Identity by descent

Template:Distinguish Template:Short description

A DNA segment is identical by descent (IBD) in two or more individuals if:

they have inherited it from a common ancestor without recombination, that is, the segment has the same ancestral origin in these individuals
the segment is maximal, that is, it is delimited at both ends by ancestral recombination events.<ref>Template:Cite journal</ref>

File:Pedigree, recombination and resulting IBD segments, schematic representation.png

The origin of IBD segments is depicted via a pedigree.

File:Pedigree, recombination and resulting IBD segments, schematic representation modified.png

A colorblind-friendly version of this image.

TheoryEdit

All individuals in a finite population are related if traced back long enough and will, therefore, share segments of their genomes IBD. During meiosis segments of IBD are broken up by recombination. Therefore, the expected length of an IBD segment depends on the number of generations since the most recent common ancestor at the locus of the segment. The length of IBD segments that result from a common ancestor n generations in the past (therefore involving 2n meiosis) is exponentially distributed with mean 1/(2n) Morgans (M).<ref name="Browning.2008">Template:Cite journal</ref> The expected number of IBD segments decreases as the number of generations since the common ancestor at this locus increases. For a specific DNA segment, the probability of being IBD decreases as 2⁻²ⁿ since in each meiosis the probability of transmitting this segment is 1/2.<ref name="Thompson.2008">Template:Cite journal</ref>

ApplicationsEdit

Identified IBD segments can be used for a wide range of purposes. As noted above the amount (length and number) of IBD sharing depends on the familial relationships between the tested individuals. Therefore, one application of IBD segment detection is to quantify relatedness.<ref name="Albrechtsen.2009">Template:Cite journal</ref><ref name="Browning.2010">Template:Cite journal</ref><ref name="Gusev.2009">Template:Cite journal</ref><ref name="Purcell.2007">Template:Cite journal</ref> Measurement of relatedness can be used in forensic genetics,<ref name="Evett.1998">Template:Cite book</ref> but can also increase information in genetic linkage mapping<ref name=" Albrechtsen.2009"/><ref name="Leutenegger.2003">Template:Cite journal</ref> and help to decrease bias by undocumented relationships in standard association studies.<ref name="Purcell.2007"/><ref name="Voight.2005">Template:Cite journal</ref> Another application of IBD is genotype imputation and haplotype phase inference.<ref name="Kong.2008">Template:Cite journal</ref><ref name="Gusev.2012">Template:Cite journal</ref><ref name="Browning.2009">Template:Cite journal</ref> Long shared segments of IBD, which are broken up by short regions may be indicative for phasing errors.<ref name="Gusev.2009"/><ref name="Hochreiter.2013"/>Template:Rp

IBD mappingEdit

IBD mapping<ref name=" Albrechtsen.2009"/> is similar to linkage analysis, but can be performed without a known pedigree on a cohort of unrelated individuals. IBD mapping can be seen as a new form of association analysis that increases the power to map genes or genomic regions containing multiple rare disease susceptibility variants.<ref name="Purcell.2007"/><ref name="Browning.2012b">Template:Cite journal</ref>

Using simulated data, Browning and Thompson showed that IBD mapping has higher power than association testing when multiple rare variants within a gene contribute to disease susceptibility.<ref name="Browning.2012b"/> Via IBD mapping, genome-wide significant regions in isolated populations as well as outbred populations were found while standard association tests failed.<ref name="Gusev.2012"/><ref name="Gusev.2011">Template:Cite journal</ref> Houwen et al. used IBD sharing to identify the chromosomal location of a gene responsible for benign recurrent intrahepatic cholestasis in an isolated fishing population.<ref name="Houwen.1994">Template:Cite journal</ref> Kenny et al. also used an isolated population to fine-map a signal found by a genome-wide association study (GWAS) of plasma plant sterol (PPS) levels, a surrogate measure of cholesterol absorption from the intestine.<ref name="Kenny.2009">Template:Cite journal</ref> Francks et al. was able to identify a potential susceptibility locus for schizophrenia and bipolar disorder with genotype data of case-control samples.<ref name="Francks.2008">Template:Cite journal</ref> Lin et al. found a genome-wide significant linkage signal in a dataset of multiple sclerosis patients.<ref name="Lin.2013">Template:Cite journal</ref> Letouzé et al. used IBD mapping to look for founder mutations in cancer samples.<ref name="Letouze.2012">Template:Cite journal</ref>

File:IBD segment detected by HapFABIA in 1000Genomes.png

An IBD segment identified by HapFABIA in Asian genomes. Rare single nucleotide variants (SNVs) that tag the IBD segment are coloured purple. Below the turquoise bar, the IBD segment in ancient genomes is displayed.

IBD in population geneticsEdit

Detection of natural selection in the human genome is also possible via detected IBD segments. Selection will usually tend to increase the number of IBD segments among individuals in a population. By scanning for regions with excess IBD sharing, regions in the human genome that have been under strong, very recent selection can be identified.<ref name="Albrechtsen.2010">Template:Cite journal</ref><ref name="Han.2013">Template:Cite journal</ref>

In addition to that, IBD segments can be useful for measuring and identifying other influences on population structure.<ref name="Purcell.2007"/><ref name="Cockerham.1983">Template:Cite journal</ref><ref name="Gusev.2012b">Template:Cite journal</ref><ref name="Palamara.2012">Template:Cite journal</ref><ref name="Palamara.2013">Template:Cite journal</ref> Gusev et al. showed that IBD segments can be used with additional modeling to estimate demographic history including bottlenecks and admixture.<ref name="Gusev.2012b"/> Using similar models Palamara et al. and Carmi et al. reconstructed the demographic history of Ashkenazi Jewish and Kenyan Maasai individuals.<ref name="Palamara.2012"/><ref name="Palamara.2013"/><ref name="Carmi.2013">Template:Cite journal</ref> Botigué et al. investigated differences in African ancestry among European populations.<ref name="Botigue.2013">Template:Cite journal</ref> Ralph and Coop used IBD detection to quantify the common ancestry of different European populations<ref name="Ralph.2013">Template:Cite journal</ref> and Gravel et al. similarly tried to draw conclusions of the genetic history of populations in the Americas.<ref name=" Gravel.2013">Template:Cite journal</ref> Ringbauer et al. utilized geographic structure of IBD segments to estimate dispersal within Eastern Europe during the last centuries.<ref>Template:Cite journal</ref> Using the 1000 Genomes data Hochreiter found differences in IBD sharing between African, Asian and European populations as well as IBD segments that are shared with ancient genomes like the Neanderthal or Denisova.<ref name="Hochreiter.2013">Template:Cite journal</ref>

Methods and softwareEdit

Programs for the detection of IBD segments in unrelated individuals:

RAPID: Ultra-fast Identity by Descent Detection in Biobank-Scale Cohorts using Positional Burrows–Wheeler Transform <ref name="Naseri 2017">Naseri A, Liu X, Zhang S, Zhi D. Ultra-fast Identity by Descent Detection in Biobank-Scale Cohorts using Positional Burrows–Wheeler Transform BioRxiv 2017.</ref>
Parente: identifies IBD segments between pairs of individuals in unphased genotype data<ref name="Rodriguez 2013">Rodriguez JM, Batzoglou S, Bercovici S. An accurate method for inferring relatedness in large datasets of unphased genotypes via an embedded likelihood-ratio test. RECOMB 2013, LNBI 7821:212-229.</ref>
BEAGLE/fastIBD: finds segments of IBD between pairs of individuals in genome-wide SNP data<ref name="Browning.2011">Template:Cite journal</ref>
BEAGLE/RefinedIBD: finds IBD segments in pairs of individuals using a hashing method and evaluates their significance via a likelihood ratio<ref name="Browning.2013b">Template:Cite journal</ref>
IBDseq: detects pairwise IBD segments in sequencing data<ref name="Browning.2013">Template:Cite journal</ref>
GERMLINE: discovers in linear-time IBD segments in pairs of individuals<ref name="Gusev.2009"/>
DASH: builds upon pairwise IBD segments to infer clusters of individuals likely to be sharing a single haplotype<ref name="Gusev.2011"/>
PLINK: is a tool set for whole genome association and population-based linkage analyses including a method for pairwise IBD segment detection<ref name="Purcell.2007"/>
Relate: estimates the probability of IBD between pairs of individuals at a specific locus using SNPs<ref name=" Albrechtsen.2009"/>
MCMC_IBDfinder: is based on Markov chain Monte Carlo (MCMC) for finding IBD segments in multiple individuals<ref name="Moltke.2011">Template:Cite journal</ref>
IBD-Groupon: detects group-wise IBD segments based on pairwise IBD relationships<ref name="He.2013">Template:Cite journal</ref>
HapFABIA: identifies very short IBD segments characterized by rare variants in large sequencing data simultaneously in multiple individuals<ref name="Hochreiter.2013"/>

ReferencesEdit

Template:Reflist

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