4.4 Article

The proteome of Toxoplasma gondii: integration with the genome provides novel insights into gene expression and annotation

期刊

GENOME BIOLOGY
卷 9, 期 7, 页码 -

出版社

BIOMED CENTRAL LTD
DOI: 10.1186/gb-2008-9-7-r116

关键词

-

资金

  1. UK Biotechnology and Biological Science Research Council [BBS/B/03807]
  2. National Institute of Allergy and Infectious Diseases [NIH-NIAID-DMID-BAA-03-38]
  3. National Institute of Health [NIH P41 RR11823]
  4. Department of Health and Human Services [HHSN266200400037C]
  5. Biotechnology and Biological Sciences Research Council [BBS/B/03742, BBS/B/03807, BBS/B/03858] Funding Source: researchfish
  6. NATIONAL CENTER FOR RESEARCH RESOURCES [P41RR011823] Funding Source: NIH RePORTER

向作者/读者索取更多资源

Background: Although the genomes of many of the most important human and animal pathogens have now been sequenced, our understanding of the actual proteins expressed by these genomes and how well they predict protein sequence and expression is still deficient. We have used three complementary approaches (two-dimensional electrophoresis, gel-liquid chromatography linked tandem mass spectrometry and MudPIT) to analyze the proteome of Toxoplasma gondii, a parasite of medical and veterinary significance, and have developed a public repository for these data within ToxoDB, making for the first time proteomics data an integral part of this key genome resource. Results: The draft genome for Toxoplasma predicts around 8,000 genes with varying degrees of confidence. Our data demonstrate how proteomics can inform these predictions and help discover new genes. We have identified nearly one-third (2,252) of all the predicted proteins, with 2,477 intron-spanning peptides providing supporting evidence for correct splice site annotation. Functional predictions for each protein and key pathways were determined from the proteome. Importantly, we show evidence for many proteins that match alternative gene models, or previously unpredicted genes. For example, approximately 15% of peptides matched more convincingly to alternative gene models. We also compared our data with existing transcriptional data in which we highlight apparent discrepancies between gene transcription and protein expression. Conclusion: Our data demonstrate the importance of protein data in expression profiling experiments and highlight the necessity of integrating proteomic with genomic data so that iterative refinements of both annotation and expression models are possible.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.4
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据