Microsatellite Mutation Rate in Atlantic Sturgeon (Acipenser oxyrinchus).

Understanding mutation rates can greatly extend the utility of population and conservation genetic analyses. Herein, we present an estimate of genome-wide microsatellite mutation rate in Atlantic sturgeon (Acipenser oxyrinchus) based on parent-offspring transmission patterns. We screened 307 individuals for parentage and mutation-rate analysis applying 43 variable markers. Out of 13228 allele transfers, 11 mutations were detected, producing a mutation rate of 8.3 × 10-4 per locus per generation (95% confidence interval: 1.48 × 10-3, 4.15 × 10-4). Single-step mutations predominated and there were trends toward mutations in loci with greater polymorphism and allele length. Two of the detected mutations were most probably cluster mutations, being identified in 12 and 28 sibs, respectively. Finally, we observed evidences of polyploidy based on the sporadic presence of 3 or 4 alleles per locus in the genotyped individuals, supporting previous reports of incomplete diploidization in Atlantic sturgeon.

Quantitative Cell Cycle Analysis Based on an Endogenous All-in-One Reporter for Cell Tracking and Classification.

Cell cycle kinetics are crucial to cell fate decisions. Although live imaging has provided extensive insights into this relationship at the single-cell level, the limited number of fluorescent markers that can be used in a single experiment has hindered efforts to link the dynamics of individual proteins responsible for decision making directly to cell cycle progression. Here, we present fluorescently tagged endogenous proliferating cell nuclear antigen (PCNA) as an all-in-one cell cycle reporter that allows simultaneous analysis of cell cycle progression, including the transition into quiescence, and the dynamics of individual fate determinants. We also provide an image analysis pipeline for automated segmentation, tracking, and classification of all cell cycle phases. Combining the all-in-one reporter with labeled endogenous cyclin D1 and p21 as prime examples of cell-cycle-regulated fate determinants, we show how cell cycle and quantitative protein dynamics can be simultaneously extracted to gain insights into G1 phase regulation and responses to perturbations.