Performance comparison of exome DNA sequencing technologies

Whole exome sequencing by high-throughput sequencing of target-enriched genomic DNA (exome-seq) has become common in basic and translational research as a means of interrogating the interpretable part of the human genome at relatively low cost. We present a comparison of three major commercial exome sequencing platforms from Agilent, Illumina and Nimblegen applied to the same human blood sample. Our results suggest that the Nimblegen platform, which is the only one to use high-density overlapping baits, covers fewer genomic regions than the other platforms but requires the least amount of sequencing to sensitively detect small variants. Agilent and Illumina are able to detect a greater total number of variants with additional sequencing. Illumina captures untranslated regions, which are not targeted by the Nimblegen and Agilent platforms. We also compare exome sequencing and whole genome sequencing (WGS) of the same sample, demonstrating that exome sequencing can detect additional small variants missed by WGS.     

High-performance single-chip exon capture allows accurate whole exome sequencing using the Illumina Genome Analyzer

Here we present an adaptation of NimbleGen 2.1M-probe array sequence capture for whole exome sequencing using the Illumina Genome Analyzer (GA) platform. The protocol involves two-stage library construction. The specificity of exome enrichment was approximately 80% with 95.6% even coverage of the 34 Mb target region at an average sequencing depth of 33-fold. Comparison of our results with whole genome shot-gun resequencing results showed that the exome SNP calls gave only 0.97% false positive and 6.27% false negative variants. Our protocol is also well suited for use with whole genome amplified DNA. The results presented here indicate that there is a promising future for large-scale population genomics and medical studies using a whole exome sequencing approach.     

Evaluating the Coverage and Potential of Imputing the Exome Microarray with Next-Generation Imputation Using the 1000 Genomes Project

Next-generation genotyping microarrays have been designed with insights from large-scale sequencing of exomes and whole genomes. The exome genotyping arrays promise to query the functional regions of the human genome at a fraction of the sequencing cost, thus allowing large number of samples to be genotyped. However, two pertinent questions exist: firstly, how representative is the content of the exome chip for populations not involved in the design of the chip; secondly, can the content of the exome chip be imputed with the reference data from the 1000 Genomes Project (1KGP). By deep whole-genome sequencing two Asian populations that are not part of the 1KGP, comprising 96 Southeast Asian Malays and 36 South Asian Indians for which the same samples have also been genotyped on both the Illumina 2.5 M and exome microarrays, we discovered the exome chip is a poor representation of exonic content in our two populations. However, up to 94.1% of the variants on the exome chip that are polymorphic in our populations can be confidently imputed with existing non-exome-centric microarrays using the 1KGP panel. The coverage further increases if there exists population-specific reference data from whole-genome sequencing. There is thus limited gain in using the exome chip for populations not involved in the microarray design. Instead, for the same cost of genotyping 2,000 samples on the exome chip, performing whole-genome sequencing of at least 35 samples in that population to complement the 1KGP may yield a higher coverage of the exonic content from imputation instead.     

Affected Kindred Analysis of Human X Chromosome Exomes to Identify Novel X-Linked Intellectual Disability Genes

X-linked Intellectual Disability (XLID) is a group of genetically heterogeneous disorders caused by mutations in genes on the X chromosome. Deleterious mutations in ~10% of X chromosome genes are implicated in causing XLID disorders in ~50% of known and suspected XLID families. The remaining XLID genes are expected to be rare and even private to individual families. To systematically identify these XLID genes, we sequenced the X chromosome exome (X-exome) in 56 well-established XLID families (a single affected male from 30 families and two affected males from 26 families) using an Agilent SureSelect X-exome kit and the Illumina HiSeq 2000 platform. To enrich for disease-causing mutations, we first utilized variant filters based on dbSNP, the male-restricted portions of the 1000 Genomes Project, or the Exome Variant Server datasets. However, these databases present limitations as automatic filters for enrichment of XLID genes. We therefore developed and optimized a strategy that uses a cohort of affected male kindred pairs and an additional small cohort of affected unrelated males to enrich for potentially pathological variants and to remove neutral variants. This strategy, which we refer to as Affected Kindred/Cross-Cohort Analysis, achieves a substantial enrichment for potentially pathological variants in known XLID genes compared to variant filters from public reference databases, and it has identified novel XLID candidate genes. We conclude that Affected Kindred/Cross-Cohort Analysis can effectively enrich for disease-causing genes in rare, Mendelian disorders, and that public reference databases can be used effectively, but cautiously, as automatic filters for X-linked disorders.     

Targeted high throughput sequencing of a cancer-related exome subset by specific sequence capture with a fully automated microarray platform

Sequence capture methods for targeted next generation sequencing promise to massively reduce cost of genomics projects compared to untargeted sequencing. However, evaluated capture methods specifically dedicated to biologically relevant genomic regions are rare. Whole exome capture has been shown to be a powerful tool to discover the genetic origin of disease and provides a reduction in target size and thus calculative sequencing capacity of > 90-fold compared to untargeted whole genome sequencing. For further cost reduction, a valuable complementing approach is the analysis of smaller, relevant gene subsets but involving large cohorts of samples. However, effective adjustment of target sizes and sample numbers is hampered by the limited scalability of enrichment systems. We report a highly scalable and automated method to capture a 480 Kb exome subset of 115 cancer-related genes using microfluidic DNA arrays. The arrays are adaptable from 125 Kb to 1 Mb target size and/or one to eight samples without barcoding strategies, representing a further 26 – 270-fold reduction of calculative sequencing capacity compared to whole exome sequencing. Illumina GAII analysis of a HapMap genome enriched for this exome subset revealed a completeness of > 96%. Uniformity was such that > 68% of exons had at least half the median depth of coverage. An analysis of reference SNPs revealed a sensitivity of up to 93% and a specificity of 98.2% or higher.     

HLA Typing from 1000 Genomes Whole Genome and Whole Exome Illumina Data

Specific HLA genotypes are known to be linked to either resistance or susceptibility to certain diseases or sensitivity to certain drugs. In addition, high accuracy HLA typing is crucial for organ and bone marrow transplantation. The most widespread high resolution HLA typing method used to date is Sanger sequencing based typing (SBT), and next generation sequencing (NGS) based HLA typing is just starting to be adopted as a higher throughput, lower cost alternative. By HLA typing the HapMap subset of the public 1000 Genomes paired Illumina data, we demonstrate that HLA-A, B and C typing is possible from exome sequencing samples with higher than 90% accuracy. The older 1000 Genomes whole genome sequencing read sets are less reliable and generally unsuitable for the purpose of HLA typing. We also propose using coverage % (the extent of exons covered) as a quality check (QC) measure to increase reliability.     

Validation of multiple single nucleotide variation calls by additional exome analysis with a semiconductor sequencer to supplement data of whole-genome sequencing of a human population

Background

Validation of single nucleotide variations in whole-genome sequencing is critical for studying disease-related variations in large populations. A combination of different types of next-generation sequencers for analyzing individual genomes may be an efficient means of validating multiple single nucleotide variations calls simultaneously.

Results

Here, we analyzed 12 independent Japanese genomes using two next-generation sequencing platforms: the Illumina HiSeq 2500 platform for whole-genome sequencing (average depth 32.4×), and the Ion Proton semiconductor sequencer for whole exome sequencing (average depth 109×). Single nucleotide polymorphism (SNP) calls based on the Illumina Human Omni 2.5-8 SNP chip data were used as the reference. We compared the variant calls for the 12 samples, and found that the concordance between the two next-generation sequencing platforms varied between 83% and 97%.

Conclusions

Our results show the versatility and usefulness of the combination of exome sequencing with whole-genome sequencing in studies of human population genetics and demonstrate that combining data from multiple sequencing platforms is an efficient approach to validate and supplement SNP calls.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-673) contains supplementary material, which is available to authorized users.     

CODEX: a normalization and copy number variation detection method for whole exome sequencing

High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures.     

Exome Sequencing of a Multigenerational Human Pedigree

Over the next few years, the efficient use of next-generation sequencing (NGS) in human genetics research will depend heavily upon the effective mechanisms for the selective enrichment of genomic regions of interest. Recently, comprehensive exome capture arrays have become available for targeting approximately 33 Mb or ∼180,000 coding exons across the human genome. Selective genomic enrichment of the human exome offers an attractive option for new experimental designs aiming to quickly identify potential disease-associated genetic variants, especially in family-based studies. We have evaluated a 2.1 M feature human exome capture array on eight individuals from a three-generation family pedigree. We were able to cover up to 98% of the targeted bases at a long-read sequence read depth of ≥3, 86% at a read depth of ≥10, and over 50% of all targets were covered with ≥20 reads. We identified up to 14,284 SNPs and small indels per individual exome, with up to 1,679 of these representing putative novel polymorphisms. Applying the conservative genotype calling approach HCDiff, the average rate of detection of a variant allele based on Illumina 1 M BeadChips genotypes was 95.2% at ≥10x sequence. Further, we propose an advantageous genotype calling strategy for low covered targets that empirically determines cut-off thresholds at a given coverage depth based on existing genotype data. Application of this method was able to detect >99% of SNPs covered ≥8x. Our results offer guidance for “real-world” applications in human genetics and provide further evidence that microarray-based exome capture is an efficient and reliable method to enrich for chromosomal regions of interest in next-generation sequencing experiments.     

New insights into the performance of human whole-exome capture platforms

Whole exome sequencing (WES) is increasingly used in research and diagnostics. WES users expect coverage of the entire coding region of known genes as well as sufficient read depth for the covered regions. It is, however, unknown which recent WES platform is most suitable to meet these expectations. We present insights into the performance of the most recent standard exome enrichment platforms from Agilent, NimbleGen and Illumina applied to six different DNA samples by two sequencing vendors per platform. Our results suggest that both Agilent and NimbleGen overall perform better than Illumina and that the high enrichment performance of Agilent is stable among samples and between vendors, whereas NimbleGen is only able to achieve vendor- and sample-specific best exome coverage. Moreover, the recent Agilent platform overall captures more coding exons with sufficient read depth than NimbleGen and Illumina. Due to considerable gaps in effective exome coverage, however, the three platforms cannot capture all known coding exons alone or in combination, requiring improvement. Our data emphasize the importance of evaluation of updated platform versions and suggest that enrichment-free whole genome sequencing can overcome the limitations of WES in sufficiently covering coding exons, especially GC-rich regions, and in characterizing structural variants.     

Haplotype Estimation Using Sequencing Reads

High-throughput sequencing technologies produce short sequence reads that can contain phase information if they span two or more heterozygote genotypes. This information is not routinely used by current methods that infer haplotypes from genotype data. We have extended the SHAPEIT2 method to use phase-informative sequencing reads to improve phasing accuracy. Our model incorporates the read information in a probabilistic model through base quality scores within each read. The method is primarily designed for high-coverage sequence data or data sets that already have genotypes called. One important application is phasing of single samples sequenced at high coverage for use in medical sequencing and studies of rare diseases. Our method can also use existing panels of reference haplotypes. We tested the method by using a mother-father-child trio sequenced at high-coverage by Illumina together with the low-coverage sequence data from the 1000 Genomes Project (1000GP). We found that use of phase-informative reads increases the mean distance between switch errors by 22% from 274.4 kb to 328.6 kb. We also used male chromosome X haplotypes from the 1000GP samples to simulate sequencing reads with varying insert size, read length, and base error rate. When using short 100 bp paired-end reads, we found that using mixtures of insert sizes produced the best results. When using longer reads with high error rates (5–20 kb read with 4%–15% error per base), phasing performance was substantially improved.     

Efficient and cost effective population resequencing by pooling and in-solution hybridization

High-throughput sequencing of targeted genomic loci in large populations is an effective approach for evaluating the contribution of rare variants to disease risk. We evaluated the feasibility of using in-solution hybridization-based target capture on pooled DNA samples to enable cost-efficient population sequencing studies. For this, we performed pooled sequencing of 100 HapMap samples across ～ 600 kb of DNA sequence using the Illumina GAIIx. Using our accurate variant calling method for pooled sequence data, we were able to not only identify single nucleotide variants with a low false discovery rate (<1%) but also accurately detect short insertion/deletion variants. In addition, with sufficient coverage per individual in each pool (30-fold) we detected 97.2% of the total variants and 93.6% of variants below 5% in frequency. Finally, allele frequencies for single nucleotide variants (SNVs) estimated from the pooled data and the HapMap genotype data were tightly correlated (correlation coefficient > = 0.995).     

Genome-Wide Profiling of Structural Genomic Variations in Korean HapMap Individuals

Background

Structural genomic variation study, along with microarray technology development has provided many genomic resources related with architecture of human genome, and led to the fact that human genome structure is a lot more complicated than previously thought.

Methodology/Principal Findings

In the case of International HapMap Project, Epstein-Barr various immortalized cell lines were preferably used over blood in order to get a larger number of genomic DNA. However, genomic aberration stemming from immortalization process, biased representation of the donor tissue, and culture process may influence the accuracy of SNP genotypes. In order to identify chromosome aberrations including loss of heterozygosity (LOH), large-scale and small-scale copy number variations, we used Illumina HumanHap500 BeadChip (555,352 markers) on Korean HapMap individuals (n = 90) to obtain Log R ratio and B allele frequency information, and then utilized the data with various programs including Illumina ChromoZone, cnvParition and PennCNV. As a result, we identified 28 LOHs (>3 mb) and 35 large-scale CNVs (>1 mb), with 4 samples having completely duplicated chromosome. In addition, after checking the sample quality (standard deviation of log R ratio <0.30), we selected 79 samples and used both signal intensity and B allele frequency simultaneously for identification of small-scale CNVs (<1 mb) to discover 4,989 small-scale CNVs. Identified CNVs in this study were successfully validated using visual examination of the genoplot images, overlapping analysis with previously reported CNVs in DGV, and quantitative PCR.

Conclusion/Significance

In this study, we describe the result of the identified chromosome aberrations in Korean HapMap individuals, and expect that these findings will provide more meaningful information on the human genome.     

X染色体变异对男性精神发育迟滞致病性的研究进展

精神发育迟滞(旧称智力低下)作为儿科神经科常见的一组疾患,具有高度的遗传和表型异质性,大约25%~50%的精神发育迟滞是由遗传因素引起的,其中X染色体基因/基因组变异占25%~30%,导致X连锁的精神发育迟滞。X连锁的精神发育迟滞患者占所有精神发育迟滞患者的10%~15％以上,约20%~25％的男性精神发育迟滞归因于X连锁的精神发育迟滞。精神发育迟滞男女患病比例为1.3:1,这与男性只有一条X染色体的遗传背景有关。随着新一代基因组检测技术的快速发展和临床应用,尤其是全外显子测序、高深度测序、X染色体深度测序和全基因组芯片杂交,这些大大改善了精神发育迟滞患者的X染色体基因/基因组变异检出。本文综述了致精神发育迟滞的X染色体基因组/基因变异特点、其对男性精神发育迟滞的致病性,以及如何采用新测序技术提高检出率,旨在促进科研人员认识X染色体变异在男性精神发育迟滞的致病性,拓宽精神发育迟滞遗传病因的认识,同时也为遗传咨询和产前诊断提供理论依据。     

Exome Capture with Heterologous Enrichment in Pig (Sus scrofa)

The discovery of new protein-coding DNA variants related to carcass traits is very important for the Italian pig industry, which requires heavy pigs with higher thickness of subcutaneous fat for Protected Designation of Origin (PDO) productions. Exome capture techniques offer the opportunity to focus on the regions of DNA potentially related to the gene and protein expression. In this research a human commercial target enrichment kit was used to evaluate its performances for pig exome capture and for the identification of DNA variants suitable for comparative analysis. Two pools of 30 pigs each, crosses of Italian Duroc X Large White (DU) and Commercial hybrid X Large White (HY), were used and NGS libraries were prepared with the SureSelectXT Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent). A total of 140.2 M and 162.5 M of raw reads were generated for DU and HY, respectively. Average coverage of all the exonic regions for Sus scrofa (ENSEMBL Sus_scrofa.Sscrofa10.2.73.gtf) was 89.33X for DU and 97.56X for HY; and 35% of aligned bases uniquely mapped to off-target regions. Comparison of sequencing data with the Sscrofa10.2 reference genome, after applying hard filtering criteria, revealed a total of 232,530 single nucleotide variants (SNVs) of which 20.6% mapped in exonic regions and 49.5% within intronic regions. The comparison of allele frequencies of 213 randomly selected SNVs from exome sequencing and the same SNVs analyzed with a Sequenom MassARRAY® system confirms that this “human-on-pig” approach offers new potentiality for the identification of DNA variants in protein-coding genes.     

Complex Patterns of Chromosome 11 Aberrations in Myeloid Malignancies Target CBL,MLL, DDB1 and LMO2

Exome sequencing of primary tumors identifies complex somatic mutation patterns. Assignment of relevance of individual somatic mutations is difficult and poses the next challenge for interpretation of next generation sequencing data. Here we present an approach how exome sequencing in combination with SNP microarray data may identify targets of chromosomal aberrations in myeloid malignancies. The rationale of this approach is that hotspots of chromosomal aberrations might also harbor point mutations in the target genes of deletions, gains or uniparental disomies (UPDs). Chromosome 11 is a frequent target of lesions in myeloid malignancies. Therefore, we studied chromosome 11 in a total of 813 samples from 773 individual patients with different myeloid malignancies by SNP microarrays and complemented the data with exome sequencing in selected cases exhibiting chromosome 11 defects. We found gains, losses and UPDs of chromosome 11 in 52 of the 813 samples (6.4%). Chromosome 11q UPDs frequently associated with mutations of CBL. In one patient the 11qUPD amplified somatic mutations in both CBL and the DNA repair gene DDB1. A duplication within MLL exon 3 was detected in another patient with 11qUPD. We identified several common deleted regions (CDR) on chromosome 11. One of the CDRs associated with de novo acute myeloid leukemia (P=0.013). One patient with a deletion at the LMO2 locus harbored an additional point mutation on the other allele indicating that LMO2 might be a tumor suppressor frequently targeted by 11p deletions. Our chromosome-centered analysis indicates that chromosome 11 contains a number of tumor suppressor genes and that the role of this chromosome in myeloid malignancies is more complex than previously recognized.     

Number and evolutionary conservation of alpha- and beta-tubulin and cytoplasmic beta- and gamma-actin genes using specific cloned cDNA probes

A partial library of cloned human DNA was screened for sequences represented on and specific to the X chromosome. The library was constructed from Bam HI-digested human DNA from cells with X chromosome polyploidy, and was cloned in pBR322. The screening was performed by individually hybridizing ³²P-labeled cloned plasmids to Southern blots containing Bam HI-digested DNA from mouse-human hybrid cells having the human X chromosome and from derivative hybrids lacking the human X. Of 45 clones assayed, 33 contained sequences homologous to ones represented many times on the X. In situ hybridization to metaphase chromosomes demonstrated that at least four of these clones were homologous to autosomes as well. Only one of the 18 clones of this kind tested cross-hybridized with another. Two recombinant plasmids were shown to be derived from the X chromosome and to be X chromosome-specific by three criteria: they hybridized to a single band in the Southern blots of Bam HI-digested DNA from hybrid cells containing the X chromosome; they hybridized to a band of the same molecular weight as did the inserted DNA fragment; and they showed a dosage effect when hybridized to Southern blots of Bam HI-digested DNA from XY and XXX cells. One of these hybridized as a single-copy or low-order reiterated sequence in a Cot analysis using male DNA as driver. Our methods can be applied to the identification of any chromosome-specific clone. The two X-specific clones identified here should be useful in investigating the mechanism of X inactivation and in isolating a Barr body.     

Characterizing and measuring bias in sequence data

Background

DNA sequencing technologies deviate from the ideal uniform distribution of reads. These biases impair scientific and medical applications. Accordingly, we have developed computational methods for discovering, describing and measuring bias.

Results

We applied these methods to the Illumina, Ion Torrent, Pacific Biosciences and Complete Genomics sequencing platforms, using data from human and from a set of microbes with diverse base compositions. As in previous work, library construction conditions significantly influence sequencing bias. Pacific Biosciences coverage levels are the least biased, followed by Illumina, although all technologies exhibit error-rate biases in high- and low-GC regions and at long homopolymer runs. The GC-rich regions prone to low coverage include a number of human promoters, so we therefore catalog 1,000 that were exceptionally resistant to sequencing. Our results indicate that combining data from two technologies can reduce coverage bias if the biases in the component technologies are complementary and of similar magnitude. Analysis of Illumina data representing 120-fold coverage of a well-studied human sample reveals that 0.20% of the autosomal genome was covered at less than 10% of the genome-wide average. Excluding locations that were similar to known bias motifs or likely due to sample-reference variations left only 0.045% of the autosomal genome with unexplained poor coverage.

Conclusions

The assays presented in this paper provide a comprehensive view of sequencing bias, which can be used to drive laboratory improvements and to monitor production processes. Development guided by these assays should result in improved genome assemblies and better coverage of biologically important loci.     

Comparison and evaluation of two exome capture kits and sequencing platforms for variant calling

Background

To promote the clinical application of next-generation sequencing, it is important to obtain accurate and consistent variants of target genomic regions at low cost. Ion Proton, the latest updated semiconductor-based sequencing instrument from Life Technologies, is designed to provide investigators with an inexpensive platform for human whole exome sequencing that achieves a rapid turnaround time. However, few studies have comprehensively compared and evaluated the accuracy of variant calling between Ion Proton and Illumina sequencing platforms such as HiSeq 2000, which is the most popular sequencing platform for the human genome. The Ion Proton sequencer combined with the Ion TargetSeq™ Exome Enrichment Kit together make up TargetSeq-Proton, whereas SureSelect-Hiseq is based on the Agilent SureSelect Human All Exon v4 Kit and the HiSeq 2000 sequencer.

Results

Here, we sequenced exonic DNA from four human blood samples using both TargetSeq-Proton and SureSelect-HiSeq. We then called variants in the exonic regions that overlapped between the two exome capture kits (33.6 Mb). The rates of shared variant loci called by two sequencing platforms were from 68.0 to 75.3 % in four samples, whereas the concordance of co-detected variant loci reached 99 %. Sanger sequencing validation revealed that the validated rate of concordant single nucleotide polymorphisms (SNPs) (91.5 %) was higher than the SNPs specific to TargetSeq-Proton (60.0 %) or specific to SureSelect-HiSeq (88.3 %). With regard to 1-bp small insertions and deletions (InDels), the Sanger sequencing validated rates of concordant variants (100.0 %) and SureSelect-HiSeq-specific (89.6 %) were higher than those of TargetSeq-Proton-specific (15.8 %).

Conclusions

In the sequencing of exonic regions, a combination of using of two sequencing strategies (SureSelect-HiSeq and TargetSeq-Proton) increased the variant calling specificity for concordant variant loci and the sensitivity for variant loci called by any one platform. However, for the sequencing of platform-specific variants, the accuracy of variant calling by HiSeq 2000 was higher than that of Ion Proton, specifically for the InDel detection. Moreover, the variant calling software also influences the detection of SNPs and, specifically, InDels in Ion Proton exome sequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1796-6) contains supplementary material, which is available to authorized users.