Fast and cost‐effective single nucleotide polymorphism (<scp>SNP</scp>) detection in the absence of a reference genome using semideep next‐generation Random Amplicon Sequencing (<scp>RAM</scp>seq)

Bayerl, Helmut; Kraus, Robert H. S.; Nowak, Carsten; Foerster, Daniel W.; Fickel, Joerns; Kuehn, Ralph

doi:10.1111/1755-0998.12717

Cited by 18 publications

(20 citation statements)

References 57 publications

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“…Scent detection teams proved to be similarly effective to baited camera stations in detecting martens during our study as compared with baited camera stations, and we were likely underestimating number of detections from dog teams because only 45% of the samples amplified. Genetically verified samples are necessary for establishing distribution for rare carnivores, and innovations using new genetic methods have promise to increase amplification rates (Davison et al , Bayerl et al ). Meanwhile, our estimated costs for distribution surveys (per marten presence) were lower for scent detection teams during this study, but low amplification rates (17%) when identifying individual marten or their sex limited their utility and increased costs compared with hair collected from baited hair snares at camera stations.…”

Section: Discussionmentioning

confidence: 99%

Seeking efficiency with carnivore survey methods: A case study with elusive martens

et al. 2018

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Obtaining reliable information on species distributions is often the first step in conservation. Distribution information can be used to focus survey efforts to estimate population size and examine drivers of occupancy or other population parameters. We compared detection rates and survey costs for 2 techniques (remote cameras and scent detection teams) used to evaluate distribution of a rare carnivore, Humboldt subspecies of Pacific marten (Martes caurina humboldtensis). We used remote cameras at randomly placed sites in coastal Oregon, USA, to compare camera set type (baited, unbaited), bait height (<0.5 m, 1.37 m), and bait types (chicken and lure, cat food) for a 21‐day survey period during winter (27 Jan–12 Apr) and summer (04 Jul–14 Oct) 2015. When a marten was detected, we completed an additional survey within 25 m. Scent detection teams (human handler and dog) performed area‐constrained searches for scat deposited. We used a Bayesian occupancy model to compare detection probabilities for baited camera treatments. We detected martens at 26 sites, and offset stations detected martens at 15 of 24 sites (62.5%). Survey‐level detection probability for martens (the probability of detecting ≥1 marten during a survey) was high for the camera survey during summer and winter (estimates ranged from 60% to 99% and 33% to 82%, respectively), and similar for all treatments. We surveyed 50 sites with both remote cameras and scent detection teams 25 April–25 May 2015. Of 33 sites with ≥1 marten detection, 36.4% of units had a marten detected only by scent detection teams, 30.3% only by remote camera, and 33.3% by both techniques. When the objective was marten detection, survey costs were less for scent detection teams. For identifying individual martens and their sex, cameras paired with hair snares were more cost‐efficient. Scent detection teams provided a complementary method to baited remote cameras for assessing distribution. Using multiple techniques provided an opportunity to quantify limitations of survey methods. © 2018 The Wildlife Society.

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Section: Discussionmentioning

confidence: 99%

Seeking efficiency with carnivore survey methods: A case study with elusive martens

et al. 2018

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“…High‐throughput sequencing or other approaches (e.g., Sanger sequencing, also see Bayerl et al., for a recent application using RAPD) have been widely used to develop SNP markers through cost‐effective, semideep sequencing. Here, we validated the possibility of using a small‐scale RAD‐Seq protocol to extend these applications to dozens of species at a time.…”

Section: Discussionmentioning

confidence: 99%

“…High-throughput sequencing or other approaches (e.g., Sanger sequencing, also see Bayerl et al, 2018 The first pipeline filter had the most drastic effect on SNP selection: across the 10 species with the lowest number of final SNP markers (<100), most RAD-tags were discarded at this step. Indeed, the number of sequencing reads after PCR duplicate removal was low for some of these species leading to a high number of RADtags displaying low depth of coverage.…”

Section: Multispecies Dna Sequencingmentioning

confidence: 99%

A cost‐and‐time effective procedure to develop SNP markers for multiple species: A support for community genetics

et al. 2018

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Multispecies population genetics is an emerging field that provides insight relevant to conservation biology and community ecology. However, to date, this approach is limited to species with available genetic resources. The use of thousands of single‐nucleotide polymorphism (SNP) markers developed from recent genotyping‐by‐sequencing (GBS) technologies is a roadmap for the study of nonmodel species, but remains cost prohibitive when several, distantly related species are involved. We aimed to overcome this issue using a single HiSeq3000 run of restriction‐site associated DNA sequencing (RAD‐Seq) to retrieve SNP markers for 40 diverse species including plants, invertebrates, fish, and mammals. We developed a Python‐based pipeline to isolate c. 100–500 high‐quality SNP markers for each species that could be genotyped through classical PCR amplification methods. To assess the quality of these markers, we validated our approach on c. 160 of the characterized SNPs for each of 18 Neotropical fish species from the river Maroni (French Guiana, South America), using the MassARRAY iPLEX platform from Agena Bioscience (San Diego, CA, USA). A run of the pipeline applying stringent filtering parameters enabled the successful design of between 130 and 3,492 SNP markers for 30 of the 40 study species. Relaxing pipeline parameters allows for an increase in the number of detected SNPs. Across the 18 species from French Guiana, an average of 85% of markers were successfully amplified, polymorphic, and scored in ≥90% of individuals (c. 200 individuals per species). The great majority (>98%) of these markers were at Hardy–Weinberg equilibrium in each sampling site from the river Maroni. This SNP discovery was performed at the cost of c. $US110 for each of the 40 species. Genotyping was performed at the cost of c. $US6000 for each of the 18 fish species with an average of 200 individuals per species. This strategy was found cost‐and‐time efficient to develop hundreds of SNP markers for a large range of nonmodel species, which can be used to investigate ecological and evolutionary questions that do not require whole‐genome coverage.

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“…It is investigated that there is a thoughtful issue of computation slant in genomic data, i.e., the size of the input file is the same while processing time of variant calling is still significantly different [4]. Single nucleotide polymorphism (SNP) is a variant of a single nucleotide which exists at a particular locus in the genome, where respective variant exists up-to noticeable degree in a population of a residence [5][6][7][8]. SNP is a genetic variation triggered by the alteration of a single nucleotide base i.e., A, C, G, and T in DNA sequences [9].…”

Section: Introductionmentioning

confidence: 99%

A Fast and Scalable Workflow for SNPs Detection in Genome Sequences Using Hadoop Map-Reduce

Tahir

Sardaraz

2020

Genes

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Next generation sequencing (NGS) technologies produce a huge amount of biological data, which poses various issues such as requirements of high processing time and large memory. This research focuses on the detection of single nucleotide polymorphism (SNP) in genome sequences. Currently, SNPs detection algorithms face several issues, e.g., computational overhead cost, accuracy, and memory requirements. In this research, we propose a fast and scalable workflow that integrates Bowtie aligner with Hadoop based Heap SNP caller to improve the SNPs detection in genome sequences. The proposed workflow is validated through benchmark datasets obtained from publicly available web-portals, e.g., NCBI and DDBJ DRA. Extensive experiments have been performed and the results obtained are compared with Bowtie and BWA aligner in the alignment phase, while compared with GATK, FaSD, SparkGA, Halvade, and Heap in SNP calling phase. Experimental results analysis shows that the proposed workflow outperforms existing frameworks e.g., GATK, FaSD, Heap integrated with BWA and Bowtie aligners, SparkGA, and Halvade. The proposed framework achieved 22.46% more efficient F-score and 99.80% consistent accuracy on average. More, comparatively 0.21% mean higher accuracy is achieved. Moreover, SNP mining has also been performed to identify specific regions in genome sequences. All the frameworks are implemented with the default configuration of memory management. The observations show that all workflows have approximately same memory requirement. In the future, it is intended to graphically show the mined SNPs for user-friendly interaction, analyze and optimize the memory requirements as well.

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Fast and cost‐effective single nucleotide polymorphism (SNP) detection in the absence of a reference genome using semideep next‐generation Random Amplicon Sequencing (RAMseq)

Cited by 18 publications

References 57 publications

Seeking efficiency with carnivore survey methods: A case study with elusive martens

Seeking efficiency with carnivore survey methods: A case study with elusive martens

A cost‐and‐time effective procedure to develop SNP markers for multiple species: A support for community genetics

A Fast and Scalable Workflow for SNPs Detection in Genome Sequences Using Hadoop Map-Reduce

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