Next-generation sequencing and large genome assemblies

Ameliorating the effects of multiple stresses on agronomic traits in crops: modern biotechnological and omics approaches

While global climate change poses a significant environmental threat to agriculture, the increasing population is another big challenge to food security. To address this, developing crop varieties with increased productivity and tolerance to biotic and abiotic stresses is crucial. Breeders must identify traits to ensure higher and consistent yields under inconsistent environmental challenges, possess resilience against emerging biotic and abiotic stresses and satisfy customer demands for safer and more nutritious meals. With the advent of omics-based technologies, molecular tools are now integrated with breeding to understand the molecular genetics of genotype-based traits and develop better climate-smart crops. The rapid development of omics technologies offers an opportunity to generate novel datasets for crop species. Identifying genes and pathways responsible for significant agronomic traits has been made possible by integrating omics data with genetic and phenotypic information. This paper discusses the importance and use of omics-based strategies, including genomics, transcriptomics, proteomics and phenomics, for agricultural and horticultural crop improvement, which aligns with developing better adaptability in these crop species to the changing climate conditions.

Next-Generation Sequencing Technology: Current Trends and Advancements

The advent of next-generation sequencing (NGS) has brought about a paradigm shift in genomics research, offering unparalleled capabilities for analyzing DNA and RNA molecules in a high-throughput and cost-effective manner. This transformative technology has swiftly propelled genomics advancements across diverse domains. NGS allows for the rapid sequencing of millions of DNA fragments simultaneously, providing comprehensive insights into genome structure, genetic variations, gene expression profiles, and epigenetic modifications. The versatility of NGS platforms has expanded the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Moreover, NGS has enabled the development of targeted therapies, precision medicine approaches, and improved diagnostic methods. This review provides an insightful overview of the current trends and recent advancements in NGS technology, highlighting its potential impact on diverse areas of genomic research. Moreover, the review delves into the challenges encountered and future directions of NGS technology, including endeavors to enhance the accuracy and sensitivity of sequencing data, the development of novel algorithms for data analysis, and the pursuit of more efficient, scalable, and cost-effective solutions that lie ahead.

Efficient Two-Stage Analysis for Complex Trait Association with Arbitrary Depth Sequencing Data

Sequencing-based genetic association analysis is typically performed by first generating genotype calls from sequence data and then performing association tests on the called genotypes. Standard approaches require accurate genotype calling (GC), which can be achieved either with high sequencing depth (typically available in a small number of individuals) or via computationally intensive multi-sample linkage disequilibrium (LD)-aware methods. We propose a computationally efficient two-stage combination approach for association analysis, in which single-nucleotide polymorphisms (SNPs) are screened in the first stage via a rapid maximum likelihood (ML)-based method on sequence data directly (without first calling genotypes), and then the selected SNPs are evaluated in the second stage by performing association tests on genotypes from multi-sample LD-aware calling. Extensive simulation- and real data-based studies show that the proposed two-stage approaches can save 80% of the computational costs and still obtain more than 90% of the power of the classical method to genotype all markers at various depths d≥2.

Utility of targeted next generation sequencing for inborn errors of immunity at a tertiary care centre in North India

Inborn errors of immunity (IEI) are a heterogeneous group of monogenic disorders that include primary immunodeficiency's and other disorders affecting different aspects of the immune system. Next-Generation Sequencing (NGS) is an essential tool to diagnose IEI. We report our 3-year experience in setting up facilities for NGS for diagnosis of IEI in Chandigarh, North India. We used a targeted, customized gene panel of 44 genes known to result in IEI. Variant analysis was done using Ion Reporter software. The in-house NGS has enabled us to offer genetic diagnoses to patients with IEI at minimal costs. Of 121 patients who were included pathogenic variants were identified in 77 patients. These included patients with Chronic Granulomatous Disease, Severe Combined Immune Deficiency, leukocyte adhesion defect, X-linked agammaglobulinemia, Ataxia Telangiectasia, Hyper-IgE syndrome, Wiskott Aldrich syndrome, Mendelian susceptibility to mycobacterial diseases, Hyper-IgM syndrome, autoimmune lymphoproliferative syndrome, and GATA-2 deficiency. This manuscript discusses the challenges encountered while setting up and running targeted NGS for IEI in our unit. Genetic diagnosis has helped our patients with IEI in genetic counselling, prenatal diagnosis, and accessing appropriate therapeutic options.

Validating Amino Acid Variants in Proteogenomics Using Sequence Coverage by Multiple Reads

Mass spectrometry-based proteome analysis implies matching the mass spectra of proteolytic peptides to amino acid sequences predicted from genomic sequences. Reliability of peptide variant identification in proteogenomic studies is often lacking. We propose a way to interpret shotgun proteomics results, specifically in the data-dependent acquisition mode, as protein sequence coverage by multiple reads as it is done in nucleic acid sequencing for calling of single nucleotide variants. Multiple reads for each sequence position could be provided by overlapping distinct peptides, thus confirming the presence of certain amino acid residues in the overlapping stretch with a lower false discovery rate. Overlapping distinct peptides originate from miscleaved tryptic peptides in combination with their properly cleaved counterparts and from peptides generated by multiple proteases after the same specimen is subject to parallel digestion and analyzed separately. We illustrate this approach using publicly available multiprotease data sets and our own data generated for the HEK-293 cell line digests obtained using trypsin, LysC, and GluC proteases. Totally, up to 30% of the whole proteome was covered by tryptic peptides with up to 7% covered twofold and more. The proteogenomic analysis of the HEK-293 cell line revealed 36 single amino acid variants, seven of which were supported by multiple reads.

A review of the resistome within the digestive tract of livestock

Antimicrobials have been widely used to prevent and treat infectious diseases and promote growth in food-production animals. However, the occurrence of antimicrobial resistance poses a huge threat to public and animal health, especially in less developed countries where food-producing animals often intermingle with humans. To limit the spread of antimicrobial resistance from food-production animals to humans and the environment, it is essential to have a comprehensive knowledge of the role of the resistome in antimicrobial resistance (AMR), The resistome refers to the collection of all antimicrobial resistance genes associated with microbiota in a given environment. The dense microbiota in the digestive tract is known to harbour one of the most diverse resistomes in nature. Studies of the resistome in the digestive tract of humans and animals are increasing exponentially as a result of advancements in next-generation sequencing and the expansion of bioinformatic resources/tools to identify and describe the resistome. In this review, we outline the various tools/bioinformatic pipelines currently available to characterize and understand the nature of the intestinal resistome of swine, poultry, and ruminants. We then propose future research directions including analysis of resistome using long-read sequencing, investigation in the role of mobile genetic elements in the expression, function and transmission of AMR. This review outlines the current knowledge and approaches to studying the resistome in food-producing animals and sheds light on future strategies to reduce antimicrobial usage and control the spread of AMR both within and from livestock production systems.

Revisiting the methods for detecting Mycobacterium tuberculosis: what has the new millennium brought thus far?

Tuberculosis (TB) affects around 10 million people worldwide in 2019. Approximately 3.4 % of new TB cases are multidrug-resistant. The gold standard method for detecting Mycobacterium tuberculosis, which is the aetiological agent of TB, is still based on microbiological culture procedures, followed by species identification and drug sensitivity testing. Sputum is the most commonly obtained clinical specimen from patients with pulmonary TB. Although smear microscopy is a low-cost and widely used method, its sensitivity is 50-60 %. Thus, owing to the need to improve the performance of current microbiological tests to provide prompt treatment, different methods with varied sensitivity and specificity for TB diagnosis have been developed. Here we discuss the existing methods developed over the past 20 years, including their strengths and weaknesses. In-house and commercial methods have been shown to be promising to achieve rapid diagnosis. Combining methods for mycobacterial detection systems demonstrates a correlation of 100 %. Other assays are useful for the simultaneous detection of M. tuberculosis species and drug-related mutations. Novel approaches have also been employed to rapidly identify and quantify total mycobacteria RNA, including assessments of global gene expression measured in whole blood to identify the risk of TB. Spoligotyping, mass spectrometry and next-generation sequencing are also promising technologies; however, their cost needs to be reduced so that low- and middle-income countries can access them. Because of the large impact of M. tuberculosis infection on public health, the development of new methods in the context of well-designed and -controlled clinical trials might contribute to the improvement of TB infection control.

Increasing the power of interpretation for soil metaproteomics data

BACKGROUND

Soil and sediment microorganisms are highly phylogenetically diverse but are currently largely under-represented in public molecular databases. Their functional characterization by means of metaproteomics is usually performed using metagenomic sequences acquired for the same sample. However, such hugely diverse metagenomic datasets are difficult to assemble; in parallel, theoretical proteomes from isolates available in generic databases are of high quality. Both these factors advocate for the use of theoretical proteomes in metaproteomics interpretation pipelines. Here, we examined a number of database construction strategies with a view to increasing the outputs of metaproteomics studies performed on soil samples.

RESULTS

The number of peptide-spectrum matches was found to be of comparable magnitude when using public or sample-specific metagenomics-derived databases. However, numbers were significantly increased when a combination of both types of information was used in a two-step cascaded search. Our data also indicate that the functional annotation of the metaproteomics dataset can be maximized by using a combination of both types of databases.

CONCLUSIONS

A two-step strategy combining sample-specific metagenome database and public databases such as the non-redundant NCBI database and a massive soil gene catalog allows maximizing the metaproteomic interpretation both in terms of ratio of assigned spectra and retrieval of function-derived information. Video abstract.

Draft genomes of Perkinsus olseni and Perkinsus chesapeaki reveal polyploidy and regional differences in heterozygosity

Perkinsus spp. parasites have significant impact on aquaculture and wild mollusc populations. We sequenced the genomes of five monoclonal isolates of Perkinsus olseni and one Perkinsus chesapeaki from international sources. Sequence analysis revealed similar levels of repetitive sequence within species, a polyploid genome structure, and substantially higher heterozygosity in Oceanian-sourced isolates. We also identified tandem replication of the rRNA transcriptional unit, with high strain variation. Characterized gene content was broadly similar amongst all Perkinsus spp. but P. olseni Oceanian isolates contained an elevated number of genes compared to other P. olseni isolates and cox3 could not be identified in any Perkinsus spp. sequence. Phylogenetics and average nucleotide identity scans were consistent with all P. olseni isolates being within one species. These are the first genome sequences generated for both P. olseni and P. chesapeaki and will allow future advances in diagnostic design and population genomics of these important aquatic parasites.

Platforms for elucidating antibiotic resistance in single genomes and complex metagenomes

Antibiotic or antimicrobial resistance (AR) facilitated by the vertical and/or horizontal transfer of antibiotic resistance genes (ARGs), is a serious global health challenge. While traditionally associated with pathogens in clinical environments, it is becoming increasingly clear that non-clinical environments may also be reservoirs of ARGs. The recent improvements in rapid and affordable next generation sequencing technologies along with sophisticated bioinformatics platforms has the potential to revolutionize diagnostic microbiology and microbial surveillance. Through the study and characterization of ARGs in bacterial genomes and complex metagenomes, we are now able to reveal the genetic scope of AR in single bacteria and complex communities, and obtain important insights into AR dynamics at species, population and community levels, providing novel epidemiological and ecological perspectives. A suite of bioinformatics pipelines and ARG databases are currently available for genomic and metagenomic data analyses. However, different platforms may significantly vary and therefore, it is crucial to choose the tools that are most suitable for the specific analysis being conducted. This review provides a detailed account of available bioinformatics platforms for identification and characterization of ARGs and associated genetic elements within single bacterial isolates and complex environmental samples. It focuses primarily on currently available ARG databases, employing a comprehensive benchmarking pipeline to identify ARGs in four bacterial genomes (Aeromonas salmonicida, Bacillus cereus, Burkholderia sp. and Escherichia coli) and three shotgun metagenomes (human gut, poultry litter and soil) providing insight into which databases should be used for different analytical scenarios.

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis-regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low-frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis-regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic-acid pathway to local adaptation.

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis-regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low-frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis-regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic-acid pathway to local adaptation.

Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application

There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors, including sample sourcing, technology selection and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems. This article provides an up-to-date overview of the evolution of HTS and the accompanying tools, infrastructure and data management approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalized medicine.

Sequencing-based methods and resources to study antimicrobial resistance

Antimicrobial resistance extracts high morbidity, mortality and economic costs yearly by rendering bacteria immune to antibiotics. Identifying and understanding antimicrobial resistance are imperative for clinical practice to treat resistant infections and for public health efforts to limit the spread of resistance. Technologies such as next-generation sequencing are expanding our abilities to detect and study antimicrobial resistance. This Review provides a detailed overview of antimicrobial resistance identification and characterization methods, from traditional antimicrobial susceptibility testing to recent deep-learning methods. We focus on sequencing-based resistance discovery and discuss tools and databases used in antimicrobial resistance studies.

The Red Fox Y-Chromosome in Comparative Context

While the number of mammalian genome assemblies has proliferated, Y-chromosome assemblies have lagged behind. This discrepancy is caused by biological features of the Y-chromosome, such as its high repeat content, that present challenges to assembly with short-read, next-generation sequencing technologies. Partial Y-chromosome assemblies have been developed for the cat (Feliscatus), dog (Canislupusfamiliaris), and grey wolf (Canislupuslupus), providing the opportunity to examine the red fox (Vulpesvulpes) Y-chromosome in the context of closely related species. Here we present a data-driven approach to identifying Y-chromosome sequence among the scaffolds that comprise the short-read assembled red fox genome. First, scaffolds containing genes found on the Y-chromosomes of cats, dogs, and wolves were identified. Next, analysis of the resequenced genomes of 15 male and 15 female foxes revealed scaffolds containing male-specific k-mers and patterns of inter-sex copy number variation consistent with the heterogametic chromosome. Analyzing variation across these two metrics revealed 171 scaffolds containing 3.37 Mbp of putative Y-chromosome sequence. The gene content of these scaffolds is consistent overall with that of the Y-chromosome in other carnivore species, though the red fox Y-chromosome carries more copies of BCORY2 and UBE1Y than has been reported in related species and fewer copies of SRY than in other canids. The assignment of these scaffolds to the Y-chromosome serves to further characterize the content of the red fox draft genome while providing resources for future analyses of canid Y-chromosome evolution.

The first draft genomes of the ant Formica exsecta, and its Wolbachia endosymbiont reveal extensive gene transfer from endosymbiont to host

Background

Adapting to changes in the environment is the foundation of species survival, and is usually thought to be a gradual process. However, transposable elements (TEs), epigenetic modifications, and/or genetic material acquired from other organisms by means of horizontal gene transfer (HGTs), can also lead to novel adaptive traits. Social insects form dense societies, which attract and maintain extra- and intracellular accessory inhabitants, which may facilitate gene transfer between species. The wood ant Formica exsecta (Formicidae; Hymenoptera), is a common ant species throughout the Palearctic region. The species is a well-established model for studies of ecological characteristics and evolutionary conflict.

Results

In this study, we sequenced and assembled draft genomes for F. exsecta and its endosymbiont Wolbachia. The F. exsecta draft genome is 277.7 Mb long; we identify 13,767 protein coding genes, for which we provide gene ontology and protein domain annotations. This is also the first report of a Wolbachia genome from ants, and provides insights into the phylogenetic position of this endosymbiont. We also identified multiple horizontal gene transfer events (HGTs) from Wolbachia to F. exsecta. Some of these HGTs have also occurred in parallel in multiple other insect genomes, highlighting the extent of HGTs in eukaryotes.

Conclusion

We present the first draft genome of ant F. exsecta, and its endosymbiont Wolbachia (wFex), and show considerable rates of gene transfer from the symbiont to the host. We expect that especially the F. exsecta genome will be valuable resource in further exploration of the molecular basis of the evolution of social organization.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5665-6) contains supplementary material, which is available to authorized users.

Whole Proteome Clustering of 2,307 Proteobacterial Genomes Reveals Conserved Proteins and Significant Annotation Issues

We clustered 8.76 M protein sequences deduced from 2,307 completely sequenced Proteobacterial genomes resulting in 707,311 clusters of one or more sequences of which 224,442 ranged in size from 2 to 2,894 sequences. To our knowledge this is the first study of this scale. We were surprised to find that no single cluster contained a representative sequence from all the organisms in the study. Given the minimal genome concept, we expected to find a shared set of proteins. To determine why the clusters did not have universal representation we chose four essential proteins, the chaperonin GroEL, DNA dependent RNA polymerase subunits beta and beta′ (RpoB/RpoB′), and DNA polymerase I (PolA), representing fundamental cellular functions, and examined their cluster distribution. We found these proteins to be remarkably conserved with certain caveats. Although the groEL gene was universally conserved in all the organisms in the study, the protein was not represented in all the deduced proteomes. The genes for RpoB and RpoB′ were missing from two genomes and merged in 88, and the sequences were sufficiently divergent that they formed separate clusters for 18 RpoB proteins (seven clusters) and 14 RpoB′ proteins (three clusters). For PolA, 52 organisms lacked an identifiable sequence, and seven sequences were sufficiently divergent that they formed five separate clusters. Interestingly, organisms lacking an identifiable PolA and those with divergent RpoB/RpoB′ were predominantly endosymbionts. Furthermore, we present a range of examples of annotation issues that caused the deduced proteins to be incorrectly represented in the proteome. These annotation issues made our task of determining protein conservation more difficult than expected and also represent a significant obstacle for high-throughput analyses.

Preimplantation genetic diagnosis and screening (PGD/S) using a semiconductor sequencing platform

Background

Recent advances in semiconductor sequencing platform (SSP) have provided new methods for preimplantation genetic diagnosis/screening (PGD/S). The present study aimed to evaluate the applicability and efficiency of SSP in PGD/S.

Methods

The artificial positive single-cell-like DNAs and normal single-cell samples were chosen to test our semiconductor sequencing platform for preimplantation genetic diagnosis/screening (SSP-PGD/S) method with two widely used whole-genome amplification (WGA) kits. A total of 557 single blastomeres were collected from in vitro fertilization (IVF) couples, and their WGA products were processed and analyzed by our SSP-PGD/S method in comparison with array comparative genomic hybridization (array-CGH).

Results

Our SSP-PGD/S method indicated high compatibilities with two commercial WGA kits. For 557 single blastomeres, our method with four million reads in average could detect 24-chromosome aneuploidies as well as microdeletion/microduplication of the size over 4 Mb, providing 100% consistent conclusion with array-CGH method in the classification of whether it was transplantable.

Conclusions

Our studies suggested that SSP-PGD/S represents a valuable alternative to array-CGH and brought PGD/S into a new era of more rapid, accurate, and economic.

Electronic supplementary material

The online version of this article (10.1186/s40246-018-0187-x) contains supplementary material, which is available to authorized users.

SMRT long reads and Direct Label and Stain optical maps allow the generation of a high-quality genome assembly for the European barn swallow (Hirundo rustica rustica)

Background

The barn swallow (Hirundo rustica) is a migratory bird that has been the focus of a large number of ecological, behavioral, and genetic studies. To facilitate further population genetics and genomic studies, we present a reference genome assembly for the European subspecies (H. r. rustica).

Findings

As part of the Genome10K effort on generating high-quality vertebrate genomes (Vertebrate Genomes Project), we have assembled a highly contiguous genome assembly using single molecule real-time (SMRT) DNA sequencing and several Bionano optical map technologies. We compared and integrated optical maps derived from both the Nick, Label, Repair, and Stain technology and from the Direct Label and Stain (DLS) technology. As proposed by Bionano, DLS more than doubled the scaffold N50 with respect to the nickase. The dual enzyme hybrid scaffold led to a further marginal increase in scaffold N50 and an overall increase of confidence in the scaffolds. After removal of haplotigs, the final assembly is approximately 1.21 Gbp in size, with a scaffold N50 value of more than 25.95 Mbp.

Conclusions

This high-quality genome assembly represents a valuable resource for future studies of population genetics and genomics in the barn swallow and for studies concerning the evolution of avian genomes. It also represents one of the very first genomes assembled by combining SMRT long-read sequencing with the new Bionano DLS technology for scaffolding. The quality of this assembly demonstrates the potential of this methodology to substantially increase the contiguity of genome assemblies.

Homologue-specific chromosome sequencing characterizes translocation junctions and permits allelic assignment

Chromosome translocations can be detected by cytogenetic analysis, but it is hard to characterize the breakpoints at the sequence level. Chromosome sorting by flow cytometry produces flow karyotypes that enable the isolation of abnormal chromosomes and the generation of chromosome-specific DNA. In this study, a derivative chromosome t(9; 14) and its homologous normal chromosomes 9 and 14 from the Ishikawa 3-H-12 cell line were sorted to collect homologue-specific samples. Chromosome sequencing identified the breakpoint junction in the der(9) at 9p24.3 and 14q13.1 and uncovered the formation of a fusion gene, WASH1–NPAS3. Amplicon sequencing targeted for neighbouring genes at the fusion breakpoint revealed that the variant frequencies correlate with the allelic copy number. Sequencing of sorted chromosomes permits the assignment of allelic variants and can lead to the characterization of abnormal chromosomes. We show that allele-specific chromosome sequencing of homologues is a robust technique for distinguishing alleles and this provides an efficient approach for the comprehensive analysis of genomic changes.

Machine Learning for detection of viral sequences in human metagenomic datasets

BACKGROUND

Detection of highly divergent or yet unknown viruses from metagenomics sequencing datasets is a major bioinformatics challenge. When human samples are sequenced, a large proportion of assembled contigs are classified as "unknown", as conventional methods find no similarity to known sequences. We wished to explore whether machine learning algorithms using Relative Synonymous Codon Usage frequency (RSCU) could improve the detection of viral sequences in metagenomic sequencing data.

RESULTS

We trained Random Forest and Artificial Neural Network using metagenomic sequences taxonomically classified into virus and non-virus classes. The algorithms achieved accuracies well beyond chance level, with area under ROC curve 0.79. Two codons (TCG and CGC) were found to have a particularly strong discriminative capacity.

CONCLUSION

RSCU-based machine learning techniques applied to metagenomic sequencing data can help identify a large number of putative viral sequences and provide an addition to conventional methods for taxonomic classification.

The State of "Omics" Research for Farmed Penaeids: Advances in Research and Impediments to Industry Utilization

Elucidating the underlying genetic drivers of production traits in agricultural and aquaculture species is critical to efforts to maximize farming efficiency. "Omics" based methods (i.e., transcriptomics, genomics, proteomics, and metabolomics) are increasingly being applied to gain unprecedented insight into the biology of many aquaculture species. While the culture of penaeid shrimp has increased markedly, the industry continues to be impeded in many regards by disease, reproductive dysfunction, and a poor understanding of production traits. Extensive effort has been, and continues to be, applied to develop critical genomic resources for many commercially important penaeids. However, the industry application of these genomic resources, and the translation of the knowledge derived from "omics" studies has not yet been completely realized. Integration between the multiple "omics" resources now available (i.e., genome assemblies, transcriptomes, linkage maps, optical maps, and proteomes) will prove critical to unlocking the full utility of these otherwise independently developed and isolated resources. Furthermore, emerging "omics" based techniques are now available to address longstanding issues with completing keystone genome assemblies (e.g., through long-read sequencing), and can provide cost-effective industrial scale genotyping tools (e.g., through low density SNP chips and genotype-by-sequencing) to undertake advanced selective breeding programs (i.e., genomic selection) and powerful genome-wide association studies. In particular, this review highlights the status, utility and suggested path forward for continued development, and improved use of "omics" resources in penaeid aquaculture.

De novo assembly of bacterial genomes with repetitive DNA regions by dnaasm application

Background

Many organisms, in particular bacteria, contain repetitive DNA fragments called tandem repeats. These structures are restored by DNA assemblers by mapping paired-end tags to unitigs, estimating the distance between them and filling the gap with the specified DNA motif, which could be repeated many times. However, some of the tandem repeats are longer than the distance between the paired-end tags.

Results

We present a new algorithm for de novo DNA assembly, which uses the relative frequency of reads to properly restore tandem repeats. The main advantage of the presented algorithm is that long tandem repeats, which are much longer than maximum reads length and the insert size of paired-end tags can be properly restored. Moreover, repetitive DNA regions covered only by single-read sequencing data could also be restored. Other existing de novo DNA assemblers fail in such cases.

The presented application is composed of several steps, including: (i) building the de Bruijn graph, (ii) correcting the de Bruijn graph, (iii) normalizing edge weights, and (iv) generating the output set of DNA sequences.

We tested our approach on real data sets of bacterial organisms.

Conclusions

The software library, console application and web application were developed. Web application was developed in client-server architecture, where web-browser is used to communicate with end-user and algorithms are implemented in C++ and Python. The presented approach enables proper reconstruction of tandem repeats, which are longer than the insert size of paired-end tags. The application is freely available to all users under GNU Library or Lesser General Public License version 3.0 (LGPLv3).

Chromosome-scale pseudomolecules refined by optical, physical and genetic maps in flax

Genomes of varying sizes have been sequenced with next-generation sequencing platforms. However, most reference sequences include draft unordered scaffolds containing chimeras caused by mis-scaffolding. A BioNano genome (BNG) optical map was constructed to improve the previously sequenced flax genome (Linum usitatissimum L., 2n = 30, about 373 Mb), which consisted of 3852 scaffolds larger than 1 kb and totalling 300.6 Mb. The high-resolution BNG map of cv. CDC Bethune totalled 317 Mb and consisted of 251 BNG contigs with an N50 of 2.15 Mb. A total of 622 scaffolds (286.6 Mb, 94.9%) aligned to 211 BNG contigs (298.6 Mb, 94.2%). Of those, 99 scaffolds, diagnosed to contain assembly errors, were refined into 225 new scaffolds. Using the newly refined scaffold sequences and the validated bacterial artificial chromosome-based physical map of CDC Bethune, the 211 BNG contigs were scaffolded into 94 super-BNG contigs (N50 of 6.64 Mb) that were further assigned to the 15 flax chromosomes using the genetic map. The pseudomolecules total about 316 Mb, with individual chromosomes of 15.6 to 29.4 Mb, and cover 97% of the annotated genes. Evidence from the chromosome-scale pseudomolecules suggests that flax has undergone palaeopolyploidization and mesopolyploidization events, followed by rearrangements and deletions or fusion of chromosome arms from an ancient progenitor with a haploid chromosome number of eight.

Construction of Red Fox Chromosomal Fragments from the Short-Read Genome Assembly

The genome of a red fox (Vulpes vulpes) was recently sequenced and assembled using next-generation sequencing (NGS). The assembly is of high quality, with 94X coverage and a scaffold N50 of 11.8 Mbp, but is split into 676,878 scaffolds, some of which are likely to contain assembly errors. Fragmentation and misassembly hinder accurate gene prediction and downstream analysis such as the identification of loci under selection. Therefore, assembly of the genome into chromosome-scale fragments was an important step towards developing this genomic model. Scaffolds from the assembly were aligned to the dog reference genome and compared to the alignment of an outgroup genome (cat) against the dog to identify syntenic sequences among species. The program Reference-Assisted Chromosome Assembly (RACA) then integrated the comparative alignment with the mapping of the raw sequencing reads generated during assembly against the fox scaffolds. The 128 sequence fragments RACA assembled were compared to the fox meiotic linkage map to guide the construction of 40 chromosomal fragments. This computational approach to assembly was facilitated by prior research in comparative mammalian genomics, and the continued improvement of the red fox genome can in turn offer insight into canid and carnivore chromosome evolution. This assembly is also necessary for advancing genetic research in foxes and other canids.

Complete genomic and transcriptional landscape analysis using third-generation sequencing: a case study of Saccharomyces cerevisiae CEN.PK113-7D

Completion of eukaryal genomes can be difficult task with the highly repetitive sequences along the chromosomes and short read lengths of second-generation sequencing. Saccharomyces cerevisiae strain CEN.PK113-7D, widely used as a model organism and a cell factory, was selected for this study to demonstrate the superior capability of very long sequence reads for de novo genome assembly. We generated long reads using two common third-generation sequencing technologies (Oxford Nanopore Technology (ONT) and Pacific Biosciences (PacBio)) and used short reads obtained using Illumina sequencing for error correction. Assembly of the reads derived from all three technologies resulted in complete sequences for all 16 yeast chromosomes, as well as the mitochondrial chromosome, in one step. Further, we identified three types of DNA methylation (5mC, 4mC and 6mA). Comparison between the reference strain S288C and strain CEN.PK113-7D identified chromosomal rearrangements against a background of similar gene content between the two strains. We identified full-length transcripts through ONT direct RNA sequencing technology. This allows for the identification of transcriptional landscapes, including untranslated regions (UTRs) (5' UTR and 3' UTR) as well as differential gene expression quantification. About 91% of the predicted transcripts could be consistently detected across biological replicates grown either on glucose or ethanol. Direct RNA sequencing identified many polyadenylated non-coding RNAs, rRNAs, telomere-RNA, long non-coding RNA and antisense RNA. This work demonstrates a strategy to obtain complete genome sequences and transcriptional landscapes that can be applied to other eukaryal organisms.

Protein Interactomics by Two-Hybrid Methods

Comprehensive identification of direct, physical interactions between biological macromolecules, such as protein-protein, protein-DNA, and protein-RNA interactions, is critical for our understanding of the function of gene products as well as the global organization and interworkings of various molecular machines within the cell. The accurate and comprehensive detection of direct interactions, however, remains a huge challenge due to the inherent structural complexity arising from various post-transcriptional and translational modifications coupled with huge heterogeneity in concentration, affinity, and subcellular location differences existing for any interacting molecules. This has created a need for developing multiple orthogonal and complementary assays for detecting various types of biological interactions. In this introduction, we discuss the methods developed for measuring different types of molecular interactions with an emphasis on direct protein-protein interactions, critical issues for generating high-quality interactome datasets, and the insights into biological networks and human diseases that current interaction mapping efforts provide. Further, we will discuss what future might lie ahead for the continued evolution of two-hybrid methods and the role of interactomics for expanding the advancement of biomedical science.

A pipeline for local assembly of minisatellite alleles from single-molecule sequencing data

Motivation

The advent of Next Generation Sequencing (NGS) has led to the generation of enormous volumes of short read sequence data, cheaply and in reasonable time scales. Nevertheless, the quality of genome assemblies generated using NGS technologies has been greatly affected, compared to those generated using Sanger DNA sequencing. This is largely due to the inability of short read sequence data to scaffold repetitive structures, creating gaps, inversions and rearrangements and resulting in assemblies that are, at best, draft forms. Third generation single-molecule sequencing (SMS) technologies (e.g. Pacific Biosciences Single Molecule Real Time (SMRT) system) address this challenge by generating sequences with increased read lengths, offering the prospect to better recover these complex repetitive structures, concomitantly improving assembly quality.

Results

Here, we evaluate the ability of SMS data (specifically human genome Pacific Biosciences SMRT data) to recover poorly represented repetitive sequences (specifically, GC-rich human minisatellites). To do this we designed a pipeline for the collection, processing and local assembly of single-molecule sequence data to form accurate contiguous local reconstructions. Our results show the recovery of an allele of the non-coding minisatellite MS1 (located on chromosome 1 at 1p33-35) at greater than 97% identity to reference (GRCh38) from the unprocessed sequence data of a haploid complete hydatidiform mole (CHM1) cell line. Furthermore, our assembly revealed an allele of over 500 repeat units; much larger than the reference (GRCh38), but consistent in structure with naturally occurring alleles that are segregating in human populations. This local assembly's reconstruction was validated with the release of the whole genome assemblies GCA_001297185.1 and GCA_000772585.3, where this allele occurs. Additionally, application of this pipeline to coding minisatellites in the PRDM9 and ZNF93 genes enabled recovery of high identity allele structures for these sequence regions whose length was confirmed by PCR from cell line genomic DNA. The internal repeat structure of the PRDM9 allele recovered was consistent with common human-specific alleles.

Availability and Implementation

Code available at https://github.com/ndliberial/smrt_pipeline.

Contact

dno2@le.ac.uk.

Whole genome DNA methylation sequencing of the chicken retina, cornea and brain

Whole genome bisulfite sequencing (WGBS) analysis of DNA methylation uses massively parallel next generation sequencing technology to characterize global epigenetic patterns and fluctuations throughout a range of tissue samples. Development of the vertebrate retina is thought to involve extensive epigenetic reprogramming during embryogenesis. The chicken embryo (Gallus gallus) is a classic model system for studying developmental biology and retinogenesis, however, there are currently no publicly available data sets describing the developing chicken retinal methylome. Here we used Illumina WGBS analysis to characterize genome-wide patterns of DNA methylation in the developing chicken retina as well as cornea and brain in an effort to further our understanding of retina-specific epigenetic regulation. These data will be valuable to the vision research community for correlating global changes in DNA methylation to differential gene expression between ocular and neural tissues during critical developmental time points of retinogenesis in the chicken retina.

Genomic approaches to diagnose rare bone disorders

Skeletal dysplasias are Mendelian disorders with a prevalence of approximatively 1 in every 5000 individuals and can usually be diagnosed based on clinical and radiological findings. However, given that some diseases can be caused by several different genes, and that some genes can cause a variety of different phenotypes, achieving a molecular diagnosis can be challenging. We review here different approaches, from single gene sequencing to genomic approaches using next-generation sequencing, to reach a molecular diagnosis for skeletal dysplasias. We will further describe the overall advantages and limitations of first, second and third-generation sequencing, including single gene sequencing, whole-exome and genome sequencing (WES and WGS), multiple gene panel sequencing and single molecule sequencing. We also provide a brief overview of potential future applications of emerging technologies.

The Peach v2.0 release: high-resolution linkage mapping and deep resequencing improve chromosome-scale assembly and contiguity

BACKGROUND

The availability of the peach genome sequence has fostered relevant research in peach and related Prunus species enabling the identification of genes underlying important horticultural traits as well as the development of advanced tools for genetic and genomic analyses. The first release of the peach genome (Peach v1.0) represented a high-quality WGS (Whole Genome Shotgun) chromosome-scale assembly with high contiguity (contig L50 214.2 kb), large portions of mapped sequences (96%) and high base accuracy (99.96%). The aim of this work was to improve the quality of the first assembly by increasing the portion of mapped and oriented sequences, correcting misassemblies and improving the contiguity and base accuracy using high-throughput linkage mapping and deep resequencing approaches.

RESULTS

Four linkage maps with 3,576 molecular markers were used to improve the portion of mapped and oriented sequences (from 96.0% and 85.6% of Peach v1.0 to 99.2% and 98.2% of v2.0, respectively) and enabled a more detailed identification of discernible misassemblies (10.4 Mb in total). The deep resequencing approach fixed 859 homozygous SNPs (Single Nucleotide Polymorphisms) and 1347 homozygous indels. Moreover, the assembled NGS contigs enabled the closing of 212 gaps with an improvement in the contig L50 of 19.2%.

CONCLUSIONS

The improved high quality peach genome assembly (Peach v2.0) represents a valuable tool for the analysis of the genetic diversity, domestication, and as a vehicle for genetic improvement of peach and related Prunus species. Moreover, the important phylogenetic position of peach and the absence of recent whole genome duplication (WGD) events make peach a pivotal species for comparative genomics studies aiming at elucidating plant speciation and diversification processes.

The Peach v2.0 release: high-resolution linkage mapping and deep resequencing improve chromosome-scale assembly and contiguity

BACKGROUND

The availability of the peach genome sequence has fostered relevant research in peach and related Prunus species enabling the identification of genes underlying important horticultural traits as well as the development of advanced tools for genetic and genomic analyses. The first release of the peach genome (Peach v1.0) represented a high-quality WGS (Whole Genome Shotgun) chromosome-scale assembly with high contiguity (contig L50 214.2 kb), large portions of mapped sequences (96%) and high base accuracy (99.96%). The aim of this work was to improve the quality of the first assembly by increasing the portion of mapped and oriented sequences, correcting misassemblies and improving the contiguity and base accuracy using high-throughput linkage mapping and deep resequencing approaches.

RESULTS

Four linkage maps with 3,576 molecular markers were used to improve the portion of mapped and oriented sequences (from 96.0% and 85.6% of Peach v1.0 to 99.2% and 98.2% of v2.0, respectively) and enabled a more detailed identification of discernible misassemblies (10.4 Mb in total). The deep resequencing approach fixed 859 homozygous SNPs (Single Nucleotide Polymorphisms) and 1347 homozygous indels. Moreover, the assembled NGS contigs enabled the closing of 212 gaps with an improvement in the contig L50 of 19.2%.

CONCLUSIONS

The improved high quality peach genome assembly (Peach v2.0) represents a valuable tool for the analysis of the genetic diversity, domestication, and as a vehicle for genetic improvement of peach and related Prunus species. Moreover, the important phylogenetic position of peach and the absence of recent whole genome duplication (WGD) events make peach a pivotal species for comparative genomics studies aiming at elucidating plant speciation and diversification processes.

Phased diploid genome assembly with single-molecule real-time sequencing

While genome assembly projects have been successful in many haploid and inbred species, the assembly of noninbred or rearranged heterozygous genomes remains a major challenge. To address this challenge, we introduce the open-source FALCON and FALCON-Unzip algorithms (https://github.com/PacificBiosciences/FALCON/) to assemble long-read sequencing data into highly accurate, contiguous, and correctly phased diploid genomes. We generate new reference sequences for heterozygous samples including an F1 hybrid of Arabidopsis thaliana, the widely cultivated Vitis vinifera cv. Cabernet Sauvignon, and the coral fungus Clavicorona pyxidata, samples that have challenged short-read assembly approaches. The FALCON-based assemblies are substantially more contiguous and complete than alternate short- or long-read approaches. The phased diploid assembly enabled the study of haplotype structure and heterozygosities between homologous chromosomes, including the identification of widespread heterozygous structural variation within coding sequences.

Oxford Nanopore MinION Sequencing and Genome Assembly

The revolution of genome sequencing is continuing after the successful second-generation sequencing (SGS) technology. The third-generation sequencing (TGS) technology, led by Pacific Biosciences (PacBio), is progressing rapidly, moving from a technology once only capable of providing data for small genome analysis, or for performing targeted screening, to one that promises high quality de novo assembly and structural variation detection for human-sized genomes. In 2014, the MinION, the first commercial sequencer using nanopore technology, was released by Oxford Nanopore Technologies (ONT). MinION identifies DNA bases by measuring the changes in electrical conductivity generated as DNA strands pass through a biological pore. Its portability, affordability, and speed in data production makes it suitable for real-time applications, the release of the long read sequencer MinION has thus generated much excitement and interest in the genomics community. While de novo genome assemblies can be cheaply produced from SGS data, assembly continuity is often relatively poor, due to the limited ability of short reads to handle long repeats. Assembly quality can be greatly improved by using TGS long reads, since repetitive regions can be easily expanded into using longer sequencing lengths, despite having higher error rates at the base level. The potential of nanopore sequencing has been demonstrated by various studies in genome surveillance at locations where rapid and reliable sequencing is needed, but where resources are limited.

A Primer on Infectious Disease Bacterial Genomics

The number of large-scale genomics projects is increasing due to the availability of affordable high-throughput sequencing (HTS) technologies. The use of HTS for bacterial infectious disease research is attractive because one whole-genome sequencing (WGS) run can replace multiple assays for bacterial typing, molecular epidemiology investigations, and more in-depth pathogenomic studies. The computational resources and bioinformatics expertise required to accommodate and analyze the large amounts of data pose new challenges for researchers embarking on genomics projects for the first time. Here, we present a comprehensive overview of a bacterial genomics projects from beginning to end, with a particular focus on the planning and computational requirements for HTS data, and provide a general understanding of the analytical concepts to develop a workflow that will meet the objectives and goals of HTS projects.

Whole-Genome Sequence of Multidrug-Resistant Pseudomonas aeruginosa Strain BAMCPA07-48, Isolated from a Combat Injury Wound

We report here the complete genome sequence of Pseudomonas aeruginosa strain BAMCPA07-48, isolated from a combat injury wound. The closed genome sequence of this isolate is a valuable resource for pathogenome characterization of P. aeruginosa associated with wounds, which will aid in the development of a higher-resolution phylogenomic framework for molecular-guided pathogen-surveillance.

Challenges, Solutions, and Quality Metrics of Personal Genome Assembly in Advancing Precision Medicine

Even though each of us shares more than 99% of the DNA sequences in our genome, there are millions of sequence codes or structure in small regions that differ between individuals, giving us different characteristics of appearance or responsiveness to medical treatments. Currently, genetic variants in diseased tissues, such as tumors, are uncovered by exploring the differences between the reference genome and the sequences detected in the diseased tissue. However, the public reference genome was derived with the DNA from multiple individuals. As a result of this, the reference genome is incomplete and may misrepresent the sequence variants of the general population. The more reliable solution is to compare sequences of diseased tissue with its own genome sequence derived from tissue in a normal state. As the price to sequence the human genome has dropped dramatically to around $1000, it shows a promising future of documenting the personal genome for every individual. However, de novo assembly of individual genomes at an affordable cost is still challenging. Thus, till now, only a few human genomes have been fully assembled. In this review, we introduce the history of human genome sequencing and the evolution of sequencing platforms, from Sanger sequencing to emerging "third generation sequencing" technologies. We present the currently available de novo assembly and post-assembly software packages for human genome assembly and their requirements for computational infrastructures. We recommend that a combined hybrid assembly with long and short reads would be a promising way to generate good quality human genome assemblies and specify parameters for the quality assessment of assembly outcomes. We provide a perspective view of the benefit of using personal genomes as references and suggestions for obtaining a quality personal genome. Finally, we discuss the usage of the personal genome in aiding vaccine design and development, monitoring host immune-response, tailoring drug therapy and detecting tumors. We believe the precision medicine would largely benefit from bioinformatics solutions, particularly for personal genome assembly.

APLICACIONES DE LA BIOINFORMÁTICA EN LA MEDICINA: EL GENOMA HUMANO. ¿CÓMO PODEMOS VER TANTO DETALLE?

<p lang="es-ES" align="JUSTIFY">La bioinformática es un campo novedoso que soporta parte de la investigación biológica dirigida a la identificación de variantes génicas que pueden ser descubiertas desde los estudios de genomas completos. Basados en esta motivación se presenta el panorama general de los aportes principales de la bioinformática en el desarrollo del secuenciamiento del primer genoma humano. Adicionalmente se resumen los principales avances en cómputo desarrollados para responder a las demandas requeridas por los métodos de secuenciamiento de última generación para lograr re-secuenciar un genoma humano. Finalmente se introducen algunos de los nuevos retos que deben asumirse para aplicar la genómica personalizada en el desarrollo de la medicina. </p><p lang="es-ES" align="JUSTIFY"> </p><p lang="es-ES" align="JUSTIFY">Abstract</p><p lang="es-ES" align="JUSTIFY">Bioinformatics is a new field that supports part of the biological research aimed at identifying gene variants that can be discovered from studies of whole genomes. Based on this motivation the overview of the main contributions of bioinformatics in the development of sequencing the first human genome is presented. Additionally it is summarized the main advances in computing developed to meet the demands to re-sequence a human genome by using the next generation sequencing technologies. Finally some new challenges that must be faced to apply the personalized genomics into the medicine development are introduced.</p>

Update on Genomic Databases and Resources at the National Center for Biotechnology Information

The National Center for Biotechnology Information (NCBI), as a primary public repository of genomic sequence data, collects and maintains enormous amounts of heterogeneous data. Data for genomes, genes, gene expressions, gene variation, gene families, proteins, and protein domains are integrated with the analytical, search, and retrieval resources through the NCBI website, text-based search and retrieval system, provides a fast and easy way to navigate across diverse biological databases.Comparative genome analysis tools lead to further understanding of evolution processes quickening the pace of discovery. Recent technological innovations have ignited an explosion in genome sequencing that has fundamentally changed our understanding of the biology of living organisms. This huge increase in DNA sequence data presents new challenges for the information management system and the visualization tools. New strategies have been designed to bring an order to this genome sequence shockwave and improve the usability of associated data.

Sequencing and de novo draft assemblies of a fathead minnow (Pimephales promelas) reference genome

The present study was undertaken to provide the foundation for development of genome-scale resources for the fathead minnow (Pimephales promelas), an important model organism widely used in both aquatic toxicology research and regulatory testing. The authors report on the first sequencing and 2 draft assemblies for the reference genome of this species. Approximately 120× sequence coverage was achieved via Illumina sequencing of a combination of paired-end, mate-pair, and fosmid libraries. Evaluation and comparison of these assemblies demonstrate that they are of sufficient quality to be useful for genome-enabled studies, with 418 of 458 (91%) conserved eukaryotic genes mapping to at least 1 of the assemblies. In addition to its immediate utility, the present work provides a strong foundation on which to build further refinements of a reference genome for the fathead minnow.

Marine Metagenome as A Resource for Novel Enzymes

More than 99% of identified prokaryotes, including many from the marine environment, cannot be cultured in the laboratory. This lack of capability restricts our knowledge of microbial genetics and community ecology. Metagenomics, the culture-independent cloning of environmental DNAs that are isolated directly from an environmental sample, has already provided a wealth of information about the uncultured microbial world. It has also facilitated the discovery of novel biocatalysts by allowing researchers to probe directly into a huge diversity of enzymes within natural microbial communities. Recent advances in these studies have led to a great interest in recruiting microbial enzymes for the development of environmentally-friendly industry. Although the metagenomics approach has many limitations, it is expected to provide not only scientific insights but also economic benefits, especially in industry. This review highlights the importance of metagenomics in mining microbial lipases, as an example, by using high-throughput techniques. In addition, we discuss challenges in the metagenomics as an important part of bioinformatics analysis in big data.

Tex19 and Sectm1 concordant molecular phylogenies support co-evolution of both eutherian-specific genes

BACKGROUND

Transposable elements (TE) have attracted much attention since they shape the genome and contribute to species evolution. Organisms have evolved mechanisms to control TE activity. Testis expressed 19 (Tex19) represses TE expression in mouse testis and placenta. In the human and mouse genomes, Tex19 and Secreted and transmembrane 1 (Sectm1) are neighbors but are not homologs. Sectm1 is involved in immunity and its molecular phylogeny is unknown.

METHODS

Using multiple alignments of complete protein sequences (MACS), we inferred Tex19 and Sectm1 molecular phylogenies. Protein conserved regions were identified and folds were predicted. Finally, expression patterns were studied across tissues and species using RNA-seq public data and RT-PCR.

RESULTS

We present 2 high quality alignments of 58 Tex19 and 58 Sectm1 protein sequences from 48 organisms. First, both genes are eutherian-specific, i.e., exclusively present in mammals except monotremes (platypus) and marsupials. Second, Tex19 and Sectm1 have both duplicated in Sciurognathi and Bovidae while they have remained as single copy genes in all further placental mammals. Phylogenetic concordance between both genes was significant (p-value < 0.05) and supported co-evolution and functional relationship. At the protein level, Tex19 exhibits 3 conserved regions and 4 invariant cysteines. In particular, a CXXC motif is present in the N-terminal conserved region. Sectm1 exhibits 2 invariant cysteines and an Ig-like domain. Strikingly, Tex19 C-terminal conserved region was lost in Haplorrhini primates while a Sectm1 C-terminal extra domain was acquired. Finally, we have determined that Tex19 and Sectm1 expression levels anti-correlate across the testis of several primates (ρ = -0.72) which supports anti-regulation.

CONCLUSIONS

Tex19 and Sectm1 co-evolution and anti-regulated expressions support a strong functional relationship between both genes. Since Tex19 operates a control on TE and Sectm1 plays a role in immunity, Tex19 might suppress an immune response directed against cells that show TE activity in eutherian reproductive tissues.

Mutational Analysis of BRAF Inhibitor-Associated Squamoproliferative Lesions

In recent years, there has been increasing use of BRAF-inhibiting drugs for the treatment of various malignancies, including melanoma. However, these agents are associated with the development of other nonmelanoma skin lesions, in particular squamoproliferative lesions such as keratoacanthomas (KAs), squamous cell carcinomas, and BRAF inhibitor-associated verrucous keratoses. The molecular pathogenesis of these lesions is of interest, not only for therapeutic reasons, but also for the insight it might provide into the development of similar lesions in a sporadic setting. We used next-generation sequencing to compare the mutational profiles of lesions after treatment with a BRAF inhibitor, with similar lesions arising sporadically. HRAS mutations were common among the BRAF inhibitor-induced lesions, being identified in 56%, compared with 14% of lesions in the sporadic group (P = 0.002). Thus, despite similar histomorphological appearances, the underlying molecular mechanisms may be different. In addition, within the BRAF inhibitor-associated group, the lesions designated as KAs and BRAF inhibitor-associated verrucous keratoses had a similar mutational profile (mutations in PIK3CA, APC, and HRAS), which was distinct to that seen in squamous cell carcinomas (FGFR3, CDKN2A, and STK11). We have previously noted histological overlap between KAs and BRAF inhibitor-associated verrucous keratoses, and this finding supports the notion that they may represent morphological or temporal variants of a single lesion type.

Next-generation sequencing in clinical virology: Discovery of new viruses

Viruses are a cause of significant health problem worldwide, especially in the developing nations. Due to different anthropological activities, human populations are exposed to different viral pathogens, many of which emerge as outbreaks. In such situations, discovery of novel viruses is utmost important for deciding prevention and treatment strategies. Since last century, a number of different virus discovery methods, based on cell culture inoculation, sequence-independent PCR have been used for identification of a variety of viruses. However, the recent emergence and commercial availability of next-generation sequencers (NGS) has entirely changed the field of virus discovery. These massively parallel sequencing platforms can sequence a mixture of genetic materials from a very heterogeneous mix, with high sensitivity. Moreover, these platforms work in a sequence-independent manner, making them ideal tools for virus discovery. However, for their application in clinics, sample preparation or enrichment is necessary to detect low abundance virus populations. A number of techniques have also been developed for enrichment or viral nucleic acids. In this manuscript, we review the evolution of sequencing; NGS technologies available today as well as widely used virus enrichment technologies. We also discuss the challenges associated with their applications in the clinical virus discovery.