SuperSAGE: the drought stress-responsive transcriptome of chickpea roots.
SuperSAGE: the drought stress-responsive transcriptome of chickpea roots.
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DOI：
10.1186/1471-2164-9-553
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发表时间：
2008-11-24
期刊：
影响因子：
4.4
通讯作者：
Winter P
中科院分区：
文献类型：
--
作者：
Molina C;Rotter B;Horres R;Udupa SM;Besser B;Bellarmino L;Baum M;Matsumura H;Terauchi R;Kahl G;Winter P
干旱是鹰嘴豆 (Cicer arietinum) 增产的主要制约因素。因此，提高耐旱性对于育种至关重要。然而，该性状的复杂性只允许取得微小的进展。创新的分子工具有望解决当前的停滞问题，例如转录组分析，提供对应激相关基因活性的洞察，与分子标记和表达（e）QTL作图相结合，可能会加速基于知识的育种。 SuperSAGE 是基因表达系列分析 (SAGE) 技术的改进版本，可从任何真核生物生成全基因组、高质量的转录谱，已在本研究中使用。该方法从 cDNA 中的指定位置产生 26 bp 长的片段（26 bp 标签），提供足够的序列信息来明确表征 mRNA。此外，SuperSAGE 标签可立即用于生产用于实时 PCR 的微阵列和探针，从而克服非模型生物中基因组工具的缺乏。我们应用 SuperSAGE 来分析鹰嘴豆根响应干旱的基因表达。为此，我们对 80,238 个 26 bp 标签进行了测序，这些标签代表来自干旱胁迫和非胁迫对照根的 17,493 个独特转录本 (UniTags)。总共 7,532 个（43%）UniTags 差异表达超过 2.7 倍，880 个（5.0%）UniTags 在应激时受到调节超过 8 倍。它们的大尺寸使得 3,858 (22%) UniTags 能够对公共数据库中的基因或蛋白质进行明确注释，从而对应激反应过程进行明确注释。我们设计了一个带有 3,000 个这样的 26 bp 标签的微阵列。芯片数据证实了 79% 的基于标签的结果，而 RT-PCR 证实了所有情况下的 SuperSAGE 数据。这项研究代表了迄今为止对鹰嘴豆干旱反应转录组最全面的分析。它表明，除其他外，在干旱胁迫后 6 小时，鹰嘴豆根中的信号转导、转录调节、渗透剂积累和 ROS 清除已经发生了强烈的转录重塑。表征这些过程的某些转录亚型是耐旱育种的潜在目标。我们证明这些可以通过 SuperSAGE 下游容易产生的微阵列和 RT-PCR 检测轻松获得。我们的研究证明 SuperSAGE 在非模式作物中也具有分子育种的潜力。
Drought is the major constraint to increase yield in chickpea (Cicer arietinum). Improving drought tolerance is therefore of outmost importance for breeding. However, the complexity of the trait allowed only marginal progress. A solution to the current stagnation is expected from innovative molecular tools such as transcriptome analyses providing insight into stress-related gene activity, which combined with molecular markers and expression (e)QTL mapping, may accelerate knowledge-based breeding. SuperSAGE, an improved version of the serial analysis of gene expression (SAGE) technique, generating genome-wide, high-quality transcription profiles from any eukaryote, has been employed in the present study. The method produces 26 bp long fragments (26 bp tags) from defined positions in cDNAs, providing sufficient sequence information to unambiguously characterize the mRNAs. Further, SuperSAGE tags may be immediately used to produce microarrays and probes for real-time-PCR, thereby overcoming the lack of genomic tools in non-model organisms. We applied SuperSAGE to the analysis of gene expression in chickpea roots in response to drought. To this end, we sequenced 80,238 26 bp tags representing 17,493 unique transcripts (UniTags) from drought-stressed and non-stressed control roots. A total of 7,532 (43%) UniTags were more than 2.7-fold differentially expressed, and 880 (5.0%) were regulated more than 8-fold upon stress. Their large size enabled the unambiguous annotation of 3,858 (22%) UniTags to genes or proteins in public data bases and thus to stress-response processes. We designed a microarray carrying 3,000 of these 26 bp tags. The chip data confirmed 79% of the tag-based results, whereas RT-PCR confirmed the SuperSAGE data in all cases. This study represents the most comprehensive analysis of the drought-response transcriptome of chickpea available to date. It demonstrates that – inter alias – signal transduction, transcription regulation, osmolyte accumulation, and ROS scavenging undergo strong transcriptional remodelling in chickpea roots already 6 h after drought stress. Certain transcript isoforms characterizing these processes are potential targets for breeding for drought tolerance. We demonstrate that these can be easily accessed by micro-arrays and RT-PCR assays readily produced downstream of SuperSAGE. Our study proves that SuperSAGE owns potential for molecular breeding also in non-model crops.
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