An EST resource for tilapia based on 17 normalized libraries and assembly of 116,899 sequence tags

Background

Large collections of expressed sequence tags (ESTs) are a fundamental resource for analysis of gene expression and annotation of genome sequences. We generated 116,899 ESTs from 17 normalized and two non-normalized cDNA libraries representing 16 tissues from tilapia, a cichlid fish widely used in aquaculture and biological research.

Results

The ESTs were assembled into 20,190 contigs and 36,028 singletons for a total of 56,218 unique sequences and a total assembled length of 35,168,415 bp. Over the whole project, a unique sequence was discovered for every 2.079 sequence reads. 17,722 (31.5%) of these unique sequences had significant BLAST hits (e-value < 10^-10) to the UniProt database.

Conclusion

Normalization of the cDNA pools with double-stranded nuclease allowed us to efficiently sequence a large collection of ESTs. These sequences are an important resource for studies of gene expression, comparative mapping and annotation of the forthcoming tilapia genome sequence.

     

Single molecule sequencing-guided scaffolding and correction of draft assemblies

Background

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.

Results

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. 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.

Conclusions

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. In addition, our reassembling process can also serve as a competitive scaffolder relative to well-established assembly benchmarks.

     

CLAME: a new alignment-based binning algorithm allows the genomic description of a novel Xanthomonadaceae from the Colombian Andes

Background

Hot spring bacteria have unique biological adaptations to survive the extreme conditions of these environments; these bacteria produce thermostable enzymes that can be used in biotechnological and industrial applications. However, sequencing these bacteria is complex, since it is not possible to culture them. As an alternative, genome shotgun sequencing of whole microbial communities can be used. The problem is that the classification of sequences within a metagenomic dataset is very challenging particularly when they include unknown microorganisms since they lack genomic reference. We failed to recover a bacterium genome from a hot spring metagenome using the available software tools, so we develop a new tool that allowed us to recover most of this genome.

Results

We present a proteobacteria draft genome reconstructed from a Colombian’s Andes hot spring metagenome. The genome seems to be from a new lineage within the family Rhodanobacteraceae of the class Gammaproteobacteria, closely related to the genus Dokdonella. We were able to generate this genome thanks to CLAME. CLAME, from Spanish “CLAsificador MEtagenomico”, is a tool to group reads in bins. We show that most reads from each bin belong to a single chromosome. CLAME is very effective recovering most of the reads belonging to the predominant species within a metagenome.

Conclusions

We developed a tool that can be used to extract genomes (or parts of them) from a complex metagenome.

     

An improved statistical model for taxonomic assignment of metagenomics

Background

With the advances in the next-generation sequencing technologies, researchers can now rapidly examine the composition of samples from humans and their surroundings. To enhance the accuracy of taxonomy assignments in metagenomic samples, we developed a method that allows multiple mismatch probabilities from different genomes.

Results

We extended the algorithm of taxonomic assignment of metagenomic sequence reads (TAMER) by developing an improved method that can set a different mismatch probability for each genome rather than imposing a single parameter for all genomes, thereby obtaining a greater degree of accuracy. This method, which we call TADIP (Taxonomic Assignment of metagenomics based on DIfferent Probabilities), was comprehensively tested in simulated and real datasets. The results support that TADIP improved the performance of TAMER especially in large sample size datasets with high complexity.

Conclusions

TADIP was developed as a statistical model to improve the estimate accuracy of taxonomy assignments. Based on its varying mismatch probability setting and correlated variance matrix setting, its performance was enhanced for high complexity samples when compared with TAMER.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Analysis of chicken anemia virus genome: evidence of intersubtype recombination

Background

Chicken anemia virus (CAV) is the causative agent of chicken infectious anemia. CAV putative intergenotypic recombinants have been reported previously. This fact is based on the previous classification of CAV sequences into three genotypes. However, it is unknown whether intersubtype recombination occurs between the recently reported four CAV genotypes and five subtypes of genome sequences.

Results

Phylogenetic analysis, together with a variety of computational recombination detection algorithms, was used to investigate CAV approximately full genomes. Statistically significant evidence of intersubtype recombination was detected in the parent-like and two putative CAV recombinant sequences. This event was shown to occur between CAV subgroup A1 and A2 sequences in the phylogenetic trees.

Conclusions

We revealed that intersubtype recombination in CAV genome sequences played a role in generating genetic diversity within the natural population of CAV.

     

Coordinate systems for supergenomes

Background

Genome sequences and genome annotation data have become available at ever increasing rates in response to the rapid progress in sequencing technologies. As a consequence the demand for methods supporting comparative, evolutionary analysis is also growing. In particular, efficient tools to visualize-omics data simultaneously for multiple species are sorely lacking. A first and crucial step in this direction is the construction of a common coordinate system. Since genomes not only differ by rearrangements but also by large insertions, deletions, and duplications, the use of a single reference genome is insufficient, in particular when the number of species becomes large.

Results

The computational problem then becomes to determine an order and orientations of optimal local alignments that are as co-linear as possible with all the genome sequences. We first review the most prominent approaches to model the problem formally and then proceed to showing that it can be phrased as a particular variant of the Betweenness Problem. It is NP hard in general. As exact solutions are beyond reach for the problem sizes of practical interest, we introduce a collection of heuristic simplifiers to resolve ordering conflicts.

Conclusion

Benchmarks on real-life data ranging from bacterial to fly genomes demonstrate the feasibility of computing good common coordinate systems.

     

MetaBinG2: a fast and accurate metagenomic sequence classification system for samples with many unknown organisms

Background

Many methods have been developed for metagenomic sequence classification, and most of them depend heavily on genome sequences of the known organisms. A large portion of sequencing sequences may be classified as unknown, which greatly impairs our understanding of the whole sample.

Result

Here we present MetaBinG2, a fast method for metagenomic sequence classification, especially for samples with a large number of unknown organisms. MetaBinG2 is based on sequence composition, and uses GPUs to accelerate its speed. A million 100 bp Illumina sequences can be classified in about 1 min on a computer with one GPU card. We evaluated MetaBinG2 by comparing it to multiple popular existing methods. We then applied MetaBinG2 to the dataset of MetaSUB Inter-City Challenge provided by CAMDA data analysis contest and compared community composition structures for environmental samples from different public places across cities.

Conclusion

Compared to existing methods, MetaBinG2 is fast and accurate, especially for those samples with significant proportions of unknown organisms.

Reviewers

This article was reviewed by Drs. Eran Elhaik, Nicolas Rascovan, and Serghei Mangul.

     

Next-generation sequencing facilitates detection of the classic E13-A20 EML4-ALK fusion in an ALK-FISH/IHC inconclusive biopsy of a stage IV lung cancer patient: a case report

Background

Inhibition of the oncogenic fusion-gene EML4-ALK is a current first-line approach for patients with stage IV non-small cell lung cancer. While FISH was established as the gold standard for identifying these patients, there is accumulating evidence that other methods of detection, i.e., immunohistochemistry and next-generation sequencing (NGS), exist that may be equally successful. However, the concordance of these methods is under investigation.

Case presentation

Adding to the current literature, we here report a 56 year old female never-smoker with stage IV lung adenocarcinoma whose biopsy was IHC and FISH inconclusive but positive in NGS. Retroactive profiling of the resection specimen corroborated fusion reads obtained by NGS, FISH-positivity and showed weak ALK-positivity by IHC. Consequently, we diagnosed the case as ALK-positive rendering the patient eligible to crizotinib treatment.

Conclusions

With IHC on biopsy material only, this case would have been overlooked withholding effective therapy.

     

Metagenomic next-generation sequencing as a diagnostic tool for toxoplasmic encephalitis

Background

More than 100 different pathogens can cause encephalitis. Testing of all the neurological pathogens by conventional methods can be difficult. Metagenomic next-generation sequencing (NGS) could identify the infectious agents in a target-independent manner. The role of this novel method in clinical diagnostic microbiology still needs to be evaluated. In present study, we used metagenomic NGS to search for an infectious etiology in a human immunodeficiency virus (HIV)-infected patient with lethally diffuse brain lesions. Sequences mapping to Toxoplasma gondii were unexpectedly detected.

Case presentation

A 31-year-old HIV-infected patient presented to hospital in a critical ill condition with a Glasgow coma scale score of 3. Brain magnetic resonance imaging showed diffuse brain abnormalities with contrast enhancement. Metagenomic NGS was performed on DNA extract from 300 μL patient’s cerebrospinal fluid (CSF) with the BGISEQ-50 platform. The sequencing detection identified 65,357 sequence reads uniquely aligned to the Toxoplasma gondii genome. Presence of Toxoplasma gondii genome in CSF was further verified by Toxoplasma gondii-specific polymerase chain reaction and Sanger sequencing. Altogether, those results confirmed the diagnosis of toxoplasmic encephalitis.

Conclusions

This study suggests that metagenomic NGS may be a useful diagnostic tool for toxoplasmic encephalitis. As metagenomic NGS is able to identify all pathogens in a single run, it may be a promising strategy to explore the clinical causative pathogens in central nervous system infections with atypical features.

     

Deep learning for DNase I hypersensitive sites identification

Background

The DNase I hypersensitive sites (DHSs) are associated with the cis-regulatory DNA elements. An efficient method of identifying DHSs can enhance the understanding on the accessibility of chromatin. Despite a multitude of resources available on line including experimental datasets and computational tools, the complex language of DHSs remains incompletely understood.

Methods

Here, we address this challenge using an approach based on a state-of-the-art machine learning method. We present a novel convolutional neural network (CNN) which combined Inception like networks with a gating mechanism for the response of multiple patterns and longterm association in DNA sequences to predict multi-scale DHSs in Arabidopsis, rice and Homo sapiens.

Results

Our method obtains 0.961 area under curve (AUC) on Arabidopsis, 0.969 AUC on rice and 0.918 AUC on Homo sapiens.

Conclusions

Our method provides an efficient and accurate way to identify multi-scale DHSs sequences by deep learning.

     

Effectively processing medical term queries on the UMLS Metathesaurus by layered dynamic programming

Background

Mapping medical terms to standardized UMLS concepts is a basic step for leveraging biomedical texts in data management and analysis. However, available methods and tools have major limitations in handling queries over the UMLS Metathesaurus that contain inaccurate query terms, which frequently appear in real world applications.

Methods

To provide a practical solution for this task, we propose a layered dynamic programming mapping (LDPMap) approach, which can efficiently handle these queries. LDPMap uses indexing and two layers of dynamic programming techniques to efficiently map a biomedical term to a UMLS concept.

Results

Our empirical study shows that LDPMap achieves much faster query speeds than LCS. In comparison to the UMLS Metathesaurus Browser and MetaMap, LDPMap is much more effective in querying the UMLS Metathesaurus for inaccurately spelled medical terms, long medical terms, and medical terms with special characters.

Conclusions

These results demonstrate that LDPMap is an efficient and effective method for mapping medical terms to the UMLS Metathesaurus.

     

Jabba: hybrid error correction for long sequencing reads

Background

Third generation sequencing platforms produce longer reads with higher error rates than second generation technologies. While the improved read length can provide useful information for downstream analysis, underlying algorithms are challenged by the high error rate. Error correction methods in which accurate short reads are used to correct noisy long reads appear to be attractive to generate high-quality long reads. Methods that align short reads to long reads do not optimally use the information contained in the second generation data, and suffer from large runtimes. Recently, a new hybrid error correcting method has been proposed, where the second generation data is first assembled into a de Bruijn graph, on which the long reads are then aligned.

Results

In this context we present Jabba, a hybrid method to correct long third generation reads by mapping them on a corrected de Bruijn graph that was constructed from second generation data. Unique to our method is the use of a pseudo alignment approach with a seed-and-extend methodology, using maximal exact matches (MEMs) as seeds. In addition to benchmark results, certain theoretical results concerning the possibilities and limitations of the use of MEMs in the context of third generation reads are presented.

Conclusion

Jabba produces highly reliable corrected reads: almost all corrected reads align to the reference, and these alignments have a very high identity. Many of the aligned reads are error-free. Additionally, Jabba corrects reads using a very low amount of CPU time. From this we conclude that pseudo alignment with MEMs is a fast and reliable method to map long highly erroneous sequences on a de Bruijn graph.

     

The role of laterally transferred genes in adaptive evolution

Background

Bacterial genomes develop new mechanisms to tide them over the imposing conditions they encounter during the course of their evolution. Acquisition of new genes by lateral gene transfer may be one of the dominant ways of adaptation in bacterial genome evolution. Lateral gene transfer provides the bacterial genome with a new set of genes that help it to explore and adapt to new ecological niches.

Methods

A maximum likelihood analysis was done on the five sequenced corynebacterial genomes to model the rates of gene insertions/deletions at various depths of the phylogeny.

Results

The study shows that most of the laterally acquired genes are transient and the inferred rates of gene movement are higher on the external branches of the phylogeny and decrease as the phylogenetic depth increases. The newly acquired genes are under relaxed selection and evolve faster than their older counterparts. Analysis of some of the functionally characterised LGTs in each species has indicated that they may have a possible adaptive role.

Conclusion

The five Corynebacterial genomes sequenced to date have evolved by acquiring between 8 – 14% of their genomes by LGT and some of these genes may have a role in adaptation.

     

Metastatic tumor cells – genotypes and phenotypes

Background

Metastasis is the primary cause of mortality in cancer patients. Therefore, elucidating the genetics and epigenetics of metastatic tumor cells and the mechanisms by which tumor cells acquire metastatic properties constitute significant challenges in cancer research.

Objective

To summarize the current understandings of the specific genotype and phenotype of the metastatic tumor cells.

Method and Result

In-depth genetic analysis of tumor cells, especially with advances in the next-generation sequencing, have revealed insights of the genotypes of metastatic tumor cells. Also, studies have shown that the cancer stem cell (CSC) and epithelial to mesenchymal transition (EMT) phenotypes are associated with the metastatic cascade.

Conclusion

In this review, we will discuss recent advances in the field by focusing on the genomic instability and phenotypic dynamics of metastatic tumor cells.