Constructing linkage maps with achiasmatic gametogenesis.

Ji-Xiang Wu, Jun Zhu, Johnie N Jenkins, Jack C McCarty
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Abstract

Maximum likelihood (ML) approach is used for estimating recombination frequency based on the achiasmatic model and the corresponding software package is developed for constructing linkage maps for achiasmatic organisms (F2 populations). The detection of sex-linked markers is done through a chi-square test. Monte Carlo simulations were conducted for comparing estimation of recombination frequency and mapping powers between these two genetic models (chiasmatic and achiasmatic models) when the achiasmata occurs. Simulation results showed that the achiasmatic model could provide unbiased estimations, while the chiasmatic model (without correction) gave under-estimates. The powers of grouping and ordering by the achiasmatic model were greater than those by the chiasmatic model (without correction) for all cases. ML approach based on the achiasmatic model can be used without correcting the data to obtain desirable linkage map powers in achiasmatic organisms.

构建非合配子发生的连锁图谱。
利用最大似然(ML)方法估计了非交叉模型的重组频率,并开发了相应的软件包,用于构建非交叉生物(F2群体)的连锁图谱。性别连锁标记的检测是通过卡方检验完成的。通过蒙特卡罗模拟,比较了两种遗传模型(交叉模型和非交叉模型)在发生非交叉时的重组频率和作图能力的估计。仿真结果表明,交叉模型可以提供无偏估计,而交叉模型(未经校正)给出的估计较低。在所有情况下,非交叉模型的分组和排序能力均大于交叉模型(未经校正)。基于非交叉模型的机器学习方法可以在不校正数据的情况下使用,以获得理想的非交叉生物体的连锁图谱功率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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