Unmapped Sequences Research Articles

Localizing unmapped sequences with families to validate the Telomere-to-Telomere assembly and identify new hotspots for genetic diversity.

Although it is ubiquitous in genomics, the current human reference genome (GRCh38) is incomplete: It is missing large sections of heterochromatic sequence, and as a singular, linear reference genome, it does not represent the full spectrum of human genetic diversity. To characterize gaps in GRCh38 and human genetic diversity, we developed an algorithm for sequence location approximation using nuclear families (ASLAN) to identify the region of origin of reads that do not align to GRCh38. Using unmapped reads and variant calls from whole-genome sequences (WGSs), ASLAN uses a maximum likelihood model to identify the most likely region of the genome that a subsequence belongs to given the distribution of the subsequence in the unmapped reads and phasings of families. Validating ASLAN on synthetic data and on reads from the alternative haplotypes in the decoy genome, ASLAN localizes >90% of 100-bp sequences with >92% accuracy and ∼1 Mb of resolution. We then ran ASLAN on 100-mers from unmapped reads from WGS from more than 700 families, and compared ASLAN localizations to alignment of the 100-mers to the recently released T2T-CHM13 assembly. We found that many unmapped reads in GRCh38 originate from telomeres and centromeres that are gaps in GRCh38. ASLAN localizations are in high concordance with T2T-CHM13 alignments, except in the centromeres of the acrocentric chromosomes. Comparing ASLAN localizations and T2T-CHM13 alignments, we identified sequences missing from T2T-CHM13 or sequences with high divergence from their aligned region in T2T-CHM13, highlighting new hotspots for genetic diversity.

Presence of periodontal pathogenic bacteria in blood of patients with coronary artery disease

It has been hypothesised that oral bacteria can migrate, through the blood, from the mouth to the arterial plaques, thus exacerbating atherosclerosis. This study compared bacteria present in the peripheral blood of individuals with and without coronary artery disease (CAD). RNA sequences obtained from blood were downloaded from GEO (GSE58150). Eight patients with coronary artery calcification (CAC) scoring > 500 and eight healthy individuals were analysed. After conducting quality control, the sequences were aligned to the hg38 reference genome using Hisat2. Bacterial taxa were analysed by inputting the unmapped sequences into Kraken. Ecological indices were calculated using Vegan. The package DESeq2 was used to compare the counts of bacteria per standard rank between groups. A total of 51 species were found only in patients with CAD and 41 were exclusively present in healthy individuals. The counts of one phylum, one class, three orders, two families and one genus were significantly different between the analysed groups (p < 0.00032, FDR < 10%), including the orders Cardiobacteriales, Corynebacteriales and Fusobacteriales. Twenty-three bacterial species belonging to the subgingival plaque bacterial complexes were also identified in the blood of individuals from both the groups; Fusobacterium nucleatum was significantly less frequent in patients with CAD (p = 0.0012, FDR = 4.8%). Furthermore, the frequency of another 11 bacteria differed significantly among patients with CAD than that among healthy individuals (p < 0.0030, FDR < 10%). These bacteria have not been previously reported in patients with atherosclerosis and periodontitis. The presence of members of the subgingival plaque bacterial complexes in the blood of patients with CAC supports the hypothesis that the periodontopathogens can be disseminated through the blood flow to other body parts where they may enhance inflammatory processes that can lead to the development or exacerbation of atherosclerosis.

Transcriptomic and Metabolomic Analyses Provide Insights Into an Aberrant Tissue of Tea Plant (Camellia sinensis).

Tea plant (Camellia sinensis (L.) O. Kuntze) is one of the most important economic crops with multiple mutants. Recently, we found a special tea germplasm that has an aberrant tissue on its branches. To figure out whether this aberrant tissue is associated with floral bud (FB) or dormant bud (DB), we performed tissue section, transcriptome sequencing, and metabolomic analysis of these tissues. Longitudinal sections indicated the aberrant tissue internal structure was more like a special bud (SB), but was similar to that of DB. Transcriptome data analysis showed that the number of heterozygous and homozygous SNPs was significantly different in the aberrant tissue compared with FB and DB. Further, by aligning the unmapped sequences of the aberrant tissue to the Non-Redundant Protein Sequences (NR) database, we observed that 36.13% of unmapped sequences were insect sequences, which suggested that the aberrant tissue might be a variation of dormant bud tissue influenced by the interaction of tea plants and insects or pathogens. Metabolomic analysis showed that the differentially expressed metabolites (DEMs) between the aberrant tissue and DB were significantly enriched in the metabolic pathways of biosynthesis of plant hormones and biosynthesis of phenylpropanoids. Subsequently, we analyzed the differentially expressed genes (DEGs) in the above mentioned two tissues, and the results indicated that photosynthetic capacity in the aberrant tissue was reduced, whereas the ethylene, salicylic acid and jasmonic acid signaling pathways were activated. We speculated that exogenous infection induced programmed cell death (PCD) and increased the lignin content in dormant buds of tea plants, leading to the formation of this aberrant tissue. This study advanced our understanding of the interaction between plants and insects or pathogens, providing important clues about biotic stress factors and key genes that lead to mutations and formation of the aberrant tissue.

Genome- wide structural and functional variant discovery of rice landraces using genotyping by sequencing.

Rice landraces are vital genetic resources for agronomic and quality traits but the undeniable collection of Kerala landraces remains poorly delineated. To effectively conserve, manage, and use these resources, understanding the genomic structure of germplasm is essential. Genotyping by sequencing (GBS) enables identification of an immense number of single nucleotide polymorphism (SNP) and insertion deletion (InDel) from 96 rice germplasm. In the present study, a total of 16.9 × 107 reads were generated, and among that 16.3 × 107 reads were mapped to the indica reference genome. Exploring GBS data unfolded a wide genomic variations including 82,59,639 SNPs and 1,07,140 Indels. Both neighbor-joining tree and principal coordinate analysis with InDel markers revealed the selected germplasm in this study as highly diverse in structure. We assembled unmapped reads which were further employed for gene ontology analysis. These unmapped sequences that are generally expelled from subsequent studies of GBS data analysis may exist as an unexplored resort for several novel significant biological findings. The discovery of SNPs from the haplotyping results of GS3 and GIF1 genes provided insight into marker- assisted selection based on grain size and yield and can be utilized for rice yield improvement. To our knowledge, this is the first report on structural variation analysis using the GBS platform in rice landraces collected from Kerala. Genomic information from this study endows with valuable resources for perceptive rice landrace structure and can also facilitate sequencing-based molecular breeding.

A novel microRNA boosts hyper-β-oxidation of fatty acids in liver by impeding CEP350-mediated sequestration of PPARα and thus restricts chronic hepatitis C

ABSTRACT Imbalance in lipid metabolism induces steatosis in liver during Chronic hepatitis C (CHC). Contribution of microRNAs in regulating lipid homoeostasis and liver disease progression is well established using small RNA-transcriptome data. Owing to the complexity in the development of liver diseases, the existence and functional importance of yet undiscovered regulatory miRNAs in disease pathogenesis was explored in this study using the unmapped sequences of the transcriptome data of HCV-HCC liver tissues following miRDeep2.pl pipeline. MicroRNA-c12 derived from the first intron of LGR5 of chromosome 12 was identified as one of the miRNA like sequences retrieved in this analysis that showed human specific origin. Northern blot hybridization has proved its existence in the hepatic cell line. Enrichment of premiR-c12 in dicer-deficient cells and miR-c12 in Ago2-RISC complex clearly suggested that it followed canonical miRNA biogenesis pathway and accomplished its regulatory function. Expression of this miRNA was quite low in CHC tissues than normal liver implying HCV-proteins might be regulating its biogenesis. Promoter scanning and ChIP analysis further revealed that under expression of p53 and hyper-methylation of STAT3 binding site upon HCV infection restricted its expression in CHC tissues. Centrosomal protein 350 (CEP350), which sequestered PPARα, was identified as one of the targets of miR-c12 using Miranda and validated by luciferase assay/western blot analysis. Furthermore, reduced triglyceride accumulation and enhanced PPARα mediated transcription of β-oxidation genes upon restoration of miR-c12 in liver cells suggested its role in lipid catabolism. Thus this study is reporting miR-c12 for the first time and showed its’ protective role during chronic HCV infection.

DeePaC: predicting pathogenic potential of novel DNA with reverse-complement neural networks.

We expect novel pathogens to arise due to their fast-paced evolution, and new species to be discovered thanks to advances in DNA sequencing and metagenomics. Moreover, recent developments in synthetic biology raise concerns that some strains of bacteria could be modified for malicious purposes. Traditional approaches to open-view pathogen detection depend on databases of known organisms, which limits their performance on unknown, unrecognized and unmapped sequences. In contrast, machine learning methods can infer pathogenic phenotypes from single NGS reads, even though the biological context is unavailable. We present DeePaC, a Deep Learning Approach to Pathogenicity Classification. It includes a flexible framework allowing easy evaluation of neural architectures with reverse-complement parameter sharing. We show that convolutional neural networks and LSTMs outperform the state-of-the-art based on both sequence homology and machine learning. Combining a deep learning approach with integrating the predictions for both mates in a read pair results in cutting the error rate almost in half in comparison to the previous state-of-the-art. The code and the models are available at: https://gitlab.com/rki_bioinformatics/DeePaC. Supplementary data are available at Bioinformatics online.

P53 and STAT3 Dependent Expression of a Novel microRNA Restricts Hepatitis C Virus Infection Through Hyper-β-Oxidation of Fatty Acids by Impeding Cytosolic CAP350

Background: The underlying complex molecular mechanism of Hepatitis C virus (HCV) mediated liver disease progression is still unresolved. Next generation sequencing of small RNAs provides genome-wide data about regulatory microRNAs. Here, we have identified undiscovered low abundant regulatory miRNAs and investigated the role of a novel human liver specific miRNAs in HCV mediated liver disease development. Methods: To discover unannotated miRNAs, unmapped sequences from small RNA transcriptome profiling of HCV infected and un-infected liver tissues were subjected to miRDeep2.pl pipeline. Targets predicted using MiRanda and Ingenuity pathway analysis (IPA). Northern-blot, Dicer knock down (K/D), Ago2-RNA immunoprecipitation (RIP), Stem-loop Real-time PCR (SLRTPCR), immunoblot (IB) analysis, luciferase assay, Chromatin immunoprecipitation (ChIP) etc. were used as required. Findings: Among seven predicted novel miRNAs, miR-c12 was found human liver specific miRNA. Dicer K/D and RIP assays showed that miR-c12 followed canonical miRNA biogenesis pathways. Its low expression in chronic HCV infected (CHC) tissues than normal liver indicated its protective role against HCV infection. Furthermore, upon HCV infection downregulation of p53 expression and hypermethylation of STAT3 binding site in the promoter of miR-c12 restricted its expression in CHC. IPA analysis revealed miR-c12 controlled mostly the fatty acid metabolism pathway. Reduced triglyceride accumulation and enhanced PPARα mediated fatty-acid catabolism upon miR-c12 retention in cells by targeting CAP350, a suppressor of PPARα, confirmed its role in lipid metabolism pathways. Interpretations: We discovered a previously unidentified low abundant human-liver specific miRNA having role in lipid homeostasis maintenance. Hence, miR-c12 together with anti-virals might be more effective therapeutic in restricting HCV infection. Funding Statement: Department of Biotechnology (DBT), Government of India [BT/PR11971/MED/29/890/2014]. Declaration of Interests: The authors declare no conflict of interest. Ethics Approval Statement: Ethics committee of the Institute of Post Graduate Medical Education and Research (IPGME&R), Kolkata, India and Indraprastha Apollo Hospital, New Delhi had approved the study. Blood and tissues were collected from patients who were willing to participate in the study with prior written consent.

From trash to treasure: detecting unexpected contamination in unmapped NGS data

BackgroundNext Generation Sequencing (NGS) experiments produce millions of short sequences that, mapped to a reference genome, provide biological insights at genomic, transcriptomic and epigenomic level. Typically the amount of reads that correctly maps to the reference genome ranges between 70% and 90%, leaving in some cases a consistent fraction of unmapped sequences. This ’misalignment’ can be ascribed to low quality bases or sequence differences between the sample reads and the reference genome. Investigating the source of the unmapped reads is definitely important to better assess the quality of the whole experiment and to check for possible downstream or upstream ’contamination’ from exogenous nucleic acids.ResultsHere we propose DecontaMiner, a tool to unravel the presence of contaminating sequences among the unmapped reads. It uses a subtraction approach to identify bacteria, fungi and viruses genome contamination. DecontaMiner generates several output files to track all the processed reads, and to provide a complete report of their characteristics. The good quality matches on microorganism genomes are counted and compared among samples. DecontaMiner builds an offline HTML page containing summary statistics and plots. The latter are obtained using the state-of-the-art D3 javascript libraries. DecontaMiner has been mainly used to detect contamination in human RNA-Seq data. The software is freely available at http://www-labgtp.na.icar.cnr.it/decontaminer.ConclusionsDecontaMiner is a tool designed and developed to investigate the presence of contaminating sequences in unmapped NGS data. It can suggest the presence of contaminating organisms in sequenced samples, that might derive either from laboratory contamination or from their biological source, and in both cases can be considered as worthy of further investigation and experimental validation. The novelty of DecontaMiner is mainly represented by its easy integration with the standard procedures of NGS data analysis, while providing a complete, reliable, and automatic pipeline.

Comparative whole genome re-sequencing analysis in upland New Rice for Africa: insights into the breeding history and respective genome compositions

BackgroundIncreasing rice demand is one of the consequences of the steadily improving socio-economic status of the African countries. New Rice for Africa (NERICA), which are interspecific hybrids between Asian and African rice varieties, are one of successful breeding products utilizing biodiversity across the two different rice crop species. Upland NERICA varieties (NU) exhibit agronomic traits of value for the harsh eco-geography, including shorter duration, higher yield and stress tolerance, compared to local African varieties. However, the molecular basis of the traits in NU varieties is largely unknown.ResultsWhole genome re-sequencing was performed of four NU lines (3, 4, 5, and 7) and for the parental Oryza sativa WAB56–104 and Oryza glaberrima CG14. The k-mer analysis predicted large genomes for the four NU lines, most likely inherited from WAB56–104. Approximately 3.1, 0.10, and 0.40 million single nucleotide polymorphisms, multi nucleotide polymorphisms, and short insertions/deletions were mined between the parental lines, respectively. Integrated analysis with another four NU lines (1, 2, 8, and 9) showed that the ratios of the donor CG14 allelic sites in the NU lines ranged from 1.3 to 9.8%. High resolution graphical genotype indicated genome-level similarities and common genetic events during the breeding process: five xyloglucan fucosyltransferase from O. glaberrima were introgressed in common. Segregation of genic segments revealed potential causal genes for some agronomic traits including grain shattering, awnness, susceptibility to bacterial leaf bright, and salt tolerance. Analysis of unmapped sequences against the reference cultivar Nipponbare indicated existence of unique genes for pathogen and abiotic stress resistance in the NU varieties.ConclusionsThe results provide understanding of NU genomes for rice improvement for Africa reinforcing local capacity for food security and insights into molecular events in breeding of interspecific hybrid crops.

Unmapped sequencing reads identify additional candidate genes linked to magnetoreception in rainbow trout

A recent study identified candidate genes linked to magnetoreception in rainbow trout (Oncorhynchus mykiss) by sequencing transcriptomes from the brains of fish exposed to a magnetic pulse. However, the discovery of these candidate genes was limited to sequences that aligned to the reference genome. The unaligned, or unmapped, sequences may yet contain valuable information resulting from regions missing, misassembled, or divergent from the reference. Using the available sequencing data from the trout brain transcriptomes, we assembled >27 million unmapped sequences (5.8% of total sequences) into 45,142 contigs and identified 12 differentially expressed contigs as a result of exposure to a pulsed magnetic field. These contigs encoded a putative superoxide dismutase – a protein necessary to prevent oxidative damage – and collagen alpha-1 type II – a structural protein important for the development and integrity of the retina. These genes were consistent with the previous study suggesting an effect of the magnetic pulse on oxidative consequences of free iron and on non-visual encephalic photoreceptors. Our results demonstrate the utility of assembling unmapped sequencing reads in studies of gene expression and identify additional candidate genes associated with a magnetic sense in trout.

Abstract 3298: Distinct microbiome populations within breast cancer microenvironments

Abstract INTRODUCTION: The tumor microenvironment consists of a complicated interplay between a heterogeneous mixture of tumor cells and the surrounding tissue and there is a burgeoning interest in the role of the tissue microbiota within this microenvironment. Our group has investigated the breast tumor microbiome using the unaligned (non-human) reads from 796 RNASequencing data obtained from The Cancer Genome Atlas (TCGA) repository of Breast Cancer. METHODS: Unmapped sequences for 720 TCGA tumor samples and 76 paired normal samples were analyzed with Kraken v0.10.5 using the RefSeq 16S and standard genomes. To minimize false discoveries Kraken results were filtered to species that have bacterial genomic and 16S read support. Cluster analysis of the T-distributed Stochastic Neighbor Embedding (tsne) was performed and consensus voting of 26 maximum scoring metrics identified 3 distinct clusters. Differential abundance analysis was performed with the edgeR package. Covariate association analysis was performed for tumor clinical characteristics, as well as sample heterogeneity characteristics. RESULTS: There were three microbiome clusters we identified using TCGA breast samples. The average silhouette width of the third cluster was deemed statistically insignificant (0.071), suggesting further stratification of this cluster is necessary. The remaining two TCGA clusters (467) shared an average silhouette width of 0.39, using Bray's dissimilarity index. Differential abundance analysis of the two clusters after Bonferroni correction identified 450 significant species. The biomes were represented by 63 triple negative, 93 HER2+, 258 Luminal, and 50 tumor adjacent normals. Concordant cluster assignment was observed in 93.7 +/- 7.3% of the normal-tumor pairings, averaged across clinical subtypes. We observed clear delineation of biome populations at the order taxonomic level, which was not associated with the clinical subtype or the tumor/tumor adjacent pairings. We found enrichment of Burkholderiales in the first biome and enrichment of Bacillales and Lactobacillales within the second biome. The second biome appears to be deplete of representatives from the Asian population (p value 0.005) and survival associations were observed to be significantly reduced for HER2 patients associated with Biome 1 (p value 0.025). Geneset enrichment analysis of the expression signatures indicated drug metabolism and chemical carcinogenesis pathways to be associated with biome 2. CONCLUSIONS: In our study, we observed two significantly different microbiomes among TCGA breast cancer samples that were not associated with the clinical subtypes. Current efforts include validating these biomes, using 16S sequencing on matching fresh frozen paraffin embedded samples. Additionally, we are evaluating the influence of the biomes in independent adjuvant and neo-adjuvant studies with next generation sequencing data. Citation Format: Kevin J. Thompson, Jason Sinnwell, Xiaojia Tang, James N. Ingle, Matthew P. Goetz, Krishna R. Kalari. Distinct microbiome populations within breast cancer microenvironments. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3298.

Anchored pseudo-de novo assembly of human genomes identifies extensive sequence variation from unmapped sequence reads.

The human genome reference (HGR) completion marked the genomics era beginning, yet despite its utility universal application is limited by the small number of individuals used in its development. This is highlighted by the presence of high-quality sequence reads failing to map within the HGR. Sequences failing to map generally represent 2-5% of total reads, which may harbor regions that would enhance our understanding of population variation, evolution, and disease. Alternatively, complete de novo assemblies can be created, but these effectively ignore the groundwork of the HGR. In an effort to find a middle ground, we developed a bioinformatic pipeline that maps paired-end reads to the HGR as separate single reads, exports unmappable reads, de novo assembles these reads per individual and then combines assemblies into a secondary reference assembly used for comparative analysis. Using 45 diverse 1000 Genomes Project individuals, we identified 351,361 contigs covering 195.5Mb of sequence unincorporated in GRCh38. 30,879 contigs are represented in multiple individuals with ~40% showing high sequence complexity. Genomic coordinates were generated for 99.9%, with 52.5% exhibiting high-quality mapping scores. Comparative genomic analyses with archaic humans and primates revealed significant sequence alignments and comparisons with model organism RefSeq gene datasetsidentified novel human genes. If incorporated, these sequences will expand the HGR, but more importantly our data highlight that with this method low coverage (~10-20×) next-generation sequencing can still be used to identify novel unmapped sequences to explore biological functions contributing to human phenotypic variation, disease and functionality for personal genomic medicine.

Identification of Known and Novel Recurrent Viral Sequences in Data from Multiple Patients and Multiple Cancers.

Virus discovery from high throughput sequencing data often follows a bottom-up approach where taxonomic annotation takes place prior to association to disease. Albeit effective in some cases, the approach fails to detect novel pathogens and remote variants not present in reference databases. We have developed a species independent pipeline that utilises sequence clustering for the identification of nucleotide sequences that co-occur across multiple sequencing data instances. We applied the workflow to 686 sequencing libraries from 252 cancer samples of different cancer and tissue types, 32 non-template controls, and 24 test samples. Recurrent sequences were statistically associated to biological, methodological or technical features with the aim to identify novel pathogens or plausible contaminants that may associate to a particular kit or method. We provide examples of identified inhabitants of the healthy tissue flora as well as experimental contaminants. Unmapped sequences that co-occur with high statistical significance potentially represent the unknown sequence space where novel pathogens can be identified.

Whole-genome re-sequencing of non-model organisms: lessons from unmapped reads.

Unmapped reads are often discarded from the analysis of whole-genome re-sequencing, but new biological information and insights can be uncovered through their analysis. In this paper, we investigate unmapped reads from the re-sequencing data of 33 pea aphid genomes from individuals specialized on different host plants. The unmapped reads for each individual were retrieved following mapping to the Acyrthosiphon pisum reference genome and its mitochondrial and symbiont genomes. These sets of unmapped reads were then cross-compared, revealing that a significant number of these unmapped sequences were conserved across individuals. Interestingly, sequences were most commonly shared between individuals adapted to the same host plant, suggesting that these sequences may contribute to the divergence between host plant specialized biotypes. Analysis of the contigs obtained from assembling the unmapped reads pooled by biotype allowed us to recover some divergent genomic regions previously excluded from analysis and to discover putative novel sequences of A. pisum and its symbionts. In conclusion, this study emphasizes the interest of the unmapped component of re-sequencing data sets and the potential loss of important information. We here propose strategies to aid the capture and interpretation of this information.

Construction of Pseudomolecule Sequences of the aus Rice Cultivar Kasalath for Comparative Genomics of Asian Cultivated Rice

Having a deep genetic structure evolved during its domestication and adaptation, the Asian cultivated rice (Oryza sativa) displays considerable physiological and morphological variations. Here, we describe deep whole-genome sequencing of the aus rice cultivar Kasalath by using the advanced next-generation sequencing (NGS) technologies to gain a better understanding of the sequence and structural changes among highly differentiated cultivars. The de novo assembled Kasalath sequences represented 91.1% (330.55 Mb) of the genome and contained 35 139 expressed loci annotated by RNA-Seq analysis. We detected 2 787 250 single-nucleotide polymorphisms (SNPs) and 7393 large insertion/deletion (indel) sites (>100 bp) between Kasalath and Nipponbare, and 2 216 251 SNPs and 3780 large indels between Kasalath and 93-11. Extensive comparison of the gene contents among these cultivars revealed similar rates of gene gain and loss. We detected at least 7.39 Mb of inserted sequences and 40.75 Mb of unmapped sequences in the Kasalath genome in comparison with the Nipponbare reference genome. Mapping of the publicly available NGS short reads from 50 rice accessions proved the necessity and the value of using the Kasalath whole-genome sequence as an additional reference to capture the sequence polymorphisms that cannot be discovered by using the Nipponbare sequence alone.

High-throughput Physical Mapping of Chromosomes using Automated &lt;em&gt;in situ&lt;/em&gt; Hybridization

Projects to obtain whole-genome sequences for 10,000 vertebrate species1 and for 5,000 insect and related arthropod species2 are expected to take place over the next 5 years. For example, the sequencing of the genomes for 15 malaria mosquitospecies is currently being done using an Illumina platform3,4. This Anopheles species cluster includes both vectors and non-vectors of malaria. When the genome assemblies become available, researchers will have the unique opportunity to perform comparative analysis for inferring evolutionary changes relevant to vector ability. However, it has proven difficult to use next-generation sequencing reads to generate high-quality de novo genome assemblies5. Moreover, the existing genome assemblies for Anopheles gambiae, although obtained using the Sanger method, are gapped or fragmented4,6.Success of comparative genomic analyses will be limited if researchers deal with numerous sequencing contigs, rather than with chromosome-based genome assemblies. Fragmented, unmapped sequences create problems for genomic analyses because: (i) unidentified gaps cause incorrect or incomplete annotation of genomic sequences; (ii) unmapped sequences lead to confusion between paralogous genes and genes from different haplotypes; and (iii) the lack of chromosome assignment and orientation of the sequencing contigs does not allow for reconstructing rearrangement phylogeny and studying chromosome evolution. Developing high-resolution physical maps for species with newly sequenced genomes is a timely and cost-effective investment that will facilitate genome annotation, evolutionary analysis, and re-sequencing of individual genomes from natural populations7,8.Here, we present innovative approaches to chromosome preparation, fluorescent in situ hybridization (FISH), and imaging that facilitate rapid development of physical maps. Using An. gambiae as an example, we demonstrate that the development of physical chromosome maps can potentially improve genome assemblies and, thus, the quality of genomic analyses. First, we use a high-pressure method to prepare polytene chromosome spreads. This method, originally developed for Drosophila9, allows the user to visualize more details on chromosomes than the regular squashing technique10. Second, a fully automated, front-end system for FISH is used for high-throughput physical genome mapping. The automated slide staining system runs multiple assays simultaneously and dramatically reduces hands-on time11. Third, an automatic fluorescent imaging system, which includes a motorized slide stage, automatically scans and photographs labeled chromosomes after FISH12. This system is especially useful for identifying and visualizing multiple chromosomal plates on the same slide. In addition, the scanning process captures a more uniform FISH result. Overall, the automated high-throughput physical mapping protocol is more efficient than a standard manual protocol.

High-throughput Physical Mapping of Chromosomes using Automated &lt;em&gt;in situ&lt;/em&gt; Hybridization

Projects to obtain whole-genome sequences for 10,000 vertebrate species1 and for 5,000 insect and related arthropod species2 are expected to take place over the next 5 years. For example, the sequencing of the genomes for 15 malaria mosquitospecies is currently being done using an Illumina platform3,4. This Anopheles species cluster includes both vectors and non-vectors of malaria. When the genome assemblies become available, researchers will have the unique opportunity to perform comparative analysis for inferring evolutionary changes relevant to vector ability. However, it has proven difficult to use next-generation sequencing reads to generate high-quality de novo genome assemblies5. Moreover, the existing genome assemblies for Anopheles gambiae, although obtained using the Sanger method, are gapped or fragmented4,6. Success of comparative genomic analyses will be limited if researchers deal with numerous sequencing contigs, rather than with chromosome-based genome assemblies. Fragmented, unmapped sequences create problems for genomic analyses because: (i) unidentified gaps cause incorrect or incomplete annotation of genomic sequences; (ii) unmapped sequences lead to confusion between paralogous genes and genes from different haplotypes; and (iii) the lack of chromosome assignment and orientation of the sequencing contigs does not allow for reconstructing rearrangement phylogeny and studying chromosome evolution. Developing high-resolution physical maps for species with newly sequenced genomes is a timely and cost-effective investment that will facilitate genome annotation, evolutionary analysis, and re-sequencing of individual genomes from natural populations7,8. Here, we present innovative approaches to chromosome preparation, fluorescent in situ hybridization (FISH), and imaging that facilitate rapid development of physical maps. Using An. gambiae as an example, we demonstrate that the development of physical chromosome maps can potentially improve genome assemblies and, thus, the quality of genomic analyses. First, we use a high-pressure method to prepare polytene chromosome spreads. This method, originally developed for Drosophila9, allows the user to visualize more details on chromosomes than the regular squashing technique10. Second, a fully automated, front-end system for FISH is used for high-throughput physical genome mapping. The automated slide staining system runs multiple assays simultaneously and dramatically reduces hands-on time11. Third, an automatic fluorescent imaging system, which includes a motorized slide stage, automatically scans and photographs labeled chromosomes after FISH12. This system is especially useful for identifying and visualizing multiple chromosomal plates on the same slide. In addition, the scanning process captures a more uniform FISH result. Overall, the automated high-throughput physical mapping protocol is more efficient than a standard manual protocol.

Mapping the pericentric heterochromatin by comparative genomic hybridization analysis and chromosome deletions in Drosophila melanogaster

Heterochromatin represents a significant portion of eukaryotic genomes and has essential structural and regulatory functions. Its molecular organization is largely unknown due to difficulties in sequencing through and assembling repetitive sequences enriched in the heterochromatin. Here we developed a novel strategy using chromosomal rearrangements and embryonic phenotypes to position unmapped Drosophila melanogaster heterochromatic sequence to specific chromosomal regions. By excluding sequences that can be mapped to the assembled euchromatic arms, we identified sequences that are specific to heterochromatin and used them to design heterochromatin specific probes (“H-probes”) for microarray. By comparative genomic hybridization (CGH) analyses of embryos deficient for each chromosome or chromosome arm, we were able to map most of our H-probes to specific chromosome arms. We also positioned sequences mapped to the second and X chromosomes to finer intervals by analyzing smaller deletions with breakpoints in heterochromatin. Using this approach, we were able to map >40% (13.9 Mb) of the previously unmapped heterochromatin sequences assembled by the whole-genome sequencing effort on arm U and arm Uextra to specific locations. We also identified and mapped 110 kb of novel heterochromatic sequences. Subsequent analyses revealed that sequences located within different heterochromatic regions have distinct properties, such as sequence composition, degree of repetitiveness, and level of underreplication in polytenized tissues. Surprisingly, although heterochromatin is generally considered to be transcriptionally silent, we detected region-specific temporal patterns of transcription in heterochromatin during oogenesis and early embryonic development. Our study provides a useful approach to elucidate the molecular organization and function of heterochromatin and reveals region-specific variation of heterochromatin.

Structural Rules and Complex Regulatory Circuitry Constrain Expression of a Notch- and EGFR-Regulated Eye Enhancer

Enhancers integrate spatiotemporal information to generate precise patterns of gene expression. How complex is the regulatory logic of a typical developmental enhancer, and how important is its internal organization? Here, we examine in detail the structure and function of sparkling, a Notch- and EGFR/MAPK-regulated, cone cell-specific enhancer of the Drosophila Pax2 gene, in vivo. In addition to its 12 previously identified protein-binding sites, sparkling is densely populated with previously unmapped regulatory sequences, which interact in complex ways to control gene expression. One segment is essential for activation at a distance, yet dispensable for other activation functions and for cell type patterning. Unexpectedly, rearranging sparkling's regulatory sites converts it into a robust photoreceptor-specific enhancer. Our results show that a single combination of regulatory inputs can encode multiple outputs, and suggest that the enhancer's organization determines the correct expression pattern by facilitating certain short-range regulatory interactions at the expense of others.

Update of the Anopheles gambiae PEST genome assembly

An update on the Anopheles gambiae PEST genome assembly places about 33% of previously unmapped sequences on the chromosomes.