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Genetic Mapping and Diversity in Plants and Animals
Research Guide
What is Genetic Mapping and Diversity in Plants and Animals?
Genetic mapping and diversity in plants and animals is the study of how genetic variants are distributed within and between populations and how those variants are linked to phenotypic traits, using linkage analysis, association mapping, and population-genetic inference to quantify inheritance and variation.
The literature cluster on genetic mapping and diversity in plants and animals comprises 280,616 works focused on genetic architecture of quantitative traits, QTL mapping, genome-wide association studies, domestication, heterosis, and marker-assisted selection in crops and livestock.
Topic Hierarchy
Research Sub-Topics
Quantitative Trait Loci Mapping
Quantitative trait loci (QTL) mapping identifies genomic regions associated with complex quantitative traits in plants and animals using linkage analysis. Researchers apply interval mapping and composite methods to crops like rice and maize for trait dissection.
Genome-Wide Association Studies
Genome-wide association studies (GWAS) detect marker-trait associations across entire genomes in diverse populations of crops and livestock. Researchers address population structure, linkage disequilibrium, and polygenic risk in plant breeding contexts.
Genetic Basis of Heterosis
Research on the genetic basis of heterosis explores dominance, overdominance, and epistasis contributing to hybrid vigor in maize and rice. Researchers use expression profiling and population genetics to dissect heterotic mechanisms.
Marker-Assisted Selection
Marker-assisted selection (MAS) integrates molecular markers into breeding programs for efficient trait introgression in plants and animals. Researchers optimize MAS strategies for pyramiding QTL and genomic prediction integration.
Crop Domestication Genomics
Crop domestication genomics examines genomic signatures of selection during maize and rice evolution from wild progenitors. Researchers identify domestication sweeps, gene flow, and parallel adaptations across species.
Why It Matters
Genetic mapping and diversity analyses directly support breeding, conservation, and genome-resource building by identifying trait-associated loci, characterizing population structure, and prioritizing genetic variation for selection. In practical association-mapping workflows, "PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses" (2007) is used to run whole-genome association and population-based linkage analyses at scale, while "Haploview: analysis and visualization of LD and haplotype maps" (2004) supports interpreting linkage disequilibrium (LD) and haplotype blocks that affect mapping resolution. For population structure and diversity inference that can prevent false positives in GWAS and clarify domestication or admixture histories, Evanno et al. (2005) in "Detecting the number of clusters of individuals using the software structure: a simulation study" formalized a simulation-based approach to selecting the number of genetic clusters, and Excoffier and Lischer (2010) in "Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows" provided a widely used toolkit for population-genetic summary statistics and analyses. Neutrality tests such as Tajima (1989) in "Statistical method for testing the neutral mutation hypothesis by DNA polymorphism." are routinely used to flag loci or genomic regions whose diversity patterns deviate from neutral expectations—information that can guide interpretation of selection signals in domestication, breeding, or conservation contexts.
Reading Guide
Where to Start
Start with "Introduction to Quantitative Genetics." (1982) because it provides the conceptual foundation (population genetic constitution, allele-frequency change, and small-population behavior) needed to interpret both mapping results and diversity statistics.
Key Papers Explained
Edwards and Falconer (1982) in "Introduction to Quantitative Genetics." supply the theoretical basis for how allele frequencies and population processes shape trait variance and genetic diversity. Tajima (1989) in "Statistical method for testing the neutral mutation hypothesis by DNA polymorphism." adds a formal test for whether observed DNA polymorphism patterns match neutral expectations, which is commonly used to interpret diversity signals. Evanno et al. (2005) in "Detecting the number of clusters of individuals using the software structure: a simulation study" addresses how to infer population structure, a key prerequisite for valid diversity inference and association mapping. Purcell et al. (2007) in "PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses" operationalizes association and linkage analyses for genome-wide genotype data, while Barrett et al. (2004) in "Haploview: analysis and visualization of LD and haplotype maps" supports interpreting LD and haplotype patterns that condition mapping resolution and signal localization.
Paper Timeline
Most-cited paper highlighted in red. Papers ordered chronologically.
Advanced Directions
A current frontier is scaling genetic mapping and diversity inference to much larger genome resources and more complex representations of variation (e.g., haplotypes and LD structure) while maintaining rigorous controls for structure and neutrality assumptions. In practice, this means combining structure inference approaches aligned with Evanno et al. (2005) and diversity/summary-statistic pipelines aligned with Excoffier and Lischer (2010), then integrating association workflows aligned with Purcell et al. (2007) and LD/haplotype interpretation aligned with Barrett et al. (2004).
Papers at a Glance
In the News
Biological 'moonshot' accelerates efforts to genetically map ...
Published in Frontiers in Science , this is the new ambition of the Earth BioGenome Project (EBP)—a global network of scientists sequencing the genomes of Earth’s eukaryotes. Its goal? To create a ...
Why scientists and policy experts are trying to map ...
We’ve applied for NSF funding to develop protocols for scaling up and cost for sequencing, we could potentially sequence up to 1,000 genomes per week. This would allow scientists working on this pr...
Agricultural Genome to Phenome Initiative
The National Institute of Food and Agriculture’s Agricultural Genome to Phenome Initiative (AG2PI) focuses on collaborative science engagement that intends to develop a community of researchers acr...
Mapping DNA of over 1 million species could lead to new ...
Six years ago, scientists around the world launched an ambitious project to map the DNA of all the animals, plants, fungi and other organisms with complex cells —all the eukaryotic life that exists...
The pan-genomics path to drought-resistant maize
Lyu, J. The pan-genomics path to drought-resistant maize. _Nat. Plants_ **11**, 2442 (2025). https://doi.org/10.1038/s41477-025-02186-4 Download citation - Published: 02 December 2025 - Versio...
Code & Tools
Build Status We foster the openness, integrity, and reproducibility of scientific research. Scripts and tools used to develop a pipeline to anal...
`rTASSEL` is an R-based front-end for accessing key TASSEL 5 methods and tools. This allows users to run powerful TASSEL 5 analyses within a unifie...
`OneMap` is a software for constructing genetic maps in experimental crosses: full-sib, RILs, F2, and backcrosses. It was developed by Gabriel R A ...
`panGenomeBreedr` ( `panGB`) is conceptualized to be a unified, crop agnostic platform for pangenome-enabled breeding that follows standardized con...
## Repository files navigation # RAD analysis workflow A bioinformatics workflow for analysing genotypes using restriction site associated DNA se...
Recent Preprints
the plant pan-genome unraveling genetic mysteries and ...
serving as a pivotal area of focus. Its application in plant studies has unveiled extensive genetic variations, identified numerous novel genes, and significantly enhanced our understanding of gene...
Genetic diversity analysis and multi-fingerprint map ...
Due to its asexual reproduction characteristics,*Naematelia aurantialba*faces limitations in genetic diversity, germplasm identification, and intellectual property protection, necessitating molecul...
Genomic resequencing reveals genetic diversity, population structure, and core collection of durian germplasm
*Durio zibethinus*Murr. is a tropical fruit crop of growing global importance, prized for its unique flavor and nutritional value. Yet only a narrow genetic base has been utilized in breeding effor...
Genomic insights into the population structure and genetic ...
**Keywords:**African native cattle, hybridization, livestock genetics, phylogenetics, population characterization, whole‐genome sequencing ## INTRODUCTION
Small Population Size and Low Levels of Genetic Diversity ...
Mapping the genetic diversity within an endangered species allows managers to optimize conservation strategies, and is increasingly being used for conservation interventions [ 13]. The genetic dive...
Latest Developments
Recent developments in genetic mapping and diversity research in plants and animals include large-scale genome sequencing projects, such as the Earth BioGenome Project aiming to sequence over 1.67 million species' genomes, which could lead to new medicines and agricultural improvements (science.org, published November 2024; asu.edu, March 2025). Additionally, advances in agricultural genetics, including gene editing techniques like CRISPR, are transforming crop and livestock breeding to enhance resilience and productivity (farmonaut.com, 2026). Significant efforts are also underway to develop pangenomes for crops such as barley, rice, and wheat, revealing structural variations and allelic diversity that aid adaptation and breeding strategies (nature.com, November 2024; nature.com, April 2025; nature.com, November 2024). These initiatives collectively advance understanding of genetic diversity and structural variation, supporting conservation, crop improvement, and biomedical research (science.org, November 2024).
Sources
Frequently Asked Questions
What is the difference between linkage mapping and genome-wide association studies (GWAS) in genetic mapping?
Linkage mapping uses recombination in pedigrees or experimental crosses to localize loci affecting traits, whereas GWAS uses historical recombination in populations to associate genome-wide markers with phenotypes. "PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses" (2007) explicitly supports both population-based linkage analyses and whole-genome association analyses in a single tool framework.
How do researchers account for population structure when analyzing genetic diversity or performing GWAS?
Population structure is commonly inferred by clustering individuals into genetically homogeneous groups and then using that structure in downstream analyses to reduce confounding. Evanno et al. (2005) in "Detecting the number of clusters of individuals using the software structure: a simulation study" evaluated how to detect the true number of clusters under a Bayesian clustering model implemented in STRUCTURE.
Which software is commonly used to compute population-genetic summary statistics from genetic data?
"Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows" (2010) provides programs for population genetics analyses and summary statistics across platforms. Raymond and Rousset (1995) in "GENEPOP (Version 1.2): Population Genetics Software for Exact Tests and Ecumenicism" provides exact tests and related population-genetic analyses that are widely used for genotype data.
How is linkage disequilibrium (LD) and haplotype structure used in genetic mapping?
LD and haplotype structure determine mapping resolution and help interpret association signals by showing whether nearby variants are correlated and inherited together. "Haploview: analysis and visualization of LD and haplotype maps" (2004) provides analysis and visualization routines that make LD blocks and haplotype patterns interpretable for association studies.
Why do neutrality tests matter for interpreting genetic diversity patterns in domestication or breeding populations?
Neutrality tests help distinguish diversity patterns expected under neutral evolution from those likely shaped by selection or demographic events. Tajima (1989) in "Statistical method for testing the neutral mutation hypothesis by DNA polymorphism." derived a statistical test based on DNA polymorphism summaries to evaluate departures from the neutral mutation hypothesis.
Which core theoretical framework underpins quantitative trait analysis in genetic mapping studies?
Quantitative genetics provides the population-genetic and statistical foundation for modeling how many loci with small effects contribute to trait variation. Edwards and Falconer (1982) in "Introduction to Quantitative Genetics." organized key principles including Hardy–Weinberg equilibrium, forces changing allele frequencies, and the behavior of small populations, which are central to interpreting mapping and diversity results.
Open Research Questions
- ? How can LD and haplotype-block structure, as operationalized in "Haploview: analysis and visualization of LD and haplotype maps" (2004), be incorporated into association models (e.g., those implemented in "PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses" (2007)) to improve fine-mapping resolution without inflating false positives?
- ? Which departures from the neutral mutation hypothesis detected using Tajima (1989) in "Statistical method for testing the neutral mutation hypothesis by DNA polymorphism." can be robustly attributed to selection rather than demography when population structure is inferred as in Evanno et al. (2005) in "Detecting the number of clusters of individuals using the software structure: a simulation study"?
- ? How should clustering choices (the inferred number of clusters) from Evanno et al. (2005) propagate uncertainty into downstream estimates of diversity and differentiation computed using Excoffier and Lischer (2010) in "Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows"?
- ? How can quantitative-genetic assumptions summarized in Edwards and Falconer (1982) in "Introduction to Quantitative Genetics." be reconciled with genome-wide association signals produced by "PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses" (2007) when traits are influenced by many loci and population structure is present?
Recent Trends
Within this topic area, tool-centered workflows have consolidated around integrated association/linkage analysis (Purcell et al., 2007, "PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses"), explicit population-structure model selection (Evanno et al., 2005, "Detecting the number of clusters of individuals using the software structure: a simulation study"), and standardized diversity/summary-statistic computation (Excoffier and Lischer, 2010, "Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows").
The scale of the research area is reflected in the provided corpus size of 280,616 works, indicating a large methodological and applied base spanning QTL mapping, GWAS, domestication studies, and marker-assisted selection.
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