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Cost-effective high-throughput single-haplotype iterative mapping and sequencing for complex genomic structures.

ABSTRACT: The reference sequences of structurally complex regions can be obtained only through highly accurate clone-based approaches. We and others have successfully used single-haplotype iterative mapping and sequencing (SHIMS) 1.0 to assemble structurally complex regions across the sex chromosomes of several vertebrate species and to allow for targeted improvements to the reference sequences of human autosomes. However, SHIMS 1.0 is expensive and time consuming, requiring resources that only a genome center can provide. Here we introduce SHIMS 2.0, an improved SHIMS protocol that allows even a small laboratory to generate high-quality reference sequence from complex genomic regions. Using a streamlined and parallelized library-preparation protocol, and taking advantage of inexpensive high-throughput short-read-sequencing technologies, a small laboratory with both molecular biology and bioinformatics experience can sequence and assemble 192 large-insert bacterial artificial chromosome (BAC) or fosmid clones in 1 week. In SHIMS 2.0, in contrast to other pooling strategies, each clone is sequenced with a unique barcode, thus enabling clones containing nearly identical sequences to be multiplexed in a single sequencing run and assembled separately. Relative to SHIMS 1.0, SHIMS 2.0 decreases the required cost and time by two orders of magnitude while preserving high sequencing accuracy.

SUBMITTER: Bellott DW

PROVIDER: S-EPMC6896216 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Cost-effective high-throughput single-haplotype iterative mapping and sequencing for complex genomic structures.

Bellott Daniel W DW Cho Ting-Jan TJ Hughes Jennifer F JF Skaletsky Helen H Page David C DC Page David C DC

Nature protocols 20180322 4

The reference sequences of structurally complex regions can be obtained only through highly accurate clone-based approaches. We and others have successfully used single-haplotype iterative mapping and sequencing (SHIMS) 1.0 to assemble structurally complex regions across the sex chromosomes of several vertebrate species and to allow for targeted improvements to the reference sequences of human autosomes. However, SHIMS 1.0 is expensive and time consuming, requiring resources that only a genome c ...[more]

PMID: 29565902

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Project description:MotivationFine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data require the pairwise correlation coefficients ([Formula: see text]) of the variants. However, haplotypes rather than pairwise [Formula: see text], are the true biological representation of linkage disequilibrium (LD) among multiple loci. In this article, we present an empirical iterative method, HAPlotype Regional Association analysis Program (HAPRAP), that enables fine mapping using summary statistics and haplotype information from an individual-level reference panel.ResultsSimulations with individual-level genotypes show that the results of HAPRAP and multiple regression are highly consistent. In simulation with summary-level data, we demonstrate that HAPRAP is less sensitive to poor LD estimates. In a parametric simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well with a small training sample size (N < 2000) while other methods become suboptimal. Moreover, HAPRAP's performance is not affected substantially by single nucleotide polymorphisms (SNPs) with low minor allele frequencies. We applied the method to existing quantitative trait and binary outcome meta-analyses (human height, QTc interval and gallbladder disease); all previous reported association signals were replicated and two additional variants were independently associated with human height. Due to the growing availability of summary level data, the value of HAPRAP is likely to increase markedly for future analyses (e.g. functional prediction and identification of instruments for Mendelian randomization).Availability and implementationThe HAPRAP package and documentation are available at http://apps.biocompute.org.uk/haprap/ CONTACT: : jie.zheng@bristol.ac.uk or tom.gaunt@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.

Dataset Information

Cost-effective high-throughput single-haplotype iterative mapping and sequencing for complex genomic structures.

Publications

Cost-effective high-throughput single-haplotype iterative mapping and sequencing for complex genomic structures.

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