基因分型
大规模并行测序
微卫星
遗传学
DNA测序
计算生物学
生物
推论
计算机科学
DNA
基因型
生物信息学
医学
基因组学
作者
Ranran Zhang,Jiaming Xue,Mengyu Tan,Fan Yang,Guihong Liu,Yazi Zheng,Qiushuo Wu,Miao Liao,Meili Lv,Chengtao Li,Suhua Zhang,Shengqiu Qu,Weibo Liang
摘要
ABSTRACT Non‐invasive prenatal paternity testing (NIPPT) enables the genotyping of cell‐free DNA (cfDNA) from maternal plasma through deep sequencing. Microhaplotypes (MHs) combine the advantages of short tandem repeats (STRs) and single‐nucleotide polymorphisms (SNPs) and have attracted much attention in NIPPT. In this study, we optimized 45 MHs from our previous study and confirmed the effectiveness of the 45plex MH panel through different kinship inferences using real samples, including duos, trios, full siblings, and second‐to‐fifth‐degree relatives, and excluding unrelated individuals. Furthermore, we tested 11 cfDNA and reference mother–child pairs in the first trimester (7 + 4–12 + 6 weeks) and 11 cfDNA and reference trios in the second trimester (18+ weeks). The R packages Familias and RelMix and the software EuroForMix were used for data interpretation. The results showed that MHs of cfDNA could be effectively detected using our sequencing and genotyping pipelines. We correctly determined paternity in 11 NIPPT cases, with Log 10 LR > 10, which were significantly separated from real unrelated males. Our study indicates that this massively parallel sequencing (MPS)‐based 45plex MH panel provides more robust relationship inference capabilities than standard STR systems, complements NIPPT, and may help solve relevant issues for relative DNA mixtures.
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