De novo construction of a transcriptome for the stink bug crop pest Chinavia impicticornis during late development

Chinavia impicticornis is a neotropical stink bug of economic importance for various crops. Little is known about the development of the species, or the genetic mechanisms that may favor the establishment of populations in cultivated plants. Here, we conduct the first large-scale molecular study of C. impicticornis. Using tissues derived from the genitalia and the rest of the body for two immature stages of both males and females, we generated RNA-seq data, then assembled and functionally annotated a transcriptome. The de novo-assembled transcriptome contained around 400,000 contigs, with an average length of 688 bp. After pruning duplicated sequences and conducting a functional annotation, the final annotated transcriptome comprised 39,478 transcripts, of which 12,665 were assigned to Gene Ontology (GO) terms. These novel datasets will be invaluable for the discovery of molecular processes related to morphogenesis and immature biology. We hope to contribute to the growing body of research on stink bug evolution and development, as well as to the development of biorational pest management solutions.

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De novo construction of a transcriptome for the stink bug crop pest Chinavia impicticornis during late development

10.1101/2020.12.04.412270 ◽

2020 ◽

Author(s):

Bruno C. Genevcius ◽

Tatiana T. Torres

Keyword(s):

Functional Annotation ◽

Large Scale ◽

De Novo ◽

Average Length ◽

Molecular Study ◽

The Body ◽

Cultivated Plants ◽

Stink Bug ◽

Rational Solutions ◽

Males And Females

AbstractChinavia impicticornis is a Neotropical stink-bug (Hemiptera: Pentatomidae) with economic importance for different crops. Little is known about the development of the species, as well as the genetic mechanisms that may favor the establishment of populations in cultivated plants. Here we conduct the first large-scale molecular study with C. impicticornis. We generated RNA-seq data for males and females, at two immature stages, for the genitalia separately and for the rest of the body. We assembled the transcriptome and conduct a functional annotation. De novo assembled transcriptome based on whole bodies and genitalia of males and females contained around 400,000 contigs with an average length of 688 bp. After pruning duplicated sequences and conducting a functional annotation, the final annotated transcriptome comprised 39,478 transcripts of which 12,665 had GO terms assigned. These novel datasets will provide invaluable data for the discovery of molecular processes related to morphogenesis and immature biology. We hope to contribute to the growing research on stink bug evo-devo as well as the development of bio-rational solutions for pest management.

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RNA-Seq reveals divergent gene expression between larvae with contrasting trophic modes in the poecilogonous polychaete Boccardia wellingtonensis

Scientific Reports ◽

10.1038/s41598-021-94646-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Álvaro Figueroa ◽

Antonio Brante ◽

Leyla Cárdenas

Keyword(s):

De Novo ◽

Juvenile Stage ◽

Type I ◽

Rna Seq ◽

Mrna Synthesis ◽

De Novo Transcriptome ◽

Larval Stages ◽

Divergent Gene ◽

Genetic Mechanisms ◽

Planktotrophic Larvae

AbstractThe polychaete Boccardia wellingtonensis is a poecilogonous species that produces different larval types. Females may lay Type I capsules, in which only planktotrophic larvae are present, or Type III capsules that contain planktotrophic and adelphophagic larvae as well as nurse eggs. While planktotrophic larvae do not feed during encapsulation, adelphophagic larvae develop by feeding on nurse eggs and on other larvae inside the capsules and hatch at the juvenile stage. Previous works have not found differences in the morphology between the two larval types; thus, the factors explaining contrasting feeding abilities in larvae of this species are still unknown. In this paper, we use a transcriptomic approach to study the cellular and genetic mechanisms underlying the different larval trophic modes of B. wellingtonensis. By using approximately 624 million high-quality reads, we assemble the de novo transcriptome with 133,314 contigs, coding 32,390 putative proteins. We identify 5221 genes that are up-regulated in larval stages compared to their expression in adult individuals. The genetic expression profile differed between larval trophic modes, with genes involved in lipid metabolism and chaetogenesis over expressed in planktotrophic larvae. In contrast, up-regulated genes in adelphophagic larvae were associated with DNA replication and mRNA synthesis.

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De Novo Transcriptomic Resources in the Brain of Vespa velutina for Invasion Control

Insects ◽

10.3390/insects11020101 ◽

2020 ◽

Vol 11 (2) ◽

pp. 101

Author(s):

Miao Wang ◽

Hanyu Li ◽

Huoqing Zheng ◽

Liuwei Zhao ◽

Xiaofeng Xue ◽

...

Keyword(s):

Large Scale ◽

Target Genes ◽

De Novo ◽

Transcriptome Profiling ◽

Molecular Study ◽

Snp Markers ◽

Nucleotide Polymorphisms ◽

Illumina Hiseq ◽

Vespa Velutina ◽

Genes Encoding

The invasion of Vespa velutina presents a great threat to the agriculture economy, the ecological environment, and human health. An effective strategy for this hornet control is urgently required, but the limited genome information of Vespa velutina restricts the application of molecular-genomic tools for targeted hornet management. Therefore, we conducted large-scale transcriptome profiling of the hornet brain to obtain functional target genes and molecular markers. Using an Illumina HiSeq platform, more than 41 million clean reads were obtained and de novo assembled into 182,087 meaningful unigenes. A total of 56,400 unigenes were annotated against publicly available protein sequence databases and a set of reliable Simple Sequence Repeats (SSRs) and Single Nucleotide Polymorphisms (SNP) markers were developed. The homologous genes encoding crucial behavior regulation factors, odorant binding proteins (OBPs), and vitellogenin, were also identified from highly expressed transcripts. This study provides abundant molecular targets and markers for invasive hornet control and further promotes the genetic and molecular study of Vespa velutina.

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Glutton: large-scale integration of non-model organism transcriptome data for comparative analysis

10.1101/077511 ◽

2016 ◽

Cited By ~ 2

Author(s):

Alan Medlar ◽

Laura Laakso ◽

Andreia Miraldo ◽

Ari Löytynoja

Keyword(s):

Comparative Analysis ◽

Large Scale ◽

De Novo ◽

Sequence Data ◽

Model Organism ◽

Model Organisms ◽

Rna Seq ◽

Reference Species ◽

Wide Range ◽

The Impact

AbstractHigh-throughput RNA-seq data has become ubiquitous in the study of non-model organisms, but its use in comparative analysis remains a challenge. Without a reference genome for mapping, sequence data has to be de novo assembled, producing large numbers of short, highly redundant contigs. Preparing these assemblies for comparative analyses requires the removal of redundant isoforms, assignment of orthologs and converting fragmented transcripts into gene alignments. In this article we present Glutton, a novel tool to process transcriptome assemblies for downstream evolutionary analyses. Glutton takes as input a set of fragmented, possibly erroneous transcriptome assemblies. Utilising phylogeny-aware alignment and reference data from a closely related species, it reconstructs one transcript per gene, finds orthologous sequences and produces accurate multiple alignments of coding sequences. We present a comprehensive analysis of Glutton’s performance across a wide range of divergence times between study and reference species. We demonstrate the impact choice of assembler has on both the number of alignments and the correctness of ortholog assignment and show substantial improvements over heuristic methods, without sacrificing correctness. Finally, using inference of Darwinian selection as an example of downstream analysis, we show that Glutton-processed RNA-seq data give results comparable to those obtained from full length gene sequences even with distantly related reference species. Glutton is available from http://wasabiapp.org/software/glutton/ and is licensed under the GPLv3.

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Compression of short-read sequences using path encoding

10.1101/006551 ◽

2014 ◽

Cited By ~ 1

Author(s):

Carl Kingsford ◽

Rob Patro

Keyword(s):

Large Scale ◽

De Novo ◽

Biological Sequence ◽

Rna Seq ◽

De Bruijn Graphs ◽

Common Task ◽

Meta Analyses ◽

Sequence Compression ◽

Good Compression ◽

Generation Sequencing

Storing, transmitting, and archiving the amount of data produced by next generation sequencing is becoming a significant computational burden. For example, large-scale RNA-seq meta-analyses may now routinely process tens of terabytes of sequence. We present here an approach to biological sequence compression that reduces the difficulty associated with managing the data produced by large-scale transcriptome sequencing. Our approach offers a new direction by sitting between pure reference-based compression and reference-free compression and combines much of the benefit of reference-based approaches with the flexibility of de novo encoding. Our method, called path encoding, draws a connection between storing paths in de Bruijn graphs --- a common task in genome assembly --- and context-dependent arithmetic coding. Supporting this method is a system, called a bit tree, to compactly store sets of kmers that is of independent interest. Using these techniques, we are able to encode RNA-seq reads using 3% -- 11% of the space of the sequence in raw FASTA files, which is on average more than 34% smaller than recent competing approaches. We also show that even if the reference is very poorly matched to the reads that are being encoded, good compression can still be achieved.

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Comparative Transcriptomic Analysis of the Larval and Adult Stages of Taenia pisiformis

Genes ◽

10.3390/genes10070507 ◽

2019 ◽

Vol 10 (7) ◽

pp. 507 ◽

Cited By ~ 1

Author(s):

Zhang

Keyword(s):

Developmental Stages ◽

De Novo ◽

Developmental Process ◽

Average Length ◽

Wnt Signaling Pathway ◽

Transcriptomic Analysis ◽

Economic Losses ◽

Rna Seq ◽

Transcriptomic Data ◽

Comparative Transcriptomic Analysis

Taenia pisiformis is a tapeworm causing economic losses in the rabbit breeding industry worldwide. Due to the absence of genomic data, our knowledge on the developmental process of T. pisiformis is still inadequate. In this study, to better characterize differential and specific genes and pathways associated with the parasite developments, a comparative transcriptomic analysis of the larval stage (TpM) and the adult stage (TpA) of T. pisiformis was performed by Illumina RNA sequencing (RNA-seq) technology and de novo analysis. In total, 68,588 unigenes were assembled with an average length of 789 nucleotides (nt) and N50 of 1485 nt. Further, we identified 4093 differentially expressed genes (DEGs) in TpA versus TpM, of which 3186 DEGs were upregulated and 907 were downregulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) analyses revealed that most DEGs involved in metabolic processes and Wnt signaling pathway were much more active in the TpA stage. Quantitative real-time PCR (qPCR) validated that the expression levels of the selected 10 DEGs were consistent with those in RNA-seq, indicating that the transcriptomic data are reliable. The present study provides comparative transcriptomic data concerning two developmental stages of T. pisiformis, which will be of great value for future functional studies on the regulatory mechanisms behind adult worm pathogenesis and for developing drugs and vaccines against this important parasite.

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Splicing and editing of ionotropic glutamate receptors: a comprehensive analysis based on human RNA-Seq data

Cellular and Molecular Life Sciences ◽

10.1007/s00018-021-03865-z ◽

2021 ◽

Author(s):

Robin Herbrechter ◽

Nadine Hube ◽

Raoul Buchholz ◽

Andreas Reiner

Keyword(s):

Alternative Splicing ◽

Human Brain ◽

Glutamate Receptors ◽

Large Scale ◽

De Novo ◽

Ionotropic Glutamate Receptors ◽

Variable Degree ◽

Rna Seq ◽

Amino Terminal ◽

Species Specific

AbstractIonotropic glutamate receptors (iGluRs) play key roles for signaling in the central nervous system. Alternative splicing and RNA editing are well-known mechanisms to increase iGluR diversity and to provide context-dependent regulation. Earlier work on isoform identification has focused on the analysis of cloned transcripts, mostly from rodents. We here set out to obtain a systematic overview of iGluR splicing and editing in human brain based on RNA-Seq data. Using data from two large-scale transcriptome studies, we established a workflow for the de novo identification and quantification of alternative splice and editing events. We detected all canonical iGluR splice junctions, assessed the abundance of alternative events described in the literature, and identified new splice events in AMPA, kainate, delta, and NMDA receptor subunits. Notable events include an abundant transcript encoding the GluA4 amino-terminal domain, GluA4-ATD, a novel C-terminal GluD1 (delta receptor 1) isoform, GluD1-b, and potentially new GluK4 and GluN2C isoforms. C-terminal GluN1 splicing may be controlled by inclusion of a cassette exon, which shows preference for one of the two acceptor sites in the last exon. Moreover, we identified alternative untranslated regions (UTRs) and species-specific differences in splicing. In contrast, editing in exonic iGluR regions appears to be mostly limited to ten previously described sites, two of which result in silent amino acid changes. Coupling of proximal editing/editing and editing/splice events occurs to variable degree. Overall, this analysis provides the first inventory of alternative splicing and editing in human brain iGluRs and provides the impetus for further transcriptome-based and functional investigations.

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Transcriptomic landscape of Dendrobium huoshanense and its genes related to polysaccharide biosynthesis

Acta Societatis Botanicorum Poloniae ◽

10.5586/asbp.3574 ◽

2018 ◽

Vol 87 (1) ◽

Cited By ~ 1

Author(s):

Rongchun Han ◽

Dongmei Xie ◽

Xiaohui Tong ◽

Wei Zhang ◽

Gang Liu ◽

...

Keyword(s):

Gene Expression ◽

De Novo ◽

Average Length ◽

Cultivated Plants ◽

Polysaccharide Biosynthesis ◽

Fastq Format ◽

Its Gene ◽

Dendrobium Huoshanense ◽

Morphological Differences ◽

Illumina Hiseq4000

Dendrobium huoshanense has long been used to treat various diseases in oriental medicine. In order to study its gene expression profile, transcripts involved in the biosynthesis of precursors of polysaccharides, as well as mechanisms underlining morphological differences between wild and cultivated plants, three organs of both wild type and cultivated D. huoshanense were collected and sequenced by Illumina HiSeq4000 platform, yielding 919,409,540 raw reads in FASTQ format. After Trinity de novo assembly and quality control, 241,242 nonredundant contigs with the average length of 967.5 bp were generated. qRT-PCR experiment on the selected transcripts showed the transcriptomic data were reliable. BLASTx was conducted against NR, SwissProt, String, Pfam, and KEGG. Gene ontology annotation revealed more than 40,000 contigs assigned to catalytic activity and metabolic process, suggesting its dynamic physiological activities. By searching KEGG pathway, six genes potentially involved in mannose biosynthetic pathway were retrieved. Gene expression analysis for stems between wild and cultivated D. huoshanense resulted in 956 genes differentially expressed. Simple sequence repeats (SSRs) analysis revealed 143 SSRs with the unit size of 4 and 3,437 SSRs the size of 3. The obtained SSRs are the potential molecular markers for discriminating distinct cultivars of D. huoshanense.

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One Cell At a Time: A Unified Framework to Integrate and Analyze Single-cell RNA-seq Data

10.1101/2021.05.12.443814 ◽

2021 ◽

Author(s):

Chloe Xueqi Wang ◽

Lin Zhang ◽

Bo Wang

Keyword(s):

Single Cell ◽

Large Scale ◽

Gene Selection ◽

De Novo ◽

Single Cells ◽

Cell Types ◽

Biological Information ◽

Rna Seq ◽

Unified Framework ◽

Gene Expressions

The surge of single-cell RNA sequencing technologies enables the accessibility to large single-cell RNA-seq datasets at the scale of hundreds of thousands of single cells. Integrative analysis of large-scale scRNA-seq datasets has the potential of revealing de novo cell types as well as aggregating biological information. However, most existing methods fail to integrate multiple large-scale scRNA-seq datasets in a computational and memory efficient way. We hereby propose OCAT, One Cell At a Time, a graph-based method that sparsely encodes single-cell gene expressions to integrate data from multiple sources without most variable gene selection or explicit batch effect correction. We demonstrate that OCAT efficiently integrates multiple scRNA-seq datasets and achieves the state-of-the-art performance in cell-type clustering, especially in challenging scenarios of non-overlapping cell types. In addition, OCAT facilitates a variety of downstream analyses, such as gene prioritization, trajectory inference, pseudotime inference and cell inference. OCAT is a unifying tool to simplify and expedite single-cell data analysis.

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Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

10.26434/chemrxiv.11663337.v3 ◽

2020 ◽

Author(s):

Salvador Guardiola ◽

Monica Varese ◽

Xavier Roig ◽

Jesús Garcia ◽

Ernest Giralt

Keyword(s):

Protein Interactions ◽

Cyclic Peptides ◽

General Framework ◽

Large Scale ◽

De Novo ◽

Inhibitory Effect ◽

Original Text ◽

Protein Protein Interactions ◽

Retraction Notice ◽

Pharmaceutical Properties

NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above. ------------------------------------------------------------------------ Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-i3 and PD-i6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our de novo design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.

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