Department of Biology, Centre for Biodiversity Dynamics, Norwegian University of Science and Technology, Trondheim, Norway.
Mol Ecol Resour. 2013 May;13(3):429-39. doi: 10.1111/1755-0998.12088. Epub 2013 Mar 9.
With the advent of next generation sequencing, new avenues have opened to study genomics in wild populations of non-model species. Here, we describe a successful approach to a genome-wide medium density Single Nucleotide Polymorphism (SNP) panel in a non-model species, the house sparrow (Passer domesticus), through the development of a 10 K Illumina iSelect HD BeadChip. Genomic DNA and cDNA derived from six individuals were sequenced on a 454 GS FLX system and generated a total of 1.2 million sequences, in which SNPs were detected. As no reference genome exists for the house sparrow, we used the zebra finch (Taeniopygia guttata) reference genome to determine the most likely position of each SNP. The 10 000 SNPs on the SNP-chip were selected to be distributed evenly across 31 chromosomes, giving on average one SNP per 100 000 bp. The SNP-chip was screened across 1968 individual house sparrows from four island populations. Of the original 10 000 SNPs, 7413 were found to be variable, and 99% of these SNPs were successfully called in at least 93% of all individuals. We used the SNP-chip to demonstrate the ability of such genome-wide marker data to detect population sub-division, and compared these results to similar analyses using microsatellites. The SNP-chip will be used to map Quantitative Trait Loci (QTL) for fitness-related phenotypic traits in natural populations.
随着下一代测序技术的出现,为非模式物种的野生种群研究基因组学开辟了新的途径。在这里,我们描述了一种在非模式物种家麻雀(Passer domesticus)中成功开发全基因组中等密度单核苷酸多态性(SNP)面板的方法,该方法是通过开发 10K Illumina iSelect HD BeadChip 实现的。从六个个体中提取基因组 DNA 和 cDNA,在 454 GS FLX 系统上进行测序,总共产生了 120 万个序列,从中检测到 SNP。由于家麻雀没有参考基因组,我们使用斑马雀(Taeniopygia guttata)参考基因组来确定每个 SNP 的最可能位置。SNP 芯片上的 10000 个 SNP 被选择均匀分布在 31 条染色体上,平均每条染色体上有一个 SNP,每个 SNP 之间的距离为 100000bp。SNP 芯片在来自四个岛屿种群的 1968 只家麻雀个体上进行了筛选。在最初的 10000 个 SNP 中,有 7413 个是可变异的,其中 99%的 SNP 在至少 93%的个体中成功被检测到。我们使用 SNP 芯片证明了这种全基因组标记数据检测种群细分的能力,并将这些结果与使用微卫星进行的类似分析进行了比较。SNP 芯片将用于在自然种群中绘制与适应相关表型性状的数量性状基因座(QTL)。