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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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Integrating GWAS-guided markers preselection with genomic selection enhances prediction of pulpwood-related traits in slash pine (Pinus elliottii Englem.).

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Updated: May 19, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Published on: June 23, 2012

Genotype imputation improves SNP density and genetic analysis accuracy in slash pine.

Yu-Xuan Jiang1, Li-Ming Bian1, Shi-Liang Zhou1

  • 1State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, College of Forestry and Grassland, Nanjing Forestry University, Nanjing 210037, China.

Yi Chuan = Hereditas
|May 18, 2026
PubMed
Summary

This study developed a high-density genotype resource for slash pine (Pinus elliottii) by imputing low-density SNP array data using whole-genome sequencing. This improves genomic relationship matrix estimation for genetic analyses in conifers.

Keywords:
SNP arraygenomic relationship matrixgenotype imputationhigh-density genotype matrixreference panel

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Infinium Assay for Large-scale SNP Genotyping Applications
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Area of Science:

  • Forest Genetics
  • Genomics
  • Bioinformatics

Background:

  • Slash pine (Pinus elliottii) has a large, complex genome, limiting current SNP array utility.
  • Low marker density hinders accurate population genetic analyses and genomic relationship matrix (GRM) estimation.

Purpose of the Study:

  • To increase marker density for slash pine genetic studies.
  • To enhance the accuracy of GRM estimation using genome-wide imputation.
  • To create a high-density genotypic resource for slash pine.

Main Methods:

  • Constructed a reference panel from 10× whole-genome resequencing of 50 slash pine parents.
  • Performed genome-wide imputation for 51K SNP-array genotypes of 715 progeny.
  • Validated imputation accuracy using masking experiments and external progeny resequencing data.

Main Results:

  • Achieved 95.5% imputation accuracy at array loci.
  • Generated a high-density genotype matrix with 120,650,180 SNPs.
  • Observed improved linkage disequilibrium (LD) signal continuity and clearer LD block structures.
  • GRM derived from imputed data showed high consistency (Pearson's r≈0.984) with array-based GRM.

Conclusions:

  • The developed imputation framework provides a valuable high-density genotypic resource for slash pine.
  • This resource facilitates genome-wide association studies and genomic selection in slash pine and other conifers.
  • Imputed loci within 500 kb of array markers yielded the highest concordance for GRM construction.