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Impact of three Illumina library construction methods on GC bias and HLA genotype calling.

ABSTRACT: Next-generation sequencing (NGS) is increasingly recognized for its ability to overcome allele ambiguity and deliver high-resolution typing in the HLA system. Using this technology, non-uniform read distribution can impede the reliability of variant detection, which renders high-confidence genotype calling particularly difficult to achieve in the polymorphic HLA complex. Recently, library construction has been implicated as the dominant factor in instigating coverage bias. To study the impact of this phenomenon on HLA genotyping, we performed long-range PCR on 12 samples to amplify HLA-A, -B, -C, -DRB1, and -DQB1, and compared the relative contribution of three Illumina library construction methods (TruSeq Nano, Nextera, Nextera XT) in generating downstream bias. Here, we show high GC% to be a good predictor of low sequencing depth. Compared to standard TruSeq Nano, GC bias was more prominent in transposase-based protocols, particularly Nextera XT, likely through a combination of transposase insertion bias being coupled with a high number of PCR enrichment cycles. Importantly, our findings demonstrate non-uniform read depth can have a direct and negative impact on the robustness of HLA genotyping, which has clinical implications for users when choosing a library construction strategy that aims to balance cost and throughput with data quality.

SUBMITTER: Lan JH

PROVIDER: S-EPMC5089167 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Impact of three Illumina library construction methods on GC bias and HLA genotype calling.

Lan James H JH Yin Yuxin Y Reed Elaine F EF Moua Kevin K Thomas Kimberly K Zhang Qiuheng Q

Human immunology 20141225 2-3

Next-generation sequencing (NGS) is increasingly recognized for its ability to overcome allele ambiguity and deliver high-resolution typing in the HLA system. Using this technology, non-uniform read distribution can impede the reliability of variant detection, which renders high-confidence genotype calling particularly difficult to achieve in the polymorphic HLA complex. Recently, library construction has been implicated as the dominant factor in instigating coverage bias. To study the impact of ...[more]

PMID: 25543015

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Project description:We developed a low-cost method for the production of Illumina-compatible sequencing libraries that allows up to 14 times more libraries for high-throughput Illumina sequencing to be generated for the same cost. We call this new method Hackflex. The quality of library preparation was tested by constructing libraries from Escherichia coli MG1655 genomic DNA using either Hackflex, standard Nextera Flex (recently renamed as Illumina DNA Prep) or a variation of standard Nextera Flex in which the bead-linked transposase is diluted prior to use. In order to test the library quality for genomes with a higher and a lower G+C content, library construction methods were also tested on Pseudomonas aeruginosa PAO1 and Staphylococcus aureus ATCC 25923, respectively. We demonstrated that Hackflex can produce high-quality libraries and yields a highly uniform coverage, equivalent to the standard Nextera Flex kit. We show that strongly size-selected libraries produce sufficient yield and complexity to support de novo microbial genome assembly, and that assemblies of the large-insert libraries can be much more contiguous than standard libraries without strong size selection. We introduce a new set of sample barcodes that are distinct from standard Illumina barcodes, enabling Hackflex samples to be multiplexed with samples barcoded using standard Illumina kits. Using Hackflex, we were able to achieve a per-sample reagent cost for library prep of A$7.22 (Australian dollars) (US $5.60; UK £3.87, £1=A$1.87), which is 9.87 times lower than the standard Nextera Flex protocol at advertised retail price. An additional simple modification and further simplification of the protocol by omitting the wash step enables a further price reduction to reach an overall 14-fold cost saving. This method will allow researchers to construct more libraries within a given budget, thereby yielding more data and facilitating research programmes where sequencing large numbers of libraries is beneficial.

Project description:BackgroundMicroRNAs(miRNAs) are 18-25 nt small RNAs playing critical roles in many biological processes. The majority of known miRNAs were discovered by conventional cloning and a Sanger sequencing approach. The next-generation sequencing (NGS) technologies enable in-depth characterization of the global repertoire of miRNAs, and different protocols for miRNA library construction have been developed. However, the possible bias between the relative expression levels and sequences introduced by different protocols of library preparation have rarely been explored.ResultsWe assessed three different miRNA library preparation protocols, SOLiD, Illumina versions 1 and 1.5, using cloning or SBS sequencing of total RNA samples extracted from skeletal muscles from Hu sheep and Dorper sheep, and then validated 9 miRNAs by qRT-PCR. Our results show that SBS sequencing data highly correlate with Illumina cloning data. The SOLiD data, when compared to Illumina's, indicate more dispersed distribution of length, higher frequency variation for nucleotides near the 3'- and 5'-ends, higher frequency occurrence for reads containing end secondary structure (ESS), and higher frequency for reads that do not map to known miRNAs. qRT-PCR results showed the best correlation with SOLiD cloning data. Fold difference of Hu sheep and Dorper sheep between qRT-PCR result and SBS sequencing data correlated well (r = 0.937), and fold difference of miR-1 and miR-206 among SOLiD cloning data, qRT-PCR and SBS sequencing data was similar.ConclusionsThe sequencing depth can influence the quantitative measurement of miRNA abundance, but the discrepancy caused by it was not statistically significant as high correlation was observed between Illumina cloning and SBS sequencing data. Bias of length distribution, sequence variation, and ESS was observed between data obtained with the different protocols. SOLiD cloning data differ from Illumina cloning data mainly because of distinct methods of adapter ligation. The good correlation between qRT-PCR result and SOLiD data might be due to the similarities of the hybridization-based methods. The fold difference analysis indicated that methods based on hybridization may be superior for quantitative measurement of miRNA abundance. Because of the genome sequence of the sheep is not available, our data may not explain how the entire miRNA bias in the natural miRNAs in sheep or other mammal miRNA expression, unbiased artificially synthesized miRNA will help on evaluating the methodology of miRNA library preparation.

Dataset Information

Impact of three Illumina library construction methods on GC bias and HLA genotype calling.

Publications

Impact of three Illumina library construction methods on GC bias and HLA genotype calling.

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