Second-generation Sequencing Data Research Articles

CDT1 is a Potential Therapeutic Target for the Progression of NAFLD to HCC and the Exacerbation of Cancer

Aims: This study aimed to identify potential therapeutic targets in the progression from non-alcoholic fatty liver disease (NAFLD) to hepatocellular carcinoma (HCC), with a focus on genes that could influence disease development and progression. Background: Hepatocellular carcinoma, significantly driven by non-alcoholic fatty liver disease, represents a major global health challenge due to late-stage diagnosis and limited treatment options. This study utilizes bioinformatics to analyze data from GEO and TCGA, aiming to uncover molecular biomarkers that bridge NAFLD to HCC. Through identifying critical genes and pathways, our research seeks to advance early detection and develop targeted therapies, potentially improving prognosis and personalizing treatment for NAFLD-HCC patients. Objective: Identify key genes that differ between NAFLD and HCC; Analyze these genes to understand their roles in disease progression; Validate the functions of these genes in NAFLD to HCC transition. Methods: Initially, we identified a set of genes differentially expressed in both NAFLD and HCC using second-generation sequencing data from the GEO and TCGA databases. We then employed a Cox proportional hazards model and a Lasso regression model, applying machine learning techniques to the large sample data from TCGA. This approach was used to screen for key disease-related genes, and an external dataset was utilized for model validation. Additionally, pseudo-temporal sequencing analysis of single-cell sequencing data was performed to further examine the variations in these genes in NAFLD and HCC. Results: The machine learning analysis identified IGSF3, CENPW, CDT1, and CDC6 as key genes. Furthermore, constructing a machine learning model for CDT1 revealed it to be the most critical gene, with model validation yielding an ROC value greater than 0.80. The single-cell sequencing data analysis confirmed significant variations in the four predicted key genes between the NAFLD and HCC groups. Conclusion: Our study underscores the pivotal role of CDT1 in the progression from NAFLD to HCC. This finding opens new avenues for early diagnosis and targeted therapy of HCC, highlighting CDT1 as a potential therapeutic target.

Mitochondrial genome study of Camellia oleifera revealed the tandem conserved gene cluster of nad5-nads in evolution.

Camellia oleifera is a kind of high-quality oil supply species. Its seeds contain rich unsaturated fatty acids and antioxidant active ingredients, which is a kind of high-quality edible oil. In this study, we used bioinformatics methods to decipher a hexaploid Camellia oil tree's mitochondrial (mt) genome based on second-generation sequencing data. A 709,596 bp circular map of C. oleifera mt genome was found for the first time. And 74 genes were annotated in the whole genome. Mt genomes of C. oleifera and three Theaceae species had regions with high similarity, including gene composition and gene sequence. At the same time, five conserved gene pairs were found in 20 species. In all of the mt genomes, most of nad genes existed in tandem pairs. In addition, the species classification result, which, according to the gene differences in tandem with nad5 genes, was consistent with the phylogenetic tree. These initial results provide a valuable basis for the further researches of Camellia oleifera and a reference for the systematic evolution of plant mt genomes.

Long-read RNA sequencing can probe organelle genome pervasive transcription.

40years ago, organelle genomes were assumed to be streamlined and, perhaps, unexciting remnants of their prokaryotic past. However, the field of organelle genomics has exposed an unparallel diversity in genome architecture (i.e. genome size, structure, and content). The transcription of these eccentric genomes can be just as elaborate - organelle genomes are pervasively transcribed into a plethora of RNA types. However, while organelle protein-coding genes are known to produce polycistronic transcripts that undergo heavy posttranscriptional processing, the nature of organelle noncoding transcriptomes is still poorly resolved. Here, we review how wet-lab experiments and second-generation sequencing data (i.e. short reads) have been useful to determine certain types of organelle RNAs, particularly noncoding RNAs. We then explain how third-generation (long-read) RNA-Seq data represent the new frontier in organelle transcriptomics. We show that public repositories (e.g. NCBI SRA) already contain enough data for inter-phyla comparative studies and argue that organelle biologists can benefit from such data. We discuss the prospects of using publicly available sequencing data for organelle-focused studies and examine the challenges of such an approach. We highlight that the lack of a comprehensive database dedicated to organelle genomics/transcriptomics is a major impediment to the development of a field with implications in basic and applied science.

Identification macrophage signatures in prostate cancer by single-cell sequencing and machine learning

BackgroundThe tumor microenvironment (TME) encompasses a variety of cells that influence immune responses and tumor growth, with tumor-associated macrophages (TAM) being a crucial component of the TME. TAM can guide prostate cancer in different directions in response to various external stimuli.MethodsFirst, we downloaded prostate cancer single-cell sequencing data and second-generation sequencing data from multiple public databases. From these data, we identified characteristic genes associated with TAM clusters. We then employed machine learning techniques to select the most accurate TAM gene set and developed a TAM-related risk label for prostate cancer. We analyzed the tumor-relatedness of the TAM-related risk label and different risk groups within the population. Finally, we validated the accuracy of the prognostic label using single-cell sequencing data, qPCR, and WB assays, among other methods.ResultsIn this study, the TAM_2 cell cluster has been identified as promoting the progression of prostate cancer, possibly representing M2 macrophages. The 9 TAM feature genes selected through ten machine learning methods and demonstrated their effectiveness in predicting the progression of prostate cancer patients. Additionally, we have linked these TAM feature genes to clinical pathological characteristics, allowing us to construct a nomogram. This nomogram provides clinical practitioners with a quantitative tool for assessing the prognosis of prostate cancer patients.ConclusionThis study has analyzed the potential relationship between TAM and PCa and established a TAM-related prognostic model. It holds promise as a valuable tool for the management and treatment of PCa patients.

Novel kinase 1 regulates CD8+T cells as a potential therapeutic mechanism for idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a rare, chronic and progressively worsening lung disease that poses a significant threat to patient prognosis, with a mortality rate exceeding that of some common malignancies. Effective methods for early diagnosis and treatment remain for this condition are elusive. In our study, we used the GEO database to access second-generation sequencing data and associated clinical information from IPF patients. By utilizing bioinformatics techniques, we identified crucial disease-related genes and their biological functions, and characterized their expression patterns. Furthermore, we mapped out the immune landscape of IPF, which revealed potential roles for novel kinase 1 and CD8+T cells in disease progression and outcome. These findings can aid the development of new strategies for the clinical diagnosis and treatment of IPF.

Targeting HDAC9 Contributes to Degradation of MLL Fusion Oncoproteins in KMT2A-Rearranged Acute Myeloid Leukemia

Acute myeloid leukemia with MLL rearrangement (MLLr-AML) is a highly aggressive subtype of AML. Existing treatment strategies are nonspecific and ineffective. The MLL fusion gene is one of the driver oncogenes in leukemia and is central to the pathogenesis of MLLr-AML, and more research has recently begun to focus on targeting MLL fusion proteins. Targeting MLL fusion proteins has been shown to have a tumor suppressor effect, demonstrating efficacy in preclinical models of MLLr-AML, and in 2022 Scott A Armstrong ‘s team suggested that degradation of MLL-AF9 can cause an increase in cell differentiation and apoptosis, confirming the efficacy of targeting MLL fusions. However, specific targets that degrade MLL fusion proteins as well as clinically translatable targeted therapies are still lacking and need to be further explored. Study confirmed that MLL-rearranged ALL cells are highly sensitive to the broad-spectrum HDAC inhibitor panobinostat. A recent clinical study by Mireia Camós’ team proposed that HDAC9 has a significantly high expression in childhood MLL-rearranged B-cell precursor acute lymphoblastic leukemia (BCP-ALL) and AML, but that article did not address any mechanistic studies. The potential value of HDAC9 in adult lymphoid hematologic diseases has been gradually revealed, however, the expression profile and precise molecular mechanisms of HDAC9 in adult myeloid hematologic tumors, have not been reported, which deserves to be further explored. In order to investigate the expression and role of HDAC9 in MLLr-AML, we analyzed the second-generation sequencing data from the Beat AML dataset and found that HDAC9 has a significantly high expression in MLLr-AML, while only HDAC9 is characterized by this feature in HDAC family molecules. Further we analyzed the data of 300 adult AML specimens in our hospital (including 20 MLLr-AML patients), and the results further confirmed that only HDAC9 among the HDAC family had a significantly higher expression level in the MLLr-AML patient group than that in the Non-MLLr-AML patient group (P<0.001), and the high expression of HDAC9 in the MLLr-AML patient group was a common phenomenon and not limited to a particular class of MLL chaperone molecules. Further studies revealed that overexpression of MLL fusion proteins in HEK293T could cause up-regulation of HDAC9 protein levels, and this experiment clarified the direct correlation between the MLL fusion genes and the high expression of HDAC9. The HDAC IIa inhibitor (TMP-269), which can target HDAC9, was significantly more sensitive in MLLr-AML cell lines than in Non-MLLr-AML cell lines, and also that MLLr-AML cell survival was dependent on HDAC9, and that knockdown of HDAC9 induced an increase in apoptosis and a slowdown in proliferation in MLLr-AML cells. We subsequently demonstrated that knockdown of HDAC9 downregulates the expression of MLL fusion proteins through degradation of MLL proteins. Furthermore, when exploring therapeutic options for targeting MLLr-AML, we found that combining the BCL-2 inhibitor Venetoclax (VEN) with an MLL-Menin specific inhibitor (MEN1i) specifically downregulated the expression of HDAC9 and had a favorable synergistic killing effect on MLLr-AML in both in vitro and in vivo models, further suggesting an important role of HDAC9 in the treatment of MLLr-AML. To sum up, through this study, we can shed light on the role of specific HDAC molecules in MLLr-AML and provide a new potential target for the degradation of MLL fusion protein to eradicate MLLr-AML.

Full-length transcriptome and analysis of bmp-related genes in Platypharodon extremus

Platypharodon extremus is an endemic species on the Qinghai–Tibet Plateau. As a secondary protected species in China, the basic genomic information of this species has not yet been reported. Here, through third-generation sequencing, the full-length transcriptome of P. extremus was obtained. We identified 323,290 CCS sequences, and a total of 50,083 unigenes were extracted after correction with second-generation sequencing data and the removal of redundant reads. A total of 50,067 transcripts were annotated with the various databases. Based on the sequence information, three members in the bone morphogenetic proteins (bmps) family and their receptors, were identified. We found that the special structures of these proteins (zinc-dependent metalloproteinase domain, CUB domains, EGF-like domains and TGF-β domain) are highly conserved in fish and that they are closely evolutionarily related to the bmps and bmp receptors of Cyprinidae fishes. This is the first study to sequence the full-length transcriptome of P. extremus, which will help us to further understand its biology.

Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction

Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases worldwide. Advances in genomics have provided new ideas for the development of novel molecular biomarkers of potential clinical value for AMI.MethodsBased on microarray data from a public database, differential analysis and functional enrichment analysis were performed to identify aberrantly expressed genes in AMI and their potential functions. CIBERSORT was used for immune landscape analysis. We also obtained whole blood samples of 3 patients with AMI and performed second-generation sequencing (SGS) analysis. Weighted gene co-expression network analysis (WGCNA) and cross-tabulation analysis identified AMI-related key genes. Receiver operating characteristic (ROC) curves were used to assess the diagnostic power of key genes. Single-gene gene set enrichment analysis (GSEA) revealed the molecular mechanisms of diagnostic indicators.ResultsA total of 53 AMI-related DEGs from a public database were obtained and found to be involved in immune cell activation, immune response regulation, and cardiac developmental processes. CIBERSORT confirmed that the immune microenvironment was altered between AMI and normal samples. A total of 77 hub genes were identified by WGCNA, and 754 DEGs were obtained from own SGS data. Seven diagnostic indicators of AMI were obtained, namely GZMA, NKG7, TBX21, TGFBR3, SMAD7, KLRC4, and KLRD1. The single-gene GSEA suggested that the diagnostic indicators seemed to be closely implicated in cell cycle, immune response, cardiac developmental, and functional regulatory processes.ConclusionThe present study provides new diagnostic indicators for AMI and further confirms the feasibility of the results of genome-wide gene expression analysis.

Discovery and Verification of Key Liver Cancer Genes and Alternative Splicing Events Based on Second-Generation Sequencing Data Analysis

Hepatocellular carcinoma (HCC) is the most common malignant liver disease in the world. Existing screening and early diagnosis methods are not highly sensitive for HCC, and patients are likely to develop the disease to the middle and advanced stages before being diagnosed. Therefore, finding new and efficient diagnosis and treatment methods has become an urgent problem. We aimed at finding and verifying new liver cancer markers by combining informatics analysis with experimental exploration to provide new ideas and methods for the diagnosis and treatment of clinical liver cancer. We used two different bioinformatic pipelines to analyze sequencing data of clinical liver cancer samples and identify differentially expressed genes and key variants after combining them with The Cancer Genome Atlas sequencing data. Then, we explored the functions and mechanisms of the key variants to identify potential liver cancer markers. Through bioinformatic analysis of sequencing data, 139 differentially expressed genes were found, including 53 upregulated genes and 86 downregulated genes. Through enrichment and alternative splicing event analysis of sequencing data, we found nine key variants with exon skipping events. Metallothionein 1E (MT1E)-203 was found to be a key variant that influenced cell proliferation through the p53 cell cycle pathway through cell viability and proliferation assays, and MT1E-203 lost the ability to bind two zinc ions due to exon skipping according to the structure prediction of MT1E-203. MT1E-203 is a potential biomarker for HCC and may play an important role in the diagnosis and treatment of HCC.

Analysis of whole-exome data of cfDNA and the tumor tissue of non-small cell lung cancer.

BackgroundNon-small cell lung cancer (NSCLC) has the highest cancer mortality rate in the world, but currently there is no effective method of dynamic monitoring. Gene mutation is an important factor in tumorigenesis and can be detected using high-throughput sequencing technology. This study aimed to analyze the driving genes in the tumor of NSCLC patients by whole exon sequencing, and to compare and analyze the subclones of the tumor at different time points.MethodsWe collected 87 cases of NSCLC tumor tissues, para-cancer tissues, and peripheral blood samples for detecting cell-free DNAs (cfDNAs) from January 2016 to December 2018, and whole-exome sequencing was performed. The gene mutation map of NSCLC was drawn in detail by second-generation sequencing data analysis and new driver genes were found. In addition, we performed a subclonal analysis of tumors from different stages of the same patient to further describe the tumor heterogeneity.ResultsWe found that the clonal analysis obtained by cfDNA detection was similar to the clonal analysis of the tissue samples, so real-time monitoring of tumor changes can be carried out through monitoring cfDNA.ConclusionsThis study provides evidence for studying the gene mutation information of NSCLC and shows the importance of cfDNA in the analysis of tumor subcloning information.

Accurate haplotype-resolved assembly reveals the origin of structural variants for human trios.

MotivationAchieving a near complete understanding of how the genome of an individual affects the phenotypes of that individual requires deciphering the order of variations along homologous chromosomes in species with diploid genomes. However, true diploid assembly of long-range haplotypes remains challenging.ResultsTo address this, we have developed Haplotype-resolved Assembly for Synthetic long reads using a Trio-binning strategy, or HAST, which uses parental information to classify reads into maternal or paternal. Once sorted, these reads are used to independently de novo assemble the parent-specific haplotypes. We applied HAST to cobarcoded second-generation sequencing data from an Asian individual, resulting in a haplotype assembly covering 94.7% of the reference genome with a scaffold N50 longer than 11 Mb. The high haplotyping precision (∼99.7%) and recall (∼95.9%) represents a substantial improvement over the commonly used tool for assembling cobarcoded reads (Supernova), and is comparable to a trio-binning-based third generation long-read-based assembly method (TrioCanu) but with a significantly higher single-base accuracy [up to 99.99997% (Q65)]. This makes HAST a superior tool for accurate haplotyping and future haplotype-based studies.Availability and implementationThe code of the analysis is available at https://github.com/BGI-Qingdao/HASTSupplementary informationSupplementary data are available at Bioinformatics online.

A case report of the differential diagnosis of Cellulosimicrobium cellulans-infected endocarditis combined with intracranial infection by conventional blood culture and second-generation sequencing

BackgroundCellulosimicrobium cellulans is a gram-positive filamentous bacterium found primarily in soil and sewage that rarely causes human infection, especially in previously healthy adults, but when it does, it often indicates a poor prognosis.Case presentationWe report a case of endocarditis and intracranial infection caused by C. cellulans in a 52-year-old woman with normal immune function and no implants in vivo. The patient started with a febrile headache that progressed to impaired consciousness after 20 days, and she finally died after treatment with vancomycin combined with rifampicin. C. cellulans was isolated from her blood cultures for 3 consecutive days after her admission; however, there was only evidence of C. cellulans sequences for two samples in the second-generation sequencing data generated from her peripheral blood, which were ignored by the technicians. No C. cellulans bands were detected in her cerebrospinal fluid by second-generation sequencing.ConclusionsSecond-generation sequencing seems to have limitations for certain specific strains of bacteria.

Linking De Novo Assembly Results with Long DNA Reads Using the dnaasm-link Application.

Currently, third-generation sequencing techniques, which make it possible to obtain much longer DNA reads compared to the next-generation sequencing technologies, are becoming more and more popular. There are many possibilities for combining data from next-generation and third-generation sequencing. Herein, we present a new application called dnaasm-link for linking contigs, the result of de novo assembly of second-generation sequencing data, with long DNA reads. Our tool includes an integrated module to fill gaps with a suitable fragment of an appropriate long DNA read, which improves the consistency of the resulting DNA sequences. This feature is very important, in particular for complex DNA regions. Our implementation is found to outperform other state-of-the-art tools in terms of speed and memory requirements, which may enable its usage for organisms with a large genome, something which is not possible in existing applications. The presented application has many advantages: (i) it significantly optimizes memory and reduces computation time; (ii) it fills gaps with an appropriate fragment of a specified long DNA read; (iii) it reduces the number of spanned and unspanned gaps in existing genome drafts. The application is freely available to all users under GNU Library or Lesser General Public License version 3.0 (LGPLv3). The demo application, Docker image, and source code can be downloaded from project homepage.

ADAR1 Editing and its Role in Cancer.

It is well established that somatic mutations and escape of immune disruption are two essential factors in cancer initiation and progression. With an increasing number of second-generation sequencing data, transcriptomic modifications, so called RNA mutations, are emerging as significant forces that drive the transition from normal cell to malignant tumor, as well as providing tumor diversity to escape an immune attack. Editing of adenosine to inosine (A-to-I) in double-stranded RNA, catalyzed by adenosine deaminases acting on RNA (ADARs), is one dynamic modification that in a combinatorial manner can give rise to a very diverse transcriptome. Since the cell interprets inosine as guanosine (G), A-to-I editing can result in non-synonymous codon changes in transcripts as well as yield alternative splicing, but also affect targeting and disrupt maturation of microRNAs. ADAR-mediated RNA editing is essential for survival in mammals, however, its dysregulation causes aberrant editing of its targets that may lead to cancer. ADAR1 is commonly overexpressed, for instance in breast, lung, liver and esophageal cancer as well as in chronic myelogenous leukemia, where it promotes cancer progression. It is well known that ADAR1 regulates type I interferon (IFN) and its induced gene signature, which are known to operate as a significant barrier to tumor formation and progression. Adding to the complexity, ADAR1 expression is also regulated by IFN. In this review, we discussed the regulatory mechanisms of ADAR1 during tumorigenesis through aberrant editing of specific substrates. Additionally, we hypothesized that elevated ADAR1 levels play a role in suppressing an innate immunity response in cancer cells.

Full-Length Transcriptome Sequencing and Modular Organization Analysis of the Naringin/Neoeriocitrin-Related Gene Expression Pattern in Drynaria roosii.

Drynaria roosii (Nakaike) is a traditional Chinese medicinal fern, known as 'GuSuiBu'. The effective components, naringin and neoeriocitrin, share a highly similar chemical structure and medicinal function. Our HPLC-tandem mass spectrometry (MS/MS) results showed that the accumulation of naringin/neoeriocitrin depended on specific tissues or ages. However, little was known about the expression patterns of naringin/neoeriocitrin-related genes involved in their regulatory pathways. Due to a lack of basic genetic information, we applied a combination of single molecule real-time (SMRT) sequencing and second-generation sequencing (SGS) to generate the complete and full-length transcriptome of D. roosii. According to the SGS data, the differentially expressed gene (DEG)-based heat map analysis revealed that naringin/neoeriocitrin-related gene expression exhibited obvious tissue- and time-specific transcriptomic differences. Using the systems biology method of modular organization analysis, we clustered 16,472 DEGs into 17 gene modules and studied the relationships between modules and tissue/time point samples, as well as modules and naringin/neoeriocitrin contents. We found that naringin/neoeriocitrin-related DEGs distributed in nine distinct modules, and DEGs in these modules showed significantly different patterns of transcript abundance to be linked to specific tissues or ages. Moreover, weighted gene co-expression network analysis (WGCNA) results further identified that PAL, 4CL and C4H, and C3H and HCT acted as the major hub genes involved in naringin and neoeriocitrin synthesis, respectively, and exhibited high co-expression with MYB- and basic helix-leucine-helix (bHLH)-regulated genes. In this work, modular organization and co-expression networks elucidated the tissue and time specificity of the gene expression pattern, as well as hub genes associated with naringin/neoeriocitrin synthesis in D. roosii. Simultaneously, the comprehensive transcriptome data set provided important genetic information for further research on D. roosii.

BAUM: improving genome assembly by adaptive unique mapping and local overlap-layout-consensus approach.

It is highly desirable to assemble genomes of high continuity and consistency at low cost. The current bottleneck of draft genome continuity using the second generation sequencing (SGS) reads is primarily caused by uncertainty among repetitive sequences. Even though the single-molecule real-time sequencing technology is very promising to overcome the uncertainty issue, its relatively high cost and error rate add burden on budget or computation. Many long-read assemblers take the overlap-layout-consensus (OLC) paradigm, which is less sensitive to sequencing errors, heterozygosity and variability of coverage. However, current assemblers of SGS data do not sufficiently take advantage of the OLC approach. Aiming at minimizing uncertainty, the proposed method BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can (i) perform reference-assisted assembly based on the genome of a close species (ii) or improve the results of existing assemblies that are obtained based on short or long sequencing reads. The tests on two eukaryote genomes, a wild rice Oryza longistaminata and a parrot Melopsittacus undulatus, show that BAUM achieved substantial improvement on genome size and continuity. Besides, BAUM reconstructed a considerable amount of repetitive regions that failed to be assembled by existing short read assemblers. We also propose statistical approaches to control the uncertainty in different steps of BAUM. http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum. Supplementary data are available at Bioinformatics online.

Abstract 5289: Enhance both precision and sensitivity of fusion gene detection by hybrid sequencing

Abstract Background: New Third Generation Sequencing (TGS) techniques, such as PacBio, can provide very informative insights into the transcriptome, such as expression of fusion genes/fusion transcripts from cancer samples. However, the currently available fusion genes analysis tools are for Second Generation Sequencing (SGS) data, where the short read length and unreliable alignments can lead to uncertain accuracy of fusion gene detections. Hybrid-Seq, which integrates SGS short read data into the analysis of TGS long read data, can complement the strengths of both and thus improve the overall performance and resolution of the output data. It also reduces the required amount of TGS data and thus the sequencing cost. Recently, we developed and reported on a Hybrid-Seq approach, IDP-fusion and the results of the proof-of-concept application to MCF-7 data. We demonstrated that IDP-fusion can identify fusions genes with much higher precision than SGS-based approaches. Although the sensitivity is comparable to the most sensitive SGS-only method, a significant proportion of experimentally verified gold standard fusion genes had yet to be identified by IDP-fusion. It indicated an opportunity to enhance the sensitivity of IDP-fusion while retaining the unparalleled precision of the results. Method: Here we present an innovative Hybrid-Seq approach which extends IDP-fusion, to filtered fusion gene candidates predicted by SGS short read alignments. The fusion gene candidates are verified by the presence of a TGS long read better aligned to an artificial chromosome created from the fusion candidate than any single genome locus. We applied IDP-fusion to a Hybrid-Seq data from the MCF-7 breast cancer cell line, including Illumina SGS data and a lately TGS data generated by PacBio P5-C3 sequencing chemistry. The new IDP-fusion considered fusion candidates reported by several popular SGS tools (TopHat-Fusion, SOAPfuse, TRUP, FusionMap, and deFuse). We compared performance of our new tool to the original IDP-fusion, and the SGS-only approaches. Results: The new algorithm of IDP-fusion improved the sensitivity from 33.8% to 54.9%. This is higher than the most sensitive SGS-only tool (deFuse, 38.0%), which is achieved at the cost of a low precision of 13.8%. The improved IDP-fusion retains a precision of 60.9%, which is only down slightly from the original IDP-fusion at 68.6%. This tradeoff is acceptable when considering the overall accuracy described by F-score for IDP-fusion. The F-score has increased from 45.3% to 57.8%, which is also considerably better than the best F-score achieved by SGS-only methods (32.8%). Conclusions: Fusion candidates identified directly from SGS reads can be screened using alignments of TGS long reads, and supplement fusion candidates detected from long reads. Comparing to SGS-only methods, this Hybrid-Seq approach provides much more sensitive and more accurate reports on the fusion genes. Citation Format: Jason L. Weirather, Tyson A. Clark, Elizabeth Tseng, Jonas Korlach, Kin Fai Au. Enhance both precision and sensitivity of fusion gene detection by hybrid sequencing. [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 5289.

Mining microsatellites for Gray’s beaked whale from second-generation sequencing data

We used three second-generation sequencing platforms to develop 12 microsatellite markers for Gray's beaked whale (Mesoplodon grayi). There was a strong correlation between the amount of sequence obtained from each platform and the number of microsatellites recovered. In order to design reliable primers we found that it was important in all cases to eliminate low quality reads and trim sequences so that 80 % of each sequence had a PHRED score of (20. We found that tri- and tetranucleo- tide repeats produced less stutter enabling robust peak- calling and consistent genotyping. The microsatellites developed here will be useful for the population genetics and conservation studies of Gray's beaked whales.

A comprehensive evaluation of assembly scaffolding tools

BackgroundGenome assembly is typically a two-stage process: contig assembly followed by the use of paired sequencing reads to join contigs into scaffolds. Scaffolds are usually the focus of reported assembly statistics; longer scaffolds greatly facilitate the use of genome sequences in downstream analyses, and it is appealing to present larger numbers as metrics of assembly performance. However, scaffolds are highly prone to errors, especially when generated using short reads, which can directly result in inflated assembly statistics.ResultsHere we provide the first independent evaluation of scaffolding tools for second-generation sequencing data. We find large variations in the quality of results depending on the tool and dataset used. Even extremely simple test cases of perfect input, constructed to elucidate the behaviour of each algorithm, produced some surprising results. We further dissect the performance of the scaffolders using real and simulated sequencing data derived from the genomes of Staphylococcus aureus, Rhodobacter sphaeroides, Plasmodium falciparum and Homo sapiens. The results from simulated data are of high quality, with several of the tools producing perfect output. However, at least 10% of joins remains unidentified when using real data.ConclusionsThe scaffolders vary in their usability, speed and number of correct and missed joins made between contigs. Results from real data highlight opportunities for further improvements of the tools. Overall, SGA, SOPRA and SSPACE generally outperform the other tools on our datasets. However, the quality of the results is highly dependent on the read mapper and genome complexity.

Second‐generation sequencing for gene discovery in the Brassicaceae

The Brassicaceae contains the most diverse collection of agriculturally important crop species of all plant families. Yet, this is one of the few families that do not form functional symbiotic associations with mycorrhizal fungi in the soil for improved nutrient acquisition. The genes involved in this symbiosis were more recently recruited by legumes for symbiotic association with nitrogen-fixing rhizobia bacteria. This study applied second-generation sequencing (SGS) and analysis tools to discover that two such genes, NSP1 (Nodulation Signalling Pathway 1) and NSP2, remain conserved in diverse members of the Brassicaceae despite the absence of these symbioses. We demonstrate the utility of SGS data for the discovery of putative gene homologs and their analysis in complex polyploid crop genomes with little prior sequence information. Furthermore, we show how this data can be applied to enhance downstream reverse genetics analyses. We hypothesize that Brassica NSP genes may function in the root in other plant-microbe interaction pathways that were recruited for mycorrhizal and rhizobial symbioses during evolution.