scholarly journals An evaluation of pool-sequencing transcriptome-based exon capture for population genomics in non-model species

2019 ◽  
Author(s):  
Emeline Deleury ◽  
Thomas Guillemaud ◽  
Aurélie Blin ◽  
Eric Lombaert
Keyword(s):  
Evolutionary Biology ◽  
High Throughput Sequencing ◽  
Harmonia Axyridis ◽  
Population Genomics ◽  
De Novo ◽  
Cost Effective ◽  
Allele Frequencies ◽  
Technical Solution ◽  
Model Species ◽  
Exon Capture

AbstractExon capture coupled to high-throughput sequencing constitutes a cost-effective technical solution for addressing specific questions in evolutionary biology by focusing on expressed regions of the genome preferentially targeted by selection. Transcriptome-based capture, a process that can be used to capture the exons of non-model species, is use in phylogenomics. However, its use in population genomics remains rare due to the high costs of sequencing large numbers of indexed individuals across multiple populations. We evaluated the feasibility of combining transcriptome-based capture and the pooling of tissues from numerous individuals for DNA extraction as a cost-effective, generic and robust approach to estimating the variant allele frequencies of any species at the population level. We designed capture probes for ∼5 Mb of chosen de novo transcripts from the Asian ladybird Harmonia axyridis (5,717 transcripts). We called ∼300,000 bi-allelic SNPs for a pool of 36 non-indexed individuals. Capture efficiency was high, and pool-seq was as effective and accurate as individual-seq for detecting variants and estimating allele frequencies. Finally, we also evaluated an approach for simplifying bioinformatic analyses by mapping genomic reads directly to targeted transcript sequences to obtain coding variants. This approach is effective and does not affect the estimation of SNP allele frequencies, except for a small bias close to some exon ends. We demonstrate that this approach can also be used to predict the intron-exon boundaries of targeted de novo transcripts, making it possible to abolish genotyping biases near exon ends.

scholarly journals A Multireference-Based Whole Genome Assembly for the Obligate Ant-Following Antbird, Rhegmatorhina melanosticta (Thamnophilidae)

Diversity ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 144 ◽  
Author(s):  
Laís Coelho ◽  
Lukas Musher ◽  
Joel Cracraft
Keyword(s):  
Genome Assembly ◽  
High Throughput Sequencing ◽  
Population Genomics ◽  
De Novo ◽  
Structural Difference ◽  
Whole Genome ◽  
Sequencing Technology ◽  
A Genome ◽  
Avian Genomes ◽  
Chromosome Level

Current generation high-throughput sequencing technology has facilitated the generation of more genomic-scale data than ever before, thus greatly improving our understanding of avian biology across a range of disciplines. Recent developments in linked-read sequencing (Chromium 10×) and reference-based whole-genome assembly offer an exciting prospect of more accessible chromosome-level genome sequencing in the near future. We sequenced and assembled a genome of the Hairy-crested Antbird (Rhegmatorhina melanosticta), which represents the first publicly available genome for any antbird (Thamnophilidae). Our objectives were to (1) assemble scaffolds to chromosome level based on multiple reference genomes, and report on differences relative to other genomes, (2) assess genome completeness and compare content to other related genomes, and (3) assess the suitability of linked-read sequencing technology for future studies in comparative phylogenomics and population genomics studies. Our R. melanosticta assembly was both highly contiguous (de novo scaffold N50 = 3.3 Mb, reference based N50 = 53.3 Mb) and relatively complete (contained close to 90% of evolutionarily conserved single-copy avian genes and known tetrapod ultraconserved elements). The high contiguity and completeness of this assembly enabled the genome to be successfully mapped to the chromosome level, which uncovered a consistent structural difference between R. melanosticta and other avian genomes. Our results are consistent with the observation that avian genomes are structurally conserved. Additionally, our results demonstrate the utility of linked-read sequencing for non-model genomics. Finally, we demonstrate the value of our R. melanosticta genome for future researchers by mapping reduced representation sequencing data, and by accurately reconstructing the phylogenetic relationships among a sample of thamnophilid species.

scholarly journals DiscoSnp-RAD: de novo detection of small variants for RAD-Seq population genomics

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9291
Author(s):  
Jérémy Gauthier ◽  
Charlotte Mouden ◽  
Tomasz Suchan ◽  
Nadir Alvarez ◽  
Nils Arrigo ◽  
...  
Keyword(s):  
Evolutionary Biology ◽  
Restriction Site ◽  
Population Genomics ◽  
De Novo ◽  
State Of The Art ◽  
Phylogenetic Reconstruction ◽  
Original Method ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Require Time

Restriction site Associated DNA Sequencing (RAD-Seq) is a technique characterized by the sequencing of specific loci along the genome that is widely employed in the field of evolutionary biology since it allows to exploit variants (mainly Single Nucleotide Polymorphism—SNPs) information from entire populations at a reduced cost. Common RAD dedicated tools, such as STACKS or IPyRAD, are based on all-vs-all read alignments, which require consequent time and computing resources. We present an original method, DiscoSnp-RAD, that avoids this pitfall since variants are detected by exploiting specific parts of the assembly graph built from the reads, hence preventing all-vs-all read alignments. We tested the implementation on simulated datasets of increasing size, up to 1,000 samples, and on real RAD-Seq data from 259 specimens of Chiastocheta flies, morphologically assigned to seven species. All individuals were successfully assigned to their species using both STRUCTURE and Maximum Likelihood phylogenetic reconstruction. Moreover, identified variants succeeded to reveal a within-species genetic structure linked to the geographic distribution. Furthermore, our results show that DiscoSnp-RAD is significantly faster than state-of-the-art tools. The overall results show that DiscoSnp-RAD is suitable to identify variants from RAD-Seq data, it does not require time-consuming parameterization steps and it stands out from other tools due to its completely different principle, making it substantially faster, in particular on large datasets.

scholarly journals FecalSeq: methylation-based enrichment for noninvasive population genomics from feces

2015 ◽  
Author(s):  
Kenneth L. Chiou ◽  
Christina M. Bergey
Keyword(s):  
High Throughput Sequencing ◽  
Population Genomics ◽  
Population Level ◽  
Cost Effective ◽  
Fecal Dna ◽  
Host Animal ◽  
Preparation Methods ◽  
Exogenous Dna ◽  
Next Generation Sequencing Technology ◽  
Genomic Scale

AbstractObtaining high-quality samples from wild animals is a major obstacle for genomic studies of many taxa, particular at the population level, as collection methods for such samples are typically invasive. DNA from feces is easy to obtain noninvasively, but is dominated by a preponderance of bacterial and other non-host DNA. Because next-generation sequencing technology sequences DNA largely indiscriminately, the high proportion of exogenous DNA drastically reduces the efficiency of high-throughput sequencing for host animal genomics. In order to address this issue, we developed an inexpensive methylation-based capture method for enriching host DNA from noninvasively obtained fecal DNA samples. Our method exploits natural differences in CpG-methylation density between vertebrate and bacterial genomes to preferentially bind and isolate host DNA from majority-bacterial fecal DNA samples. We demonstrate that the enrichment is robust, efficient, and compatible with downstream library preparation methods useful for population studies (e.g., RADseq). Compared to other enrichment strategies, our method is quick and inexpensive, adding only a negligible cost to sample preparation for research that is often severely constrained by budgetary limitations. In combination with downstream methods such as RADseq, our approach allows for cost-effective and customizable genomic-scale genotyping that was previously feasible in practice only with invasive samples. Because feces are widely available and convenient to collect, our method empowers researchers to explore genomic-scale population-level questions in organisms for which invasive sampling is challenging or undesirable.

scholarly journals A beginner's guide to low-coverage whole genome sequencing for population genomics

2021 ◽  
Author(s):  
Runyang Nicolas Lou ◽  
Arne Jacobs ◽  
Aryn Wilder ◽  
Nina Overgaard Therkildsen
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Population Genomics ◽  
Cost Effective ◽  
Whole Genome ◽  
Model Species ◽  
Population Genomic ◽  
Genomic Studies ◽  
Lower Depth ◽  
Low Coverage

Low-coverage whole genome sequencing (lcWGS) has emerged as a powerful and cost-effective approach for population genomic studies in both model and non-model species. However, with read depths too low to confidently call individual genotypes, lcWGS requires specialized analysis tools that explicitly account for genotype uncertainty. A growing number of such tools have become available, but it can be difficult to get an overview of what types of analyses can be performed reliably with lcWGS data, and how the distribution of sequencing effort between the number of samples analyzed and per-sample sequencing depths affects inference accuracy. In this introductory guide to lcWGS, we first illustrate how the per-sample cost for lcWGS is now comparable to RAD-seq and Pool-seq in many systems. We then provide an overview of software packages that explicitly account for genotype uncertainty in different types of population genomic inference. Next, we use both simulated and empirical data to assess the accuracy of allele frequency and genetic diversity estimation, detection of population structure, and selection scans under different sequencing strategies. Our results show that spreading a given amount of sequencing effort across more samples with lower depth per sample consistently improves the accuracy of most types of inference, with a few notable exceptions. Finally, we assess the potential for using imputation to bolster inference from lcWGS data in non-model species, and discuss current limitations and future perspectives for lcWGS-based population genomics research. With this overview, we hope to make lcWGS more approachable and stimulate its broader adoption.

scholarly journals A beginner's guide to low-coverage whole genome sequencing for population genomics

2021 ◽  
Author(s):  
Runyang Nicolas Lou ◽  
Arne Jacobs ◽  
Aryn Wilder ◽  
Nina Overgaard Therkildsen
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Population Genomics ◽  
Cost Effective ◽  
Whole Genome ◽  
Model Species ◽  
Population Genomic ◽  
Genomic Studies ◽  
Lower Depth ◽  
Low Coverage

Low-coverage whole genome sequencing (lcWGS) has emerged as a powerful and cost-effective approach for population genomic studies in both model and non-model species. However, with read depths too low to confidently call individual genotypes, lcWGS requires specialized analysis tools that explicitly account for genotype uncertainty. A growing number of such tools have become available, but it can be difficult to get an overview of what types of analyses can be performed reliably with lcWGS data, and how the distribution of sequencing effort between the number of samples analyzed and per-sample sequencing depths affects inference accuracy. In this introductory guide to lcWGS, we first illustrate how the per-sample cost for lcWGS is now comparable to RAD-seq and Pool-seq in many systems. We then provide an overview of software packages that explicitly account for genotype uncertainty in different types of population genomic inference. Next, we use both simulated and empirical data to assess the accuracy of allele frequency and genetic diversity estimation, detection of population structure, and selection scans under different sequencing strategies. Our results show that spreading a given amount of sequencing effort across more samples with lower depth per sample consistently improves the accuracy of most types of inference, with a few notable exceptions. Finally, we assess the potential for using imputation to bolster inference from lcWGS data in non-model species, and discuss current limitations and future perspectives for lcWGS-based population genomics research. With this overview, we hope to make lcWGS more approachable and stimulate its broader adoption.

Successful development of microsatellite markers in a challenging species: the horizontal borer Austroplatypus incompertus (Coleoptera: Curculionidae)

2011 ◽  
Vol 101 (5) ◽  
pp. 551-555 ◽  
Author(s):  
S. Smith ◽  
T. Joss ◽  
A. Stow
Keyword(s):  
Microsatellite Markers ◽  
High Throughput ◽  
Evolutionary Biology ◽  
High Throughput Sequencing ◽  
Genomic Library ◽  
454 Sequencing ◽  
Cost Effective ◽  
Microsatellite Isolation ◽  
Potential Benefits ◽  
Neutral Markers

AbstractThe analysis of microsatellite loci has allowed significant advances in evolutionary biology and pest management. However, until very recently, the potential benefits have been compromised by the high costs of developing these neutral markers. High-throughput sequencing provides a solution to this problem. We describe the development of 13 microsatellite markers for the eusocial ambrosia beetle, Austroplatypus incompertus, a significant pest of forests in southeast Australia. The frequency of microsatellite repeats in the genome of A. incompertus was determined to be low, and previous attempts at microsatellite isolation using a traditional genomic library were problematic. Here, we utilised two protocols, microsatellite-enriched genomic library construction and high-throughput 454 sequencing and characterised 13 loci which were polymorphic among 32 individuals. Numbers of alleles per locus ranged from 2 to 17, and observed and expected heterozygosities from 0.344 to 0.767 and from 0.507 to 0.860, respectively. These microsatellites have the resolution required to analyse fine-scale colony and population genetic structure. Our work demonstrates the utility of next-generation 454 sequencing as a method for rapid and cost-effective acquisition of microsatellites where other techniques have failed, or for taxa where marker development has historically been both complicated and expensive.

scholarly journals DiscoSnp-RAD: de novo detection of small variants for population genomics

2017 ◽  
Author(s):  
Jèrèmy Gauthier ◽  
Charlotte Mouden ◽  
Tomasz Suchan ◽  
Nadir Alvarez ◽  
Nils Arrigo ◽  
...  
Keyword(s):  
Evolutionary Biology ◽  
Restriction Site ◽  
Population Genomics ◽  
De Novo ◽  
State Of The Art ◽  
Phylogenetic Reconstruction ◽  
Original Method ◽  
De Bruijn Graph ◽  
Order Of Magnitude ◽  
Two Populations

AbstractWe present an original method to de novo call variants for Restriction site associated DNA Sequencing (RAD-Seq). RAD-Seq is a technique characterized by the sequencing of specific loci along the genome, that is widely employed in the field of evolutionary biology since it allows to exploit variants (mainly SNPs) information from entire populations at a reduced cost. Common RAD dedicated tools, as STACKS or IPyRAD, are based on all-versus-all read comparisons, which require consequent time and computing resources. Based on the variant caller DiscoSnp, initially designed for shotgun sequencing, DiscoSnp-RAD avoids this pitfall as variants are detected by exploring the De Bruijn Graph built from all the read datasets. We tested the implementation on RAD data from 259 specimens of Chiastocheta flies, morphologically assigned to 7 species. All individuals were successfully assigned to their species using both STRUCTURE and Maximum Likelihood phylogenetic reconstruction. Moreover, identified variants succeeded to reveal a within species structuration and the existence of two populations linked to their geographic distributions. Furthermore, our results show that DiscoSnp-RAD is at least one order of magnitude faster than state-of-the-art tools. The overall results show that DiscoSnp-RAD is suitable to identify variants from RAD data, and stands out from other tools due to his completely different principle, making it significantly faster, in particular on large datasets.LicenseGNU Affero general public licenseAvailabilityhttps://github.com/GATB/[email protected]

scholarly journals Higher quality de novo genome assemblies from degraded museum specimens: a linked-read approach to museomics

2019 ◽  
Author(s):  
Jocelyn P. Colella ◽  
Anna Tigano ◽  
Matthew D. MacManes
Keyword(s):  
High Throughput Sequencing ◽  
De Novo ◽  
Deer Mouse ◽  
Cost Effective ◽  
Molecular Data ◽  
Degraded Dna ◽  
Museum Specimens ◽  
Sequencing Technologies ◽  
Long Read ◽  
Genome Assemblies

AbstractHigh-throughput sequencing technologies are a proposed solution for accessing the molecular data in historic specimens. However, degraded DNA combined with the computational demands of short-read assemblies has posed significant laboratory and bioinformatics challenges. Linked-read or ‘synthetic long-read’ sequencing technologies, such as 10X Genomics, may provide a cost-effective alternative solution to assemble higher quality de novo genomes from degraded specimens. Here, we compare assembly quality (e.g., genome contiguity and completeness, presence of orthogroups) between four published genomes assembled from a single shotgun library and four deer mouse (Peromyscus spp.) genomes assembled using 10X Genomics technology. At a similar price-point, these approaches produce vastly different assemblies, with linked-read assemblies having overall higher quality, measured by larger N50 values and greater gene content. Although not without caveats, our results suggest that linked-read sequencing technologies may represent a viable option to build de novo genomes from historic museum specimens, which may prove particularly valuable for extinct, rare, or difficult to collect taxa.

scholarly journals A beginner's guide to low-coverage whole genome sequencing for population genomics

2020 ◽  
Author(s):  
Runyang Nicolas Lou ◽  
Arne Jacobs ◽  
Aryn Wilder ◽  
Nina Overgaard Therkildsen
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Population Genomics ◽  
Frequency Estimation ◽  
Cost Effective ◽  
Whole Genome ◽  
Model Species ◽  
Population Genomic ◽  
Lower Depth ◽  
Low Coverage

Low-coverage whole genome sequencing (lcWGS) has emerged as a powerful and cost-effective approach for population genomic studies in both model and non-model species. However, with read depths too low to confidently call individual genotypes, lcWGS requires specialized analysis tools that explicitly account for genotype uncertainty. A growing number of such tools have become available, but it can be difficult to get an overview of what types of analyses can be performed reliably with lcWGS data and how the distribution of sequencing effort between the number of samples analyzed and per-sample sequencing depths affects inference accuracy. In this introductory guide to lcWGS, we first illustrate that the per-sample cost for lcWGS is now comparable to RAD-seq and Pool-seq in many systems. We then provide an overview of software packages that explicitly account for genotype uncertainty in different types of population genomic inference. Next, we use both simulated and empirical data to assess the accuracy of allele frequency estimation, detection of population structure, and selection scans under different sequencing strategies. Our results show that spreading a given amount of sequencing effort across more samples with lower depth per sample consistently improves the accuracy of most types of inference compared to sequencing fewer samples each at higher depth. Finally, we assess the potential for using imputation to bolster inference from lcWGS data in non-model species, and discuss current limitations and future perspectives for lcWGS-based analysis. With this overview, we hope to make lcWGS more approachable and stimulate broader adoption.

scholarly journals The Oyster River Protocol: A Multi Assembler and Kmer Approach For de novo Transcriptome Assembly

2017 ◽  
Author(s):  
Matthew D. MacManes
Keyword(s):  
High Throughput Sequencing ◽  
Population Genomics ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Model Organisms ◽  
De Novo Transcriptome ◽  
Link Type ◽  
Biological Phenomena ◽  
Complicated Process ◽  
Downstream Analysis

AbstractCharacterizing transcriptomes in non-model organisms has resulted in a massive increase in our understanding of biological phenomena. This boon, largely made possible via high-throughput sequencing, means that studies of functional, evolutionary and population genomics are now being done by hundreds or even thousands of labs around the world. For many, these studies begin with a de novo transcriptome assembly, which is a technically complicated process involving several discrete steps. The Oyster River Protocol (ORP), described here, implements a standardized and benchmarked set of bioinformatic processes, resulting in an assembly with enhanced qualities over other standard assembly methods. Specifically, ORP produced assemblies have higher Detonate and TransRate scores and mapping rates, which is largely a product of the fact that it leverages a multi-assembler and kmer assembly process, thereby bypassing the shortcomings of any one approach. These improvements are important, as previously unassembled transcripts are included in ORP assemblies, resulting in a significant enhancement of the power of downstream analysis. Further, as part of this study, I show that assembly quality is unrelated with the number of reads generated, above 30 million reads. Code Availability: The version controlled open-source code is available at https://github.com/macmanes-lab/Oyster_River_Protocol. Instructions for software installation and use, and other details are available at http://oyster-river-protocol.rtfd.org/.

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