The cost of parentage assignment precludes its application in many selective breeding programmes and molecular ecology studies, and/or limits the circumstances or number of individuals to which it is applied. Pooling samples from more than one individual, and using appropriate genetic markers and algorithms to determine parental contributions to pools, is one means of reducing the cost of parentage assignment. This paper describes and validates a novel maximum likelihood (ML) parentage-assignment method, that can be used to accurately assign parentage to pooled samples of multiple individuals—previously published ML methods are applicable to samples of single individuals only—using low-density single nucleotide polymorphism (SNP) ‘quantitative’ (also referred to as ‘continuous’) genotype data. It is demonstrated with simulated data that, when applied to pools, this ‘quantitative maximum likelihood’ method assigns parentage with greater accuracy than established maximum likelihood parentage-assignment approaches, which rely on accurate discrete genotype calls; exclusion methods; and estimating parental contributions to pools by solving the weighted least squares problem. Quantitative maximum likelihood can be applied to pools generated using either a ‘pooling-for-individual-parentage-assignment’ approach, whereby each individual in a pool is tagged or traceable and from a known and mutually exclusive set of possible parents; or a ‘pooling-by-phenotype’ approach, whereby individuals of the same, or similar, phenotype/s are pooled. Although computationally intensive when applied to large pools, quantitative maximum likelihood has the potential to substantially reduce the cost of parentage assignment, even if applied to pools comprised of few individuals.

亲子分配的成本排除了其在许多选择性育种计划和分子生态学研究中的应用，和/或限制了其应用的环境或个体数量。汇集来自多个个体的样本，并使用适当的遗传标记和算法来确定父母对汇集的贡献，是降低亲子分配成本的一种方法。本文描述并验证了一种新的最大似然 (ML) 亲子分配方法，该方法可用于准确地将亲子分配给多个个体的合并样本——以前发布的 ML 方法仅适用于单个个体的样本——使用低密度单核苷酸多态性（SNP）“定量”（也称为“连续”）基因型数据。用模拟数据证明，当应用于池时，这种“定量最大似然”方法比已建立的最大似然亲子分配方法更准确地分配亲子关系，后者依赖于准确的离散基因型调用；排除方法；并通过解决加权最小二乘问题来估计父母对池的贡献。定量最大似然可以应用于使用“个人亲子分配池”方法生成的池，其中池中的每个人都被标记或可追踪，并且来自一组已知且互斥的可能父母；或“按表型汇集”方法，即汇集具有相同或相似表型的个体。虽然在应用于大型池时计算量很大，