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Amplified fragment length polymorphism

Amplified fragment length polymorphism (AFLP) is a (PCR)-based molecular technique used to generate DNA fingerprints by selectively amplifying subsets of restriction enzyme-digested genomic fragments, enabling the detection of genetic variations such as single nucleotide polymorphisms (SNPs) or insertions/deletions (INDELs) without requiring prior sequence knowledge. Developed in the early by Vos et al. and first described in , AFLP combines the reliability of (RFLP) analysis with the sensitivity of to produce reproducible banding patterns that represent polymorphic loci across genomes. The method typically involves digesting total genomic DNA with two restriction endonucleases, such as EcoRI (a rare cutter) and MseI (a frequent cutter), followed by of synthetic adapters to the resulting fragments; these adapters provide primer binding sites for subsequent amplification. A pre-selective step uses primers with one selective to amplify a of fragments, while a final selective employs primers with three selective (often with one labeled for detection) to further refine the products, yielding 50–100 resolvable bands per reaction that are separated and visualized via or . AFLP has been widely applied in genetics and microbiology for assessing genetic diversity, constructing phylogenetic trees, mapping genes, and differentiating microbial strains, such as in epidemiological studies of bacteria like Aeromonas or Xanthomonas, where it offers high resolution with up to 50 loci per primer combination and a 93% probability of excluding non-parental genotypes in parentage analysis using just three primer pairs. Variants like cDNA-AFLP extend its utility to transcriptomics for identifying differentially expressed genes, while methylation-sensitive AFLP (MSAP) detects epigenetic modifications such as DNA methylation patterns. Its advantages include high reproducibility, the ability to work with minute DNA quantities (as low as 10–50 ng), and the generation of thousands of markers rapidly using 128 possible three-base selective primer combinations, making it particularly valuable for non-model organisms. Despite its strengths, AFLP is a dominant marker system, complicating the distinction between homozygous and heterozygous states without additional genotyping, and it demands careful optimization of enzyme combinations and PCR conditions, rendering it labor-intensive, time-consuming, and relatively costly compared to sequence-based methods like next-generation sequencing. These limitations have led to its partial replacement by more accessible techniques in modern genomics, though it remains a robust tool for initial diversity screening in resource-limited settings.

Introduction

Definition and Principles

Amplified fragment length polymorphism (AFLP) is a polymerase chain reaction (PCR)-based DNA fingerprinting technique that detects genome-wide polymorphisms without requiring prior knowledge of DNA sequences. It combines the generation of restriction fragments from total genomic DNA with selective amplification to produce a set of DNA bands that serve as genetic markers. Developed as a high-throughput method, AFLP enables the simultaneous screening of hundreds of loci across individuals or populations. The core principles of AFLP rely on restriction enzymes, which are endonucleases that cleave double-stranded DNA at specific recognition sites. Typically, a rare-cutting enzyme such as EcoRI, recognizing the 6-base pair palindromic sequence 5'-GAATTC-3', and a frequent-cutting enzyme like MseI, recognizing the 4-base pair sequence 5'-TTAA-3', are used to digest genomic DNA, yielding thousands of fragments with cohesive ends. Synthetic double-stranded oligonucleotide adapters, non-palindromic and compatible with the enzyme-generated overhangs, are then ligated to these fragment ends using DNA ligase; the adapters provide universal primer-binding sites and prevent recutting at the original restriction sites. PCR, a method that employs thermostable DNA polymerase (e.g., Taq), primers, deoxynucleotide triphosphates, and repeated cycles of denaturation, annealing, and extension to exponentially amplify targeted DNA sequences, is applied in two stages: a pre-selective amplification using primers matching the adapters plus one additional selective nucleotide each, followed by a selective amplification with primers extended by two or three selective nucleotides at their 3' ends. This selectivity reduces complexity, typically amplifying 50–100 fragments per reaction, depending on the genome size and selective bases chosen. Polymorphisms in AFLP arise from variations that alter recognition sites, leading to the presence or absence of specific fragments, or from insertions/deletions (indels) that change fragment lengths. These variations are visualized as distinct bands after electrophoretic separation on denaturing gels, where one of the selective primers is radiolabeled or fluorescently tagged for detection. The resulting banding pattern reflects genetic differences across samples, with polymorphic bands indicating sequence divergence. The overall proceeds as follows: of DNA, adapter , pre-selective PCR, selective PCR, and fragment separation by .

History and Development

Amplified fragment length polymorphism (AFLP) was developed in 1995 by Pieter Vos and colleagues at KeyGene N.V., a biotechnology company based in Wageningen, Netherlands, as a proprietary PCR-based method for generating high-throughput DNA fingerprints without prior sequence knowledge. The technique combined restriction digestion, adapter ligation, and selective amplification to detect polymorphisms, offering a more reproducible and multiplexed alternative to existing methods like restriction fragment length polymorphism (RFLP) and random amplified polymorphic DNA (RAPD). KeyGene's innovation addressed the need for rapid marker discovery in complex genomes, particularly in agriculture, and the method was immediately protected under patents owned by the company. The seminal description of AFLP appeared in a 1995 Nucleic Acids Research paper by Vos et al., which demonstrated its ability to produce hundreds of polymorphic fragments per reaction, enabling efficient for marker-assisted . Early adoption surged in the late , primarily in programs, where AFLP facilitated high-density genetic mapping; for instance, it was applied to construct linkage maps in crops like in 2000, accelerating the identification of quantitative trait loci. KeyGene secured multiple patents, including US Patent 6,045,994 (2000) for AFLP-based polymorphism detection, which solidified its commercial role in research. By the early 2000s, AFLP expanded beyond to microbial typing, such as in bacterial , and animal population studies, revealing genetic diversity in like and . In the 2000s, AFLP evolved through automation, integrating fluorescent labeling and for higher resolution and throughput, as seen in protocols for bacterial strain differentiation by 2000. The 2010s marked a shift toward next-generation sequencing (NGS) adaptations, such as AFLP-seq, which combined traditional AFLP enrichment with NGS for cost-effective discovery in non-model organisms, enhancing resolution in surveys. Post-2020, AFLP has been applied in studies of fungal pathogens and assessments in crops. As of 2024, AFLP continues to be utilized for developing markers in fungal pathogens like and assessing in crops such as carrots. These adaptations have positioned AFLP as a complementary tool in modern , bridging legacy methods with high-resolution sequencing.

Methodology

DNA Preparation and Restriction Digestion

High-quality genomic DNA is essential for amplified fragment length polymorphism (AFLP) analysis, typically requiring 100-500 ng per reaction to ensure sufficient template for generating a representative set of restriction fragments. The DNA must be free of contaminants such as proteins, polysaccharides, and phenols, which can inhibit restriction enzyme activity; degraded or impure DNA leads to incomplete digestion and inconsistent results. For plant tissues, cetyltrimethylammonium bromide (CTAB)-based extraction methods are commonly used due to their effectiveness in removing polyphenolic compounds and polysaccharides, yielding high-molecular-weight DNA suitable for downstream applications. In microbial samples, commercial kits employing silica-based columns or magnetic beads are preferred for rapid isolation of clean DNA from diverse bacterial or fungal sources. The restriction digestion step involves simultaneous cleavage of the genomic DNA using a pair of restriction endonucleases: a rare cutter with a 6-base pair (bp) recognition site, such as (recognizing 5'-GAATTC-3'), and a frequent cutter with a 4-bp site, such as MseI (recognizing 5'-TTAA-3'). This enzyme combination is selected to produce approximately 50,000-100,000 fragments averaging 100-500 bp in length, providing a balanced complexity for subsequent selective amplification while avoiding over-fragmentation. The reaction is typically set up in a 25-50 µl volume containing 5-10 units each of and MseI, 100-500 ng DNA, 1× restriction buffer (e.g., 10 mM Tris-HCl pH 7.5, 10 mM MgCl₂, 50 mM KCl, 0.1 mg/ml [BSA]), and incubated at 37°C for 2-3 hours, followed by heat inactivation at 65-70°C for 15 minutes to stop enzymatic activity. BSA is included to stabilize the enzymes and protect against non-specific binding in complex samples. Quality control is critical to confirm complete digestion and rule out artifacts. Post-digestion samples are analyzed on a 1-1.5% agarose gel stained with ethidium bromide, where successful digestion appears as a continuous smear from approximately 100-1,500 bp, indicating the expected fragment size distribution without prominent high-molecular-weight bands from undigested DNA. Partial digests, evidenced by residual genomic DNA bands, can be addressed by increasing enzyme units (e.g., to 10-20 U) or extending incubation time to 4-6 hours, while star activity—non-specific cleavage due to improper conditions—is minimized by using fresh buffers, avoiding excessive glycerol (>5%), and maintaining optimal salt concentrations. Protocol variations are employed for challenging genomes to optimize fragment yield and reduce bias. For GC-rich DNA (e.g., >50% GC content), enzyme pairs with GC-biased recognition sites, such as HindIII (AAGCTT) paired with TaqI (TCGA), are substituted for EcoRI/MseI to increase cutting frequency in high-GC regions and generate more even fragment distribution. In cases of heavily methylated DNA, methylation-sensitive enzymes like PstI (CTGCAG) replace EcoRI, as it is inhibited by cytosine methylation, allowing detection of epigenetic variation while avoiding under-representation of methylated loci. These adjustments ensure reproducible fragment generation across diverse taxa.

Adapter Ligation and Selective Amplification

Following restriction digestion of genomic DNA with enzymes such as EcoRI and MseI, synthetic oligonucleotide adapters are ligated to the cohesive ends of the resulting fragments to facilitate subsequent PCR amplification. These adapters are designed to be non-palindromic, ensuring directional ligation and preventing self-annealing or adapter dimer formation; for instance, the EcoRI adapter consists of the oligonucleotides 5'-CTCGTAGACTGCGTACC-3' and 5'-AATTGGTACGCAGT-3', while the MseI adapter comprises 5'-GACGATGAGTCCTGAG-3' and 5'-TACTCAGGACTCAT-3'. The ligation reaction typically employs T4 DNA ligase at 16°C overnight with 50-100 units of enzyme, providing primer binding sites on the adapters without altering the original restriction site sequences or disrupting the fragment ends. The ligated products then undergo pre-selective amplification via to enrich for fragments bearing the , using primers that include the adapter sequence plus one selective at the 3' end. Examples include the primer E01 (5'-GACTGCGTACCAATTCA-3', selective A) and the MseI primer M02 (5'-GATGAGTCCTGAGTAAAC-3', selective C). This step involves 20-30 cycles of amplification under conditions such as 94°C for 30 s (denaturation), 56°C for 30 s (annealing), and 72°C for 1 min (extension), generating a moderately pool of amplicons that reduces the initial genomic complexity by approximately 16-fold per enzyme. Selective amplification follows as a nested on a 20- to 50-fold dilution of the pre-selective product, employing primers with two to three additional selective bases to further refine the subset of amplified fragments. For example, primers might be +AAC (5'-GACTGCGTACCAATTCAAC-3') and MseI +CAA (5'-GATGAGTCCTGAGTAACAA-3'), with the primer often labeled fluorescently or with a radioisotope for detection. The thermal cycling protocol includes 12-13 cycles with touchdown annealing, starting at 65°C and decreasing by 1°C per to 56°C (94°C for 30 s, annealing for 30 s, 72°C for 1 min), followed by additional cycles at 56°C annealing to enhance specificity and yield. Optimization of the process involves selecting primer combinations—up to 256 possible for two selective bases per primer pair—to achieve balanced without toward GC-rich regions, alongside careful dilution of the pre-amplification product to prevent over- and non-specific products. Typically, this results in 50-200 scorable bands per lane, depending on and primer selectivity.

Data Analysis

Fragment Separation and Visualization

Following selective amplification, the resulting AFLP fragments, typically ranging from 40 to 400 base pairs, are separated by size to generate distinct fingerprint patterns. Traditional separation employs denaturing (PAGE) using a 5% gel containing 7.5 M in Tris-boric acid-EDTA (TBE) buffer, run at constant power of 110 W for approximately 2 hours to achieve high resolution of 1-2 base pairs. Modern protocols favor automated for enhanced throughput and precision, utilizing instruments such as the ABI 310 or ABI 3730 with a 47 cm array filled with POP-4 polymer, involving electrokinetic injection at 15 kV for 3 seconds followed by electrophoresis at 15 kV for 25 minutes at 60°C. Visualization of separated fragments historically relied on radioactive end-labeling of the selective primer with [γ-³³P]ATP (100 µCi per reaction) prior to amplification, followed by autoradiography using phosphoimaging systems after gel drying and exposure for 16 hours. Contemporary methods incorporate fluorescent labeling, such as FAM or dyes attached to the primer, enabling laser-induced detection during to produce digital electropherograms with clearly defined peaks corresponding to fragment sizes. This shift from radioactive to fluorescent detection has improved safety, reproducibility, and compatibility with automated analysis software. For gel-based PAGE, samples are denatured in a formamide-based loading dye (e.g., 95% with ) and loaded alongside an internal size standard, such as a 50-700 ladder, to calibrate fragment lengths accurately. In capillary systems, 1-2 µL of amplified product is mixed with 10 µL Hi-Di and 0.5 µL of a fluorescent size standard like GeneScan 500 ROX or LIZ-600, then heat-denatured before injection. The resulting outputs include gel images for PAGE (scanned via autoradiography or silver staining) or electropherogram traces for capillary runs, displaying bands or peaks at precise sizes within the 40-400 range. Quality assessment of AFLP fingerprints involves evaluating gel images or electropherograms for the absence of smears (indicating non-specific amplification), consistent band/ across lanes (reflecting uniform amplification efficiency), and high between technical replicates, typically achieving >95% band matching. Suboptimal patterns, such as excessive smearing or faint bands, may necessitate optimization of amplification conditions or repeat runs to ensure reliable polymorphism detection.

Polymorphism Detection and Scoring

Polymorphisms in amplified fragment length polymorphism (AFLP) analysis are primarily detected through differences in banding patterns, manifesting as presence or absence of DNA fragments across samples, which serve as dominant markers. These variations arise from mutations affecting restriction sites or adjacent sequences that alter fragment amplification or length, resulting in a binary scoring system where bands are coded as 1 (present) or 0 (absent) for each locus position in a matrix. Initial processing of raw data involves peak calling software such as GeneScan or Peak Scanner to identify and size fragments based on , typically setting thresholds like a minimum peak height of 100 (RFU) to distinguish true signals from . AFLP-specific tools like RawGeno, an , automate scoring by normalizing peak positions, binning fragments into loci, and generating binary matrices while correcting for stutter peaks and size shifts; it ensures reproducibility by filtering samples with low peak counts or high error rates from replicates. Similarly, AFLPdat, another R-based toolkit, handles data formatting, error rate estimation, and conversion to inputs for downstream software like or ARLEQUIN, often requiring replicate matches exceeding 90% for reliable loci. Statistical methods for quantifying polymorphisms include Jaccard's similarity coefficient, calculated as the number of shared bands divided by the total number of bands across samples (J = a / (a + b + c), where a is shared presences, b and c are unique presences), to construct similarity matrices that reveal genetic distances. Principal coordinate analysis (PCoA) is applied to these matrices for visualizing population clustering, while frequencies are estimated to account for dominant marker limitations. Common error sources in scoring include , where non-homologous fragments co-migrate to the same size, leading to overestimation of similarity, and stochastic PCR variations causing inconsistent peak heights; mitigation involves replicate analyses (ideally 20% of samples) to achieve error rates below 5%, along with stringent thresholds and negative controls. The output from scoring typically comprises a per primer combination, which feeds into matrices or phylogenetic trees via methods like unweighted pair group method with (UPGMA), enabling downstream applications in .

Applications

Genetic Diversity and

Amplified fragment length polymorphism (AFLP) serves as a powerful tool for assessing by generating multilocus DNA fingerprints that reveal polymorphisms across the without requiring prior sequence knowledge. In , AFLP markers enable the estimation of key metrics such as heterozygosity, polymorphism information content (PIC), and genetic differentiation (FST), facilitating the identification of population structure and patterns. This technique's high throughput and reproducibility make it particularly suitable for non-model organisms, where it has been applied to quantify intraspecific variation and evolutionary relationships. In plant studies, AFLP has been extensively used to evaluate genetic diversity and phylogeographic patterns, such as in the analysis of Spartina species to explore hybridization and polyploidy events, revealing distinct genetic clusters corresponding to geographic distributions. Similarly, in conservation genetics, AFLP markers have helped monitor diversity in threatened species like Norway spruce (Picea abies), to estimate heterozygosity and inform breeding strategies. Animal applications include assessing nuclear genome divergence in cattle breeds, identifying intraspecific variation that supports population management and traceability programs. Microbial population genetics benefits from AFLP's discriminatory power in delineating strain diversity and epidemiological links, as demonstrated in Paracoccidioides species, where it uncovered high PIC values (0.068–0.292) and structured populations with 65–66% variance between complexes, highlighting cryptic and regional in . In protozoan parasites like , AFLP has revealed intraspecific variation tied to host adaptation and geographic isolation. These applications underscore AFLP's role in evolutionary , such as detecting selective loci in ecotypes of Littorina saxatilis, where it identified outlier markers under divergent selection despite challenges. Overall, AFLP's ability to produce hundreds of markers per has established it as a for rapid, genome-wide surveys in diverse taxa.

Linkage Mapping and Breeding

Amplified fragment length polymorphism (AFLP) markers have been instrumental in linkage mapping, particularly through the use of recombinant inbred line (RIL) populations, which facilitate the detection of co-segregating markers with traits of interest. In co-segregation analysis, AFLP fragments are scored for presence or absence in progeny, allowing placement on s via linkage group ; for instance, in an Ler/Cvi RIL population, 321 AFLP markers were integrated into a spanning chromosomes, with common markers aligning positions across related RIL sets to confirm locus identity. Software like JoinMap is commonly employed for this, applying logarithm of odds (LOD) thresholds greater than 3 to group markers into linkage groups while minimizing false linkages, as demonstrated in AFLP-based maps of crops such as wolfberry, where LOD scores ranging from 3 to 10 ensured robust across 12 linkage groups. This approach outputs groups, with distances calculated in centimorgans () using functions like Kosambi's, defined as d = 25 \ln\left( \frac{1 + 2r}{1 - 2r} \right), where r is the recombination , to account for double crossovers and provide accurate interval estimates, as applied in AFLP maps of the yielding a total length of 180.9 across three chromosomes. For (QTL) detection, AFLP markers are integrated with phenotypic data from mapping to identify genomic regions associated with traits, enabling fine-mapping of complex loci. In , early studies utilized AFLP maps to detect QTLs for components; for example, an AFLP-based linkage map in a testcross identified multiple QTLs influencing and related traits like kernel number, with cofactor analysis adjusting for genetic background effects to enhance detection accuracy. These QTLs often explained 10-20% of phenotypic variance per locus, highlighting AFLP's utility in dissecting polygenic traits under varying environmental conditions. In breeding applications, AFLP supports (MAS) by linking polymorphisms to disease resistance genes, accelerating in programs. For instance, AFLP-derived markers have been converted to sequence-characterized amplified regions (SCARs) for MAS of broad-spectrum late blight resistance in , allowing efficient transfer from wild species into elite lines while monitoring background recovery. High-density AFLP maps, typically comprising 500-1000 loci, facilitate this by providing genome-wide coverage; a map with 561 AFLP markers spanned 1062 cM, enabling precise QTL positioning for resistance traits in backcross-derived lines. Case studies illustrate AFLP's impact in variety development. In potato breeding during the 2000s, recurrent selection combined AFLP background selection with phenotypic evaluation for late blight resistance, increasing resistant genotypes by 23.8% across generations while preserving 96% of parental in a tetraploid B3C2 population. More recently, in the 2020s, AFLP has aided homoeologous differentiation in polyploid crops like , a hexaploid, where markers distinguished sets in populations, supporting selection amid complex patterns.

Advantages and Limitations

Key Strengths

Amplified fragment length polymorphism (AFLP) excels in generating genetic markers without requiring prior sequence knowledge of the , making it particularly valuable for non-model organisms where genomic resources are limited. This approach allows researchers to rapidly produce fingerprints from total DNA using restriction enzymes and selective amplification, enabling studies in diverse taxa without the need for sequence databases or probes. A key strength lies in its high throughput and reproducibility, with a single assay typically yielding 50-100 fragments per primer combination, many of which are polymorphic, and reproducibility rates exceeding 95% across laboratories when protocols are standardized. The technique's efficiency stems from multiplex PCR, which amplifies numerous restriction fragments simultaneously, and its relatively low per-sample cost—approximately $7-15 depending on scale and reagents—facilitates large-scale genotyping without extensive optimization. This cost-effectiveness is achieved through minimal DNA input (as little as 100 ng) and the avoidance of costly sequencing or cloning steps. AFLP provides broad genome-wide coverage by randomly sampling restriction sites across all chromosomes, which is advantageous for complex, polyploid, or large genomes where uniform marker distribution is essential. Its versatility extends to applications in , animals, and microbes, and it scales seamlessly from traditional gel-based detection to modern or next-generation sequencing platforms for enhanced resolution. Additionally, AFLP offers a quantitative by assessing peak intensities to infer codominant polymorphisms, allowing dosage-based detection in heterozygous individuals beyond simple presence-absence scoring.

Limitations and Comparisons

Amplified fragment length polymorphism (AFLP) markers are dominant, meaning they cannot distinguish between homozygous dominant and heterozygous genotypes, leading to an underestimation of heterozygosity in population genetic analyses. This limitation complicates accurate estimation and reduces the method's utility for studies requiring codominant data. Size homoplasy poses another significant challenge, where non-homologous fragments of identical length co-migrate during electrophoresis, resulting in false homozygosity or overestimation of genetic similarity. Studies have shown that homoplasy increases with fragment size and genome complexity, potentially biasing diversity metrics by 10-20% in some species. Additionally, AFLP is highly sensitive to DNA quality, requiring high-molecular-weight, pure genomic DNA (typically 100-500 ng) to avoid incomplete restriction digestion or false polymorphisms. Poor-quality templates, such as those degraded or contaminated, often yield inconsistent amplification patterns. The protocol's labor-intensive nature further restricts its scalability, involving multiple steps like restriction digestion, adapter ligation, selective , and manual or semi-automated gel scoring, which can introduce subjective errors in interpretation. Non-uniform amplification introduces technical biases, with efficiency varying due to primer interactions and template complexity, often favoring certain genomic regions and complicating allele-specific quantification. In large-scale studies, these issues can amplify variability, making AFLP less reliable without rigorous standardization. Compared to (RFLP), AFLP offers faster processing and eliminates the need for Southern blotting or radiolabeling, enabling higher throughput without sequence-specific probes. However, relative to simple sequence repeats (SSRs or microsatellites), AFLP generates numerous markers per assay but typically exhibits lower polymorphism levels than SSRs, which provide codominant scoring and higher resolution for fine-scale mapping, making them preferable for breeding programs despite higher development costs. In contrast to single nucleotide polymorphisms (SNPs), AFLP delivers lower genomic resolution and struggles with precise due to its anonymous nature, whereas SNPs enable direct sequence-based analysis with minimal . AFLP remains advantageous for initial screening in non-model organisms lacking reference genomes, as it requires no prior sequence knowledge. Next-generation sequencing (NGS)-based methods like restriction-site associated DNA sequencing have largely supplanted AFLP for high-resolution applications since the 2010s, offering millions of codominant markers at reduced per-sample costs in well-resourced labs. Nonetheless, AFLP persists in resource-limited field settings, such as 2020s surveys in remote ecosystems, where its simplicity and low equipment needs facilitate rapid assessments comparable to reduced-representation NGS in smaller-scale studies. As of 2025, AFLP continues to be employed in studies like genetic analysis of birch , demonstrating its persistence in targeted assessments. AFLP should be avoided for applications demanding precise allele quantification or high-resolution genotyping, such as quantitative trait locus mapping in large genomes, where SNPs or NGS provide superior accuracy. In automated pipelines, its manual scoring vulnerabilities exacerbate errors, favoring alternatives in high-throughput environments.

Intellectual Property and Patents

The Amplified Fragment Length Polymorphism (AFLP) technique was developed by researchers at KeyGene N.V. in the , with the foundational patent EP0534858B1 filed on September 24, 1992, and granted on April 27, 2005, covering the selective restriction fragment amplification method central to AFLP for DNA fingerprinting and polymorphism detection. The corresponding patent, US6045994, was granted on April 4, 2000, protecting the adapters, primers, and amplification processes used in AFLP analysis. These patents, along with related filings, established KeyGene's rights over the core AFLP methodology, influencing its global adoption in genomics research. During the and , KeyGene enforced licensing requirements for commercial applications of AFLP, requiring fees and agreements for uses in , genetic mapping, and , which restricted widespread access and prompted collaborations such as non-exclusive licenses with academic institutions and kit manufacturers like . Research kits were distributed under these licenses, but proprietary software and protocols remained controlled, leading to the development of alternative open methods like inter-retrotransposon amplified polymorphism (IRAP) as workarounds during the patent period. The primary AFLP patents expired around 2012 in (EP0534858B1 on September 24, 2012) and on April 4, 2017, in the (US6045994, the later of 17 years from grant or 20 years from filing), entering the and eliminating royalty obligations for the core technique. By 2025, AFLP is fully accessible without enforcement, though the "AFLP" remains registered to KeyGene N.V., potentially applying to branded kits or derivatives. No major ongoing legal disputes over the original method have been reported, allowing unrestricted use in and applications.

Current Availability and Usage

Amplified fragment length polymorphism (AFLP) remains commercially available through kits provided by Thermo Fisher Scientific, such as the AFLP® Analysis System, which enables the generation of DNA fingerprints for various organisms without prior genomic sequence knowledge. Following the expiration of foundational patents, open protocols for AFLP implementation using standard restriction enzymes and PCR reagents have proliferated, facilitating widespread adoption in research laboratories. Free software tools support AFLP data analysis, including AFLP-SURV, which computes , population structure, and genetic distances from dominant marker data like AFLP and RAPD. Public resources for AFLP data include repositories such as dbGaP, where AFLP-derived polymorphic loci caused by SNPs or indels are archived for genomic studies. Detailed training protocols for AFLP, including transcript profiling variants, are outlined in established resources like Current Protocols in Molecular Biology. In 2025, AFLP usage persists in niche ecological and genetic applications, particularly for population structure analysis in non-model organisms, as demonstrated in a study generating 590 polymorphic loci to evaluate in across populations. It finds continued relevance in field and assessments of crop wild relatives, where low-input methods aid in conserving amid challenges, with recent integrations guiding targeted next-generation sequencing (NGS) for deeper genomic insights. Publication trends indicate a decline from over 13,000 cumulative papers by 2019—peaking in the early —to roughly 500 annually in recent years, reflecting a shift toward high-throughput alternatives while maintaining utility in resource-limited settings. AFLP's accessibility stems from its reliance on basic laboratory equipment, such as thermal cyclers for and systems for fragment separation, making it suitable for labs in developing regions or field stations. Cost-effective optimizations, including fluorescent labeling and , reduce per-sample expenses, enhancing its viability for large-scale surveys despite the rise of NGS.

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