Eagle for better genome-wide association mapping

Abstract Eagle is an R package for multi-locus association mapping on a genome-wide scale. It is unlike other multi-locus packages in that it is easy-to-use for R users and non-users alike. It has two modes of use, command line and GUI. Eagle is fully documented and has its own supporting website, http://eagle.r-forge.r-project.org/index.html. Eagle is a significant improvement over the method-of-choice, single-locus association mapping. It has greater power to detect SNP-trait associations. It is based on model selection, linear mixed models, and a clever idea on how random effects can be used to identify SNP-trait associations. Through an example with real mouse data, we demonstrate Eagle’s ability to bring clarity and increased insight to single-locus findings. Initially, we see Eagle complementing single-locus analyses. However, over time, we hope the community will make, increasingly, multi-locus association mapping their method-of-choice for the analysis of genome-wide association study data.

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Eagle: multi-locus association mapping on a genome-wide scale made routine

Bioinformatics ◽

10.1093/bioinformatics/btz759 ◽

2019 ◽

Vol 36 (5) ◽

pp. 1509-1516

Author(s):

Andrew W George ◽

Arunas Verbyla ◽

Joshua Bowden

Keyword(s):

Association Mapping ◽

Multiple Testing ◽

R Package ◽

Single Locus ◽

Supplementary Information ◽

Locus Method ◽

Genome Wide ◽

A Genome ◽

Wide Scale ◽

Mouse Study

Abstract Motivation We present Eagle, a new method for multi-locus association mapping. The motivation for developing Eagle was to make multi-locus association mapping ‘easy’ and the method-of-choice. Eagle’s strengths are that it (i) is considerably more powerful than single-locus association mapping, (ii) does not suffer from multiple testing issues, (iii) gives results that are immediately interpretable and (iv) has a computational footprint comparable to single-locus association mapping. Results By conducting a large simulation study, we will show that Eagle finds true and avoids false single-nucleotide polymorphism trait associations better than competing single- and multi-locus methods. We also analyze data from a published mouse study. Eagle found over 50% more validated findings than the state-of-the-art single-locus method. Availability and implementation Eagle has been implemented as an R package, with a browser-based Graphical User Interface for users less familiar with R. It is freely available via the CRAN website at https://cran.r-project.org. Videos, Quick Start guides, FAQs and Demos are available via the Eagle website http://eagle.r-forge.r-project.org. Supplementary information Supplementary data are available at Bioinformatics online.

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Genome-Wide Association Mapping for Heat and Drought Adaptive Traits in Pea

Genes ◽

10.3390/genes12121897 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1897

Author(s):

Endale G. Tafesse ◽

Krishna K. Gali ◽

V. B. Reddy Lachagari ◽

Rosalind Bueckert ◽

Thomas D. Warkentin

Keyword(s):

Association Mapping ◽

Candidate Genes ◽

Vegetation Index ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Nucleotide Polymorphisms ◽

Adaptive Traits ◽

Flowering Duration ◽

Genome Wide ◽

A Genome

Heat and drought, individually or in combination, limit pea productivity. Fortunately, substantial genetic diversity exists in pea germplasm for traits related to abiotic stress resistance. Understanding the genetic basis of resistance could accelerate the development of stress-adaptive cultivars. We conducted a genome-wide association study (GWAS) in pea on six stress-adaptive traits with the aim to detect the genetic regions controlling these traits. One hundred and thirty-five genetically diverse pea accessions were phenotyped in field studies across three or five environments under stress and control conditions. To determine marker trait associations (MTAs), a total of 16,877 valuable single nucleotide polymorphisms (SNPs) were used in association analysis. Association mapping detected 15 MTAs that were significantly (p ≤ 0.0005) associated with the six stress-adaptive traits averaged across all environments and consistent in multiple individual environments. The identified MTAs were four for lamina wax, three for petiole wax, three for stem thickness, two for the flowering duration, one for the normalized difference vegetation index (NDVI), and two for the normalized pigment and chlorophyll index (NPCI). Sixteen candidate genes were identified within a 15 kb distance from either side of the markers. The detected MTAs and candidate genes have prospective use towards selecting stress-hardy pea cultivars in marker-assisted selection.

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LASSO model selection with post-processing for a genome-wide association study data set

BMC Proceedings ◽

10.1186/1753-6561-5-s9-s24 ◽

2011 ◽

Vol 5 (S9) ◽

Cited By ~ 4

Author(s):

Allan J Motyer ◽

Chris McKendry ◽

Sally Galbraith ◽

Susan R Wilson

Keyword(s):

Model Selection ◽

Association Study ◽

Genome Wide Association Study ◽

Study Data ◽

Genome Wide Association ◽

Post Processing ◽

Data Set ◽

Genome Wide ◽

A Genome

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Genome-wide association mapping reveals new loci associated with light-colored seed coat at harvest and slow darkening in carioca beans

BMC Plant Biology ◽

10.1186/s12870-021-03122-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Caléo Panhoca de Almeida ◽

Isabella Laporte Santos ◽

Jean Fausto de Carvalho Paulino ◽

Caio Cesar Ferrari Barbosa ◽

Cássia Cristina Augusto Pereira ◽

...

Keyword(s):

Association Mapping ◽

Genetic Control ◽

Seed Coat ◽

Genome Wide Association Study ◽

Coat Color ◽

Genome Wide Association ◽

Seed Coat Color ◽

Market Values ◽

Genome Wide ◽

A Genome

Abstract Background Common bean (Phaseolus vulgaris L.) is a legume whose grain can be stored for months, a common practice among Brazilian growers. Over time, seed coats become darker and harder to cook, traits that are undesirable to consumers, who associate darker-colored beans with greater age. Like commercial pinto and cranberry bean varieties, carioca beans that have darker seeds at harvest time and after storage are subject to decreased market values. Results The goal of our study was to identify the genetic control associated with lightness of seed coat color at harvest (HL) and with tolerance to post-harvest seed coat darkening (PHD) by a genome-wide association study. For that purpose, a carioca diversity panel previously validated for association mapping studies was used with 138 genotypes and 1,516 high-quality SNPs. The panel was evaluated in two environments using a colorimeter and the CIELAB scale. Shelf storage for 30 days had the most expressive results and the L* (luminosity) parameter led to the greatest discrimination of genotypes. Three QTL were identified for HL, two on chromosome Pv04 and one on Pv10. Regarding PHD, results showed that genetic control differs for L* after 30 days and for the ΔL* (final L*—initial L*); only ΔL* was able to properly express the PHD trait. Four phenotypic classes were proposed, and five QTL were identified through six significant SNPs. Conclusions Lightness of seed coat color at harvest showed an oligogenic inheritance corroborated by moderate broad-sense heritability and high genotypic correlation among the experiments. Only three QTL were significant for this trait – two were mapped on Pv04 and one on Pv10. Considering the ΔL, six QTL were mapped on four different chromosomes for PHD. The same HL QTL at the beginning of Pv10 was also associated with ΔL* and could be used as a tool in marker-assisted selection. Several candidate genes were identified and may be useful to accelerate the genetic breeding process.

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