{ "id": "epa4vb9gqz", "slug": "targeted-sequencing", "title": "Targeted sequencing", "updated": "2026-10-21", "topic_path": [ { "id": "life", "label": "Life and health", "api_url": "https://www.edgepedia.org/api/v1/topics/life" }, { "id": "life.biology", "label": "Biological foundations", "api_url": "https://www.edgepedia.org/api/v1/topics/life.biology" }, { "id": "life.biology.genetics", "label": "Genetics and genomic reference", "api_url": "https://www.edgepedia.org/api/v1/topics/life.biology.genetics" }, { "id": "life.biology.genetics.genomics_projects_databases", "label": "Genomics, sequencing, and genome resources", "api_url": "https://www.edgepedia.org/api/v1/topics/life.biology.genetics.genomics_projects_databases" }, { "id": "life.biology.genetics.genomics_projects_databases.targeted-sequencing-and-enrichment-methods", "label": "Targeted sequencing and enrichment methods", "api_url": "https://www.edgepedia.org/api/v1/topics/life.biology.genetics.genomics_projects_databases.targeted-sequencing-and-enrichment-methods" } ], "geo": [ { "id": "geo.nongeo.t2001.life.biology.genetics.genomics_projects_databases", "label": "Non-geographic · 2001 to 2020: Genomics, sequencing, and genome resources", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life.biology.genetics.genomics_projects_databases", "path": [ { "id": "geo.nongeo", "label": "Non-geographic", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo" }, { "id": "geo.nongeo.t2001", "label": "Non-geographic · 2001 to 2020", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001" }, { "id": "geo.nongeo.t2001.life", "label": "Life and health", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life" }, { "id": "geo.nongeo.t2001.life.biology", "label": "Biological foundations", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life.biology" }, { "id": "geo.nongeo.t2001.life.biology.genetics", "label": "Genetics and genomic reference", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life.biology.genetics" }, { "id": "geo.nongeo.t2001.life.biology.genetics.genomics_projects_databases", "label": "Genomics, sequencing, and genome resources", "api_url": "https://www.edgepedia.org/api/v1/geo/geo.nongeo.t2001.life.biology.genetics.genomics_projects_databases" } ] } ], "excerpt": "Targeted sequencing is a DNA sequencing approach that enriches defined genomic regions, such as an exome or disease-gene panel, before sequencing, producing fewer data at lower cost than whole-genome sequencing.", "snippet": "Targeted sequencing is a DNA sequencing approach that enriches defined genomic regions, such as an exome or disease-gene panel, before sequencing, producing fewer data at lower cost than whole-genome sequencing.", "node": "life.biology.genetics.genomics_projects_databases.targeted-sequencing-and-enrichment-methods", "markdown": "# Targeted sequencing\n\nTargeted sequencing is a [DNA sequencing](https://www.edgepedia.org/dna-sequencing) approach that enriches a defined set of genomic regions, such as an exome or a disease-gene panel, before sequencing, so that reads and variant calls concentrate on regions of interest instead of the whole genome. Compared with whole-genome sequencing (WGS) and whole-exome sequencing (WES), targeted panels produce fewer data, run faster, cost as little as USD 300 per panel, whereas WGS now costs on the order of a few hundred dollars per 30x research genome (USD 221 on the Ultima UG 100 platform) and WES USD 5,169, and targeted panels impose a lower computational and interpretive burden.[1](https://pmc.ncbi.nlm.nih.gov/articles/PMC9913990/) The two dominant enrichment chemistries are hybridization capture, which uses biotinylated oligonucleotide probes, and amplicon sequencing, which uses PCR.[2](https://www.idtdna.com/pages/technology/next-generation-sequencing/dna-sequencing/targeted-sequencing)\n\n| Key fact | Value |\n|---|---|\n| Enrichment categories | Hybridization capture, PCR/amplicon-based, and selective circularization (including molecular inversion probes)[3](https://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-13-500) • [4](https://idtdevblob.blob.core.windows.net/sitefinity/docs/default-source/application-guide/idt-targeted-sequencing-guide.pdf?sfvrsn=ae151807_4) |\n| Typical panel cost | From USD 300 (panel) to USD 5,169 (WES)[1](https://pmc.ncbi.nlm.nih.gov/articles/PMC9913990/) |\n| Depth for 95% SNP sensitivity | 40x mean on-target for exome-seq vs 14x for WGS[5](https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-15-247.pdf) |\n| Cost vs WGS | Exome sequencing is 4.2x cheaper at 93–94% coding sensitivity and 5.4x cheaper at 98–99%[5](https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-15-247.pdf) |\n| Input DNA | Hybrid capture 1–250 ng for library prep; amplicon 10–100 ng, with Ion AmpliSeq down to 1 ng of FFPE DNA[2](https://www.idtdna.com/pages/technology/next-generation-sequencing/dna-sequencing/targeted-sequencing) • [6](https://www.thermofisher.com/us/en/home/life-science/sequencing/sequencing-learning-center/next-generation-sequencing-information/ngs-basics/targeted-sequencing-approaches.html) |\n| Allele frequency sensitivity | Down to 1% VAF for capture without UMIs vs down to 5% for amplicon panels[2](https://www.idtdna.com/pages/technology/next-generation-sequencing/dna-sequencing/targeted-sequencing) |\n| First diagnostic exome | PNAS 2010, congenital chloride diarrhea diagnosed via SLC26A3 D652N[7](https://www.pnas.org/doi/10.1073/pnas.0910672106) |\n\n## How it works\n\nMost targeted methods enrich the regions of interest before sequencing, and published schemes fall into three categories: hybridization capture, PCR/amplification-based enrichment, and selective circularization, while adaptive sampling instead selects or rejects molecules in real time during nanopore sequencing.[3](https://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-13-500) In hybridization capture, denatured sequencing libraries hybridize to biotinylated probes; solution-phase capture lets probes and library interact in solution, and streptavidin-coated magnetic beads then pull down the hybridized targets.[8](https://pmc.ncbi.nlm.nih.gov/articles/PMC9318977/) Amplicon methods amplify targets directly with primer pairs; many amplicon panels use fewer than 10,000 amplicons, although the Ion AmpliSeq platform multiplexes up to 24,000 primer pairs, whereas capture panel size is virtually unlimited.[2](https://www.idtdna.com/pages/technology/next-generation-sequencing/dna-sequencing/targeted-sequencing) Molecular inversion probes (MIPs) circularize on target through gap-fill and ligation and are used mainly for large-scale genotyping.[4](https://idtdevblob.blob.core.windows.net/sitefinity/docs/default-source/application-guide/idt-targeted-sequencing-guide.pdf?sfvrsn=ae151807_4) The trade-offs are consistent: capture produces more off-target reads from adapter cross-hybridization, while amplicon enrichment gives higher on-target rates but lower uniformity because of PCR bias and possible primer-site dropouts.[4](https://idtdevblob.blob.core.windows.net/sitefinity/docs/default-source/application-guide/idt-targeted-sequencing-guide.pdf?sfvrsn=ae151807_4) A hybrid design, Linked Target Capture, links capture probes to universal PCR primers so that a single-day combined target-capture-PCR reaction replaces multi-day workflows across panel sizes from 100 bp to more than 10 Mbp.[9](https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0208283)\n\n## How it is done\n\nA capture panel follows a two-day workflow: prepare sequencing libraries, hybridize probes (16 hours at 70 °C in the Twist protocol, which supports up to 8-plex multiplex hybridization), bind hybridized targets to streptavidin beads, post-capture PCR amplify, purify, run QC, and sequence.[10](https://8494339.fs1.hubspotusercontent-na1.net/hubfs/8494339/Protocol_NGS_TargetEnrichmentStandardHybridization_v1Protocol_2FEB22_Rev4.0.pdf) Keeping the reaction at 70 °C until bead binding matters: cooling to room temperature for under five minutes raises off-target binding by 10–20%.[10](https://8494339.fs1.hubspotusercontent-na1.net/hubfs/8494339/Protocol_NGS_TargetEnrichmentStandardHybridization_v1Protocol_2FEB22_Rev4.0.pdf) Capture libraries can be multiplexed before enrichment; amplicon samples are enriched individually and multiplexed immediately before sequencing.[4](https://idtdevblob.blob.core.windows.net/sitefinity/docs/default-source/application-guide/idt-targeted-sequencing-guide.pdf?sfvrsn=ae151807_4) Coverage planning uses simple arithmetic: required mean coverage equals desired coverage divided by mean normalized coverage; for a 62 Mb target at 50x mean coverage and 0.65 enrichment efficiency, about 4.8 Gb of mapped sequence is needed.[11](https://www.illumina.com/documents/products/technotes/technote_optimizing_coverage_for_targeted_resequencing.pdf) Detailed capture and bioinformatics pipelines for the Agilent SureSelect Human All Exon 50 Mb and Roche NimbleGen SeqCap EZ Exome platforms are published as laboratory protocols.[12](https://currentprotocols.onlinelibrary.wiley.com/doi/10.1002/0471142727.mb0712s102)\n\n## Origin\n\nThe precursor work is array-based: Hodges and colleagues reported genome-wide in situ exon capture for selective resequencing in [Nature Genetics](https://www.edgepedia.org/nature-genetics) in 2007,[13](https://doi.org/10.1038/ng.2007.42) and Albert and colleagues reported direct selection of human genomic loci by microarray hybridization in [Nature Methods](https://www.edgepedia.org/nature-methods) the same year.[14](https://doi.org/10.1038/nmeth1111) In 2009, Ng and colleagues reported targeted capture and massively parallel sequencing of 12 human exomes in Nature, enriching coding sequences from 10 micrograms of DNA on two Agilent 244K microarrays; the run generated an average of 6.4 Gb of mappable sequence per individual, about 20-fold less than WGS on the same platform, with 49% of reads on target and 96.3% of targeted bases covered sufficiently for variant calling at 8x or more.[15](https://doi.org/10.1038/nature08250) Also in 2009, Gnirke and colleagues reported solution hybrid selection with ultra-long oligonucleotides,[16](https://doi.org/10.1038/nbt.1523) Tewhey and colleagues reported microdroplet-based PCR enrichment,[17](https://doi.org/10.1038/nbt.1583) and Turner and colleagues reported library-free MIP exon capture across 16 genomes.[18](https://doi.org/10.1038/nmeth.f.248) A PNAS study coupled Roche/NimbleGen exome capture to the Illumina platform and diagnosed congenital chloride diarrhea (homozygous SLC26A3 D652N); its authors estimated that exon capture reduces the cost of detecting exonic mutations by a factor of 10 to 20 versus WGS.[7](https://www.pnas.org/doi/10.1073/pnas.0910672106)\n\n## Variants\n\nThe IDT xGen Exome Research Panel v2 uses 415,115 individually synthesized probes over a 34 Mb target region covering 19,433 genes.[2](https://www.idtdna.com/pages/technology/next-generation-sequencing/dna-sequencing/targeted-sequencing) The Illumina TruSeq Exome kit targets 62 Mb with 95mer probes.[11](https://www.illumina.com/documents/products/technotes/technote_optimizing_coverage_for_targeted_resequencing.pdf) Ion AmpliSeq can multiplex up to 24,000 PCR primer pairs in one reaction and enriches from as little as 1 ng of low-quality DNA or RNA, including FFPE and circulating DNA.[6](https://www.thermofisher.com/us/en/home/life-science/sequencing/sequencing-learning-center/next-generation-sequencing-information/ngs-basics/targeted-sequencing-approaches.html) Anchored multiplex PCR (AMP), used in the ArcherDX FusionPlex kits, primes from a known exon into unknown sequence, so it identifies gene fusions regardless of the fusion partner.[19](https://www.jove.com/t/59895/oncogenic-gene-fusion-detection-using-anchored-multiplex-polymerase) In a three-method comparison on FFPE DNA, a hybridization SureSeq panel detected 24 of 24 expected mutations versus 20 for [Fluidigm](https://www.edgepedia.org/fluidigm) microfluidic PCR and 18 for Ion AmpliSeq; across four exome methods, hybrid capture outperformed amplicon-based methods on library complexity, uniformity, and analytical sensitivity.[8](https://pmc.ncbi.nlm.nih.gov/articles/PMC9318977/) A 2024 comparison of four exome kits found 10x coverage above 97.5% of targets at 50 M reads and fold-80 uniformity metrics now in the 1.4–1.6 range versus over 2 for earlier kits.[20](https://link.springer.com/article/10.1186/s12864-024-11196-z) Long-read platforms add enrichment methods that do not use probes or primers. [Adaptive sampling](https://www.edgepedia.org/adaptive-sampling), reported by Loose, Malla, and Stout in 2016 as real-time selective sequencing on nanopores and implemented at scale by the readfish software from Payne and colleagues in 2020, rejects off-target molecules mid-read on the sequencer itself.[21](https://doi.org/10.1038/nmeth.3930) • [22](https://doi.org/10.1038/s41587-020-00746-x) Cas9-based enrichment excises targets in solution; an affinity-based Cas9-mediated method (ACME), reported by Iyer and colleagues in 2022, achieved 2- to 25-fold higher target coverage than the earlier nCATS protocol and captured targets up to 100 kb.[23](https://doi.org/10.1101/2022.02.03.478550) • [24](https://genome.cshlp.org/content/34/11/1701.long) The commercial nCATS kit (SQK-CS9109) was discontinued in early 2024, and improved bead-based variants report 90% on-target yield and 51,000x coverage on a 10 kb bacterial target, a 353-fold increase over WGS.[24](https://genome.cshlp.org/content/34/11/1701.long) • [25](https://doi.org/10.1016/j.crmeth.2026.101410) Long-read hybridization capture methods such as t-nanoEM achieved 36–38x mean bait coverage from 14–26 ng of clinical tumor DNA with 93–94% on-target rate.[26](https://www.cell.com/cell-reports-methods/fulltext/S2667-2375%2825%2900251-6?uuid=uuid%3Ae185d276-2501-4a17-a5f1-6c969f20aed3)\n\n## Applications\n\nFor liquid biopsy, Illumina TruSight Oncology 500 ctDNA uses hybrid capture over 523 genes and shows greater than 99% sensitivity for SNVs and greater than 98% for indels with 20 ng ctDNA input; Roche AVENIO ctDNA kits span 17–197 genes across 192 kb.[1](https://pmc.ncbi.nlm.nih.gov/articles/PMC9913990/) In a head-to-head ctDNA comparison, the hybrid-capture Avenio panel captured 99% of targeted regions versus 85% for amplicon QIAseq, with analytical sensitivity of 92.3% versus 86.4% at VAF of 20% or less and 75.0% versus 53.8% at VAF of 5% or less, at the cost of a 3-day workflow versus 1 day.[8](https://pmc.ncbi.nlm.nih.gov/articles/PMC9318977/) For minimal residual disease, capture-region design determines how many mutations can be tracked: the MRDtarget design method gave four or more trackable mutation sites in 97% of patients, and with 30 ng and 60 ng cfDNA input and four tracked mutations the modeled limit of detection reaches 0.02% and 0.01% VAF.[27](https://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1013443) RNA-based AMP panels are used for oncogenic fusion detection in clinical solid tumor specimens.[19](https://www.jove.com/t/59895/oncogenic-gene-fusion-detection-using-anchored-multiplex-polymerase) Unique molecular identifiers on adapters mark original molecules, enabling PCR duplicate removal and in silico error correction; with integrated UMIs, one single-day capture workflow detected variants down to 0.25% abundance.[2](https://www.idtdna.com/pages/technology/next-generation-sequencing/dna-sequencing/targeted-sequencing) • [9](https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0208283) In 33 hereditary cancer genomes, target adaptive sampling long-read sequencing (TAS-LRS) achieved a median on-target depth of 21.9x with 10.4-fold median enrichment, SNV recall of 98.8% and precision of 98.2% against high-coverage short-read WGS, and newly identified SVA insertions affecting APC in two familial adenomatous polyposis patients.[28](https://doi.org/10.1038/s41525-024-00394-z) A 2025 study found adaptive sampling suitable for germline cancer-predisposition analysis, improving characterization of large-scale rearrangements and detecting SNVs at a minimum coverage of 10x.[29](https://journal.hep.com.cn/ctm/EN/10.1002/ctm2.70138)\n\n## Limitations and alternatives\n\nDepth drives sensitivity. Exome-seq reaches 95% [SNP detection](https://www.edgepedia.org/snp-detection) sensitivity at a mean on-target depth of 40 reads, whereas WGS needs only 14; heterozygous sensitivity in one exome study rose from 78.6% at 10x to roughly 100% at 30x or greater.[5](https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-15-247.pdf) • [7](https://www.pnas.org/doi/10.1073/pnas.0910672106) Low input reduces both depth and sensitivity: an optimized SureSelect protocol achieved over 700–800x mean depth from 25 ng of DNA, but at 6.25 ng only about 300x was reached, SNV sensitivity at MAF of 15% or more stayed above 96% while sensitivity at MAF of 10% or less fell to about 90% or below, and the fraction of targets covered above 500x dropped from 80.1% to 22.7%.[30](https://www.nature.com/articles/srep26732) The main structural failure mode is mappability, not GC bias: short reads leave 478 ± 37 kb (WGS) and 751 ± 34 kb (best WES) of coding sequence unreachable, about 1 Mb of the exome can be skipped in low-mappability regions such as pseudogenes and tandem repeats, and for well-designed kits GC content has little effect on coverage.[31](https://www.nature.com/articles/s41598-020-59026-y) • [20](https://link.springer.com/article/10.1186/s12864-024-11196-z) Comparing WES with PCR-free WGS at 65x, WGS completely covered 100.00% of uniquely mappable RefSeq coding exons at 13x or more versus 98.15% for WES at 154x, and WES may miss 0.42% of currently known exonic disease mutations detectable by WGS.[32](https://link.springer.com/article/10.1007/s00439-015-1631-9) Published cost models disagree on the tipping point: one benchmark puts exome sequencing 4.2x to 5.4x cheaper than WGS at comparable coding sensitivity, with cost parity requiring per-lane sequencing costs to fall to 15–20% of then-current levels,[5](https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-15-247.pdf) while the completeness comparison above argues WGS is the more comprehensive choice for Mendelian diagnostics.[32](https://link.springer.com/article/10.1007/s00439-015-1631-9) Amplicon panels have their own failure modes: primer-target mismatches risk amplification failure, and coverage suffers at low viral load or with poor-quality samples, though amplicon enrichment distinguishes homologous regions such as PTEN versus its PTENP1 pseudogene better than capture probes, which may fail to hybridize over variant sites.[1](https://pmc.ncbi.nlm.nih.gov/articles/PMC9913990/) • [6](https://www.thermofisher.com/us/en/home/life-science/sequencing/sequencing-learning-center/next-generation-sequencing-information/ngs-basics/targeted-sequencing-approaches.html) Among long-read options, input requirements constrain the choice: adaptive sampling needs several hundred nanograms of DNA and Cas9 enrichment several micrograms, and reviewers describe adaptive sampling as potentially the lowest-cost targeted enrichment with the fastest time-to-answer, subject to read-length limits of 8–15 kb and substantial computational resources.[24](https://genome.cshlp.org/content/34/11/1701.long) • [26](https://www.cell.com/cell-reports-methods/fulltext/S2667-2375%2825%2900251-6?uuid=uuid%3Ae185d276-2501-4a17-a5f1-6c969f20aed3)\n\n## References\n\n1. [Targeted Sequencing Approach and Its Clinical Applications for the Molecular Diagnosis of Human Diseases](https://pmc.ncbi.nlm.nih.gov/articles/PMC9913990/)\n2. [Targeted next generation sequencing (NGS) | IDT](https://www.idtdna.com/pages/technology/next-generation-sequencing/dna-sequencing/targeted-sequencing)\n3. [Accurate variant detection across non-amplified and whole genome amplified DNA using targeted next generation sequencing](https://bmcgenomics.biomedcentral.com/articles/10.1186/1471-2164-13-500)\n4. [IDT Targeted sequencing guide (NGS-10161-AG 07/19)](https://idtdevblob.blob.core.windows.net/sitefinity/docs/default-source/application-guide/idt-targeted-sequencing-guide.pdf?sfvrsn=ae151807_4)\n5. [Comparison of exome-seq and whole genome sequencing for SNP detection sensitivity (BMC Bioinformatics)](https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/1471-2105-15-247.pdf)\n6. [Targeted Sequencing Approaches for NGS | Thermo Fisher Scientific](https://www.thermofisher.com/us/en/home/life-science/sequencing/sequencing-learning-center/next-generation-sequencing-information/ngs-basics/targeted-sequencing-approaches.html)\n7. [Genetic diagnosis by whole exome capture and massively parallel DNA sequencing](https://www.pnas.org/doi/10.1073/pnas.0910672106)\n8. [Target Enrichment Approaches for Next-Generation Sequencing Applications in Oncology](https://pmc.ncbi.nlm.nih.gov/articles/PMC9318977/)\n9. [Rapid and highly-specific generation of targeted DNA sequencing libraries enabled by linking capture probes with universal primers (Linked Target Capture)](https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0208283)\n10. [Twist Target Enrichment Standard protocol](https://8494339.fs1.hubspotusercontent-na1.net/hubfs/8494339/Protocol_NGS_TargetEnrichmentStandardHybridization_v1Protocol_2FEB22_Rev4.0.pdf)\n11. [Optimizing Coverage for Targeted Resequencing (Illumina TruSeq Exome technical note)](https://www.illumina.com/documents/products/technotes/technote_optimizing_coverage_for_targeted_resequencing.pdf)\n12. [Exome Sequencing by Targeted Enrichment (Current Protocols)](https://currentprotocols.onlinelibrary.wiley.com/doi/10.1002/0471142727.mb0712s102)\n13. [Emily Hodges and colleagues (2007). Genome-wide in situ exon capture for selective resequencing. Nature Genetics.](https://doi.org/10.1038/ng.2007.42)\n14. [Thomas J Albert and colleagues (2007). Direct selection of human genomic loci by microarray hybridization. Nature Methods.](https://doi.org/10.1038/nmeth1111)\n15. [Sarah B. Ng and colleagues (2009). Targeted capture and massively parallel sequencing of 12 human exomes. Nature.](https://doi.org/10.1038/nature08250)\n16. [Andreas Gnirke and colleagues (2009). Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing. Nature Biotechnology.](https://doi.org/10.1038/nbt.1523)\n17. [Ryan Tewhey and colleagues (2009). Microdroplet-based PCR enrichment for large-scale targeted sequencing. Nature Biotechnology.](https://doi.org/10.1038/nbt.1583)\n18. [Emily H Turner and colleagues (2009). Massively parallel exon capture and library-free resequencing across 16 genomes. Nature Methods.](https://doi.org/10.1038/nmeth.f.248)\n19. [Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing](https://www.jove.com/t/59895/oncogenic-gene-fusion-detection-using-anchored-multiplex-polymerase)\n20. [Comparative evaluation of four exome enrichment solutions in 2024 (BMC Genomics)](https://link.springer.com/article/10.1186/s12864-024-11196-z)\n21. [Matthew Loose, Sunir Malla, Michael Stout (2016). Real-time selective sequencing using nanopore technology. Nature Methods.](https://doi.org/10.1038/nmeth.3930)\n22. [Alexander Payne and colleagues (2020). Readfish enables targeted nanopore sequencing of gigabase-sized genomes. Nature Biotechnology.](https://doi.org/10.1038/s41587-020-00746-x)\n23. [Shruti V Iyer and colleagues (2022). ACME: an Affinity-based Cas9 Mediated Enrichment method for targeted nanopore sequencing. bioRxiv (Cold Spring Harbor Laboratory).](https://doi.org/10.1101/2022.02.03.478550)\n24. [Leveraging the power of long reads for targeted sequencing (Genome Research review, 2024)](https://genome.cshlp.org/content/34/11/1701.long)\n25. [Improved Cas9-targeted nanopore sequencing facilitates ultra-deep analysis of genomic variation (Cell Reports Methods, 2026)](https://doi.org/10.1016/j.crmeth.2026.101410)\n26. [S2667 2375(25)00251 6 (cell.com)](https://www.cell.com/cell-reports-methods/fulltext/S2667-2375%2825%2900251-6?uuid=uuid%3Ae185d276-2501-4a17-a5f1-6c969f20aed3)\n27. [MRDtarget: A heuristic Gaussian approach for optimizing targeted capture regions to enhance Minimal Residual Disease detection](https://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1013443)\n28. [Wataru Nakamura and colleagues (2024). Assessing the efficacy of target adaptive sampling long-read sequencing through hereditary cancer patient genomes. npj Genomic Medicine.](https://doi.org/10.1038/s41525-024-00394-z)\n29. [Nanopore adaptive sampling accurately detects nucleotide variants and improves the characterization of large-scale rearrangement for the diagnosis of cancer predisposition (Clinical and Translational Medicine, 2025)](https://journal.hep.com.cn/ctm/EN/10.1002/ctm2.70138)\n30. [Minimal amount of starting DNA for Agilent's hybrid capture-based targeted MPS (Scientific Reports)](https://www.nature.com/articles/srep26732)\n31. [Systematic dissection of biases in whole-exome and whole-genome sequencing reveals major determinants of coding sequence coverage](https://www.nature.com/articles/s41598-020-59026-y)\n32. [Clinical sequencing: is WGS the better WES?](https://link.springer.com/article/10.1007/s00439-015-1631-9)\n\n---\n*Topic: Encyclopedia › Life and health › Biological foundations › Genetics and genomic reference › Genomics, sequencing, and genome resources › Targeted sequencing and enrichment methods*\n\n*Initially written Sep 29, 2026 · Reviewed: Sep 30, 2026 · Edited: Oct 15, 2026; Oct 21, 2026 · Last review: Sep 30, 2026*\n\n*Copyright 2026 EdgeChat AI, a subsidiary of Biostate AI.*\n\nLicense: Edgepedia Community License 1.0, https://www.edgepedia.org/edgepedia/license\n", "same_as": [], "url": "https://www.edgepedia.org/targeted-sequencing", "markdown_url": "https://www.edgepedia.org/targeted-sequencing.md", "license": { "name": "Edgepedia Community License 1.0", "url": "https://www.edgepedia.org/edgepedia/license", "summary": "Free with credit, commercial use included. AI training is open to everyone. For other uses, organizations over USD 100M in revenue or 100M monthly users license separately.", "spdx": "LicenseRef-Edgepedia-Community-1.0" }, "credit": "\"Targeted sequencing\", Edgepedia (EdgeChat), https://www.edgepedia.org/targeted-sequencing. Edgepedia Community License 1.0.", "credit_md": "\"[Targeted sequencing](https://www.edgepedia.org/targeted-sequencing)\", Edgepedia (EdgeChat), [https://www.edgepedia.org/targeted-sequencing](https://www.edgepedia.org/targeted-sequencing). [Edgepedia Community License 1.0](https://www.edgepedia.org/edgepedia/license).", "credit_html": "\"Targeted sequencing\", Edgepedia (EdgeChat), https://www.edgepedia.org/targeted-sequencing. Edgepedia Community License 1.0.", "speakable": "Targeted sequencing is a DNA sequencing approach that enriches defined genomic regions, such as an exome or disease-gene panel, before sequencing, producing fewer data at lower cost than whole-genome sequencing." }