Symonds V Vaughan, Godoy A Veronica, Alconada Teresa, Botto Javier F, Juenger Thomas E, Casal Jorge J, Lloyd Alan M
Section of Molecular, Cell and Developmental Biology, Institute for Cellular and Molecular Biology, University of Texas, 78712, USA.
Genetics. 2005 Mar;169(3):1649-58. doi: 10.1534/genetics.104.031948. Epub 2005 Jan 16.
The majority of biological traits are genetically complex. Mapping the quantitative trait loci (QTL) that determine these phenotypes is a powerful means for estimating many parameters of the genetic architecture for a trait and potentially identifying the genes responsible for natural variation. Typically, such experiments are conducted in a single mapping population and, therefore, have only the potential to reveal genomic regions that are polymorphic between the progenitors of the population. What remains unclear is how well the QTL identified in any one mapping experiment characterize the genetics that underlie natural variation in traits. Here we provide QTL mapping data for trichome density from four recombinant inbred mapping populations of Arabidopsis thaliana. By aligning the linkage maps for these four populations onto a common physical map, the results from each experiment were directly compared. Seven of the nine QTL identified are population specific while two were mapped in all four populations. Our results show that many lineage-specific alleles that either increase or decrease trichome density persist in natural populations and that most of this genetic variation is additive. More generally, these findings suggest that the use of multiple populations holds great promise for better understanding the genetic architecture of natural variation.
大多数生物学性状在遗传上是复杂的。绘制决定这些表型的数量性状基因座(QTL)图谱是估计性状遗传结构的许多参数并有可能鉴定导致自然变异的基因的有力手段。通常,此类实验在单个作图群体中进行,因此仅有可能揭示群体亲本之间多态的基因组区域。尚不清楚的是,在任何一个作图实验中鉴定出的QTL在多大程度上表征了性状自然变异背后的遗传学。在这里,我们提供了来自拟南芥四个重组自交作图群体的毛状体密度的QTL作图数据。通过将这四个群体的连锁图谱比对到一个共同的物理图谱上,直接比较了每个实验的结果。鉴定出的9个QTL中有7个是群体特异性的,而有2个在所有四个群体中都被定位到。我们的结果表明,许多增加或减少毛状体密度的谱系特异性等位基因在自然群体中持续存在,并且这种遗传变异大多是加性的。更普遍地说,这些发现表明使用多个群体对于更好地理解自然变异的遗传结构具有很大的前景。