scholarly journals High-throughput sequencing reveals inbreeding depression in a natural population

2014 ◽  
Vol 111 (10) ◽  
pp. 3775-3780 ◽  
Author(s):  
Joseph I. Hoffman ◽  
Fraser Simpson ◽  
Patrice David ◽  
Jolianne M. Rijks ◽  
Thijs Kuiken ◽  
...  
Keyword(s):  
Natural Population ◽  
Inbreeding Depression ◽  
High Throughput Sequencing ◽  
Natural Populations ◽  
Harbor Seals ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Peromyscus Polionotus ◽  
Genome Wide ◽  
Underlying Mechanisms

Proxy measures of genome-wide heterozygosity based on approximately 10 microsatellites have been used to uncover heterozygosity fitness correlations (HFCs) for a wealth of important fitness traits in natural populations. However, effect sizes are typically very small and the underlying mechanisms remain contentious, as a handful of markers usually provides little power to detect inbreeding. We therefore used restriction site associated DNA (RAD) sequencing to accurately estimate genome-wide heterozygosity, an approach transferrable to any organism. As a proof of concept, we first RAD sequenced oldfield mice (Peromyscus polionotus) from a known pedigree, finding strong concordance between the inbreeding coefficient and heterozygosity measured at 13,198 single-nucleotide polymorphisms (SNPs). When applied to a natural population of harbor seals (Phoca vitulina), a weak HFC for parasite infection based on 27 microsatellites strengthened considerably with 14,585 SNPs, the deviance explained by heterozygosity increasing almost fivefold to a remarkable 49%. These findings arguably provide the strongest evidence to date of an HFC being due to inbreeding depression in a natural population lacking a pedigree. They also suggest that under some circumstances heterozygosity may explain far more variation in fitness than previously envisaged.

scholarly journals Association Mapping across Numerous Traits Reveals Patterns of Functional Variation in Maize

2014 ◽  
Author(s):  
Jason G Wallace ◽  
Peter Bradbury ◽  
Nengyi Zhang ◽  
Yves Gibon ◽  
Mark Stitt ◽  
...  
Keyword(s):  
Phenotypic Variation ◽  
Copy Number Variants ◽  
Natural Populations ◽  
Nucleotide Polymorphisms ◽  
Functional Variation ◽  
Single Nucleotide ◽  
Gene By Environment Interactions ◽  
Genome Wide ◽  
Intergenic Regions ◽  
Regulatory Functions

Phenotypic variation in natural populations results from a combination of genetic effects, environmental effects, and gene-by-environment interactions. Despite the vast amount of genomic data becoming available, many pressing questions remain about the nature of genetic mutations that underlie functional variation. We present the results of combining genome-wide association analysis of 41 different phenotypes in ~5,000 inbred maize lines to analyze patterns of high-resolution genetic association among of 28.9 million single-nucleotide polymorphisms (SNPs) and ~800,000 copy-number variants (CNVs). We show that genic and intergenic regions have opposite patterns of enrichment, minor allele frequencies, and effect sizes, implying tradeoffs among the probability that a given polymorphism will have an effect, the detectable size of that effect, and its frequency in the population. We also find that genes tagged by GWAS are enriched for regulatory functions and are ~50% more likely to have a paralog than expected by chance, indicating that gene regulation and neofunctionalization are strong drivers of phenotypic variation. These results will likely apply to many other organisms, especially ones with large and complex genomes like maize.

scholarly journals Performance comparison of two reduced-representation based genome-wide marker-discovery strategies in a multi-taxon phylogeographic framework

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Philipp Kirschner ◽  
◽  
Wolfgang Arthofer ◽  
Stefanie Pfeifenberger ◽  
Eliška Záveská ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Performance Comparison ◽  
Nucleotide Polymorphisms ◽  
Aflp Data ◽  
Single Nucleotide ◽  
Reduced Representation ◽  
Genome Wide ◽  
Taxonomic Groups ◽  
Marker Discovery ◽  
Study Species

AbstractMulti-locus genetic data are pivotal in phylogenetics. Today, high-throughput sequencing (HTS) allows scientists to generate an unprecedented amount of such data from any organism. However, HTS is resource intense and may not be accessible to wide parts of the scientific community. In phylogeography, the use of HTS has concentrated on a few taxonomic groups, and the amount of data used to resolve a phylogeographic pattern often seems arbitrary. We explore the performance of two genetic marker sampling strategies and the effect of marker quantity in a comparative phylogeographic framework focusing on six species (arthropods and plants). The same analyses were applied to data inferred from amplified fragment length polymorphism fingerprinting (AFLP), a cheap, non-HTS based technique that is able to straightforwardly produce several hundred markers, and from restriction site associated DNA sequencing (RADseq), a more expensive, HTS-based technique that produces thousands of single nucleotide polymorphisms. We show that in four of six study species, AFLP leads to results comparable with those of RADseq. While we do not aim to contest the advantages of HTS techniques, we also show that AFLP is a robust technique to delimit evolutionary entities in both plants and animals. The demonstrated similarity of results from the two techniques also strengthens biological conclusions that were based on AFLP data in the past, an important finding given the wide utilization of AFLP over the last decades. We emphasize that whenever the delimitation of evolutionary entities is the central goal, as it is in many fields of biodiversity research, AFLP is still an adequate technique.

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 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.

scholarly journals Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture

2016 ◽  
Vol 283 (1835) ◽  
pp. 20160569 ◽  
Author(s):  
M. E. Goddard ◽  
K. E. Kemper ◽  
I. M. MacLeod ◽  
A. J. Chamberlain ◽  
B. J. Hayes
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Quantitative Traits ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Crop Breeding ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Phenotype Identification

Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement.

Sign in / Sign up

Export Citation Format

Share Document