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.

Epi2Loc: An R Package to Investigate Two-Locus Epistatic Models

2014 ◽  
Vol 17 (4) ◽  
pp. 272-278 ◽  
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, Epi2Loc, to aid users who wish to easily compare, interpret, and utilize models for two-locus epistatic interactions. Epi2Loc 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 Mining SNPs From EST Databases

1999 ◽  
Vol 9 (2) ◽  
pp. 167-174 ◽  
Author(s):  
Leslie Picoult-Newberg ◽  
Trey E. Ideker ◽  
Mark G. Pohl ◽  
Scott L. Taylor ◽  
Miriam A. Donaldson ◽  
...  
Keyword(s):  
Expressed Sequence Tag ◽  
De Novo ◽  
Cdna Libraries ◽  
Human Populations ◽  
Data Sets ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Using Data

There is considerable interest in the discovery and characterization of single nucleotide polymorphisms (SNPs) to enable the analysis of the potential relationships between human genotype and phenotype. Here we present a strategy that permits the rapid discovery of SNPs from publicly available expressed sequence tag (EST) databases. From a set of ESTs derived from 19 different cDNA libraries, we assembled 300,000 distinct sequences and identified 850 mismatches from contiguous EST data sets (candidate SNP sites), without de novo sequencing. Through a polymerase-mediated, single-base, primer extension technique, Genetic Bit Analysis (GBA), we confirmed the presence of a subset of these candidate SNP sites and have estimated the allele frequencies in three human populations with different ethnic origins. Altogether, our approach provides a basis for rapid and efficient regional and genome-wide SNP discovery using data assembled from sequences from different libraries of cDNAs.[The SNPs identified in this study can be found in the National Center of Biotechnology (NCBI) SNP database under submitter handles ORCHID (SNPS-981210-A) and debnick (SNPS-981209-A and SNPS-981209-B).]

scholarly journals Genetic “General Intelligence,” Objectively Determined and Measured

2019 ◽  
Author(s):  
Javier de la Fuente ◽  
Gail Davies ◽  
Andrew D. Grotzinger ◽  
Elliot M. Tucker-Drob ◽  
Ian J. Deary
Keyword(s):  
Genetic Basis ◽  
Genetic Variance ◽  
Genetic Factors ◽  
General Factor ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Fundamental Dimension ◽  
Cognitive Traits ◽  
Using Data

AbstractIt has been known for 125 years that, in humans, diverse cognitive traits are positively intercorrelated; this forms the basis for the general factor of intelligence (g). We directly test for a genetic basis for g using data from seven different cognitive tests (N = 11,263 to N = 331,679) and genome-wide autosomal single nucleotide polymorphisms. A genetic g factor accounts for 58.4% (SE = 4.8%) of the genetic variance in the cognitive traits, with trait-specific genetic factors accounting for the remaining 41.6%. We distill genetic loci broadly relevant for many cognitive traits (g) from loci associated with only individual cognitive traits. These results elucidate the etiological basis for a long-known yet poorly-understood phenomenon, revealing a fundamental dimension of genetic sharing across diverse cognitive traits.

scholarly journals qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots

2014 ◽  
Author(s):  
Stephen D. Turner
Keyword(s):  
Association Studies ◽  
Source Code ◽  
R Package ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Human Trait ◽  
General Public License

Summary: Genome-wide association studies (GWAS) have identified thousands of human trait-associated single nucleotide polymorphisms. Here, I describe a freely available R package for visualizing GWAS results using Q-Q and manhattan plots. The qqman package enables the flexible creation of manhattan plots, both genome-wide and for single chromosomes, with optional highlighting of SNPs of interest. Availability: qqman is released under the GNU General Public License, and is freely available on the Comprehensive R Archive Network (http://cran.r-project.org/package=qqman). The source code is available on GitHub (https://github.com/stephenturner/qqman).

scholarly journals Genomic Analyses of Globodera pallida, A Quarantine Agricultural Pathogen in Idaho

Pathogens ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 363
Author(s):  
Sulochana K. Wasala ◽  
Dana K. Howe ◽  
Louise-Marie Dandurand ◽  
Inga A. Zasada ◽  
Dee R. Denver
Keyword(s):  
Genetic Variation ◽  
Potato Production ◽  
Globodera Pallida ◽  
Fixation Index ◽  
Parasitic Nematodes ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Field Samples ◽  
Multiple Introduction

Globodera pallida is among the most significant plant-parasitic nematodes worldwide, causing major damage to potato production. Since it was discovered in Idaho in 2006, eradication efforts have aimed to contain and eradicate G. pallida through phytosanitary action and soil fumigation. In this study, we investigated genome-wide patterns of G. pallida genetic variation across Idaho fields to evaluate whether the infestation resulted from a single or multiple introduction(s) and to investigate potential evolutionary responses since the time of infestation. A total of 53 G. pallida samples (~1,042,000 individuals) were collected and analyzed, representing five different fields in Idaho, a greenhouse population, and a field in Scotland that was used for external comparison. According to genome-wide allele frequency and fixation index (Fst) analyses, most of the genetic variation was shared among the G. pallida populations in Idaho fields pre-fumigation, indicating that the infestation likely resulted from a single introduction. Temporal patterns of genome-wide polymorphisms involving (1) pre-fumigation field samples collected in 2007 and 2014 and (2) pre- and post-fumigation samples revealed nucleotide variants (SNPs, single-nucleotide polymorphisms) with significantly differentiated allele frequencies indicating genetic differentiation. This study provides insights into the genetic origins and adaptive potential of G. pallida invading new environments.

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 Genome-Wide Patterns of Homozygosity Reveal the Conservation Status in Five Italian Goat Populations

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1510
Author(s):  
Salvatore Mastrangelo ◽  
Rosalia Di Gerlando ◽  
Maria Teresa Sardina ◽  
Anna Maria Sutera ◽  
Angelo Moscarelli ◽  
...  
Keyword(s):  
Conservation Status ◽  
Phenotypic Traits ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Local Populations ◽  
Genomic Technologies ◽  
Fitness Traits ◽  
Genome Wide ◽  
Breeding Schemes ◽  
Genomic Inbreeding

The application of genomic technologies has facilitated the assessment of genomic inbreeding based on single nucleotide polymorphisms (SNPs). In this study, we computed several runs of homozygosity (ROH) parameters to investigate the patterns of homozygosity using Illumina Goat SNP50 in five Italian local populations: Argentata dell’Etna (N = 48), Derivata di Siria (N = 32), Girgentana (N = 59), Maltese (N = 16) and Messinese (N = 22). The ROH results showed well-defined differences among the populations. A total of 3687 ROH segments >2 Mb were detected in the whole sample. The Argentata dell’Etna and Messinese were the populations with the lowest mean number of ROH and inbreeding coefficient values, which reflect admixture and gene flow. In the Girgentana, we identified an ROH pattern related with recent inbreeding that can endanger the viability of the breed due to reduced population size. The genomes of Derivata di Siria and Maltese breeds showed the presence of long ROH (>16 Mb) that could seriously impact the overall biological fitness of these breeds. Moreover, the results confirmed that ROH parameters are in agreement with the known demography of these populations and highlighted the different selection histories and breeding schemes of these goat populations. In the analysis of ROH islands, we detected harbored genes involved with important traits, such as for milk yield, reproduction, and immune response, and are consistent with the phenotypic traits of the studied goat populations. Finally, the results of this study can be used for implementing conservation programs for these local populations in order to avoid further loss of genetic diversity and to preserve the production and fitness traits. In view of this, the availability of genomic data is a fundamental resource.

scholarly journals Genotyping-by-Sequencing of Gossypium hirsutum Races and Cultivars Uncovers Novel Patterns of Genetic Relationships and Domestication Footprints

2019 ◽  
Vol 15 ◽  
pp. 117693431988994
Author(s):  
Shulin Zhang ◽  
Yaling Cai ◽  
Jinggong Guo ◽  
Kun Li ◽  
Renhai Peng ◽  
...  
Keyword(s):  
Gossypium Hirsutum ◽  
Genetic Relationships ◽  
Phylogenetic Analyses ◽  
Genotyping By Sequencing ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Breeding Programs ◽  
Association Analyses ◽  
Genome Wide ◽  
Candidate Gene Locus

Determining the genetic rearrangement and domestication footprints in Gossypium hirsutum cultivars and primitive race genotypes are essential for effective gene conservation efforts and the development of advanced breeding molecular markers for marker-assisted breeding. In this study, 94 accessions representing the 7 primitive races of G hirsutum, along with 9 G hirsutum and 12 Gossypium barbadense cultivated accessions were evaluated. The genotyping-by-sequencing (GBS) approach was employed and 146 558 single nucleotide polymorphisms (SNP) were generated. Distinct SNP signatures were identified through the combination of selection scans and association analyses. Phylogenetic analyses were also conducted, and we concluded that the Latifolium, Richmondi, and Marie-Galante race accessions were more genetically related to the G hirsutum cultivars and tend to cluster together. Fifty-four outlier SNP loci were identified by selection-scan analysis, and 3 SNPs were located in genes related to the processes of plant responding to stress conditions and confirmed through further genome-wide signals of marker-phenotype association analysis, which indicate a clear selection signature for such trait. These results identified useful candidate gene locus for cotton breeding programs.

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