence alignments while maintaining assembly quality. Developed as part of the ongoing efforts in maize genome sequencing, we applied our assembly framework to genomic data containing a mixture of gene enriched and random shotgun sequences. We report the partitioning of more than 1.6 million fragments of over 1.25 billion nucleotides total size into genomic islands in under 2h on 1024 processors of an IBM BlueGene/L supercomputer. We also demonstrate the effectiveness of the proposed approach for traditional whole genome shotgun sequencing and assembly of environmental sequences.

*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.

Ancestral reconstruction can be useful in many facets of genetic analysis. It allows for a look into the (potential) past, and can provide a clearer idea of species divergance. Unfortunately, ancestral construction is not as easy with swiftly changing genomes as input. Confounding factors such as horizontal gene transfer and gene loss limit available information under current heuristics that mitigate the computational difficulty of finding an exact solution. Here, we address a specific limitation of these heursitics, namely the restriction that genes be present in all leaf genomes. We show that we can greatly improve the number of genes placed in an ancestral genome by accepting genes not universal to the whole data set but universal to a given subtree. We implement this approach by modifying the popular ancestral reconstruction program PATHGROUPS and test it on fruit fly and mosquito data with multiple available genomes.

Artemisinins are the corner stone of anti-malarial drugs1. Emergence and spread of resistance to them2–4 raises risk of wiping out recent gains achieved in reducing world-wide malaria burden and threatens future malaria control and elimination on a global level. Genome wide association studies (GWAS) have revealed parasite genetic loci associated with artemisinin resistance5–10. However, there is no consensus on biochemical targets of artemisinin. Whether and how these targets interact with genes identified by GWAS, remains unknown. Here we provide biochemical and cellular evidence that artemisinins are potent inhibitors of Plasmodium falciparum phosphatidylinositol-3-kinase (PfPI3K), revealing an unexpected mechanism of action. In resistant clinical strains, increased PfPI3K was associated with the C580Y mutation in P. falciparum Kelch13 (PfKelch13), a primary marker of artemisinin resistance. Polyubiquitination of PfPI3K and its binding to PfKelch13 were reduced by PfKelch13 mutation, which limited proteolysis of PfPI3K and thus increased levels of the kinase as well as its lipid product phosphatidylinositol 3-phosphate (PI3P). We find PI3P levels to be predictive of artemisinin resistance in both clinical and engineered laboratory parasites as well as across non-isogenic strains. Elevated PI3P induced artemisinin resistance in absence of PfKelch13 mutations, but remained responsive to regulation by PfKelch13. Evidence is presented for PI3P-dependent signaling, where transgenic expression of an additional kinase confers resistance. Together these data present PI3P as the key mediator of artemisinin resistance and the sole PfPI3K as an important target for malaria elimination.

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

Five ab initio programs (FGENESH, GeneMark.hmm, GENSCAN, GlimmerR and Grail) were evaluated for their accuracy in predicting maize genes. Two of these programs, GeneMark.hmm and GENSCAN had been trained for maize; FGENESH had been trained for monocots (including maize), and the others had been trained for rice or Arabidopsis. Initial evaluations were conducted using eight maize genes (gl8a, pdc2, pdc3, rf2c, rf2d, rf2e1, rth1, and rth3) of which the sequences were not released to the public prior to conducting this evaluation. The significant advantage of this data set for this evaluation is that these genes could not have been included in the training sets of the prediction programs. FGENESH yielded the most accurate and GeneMark.hmm the second most accurate predictions. The five programs were used in conjunction with RT-PCR to identify and establish the structures of two new genes in the a1-sh2 interval of the maize genome. FGENESH, GeneMark.hmm and GENSCAN were tested on a larger data set consisting of maize assembled genomic islands (MAGIs) that had been aligned to ESTs. FGENESH, GeneMark.hmm and GENSCAN correctly predicted gene models in 773, 625, and 371 MAGIs, respectively, out of the 1353 MAGIs that comprise data set 2.

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

Analysis of gene expression data has emerged as an important approach to discover active pathways related to biological phenotypes. Previous pathway analysis methods use all genes in a pathway for linking it to a particular phenotype. Using only a subset of informative genes, however, could better classify samples. Here, we propose a two-stage machine learning approach for pathway analysis. During the first stage, informative genes that can represent a pathway are selected using feature selection methods. These “representative genes” are mostly associated with the phenotype of interest. In the second stage, pathways are ranked based on their “representative genes” using classification methods. We applied our two-stage approach on three gene expression datasets. The results indicate our method does outperform methods that consider every gene in a pathway.

Background Complexity and noise in expression quantitative trait loci (eQTL) studies make it difficult to distinguish potential regulatory relationships among the many interactions. The predominant method of identifying eQTLs finds associations that are significant at a genome-wide level. The vast number of statistical tests carried out on these data make false negatives very likely. Corrections for multiple testing error render genome-wide eQTL techniques unable to detect modest regulatory effects. We propose an alternative method to identify eQTLs that builds on traditional approaches. In contrast to genome-wide techniques, our method determines the significance of an association between an expression trait and a locus with respect to the set of all associations to the expression trait. The use of this specific information facilitates identification of expression traits that have an expression profile that is characterized by a single exceptional association to a locus. Our approach identifies expression traits that have exceptional associations regardless of the genome-wide significance of those associations. This property facilitates the identification of possible false negatives for genome-wide significance. Further, our approach has the property of prioritizing expression traits that are affected by few strong associations. Expression traits identified by this method may warrant additional study because their expression level may be affected by targeting genes near a single locus. Results We demonstrate our method by identifying eQTL hotspots in Plasmodium falciparum (malaria) and Saccharomyces cerevisiae (yeast). We demonstrate the prioritization of traits with few strong genetic effects through Gene Ontology (GO) analysis of Yeast. Our results are strongly consistent with results gathered using genome-wide methods and identify additional hotspots and eQTLs. Conclusions New eQTLs and hotspots found with this method may represent regions of the genome or biological processes that are controlled through few relatively strong genetic interactions. These points of interest warrant experimental investigation.

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 ).

As an ancient segmental tetraploid, the maize (Zea mays L.) genome contains large numbers of paralogs that are expected to have diverged by a minimum of 10% over time. Nearly identical paralogs (NIPs) are defined as paralogous genes that exhibit ≥98% identity. Sequence analyses of the “gene space” of the maize inbred line B73 genome, coupled with wet lab validation, have revealed that, conservatively, at least ∼1% of maize genes have a NIP, a rate substantially higher than that in Arabidopsis. In most instances, both members of maize NIP pairs are expressed and are therefore at least potentially functional. Of evolutionary significance, members of many NIP families also exhibit differential expression. The finding that some families of maize NIPs are closely linked genetically while others are genetically unlinked is consistent with multiple modes of origin. NIPs provide a mechanism for the maize genome to circumvent the inherent limitation that diploid genomes can carry at most two “alleles” per “locus.” As such, NIPs may have played important roles during the evolution and domestication of maize and may contribute to the success of long-term selection experiments in this important crop species.

Recent sequencing efforts have targeted the gene-rich regions of the maize ( Zea mays L.) genome. We report the release of an improved assembly of maize assembled genomic islands (MAGIs). The 114,173 resulting contigs have been subjected to computational and physical quality assessments. Comparisons to the sequences of maize bacterial artificial chromosomes suggest that at least 97% (160 of 165) of MAGIs are correctly assembled. Because the rates at which junction-testing PCR primers for genomic survey sequences (90-92%) amplify genomic DNA are not significantly different from those of control primers (≈91%), we conclude that a very high percentage of genic MAGIs accurately reflect the structure of the maize genome. EST alignments, ab initio gene prediction, and sequence similarity searches of the MAGIs are available at the Iowa State University MAGI web site. This assembly contains 46,688 ab initio predicted genes. The expression of almost half (628 of 1,369) of a sample of the predicted genes that lack expression evidence was validated by RT-PCR. Our analyses suggest that the maize genome contains between ≈33,000 and ≈54,000 expressed genes. Approximately 5% (32 of 628) of the maize transcripts discovered do not have detectable paralogs among maize ESTs or detectable homologs from other species in the GenBank NR nucleotide/protein database. Analyses therefore suggest that this assembly of the maize genome contains approximately 350 previously uncharacterized expressed genes. We hypothesize that these “orphans” evolved quickly during maize evolution and/or domestication.

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.

Recently, the utility of trait-based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. We proposed a machine learning framework to quantitatively link the genomic features with functional traits. Genes from bacteria genomes belonging to different functional traits were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. Extensive experimental results demonstrated that functional trait related genes can be detected using our method. Further, the method has the potential to provide novel biological insights.

Background Despite substantial progress in mosquito genomic and genetic research, few cis-regulatory elements (CREs), DNA sequences that control gene expression, have been identified in mosquitoes or other non-model insects. Formaldehyde-assisted isolation of regulatory elements paired with DNA sequencing, FAIRE-seq, is emerging as a powerful new high-throughput tool for global CRE discovery. FAIRE results in the preferential recovery of open chromatin DNA fragments that are not bound by nucleosomes, an evolutionarily conserved indicator of regulatory activity, which are then sequenced. Despite the power of the approach, FAIRE-seq has not yet been applied to the study of non-model insects. In this investigation, we utilized FAIRE-seq to profile open chromatin and identify likely regulatory elements throughout the genome of the human disease vector mosquito Aedes aegypti. We then assessed genetic variation in the regulatory elements of dengue virus susceptible (Moyo-S) and refractory (Moyo-R) mosquito strains. Results Analysis of sequence data obtained through next generation sequencing of FAIRE DNA isolated from A. aegypti embryos revealed >121,000 FAIRE peaks (FPs), many of which clustered in the 1 kb 5’ upstream flanking regions of genes known to be expressed at this stage. As expected, known transcription factor consensus binding sites were enriched in the FPs, and of these FoxA1, Hunchback, Gfi, Klf4, MYB/ph3 and Sox9 are most predominant. All of the elements tested in vivo were confirmed to drive gene expression in transgenic Drosophila reporter assays. Of the >13,000 single nucleotide polymorphisms (SNPs) recently identified in dengue virus-susceptible and refractory mosquito strains, 3365 were found to map to FPs. Conclusion FAIRE-seq analysis of open chromatin in A. aegypti permitted genome-wide discovery of CREs. The results of this investigation indicate that FAIRE-seq is a powerful tool for identification of regulatory DNA in the genomes of non-model organisms, including human disease vector mosquitoes. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2468-x) contains supplementary material, which is available to authorized users.

Background Alternative arrangements of chromosome 2 inversions in Anopheles gambiae are important sources of population structure, and are associated with adaptation to environmental heterogeneity. The forces responsible for their origin and maintenance are incompletely understood. Molecular characterization of inversion breakpoints provides insight into how they arose, and provides the basis for development of molecular karyotyping methods useful in future studies. Methods Sequence comparison of regions near the cytological breakpoints of 2Rb allowed the molecular delineation of breakpoint boundaries. Comparisons were made between the standard 2R+b arrangement in the An. gambiae PEST reference genome and the inverted 2Rb arrangements in the An. gambiae M and S genome assemblies. Sequence differences between alternative 2Rb arrangements were exploited in the design of a PCR diagnostic assay, which was evaluated against the known chromosomal banding pattern of laboratory colonies and field-collected samples from Mali and Cameroon. Results The breakpoints of the 7.55 Mb 2Rb inversion are flanked by extensive runs of the same short (72 bp) tandemly organized sequence, which was likely responsible for chromosomal breakage and rearrangement. Application of the molecular diagnostic assay suggested that 2Rb has a single common origin in An. gambiae and its sibling species, Anopheles arabiensis, and also that the standard arrangement (2R+b) may have arisen twice through breakpoint reuse. The molecular diagnostic was reliable when applied to laboratory colonies, but its accuracy was lower in natural populations. Conclusions The complex repetitive sequence flanking the 2Rb breakpoint region may be prone to structural and sequence-level instability. The 2Rb molecular diagnostic has immediate application in studies based on laboratory colonies, but its usefulness in natural populations awaits development of complementary molecular tools.