An Updated Guide to Illumina Library Preparation: Kits, Methods, and Strategies for Challenging Sample Types

Library preparation is the single most important determinant of sequencing success. Regardless of how powerful the sequencing platform or how sophisticated the data analysis pipeline, a poorly prepared library will produce unusable data, wasted flow cell capacity, and lost time.

But in 2026, the challenge for most researchers is no longer understanding the basic steps of library preparation. The challenge is choosing the right method from an increasingly crowded field of options—PCR-based vs. PCR-free, fragmentation-based vs. tagmentation-based, and kits optimized for specific sample types such as FFPE tissues, circulating cell-free DNA (cfDNA), and ultra-low-input samples.

This guide provides a practical framework for making those choices. It covers the major library preparation strategies and kits available for Illumina sequencing, with a focus on selecting the right approach for your sample type, project scale, and data quality requirements.

Why Library Preparation Choices Matter More Than Ever

Library preparation accounts for the majority of variability in NGS workflows. A well-designed library consistently produces high-quality data; a poorly designed one can fail even on the best sequencing instrument. As sequencing costs have dropped, library preparation has become a proportionally larger share of total project cost, making the choice of method a significant financial decision.

Three key factors drive the choice of library preparation method:

• Sample quality and quantity: High-quality genomic DNA (>1 µg) allows access to PCR-free methods that minimize bias. Low-quality or low-quantity samples (FFPE, cfDNA, single cells) require specialized kits with repair enzymes or ultra-low-input protocols. The single most common cause of library failure is degraded input material that was not identified until after the library was quantified—which is why investing in rigorous up-front QC pays for itself many times over.
• Project type: Whole-genome sequencing (WGS) demands low experimental bias and consistent coverage. Targeted sequencing requires high capture efficiency. Amplicon sequencing relies on balanced multiplex primers. Each application type places different demands on the library preparation method, meaning there is no single "best" kit—only the best kit for a given combination of sample and application.
• Throughput and turnaround: Some methods can go from DNA to ready-to-sequence library in under 3 hours; others require 6–8 hours. For large batches, automation compatibility becomes an important factor. A lab processing 96 samples per week will have different throughput requirements than one processing 16 samples per month.

Beyond these factors, a fourth consideration is growing in importance: library complexity. A library with high complexity—meaning it represents the original genome or transcriptome with minimal duplication—produces higher-quality variant calls, more reliable expression measurements, and more reproducible results across batches. Library preparation methods that preserve complexity (PCR-free, low-cycle PCR, and optimized tagmentation protocols) are increasingly favored for projects where data quality is the primary concern.

For researchers planning their first NGS project or looking to optimize an existing pipeline, understanding these trade-offs is essential. Comprehensive NGS services cover the full range of library preparation methods, making it possible to select the optimal approach for each project's specific requirements.

The Standard Workflow in Brief

The core steps of Illumina library preparation remain consistent across most methods, though the specific implementation varies:

1. Fragmentation: DNA is broken into target-size fragments (typically 200–800 bp) by mechanical shearing, enzymatic digestion, or tagmentation.
2. End repair and A-tailing: Fragment ends are blunted, phosphorylated, and A-tailed to enable adapter ligation.
3. Adapter ligation: Sequencing adapters containing P5/P7 sequences, index barcodes, and sequencing primer binding sites are ligated to the fragments.
4. Size selection: Fragments outside the target size range are removed, typically using SPRI magnetic beads.
5. Library amplification (optional): PCR amplification adds sufficient material for sequencing. PCR-free methods skip this step entirely.
6. Library QC: The final library is quantified and quality-checked using qPCR, fluorometric assays, and capillary electrophoresis (Bioanalyzer or TapeStation).

This overview is intentionally brief because the detailed mechanics of each step are already covered in existing resources. The focus of this guide is on choosing between the available methods, not on the step-by-step protocol.

Figure 1. Library preparation decision framework — from sample type and project goals to optimal preparation strategy
Caption: Decision framework guiding researchers from sample type, input quantity, and project goals to the optimal library preparation strategy across PCR-based, PCR-free, and tagmentation methods.

Choosing the Right Library Prep Strategy — PCR-Based, PCR-Free, or Tagmentation

Every Illumina library preparation method falls into one of three technical categories. Understanding the differences between these categories is the first step in selecting the right kit for your project.

PCR-based fragmentation + ligation: DNA is fragmented by mechanical shearing (Covaris) or enzymatic digestion, followed by end repair, A-tailing, adapter ligation, and PCR amplification. This is the most flexible and widely used approach. It works well across a broad range of input amounts (0.1 ng to 1 µg) and sample types. The trade-off is that PCR amplification can introduce bias in GC-rich regions and increase duplication rates. Kits using this strategy typically require 4–8 hours for complete workflow.

PCR-free fragmentation + ligation: The same workflow as above, but PCR amplification is omitted. This eliminates PCR-introduced bias and produces the most uniform genome coverage, making it the gold standard for WGS applications. The limitation is that PCR-free methods require higher input DNA (typically >100 ng to >1 µg depending on the kit) because there is no amplification step to increase library yield.

Tagmentation (transposase-based): A modified transposase enzyme simultaneously fragments DNA and inserts adapter sequences in a single reaction step. This reduces hands-on time and input requirements significantly—some tagmentation kits work with as little as 1 ng of input DNA. The trade-off is that tagmentation methods can introduce sequence-dependent bias, particularly in low-GC regions, and may produce libraries with a narrower insert size distribution.

Selection framework: Based on the analysis above, a practical guide for method selection can be summarized as follows:

• High-quality DNA >1 µg for WGS → PCR-free fragmentation + ligation produces the most uniform coverage with the lowest duplication rates
• Input 10–100 ng, need fast turnaround → Tagmentation-based methods are the most efficient, reducing library prep time by roughly half
• FFPE, cfDNA, or other challenging samples → PCR-based fragmentation + ligation with repair enzymes or specialized ultra-low-input kits
• Flexible, multi-purpose lab processing diverse sample types → PCR-based fragmentation + ligation offers the widest input range and application compatibility

Figure 2. Three library preparation strategies — PCR-based fragmentation + ligation, PCR-free, and tagmentation
Caption: Comparison of the three major Illumina library preparation strategies showing differences in fragmentation mechanism, amplification requirement, input DNA range, and best-fit applications for each approach.

Laboratory workflow considerations: In addition to the technical factors above, practical laboratory logistics should inform the choice. PCR-based fragmentation + ligation kits produce consistent results across a wide range of sample types, making them ideal for core facilities or service labs that receive diverse sample types. Tagmentation methods are better suited to labs that process a consistent sample type at scale and prioritize speed. PCR-free methods are most appropriate for labs with reliable access to high-quality, high-quantity DNA and a specific need for the bias reduction they provide.

Comparing Available Library Prep Kits by Key Parameters

Several commercially available kits implement each of the three strategies above. The choice between them depends on the specific requirements of your project.

Kit Type	Method	Input Range	Typical Time	Best Application
PCR-Free (standard fragmentation + ligation)	Sonicate + ligation, no PCR	100 ng – 1 µg	~6 hr	WGS where minimal bias is critical; high-quality DNA
PCR-Based (standard fragmentation + ligation)	Sonicate/enzymatic + ligation + PCR	0.1 ng – 1 µg	~4–6 hr	Broadest application range; flexible input; FFPE with repair
Tagmentation-based	Transposase fragmentation + adapter insertion	1–50 ng	~3 hr	Low input; rapid workflow; bacteria, viral, small genomes
Ultra-low-input / cfDNA-optimized	Stem-loop or specialized ligation	0.05–50 ng	~2.5–3 hr	cfDNA, liquid biopsy, single-cell, sub-nanogram inputs

Practical selection advice: For labs processing a diverse range of sample types, a PCR-based fragmentation + ligation kit with a broad input range is the most versatile choice, covering everything from high-quality gDNA to FFPE, cfDNA, and RNA-seq libraries. For labs focused exclusively on high-quality DNA WGS, a PCR-free approach provides the best data quality with the lowest duplication rates. For labs prioritizing speed and low input on simple sample types, tagmentation is an excellent option that can reduce hands-on time by up to 50%. For projects involving cfDNA or other ultra-low-input applications, a kit specifically optimized for those inputs should be the first consideration—using a standard PCR-based kit on cfDNA frequently leads to adapter dimer contamination because the short insert fragments do not provide sufficient separation from adapter-adapter ligation products.

Cost considerations: The cost per library varies across the three strategies. PCR-based fragmentation + ligation kits typically have the highest per-reaction cost, while tagmentation kits are often lower. The per-library kit cost, however, should be weighed against the cost of a failed sequencing run. A small savings on library reagents is insignificant if it produces a library that clusters poorly, yields low data output, or introduces bias that compromises biological interpretation. The total project cost—not the per-library reagent cost—is the relevant economic metric.

Special Sample Type 1 — FFPE and Degraded DNA

FFPE-derived DNA presents unique challenges for library preparation. Formalin fixation causes crosslinking that fragments DNA and introduces base modifications—most notably, cytosine deamination (C→T) that can appear as apparent mutations in sequencing data.

Successful FFPE library preparation requires two specific adaptations:

1. Damage repair before library construction: A pre-library repair step using an enzyme mix containing uracil-DNA glycosylase (UDG) and other damage-repair enzymes removes deaminated cytosines and repairs nicks. This step is essential for eliminating C→T artifacts that would otherwise appear as false-positive variants.
2. Input flexibility and reduced cycle count: FFPE DNA is typically fragmented to an average size of 200–400 bp, which is already within the target range for most Illumina libraries. The emphasis should be on minimizing additional cycles of amplification to avoid further bias. PCR-based fragmentation + ligation kits with repair modules are the recommended approach.

FFPE libraries typically show a broader insert size distribution and lower complexity than libraries from high-quality DNA. A Bioanalyzer trace showing a broad peak from 150–600 bp, rather than a sharp peak, is normal for FFPE samples. The key QC metric is not peak shape but the presence of a clear library peak above any adapter dimer signal.

Figure 3. FFPE DNA Bioanalyzer trace comparison — degraded FFPE DNA versus high-quality genomic DNA library traces
Caption: Comparative Bioanalyzer electrophoretogram showing the broad peak shape typical of FFPE-derived DNA libraries versus the sharp, well-defined peak of high-quality genomic DNA libraries.

Special Sample Type 2 — cfDNA and Ultra-Low-Input Samples

Circulating cell-free DNA (cfDNA) is present in plasma at very low concentrations (typically 1–50 ng per mL of blood) and consists of fragments averaging ~167 bp—the length of DNA wrapped around a single nucleosome. These characteristics require a fundamentally different approach to library preparation than genomic DNA.

Key considerations for cfDNA library preparation:

• Adapter dimer control: Because cfDNA fragments are short (~167 bp + adapters = ~300 bp final library), any adapter dimer contamination (~120 bp) is within the same size range and cannot be effectively removed by size selection. Kits with stem-loop or bubble-type adapters reduce dimer formation more effectively than standard Y-adapters for cfDNA applications.
• PCR cycle optimization: cfDNA input is too low for PCR-free methods, so amplification is required. However, each additional PCR cycle risks introducing bias and duplicates. The optimal balance is typically 8–12 cycles, calibrated to produce sufficient library yield without exceeding 10–15% duplication rates.
• Index hopping sensitivity: Because every molecule in a cfDNA library is valuable, index hopping that misassigns reads between samples is particularly damaging. Unique dual indexes (UDI) are strongly recommended for cfDNA multiplexed projects.

The cfDNA library profile on a Bioanalyzer should show a peak at approximately 280–330 bp (167 bp insert + 120–140 bp adapter). A second peak at 120–140 bp indicates adapter dimer contamination and suggests the need for protocol optimization.

Figure 4. cfDNA library Bioanalyzer trace — typical library peak and adapter dimer contamination
Caption: Bioanalyzer trace of a cfDNA library showing the expected library peak at ~280–330 bp and a smaller adapter dimer peak at ~120–140 bp that indicates contamination requiring protocol optimization.

Comparison: cfDNA vs. standard gDNA library preparation: The fundamental differences between cfDNA and gDNA library prep extend beyond input quantity. Because cfDNA fragments are already short and have characteristic ends (5-phosphate, 3-hydroxyl groups from nucleosomal cleavage), the fragmentation step is omitted entirely. The library preparation workflow starts directly with end repair and A-tailing, followed by adapter ligation. The cleanup strategy also differs: SPRI bead ratios must be carefully optimized to retain the short cfDNA fragments while removing adapter dimers, which are only ~40–60 bp shorter than the target library fragments. A double-sided bead cleanup—first at 0.6–0.8× to remove large fragments, then at 1.5–1.8× to capture the cfDNA-range fragments—is a common and effective approach.

WGS vs. Targeted Enrichment vs. Amplicon — How Library Prep Differs by Application

The library preparation workflow changes depending on what comes after it.

Application	Prep Goal	Key QC Metric	Input Requirement
Whole-genome sequencing	Uniform coverage with minimal bias	Insert size distribution, duplication rate	100 ng – 1 µg; PCR-free preferred
Targeted enrichment (WES, panels)	Efficient capture of target regions	% on-target, coverage uniformity	10–200 ng
Amplicon sequencing	Balanced amplification across targets	Read balance across amplicons, primer dimer	1–100 ng

For WGS library preparation, the priority is minimizing experimental bias. PCR-free methods are preferred when input quantity allows. The critical QC checkpoints are fragment size distribution (a tight peak at the target size) and duplication rate (should be <10% for PCR-free, <15% for PCR-based methods).

For targeted enrichment library preparation, the initial library is built the same way as a WGS library, but an additional hybridization-capture step is added to pull down target regions. The critical QC metric shifts from coverage uniformity to capture efficiency (% of reads mapping to target regions). Library preparation for targeted enrichment must produce enough complexity to avoid duplicate reads dominating the on-target data after capture.

For amplicon-based library preparation, the library is generated by multiplex PCR rather than by fragmentation and adapter ligation. The primary challenge is balancing primer performance across all targets to avoid dropout of specific regions. QC focuses on the evenness of coverage across the target set—a standard metric is the percentage of amplicons within 0.2×–2× of the mean coverage depth.

A note on RNA library preparation: While the primary focus of this guide is DNA library preparation, RNA-seq library prep follows a different workflow. Instead of fragmentation before adapter ligation, RNA is first converted to cDNA through reverse transcription, then fragmented (or fragmented before reverse transcription, depending on the protocol). The adapter ligation and amplification steps are similar to DNA library prep, but strand-specificity must be preserved if the experimental design requires distinguishing the original RNA strand from its complement.

Figure 5. WGS library prep vs targeted enrichment library prep vs amplicon library prep — workflow comparison
Caption: Comparative workflow diagram showing the three main NGS library preparation pathways—WGS, targeted enrichment, and amplicon—with differences in fragmentation strategy, capture/amplification steps, and key QC metrics for each.

Several commercially available RNA library prep kits achieve this through different chemical strategies. RNA-seq library QC must also assess ribosomal RNA depletion efficiency, which is a critical quality metric not applicable to DNA library prep.

Multiplexing strategy for batch projects: When preparing libraries for a multi-sample project, the barcoding strategy must be planned before library construction begins. For projects with 96 or fewer samples per sequencing run, single indexing is usually sufficient, provided the index sequences have adequate diversity. For projects exceeding 96 samples, or when multiplexing runs will be combined for analysis, unique dual indexes (UDI) are strongly recommended. UDI eliminates the risk of index hopping, which can cause false-positive variant calls in pooled sequencing designs. The choice of indexing strategy affects library preparation workflow because some index sets require specific adapter configurations, which in turn affect the ligation chemistry and cleanup protocol.

Reading Library QC Results — A Practical Guide to Common Failure Patterns

Learning to interpret Bioanalyzer or TapeStation traces is one of the most useful skills for anyone working with NGS libraries. Here are the six most common trace patterns and what they mean:

• Normal library: A single, symmetrical peak in the expected size range. For a standard 350 bp insert library with adapters, this means a peak at approximately 470 bp. Minor shoulders on either side are acceptable.
• Adapter dimer peak: A second, smaller peak at 120–140 bp (depending on adapter design). This indicates that adapter molecules ligated to each other during the ligation step rather than to insert DNA. A dimer peak <5% of total library mass is generally acceptable; higher levels require additional cleanup or protocol revision.
• Left-shifted peak (short fragments): The library peak is below the expected size range. This usually indicates over-fragmentation during the shearing or tagmentation step. It reduces mappable read length and may require re-optimization of fragmentation conditions.
• Right-shifted peak (long fragments): The library peak is above the expected size range. This indicates under-fragmentation or inefficient size selection. These libraries may produce lower cluster density on the flow cell because longer fragments do not amplify as efficiently.
• Broad peak (wide size distribution): The trace spans 500+ bp with no dominant peak. This is common with degraded input DNA, particularly FFPE. It is acceptable for FFPE libraries as long as the majority of fragments fall within or near the sequencing read length.
• No peak or very low signal: The library has extremely low yield or completely failed. Common causes include failed adapter ligation, insufficient input DNA, or degraded ligation enzyme. This requires repeating the library preparation with a positive control to isolate the cause.

Examples of each trace pattern are shown below.

Figure 6. Normal vs abnormal Bioanalyzer library traces — six common trace patterns with annotations
Caption: Six common Bioanalyzer trace patterns for NGS libraries: normal library peak, adapter dimer contamination, left-shifted (over-fragmented), right-shifted (under-fragmented), broad peak (degraded input), and failed library with no detectable signal.

How to Optimize Library Yields for Low-Input Samples

One of the most common practical questions researchers face is how to maximize library yield when input material is limited. The standard recommendation of "use more input DNA" is often not an option, so alternative strategies are required.

Minimize losses at every cleanup step: Each SPRI bead cleanup step loses 10–20% of library material, even under optimal conditions. For low-input samples, reducing the number of cleanup steps can significantly improve final yield. Some protocols combine post-ligation and post-PCR cleanup into a single bead step, at the cost of slightly broader size distribution. When input is critically limited (sub-10 ng), this trade-off is usually worth accepting.

Optimize PCR cycle count: The relationship between PCR cycles and library yield is not linear. The first few cycles produce exponential amplification; after 10–12 cycles, additional cycles add relatively little yield while significantly increasing duplication rates. For very low inputs (<5 ng), 12–14 cycles may be necessary. For inputs above 10 ng, 8–10 cycles are typically sufficient. Monitoring the amplification curve by qPCR or running a small-scale pilot test at 8, 10, 12, and 14 cycles for a new sample type helps identify the optimal balance.

Use carrier molecules: Adding a carrier (e.g., linear polyacrylamide or glycogen) during ethanol precipitation steps can improve recovery of low-concentration DNA. This is particularly useful for cfDNA samples where input quantities are in the 1–10 ng range and every nanogram counts.

Consider single-tube workflows: Some recently developed library preparation methods perform fragmentation, end repair, A-tailing, and adapter ligation in a single tube without intermediate cleanup steps. These single-tube workflows can improve conversion efficiency for low-input samples by 30–50% compared to multi-step protocols, at the expense of less precise size control.

Automation and Scalability in Library Preparation

As sequencing projects grow in scale, manual library preparation becomes a bottleneck. A lab processing 384 libraries per week cannot afford to prepare each library by hand, and batch effects from different operators can introduce unwanted technical variation.

Liquid handling automation platforms (such as those from Beckman Coulter, Hamilton, or Agilent) can process 96 or 384 samples in parallel with consistent reagent volumes and incubation times. The key considerations for adopting automated library preparation include:

• Protocol compatibility: Not all commercial library prep kits have validated automation protocols. Selecting a kit with an established automation script reduces development time significantly.
• Volume constraints: Automated liquid handlers have minimum pipetting volumes (typically 0.5–2 µL). Kits with smaller reaction volumes may require switching to higher-volume versions for automation compatibility.
• Magnetic bead handling: Automated bead-based cleanup is the most challenging step to optimize. Bead settling time, magnet engagement, and supernatant removal speed all affect reproducibility.
• QC integration: The most efficient automated workflows include inline QC steps, such as automated plate reading for quantification, to identify failed libraries before they proceed to sequencing.

For research teams building large-scale sequencing projects, NGS services with automated library preparation capabilities can provide the throughput and reproducibility that manual methods cannot match.

A Practical QC Workflow Before Sequencing

Before committing a batch of libraries to a sequencing run, a standardized QC workflow should be applied to every library. The goal is to identify libraries that are likely to fail before they waste flow cell capacity.

1. Quantification by qPCR: This is the most accurate method for determining the concentration of amplifiable library molecules. A qPCR result that differs from the Qubit measurement by more than 3-fold often indicates adapter dimer contamination or failed ligation.
2. Size distribution by capillary electrophoresis: A Bioanalyzer or TapeStation trace confirms that fragments fall within the expected size range and that adapter dimer levels are acceptable.
3. Molarity calculation: Concentration from qPCR is converted to molarity using the average fragment size from the Bioanalyzer trace, which is used to calculate loading volume.
4. Pool normalization: For multiplexed runs, individual libraries are pooled in equimolar amounts, with 10-20% excess prepared.
5. Pilot titration: For novel library types, a pilot test of 2-3 loading concentrations on the intended flow cell type is highly recommended.

This QC workflow takes approximately 2-3 hours for 96 libraries and should be considered a routine part of every NGS project.

Figure 7. Automation workflow for high-throughput library preparation
Caption: Automated liquid handling workflow for library preparation showing the key integration points: protocol compatibility, volume constraints, magnetic bead handling optimization, and inline QC for scalable production.

How CD Genomics Supports Library Preparation

CD Genomics provides comprehensive library preparation services covering the full range of Illumina-compatible methods and sample types.

Methods available: Our laboratory executes PCR-based fragmentation + ligation, PCR-free, and tagmentation-based library preparation methods, using the most widely adopted commercial kits. The choice of method is driven by your sample type and project requirements.

Special sample expertise: We have accumulated extensive experience with FFPE DNA repair and library construction, cfDNA and ultra-low-input library preparation, and automation-optimized workflows for large-scale projects. Our protocols are validated for blood, tissue, FFPE, cfDNA, single cells, and plant and microbial samples.

Library QC: Every library undergoes rigorous quality control including Bioanalyzer or TapeStation trace analysis, qPCR quantification, and size distribution confirmation before proceeding to sequencing.

Scalability: For large batch projects, we deploy automated liquid handling workflows that ensure consistent library quality across all samples. This is particularly valuable for multi-batch projects where batch-to-batch reproducibility is essential.

For more details, explore our NGS services or contact our team for project-specific recommendations.

FAQ

What is the difference between PCR-based and PCR-free library preparation?

PCR-based libraries include an amplification step that increases yield but can introduce bias in GC-rich regions and increase duplication rates. PCR-free libraries skip amplification, producing more uniform coverage, but require higher input DNA (>100 ng).

Which library prep method is best for FFPE DNA samples?

PCR-based fragmentation + ligation with a pre-library DNA damage repair step is recommended for FFPE samples. The repair step removes cytosine deamination artifacts that would otherwise appear as false-positive mutations.

Can PCR-free library preparation be used with low-input DNA?

Not typically. PCR-free methods require 100 ng to 1 µg of input DNA. For inputs below 100 ng, a PCR-based method is necessary to generate sufficient library yield.

What does an adapter dimer look like on a Bioanalyzer trace?

An adapter dimer appears as a small peak at approximately 120–140 bp, well below the expected library peak. If the dimer constitutes more than 5% of total library mass, additional cleanup is recommended.

How do I choose between tagmentation and fragmentation + ligation?

Tagmentation offers a faster workflow and lower input requirements but can introduce GC bias. Fragmentation + ligation delivers more uniform coverage across GC content and is the preferred choice for WGS and applications requiring uniform genomic representation.

What is the minimum input DNA for standard library preparation?

Standard PCR-based kits typically require 0.1–1 ng minimum input. Ultra-low-input kits can work with as little as 50 pg. PCR-free kits require 100 ng–1 µg.

How do I remove adapter dimers from my library?

Adapter dimers can be reduced by optimizing the SPRI bead cleanup ratio (higher ratios retain more dimers), using a double-sided size selection, or adding a gel-based size selection step for stubborn cases.

What QC metrics should I report for WGS library preparation?

At minimum: library concentration (from qPCR), fragment size distribution (from Bioanalyzer), and duplication rate (from a shallow-sequencing QC run or computational estimation).

Can CD Genomics prepare libraries from cfDNA?

Yes. We offer cfDNA-optimized library preparation using ultra-low-input protocols and stem-loop adapter designs that minimize adapter dimer formation in short-fragment libraries.

How long does a typical library preparation take?

A standard PCR-based fragmentation + ligation protocol takes 4-6 hours from DNA input to ready-to-sequence library. Tagmentation methods can be completed in approximately 3 hours. PCR-free methods require 5-7 hours due to additional cleanup steps required to remove unincorporated adapters without the option of PCR-based cleanup.

What is the difference between single-index and dual-index library preparation?

Single-index libraries use one barcode sequence per sample, while dual-index libraries use two independent barcode sequences (one on each adapter). Dual indexing reduces the risk of sample misassignment when multiple libraries are pooled for sequencing, particularly on patterned flow cell platforms where index hopping is more common.

What causes high duplication rates in sequencing data?

High duplication rates (>20%) are most commonly caused by insufficient input DNA, excessive PCR cycles, or low starting library complexity. For WGS libraries, PCR-free methods produce the lowest duplication rates, while PCR-based methods with inputs below the recommended range are most prone to this issue.

For Research Use Only.

References:

1. Best practices for Illumina library preparation. Current Protocols in Human Genetics. 2019;102(1):e86.
2. Comparison of sequencing bias of currently available library preparation kits. DNA Research. 2019;26(5):391-402.
3. Comparative analysis of library preparation approaches for FFPE DNA. Scientific Reports. 2025;15:12992.
4. A comparative analysis of library prep approaches for low-input samples. BMC Genomics. 2018;19:763.