Reuveni Eli, Ramensky Vasily E, Gross Cornelius
Mouse Biology Unit, EMBL, Via Ramarini 32, 00016 Monterotondo, Italy.
BMC Genomics. 2007 Jan 21;8:24. doi: 10.1186/1471-2164-8-24.
The mapping of quantitative trait loci in rat and mouse has been extremely successful in identifying chromosomal regions associated with human disease-related phenotypes. However, identifying the specific phenotype-causing DNA sequence variations within a quantitative trait locus has been much more difficult. The recent availability of genomic sequence from several mouse inbred strains (including C57BL/6J, 129X1/SvJ, 129S1/SvImJ, A/J, and DBA/2J) has made it possible to catalog DNA sequence differences within a quantitative trait locus derived from crosses between these strains. However, even for well-defined quantitative trait loci (<10 Mb) the identification of candidate functional DNA sequence changes remains challenging due to the high density of sequence variation between strains.
To help identify functional DNA sequence variations within quantitative trait loci we have used the Ensembl annotated genome sequence to compile a database of mouse single nucleotide polymorphisms (SNPs) that are predicted to cause missense, nonsense, frameshift, or splice site mutations (available at http://bioinfo.embl.it/SnpApplet/). For missense mutations we have used the PolyPhen and PANTHER algorithms to predict whether amino acid changes are likely to disrupt protein function.
We have developed a database of mouse SNPs predicted to cause missense, nonsense, frameshift, and splice-site mutations. Our analysis revealed that 20% and 14% of missense SNPs are likely to be deleterious according to PolyPhen and PANTHER, respectively, and 6% are considered deleterious by both algorithms. The database also provides gene expression and functional annotations from the Symatlas, Gene Ontology, and OMIM databases to further assess candidate phenotype-causing mutations. To demonstrate its utility, we show that Mouse SNP Miner successfully finds a previously identified candidate SNP in the taste receptor, Tas1r3, that underlies sucrose preference in the C57BL/6J strain. We also use Mouse SNP Miner to derive a list of candidate phenotype-causing mutations within a previously uncharacterized QTL for response to morphine in the 129/Sv strain.
在大鼠和小鼠中对数量性状基因座进行定位，在识别与人类疾病相关表型相关的染色体区域方面极其成功。然而，在一个数量性状基因座内鉴定导致特定表型的DNA序列变异则困难得多。最近，几种小鼠近交系（包括C57BL/6J、129X1/SvJ、129S1/SvImJ、A/J和DBA/2J）的基因组序列可用，这使得对这些品系杂交产生的数量性状基因座内的DNA序列差异进行编目成为可能。然而，即使对于定义明确的数量性状基因座（<10 Mb），由于品系间序列变异的高密度，鉴定候选功能性DNA序列变化仍然具有挑战性。
为了帮助识别数量性状基因座内的功能性DNA序列变异，我们使用了Ensembl注释的基因组序列来编制一个小鼠单核苷酸多态性（SNP）数据库，这些SNP预计会导致错义、无义、移码或剪接位点突变（可在http://bioinfo.embl.it/SnpApplet/获取）。对于错义突变，我们使用了PolyPhen和PANTHER算法来预测氨基酸变化是否可能破坏蛋白质功能。
我们开发了一个小鼠SNP数据库，预计这些SNP会导致错义、无义、移码和剪接位点突变。我们的分析表明，根据PolyPhen和PANTHER算法，分别有20%和14%的错义SNP可能有害，两种算法都认为6%的错义SNP有害。该数据库还提供了来自Symatlas、基因本体论和OMIM数据库的基因表达和功能注释，以进一步评估候选的导致表型的突变。为了证明其效用，我们展示了Mouse SNP Miner成功地在味觉受体Tas1r3中找到了一个先前鉴定的候选SNP，它是C57BL/6J品系中蔗糖偏好的基础。我们还使用Mouse SNP Miner得出了129/Sv品系中一个先前未表征的对吗啡反应的数量性状基因座内候选的导致表型的突变列表。
