Population genomics ofC. melanopterususing target gene capture data: demographic inferences and conservation perspectives

Mapping Intimacies ◽

10.1101/068106 ◽

2016 ◽

Author(s):

Pierpaolo Maisano Delser ◽

Shannon Corrigan ◽

Matthew Hale ◽

Chenhong Li ◽

Michel Veuille ◽

...

Keyword(s):

Target Gene ◽

Population Genomics ◽

Model Organism ◽

Sampling Scheme ◽

Model Organisms ◽

Gene Capture ◽

Sampling Schemes ◽

History Of ◽

Carcharhinus Melanopterus ◽

Target Gene Capture

AbstractPopulation genetics studies on non-model organisms typically involve sampling few markers from multiple individuals. Next-generation sequencing approaches open up the possibility of sampling many more markers from fewer individuals to address the same questions. Here, we applied a target gene capture method to deep sequence ∼1000 independent autosomal regions of a non-model organism, the blacktip reef shark (Carcharhinus melanopterus). We devised a sampling scheme based on the predictions of theoretical studies of metapopulations to show that sampling few individuals, but many loci, can be extremely informative to reconstruct the evolutionary history of species. We collected data from a single deme (SID) from Northern Australia and from a scattered sampling representing various locations throughout the Indian Ocean (SCD). We explored the genealogical signature of population dynamics detected from both sampling schemes using an ABC algorithm. We then contrasted these results with those obtained by fitting the data to a non-equilibrium finite island model. Both approaches supported anNmvalue ∼40, consistent with philopatry in this species. Finally, we demonstrate through simulation that metapopulations exhibit greater resilience to recent changes in effective size compared to unstructured populations. We propose an empirical approach to detect recent bottlenecks based on our sampling scheme.

Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives

Scientific Reports ◽

10.1038/srep33753 ◽

2016 ◽

Vol 6 (1) ◽

Cited By ~ 17

Author(s):

Pierpaolo Maisano Delser ◽

Shannon Corrigan ◽

Matthew Hale ◽

Chenhong Li ◽

Michel Veuille ◽

...

Keyword(s):

Target Gene ◽

Population Genomics ◽

Gene Capture ◽

Target Gene Capture

Molecular Diagnostic Approaches to Metabolic Myopathies by Target Gene Capture and Next Generation Sequencing (P07.215)

Neurology ◽

10.1212/wnl.78.1_meetingabstracts.p07.215 ◽

2012 ◽

Vol 78 (Meeting Abstracts 1) ◽

pp. P07.215-P07.215

Author(s):

V. Zhang ◽

H. Cui ◽

J. Wang ◽

L.-j. Wong

Keyword(s):

Next Generation Sequencing ◽

Target Gene ◽

Molecular Diagnostic ◽

Next Generation ◽

Gene Capture ◽

Metabolic Myopathies ◽

Diagnostic Approaches ◽

Generation Sequencing ◽

Target Gene Capture

Improved molecular diagnosis by the detection of exonic deletions with target gene capture and deep sequencing

Genetics in Medicine ◽

10.1038/gim.2014.80 ◽

2014 ◽

Vol 17 (2) ◽

pp. 99-107 ◽

Cited By ~ 50

Author(s):

Yanming Feng ◽

David Chen ◽

Guo-Li Wang ◽

Victor Wei Zhang ◽

Lee-Jun C. Wong

Keyword(s):

Molecular Diagnosis ◽

Deep Sequencing ◽

Target Gene ◽

Gene Capture ◽

Target Gene Capture

Target Gene Capture Sequencing in Chinese Population of Sporadic Parkinson Disease

Medicine ◽

10.1097/md.0000000000000836 ◽

2015 ◽

Vol 94 (20) ◽

pp. e836 ◽

Cited By ~ 4

Author(s):

Zhiming Li ◽

Qing Lin ◽

Wenqing Huang ◽

Chi-Meng Tzeng

Keyword(s):

Parkinson Disease ◽

Chinese Population ◽

Target Gene ◽

Gene Capture ◽

Capture Sequencing ◽

Target Gene Capture

ParameciumDB 2019: integrating genomic data across the genus for functional and evolutionary biology

Nucleic Acids Research ◽

10.1093/nar/gkz948 ◽

2019 ◽

Cited By ~ 2

Author(s):

Olivier Arnaiz ◽

Eric Meyer ◽

Linda Sperling

Keyword(s):

Evolutionary Biology ◽

Model Organism ◽

Model Organisms ◽

Web Interface ◽

Model Organism Database ◽

Whole Genome Duplications ◽

Community Model ◽

Genome Duplications ◽

History Of ◽

Somatic Genome

Abstract ParameciumDB (https://paramecium.i2bc.paris-saclay.fr) is a community model organism database for the genome and genetics of the ciliate Paramecium. ParameciumDB development relies on the GMOD (www.gmod.org) toolkit. The ParameciumDB web site has been publicly available since 2006 when the P. tetraurelia somatic genome sequence was released, revealing that a series of whole genome duplications punctuated the evolutionary history of the species. The genome is linked to available genetic data and stocks. ParameciumDB has undergone major changes in its content and website since the last update published in 2011. Genomes from multiple Paramecium species, especially from the P. aurelia complex, are now included in ParameciumDB. A new modern web interface accompanies this transition to a database for the whole Paramecium genus. Gene pages have been enriched with orthology relationships, among the Paramecium species and with a panel of model organisms across the eukaryotic tree. This update also presents expert curation of Paramecium mitochondrial genomes.

The unlimited potential of the great pond snail, Lymnaea stagnalis

eLife ◽

10.7554/elife.56962 ◽

2020 ◽

Vol 9 ◽

Cited By ~ 4

Author(s):

István Fodor ◽

Ahmed AA Hussein ◽

Paul R Benjamin ◽

Joris M Koene ◽

Zsolt Pirger

Keyword(s):

Animal Species ◽

Lymnaea Stagnalis ◽

Large Range ◽

Model Organism ◽

Freshwater Snail ◽

Model Organisms ◽

Pond Snail ◽

Host Parasite Interactions ◽

History Of ◽

Host Parasite

Only a limited number of animal species lend themselves to becoming model organisms in multiple biological disciplines: one of these is the great pond snail, Lymnaea stagnalis. Extensively used since the 1970s to study fundamental mechanisms in neurobiology, the value of this freshwater snail has been also recognised in fields as diverse as host–parasite interactions, ecotoxicology, evolution, genome editing and 'omics', and human disease modelling. While there is knowledge about the natural history of this species, what is currently lacking is an integration of findings from the laboratory and the field. With this in mind, this article aims to summarise the applicability of L. stagnalis and points out that this multipurpose model organism is an excellent, contemporary choice for addressing a large range of different biological questions, problems and phenomena.

C. elegans outside the Petri dish

eLife ◽

10.7554/elife.05849 ◽

2015 ◽

Vol 4 ◽

Cited By ~ 170

Author(s):

Lise Frézal ◽

Marie-Anne Félix

Keyword(s):

Model Organism ◽

Resource Depletion ◽

Petri Dish ◽

Model Organisms ◽

Laboratory Animals ◽

Biological Research ◽

C Elegans ◽

The Status ◽

Boom And Bust ◽

History Of

The roundworm Caenorhabditis elegans has risen to the status of a top model organism for biological research in the last fifty years. Among laboratory animals, this tiny nematode is one of the simplest and easiest organisms to handle. And its life outside the laboratory is beginning to be unveiled. Like other model organisms, C. elegans has a boom-and-bust lifestyle. It feasts on ephemeral bacterial blooms in decomposing fruits and stems. After resource depletion, its young larvae enter a migratory diapause stage, called the dauer. Organisms known to be associated with C. elegans include migration vectors (such as snails, slugs and isopods) and pathogens (such as microsporidia, fungi, bacteria and viruses). By deepening our understanding of the natural history of C. elegans, we establish a broader context and improved tools for studying its biology.

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 ◽

10.3390/ani11082226 ◽

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.

Alliance of Genome Resources Portal: unified model organism research platform

Nucleic Acids Research ◽

10.1093/nar/gkz813 ◽

2019 ◽

Vol 48 (D1) ◽

pp. D650-D658 ◽

Cited By ~ 36

Author(s):

◽

Julie Agapite ◽

Laurent-Philippe Albou ◽

Suzi Aleksander ◽

Joanna Argasinska ◽

...

Keyword(s):

Gene Ontology ◽

Model Organism ◽

Model Organisms ◽

Data Types ◽

Primary Model ◽

Genomic Studies ◽

Health And Disease ◽

Extensive Body ◽

Access To Data ◽

Model Organism Databases

Abstract The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource.

Power-Cost Efficiency of Eight Macrobenthic Sampling Schemes in Puget Sound, Washington, USA

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f89-267 ◽

1989 ◽

Vol 46 (12) ◽

pp. 2157-2165 ◽

Cited By ~ 32

Author(s):

Steven P. Ferraro ◽

Faith A. Cole ◽

Waldemar A. DeBen ◽

Richard C. Swartz

Keyword(s):

Cost Efficiency ◽

Statistical Power ◽

Rank Order ◽

Puget Sound ◽

Sampling Scheme ◽

Total Biomass ◽

Type I ◽

Power Cost ◽

Sampling Schemes ◽

Sample Unit

Power-cost efficiency (PCEi = (n × c)min/(ni × ci), where i = sampling scheme, n = minimum number of replicate samples needed to detect a difference between locations with an acceptable probability of Type I (α) and Type II (β) error (e.g. α = β = 0.05), c = mean "cost," in time or money, per replicate sample, and (n × c)min = minimum value of (n × c) among the i sampling schemes) is the appropriate expression for comparing the cost efficiency of alternative sampling schemes having equivalent statistical rigor when the statistical model is a redistribution for comparisons of two means. PCEs were determined for eight macrobenthic sampling schemes (four sample unit sizes and two sieve mesh sizes) in a comparison of a reference site versus a putative polluted site in Puget Sound, Washington. Laboratory processing times were, on average, about 2.5 times greater for the [Formula: see text]- than the [Formula: see text] samples. The 0.06-m2, 0- to 8-cm-deep sample unit size and 1.0-mm sieve mesh size was the overall optimum sampling scheme in this study; it ranked first in PCE on 8 and second on 3 of 11 measures of community structure. Rank order by statistical power of the 11 measures for this scheme was Infaunal Index > log10 (mollusc biomass + 1) > number of species > log10 (numerical abundance) > log10 (polychaete biomass + 1) > log10 (total biomass + 1) > log10 (crustacean biomass + 1) > McIntosh's index > 1 – Simpson's Index > Shannon's Index > Dominance Index.