Realizing the Potential of the Genome Revolution: The Genomes to Life Program

Frazier, M.E.; Johnson, Gary M.; Thomassen, David G.; Oliver, C.E.

doi:10.1126/science.1084566

Cited by 70 publications

(41 citation statements)

References 4 publications

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“…We were also able to identify homologs for nearly all (520, 97% of 538) expressed proteins. The existence of such a large and uncharacterized group of genes that are conserved among a variety of organisms is disconcerting in that it highlights major gaps in our understanding of basic biology (2,(7)(8)(9)(10)(11)(12)(13)22). Using a tiered-based annotation approach, this study significantly or modestly improved annotations for 256 proteins (categories 1-5; 48% of 538).…”

Section: Discussionmentioning

confidence: 92%

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Global profiling of Shewanella oneidensis MR-1: Expression of hypothetical genes and improved functional annotations

Kolker

Picone

Galperin

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

114

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The ␥-proteobacterium Shewanella oneidensis strain MR-1 is a metabolically versatile organism that can reduce a wide range of organic compounds, metal ions, and radionuclides. Similar to most other sequenced organisms, Ϸ40% of the predicted ORFs in the S. oneidensis genome were annotated as uncharacterized ''hypothetical'' genes. We implemented an integrative approach by using experimental and computational analyses to provide more detailed insight into gene function. Global expression profiles were determined for cells after UV irradiation and under aerobic and suboxic growth conditions. Transcriptomic and proteomic analyses confidently identified 538 hypothetical genes as expressed in S. oneidensis cells both as mRNAs and proteins (33% of all predicted hypothetical proteins). Publicly available analysis tools and databases and the expression data were applied to improve the annotation of these genes. The annotation results were scored by using a seven-category schema that ranked both confidence and precision of the functional assignment. We were able to identify homologs for nearly all of these hypothetical proteins (97%), but could confidently assign exact biochemical functions for only 16 proteins (category 1; 3%). Altogether, computational and experimental evidence provided functional assignments or insights for 240 more genes (categories 2-5; 45%). These functional annotations advance our understanding of genes involved in vital cellular processes, including energy conversion, ion transport, secondary metabolism, and signal transduction. We propose that this integrative approach offers a valuable means to undertake the enormous challenge of characterizing the rapidly growing number of hypothetical proteins with each newly sequenced genome.computational biology ͉ expression analysis ͉ microarrays ͉ proteomics ͉ integrative microbiology

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Section: Discussionmentioning

confidence: 92%

“…It is currently the subject of comprehensive study by the Shewanella Federation, a multiinstitutional consortium supported through the U.S. Department of Energy Genomics: GTL program (ref. 2; http:͞͞doegenomestolife. org).…”

mentioning

confidence: 99%

Global profiling of Shewanella oneidensis MR-1: Expression of hypothetical genes and improved functional annotations

Kolker

Picone

Galperin

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

114

View full text Add to dashboard Cite

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“…The very idea that there are important genes whose functions are still obscure is quite unsettling as it reveals that there are still important gaps in our understanding of basic (micro)biology (9,10). Our recent study of the H.in¯uenzae proteome identi®ed 15`conserved hypothetical' proteins that were con®dently detected in aerobically grown cells (11) and whose genes were found to be essential in transposon mutagenesis studies (12).…”

Section: Introductionmentioning

confidence: 99%

Identification and functional analysis of 'hypothetical' genes expressed in Haemophilus influenzae

Kolker¹,

Makarova

Shabalina

et al. 2004

Nucleic Acids Research

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The progress in genome sequencing has led to a rapid accumulation in GenBank submissions of uncharacterized`hypothetical' genes. These genes, which have not been experimentally characterized and whose functions cannot be deduced from simple sequence comparisons alone, now comprise a signi®cant fraction of the public databases. Expression analyses of Haemophilus in¯uenzae cells using a combination of transcriptomic and proteomic approaches resulted in con®dent identi®ca-tion of 54`hypothetical' genes that were expressed in cells under normal growth conditions. In an attempt to understand the functions of these proteins, we used a variety of publicly available analysis tools. Close homologs in other species were detected for each of the 54`hypothetical' genes. For 16 of them, exact functional assignments could be found in one or more public databases. Additionally, we were able to suggest general functional characterization for 27 more genes (comprising~80% total). Findings from this analysis include the identi®cation of a pyruvate-formate lyase-like operon, likely to be expressed not only in H.in¯uenzae but also in several other bacteria. Further, we also observed three genes that are likely to participate in the transport and/or metabolism of sialic acid, an important component of the H.in¯uenzae lipo-oligosaccharide. Accurate functional annotation of uncharacterized genes calls for an integrative approach, combining expression studies with extensive computational analysis and curation, followed by eventual experimental veri®cation of the computational predictions.

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“…1) with an additional written description, whereas quantitative models are commonly represented by mathematical expressions. Recently, the rate at which data are acquired in molecular biology research, has increased tremendously and it is considered to be a great challenge to build models to account for these data (Frazier et al, 2003;Nurse, 2003). Surprisingly however, model building generally receives relatively little attention during a molecular life sciences curriculum.…”

Section: Introductionmentioning

confidence: 99%

Digital Learning Material for Model Building in Molecular Biology

et al. 2005

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Building models to describe processes forms an essential part of molecular biology research. However, in molecular biology curricula little attention is generally being paid to the development of this skill. In order to provide students the opportunity to improve their model building skills, we decided to develop a number of digital cases about developmental biology. In these cases the students are guided to build a model according to a method that is based on expert analysis and historical data; they first build a simplified model based on the wild-type only and then they extend this model step by step based on experimental results. After each extension, the biological implications of the extension are evaluated. The first case was evaluated three times during a regular course at Wageningen University, The Netherlands and once at the University of Zurich, Switzerland. The analysis of audiotapes revealed that students did indeed engage in the reasoning processes, which are typical for model building. Furthermore, exam results seem to suggest that working with the case indeed facilitates model building in analogical situations and the students judged working with the case positively.

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Realizing the Potential of the Genome Revolution: The Genomes to Life Program

Cited by 70 publications

References 4 publications

Global profiling of Shewanella oneidensis MR-1: Expression of hypothetical genes and improved functional annotations

Global profiling of Shewanella oneidensis MR-1: Expression of hypothetical genes and improved functional annotations

Identification and functional analysis of 'hypothetical' genes expressed in Haemophilus influenzae

Digital Learning Material for Model Building in Molecular Biology

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