ResearchPad - bioinformatics https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[TIM, a targeted insertional mutagenesis method utilizing CRISPR/Cas9 in <i>Chlamydomonas reinhardtii</i>]]> https://www.researchpad.co/article/elastic_article_13864 Generation and subsequent analysis of mutants is critical to understanding the functions of genes and proteins. Here we describe TIM, an efficient, cost-effective, CRISPR-based targeted insertional mutagenesis method for the model organism Chlamydomonas reinhardtii. TIM utilizes delivery into the cell of a Cas9-guide RNA (gRNA) ribonucleoprotein (RNP) together with exogenous double-stranded (donor) DNA. The donor DNA contains gene-specific homology arms and an integral antibiotic-resistance gene that inserts at the double-stranded break generated by Cas9. After optimizing multiple parameters of this method, we were able to generate mutants for six out of six different genes in two different cell-walled strains with mutation efficiencies ranging from 40% to 95%. Furthermore, these high efficiencies allowed simultaneous targeting of two separate genes in a single experiment. TIM is flexible with regard to many parameters and can be carried out using either electroporation or the glass-bead method for delivery of the RNP and donor DNA. TIM achieves a far higher mutation rate than any previously reported for CRISPR-based methods in C. reinhardtii and promises to be effective for many, if not all, non-essential nuclear genes.

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<![CDATA[Identification of crucial aberrantly methylated and differentially expressed genes related to cervical cancer using an integrated bioinformatics analysis]]> https://www.researchpad.co/article/elastic_article_13844 Methylation functions in the pathogenesis of cervical cancer. In the present study, we applied an integrated bioinformatics analysis to identify the aberrantly methylated and differentially expressed genes (DEGS), and their related pathways in cervical cancer. Data of gene expression microarrays (GSE9750) and gene methylation microarrays (GSE46306) were gained from Gene Expression Omnibus (GEO) databases. Hub genes were identified by ‘limma’ packages and Venn diagram tool. Functional analysis was conducted by FunRich. Search Tool for the Retrieval of Interacting Genes Database (STRING) was used to analyze protein–protein interaction (PPI) information. Gene Expression Profiling Interactive Analysis (GEPIA), immunohistochemistry staining, and ROC curve analysis were conducted for validation. Gene Set Enrichment Analysis (GSEA) was also performed to identify potential functions.We retrieved two upregulated-hypomethylated oncogenes and eight downregulated-hypermethylated tumor suppressor genes (TSGs) for functional analysis. Hypomethylated and highly expressed genes (Hypo-HGs) were significantly enriched in cell cycle and autophagy, and hypermethylated and lowly expressed genes (Hyper-LGs) in estrogen receptor pathway and Wnt/β-catenin signaling pathway. Estrogen receptor 1 (ESR1), Erythrocyte membrane protein band 4.1 like 3 (EPB41L3), Endothelin receptor B (EDNRB), Inhibitor of DNA binding 4 (ID4) and placenta-specific 8 (PLAC8) were hub genes. Kaplan–Meier method was used to evaluate survival data of each identified gene. Lower expression levels of ESR1 and EPB41L3 were correlated with a shorter survival time. GSEA results showed that ‘cell adhesion molecules’ was the most enriched item. This research inferred the candidate genes and pathways that might be used in the diagnosis, treatment, and prognosis of cervical cancer.

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<![CDATA[Genetic evidence for a species complex within the piranha <i>Serrasalmus maculatus</i> (Characiformes, Serrasalmidae) from three Neotropical river basins based on mitochondrial DNA sequences]]> https://www.researchpad.co/article/elastic_article_13899 Mitochondrial molecular markers (DNA sequences of D-loop, cytochrome b and cytochrome c oxidase I) were employed to characterize populations of the piranha Serrasalmus maculatus from Upper Paraná, Upper Paraguay and Tocantins River basins. D-loop sequences of S. maculatus population from Paraná-Paraguay River basin exhibited tandem repeats of short motifs (12 base pairs) and variable numbers depending on specimens, accounting for length variation. Concatenated mitochondrial sequences suggested that S. maculatus encompasses different mitochondrial DNA lineages. Although sampling was restricted to three river basins, phylogenetic analysis clearly indicated that the species currently recognized as S. maculatus presents high genetic variability. Maximum likelihood and Bayesian analysis clustered S. maculatus populations according to their locations. However, the highest genetic differentiation was identified between populations from Paraná-Paraguay system and Tocantins River basin. Three species delimitation analyses (PTP, GMYC, and ABGD) suggested that there are at least two species among the analyzed populations. The analysis of the mitochondrial sequences evidenced genetic differentiation among populations corresponding to related, but different species, suggesting that at least S. maculatus from the Tocantins River and Paraná-Paraguay River basins are most likely different species. Therefore, S. maculatus should be considered a species complex with morphologically cryptic diversity. An integrative revision is suggested.

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<![CDATA[Post-transcriptional regulation of several biological processes involved in latex production in <i>Hevea brasiliensis</i>]]> https://www.researchpad.co/article/elastic_article_12852 Small RNAs modulate plant gene expression at both the transcriptional and post-transcriptional level, mostly through the induction of either targeted DNA methylation or transcript cleavage, respectively. Small RNA networks are involved in specific plant developmental processes, in signaling pathways triggered by various abiotic stresses and in interactions between the plant and viral and non-viral pathogens. They are also involved in silencing maintenance of transposable elements and endogenous viral elements. Alteration in small RNA production in response to various environmental stresses can affect all the above-mentioned processes. In rubber trees, changes observed in small RNA populations in response to trees affected by tapping panel dryness, in comparison to healthy ones, suggest a shift from a transcriptional to a post-transcriptional regulatory pathway. This is the first attempt to characterise small RNAs involved in post-transcriptional silencing and their target transcripts in Hevea.MethodsGenes producing microRNAs (MIR genes) and loci producing trans-activated small interfering RNA (ta-siRNA) were identified in the clone PB 260 re-sequenced genome. Degradome libraries were constructed with a pool of total RNA from six different Hevea tissues in stressed and non-stressed plants. The analysis of cleaved RNA data, associated with genomics and transcriptomics data, led to the identification of transcripts that are affected by 20–22 nt small RNA-mediated post-transcriptional regulation. A detailed analysis was carried out on gene families related to latex production and in response to growth regulators.ResultsCompared to other tissues, latex cells had a higher proportion of transcript cleavage activity mediated by miRNAs and ta-siRNAs. Post-transcriptional regulation was also observed at each step of the natural rubber biosynthesis pathway. Among the genes involved in the miRNA biogenesis pathway, our analyses showed that all of them are expressed in latex. Using phylogenetic analyses, we show that both the Argonaute and Dicer-like gene families recently underwent expansion. Overall, our study underlines the fact that important biological pathways, including hormonal signalling and rubber biosynthesis, are subject to post-transcriptional silencing in laticifers. ]]> <![CDATA[A non-linear reverse-engineering method for inferring genetic regulatory networks]]> https://www.researchpad.co/article/elastic_article_12816 Hematopoiesis is a highly complex developmental process that produces various types of blood cells. This process is regulated by different genetic networks that control the proliferation, differentiation, and maturation of hematopoietic stem cells (HSCs). Although substantial progress has been made for understanding hematopoiesis, the detailed regulatory mechanisms for the fate determination of HSCs are still unraveled. In this study, we propose a novel approach to infer the detailed regulatory mechanisms. This work is designed to develop a mathematical framework that is able to realize nonlinear gene expression dynamics accurately. In particular, we intended to investigate the effect of possible protein heterodimers and/or synergistic effect in genetic regulation. This approach includes the Extended Forward Search Algorithm to infer network structure (top-down approach) and a non-linear mathematical model to infer dynamical property (bottom-up approach). Based on the published experimental data, we study two regulatory networks of 11 genes for regulating the erythrocyte differentiation pathway and the neutrophil differentiation pathway. The proposed algorithm is first applied to predict the network topologies among 11 genes and 55 non-linear terms which may be for heterodimers and/or synergistic effect. Then, the unknown model parameters are estimated by fitting simulations to the expression data of two different differentiation pathways. In addition, the edge deletion test is conducted to remove possible insignificant regulations from the inferred networks. Furthermore, the robustness property of the mathematical model is employed as an additional criterion to choose better network reconstruction results. Our simulation results successfully realized experimental data for two different differentiation pathways, which suggests that the proposed approach is an effective method to infer the topological structure and dynamic property of genetic regulations.

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<![CDATA[The predictive value of PRDM2 in solid tumor: a systematic review and meta-analysis]]> https://www.researchpad.co/article/elastic_article_12811 Many studies have reported the presence of Positive Regulatory/Su(var)3-9, Enhancer-of-zeste and Trithorax Domain 2 (PRDM2) downregulation in cancer. However, its potential as a diagnostic biomarker is still unclear. Hence, a systematic review and meta-analysis were conducted to address this issue.IntroductionAs of 2018, cancer has become the second leading cause of death worldwide. Thus, cancer control is exceptionally vital in reducing mortality. One such example is through early diagnosis of cancer using tumor biomarkers. Having a function as a tumor suppressor gene (TSG), PRDM2 has been linked with carcinogenesis in several solid tumor. This study aims to assess the relationship between PRDM2 downregulation and solid tumor, its relationship with clinicopathological data, and its potential as a diagnostic biomarker. This study also aims to evaluate the quality of the studies, data reliability and confidence in cumulative evidence.Materials & MethodsA protocol of this study is registered at the International Prospective Register of Systematic Reviews (PROSPERO) with the following registration number: CRD42019132156. PRISMA was used as a guideline to conduct this review. A comprehensive electronic search was performed from inception to June 2019 in Pubmed, Cochrane Library, ProQuest, EBSCO and ScienceDirect. Studies were screened and included studies were identified based on the criteria made. Finally, data synthesis and quality assessment were conducted.ResultsThere is a significant relationship between PRDM2 downregulation with solid tumor (RR 4.29, 95% CI [2.58–7.13], P < 0.00001). The overall sensitivity and specificity of PRDM2 downregulation in solid tumors is 84% (95% CI [39–98%]) and 86% (95% CI [71–94%]), respectively. There is a low risk of bias for the studies used. TSA results suggested the presence of marked imprecision. The overall quality of evidence for this study is very low.DiscussionWe present the first meta-analysis that investigated the potential of PRDM2 downregulation as a diagnostic biomarker in solid tumor. In line with previous studies, our results demonstrated that PRDM2 downregulation occurs in solid tumor. A major source of limitation in this study is the small number of studies.ConclusionsOur review suggested that PRDM2 is downregulated in solid tumor. The relationship between PRDM2 downregulation and clinicopathological data is still inconclusive. Although the sensitivity and specificity of PRDM2 downregulation are imprecise, its high values, in addition to the evidence that suggested PRDM2 downregulation in solid tumor, hinted that it might still have a potential to be used as a diagnostic biomarker. In order to further strengthen these findings, more research regarding PRDM2 in solid tumors are encouraged. ]]> <![CDATA[SSD - a free software for designing multimeric mono-, bi- and trivalent shRNAs]]> https://www.researchpad.co/article/elastic_article_12490 RNA interference (RNAi) is a powerful gene silencing technology, widely used in analyses of reverse genetics, development of therapeutic strategies and generation of biotechnological products. Here we present a free software tool for the rational design of RNAi effectors, named siRNA and shRNA designer (SSD). SSD incorporates our previously developed software Strand Analysis to construct template DNAs amenable for the large scale production of mono-, bi- and trivalent multimeric shRNAs, via in vitro rolling circle transcription. We tested SSD by creating a trivalent multimeric shRNA against the vitellogenin gene of Apis mellifera. RT-qPCR analysis revealed that our molecule promoted a decrease in more than 50% of the target mRNA, in a dose-dependent manner, when compared to the control group. Thus, SSD software allows the easy design of multimeric shRNAs, for single or multiple simultaneous knockdowns, which is especially interesting for studies involving large amounts of double-stranded molecules.

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<![CDATA[Metabarcoding reveals that a non-nutritive sweetener and sucrose yield similar gut microbiota patterns in Wistar rats]]> https://www.researchpad.co/article/elastic_article_12460 The effects of non-nutritive sweeteners (NNS) on the gut microbiota are an area of increasing research interest due to their potential influence on weight gain, insulin resistance, and inflammation. Studies have shown that mice and rats fed saccharin develop weight gain and metabolic alterations, possibly related to changes in gut microbiota. Here, we hypothesized that chronic exposure to a commercial NNS would change the gut microbiota composition in Wistar rats when compared to sucrose exposure. To test this hypothesis, Wistar rats were fed either NNS- or sucrose-supplemented yogurt for 17 weeks alongside standard chow (ad libitum). The gut microbiome was assessed by 16S rDNA deep sequencing. Assembly and quantification were conducted using the Brazilian Microbiome Project pipeline for Ion Torrent data with modifications. Statistical analyses were performed in the R software environment. We found that chronic feeding of a commercial NNS-sweetened yogurt to Wistar rats, within the recommended dose range, did not significantly modify gut microbiota composition in comparison to sucrose-sweetened yogurt. Our findings do not support the hypothesis that moderate exposure to NNS is associated with changes in gut microbiota pattern compared to sucrose, at least in this experimental model.

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<![CDATA[Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis]]> https://www.researchpad.co/article/elastic_article_12440 For a better interpretation of variants, evidence-based databases, such as ClinVar, compile data on the presumed relationships between variants and phenotypes. In this study, we aimed to analyze the pattern of sequencing depth in variants from whole-exome sequencing data in the 1000 Genomes project phase 3, focusing on the variants present in the ClinVar database that were predicted to affect protein-coding regions. We demonstrate that the distribution of the sequencing depth varies across different sequencing centers (pair-wise comparison, p < 0.001). Most importantly, we found that the distribution pattern of sequencing depth is specific to each facility, making it possible to correctly assign 96.9% of the samples to their sequencing center. Thus, indicating the presence of a systematic bias, related to the methods used in the different facilities, which generates significant variations in breadth and depth in whole-exome sequencing data in clinically relevant regions. Our results show that methodological differences, leading to significant heterogeneity in sequencing depth, may potentially influence the accuracy of genetic diagnosis. Furthermore, our findings highlight how it is still challenging to integrate results from different sequencing centers, which may also have an impact on genomic research.

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<![CDATA[Boundaries in metagenomic screenings using <i>lac</i>Zα-based vectors]]> https://www.researchpad.co/article/elastic_article_12436 Metagenomics approaches have been of high relevance for providing enzymes used in diverse industrial applications. In the current study, we have focused on the prospection of protease and glycosyl hydrolase activities from a soil sample by using the lacZα -based plasmid pSEVA232. For this, we used a functional screen based on skimmed milk agar and a pH indicator dye for detection of both enzymes, as previously reported in literature. Although we effectively identified positive clones in the screenings, subsequent experiments revealed that this phenotype was not because of the hydrolytic activity encoded in the metagenomic fragments, but rather due to the insertion of small metagenomic DNA fragments in frame within the coding region of the lacZ gene present in the original vector. Analyses of the thermodynamic stability of mRNA secondary structures indicated that recovering of positive clones was probably due to higher expression levels of the chimeric lacZα-genes in respect to the original from empty vector. We concluded that this method has a higher tendency for recovery false positive clones, when used in combination with a lacZα-based vector. As these vectors are massively used in functional metagenomic screenings, we highlight the importance of reporting boundaries in established metagenomic screenings methodologies.

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<![CDATA[Identification of LincRNA from <i>Dermatophagoides farinae</i> (Acari: Pyroglyphidae) for Potential Allergen-Related Targets]]> https://www.researchpad.co/article/elastic_article_12423 Long noncoding RNAs (lncRNAs), especially their important subclass of long intergenic noncoding RNAs (lincRNAs), have been identified in some insects. They play important roles in the regulation of biological processes, such as immune response or cell differentiation and as possible evolutionary precursors for protein coding genes. House dust mites (HDMs) are recognized as allergenic mites because allergens are found in their feces and bodies. Dermatophagoides farinae is one of the most important pyroglyphid mites because of its abundance in the household. To determine if lincRNAs can regulate allergen presentation in HDMs, we analyzed RNA-seq data for HDMs. We identified 11 lincRNAs that are related to mRNAs coding for allergens in HDMs. Using qRT-PCR, we amplified 10 lincRNAs and their putative target allergen-encoding mRNAs, confirming expression of these lincRNAs and allergen genes. The results suggest that lincRNAs might be involved in the regulation of allergen production in HDMs and might represent potential acaricidal candidates to inhibit mite allergen production.

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<![CDATA[Transcriptional regulators and regulatory pathways involved in prostate gland adaptation to a hypoandrogen environment]]> https://www.researchpad.co/article/elastic_article_12401 Anti-androgen therapies, including orchiectomy, are effective at promoting prostate cancer remission, but are followed by progression to the more aggressive castration-resistant prostate cancer (CRPC). Castration promotes gland and tumor shrinkage. However, prostate adaptation to androgen deprivation involves striking parallel events, all requiring changes in gene expression. We hypothesized that transcription factors (TF) and other transcription-related genes are needed to orchestrate those changes. In this work, downstream analysis using bioinformatic tools and published microarray data allowed us to identify sixty transcriptional regulators (including 10 TF) and to integrate their function in physiologically relevant networks. Functional associations revealed a connection between Arnt, Bhlhe41 and Dbp circadian rhythm genes with the Ar circuitry and a small gene network centered in Pex14, which might indicate a previously unanticipated metabolic shift. We have also identified human homologs and mapped the corresponding genes to human chromosome regions commonly affected in prostate cancer, with particular attention to the PTEN/HHEX/MXI1 cluster at 10q23-25 (frequently deleted in PCa) and to MAPK1 at 22q11.21 (delete in intermediate risk but not in high risk PCa). Twenty genes were found mutated or with copy number alterations in at least five percent of three cancer cohorts and six of them (PHOX2A, NFYC, EST2, EIF2S1, SSRP1 and PARP1) associated with impacted patient survival. These changes are specific to the adaptation to the hypoandrogen environment and seem important for the progression to CRPC when mutated.

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<![CDATA[A comparison between SOLiD 5500XLand Ion Torrent PGM-derived miRNA expression profiles in two breast cell lines]]> https://www.researchpad.co/article/elastic_article_10869 Next-generation sequencing (NGS) platforms allow the analysis of hundreds of millions of molecules in a single sequencing run, revolutionizing many research areas. NGS-based microRNA studies enable expression quantification in unprecedented scale without the limitations of closed-platforms. Yet, whereas a massive amount of data produced by these platforms is available, comparisons of quantification/discovery capabilities between platforms are still lacking. Here we compare two NGS-platforms: SOLiD and PGM, by evaluating their microRNA identification/quantification capabilities using two breast-derived cell-lines. A high expression correlation (R2 > 0.9) was achieved, encompassing 97% of the miRNAs, and the few discrepancies in miRNA counts were attributable to molecules that have very low expression. Quantification divergences indicative of artefactual representation were seen for 14 miRNAs (higher in SOLiD-reads) and another 10 miRNAs more abundant in PGM-data. An inspection of these revealed an increased and statistically significant count of uracyls and uracyl-stretches for PGM-enriched miRNAs, compared to SOLiD and to the miRBase. In parallel, adenines and adenine-stretches were enriched for SOLiDderived miRNA reads. We conclude that, whereas both platforms are overall consistent and can be used interchangeably for microRNA expression studies, particular sequence features appear to be indicative of specific platform bias, and their presence in microRNAs should be considered for database-analyses.

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<![CDATA[MiR-139-5p influences hepatocellular carcinoma cell invasion and proliferation capacities via decreasing SLITRK4 expression]]> https://www.researchpad.co/article/elastic_article_9224 The microRNA, miR-139-5p, has been proved to play important roles in regulating tumor progression, including prostate cancer, osteosarcoma, esophageal cancer, and so on, but its correlation of hepatocellular carcinoma (HCC) still remains unclear. Here we found that hsa-miR-139-5p (miR-139-5p) was decreased in HCC samples compared with normal liver tissues, and a lower expression of miR-139-5p was connected to a poorer prognosis. Mechanism study indicated that a decreased/increased miR-139-5p could increase/decrease HCC cells invasion and proliferation capacities via increasing SLITRK4 expression, what’s more, the reverse assays also confirmed the conclusion when we knocked down SLITRK4 in the miR-139-5p low-expression cells. Luciferase assay confirmed that miR-139-5p could directly bind to the 3′UTR of SLITRK4 mRNA to regulate its expression. Together, these findings show the importance of miR-139-5p/SLITRK4 pathway in HCC growth and progression and may provide new targets for us to better arrange the progression of HCC.

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<![CDATA[Using case-level context to classify cancer pathology reports]]> https://www.researchpad.co/article/elastic_article_7869 Individual electronic health records (EHRs) and clinical reports are often part of a larger sequence—for example, a single patient may generate multiple reports over the trajectory of a disease. In applications such as cancer pathology reports, it is necessary not only to extract information from individual reports, but also to capture aggregate information regarding the entire cancer case based off case-level context from all reports in the sequence. In this paper, we introduce a simple modular add-on for capturing case-level context that is designed to be compatible with most existing deep learning architectures for text classification on individual reports. We test our approach on a corpus of 431,433 cancer pathology reports, and we show that incorporating case-level context significantly boosts classification accuracy across six classification tasks—site, subsite, laterality, histology, behavior, and grade. We expect that with minimal modifications, our add-on can be applied towards a wide range of other clinical text-based tasks.

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<![CDATA[Personalized analysis of breast cancer using sample-specific networks]]> https://www.researchpad.co/article/elastic_article_8419 Breast cancer is a disease with high heterogeneity. Cancer is not usually caused by a single gene, but by multiple genes and their interactions with others and surroundings. Estimating breast cancer-specific gene–gene interaction networks is critical to elucidate the mechanisms of breast cancer from a biological network perspective. In this study, sample-specific gene–gene interaction networks of breast cancer samples were established by using a sample-specific network analysis method based on gene expression profiles. Then, gene–gene interaction networks and pathways related to breast cancer and its subtypes and stages were further identified. The similarity and difference among these subtype-related (and stage-related) networks and pathways were studied, which showed highly specific for subtype Basal-like and Stages IV and V. Finally, gene pairwise interactions associated with breast cancer prognosis were identified by a Cox proportional hazards regression model, and a risk prediction model based on the gene pairs was established, which also performed very well on an independent validation data set. This work will help us to better understand the mechanism underlying the occurrence of breast cancer from the sample-specific network perspective.

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<![CDATA[fRNAkenseq: a fully powered-by-CyVerse cloud integrated RNA-sequencing analysis tool]]> https://www.researchpad.co/article/elastic_article_8314 Decreasing costs make RNA sequencing technologies increasingly affordable for biologists. However, many researchers who can now afford sequencing lack access to resources necessary for downstream analysis. This means that even as algorithms to process RNA-Seq data improve, many biologists still struggle to manage the sheer volume of data produced by next generation sequencing (NGS) technologies. Scalable bioinformatics tools that exploit multiple platforms are needed to democratize bioinformatics resources in the sequencing era. This is essential for equipping many research groups in the life sciences with the tools to process the increasingly unwieldy datasets they produce.MethodsOne strategy to address this challenge is to develop a modern generation of sequence analysis tools capable of seamless data sharing and communication. Such tools will provide interoperability through offerings of interlinked resources. Systems of interlinked, scalable resources, which often incorporate cloud data storage, are broadly referred to as cyberinfrastructure. Cyberinfrastructure integrated tools will help researchers to robustly analyze large scale datasets by efficiently sharing data burdens across a distributed architecture. Additionally, interoperability will allow emerging tools to cross-adapt features of existing tools. It is important that these tools are designed to be easy to use for biologists.ResultsWe introduce fRNAkenseq, a powered-by-CyVerse RNA sequencing analysis tool that exhibits interoperability with other resources and meets the needs of biologists for comprehensive, easy to use RNA sequencing analysis. fRNAkenseq leverages a complex set of Application Programming Interfaces (APIs) associated with the NSF-funded cyberinfrastructure project, CyVerse, to execute FASTQ-to-differential expression RNA-Seq analyses. Integrating across bioinformatics platforms, fRNAkenseq also exploits cloud integration and cross-talk with another CyVerse associated tool, CoGe. fRNAkenseq offers novel features for the biologist such as more robust and comprehensive pipelines for enrichment than those currently available by default in a single tool, whether they are cloud-based or local installation. Importantly, cross-talk with CoGe allows fRNAkenseq users to execute RNA-Seq pipelines on an inventory of 47,000 archived genomes stored in CoGe or upload their own draft genome. ]]> <![CDATA[Comparative analysis of the complete chloroplast genomes from six Neotropical species of Myrteae (Myrtaceae)]]> https://www.researchpad.co/article/elastic_article_6282 Myrteae is the largest and most diverse tribe within Myrtaceae and represents the majority of its diversity in the Neotropics. Members of Myrteae hold ecological importance in tropical biomes for the provision of food sources for many animal species. Thus, due to its several roles, a growing interest has been addressed to this group. In this study, we report the sequencing and de novo assembly of the complete chloroplast (cp) genomes of six Myrteae species: Eugenia brasiliensis, E. pyriformis, E. nitida, Myrcianthes pungens, Plinia edulis and Psidium cattleianum. We characterized genome structure, gene content, and identified SSRs to detect variation within Neotropical Myrteae. The six newly sequenced plastomes exhibit a typical quadripartite structure, gene content and organization highly conserved among Myrtaceae species. Some differences in genome length, protein-coding genes and non-coding regions were found. Besides, IR boundaries present structural changes among species. Increased sequence diversity was observed in some intergenic regions, suggesting their suitability for investigating intraand interspecific genetic diversity in populational studies. These data also contribute to the improvement of taxa sampling in further phylogenetic investigations to understand Myrtaceae evolution.

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<![CDATA[PISA-SPARKY: an interactive SPARKY plugin to analyze oriented solid-state NMR spectra of helical membrane proteins]]> https://www.researchpad.co/article/N981a32bd-a37b-4315-9117-3eabfe7b2b1c Two-dimensional [15N-1H] separated local field solid-state nuclear magnetic resonance (NMR) experiments of membrane proteins aligned in lipid bilayers provide tilt and rotation angles for α-helical segments using Polar Index Slant Angle (PISA)-wheel models. No integrated software has been made available for data analysis and visualization.ResultsWe have developed the PISA-SPARKY plugin to seamlessly integrate PISA-wheel modeling into the NMRFAM-SPARKY platform. The plugin performs basic simulations, exhaustive fitting against experimental spectra, error analysis and dipolar and chemical shift wave plotting. The plugin also supports PyMOL integration and handling of parameters that describe variable alignment and dynamic scaling encountered with magnetically aligned media, ensuring optimal fitting and generation of restraints for structure calculation.Availability and implementation PISA-SPARKY is freely available in the latest version of NMRFAM-SPARKY from the National Magnetic Resonance Facility at Madison (http://pine.nmrfam.wisc.edu/download_packages.html), the NMRbox Project (https://nmrbox.org) and to subscribers of the SBGrid (https://sbgrid.org). The pisa.py script is available and documented on GitHub (https://github.com/weberdak/pisa.py) along with a tutorial video and sample data.Supplementary information Supplementary data are available at Bioinformatics online. ]]> <![CDATA[atomium—a Python structure parser]]> https://www.researchpad.co/article/N48cdda5b-592b-40b2-a389-9dd18c3d3ef7 Structural biology relies on specific file formats to convey information about macromolecular structures. Traditionally this has been the PDB format, but increasingly newer formats, such as PDBML, mmCIF and MMTF are being used. Here we present atomium, a modern, lightweight, Python library for parsing, manipulating and saving PDB, mmCIF and MMTF file formats. In addition, we provide a web service, pdb2json, which uses atomium to give a consistent JSON representation to the entire Protein Data Bank.Availability and implementationatomium is implemented in Python and its performance is equivalent to the existing library BioPython. However, it has significant advantages in features and API design. atomium is available from atomium.bioinf.org.uk and pdb2json can be accessed at pdb2json.bioinf.org.ukSupplementary information Supplementary data are available at Bioinformatics online. ]]>