Method

MAPLE enables ultrasensitive detection of low-frequency cfDNA methylation haplotypes using short capture probes with cost-efficient performance

    • 1Research and Development, Shanghai Xiaohe Medical Laboratory Co., Ltd., Shanghai 201321, China;
    • 2Department of Colorectal Surgery, Department of General Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China;
    • 3Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China;
    • 4Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China;
    • 5Health Medical Center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400067, China;
    • 6Department of Gastrointestinal Surgery, Institute of Gastrointestinal Oncology, Zhongshan Hospital of Xiamen University, Xiamen 361004, China
    • 7 These authors contributed equally to this work.
Published June 16, 2026. https://doi.org/10.1101/gr.280736.125
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cover of Genome Research Vol 36 Issue 6
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Abstract

One major challenge in disease detection using methylation biomarkers is accurately identifying low-frequency, disease-specific methylation haplotypes. Conventional methods detect these haplotypes using unbiased long capture probes, requiring high sequencing depth, with most reads being uninformative. Here, we present Methylation Anchor Probe for Low-signal Enrichment (MAPLE), a novel technology that uses rationally designed, ultrasensitive short capture probes to selectively enrich low-frequency methylation haplotypes, significantly reducing sequencing costs while enhancing detection sensitivity. We experimentally validate MAPLE on reference samples and develop the Enrichment Factor Model (EFM) to quantify the enrichment efficiency of individual probes. To our knowledge, this is the first model to enable correction of observed disease-specific haplotype fractions to their original levels, essential for estimating the limit of detection (LOD) in assay performance evaluation. Finally, two panels are designed using MAPLE and the conventional method respectively to target 13,264 colorectal cancer (CRC)-related methylation haplotypes and are validated through a blood plasma cohort of 162 samples including CRC patients and controls. In 24 stage I and II cancer samples, MAPLE maps 22.7% of unique reads to 5045 targeted haplotypes, compared to 0.8% of reads mapping to 190 haplotypes with the conventional method. MAPLE also enriches tumor-specific fragmentomic characteristics, including fragment size and DNA cleavage profiles. Aided by a LightGBM classifier, the MAPLE panel accurately identifies patients with 95% specificity and 80% sensitivity. Even with just 0.05% of total sequencing reads, MAPLE exhibits only a modest performance decline, in contrast to the conventional method’s significant decline, highlighting MAPLE’s superior efficiency and robustness.

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