Analysis of archived residual newborn screening blood spots after whole genome amplification

Background

Deidentified newborn screening bloodspot samples (NBS) represent a valuable potential resource for genomic research if impediments to whole exome sequencing of NBS deoxyribonucleic acid (DNA), including the small amount of genomic DNA in NBS material, can be overcome. For instance, genomic analysis of NBS could be used to define allele frequencies of disease-associated variants in local populations, or to conduct prospective or retrospective studies relating genomic variation to disease emergence in pediatric populations over time. In this study, we compared the recovery of variant calls from exome sequences of amplified NBS genomic DNA to variant calls from exome sequencing of non-amplified NBS DNA from the same individuals.

Results

Using a standard alignment-based Genome Analysis Toolkit (GATK), we find 62,000–76,000 additional variants in amplified samples. After application of a unique kmer enumeration and variant detection method (RUFUS), only 38,000–47,000 additional variants are observed in amplified gDNA. This result suggests that roughly half of the amplification-introduced variants identified using GATK may be the result of mapping errors and read misalignment.

Conclusions

Our results show that it is possible to obtain informative, high-quality data from exome analysis of whole genome amplified NBS with the important caveat that different data generation and analysis methods can affect variant detection accuracy, and the concordance of variant calls in whole-genome amplified and non-amplified exomes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1747-2) contains supplementary material, which is available to authorized users.     

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.     

Effects of DNA mass on multiple displacement whole genome amplification and genotyping performance

Background

Whole genome amplification (WGA) promises to eliminate practical molecular genetic analysis limitations associated with genomic DNA (gDNA) quantity. We evaluated the performance of multiple displacement amplification (MDA) WGA using gDNA extracted from lymphoblastoid cell lines (N = 27) with a range of starting gDNA input of 1–200 ng into the WGA reaction. Yield and composition analysis of whole genome amplified DNA (wgaDNA) was performed using three DNA quantification methods (OD, PicoGreen^® and RT-PCR). Two panels of N = 15 STR (using the AmpFlSTR^® Identifiler^® panel) and N = 49 SNP (TaqMan^®) genotyping assays were performed on each gDNA and wgaDNA sample in duplicate. gDNA and wgaDNA masses of 1, 4 and 20 ng were used in the SNP assays to evaluate the effects of DNA mass on SNP genotyping assay performance. A total of N = 6,880 STR and N = 56,448 SNP genotype attempts provided adequate power to detect differences in STR and SNP genotyping performance between gDNA and wgaDNA, and among wgaDNA produced from a range of gDNA templates inputs.

Results

The proportion of double-stranded wgaDNA and human-specific PCR amplifiable wgaDNA increased with increased gDNA input into the WGA reaction. Increased amounts of gDNA input into the WGA reaction improved wgaDNA genotyping performance. Genotype completion or genotype concordance rates of wgaDNA produced from all gDNA input levels were observed to be reduced compared to gDNA, although the reduction was not always statistically significant. Reduced wgaDNA genotyping performance was primarily due to the increased variance of allelic amplification, resulting in loss of heterozygosity or increased undetermined genotypes. MDA WGA produces wgaDNA from no template control samples; such samples exhibited substantial false-positive genotyping rates.

Conclusion

The amount of gDNA input into the MDA WGA reaction is a critical determinant of genotyping performance of wgaDNA. At least 10 ng of lymphoblastoid gDNA input into MDA WGA is required to obtain wgaDNA TaqMan^® SNP assay genotyping performance equivalent to that of gDNA. Over 100 ng of lymphoblastoid gDNA input into MDA WGA is required to obtain optimal STR genotyping performance using the AmpFlSTR^® Identifiler^® panel from wgaDNA equivalent to that of gDNA.

     

Whole genome amplification of buccal cytobrush DNA collected for molecular epidemiology studies.

When cytobrush buccal cell samples have been collected as a genomic DNA (gDNA) source for an epidemiological study, whole genome amplification (WGA) can be critical to maintain sufficient DNA for genotyping. We evaluated REPLI-g WGA using gDNA from two paired cytobrushes (cytobush 'A' kept in a cell lysis buffer, and 'B' dried and kept at room temperature for 3 days, and frozen until DNA extraction) in a pilot study (n=21), and from 144 samples collected by mail in a breast cancer study. WGA success was assessed as the per cent completion/concordance of STR/SNP genotypes. Locus amplification bias was assessed using quantitative PCR of 23 human loci. The pilot study showed > 98% completion but low genotype concordance between cytobrush wgaDNA and paired blood gDNA (82% and 84% for cytobrushes A and B, respectively). Substantial amplification bias was observed with significantly lower human gDNA amplification from cytobrush B than A. Using cytobrush gDNA samples from the breast cancer study (n =20), an independent laboratory demonstrated that increasing template gDNA to the REPLI-g reaction improved genotype performance for 49 SNPs; however, average completion and concordance remained below 90%. To reduce genotype misclassification when cytobrush wgaDNA is used, inclusion of paired gDNA/wgaDNA and/or duplicate wgaDNA samples is critical to monitor data quality.     

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.     

Amplicon Sequencing of Colorectal Cancer: Variant Calling in Frozen and Formalin-Fixed Samples

Next generation sequencing (NGS) is an emerging technology becoming relevant for genotyping of clinical samples. Here, we assessed the stability of amplicon sequencing from formalin-fixed paraffin-embedded (FFPE) and paired frozen samples from colorectal cancer metastases with different analysis pipelines. 212 amplicon regions in 48 cancer related genes were sequenced with Illumina MiSeq using DNA isolated from resection specimens from 17 patients with colorectal cancer liver metastases. From ten of these patients, paired fresh frozen and routinely processed FFPE tissue was available for comparative study. Sample quality of FFPE tissues was determined by the amount of amplifiable DNA using qPCR, sequencing libraries were evaluated using Bioanalyzer. Three bioinformatic pipelines were compared for analysis of amplicon sequencing data. Selected hot spot mutations were reviewed using Sanger sequencing. In the sequenced samples from 16 patients, 29 non-synonymous coding mutations were identified in eleven genes. Most frequent were mutations in TP53 (10), APC (7), PIK3CA (3) and KRAS (2). A high concordance of FFPE and paired frozen tissue samples was observed in ten matched samples, revealing 21 identical mutation calls and only two mutations differing. Comparison of these results with two other commonly used variant calling tools, however, showed high discrepancies. Hence, amplicon sequencing can potentially be used to identify hot spot mutations in colorectal cancer metastases in frozen and FFPE tissue. However, remarkable differences exist among results of different variant calling tools, which are not only related to DNA sample quality. Our study highlights the need for standardization and benchmarking of variant calling pipelines, which will be required for translational and clinical applications.     

Whole genome amplification of buccal cytobrush DNA collected for molecular epidemiology studies

Abstract

When cytobrush buccal cell samples have been collected as a genomic DNA (gDNA) source for an epidemiological study, whole genome amplification (WGA) can be critical to maintain sufficient DNA for genotyping. We evaluated REPLI-g? WGA using gDNA from two paired cytobrushes (cytobush ‘A’ kept in a cell lysis buffer, and ‘B’ dried and kept at room temperature for 3 days, and frozen until DNA extraction) in a pilot study (n=21), and from 144 samples collected by mail in a breast cancer study. WGA success was assessed as the per cent completion/concordance of STR/SNP genotypes. Locus amplification bias was assessed using quantitative PCR of 23 human loci. The pilot study showed > 98% completion but low genotype concordance between cytobrush wgaDNA and paired blood gDNA (82% and 84% for cytobrushes A and B, respectively). Substantial amplification bias was observed with significantly lower human gDNA amplification from cytobrush B than A. Using cytobrush gDNA samples from the breast cancer study (n =20), an independent laboratory demonstrated that increasing template gDNA to the REPLI-g reaction improved genotype performance for 49 SNPs; however, average completion and concordance remained below 90%. To reduce genotype misclassification when cytobrush wgaDNA is used, inclusion of paired gDNA/wgaDNA and/or duplicate wgaDNA samples is critical to monitor data quality.     

Library Preparation and Multiplex Capture for Massive Parallel Sequencing Applications Made Efficient and Easy

During the recent years, rapid development of sequencing technologies and a competitive market has enabled researchers to perform massive sequencing projects at a reasonable cost. As the price for the actual sequencing reactions drops, enabling more samples to be sequenced, the relative price for preparing libraries gets larger and the practical laboratory work becomes complex and tedious. We present a cost-effective strategy for simplified library preparation compatible with both whole genome- and targeted sequencing experiments. An optimized enzyme composition and reaction buffer reduces the number of required clean-up steps and allows for usage of bulk enzymes which makes the whole process cheap, efficient and simple. We also present a two-tagging strategy, which allows for multiplex sequencing of targeted regions. To prove our concept, we have prepared libraries for low-pass sequencing from 100 ng DNA, performed 2-, 4- and 8-plex exome capture and a 96-plex capture of a 500 kb region. In all samples we see a high concordance (>99.4%) of SNP calls when comparing to commercially available SNP-chip platforms.     

Comparison of solution-based exome capture methods for next generation sequencing

Background

Techniques enabling targeted re-sequencing of the protein coding sequences of the human genome on next generation sequencing instruments are of great interest. We conducted a systematic comparison of the solution-based exome capture kits provided by Agilent and Roche NimbleGen. A control DNA sample was captured with all four capture methods and prepared for Illumina GAII sequencing. Sequence data from additional samples prepared with the same protocols were also used in the comparison.

Results

We developed a bioinformatics pipeline for quality control, short read alignment, variant identification and annotation of the sequence data. In our analysis, a larger percentage of the high quality reads from the NimbleGen captures than from the Agilent captures aligned to the capture target regions. High GC content of the target sequence was associated with poor capture success in all exome enrichment methods. Comparison of mean allele balances for heterozygous variants indicated a tendency to have more reference bases than variant bases in the heterozygous variant positions within the target regions in all methods. There was virtually no difference in the genotype concordance compared to genotypes derived from SNP arrays. A minimum of 11× coverage was required to make a heterozygote genotype call with 99% accuracy when compared to common SNPs on genome-wide association arrays.

Conclusions

Libraries captured with NimbleGen kits aligned more accurately to the target regions. The updated NimbleGen kit most efficiently covered the exome with a minimum coverage of 20×, yet none of the kits captured all the Consensus Coding Sequence annotated exons.     

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.     

Variant detection sensitivity and biases in whole genome and exome sequencing

Background

Less than two percent of the human genome is protein coding, yet that small fraction harbours the majority of known disease causing mutations. Despite rapidly falling whole genome sequencing (WGS) costs, much research and increasingly the clinical use of sequence data is likely to remain focused on the protein coding exome. We set out to quantify and understand how WGS compares with the targeted capture and sequencing of the exome (exome-seq), for the specific purpose of identifying single nucleotide polymorphisms (SNPs) in exome targeted regions.

Results

We have compared polymorphism detection sensitivity and systematic biases using a set of tissue samples that have been subject to both deep exome and whole genome sequencing. The scoring of detection sensitivity was based on sequence down sampling and reference to a set of gold-standard SNP calls for each sample. Despite evidence of incremental improvements in exome capture technology over time, whole genome sequencing has greater uniformity of sequence read coverage and reduced biases in the detection of non-reference alleles than exome-seq. Exome-seq achieves 95% SNP detection sensitivity at a mean on-target depth of 40 reads, whereas WGS only requires a mean of 14 reads. Known disease causing mutations are not biased towards easy or hard to sequence areas of the genome for either exome-seq or WGS.

Conclusions

From an economic perspective, WGS is at parity with exome-seq for variant detection in the targeted coding regions. WGS offers benefits in uniformity of read coverage and more balanced allele ratio calls, both of which can in most cases be offset by deeper exome-seq, with the caveat that some exome-seq targets will never achieve sufficient mapped read depth for variant detection due to technical difficulties or probe failures. As WGS is intrinsically richer data that can provide insight into polymorphisms outside coding regions and reveal genomic rearrangements, it is likely to progressively replace exome-seq for many applications.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-247) contains supplementary material, which is available to authorized users.     

Whole Exome Sequencing Identifies a Troponin T Mutation Hot Spot in Familial Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) commonly causes heart failure and shows extensive genetic heterogeneity that may be amenable to newly developed next-generation DNA sequencing of the exome. In this study we report the successful use of exome sequencing to identify a pathogenic variant in the TNNT2 gene using segregation analysis in a large DCM family. Exome sequencing was performed on three distant relatives from a large family with a clear DCM phenotype. Missense, nonsense, and splice variants were analyzed for segregation among the three affected family members and confirmed in other relatives by direct sequencing. A c.517T C>T, Arg173Trp TNNT2 variant segregated with all affected family members and was also detected in one additional DCM family in our registry. The inclusion of segregation analysis using distant family members markedly improved the bioinformatics filtering process by removing from consideration variants that were not shared by all affected subjects. Haplotype analysis confirmed that the variant found in both DCM families was located on two distinct haplotypes, supporting the notion of independent mutational events in each family. In conclusion, an exome sequencing strategy that includes segregation analysis using distant affected relatives within a family represents a viable diagnostic strategy in a genetically heterogeneous disease like DCM.     

Genotyping performance assessment of whole genome amplified DNA with respect to multiplexing level of assay and its period of storage

Whole genome amplification can faithfully amplify genomic DNA (gDNA) with minimal bias and substantial genome coverage. Whole genome amplified DNA (wgaDNA) has been tested to be workable for high-throughput genotyping arrays. However, issues about whether wgaDNA would decrease genotyping performance at increasing multiplexing levels and whether the storage period of wgaDNA would reduce genotyping performance have not been examined. Using the Sequenom MassARRAY iPLEX Gold assays, we investigated 174 single nucleotide polymorphisms for 3 groups of matched samples: group 1 of 20 gDNA samples, group 2 of 20 freshly prepared wgaDNA samples, and group 3 of 20 stored wgaDNA samples that had been kept frozen at -70°C for 18 months. MassARRAY is a medium-throughput genotyping platform with reaction chemistry different from those of high-throughput genotyping arrays. The results showed that genotyping performance (efficiency and accuracy) of freshly prepared wgaDNA was similar to that of gDNA at various multiplexing levels (17-plex, 21-plex, 28-plex and 36-plex) of the MassARRAY assays. However, compared with gDNA or freshly prepared wgaDNA, stored wgaDNA was found to give diminished genotyping performance (efficiency and accuracy) due to potentially inferior quality. Consequently, no matter whether gDNA or wgaDNA was used, better genotyping efficiency would tend to have better genotyping accuracy.     

Saliva as a comparable-quality source of DNA for Whole Exome Sequencing on Ion platforms

BackgroundWhole Exome Sequencing (WES) utilises overlapping fragments prone to sequencing artefacts. Saliva, a non-invasive source of DNA, has been successfully used in WES studies on various platforms. This study explored the validity and quality of DNA sourced from saliva compared to whole blood on an Ion Platform.MethodsDNA was extracted from both sample types from four individuals. WES, performed on the Ion Proton platform was assessed for quality metrics (Depth, Genotyping Quality, etc.) and variant identification for the same source sample-pairs.ResultsNo significant differences in quality metrics were identified between data obtained from whole blood and saliva samples, with several saliva samples demonstrating higher coverage depth. Variants within the same sample, from the two genomic DNA sources, had an average concordance similar to other studies and platforms with different chemistry.ConclusionSaliva-extracted DNA provides comparable sequencing quality to whole blood for WES on Ion Torrent Platforms.     

The impact of post-alignment processing procedures on whole-exome sequencing data

The use of post-alignment procedures has been suggested to prevent the identification of false-positives in massive DNA sequencing data. Insertions and deletions are most likely to be misinterpreted by variant calling algorithms. Using known genetic variants as references for post-processing pipelines can minimize mismatches. They allow reads to be correctly realigned and recalibrated, resulting in more parsimonious variant calling. In this work, we aim to investigate the impact of using different sets of common variants as references to facilitate variant calling from whole-exome sequencing data. We selected reference variants from common insertions and deletions available within the 1K Genomes project data and from databases from the Latin American Database of Genetic Variation (LatinGen). We used the Genome Analysis Toolkit to perform post-processing procedures like local realignment, quality recalibration procedures, and variant calling in whole exome samples. We identified an increased number of variants from the call set for all groups when no post-processing procedure was performed. We found that there was a higher concordance rate between variants called using 1K Genomes and LatinGen. Therefore, we believe that the increased number of rare variants identified in the analysis without realignment or quality recalibration indicated that they were likely false-positives.     

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.     

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Here we outline a next-generation RNA sequencing protocol that enables de novo assemblies and intra-host variant calls of viral genomes collected from clinical and biological sources. The method is unbiased and universal; it uses random primers for cDNA synthesis and requires no prior knowledge of the viral sequence content. Before library construction, selective RNase H-based digestion is used to deplete unwanted RNA — including poly(rA) carrier and ribosomal RNA — from the viral RNA sample. Selective depletion improves both the data quality and the number of unique reads in viral RNA sequencing libraries. Moreover, a transposase-based ''tagmentation'' step is used in the protocol as it reduces overall library construction time. The protocol has enabled rapid deep sequencing of over 600 Lassa and Ebola virus samples-including collections from both blood and tissue isolates-and is broadly applicable to other microbial genomics studies.     

MiST: A new approach to variant detection in deep sequencing datasets

MiST is a novel approach to variant calling from deep sequencing data, using the inverted mapping approach developed for Geoseq. Reads that can map to a targeted exonic region are identified using exact matches to tiles from the region. The reads are then aligned to the targets to discover variants. MiST carefully handles paralogous reads that map ambiguously to the genome and clonal reads arising from PCR bias, which are the two major sources of errors in variant calling. The reduced computational complexity of mapping selected reads to targeted regions of the genome improves speed, specificity and sensitivity of variant detection. Compared with variant calls from the GATK platform, MiST showed better concordance with SNPs from dbSNP and genotypes determined by an exonic-SNP array. Variant calls made only by MiST confirm at a high rate (>90%) by Sanger sequencing. Thus, MiST is a valuable alternative tool to analyse variants in deep sequencing data.     

Are special read alignment strategies necessary and cost-effective when handling sequencing reads from patient-derived tumor xenografts?

Background

Patient-derived tumor xenografts in mice are widely used in cancer research and have become important in developing personalized therapies. When these xenografts are subject to DNA sequencing, the samples could contain various amounts of mouse DNA. It has been unclear how the mouse reads would affect data analyses. We conducted comprehensive simulations to compare three alignment strategies at different mutation rates, read lengths, sequencing error rates, human-mouse mixing ratios and sequenced regions. We also sequenced a nasopharyngeal carcinoma xenograft and a cell line to test how the strategies work on real data.

Results

We found the "filtering" and "combined reference" strategies performed better than aligning reads directly to human reference in terms of alignment and variant calling accuracies. The combined reference strategy was particularly good at reducing false negative variants calls without significantly increasing the false positive rate. In some scenarios the performance gain of these two special handling strategies was too small for special handling to be cost-effective, but it was found crucial when false non-synonymous SNVs should be minimized, especially in exome sequencing.

Conclusions

Our study systematically analyzes the effects of mouse contamination in the sequencing data of human-in-mouse xenografts. Our findings provide information for designing data analysis pipelines for these data.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1172) contains supplementary material, which is available to authorized users.     

A roadmap for high‐throughput sequencing studies of wild animal populations using noninvasive samples and hybridization capture

Large‐scale genomic studies of wild animal populations are often limited by access to high‐quality DNA. Although noninvasive samples, such as faeces, can be readily collected, DNA from the sample producers is usually present in low quantities, fragmented, and contaminated by microorganism and dietary DNAs. Hybridization capture can help to overcome these impediments by increasing the proportion of subject DNA prior to high‐throughput sequencing. Here we evaluate a key design variable for hybridization capture, the number of rounds of capture, by testing whether one or two rounds are most appropriate, given varying sample quality (as measured by the ratios of subject to total DNA). We used a set of 1,780 quality‐assessed wild chimpanzee (Pan troglodytes schweinfurthii) faecal samples and chose 110 samples of varying quality for exome capture and sequencing. We used multiple regression to assess the effects of the ratio of subject to total DNA (sample quality), rounds of capture and sequencing effort on the number of unique exome reads sequenced. We not only show that one round of capture is preferable when the proportion of subject DNA in a sample is above ~2%–3%, but also explore various types of bias introduced by capture, and develop a model that predicts the sequencing effort necessary for a desired data yield from samples of a given quality. Thus, our results provide a useful guide and pave a methodological way forward for researchers wishing to plan similar hybridization capture studies.