scholarly journals ClineHelpR: an R package for genomic cline outlier detection and visualization

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Bradley T. Martin ◽  
Tyler K. Chafin ◽  
Marlis R. Douglas ◽  
Michael E. Douglas
Keyword(s):  
Management Strategies ◽  
R Package ◽  
Model Organisms ◽  
Hybrid Zones ◽  
Testing Tools ◽  
File Formats ◽  
Genome Wide ◽  
Outlier Loci ◽  
Adaptive Processes ◽  
Post Hoc

Abstract Background Patterns of multi-locus differentiation (i.e., genomic clines) often extend broadly across hybrid zones and their quantification can help diagnose how species boundaries are shaped by adaptive processes, both intrinsic and extrinsic. In this sense, the transitioning of loci across admixed individuals can be contrasted as a function of the genome-wide trend, in turn allowing an expansion of clinal theory across a much wider array of biodiversity. However, computational tools that serve to interpret and consequently visualize ‘genomic clines’ are limited, and users must often write custom, relatively complex code to do so. Results Here, we introduce the ClineHelpR R-package for visualizing genomic clines and detecting outlier loci using output generated by two popular software packages, bgc and Introgress. ClineHelpR bundles both input generation (i.e., filtering datasets and creating specialized file formats) and output processing (e.g., MCMC thinning and burn-in) with functions that directly facilitate interpretation and hypothesis testing. Tools are also provided for post-hoc analyses that interface with external packages such as ENMeval and RIdeogram. Conclusions Our package increases the reproducibility and accessibility of genomic cline methods, thus allowing an expanded user base and promoting these methods as mechanisms to address diverse evolutionary questions in both model and non-model organisms. Furthermore, the ClineHelpR extended functionality can evaluate genomic clines in the context of spatial and environmental features, allowing users to explore underlying processes potentially contributing to the observed patterns and helping facilitate effective conservation management strategies.

scholarly journals ClinePlotR: Visualizing genomic clines and detecting outliers in R

2020 ◽  
Author(s):  
Bradley T. Martin ◽  
Tyler K. Chafin ◽  
Marlis R. Douglas ◽  
Michael E. Douglas
Keyword(s):  
R Package ◽  
Model Organisms ◽  
Hybrid Zones ◽  
Testing Tools ◽  
Software Packages ◽  
File Formats ◽  
Genome Wide ◽  
Outlier Loci ◽  
Adaptive Processes ◽  
Post Hoc

AbstractPatterns of multi-locus differentiation (i.e., genomic clines) often extend broadly across hybrid zones and their quantification can help diagnose how species boundaries are shaped by adaptive processes, both intrinsic and extrinsic. In this sense, the transitioning of loci across admixed individuals can be contrasted as a function of the genome-wide trend, in turn allowing an expansion of clinal theory across a much wider array of biodiversity. However, computational tools that serve to interpret and consequently visualize ‘genomic clines’ are limited. Here, we introduce the ClinePlotR R-package for visualizing genomic clines and detecting outlier loci using output generated by two popular software packages, bgc and Introgress. ClinePlotR bundles both input generation (i.e, filtering datasets and creating specialized file formats) and output processing (e.g., MCMC thinning and burn-in) with functions that directly facilitate interpretation and hypothesis testing. Tools are also provided for post-hoc analyses that interface with external packages such as ENMeval and RIdeogram. Our package increases the reproducibility and accessibility of genomic cline methods, thus allowing an expanded user base and promoting these methods as mechanisms to address diverse evolutionary questions in both model and non-model organisms.

EpiPen: An R Package to Investigate Two-Locus Epistatic Models

2014 ◽  
Vol 17 (4) ◽  
Author(s):  
Raymond K. Walters ◽  
Charles Laurin ◽  
Gitta H. Lubke
Keyword(s):  
Power Analysis ◽  
R Package ◽  
Simulation Studies ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Epistatic Interactions ◽  
Model Interpretation ◽  
Genome Wide ◽  
Using Data ◽  
Power Analyses

Epistasis is a growing area of research in genome-wide studies, but the differences between alternative definitions of epistasis remain a source of confusion for many researchers. One problem is that models for epistasis are presented in a number of formats, some of which have difficult-to-interpret parameters. In addition, the relation between the different models is rarely explained. Existing software for testing epistatic interactions between single-nucleotide polymorphisms (SNPs) does not provide the flexibility to compare the available model parameterizations. For that reason we have developed an R package for investigating epistatic and penetrance models, EpiPen, to aid users who wish to easily compare, interpret, and utilize models for two-locus epistatic interactions. EpiPen facilitates research on SNP-SNP interactions by allowing the R user to easily convert between common parametric forms for two-locus interactions, generate data for simulation studies, and perform power analyses for the selected model with a continuous or dichotomous phenotype. The usefulness of the package for model interpretation and power analysis is illustrated using data on rheumatoid arthritis.

scholarly journals Rapid and inexpensive preparation of genome-wide nucleosome footprints from model and non-model organisms

2021 ◽  
Vol 2 (2) ◽  
pp. 100486
Author(s):  
Laura E. McKnight ◽  
Johnathan G. Crandall ◽  
Thomas B. Bailey ◽  
Orion G.B. Banks ◽  
Kona N. Orlandi ◽  
...  
Keyword(s):  
Model Organisms ◽  
Genome Wide

scholarly journals Genome-wide characterization of 2-oxoglutarate and Fe(II)-dependent dioxygenase family genes in tomato during growth cycle and their roles in metabolism

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shuo Wei ◽  
Wen Zhang ◽  
Rao Fu ◽  
Yang Zhang
Keyword(s):  
Metabolic Pathways ◽  
Developmental Stages ◽  
Expression Patterns ◽  
Growth Cycle ◽  
Model Organisms ◽  
Gibberellin Biosynthesis ◽  
Type I ◽  
Multiple Model ◽  
Genome Wide ◽  
Tomato Growth

Abstract Background 2-Oxoglutarate and Fe(II)-dependent dioxygenases (2ODDs) belong to the 2-oxoglutarate-dependent dioxygenase (2OGD) superfamily and are involved in various vital metabolic pathways of plants at different developmental stages. These proteins have been extensively investigated in multiple model organisms. However, these enzymes have not been systematically analyzed in tomato. In addition, type I flavone synthase (FNSI) belongs to the 2ODD family and contributes to the biosynthesis of flavones, but this protein has not been characterized in tomato. Results A total of 131 2ODDs from tomato were identified and divided into seven clades by phylogenetic classification. The Sl2ODDs in the same clade showed similar intron/exon distributions and conserved motifs. The Sl2ODDs were unevenly distributed across the 12 chromosomes, with different expression patterns among major tissues and at different developmental stages of the tomato growth cycle. We characterized several Sl2ODDs and their expression patterns involved in various metabolic pathways, such as gibberellin biosynthesis and catabolism, ethylene biosynthesis, steroidal glycoalkaloid biosynthesis, and flavonoid metabolism. We found that the Sl2ODD expression patterns were consistent with their functions during the tomato growth cycle. These results indicated the significance of Sl2ODDs in tomato growth and metabolism. Based on this genome-wide analysis of Sl2ODDs, we screened six potential FNSI genes using a phylogenetic tree and coexpression analysis. However, none of them exhibited FNSI activity. Conclusions Our study provided a comprehensive understanding of the tomato 2ODD family and demonstrated the significant roles of these family members in plant metabolism. We also suggest that no FNSI genes in tomato contribute to the biosynthesis of flavones.

scholarly journals BREC: an R package/Shiny app for automatically identifying heterochromatin boundaries and estimating local recombination rates along chromosomes

2021 ◽  
Vol 22 (S6) ◽  
Author(s):  
Yasmine Mansour ◽  
Annie Chateau ◽  
Anna-Sophie Fiston-Lavier
Keyword(s):  
Data Quality ◽  
Data Science ◽  
Fruit Fly ◽  
R Package ◽  
Model Organisms ◽  
Data Quality Control ◽  
Recombination Rates ◽  
Functional Dynamics ◽  
Shiny App ◽  
User Friendly

Abstract Background Meiotic recombination is a vital biological process playing an essential role in genome's structural and functional dynamics. Genomes exhibit highly various recombination profiles along chromosomes associated with several chromatin states. However, eu-heterochromatin boundaries are not available nor easily provided for non-model organisms, especially for newly sequenced ones. Hence, we miss accurate local recombination rates necessary to address evolutionary questions. Results Here, we propose an automated computational tool, based on the Marey maps method, allowing to identify heterochromatin boundaries along chromosomes and estimating local recombination rates. Our method, called BREC (heterochromatin Boundaries and RECombination rate estimates) is non-genome-specific, running even on non-model genomes as long as genetic and physical maps are available. BREC is based on pure statistics and is data-driven, implying that good input data quality remains a strong requirement. Therefore, a data pre-processing module (data quality control and cleaning) is provided. Experiments show that BREC handles different markers' density and distribution issues. Conclusions BREC's heterochromatin boundaries have been validated with cytological equivalents experimentally generated on the fruit fly Drosophila melanogaster genome, for which BREC returns congruent corresponding values. Also, BREC's recombination rates have been compared with previously reported estimates. Based on the promising results, we believe our tool has the potential to help bring data science into the service of genome biology and evolution. We introduce BREC within an R-package and a Shiny web-based user-friendly application yielding a fast, easy-to-use, and broadly accessible resource. The BREC R-package is available at the GitHub repository https://github.com/GenomeStructureOrganization.

scholarly journals Single Nucleotide Polymorphism Discovery and Genetic Differentiation Analysis of Geese Bred in Poland, Using Genotyping-by-Sequencing (GBS)

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 1074
Author(s):  
Joanna Grzegorczyk ◽  
Artur Gurgul ◽  
Maria Oczkowicz ◽  
Tomasz Szmatoła ◽  
Agnieszka Fornal ◽  
...  
Keyword(s):  
Genotyping By Sequencing ◽  
Read Depth ◽  
Model Organisms ◽  
Single Nucleotide Polymorphism Discovery ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Polymorphism Discovery ◽  
Genome Wide ◽  
Plumage Development ◽  
Edar Gene

Poland is the largest European producer of goose, while goose breeding has become an essential and still increasing branch of the poultry industry. The most frequently bred goose is the White Kołuda® breed, constituting 95% of the country’s population, whereas geese of regional varieties are bred in smaller, conservation flocks. However, a goose’s genetic diversity is inaccurately explored, mainly because the advantages of the most commonly used tools are strongly limited in non-model organisms. One of the most accurate used markers for population genetics is single nucleotide polymorphisms (SNP). A highly efficient strategy for genome-wide SNP detection is genotyping-by-sequencing (GBS), which has been already widely applied in many organisms. This study attempts to use GBS in 12 conservative goose breeds and the White Kołuda® breed maintained in Poland. The GBS method allowed for the detection of 3833 common raw SNPs. Nevertheless, after filtering for read depth and alleles characters, we obtained the final markers panel used for a differentiation analysis that comprised 791 SNPs. These variants were located within 11 different genes, and one of the most diversified variants was associated with the EDAR gene, which is especially interesting as it participates in the plumage development, which plays a crucial role in goose breeding.

scholarly journals Gene set enrichment analysis for genome-wide DNA methylation data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jovana Maksimovic ◽  
Alicia Oshlack ◽  
Belinda Phipson
Keyword(s):  
Dna Methylation ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Methylation Array ◽  
Gene Set ◽  
Genome Wide ◽  
Genome Methylation ◽  
Unbiased Gene ◽  
Gene Set Testing

AbstractDNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.

scholarly journals Humans and other commonly used model organisms are resistant to cycloheximide-mediated biases in ribosome profiling experiments

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Puneet Sharma ◽  
Jie Wu ◽  
Benedikt S. Nilges ◽  
Sebastian A. Leidel
Keyword(s):  
Human Cells ◽  
Ribosome Profiling ◽  
Model Organisms ◽  
Treatment Conditions ◽  
Genome Wide ◽  
Optimized Protocol ◽  
Gene Level ◽  
Translation Inhibitor ◽  
Species Specific ◽  
Conformational Restrictions

AbstractRibosome profiling measures genome-wide translation dynamics at sub-codon resolution. Cycloheximide (CHX), a widely used translation inhibitor to arrest ribosomes in these experiments, has been shown to induce biases in yeast, questioning its use. However, whether such biases are present in datasets of other organisms including humans is unknown. Here we compare different CHX-treatment conditions in human cells and yeast in parallel experiments using an optimized protocol. We find that human ribosomes are not susceptible to conformational restrictions by CHX, nor does it distort gene-level measurements of ribosome occupancy, measured decoding speed or the translational ramp. Furthermore, CHX-induced codon-specific biases on ribosome occupancy are not detectable in human cells or other model organisms. This shows that reported biases of CHX are species-specific and that CHX does not affect the outcome of ribosome profiling experiments in most settings. Our findings provide a solid framework to conduct and analyze ribosome profiling experiments.

Hybrid Zones and the Genetic Architecture of a Barrier to Gene Flow Between Two Sunflower Species

Genetics ◽  
1999 ◽  
Vol 152 (2) ◽  
pp. 713-727 ◽  
Author(s):  
Loren H Rieseberg ◽  
Jeannette Whitton ◽  
Keith Gardner
Keyword(s):  
Genetic Study ◽  
Genetic Architecture ◽  
Chromosomal Rearrangements ◽  
Pollen Sterility ◽  
Model Organisms ◽  
Hybrid Zones ◽  
Reproductive Barriers ◽  
Natural Hybrid ◽  
Generation Times ◽  
Helianthus Petiolaris

Abstract Genetic analyses of reproductive barriers represent one of the few methods by which theories of speciation can be tested. However, genetic study is often restricted to model organisms that have short generation times and are easily propagated in the laboratory. Replicate hybrid zones with a diversity of recombinant genotypes of varying age offer increased resolution for genetic mapping experiments and expand the pool of organisms amenable to genetic study. Using 88 markers distributed across 17 chromosomes, we analyze the introgression of chromosomal segments of Helianthus petiolaris into H. annuus in three natural hybrid zones. Introgression was significantly reduced relative to neutral expectations for 26 chromosomal segments, suggesting that each segment contains one or more factors that contribute to isolation. Pollen sterility is significantly associated with 16 of these 26 segments, providing a straightforward explanation of why this subset of blocks is disadvantageous in hybrids. In addition, comparison of rates of introgression across colinear vs. rearranged chromosomes indicates that close to 50% of the barrier to introgression is due to chromosomal rearrangements. These results demonstrate the utility of hybrid zones for identifying factors contributing to isolation and verify the prediction of increased resolution relative to controlled crosses.

scholarly journals High-Quality Genome Resource of the Pathogen of Diaporthe (Phomopsis) phragmitis Causing Kiwifruit Soft Rot

2020 ◽  
Author(s):  
Pu Liu ◽  
Wang Xiaojie ◽  
Dong Hongjie ◽  
Jianbin Lan ◽  
Kuan Liang ◽  
...  
Keyword(s):  
Plant Pathogens ◽  
Management Strategies ◽  
Soft Rot ◽  
Fruit Rot ◽  
Economic Plant ◽  
High Quality ◽  
Total Size ◽  
Genome Wide ◽  
Solid Foundation ◽  
High Quality Genome

Diaporthe spp. are critical plant pathogens that cause wood cankers, wilt, dieback, and fruit rot in a wide variety of economic plant hosts and are regarded as one of the most acute threats faced by kiwifruit industry worldwide. Diaporthe phragmitis strain NJD1 is a highly pathogenic isolate of soft rot of kiwifruit. Here, we present a high-quality genome-wide sequence of D. phragmitis NJD1 that was assembled into 28 contigs containing a total size of 58.33 Mb and N50 length of 3.55 Mb. These results lay a solid foundation for understanding host–pathogen interaction and improving disease management strategies.

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