HaploBlocker: Creation of Subgroup-Specific Haplotype Blocks and Libraries. Issue 4 (31st May 2019)

• Record Type: Journal Article
• Authors: Pook, Torsten; Schlather, Martin; de los Campos, Gustavo; Mayer, Manfred; Schoen, Chris Carolin; Simianer, Henner
• Is Part Of: Genetics. Volume 212:Issue 4(2019)
• Page Start: 1045
• Page End: 1061
• Publication Date: 2019-05-31
• Subjects: haplotype blocks -- haplotype libraries -- population genetics -- selection signatures -- R-package -- identity-by-descent; Genetics -- Periodicals; 576.5
• DOI: 10.1534/genetics.119.302283
• Languages: English
• ISSNs: 0016-6731

Abstract

Abstract: The concept of haplotype blocks has been shown to be useful in genetics. Fields of application range from the detection of regions under positive selection to statistical methods that make use of dimension reduction... The concept of haplotype blocks has been shown to be useful in genetics. Fields of application range from the detection of regions under positive selection to statistical methods that make use of dimension reduction. We propose a novel approach ("HaploBlocker") for defining and inferring haplotype blocks that focuses on linkage instead of the commonly used population-wide measures of linkage disequilibrium. We define a haplotype block as a sequence of genetic markers that has a predefined minimum frequency in the population, and only haplotypes with a similar sequence of markers are considered to carry that block, effectively screening a dataset for group-wise identity-by-descent. From these haplotype blocks, we construct a haplotype library that represents a large proportion of genetic variability with a limited number of blocks. Our method is implemented in the associated R-package HaploBlocker, and provides flexibility not only to optimize the structure of the obtained haplotype library for subsequent analyses, but also to handle datasets of different marker density and genetic diversity. By using haplotype blocks instead of single nucleotide polymorphisms (SNPs), local epistatic interactions can be naturally modeled, and the reduced number of parameters enables a wide variety of new methods for further genomic analyses such as genomic prediction and the detection of selection signatures. We illustrate our methodology with a dataset comprising 501 doubled haploid lines in a European maize landrace genotyped at 501, 124 SNPs. With the suggested approach, we identified 2991 haplotype blocks with an average length of 2685 SNPs that together represent 94% of the dataset.