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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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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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Heritability01:06

Heritability

Heritability is a statistical concept that measures the degree to which genetic differences among individuals contribute to trait variations within a population. It is a fundamental idea in genetics, often prone to misinterpretation. Heritability is expressed as a percentage, reflecting the proportion of variation in a specific trait across a population that can be linked to genetic differences. However, it's important to understand that heritability does not determine how "genetic" a trait is,...
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Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
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Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
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Related Experiment Video

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

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Published on: December 7, 2021

Maximum-likelihood estimation of recent shared ancestry (ERSA).

Chad D Huff1, David J Witherspoon, Tatum S Simonson

  • 1Department of Human Genetics, University of Utah Health Sciences Center, Salt Lake City, Utah 84112, USA.

Genome Research
|February 18, 2011
PubMed
Summary
This summary is machine-generated.

We developed a new method to estimate recent shared ancestry using identity by descent (IBD) segments. This tool accurately identifies relationships up to seventh-degree relatives, expanding genetic relationship analysis.

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Area of Science:

  • Population Genetics
  • Genomic Analysis
  • Bioinformatics

Background:

  • Accurate estimation of recent shared ancestry is crucial across diverse scientific fields, including genetics, evolutionary studies, medicine, conservation, and forensics.
  • Existing kinship estimation methods are reliable for close relatives (first to third-degree) but have limitations for more distant relationships.

Purpose of the Study:

  • To develop and validate a novel maximum-likelihood method for estimating recent shared ancestry.
  • To leverage chromosomal segments shared due to identity by descent (IBD) for enhanced relationship inference.

Main Methods:

  • Developed the Estimation of Recent Shared Ancestry (ERSA) method.
  • Utilized the number and lengths of IBD segments derived from high-density SNP or whole-genome sequencing data.
  • Applied ERSA to SNP genotypes from 169 individuals across three well-defined human pedigrees.

Main Results:

  • ERSA accurately estimates relationships to within one degree for 97% of individuals from first to fifth-degree relatives.
  • The method achieves 80% accuracy for sixth and seventh-degree relatives.
  • ERSA's statistical power approaches theoretical limits, even for distant relatives who may share no IBD segments.

Conclusions:

  • ERSA significantly expands the range of familial relationships detectable using genetic data.
  • The method provides a powerful and accurate tool for inferring recent shared ancestry.
  • ERSA is available as a freely accessible software package for broader scientific application.