Measuring the extent of linkage disequilibrium in commercial pig populations

Harmegnies, Natacha; Farnir, Frédéric; Davin, Fabienne; Buys, Nadine; Georges, Michel; Coppieters, Wouter

doi:10.1111/j.1365-2052.2006.01438.x

Cited by 34 publications

(29 citation statements)

References 25 publications

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“…Herrero-Viedma et al, 2013) N e (LD) have large standard errors and are also sensitive to assumptions of constant N e (Corbin et al, 2012). Suggesting that the assumptions of the Wright equation are sometimes met in actual populations, Harmegnies et al (2006) found that in two commercial pig populations (each maintained at about ten boars and 250 to 300 sows) N e (LD) agreed 'reasonably well' with N e (Wright). Leroy et al (2013) found substantial variation between breeds in N e (DF).…”

Section: Discussionmentioning

confidence: 50%

Effective population sizes in cattle, sheep, horses, pigs and goats estimated from census and herdbook data

Hall¹

2016

Animal

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Accurate measures of effective population sizes ( N e ) in livestock require good quality data and specialized skills for their computation and analysis. N e can be estimated by Wright's equation N e = 4MF/( M + F) (M, F being sires and dams, respectively), but this requires assumptions which are often not met. Total census sizes N c of livestock breeds are collated globally. This paper investigates whether estimates of N e can be made from N c ; this would facilitate conservation monitoring. Some N e methodologies avoid the assumptions of Wright's equation and permit measurement, rather than estimation, of N e . Those considered here employ, respectively, linkage disequilibrium (LD) of single-nucleotide polymorphisms (yielding N e ( LD)), and genealogical analysis (rate of increase of inbreeding, DF), yielding N e (DF). Considering breeds of cattle, sheep, horses, pigs and goats for which N c and either N e ( LD) or N e ( DF) are known (totals of 203 breeds and 321 breeds, respectively), proportionality has been investigated between N c and these measures of N e . N e ( LD) was found to increase with N c , significantly in sheep and horses, less so in cattle, but not at all in pigs. N e ( DF) was correlated with log 10 ( N c ) in cattle, sheep and horses (53, 56, 43 breeds, respectively). N e ( LD) was correlated in cattle (73 breeds) and pigs (31 breeds) with the log 10 transformation of N e as calculated by Wright's equation.Further verification and refinement are needed, particularly of census data, but credible predictions of N e are obtainable by applying the following multipliers to log 10 ( N c ): cattle 17.61, sheep 97.72, horse 70.78. For cattle and pigs, multiplying log 10 ( N e (Wright)) by, respectively, 40.69 and 60.09, also gives credible predictions. Such census-based estimates of N e could in principle be generated by non-specialists and are likely to be suited to audits of conservation activity when financial resources or availability of data are limiting. The ratio N e /N c varied among species with an overall median value of 0.03, less than a tenth of that typically observed in wild mammals. Characteristics were also investigated of a distinct herdbook-based methodology, namely the development of Wright's equation to take into account variances of progeny numbers to yield what has been termed here N e (Hill). Comparison of these values with N e (Wright) could help to identify breeds with breeding structures conducive or inimical to genetic conservation. However, N e (Hill) requires breed-specific values for these variances, and this restricts its applicability.

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Section: Discussionmentioning

confidence: 50%

Effective population sizes in cattle, sheep, horses, pigs and goats estimated from census and herdbook data

Hall¹

2016

Animal

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“…Founder effects in pigs can arise because of the economically driven extensive selection programmes, which reduce the effective population sizes strongly. In Belgian commercial pigs for example, the effective population size is diminished from thousands to less than 200 animals (Harmegnies et al, 2006). Selection for FUT1 A/A pigs implies that a positive selection for pigs deficient in the FUT1 gene is carried out.…”

Section: Discussionmentioning

confidence: 99%

The possibility of positive selection for both F18+ Escherichia coli and stress resistant pigs opens new perspectives for pig breeding

Coddens¹,

Verdonck²,

Mulinge³

et al. 2008

Veterinary Microbiology

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F18+ Escherichia coli infections causing post-weaning diarrhoea and/or oedema disease are a major cause of economic losses in pig industry. To date, no preventive strategy can protect pigs from F18 + E. coli infections. One of the most attractive approaches to eliminate F18 + E. coli infections is the selection for pigs that are resistant to F18 + E. coli infections. However, this strategy was not believed to be favourable because of reports of genetic association with the stress-susceptibility gene in the Swiss Landrace. To investigate this potential association more thoroughly, 131 randomly selected Belgian hybrid pigs were genotyped for both the F18 + E. coli resistance alleles (FUT1 A ) and the stress-susceptibility alleles (RYR1 T ) and their association was investigated by determining the linkage disequilibrium. This linkage disequilibrium (LD = À 0.0149) is close to zero and does not differ significantly from 0 (likelihood ratio test x 2 1 ¼ 1:123, P = 0.29), demonstrating no association between the FUT1 A and RYR1 T alleles. Furthermore, only a small fraction (4.6%) of the Belgian pigs was found to be resistant to F18 + E. coli infections. Our results suggest that selection for F18 + E. coli resistant pigs might be an attractive approach to prevent pigs from F18 + E. coli infections, unlike to what has previously been postulated. #

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“…LD mapping has been used extensively to identify genes for monogenic diseases in humans (Peltonen 2000). Contrary to the situation in humans, extensive LD over a long range was observed in dairy cattle, sheep, and pigs (Farnir et al 2000;Mcrae et al 2002;Tenesa et al 2003;Nsengimana et al 2004;Harmegnies et al 2006) because of limited effective population sizes. Thus, LD mapping in livestock, and in other populations with (historically) limited effective population sizes, might be effective using marker maps of more limited density than what is required for most human populations because of the extensive LD that is created by drift in populations of limited effective sizes (Terwilliger et al 1998;Farnir et al 2002).…”

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confidence: 99%

Power and Precision of Alternate Methods for Linkage Disequilibrium Mapping of Quantitative Trait Loci

2007

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Linkage disequilibrium (LD) analysis in outbred populations uses historical recombinations to detect and fine map quantitative trait loci (QTL). Our objective was to evaluate the effect of various factors on power and precision of QTL detection and to compare LD mapping methods on the basis of regression and identity by descent (IBD) in populations of limited effective population size (N e ). An 11-cM region with 6-38 segregating single-nucleotide polymorphisms (SNPs) and a central QTL was simulated. After 100 generations of random mating with N e of 50, 100, or 200, SNP genotypes and phenotypes were generated on 200, 500, or 1000 individuals with the QTL explaining 2 or 5% of phenotypic variance. To detect and map the QTL, phenotypes were regressed on genotypes or (assumed known) haplotypes, in comparison with the IBD method. Power and precision to detect QTL increased with sample size, marker density, and QTL effect. Power decreased with N e , but precision was affected little by N e . Single-marker regression had similar or greater power and precision than other regression models, and was comparable to the IBD method. Thus, for rapid initial screening of samples of adequate size in populations in which drift is the primary force that has created LD, QTL can be detected and mapped by regression on SNP genotypes without recovering haplotypes.

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Measuring the extent of linkage disequilibrium in commercial pig populations

Cited by 34 publications

References 25 publications

Effective population sizes in cattle, sheep, horses, pigs and goats estimated from census and herdbook data

Effective population sizes in cattle, sheep, horses, pigs and goats estimated from census and herdbook data

The possibility of positive selection for both F18+ Escherichia coli and stress resistant pigs opens new perspectives for pig breeding

Power and Precision of Alternate Methods for Linkage Disequilibrium Mapping of Quantitative Trait Loci

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