scholarly journals Low-bias RNA sequencing of the HIV-2 genome from blood plamsa

2018 ◽  
Author(s):  
Katherine L. James ◽  
Thushan de Silva ◽  
Katherine Brown ◽  
Hilton Whittle ◽  
Stephen Taylor ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Blood Plasma ◽  
De Novo ◽  
A Priori ◽  
Pcr Amplification ◽  
Hiv Vaccine ◽  
Whole Genome ◽  
Plasma Samples ◽  
Target Enrichment ◽  
Rna Seq

ABSTRACTAccurate determination of the genetic diversity present in the HIV quasi-species is critical for the development of a preventative vaccine: in particular, little is known about viral genetic diversity for the second strain of HIV, HIV-2. A better understanding of HIV-2 biology is relevant to the HIV vaccine field because a substantial proportion of infected people experience long-term viral control, and prior HIV-2 infection is associated with slower HIV-1 disease progression in co-infected subjects. The majority of traditional and next generation sequencing methods have relied on target amplification prior to sequencing, introducing biases that may obscure the true signals of diversity in the viral population. Additionally, target-enrichment through PCR requiresa priorisequence knowledge, which is lacking for HIV-2. Therefore, a target enrichment free method of library preparation would be valuable for the field. We applied an RNA shotgun sequencing (RNA-Seq) method without PCR amplification to cultured viral stocks and patient plasma samples from HIV-2 infected individuals. Libraries generated from total plasma RNA were analysed with a two-step pipeline: (1)de novogenome assembly, followed by (2) read re-mapping. By this approach, whole genome sequences were generated with a 28x-67x mean depth of coverage. Assembled reads showed a low level of GC-bias and comparison of the genome diversity on the intra-host level showed low diversity in the accessory genevpxin all patients. Our study demonstrates that RNA-Seq is a feasible full-genomede novosequencing method for blood plasma samples collected from HIV-2 infected individuals.IMPORTANCEAn accurate picture of viral genetic diversity is critical for the development of a globally effective HIV vaccine. However, sequencing strategies are often complicated by target enrichment prior to sequencing, introducing biases that can distort variant frequencies, which are not easily corrected for in downstream analyses. Additionally, detaileda priorisequence knowledge is needed to inform robust primer design when employing PCR amplification, a factor that is often lacking when working with tropical diseases localised in developing countries. Previous work has demonstrated that direct RNA shotgun sequencing (RNA-Seq) can be used to circumvent these issues for HCV and Norovirus. We applied shotgun RNA sequencing (RNA-Seq) to total RNA extracted from HIV-2 blood plasma samples, demonstrating the applicability of this technique to HIV-2 and allowing us to generate a dynamic picture of genetic diversity over the whole genome of HIV-2 in the context of low-bias sequencing.

scholarly journals Low-Bias RNA Sequencing of the HIV-2 Genome from Blood Plasma

2018 ◽  
Vol 93 (1) ◽  
Author(s):  
Katherine L. James ◽  
Thushan I. de Silva ◽  
Katherine Brown ◽  
Hilton Whittle ◽  
Stephen Taylor ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Blood Plasma ◽  
De Novo ◽  
A Priori ◽  
Pcr Amplification ◽  
Hiv Vaccine ◽  
Whole Genome ◽  
Plasma Samples ◽  
Target Enrichment ◽  
Rna Seq

ABSTRACTAccurate determination of the genetic diversity present in the HIV quasispecies is critical for the development of a preventative vaccine: in particular, little is known about viral genetic diversity for the second type of HIV, HIV-2. A better understanding of HIV-2 biology is relevant to the HIV vaccine field because a substantial proportion of infected people experience long-term viral control, and prior HIV-2 infection has been associated with slower HIV-1 disease progression in coinfected subjects. The majority of traditional and next-generation sequencing methods have relied on target amplification prior to sequencing, introducing biases that may obscure the true signals of diversity in the viral population. Additionally, target enrichment through PCR requiresa priorisequence knowledge, which is lacking for HIV-2. Therefore, a target enrichment free method of library preparation would be valuable for the field. We applied an RNA shotgun sequencing (RNA-Seq) method without PCR amplification to cultured viral stocks and patient plasma samples from HIV-2-infected individuals. Libraries generated from total plasma RNA were analyzed with a two-step pipeline: (i)de novogenome assembly, followed by (ii) read remapping. By this approach, whole-genome sequences were generated with a 28× to 67× mean depth of coverage. Assembled reads showed a low level of GC bias, and comparison of the genome diversities at the intrahost level showed low diversity in the accessory genevpxin all patients. Our study demonstrates that RNA-Seq is a feasible full-genomede novosequencing method for blood plasma samples collected from HIV-2-infected individuals.IMPORTANCEAn accurate picture of viral genetic diversity is critical for the development of a globally effective HIV vaccine. However, sequencing strategies are often complicated by target enrichment prior to sequencing, introducing biases that can distort variant frequencies, which are not easily corrected for in downstream analyses. Additionally, detaileda priorisequence knowledge is needed to inform robust primer design when employing PCR amplification, a factor that is often lacking when working with tropical diseases localized in developing countries. Previous work has demonstrated that direct RNA shotgun sequencing (RNA-Seq) can be used to circumvent these issues for hepatitis C virus (HCV) and norovirus. We applied RNA-Seq to total RNA extracted from HIV-2 blood plasma samples, demonstrating the applicability of this technique to HIV-2 and allowing us to generate a dynamic picture of genetic diversity over the whole genome of HIV-2 in the context of low-bias sequencing.

scholarly journals Application of an optimized annotation pipeline to the Cryptococcus deuterogattii genome reveals dynamic primary metabolic gene clusters and genomic impact of RNAi loss

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Patrícia Aline Gröhs Ferrareze ◽  
Corinne Maufrais ◽  
Rodrigo Silva Araujo Streit ◽  
Shelby J Priest ◽  
Christina A Cuomo ◽  
...  
Keyword(s):  
De Novo ◽  
Intron Retention ◽  
A Priori ◽  
Gene Clusters ◽  
Antisense Transcription ◽  
Fungal Genome ◽  
Rna Seq ◽  
Bioinformatics Pipeline ◽  
Subtelomeric Regions

Abstract Evaluating the quality of a de novo annotation of a complex fungal genome based on RNA-seq data remains a challenge. In this study, we sequentially optimized a Cufflinks-CodingQuary-based bioinformatics pipeline fed with RNA-seq data using the manually annotated model pathogenic yeasts Cryptococcus neoformans and Cryptococcus deneoformans as test cases. Our results show that the quality of the annotation is sensitive to the quantity of RNA-seq data used and that the best quality is obtained with 5–10 million reads per RNA-seq replicate. We also showed that the number of introns predicted is an excellent a priori indicator of the quality of the final de novo annotation. We then used this pipeline to annotate the genome of the RNAi-deficient species Cryptococcus deuterogattii strain R265 using RNA-seq data. Dynamic transcriptome analysis revealed that intron retention is more prominent in C. deuterogattii than in the other RNAi-proficient species C. neoformans and C. deneoformans. In contrast, we observed that antisense transcription was not higher in C. deuterogattii than in the two other Cryptococcus species. Comparative gene content analysis identified 21 clusters enriched in transcription factors and transporters that have been lost. Interestingly, analysis of the subtelomeric regions in these three annotated species identified a similar gene enrichment, reminiscent of the structure of primary metabolic clusters. Our data suggest that there is active exchange between subtelomeric regions, and that other chromosomal regions might participate in adaptive diversification of Cryptococcus metabolite assimilation potential.

scholarly journals Application of an optimized annotation pipeline to the Cryptococcus deuterogattii genome reveals dynamic primary metabolic gene clusters and genomic impact of RNAi loss

2020 ◽  
Author(s):  
Patricia A.G. Ferrareze ◽  
Corinne Maufrais ◽  
Rodrigo Silva Aroujo Streit ◽  
Shelby J. Priest ◽  
Christina A. Cuomo ◽  
...  
Keyword(s):  
De Novo ◽  
Intron Retention ◽  
A Priori ◽  
Gene Clusters ◽  
Antisense Transcription ◽  
Fungal Genome ◽  
Rna Seq ◽  
Bioinformatics Pipeline ◽  
Subtelomeric Regions

Evaluating the quality of a de novo annotation of a complex fungal genome based on RNA-seq data remains a challenge. In this study, we sequentially optimized a Cufflinks-CodingQuary based bioinformatics pipeline fed with RNA-seq data using the manually annotated model pathogenic yeasts Cryptococcus neoformans and Cryptococcus deneoformans as test cases. Our results demonstrate that the quality of the annotation is sensitive to the quantity of RNA-seq data used and that the best quality is obtained with 5 to 10 million reads per RNA-seq replicate. We also demonstrated that the number of introns predicted is an excellent a priori indicator of the quality of the final de novo annotation. We then used this pipeline to annotate the genome of the RNAi-deficient species Cryptococcus deuterogattii strain R265 using RNA-seq data. Dynamic transcriptome analysis revealed that intron retention is more prominent in C. deuterogattii than in the other RNAi-proficient species C. neoformans and C. deneoformans. In contrast, we observed that antisense transcription was not higher in C. deuterogattii than in the two other Cryptococcus species. Comparative gene content analysis identified 21 clusters enriched in transcription factors and transporters that have been lost. Interestingly, analysis of the subtelomeric regions in these three annotated species identified a similar gene enrichment, reminiscent of the structure of primary metabolic clusters. Our data suggest that there is active exchange between subtelomeric regions, and that other chromosomal regions might participate in adaptive diversification of Cryptococcus metabolite assimilation potential.

scholarly journals First de-novo transcriptome assembly of a South American frog, Oreobates cruralis, enables population genomic studies of Neotropical amphibians

2017 ◽  
Author(s):  
Santiago Montero-Mendieta ◽  
Manfred Grabherr ◽  
Henrik Lantz ◽  
Ignacio De la Riva ◽  
Jennifer A Leonard ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Cost Effective ◽  
Model Organisms ◽  
South American ◽  
Whole Genome ◽  
Rna Seq ◽  
De Novo Transcriptome

Whole genome sequencing is opening the door to novel insights into the population structure and evolutionary history of poorly known species. In organisms with large genomes, which includes most amphibians, whole-genome sequencing is 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 to facilitate assembly and the transcriptome sequence must be assembled de-novo. We used RNA-seq to obtain the transcriptome profile for Oreobates 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 of O. cruralis. We also present a workflow to assist with pre-processing, assembling, evaluating and functionally annotating a de-novo transcriptome from RNA-seq data of non-model organisms. Our workflow guides the inexperienced user in an intuitive way through all the necessary steps to build de-novo transcriptome assemblies using readily available software and is freely available at: https://github.com/biomendi/PRACTICAL-GUIDE-TO-BUILD-DE-NOVO-TRANSCRIPTOME-ASSEMBLIES-FOR-NON-MODEL-ORGANISMS/wiki

scholarly journals First de-novo transcriptome assembly of a South American frog, Oreobates cruralis, enables population genomic studies of Neotropical amphibians

2017 ◽  
Author(s):  
Santiago Montero-Mendieta ◽  
Manfred Grabherr ◽  
Henrik Lantz ◽  
Ignacio De la Riva ◽  
Jennifer A Leonard ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Cost Effective ◽  
Model Organisms ◽  
South American ◽  
Whole Genome ◽  
Rna Seq ◽  
De Novo Transcriptome

Whole genome sequencing is opening the door to novel insights into the population structure and evolutionary history of poorly known species. In organisms with large genomes, which includes most amphibians, whole-genome sequencing is 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 to facilitate assembly and the transcriptome sequence must be assembled de-novo. We used RNA-seq to obtain the transcriptome profile for Oreobates 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 of O. cruralis. We also present a workflow to assist with pre-processing, assembling, evaluating and functionally annotating a de-novo transcriptome from RNA-seq data of non-model organisms. Our workflow guides the inexperienced user in an intuitive way through all the necessary steps to build de-novo transcriptome assemblies using readily available software and is freely available at: https://github.com/biomendi/PRACTICAL-GUIDE-TO-BUILD-DE-NOVO-TRANSCRIPTOME-ASSEMBLIES-FOR-NON-MODEL-ORGANISMS/wiki

scholarly journals Effective variant filtering and expected candidate variant yield in studies of rare human disease

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Brent S. Pedersen ◽  
Joe M. Brown ◽  
Harriet Dashnow ◽  
Amelia D. Wallace ◽  
Matt Velinder ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Rare Disease ◽  
Genome Sequencing ◽  
Autosomal Dominant ◽  
De Novo ◽  
Autosomal Dominant Inheritance ◽  
Compound Heterozygous ◽  
Whole Genome ◽  
Dominant Inheritance ◽  
Family Based

AbstractIn studies of families with rare disease, it is common to screen for de novo mutations, as well as recessive or dominant variants that explain the phenotype. However, the filtering strategies and software used to prioritize high-confidence variants vary from study to study. In an effort to establish recommendations for rare disease research, we explore effective guidelines for variant (SNP and INDEL) filtering and report the expected number of candidates for de novo dominant, recessive, and autosomal dominant modes of inheritance. We derived these guidelines using two large family-based cohorts that underwent whole-genome sequencing, as well as two family cohorts with whole-exome sequencing. The filters are applied to common attributes, including genotype-quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield ~10 candidate SNP and INDEL variants per exome, and 18 per genome for recessive and de novo dominant modes of inheritance, with substantially more candidates for autosomal dominant inheritance. For family-based, whole-genome sequencing studies, this number includes an average of three de novo, ten compound heterozygous, one autosomal recessive, four X-linked variants, and roughly 100 candidate variants following autosomal dominant inheritance. The slivar software we developed to establish and rapidly apply these filters to VCF files is available at https://github.com/brentp/slivar under an MIT license, and includes documentation and recommendations for best practices for rare disease analysis.

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