scholarly journals Low impact of different SNP panels from two building-loci pipelines on RAD-Seq population genomic metrics: case study on five diverse aquatic species

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Adrián Casanova ◽  
Francesco Maroso ◽  
Andrés Blanco ◽  
Miguel Hermida ◽  
Néstor Ríos ◽  
...  
Keyword(s):  
Brown Trout ◽  
Reference Genome ◽  
De Novo ◽  
Manila Clam ◽  
Model Organisms ◽  
Aquatic Species ◽  
Single Nucleotide ◽  
Snp Panels ◽  
Next Generation Sequencing Ngs

Abstract Background The irruption of Next-generation sequencing (NGS) and restriction site-associated DNA sequencing (RAD-seq) in the last decade has led to the identification of thousands of molecular markers and their genotyping for refined genomic screening. This approach has been especially useful for non-model organisms with limited genomic resources. Many building-loci pipelines have been developed to obtain robust single nucleotide polymorphism (SNPs) genotyping datasets using a de novo RAD-seq approach, i.e. without reference genomes. Here, the performances of two building-loci pipelines, STACKS 2 and Meyer’s 2b-RAD v2.1 pipeline, were compared using a diverse set of aquatic species representing different genomic and/or population structure scenarios. Two bivalve species (Manila clam and common edible cockle) and three fish species (brown trout, silver catfish and small-spotted catshark) were studied. Four SNP panels were evaluated in each species to test both different building-loci pipelines and criteria for SNP selection. Furthermore, for Manila clam and brown trout, a reference genome approach was used as control. Results Despite different outcomes were observed between pipelines and species with the diverse SNP calling and filtering steps tested, no remarkable differences were found on genetic diversity and differentiation within species with the SNP panels obtained with a de novo approach. The main differences were found in brown trout between the de novo and reference genome approaches. Genotyped vs missing data mismatches were the main genotyping difference detected between the two building-loci pipelines or between the de novo and reference genome comparisons. Conclusions Tested building-loci pipelines for selection of SNP panels seem to have low influence on population genetics inference across the diverse case-study scenarios here studied. However, preliminary trials with different bioinformatic pipelines are suggested to evaluate their influence on population parameters according with the specific goals of each study.

scholarly journals Genomic outcomes from diverse SNP panels obtained with different de novo building-loci pipelines in a varied species context: Can pipelines be influencing biological interpretations?

2020 ◽  
Author(s):  
Adrian Casanova ◽  
Francesco Maroso ◽  
Andrés Blanco ◽  
Miguel Hermida ◽  
Nestor Rios ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Brown Trout ◽  
Reference Genome ◽  
De Novo ◽  
Manila Clam ◽  
Model Organisms ◽  
Single Nucleotide ◽  
Snp Panels ◽  
Next Generation Sequencing Ngs ◽  
Genome Comparisons

Abstract Background The irruption of Next-generation sequencing (NGS) and restriction site-associated DNA sequencing (RAD-seq) in the last decade has led to the identification of thousands of molecular markers and their genotyping for refined genomic screening. This approach has been especially useful for non-model organisms with limited genomic resources. Many building-loci pipelines have been developed to obtain robust single nucleotide polymorphism (SNPs) genotyping datasets using a de novo RAD-seq approach, i.e. without reference genomes. Here, the performances of two building-loci pipelines, STACKS 2 and Meyer’s 2b-RAD v2.1 pipeline, were compared using a diverse set of aquatic species representing different genomic and/or population structure scenarios. Two bivalve species (Manila clam and common edible cockle) and three fish species (brown trout, silver catfish and small-spotted catshark) were studied. Four SNP panels were evaluated in each species to test both different building-loci pipelines and criteria for SNP selection. Furthermore, for Manila clam and brown trout, a reference genome approach was used as control. Results Despite different outcomes were observed between pipelines and species with the diverse SNP calling and filtering steps tested, no remarkable differences were found on genetic diversity and differentiation within species with the SNP panels obtained with a de novo approach. The main differences were found in brown trout between the de novo and reference genome approaches. Genotyped vs missing data mismatches were the main genotyping difference detected between the two building-loci pipelines or between the de novo and reference genome comparisons. Conclusions Building-loci pipelines seem not to have a substantial influence on population genetics inference. Anyway, we recommend being careful with certain building-loci pipeline parameters and SNP filtering steps, especially when a de novo approach is used. Preliminary trials with subsets of data should be performed for comparison of genetic diversity and differentiation, but always considering the specific goals of the study.

scholarly journals Genomic outcomes from diverse SNP panels obtained with different de novo building-loci pipelines in a varied species context: Can pipelines be influencing biological interpretations?

2020 ◽  
Author(s):  
Adrian Casanova ◽  
Francesco Maroso ◽  
Andrés Blanco ◽  
Miguel Hermida ◽  
Nestor Rios ◽  
...  
Keyword(s):  
Brown Trout ◽  
Reference Genome ◽  
De Novo ◽  
Manila Clam ◽  
Model Organisms ◽  
Single Nucleotide ◽  
Snp Panels ◽  
Next Generation Sequencing Ngs ◽  
Genome Comparisons ◽  
Reference Genomes

Abstract Background: The irruption of Next-generation sequencing (NGS) and restriction site-associated DNA sequencing (RAD-seq) in the last decade has led to the identification of thousands of molecular markers and their genotyping for refined genomic screening. This approach has been especially useful for non-model organisms with limited genomic resources. Many building-loci pipelines have been developed to obtain robust single nucleotide polymorphism (SNPs) genotyping datasets using a de novo RAD-seq approach, i.e. without reference genomes. Here, the performances of two building-loci pipelines, STACKS 2 and Meyer’s 2b-RAD v2.1 pipeline, were compared using a diverse set of aquatic species representing different genomic and/or population structure scenarios. Two bivalve species (Manila clam and common edible cockle) and three fish species (brown trout, silver catfish and small-spotted catshark) were studied. Four SNP panels were evaluated in each species to test both different building-loci pipelines and criteria for SNP selection. Furthermore, for Manila clam and brown trout, a reference genome approach was used as control. Results: Despite different outcomes were observed between pipelines and species with the diverse SNP calling and filtering steps tested, no remarkable differences were found on genetic diversity and differentiation within species with the SNP panels obtained with a de novo approach. The main differences were found in brown trout between the de novo and reference genome approaches. Genotyped vs missing data mismatches were the main genotyping difference detected between the two building-loci pipelines or between the de novo and reference genome comparisons. Conclusions: Tested building-loci pipelines seem not to have a substantial influence on population genetics inference. Preliminary trials with bioinformatic pipelines are suggested to evaluate their influence in population parameters related to the specific goals of the study.

scholarly journals DiscoSnp++: de novo detection of small variants from raw unassembled read set(s)

2017 ◽  
Author(s):  
Pierre Peterlongo ◽  
Chloé Riou ◽  
Erwan Drezen ◽  
Claire Lemaitre
Keyword(s):  
Reference Genome ◽  
De Novo ◽  
Model Organisms ◽  
Small Indels ◽  
Desktop Computers ◽  
Resource Requirements ◽  
Computational Resources ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Source Of Information

AbstractMotivationNext Generation Sequencing (NGS) data provide an unprecedented access to life mechanisms. In particular, these data enable to detect polymorphisms such as SNPs and indels. As these polymorphisms represent a fundamental source of information in agronomy, environment or medicine, their detection in NGS data is now a routine task. The main methods for their prediction usually need a reference genome. However, non-model organisms and highly divergent genomes such as in cancer studies are extensively investigated.ResultsWe propose DiscoSnp++, in which we revisit the DiscoSnp algorithm. DiscoSnp++ is designed for detecting and ranking all kinds of SNPs and small indels from raw read set(s). It outputs files in fasta and VCF formats. In particular, predicted variants can be automatically localized afterwards on a reference genome if available. Its usage is extremely simple and its low resource requirements make it usable on common desktop computers. Results show that DiscoSnp++ performs better than state-of-the-art methods in terms of computational resources and in terms of results quality. An important novelty is the de novo detection of indels, for which we obtained 99% precision when calling indels on simulated human datasets and 90% recall on high confident indels from the Platinum dataset.LicenseGNU Affero general public licenseAvailabilityhttps://github.com/GATB/[email protected]

scholarly journals In Search of Species-Specific SNPs in a Non-Model Animal (European Bison (Bison bonasus))—Comparison of De Novo and Reference-Based Integrated Pipeline of STACKS Using Genotyping-by-Sequencing (GBS) Data

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2226
Author(s):  
Sazia Kunvar ◽  
Sylwia Czarnomska ◽  
Cino Pertoldi ◽  
Małgorzata Tokarska
Keyword(s):  
Reference Genome ◽  
De Novo ◽  
Bos Taurus ◽  
Model Organism ◽  
Genotyping By Sequencing ◽  
Model Organisms ◽  
European Bison ◽  
Model Animal ◽  
Pcr Duplicates ◽  
Species Specific

The European bison is a non-model organism; thus, most of its genetic and genomic analyses have been performed using cattle-specific resources, such as BovineSNP50 BeadChip or Illumina Bovine 800 K HD Bead Chip. The problem with non-specific tools is the potential loss of evolutionary diversified information (ascertainment bias) and species-specific markers. Here, we have used a genotyping-by-sequencing (GBS) approach for genotyping 256 samples from the European bison population in Bialowieza Forest (Poland) and performed an analysis using two integrated pipelines of the STACKS software: one is de novo (without reference genome) and the other is a reference pipeline (with reference genome). Moreover, we used a reference pipeline with two different genomes, i.e., Bos taurus and European bison. Genotyping by sequencing (GBS) is a useful tool for SNP genotyping in non-model organisms due to its cost effectiveness. Our results support GBS with a reference pipeline without PCR duplicates as a powerful approach for studying the population structure and genotyping data of non-model organisms. We found more polymorphic markers in the reference pipeline in comparison to the de novo pipeline. The decreased number of SNPs from the de novo pipeline could be due to the extremely low level of heterozygosity in European bison. It has been confirmed that all the de novo/Bos taurus and Bos taurus reference pipeline obtained SNPs were unique and not included in 800 K BovineHD BeadChip.

AStrap: identification of alternative splicing from transcript sequences without a reference genome

2018 ◽  
Vol 35 (15) ◽  
pp. 2654-2656 ◽  
Author(s):  
Guoli Ji ◽  
Wenbin Ye ◽  
Yaru Su ◽  
Moliang Chen ◽  
Guangzao Huang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Alternative Splicing ◽  
Single Molecule ◽  
Reference Genome ◽  
De Novo ◽  
Supplementary Information ◽  
Model Organisms ◽  
Sequencing Data ◽  
Extensive Evaluation ◽  
Reference Genomes

Abstract Summary Alternative splicing (AS) is a well-established mechanism for increasing transcriptome and proteome diversity, however, detecting AS events and distinguishing among AS types in organisms without available reference genomes remains challenging. We developed a de novo approach called AStrap for AS analysis without using a reference genome. AStrap identifies AS events by extensive pair-wise alignments of transcript sequences and predicts AS types by a machine-learning model integrating more than 500 assembled features. We evaluated AStrap using collected AS events from reference genomes of rice and human as well as single-molecule real-time sequencing data from Amborella trichopoda. Results show that AStrap can identify much more AS events with comparable or higher accuracy than the competing method. AStrap also possesses a unique feature of predicting AS types, which achieves an overall accuracy of ∼0.87 for different species. Extensive evaluation of AStrap using different parameters, sample sizes and machine-learning models on different species also demonstrates the robustness and flexibility of AStrap. AStrap could be a valuable addition to the community for the study of AS in non-model organisms with limited genetic resources. Availability and implementation AStrap is available for download at https://github.com/BMILAB/AStrap. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Ion channel profiling of the Lymnaea stagnalis ganglia via transcriptome analysis

2020 ◽  
Author(s):  
Nan Dong ◽  
Julia Bandura ◽  
Zhaolei Zhang ◽  
Yan Wang ◽  
Karine Labadie ◽  
...  
Keyword(s):  
Ion Channels ◽  
Reference Genome ◽  
Lymnaea Stagnalis ◽  
De Novo ◽  
Model Organisms ◽  
Sequence Length ◽  
Pond Snail ◽  
Sequence Information ◽  
Functional Domain ◽  
Rna Seq

Abstract Background. The pond snail Lymnaea stagnalis (L. stagnalis) has been widely used as a model organism in neurobiology, ecotoxicology, and parasitology due to the relative simplicity of its CNS. However, its usefulness is restricted by a limited availability of transcriptome data. While sequence information for the L. stagnalis CNS transcripts has been obtained from EST library and a de novo RNA-seq assembly, the quality of these assemblies is limited by a combination of low coverage of EST libraries, the fragmented nature of de novo assemblies, and lack of reference genome. Results. In this study, taking advantage of the recent availability of the L. stagnalis reference genome, we generated an RNA-seq library from the adult L. stagnalis CNS, using a combination of genome-guided and de novo assembly programs to identify 17,832 protein-coding L. stagnalis transcripts. We combined our library with existing resources to produce a transcript set with greater sequence length, completeness, and diversity than previously available ones. Using our assembly and functional domain analysis, we profiled L. stagnalis CNS transcripts encoding ion channels and ionotropic receptors, which are key proteins for CNS function, and compared their sequences to other vertebrate and invertebrate model organisms. Interestingly, L. stagnalis transcripts encoding numerous putative Ca2+ channels showed the most sequence similarity to those of mouse, zebrafish, Xenopus tropicalis, fruit fly, and C. elegans, suggesting that many calcium channel-related signaling pathways may be evolutionarily conserved. Conclusions. Our study provides the most thorough characterization to date of the L. stagnalis transcriptome and provides insights into differences between vertebrates and invertebrates in CNS transcript diversity, according to function and protein class. Furthermore, this study is, to the best of our knowledge, the first to provide a complete characterization of the ion channels of a single species, opening new avenues for future research on fundamental neurobiological processes.

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.

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