ExprAlign--the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles.
ExprAlign--the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles.
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DOI：
10.1186/1471-2164-10-560
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发表时间：
2009-11-26
期刊：
影响因子：
4.4
通讯作者：
Cossins AR
中科院分区：
文献类型：
--
作者：
Li W;Gracey AY;Mello LV;Brass A;Cossins AR
非模式物种的EST序列鉴定提供了独特的挑战，特别是当这些物种有重复的基因组，当他们是在遗传学上远离测序的模式生物。对于鲤鱼，水产养殖的利益，大量的ESTs使用BLAST序列比对仍然不明。我们已经使用大规模微阵列实验的表达谱来提示基因的身份。来自描述7种主要组织对多种环境应激的反应的~700个cDNA微阵列的表达谱被用于定义共表达景观。这是基于Pearson相关系数将每个基因与所有其他基因相关联，由此网络描述将高度相关的基因簇提供为“山”。我们发现，这些包含基因与已知的身份和基因与未知的身份，并在后者的相关性构成身份的证据。结果表明，该方法与2701条未知鲤鱼EST序列中的522条具有相同性。我们还区分了几个常见的鲤鱼基因和基因亚型，不能单独区分BLAST序列比对。通过使用来自多个组织和治疗的数据，识别的精确度得到了显著提高。共表达景观的详细分析是一个敏感的技术，建议大量的BLAST身份不明的cDNA产生的EST项目。它能够检测表达谱中甚至细微的变化，从而将具有共同BLAST身份的基因区分为不同的身份。它受益于多种治疗或对比的使用，以及大规模的微阵列数据。
Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data.
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影响因子：
3
作者：
Christoffels, Alan;Bartfai, Richard;Orban, Laszlo
通讯作者：
Orban, Laszlo
影响因子：
3.4
作者：
McLean, Lynn;Young, Iain S.;Whitfield, Phillip D.
通讯作者：
Whitfield, Phillip D.
影响因子：
3.5
作者：
Kondo, H;Morinaga, K;Watabe, S
通讯作者：
Watabe, S
DOI：
10.1073/pnas.0403627101
发表时间：
2004-11-30
影响因子：
11.1
作者：
Gracey, AY;Fraser, EJ;Cossins, AR
通讯作者：
Cossins, AR
影响因子：
13.8
作者：
MARSH, JJ;LEBHERZ, HG
通讯作者：
LEBHERZ, HG