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GenoTypeMapper: graphical genotyping on genetic and sequence-based maps

机译:基因型映射:基于遗传和序列地图的图形基因分型

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The rising availability of assemblies of large genomes (e.g. bread and durum wheat, barley) and their annotations deliver the basis to graphically present genome organization of parents and progenies on a physical scale. Genetic maps are a very important tool for breeders but often represent distorted models of the actual chromosomes, e.g., in centromeric and telomeric regions. This biased picture might lead to imprecise assumptions and estimations about the size and complexity of genetic regions and the selection of suitable molecular markers for the incorporation of traits in breeding populations or near-isogenic lines (NILs). Some software packages allow the graphical illustration of genotypic data, but to the best of our knowledge, suitable software packages that allow the comparison of genotypic data on the physical and genetic scale are currently unavailable. We developed a simple Java-based-software called GenoTypeMapper (GTM) for comparing genotypic data on genetic and physical maps and tested it for effectiveness on data of two NILs that carry QTL-regions for drought stress tolerance from wild emmer on chromosome 2BS and 7AS. Both NILs were more tolerant to drought stress than their recurrent parents but exhibited additional undesirable traits such as delayed heading time. In this article, we illustrate that the software easily allows users to display and identify additional chromosomal introgressions in both NILs originating from the wild emmer parent. The ability to detect and diminish linkage drag can be of particular interest for pre-breeding purposes and the developed software is a well-suited tool in this respect. The software is based on a simple allele-matching algorithm between the offspring and parents of a crossing scheme. Despite this simple approach, GTM seems to be the only software that allows us to analyse, illustrate and compare genotypic data of offspring of different crossing schemes with up to four parents in two different maps. So far, up to 500 individuals with a maximum number of 50,000 markers can be examined with the software. The main limitation that hampers the performance of the software is the number of markers that are examined in parallel. Since each individual must be analysed separately, a maximum of ten individuals can currently be displayed in a single run. On a computer with an Intel five processor of the 8th generation, GTM can reliably either analyse a single individual with up to 12,000 markers or ten individuals with up to 3,600 markers in less than five seconds. Future work aims to improve the performance of the software so that more complex crossing schemes with more parents and more markers can be analysed.
机译:大型基因组组件的上升可用性(例如,面包和杜姆兰小麦,大麦)及其注释为以图形方式提供了物理规模的父母和后期的基因组组织。遗传地图是育种者的一个非常重要的工具,但通常代表实际染色体的扭曲模型,例如焦点和端粒区域。这种偏见的图片可能导致关于遗传区域的大小和复杂性的不精确假设和估计以及选择合适的分子标记,用于掺入繁殖群体或近代源性线(NIL)的特性。一些软件包允许基因型数据的图形插图,但据我们所知,允许比较基因型数据对物理和遗传规模进行比较的合适软件包目前无法使用。我们开发了一种称为GenotypeMapper(GTM)的简单Java的软件,用于比较基因型数据,用于比较遗传和物理地图的基因型数据,并测试其对两种NIL数据的有效性,该数据在染色体2BS和7AS上携带QTL-区进行QTL-RECOR的QTL-RECMER。 。两种含量比其经常性父母更容易耐受干旱压力,但展示了额外的不良特征,例如延迟前进时间。在本文中,我们说明软件容易允许用户在源自野生EMMER父母的两种含量中显示和识别额外的染色体血栓增。检测和减少联动阻力的能力可能特别令人口感兴趣的预育目的,并且开发的软件是这方面的一个很好的工具。该软件基于交叉方案的后代和父母之间的简单等位基因匹配算法。尽管这种简单的方法,GTM似乎是唯一一个允许我们分析的软件,说明和比较不同横穿方案的后代的基因型数据,在两个不同的地图中最多有四个父母。到目前为止,可以使用该软件检查最多500个具有50,000个标记数的人。妨碍软件性能的主要限制是并行检查的标记数。由于必须单独分析每个人,因此目前最多可以在一次运行中显示十个。在具有第8代的英特尔五个处理器的计算机上,GTM可以可靠地分析单个个体,其中包含多达12,000个标记或十个个体,在不到五秒钟的时间内最多可达3,600个标记。未来的工作旨在提高软件的性能,以便分析具有更多父母和更多标记的更复杂的交叉方案。

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