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How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species.

ABSTRACT: BACKGROUND:PLINK is probably the most used program for analyzing SNP genotypes and runs of homozygosity (ROH), both in human and in animal populations. The last decade, ROH analyses have become the state-of-the-art method for inbreeding assessment. In PLINK, the --homozyg function is used to perform ROH analyses and relies on several input settings. These settings can have a large impact on the outcome and default values are not always appropriate for medium density SNP array data. Guidelines for a robust and uniform ROH analysis in PLINK using medium density data are lacking, albeit these guidelines are vital for comparing different ROH studies. In this study, 8 populations of different livestock and pet species are used to demonstrate the importance of PLINK input settings. Moreover, the effects of pruning SNPs for low minor allele frequencies and linkage disequilibrium on ROH detection are shown. RESULTS:We introduce the genome coverage parameter to appropriately estimate FROH and to check the validity of ROH analyses. The effect of pruning for linkage disequilibrium and low minor allele frequencies on ROH analyses is highly population dependent and such pruning may result in missed ROH. PLINK's minimal density requirement is crucial for medium density genotypes and if set too low, genome coverage of the ROH analysis is limited. Finally, we provide recommendations for the maximal gap, scanning window length and threshold settings. CONCLUSIONS:In this study, we present guidelines for an adequate and robust ROH analysis in PLINK on medium density SNP data. Furthermore, we advise to report parameter settings in publications, and to validate them prior to analysis. Moreover, we encourage authors to report genome coverage to reflect the ROH analysis' validity. Implementing these guidelines will substantially improve the overall quality and uniformity of ROH analyses.

SUBMITTER: Meyermans R

PROVIDER: S-EPMC6990544 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species.

Meyermans R R Gorssen W W Buys N N Janssens S S

BMC genomics 20200129 1

<h4>Background</h4>PLINK is probably the most used program for analyzing SNP genotypes and runs of homozygosity (ROH), both in human and in animal populations. The last decade, ROH analyses have become the state-of-the-art method for inbreeding assessment. In PLINK, the --homozyg function is used to perform ROH analyses and relies on several input settings. These settings can have a large impact on the outcome and default values are not always appropriate for medium density SNP array data. Guide ...[more]

PMID: 31996125

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Project description:Pedigree information was traditionally used to assess inbreeding. The availability of high-density marker panels provides an alternative to assess inbreeding, particularly in the presence of incomplete and error-prone pedigrees. Assessment of autozygosity across chromosomal segments using runs of homozygosity (ROH) has emerged as a valuable tool to estimate inbreeding due to its general flexibility and ability to quantify the chromosomal contribution to genome-wide inbreeding. Unfortunately, the identification of ROH segments is sensitive to the parameters used during the search process. These parameters are heuristically set, leading to significant variation in the results. The minimum length required to identify an ROH segment has major effects on the estimation of inbreeding and inbreeding depression, yet it is arbitrarily set. To overcome this limitation, a search algorithm to approximate mutation enrichment was developed to determine the minimum length of ROH segments. It consists of finding genome segments with significant effect differences in trait means between animals with high and low burdens of autozygous intervals with a specific length. The minimum length could be determined heuristically as the smallest interval at which a significant signal is detected. The proposed method was tested in an inbred Hereford cattle population genotyped for 30,220 SNPs. Phenotypes recorded for six traits were used for the approximation of mutation loads. The estimated minimum length was around 1 Mb for yearling weight (YW) and average daily gain (ADG) and 4 Mb for birth weight and weaning weight. These trait-specific thresholds estimated using the proposed method could be attributed to a trait-dependent effect of homozygosity. The detection of significant inbreeding effects was well aligned with the estimated thresholds, especially for YW and ADG. Although highly deleterious alleles are expected to be more frequent in recent inbreeding (long ROH), short ROH segments (<5 Mb) could contain a large number of less deleterious mutations with substantial joint effects on some traits (YW and ADG). Our results highlight the importance of accurate estimation of the ROH-based inbreeding and the necessity to consider a trait-specific minimum length threshold for the identification of ROH segments in inbreeding depression analyses. These thresholds could be determined using the proposed method provided the availability of phenotypic information.

Dataset Information

How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species.

Publications

How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species.

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