Grandke Fabian, Ranganathan Soumya, van Bers Nikkie, de Haan Jorn R, Metzler Dirk
Genetwister Technologies B.V., Wageningen, The Netherlands.
Fakultät für Biologie, University of Munich (LMU), Munich, Germany.
BMC Bioinformatics. 2017 Jan 4;18(1):12. doi: 10.1186/s12859-016-1416-8.
A large share of agriculturally and horticulturally important plant species are polyploid. Linkage maps are used to locate associations between genes and traits by breeders and geneticists. Linkage map creation for polyploid species is not supported by standard tools. We want to overcome this limitation and validate our results with simulation studies.
We developed PERGOLA, a deterministic and heuristic method that addresses this problem. We show that it creates correct linkage groups, marker orders and distances for simulated and real datasets. We compare it to existing tools and demonstrate that it overcomes limitations in ploidy and outperforms them in computational time and mapping accuracy. We represent linkage maps as dendrograms and show that this has advantages in the comparison of different maps.
PERGOLA can be used successfully to calculate linkage maps for diploid and polyploid species and outperforms existing tools.
在农业和园艺领域具有重要意义的植物物种中，很大一部分是多倍体。育种者和遗传学家利用连锁图谱来定位基因与性状之间的关联。标准工具不支持创建多倍体物种的连锁图谱。我们希望克服这一限制，并通过模拟研究验证我们的结果。
我们开发了PERGOLA，这是一种确定性启发式方法，可解决此问题。我们表明，它为模拟数据集和真实数据集创建了正确的连锁群、标记顺序和距离。我们将其与现有工具进行比较，并证明它克服了倍性方面的限制，在计算时间和映射准确性方面优于现有工具。我们将连锁图谱表示为树状图，并表明这在不同图谱的比较中具有优势。
PERGOLA可成功用于计算二倍体和多倍体物种的连锁图谱，并且优于现有工具。
