Runs of homozygosity (ROH) are sizeable stretches of homozygous genotypes at consecutive polymorphic DNA marker positions, traditionally captured by means of genome-wide single nucleotide polymorphism (SNP) genotyping. With the advent of next-generation sequencing (NGS) technologies, a number of methods initially devised for the analysis of SNP array data (those based on sliding-window algorithms such as PLINK or GERMLINE and graphical tools like HomozygosityMapper) or specifically conceived for NGS data have been adopted for the detection of ROH from whole exome sequencing (WES) data. In the latter group, algorithms for both graphical representation (AgileVariantMapper, HomSI) and computational detection ((HM2)-M-3) of WES-derived ROH have been proposed. Here we examine these different approaches and discuss available strategies to implement ROH detection in WES analysis. Among sliding-window algorithms, PLINK appears to be well-suited for the detection of ROH, especially of the long ones. As a method specifically tailored for WES data, (HM2)-M-3 outperforms existing algorithms especially on short and medium ROH. We conclude that, notwithstanding the irregular distribution of exons, WES data can be used with some approximation for unbiased genome-wide analysis of ROH features, with promising applications to homozygosity mapping of disease genes, comparative analysis of populations and epidemiological studies based on consanguinity.

Detection of runs of homozygosity from whole exome sequencing data: state of the art and perspectives for clinical, population and epidemiological studies

Gialluisi A;
2014

Abstract

Runs of homozygosity (ROH) are sizeable stretches of homozygous genotypes at consecutive polymorphic DNA marker positions, traditionally captured by means of genome-wide single nucleotide polymorphism (SNP) genotyping. With the advent of next-generation sequencing (NGS) technologies, a number of methods initially devised for the analysis of SNP array data (those based on sliding-window algorithms such as PLINK or GERMLINE and graphical tools like HomozygosityMapper) or specifically conceived for NGS data have been adopted for the detection of ROH from whole exome sequencing (WES) data. In the latter group, algorithms for both graphical representation (AgileVariantMapper, HomSI) and computational detection ((HM2)-M-3) of WES-derived ROH have been proposed. Here we examine these different approaches and discuss available strategies to implement ROH detection in WES analysis. Among sliding-window algorithms, PLINK appears to be well-suited for the detection of ROH, especially of the long ones. As a method specifically tailored for WES data, (HM2)-M-3 outperforms existing algorithms especially on short and medium ROH. We conclude that, notwithstanding the irregular distribution of exons, WES data can be used with some approximation for unbiased genome-wide analysis of ROH features, with promising applications to homozygosity mapping of disease genes, comparative analysis of populations and epidemiological studies based on consanguinity.
Exome sequencing, Runs of homozygosity, Homozygosity mapping
Pippucci, T; Magi, A; Gialluisi, A; Romeo, G
File in questo prodotto:
File Dimensione Formato  
Pippucci2014_HumanHeredityReview.pdf

non disponibili

Tipologia: Versione Editoriale (PDF)
Licenza: DRM non definito
Dimensione 904.35 kB
Formato Adobe PDF
904.35 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2125143
Citazioni
  • ???jsp.display-item.citation.pmc??? 11
  • Scopus 20
  • ???jsp.display-item.citation.isi??? 20
social impact