scholarly journals Gray whale transcriptome reveals longevity adaptations associated with DNA repair and ubiquitination

2019 ◽  
Author(s):  
Dmitri Toren ◽  
Anton Kulaga ◽  
Mineshbhai Jethva ◽  
Eitan Rubin ◽  
Anastasia V Snezhkina ◽  
...  
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Expression Patterns ◽  
Model Organisms ◽  
Gray Whale ◽  
Aging Research ◽  
Arctic Water ◽  
Gray Whales ◽  
Longevity Genes

AbstractOne important question in aging research is how differences in genomics and transcriptomics determine the maximum lifespan in various species. Despite recent progress, much is still unclear on the topic, partly due to the lack of samples in non-model organisms and due to challenges in direct comparisons of transcriptomes from different species. The novel ranking-based method that we employ here is used to analyze gene expression in the gray whale and compare its de novo assembled transcriptome with that of other long- and short-lived mammals. Gray whales are among the top 1% longest-lived mammals. Despite the extreme environment, or maybe due to a remarkable adaptation to its habitat (intermittent hypoxia, Arctic water, and high pressure), gray whales reach at least the age of 77 years. In this work, we show that long-lived mammals share common gene expression patterns between themselves, including high expression of DNA maintenance and repair, ubiquitination, apoptosis, and immune responses. Additionally, the level of expression for gray whale orthologs of pro- and anti-longevity genes found in model organisms is in support of their alleged role and direction in lifespan determination. Remarkably, among highly expressed pro-longevity genes many are stress-related, reflecting an adaptation to extreme environmental conditions. The conducted analysis suggests that the gray whale potentially possesses high resistance to cancer and stress, at least in part ensuring its longevity. This new transcriptome assembly also provides important resources to support the efforts of maintaining the endangered population of gray whales.

scholarly journals The brain transcriptome of the wolf spider, Schizocosa ocreata

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Daniel Stribling ◽  
Peter L. Chang ◽  
Justin E. Dalton ◽  
Christopher A. Conow ◽  
Malcolm Rosenthal ◽  
...  
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Model Organisms ◽  
De Novo Transcriptome Assembly ◽  
De Novo Transcriptome ◽  
Wolf Spiders ◽  
Schizocosa Ocreata ◽  
Genomic Studies ◽  
The Brain

Abstract Objectives Arachnids have fascinating and unique biology, particularly for questions on sex differences and behavior, creating the potential for development of powerful emerging models in this group. Recent advances in genomic techniques have paved the way for a significant increase in the breadth of genomic studies in non-model organisms. One growing area of research is comparative transcriptomics. When phylogenetic relationships to model organisms are known, comparative genomic studies provide context for analysis of homologous genes and pathways. The goal of this study was to lay the groundwork for comparative transcriptomics of sex differences in the brain of wolf spiders, a non-model organism of the pyhlum Euarthropoda, by generating transcriptomes and analyzing gene expression. Data description To examine sex-differential gene expression, short read transcript sequencing and de novo transcriptome assembly were performed. Messenger RNA was isolated from brain tissue of male and female subadult and mature wolf spiders (Schizocosa ocreata). The raw data consist of sequences for the two different life stages in each sex. Computational analyses on these data include de novo transcriptome assembly and differential expression analyses. Sample-specific and combined transcriptomes, gene annotations, and differential expression results are described in this data note and are available from publicly-available databases.

scholarly journals Transcriptome Sequencing of Trichoderma Koningiopsis Strain Tk1 to Identify and Analyze Differential Gene Expression Patterns

2020 ◽  
Author(s):  
Mei Luo ◽  
Zhangyong Dong ◽  
Yongxin Shu ◽  
Mobing Chen
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Differential Gene Expression ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Antimicrobial Effect ◽  
Carbohydrate Active Enzymes ◽  
Differential Gene

Abstract Background: Trichoderma koningiopsis strain Tk1 shows good biocontrol potential. However, its biocontrol function may differ under different conditions. The objective of this study is to elucidate the biological and transcriptome differences of T. koningiopsis Tk1 under different media. Results: In this study, the mycelium weight and sporulation of T. koningiopsis Tk1 was found to differ in various media. Further, the Tk1 strain inhibited the growth of the pathogen Fusarium oxysporum in the three media tested. Fries3, PD, and PS were collected for RNA sequencing of Tk1 mycelia to identify the genes that are differentially expressed genes (DEGs) between Tk1 grown on different media. De novo transcriptome assembly resulted in identification of 14,208 unigenes. The differential gene expression pattern was more similar between the Fries3 and PS samples, whereas PD samples showed a different expression pattern. The DEGs were enriched in some metabolic and biosynthetic pathways. Additional analysis of the DEGs identified a set of carbohydrate-active enzymes that are upregulated or downregulated under different conditions.Conclusions: These results indicate that the Tk1 strain cultured in Fires3 and PS mediums can produce specific metabolic and carbohydrate-active enzymes to enhance their antimicrobial effect, providing a foundation for the subsequent mining of specific genes.

scholarly journals A consensus-based ensemble approach to improve de novo transcriptome assembly

2020 ◽  
Author(s):  
Adam Voshall ◽  
Sairam Behera ◽  
Xiangjun Li ◽  
Xiao-Hong Yu ◽  
Kushagra Kapil ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Reference Genome ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Model Organisms ◽  
Pathway Reconstruction ◽  
Rnaseq Data ◽  
Metabolic Pathway Reconstruction ◽  
Assembly Performance

AbstractSystems-level analyses, such as differential gene expression analysis, co-expression analysis, and metabolic pathway reconstruction, depend on the accuracy of the transcriptome. Multiple tools exist to perform transcriptome assembly from RNAseq data. However, assembling high quality transcriptomes is still not a trivial problem. This is especially the case for non-model organisms where adequate reference genomes are often not available. Different methods produce different transcriptome models and there is no easy way to determine which are more accurate. Furthermore, having alternative splicing events could exacerbate such difficult assembly problems. While benchmarking transcriptome assemblies is critical, this is also not trivial due to the general lack of true reference transcriptomes. In this study, we provide a pipeline to generate a set of the benchmark transcriptome and corresponding RNAseq data. Using the simulated benchmarking datasets, we compared the performance of various transcriptome assembly approaches including genome-guided, de novo, and ensemble methods. The results showed that the assembly performance deteriorates significantly when the reference is not available from the same genome (for genome-guided methods) or when alternative transcripts (isoforms) exist. We demonstrated the value of consensus between de novo assemblers in transcriptome assembly. Leveraging the overlapping predictions between the four de novo assemblers, we further present ConSemble, a consensus-based de novo ensemble transcriptome assembly pipeline. Without using a reference genome, ConSemble achieved an accuracy up to twice as high as any de novo assemblers we compared. It matched or exceeded the best performing genome-guided assemblers even when the transcriptomes included isoforms. The RNAseq simulation pipeline, the benchmark transcriptome datasets, and the ConSemble pipeline are all freely available from: http://bioinfolab.unl.edu/emlab/consemble/.Author summaryObtaining the accurate representation of the gene expression is critical in many analyses, such as differential gene expression analysis, co-expression analysis, and metabolic pathway reconstruction. The state of the art high-throughput RNA-sequencing (RNAseq) technologies can be used to sequence the set of all transcripts in a cell, the transcriptome. Although many computational tools are available for transcriptome assembly from RNAseq data, assembling high-quality transcriptomes is difficult especially for non-model organisms. Different methods often produce different transcriptome models and there is no easy way to determine which are more accurate. In this study, we present an approach to evaluate transcriptome assembly performance using simulated benchmarking read sets. The results showed that the assembly performance of genome-guided assembly methods deteriorates significantly when the adequate reference genome is not available. The assembly performance of all methods is affected when alternative transcripts (isoforms) exist. We further demonstrated the value of consensus among assemblers in improving transcriptome assembly. Leveraging the overlapping predictions between the four de novo assemblers, we present ConSemble. Without using a reference genome, ConSemble achieved a much higher accuracy than any de novo assemblers we compared. It matched or exceeded the best performing genome-guided assemblers even when the transcriptomes included isoforms.

scholarly journals Assembly-free rapid differential gene expression analysis in non-model organisms using DNA-protein alignment

2021 ◽  
Author(s):  
Anish M.S. Shrestha ◽  
Joyce Emlyn B. Guiao ◽  
Kyle Christian R. Santiago
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Expression Analysis ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Differential Expression Analysis ◽  
Homology Search ◽  
Model Organisms ◽  
Rna Seq ◽  
Protein Database

AbstractRNA-seq is being increasingly adopted for gene expression studies in a panoply of non-model organisms, with applications spanning the fields of agriculture, aquaculture, ecology, and environment. Conventional differential expression analysis for organisms without reference sequences requires performing computationally expensive and error-prone de-novo transcriptome assembly, followed by homology search against a high-confidence protein database for functional annotation. We propose a shortcut, where we obtain counts for differential expression analysis by directly aligning RNA-seq reads to the protein database. Through experiments on simulated and real data, we show drastic reductions in run-time and memory usage, with no loss in accuracy. A Snakemake implementation of our workflow is available at:https://bitbucket.org/project_samar/samar

scholarly journals The neurotranscriptome of the Aedes aegypti mosquito

2015 ◽  
Author(s):  
Benjamin J Matthews ◽  
Carolyn S McBride ◽  
Matthew DeGennaro ◽  
Orion Despo ◽  
Leslie B Vosshall
Keyword(s):  
Gene Expression ◽  
Aedes Aegypti ◽  
Vector Control ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Molecular Genetic ◽  
Blood Feeding ◽  
Model Organisms ◽  
Protein Coding ◽  
Male And Female

Background A complete genome sequence and the advent of genome editing open up non-traditional model organisms to mechanistic genetic studies. The mosquito Aedes aegypti is an important vector of infectious diseases such as dengue, chikungunya, and yellow fever, and has a large and complex genome, which has slowed annotation efforts. We used comprehensive transcriptomic analysis of adult gene expression to improve the genome annotation and to provide a detailed tissue-specific catalogue of neural gene expression at different adult behavioral states. Results We carried out deep RNA sequencing across all major peripheral male and female sensory tissues, the brain, and (female) ovary. Furthermore, we examined gene expression across three important phases of the female reproductive cycle, a remarkable example of behavioral switching in which a female mosquito alternates between obtaining blood-meals from humans and laying eggs. Using genome-guided alignments and de novo transcriptome assembly, our re-annotation includes 572 new putative protein-coding genes and updates to 13.5% and 50.3% of existing transcripts within coding sequences and untranslated regions, respectively. Using this updated annotation, we detail gene expression in each tissue, identifying large numbers of transcripts regulated by blood-feeding and sexually dimorphic transcripts that may provide clues to the biology of male- and female-specific behaviors, such as mating and blood-feeding, which are areas of intensive study for those interested in vector control. Conclusions This neurotranscriptome forms a strong foundation for the study of genes in the mosquito nervous system and investigation of sensory-driven behaviors and their regulation. Furthermore, understanding the molecular genetic basis of mosquito chemosensory behavior has important implications for vector control.

scholarly journals Viral Gene Expression Patterns in Human Herpesvirus 6B-Infected T Cells

2002 ◽  
Vol 76 (15) ◽  
pp. 7578-7586 ◽  
Author(s):  
Bodil Øster ◽  
Per Höllsberg
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Protein Synthesis ◽  
De Novo ◽  
Expression Patterns ◽  
Human Herpesvirus ◽  
Viral Gene Expression ◽  
Polymerase Activity ◽  
Viral Gene ◽  
De Novo Protein Synthesis

ABSTRACT Herpesvirus gene expression is divided into immediate-early (IE) or α genes, early (E) or β genes, and late (L) or γ genes on the basis of temporal expression and dependency on other gene products. By using real-time PCR, we have investigated the expression of 35 human herpesvirus 6B (HHV-6B) genes in T cells infected by strain PL-1. Kinetic analysis and dependency on de novo protein synthesis and viral DNA polymerase activity suggest that the HHV-6B genes segregate into six separate kinetic groups. The genes expressed early (groups I and II) and late (groups V and VI) corresponded well with IE and L genes, whereas the intermediate groups III and IV contained E and L genes. Although HHV-6B has characteristics similar to those of other roseoloviruses in its overall gene regulation, we detected three B-variant-specific IE genes. Moreover, genes that were independent of de novo protein synthesis clustered in an area of the viral genome that has the lowest identity to the HHV-6A variant. The organization of IE genes in an area of the genome that differs from that of HHV-6A underscores the distinct differences between HHV-6B and HHV-6A and may provide a basis for further molecular and immunological analyses to elucidate their different biological behaviors.

scholarly journals De Novo Transcriptome Assembly and Analyses of Gene Expression during Photomorphogenesis in Diploid Wheat Triticum monococcum

PLoS ONE ◽  
2014 ◽  
Vol 9 (5) ◽  
pp. e96855 ◽  
Author(s):  
Samuel E. Fox ◽  
Matthew Geniza ◽  
Mamatha Hanumappa ◽  
Sushma Naithani ◽  
Chris Sullivan ◽  
...  
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Triticum Monococcum ◽  
Diploid Wheat ◽  
De Novo Transcriptome Assembly ◽  
De Novo Transcriptome

scholarly journals A practical guide to buildde-novoassemblies for single tissues of non-model organisms: the example of a Neotropical frog

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3702 ◽  
Author(s):  
Santiago Montero-Mendieta ◽  
Manfred Grabherr ◽  
Henrik Lantz ◽  
Ignacio De la Riva ◽  
Jennifer A. Leonard ◽  
...  
Keyword(s):  
Defense Mechanisms ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Cost Effective ◽  
Model Organisms ◽  
Rna Seq ◽  
Assembly Pipeline ◽  
Wide Variability ◽  
History Of ◽  
Inexperienced User

Whole genome sequencing (WGS) is a very valuable resource to understand the evolutionary history of poorly known species. However, in organisms with large genomes, as most amphibians, WGS is still excessively challenging and transcriptome sequencing (RNA-seq) represents a cost-effective tool to explore genome-wide variability. Non-model organisms do not usually have a reference genome and the transcriptome must be assembledde-novo. We used RNA-seq to obtain the transcriptomic profile forOreobates cruralis, a poorly known South American direct-developing frog. In total, 550,871 transcripts were assembled, corresponding to 422,999 putative genes. Of those, we identified 23,500, 37,349, 38,120 and 45,885 genes present in the Pfam, EggNOG, KEGG and GO databases, respectively. Interestingly, our results suggested that genes related to immune system and defense mechanisms are abundant in the transcriptome ofO. cruralis. We also present a pipeline to assist with pre-processing, assembling, evaluating and functionally annotating ade-novotranscriptome from RNA-seq data of non-model organisms. Our pipeline guides the inexperienced user in an intuitive way through all the necessary steps to buildde-novotranscriptome assemblies using readily available software and is freely available at:https://github.com/biomendi/TRANSCRIPTOME-ASSEMBLY-PIPELINE/wiki.

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