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		<title>BMC Genomics - Most viewed articles</title>
		<link>http://www.biomedcentral.com/bmcgenomics/mostviewed/</link>
		<description>Most viewed articles in last 30 days from BMC Genomics (ISSN 1471-2164) published by 
				
				BioMed Central
		</description>
        <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
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				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/247"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/77"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/5/96"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/269"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/274"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/285"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/275"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/268"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/265"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2164/9/245"/>			    
            
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		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/247">
            
            <title>Comparative genomic analysis of the gut bacterium Bifidobacterium longum reveals loci susceptible to deletion during pure culture growth</title>
			<description>Background:
Bifidobacteria are frequently proposed to be associated with good intestinal health primarily because of their overriding dominance in the feces of breast fed infants. However, clinical feeding studies with exogenous bifidobacteria show they don't remain in the intestine, suggesting they may lose competitive fitness when grown outside the gut.
Results:
To further the understanding of genetic attenuation that may be occurring in bifidobacteria cultures, we obtained the complete genome sequence of an intestinal isolate, Bifidobacterium longum DJO10A that was minimally cultured in the laboratory, and compared it to that of a culture collection strain, B. longum NCC2705. This comparison revealed colinear genomes that exhibited high sequence identity, except for the presence of 17 unique DNA regions in strain DJO10A and six in strain NCC2705. While the majority of these unique regions encoded proteins of diverse function, eight from the DJO10A genome and one from NCC2705, encoded gene clusters predicted to be involved in diverse traits pertinent to the human intestinal environment, specifically oligosaccharide and polyol utilization, arsenic resistance and lantibiotic production. Seven of these unique regions were suggested by a base deviation index analysis to have been precisely deleted from strain NCC2705 and this is substantiated by a DNA remnant from within one of the regions still remaining in the genome of NCC2705 at the same locus. This targeted loss of genomic regions was experimentally validated when growth of the intestinal B. longum in the laboratory for 1,000 generations resulted in two large deletions, one in a lantibiotic encoding region, analogous to a predicted deletion event for NCC2705. A simulated fecal growth study showed a significant reduced competitive ability of this deletion strain against Clostridium difficile and E. coli. The deleted region was between two IS30 elements which were experimentally demonstrated to be hyperactive within the genome. The other deleted region bordered a novel class of mobile elements, termed mobile integrase cassettes (MIC) substantiating the likely role of these elements in genome deletion events.
Conclusion:
Deletion of genomic regions, often facilitated by mobile elements, allows bifidobacteria to adapt to fermentation environments in a very rapid manner (2 genome deletions per 1,000 generations) and the concomitant loss of possible competitive abilities in the gut.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/247</link>		
			<dc:creator>Ju-Hoon Lee, VN Karamychev, SA Kozyavkin, D Mills, AR Pavlov, NV Pavlova, NN Polouchine, PM Richardson, VV Shakhova, AI Slesarev, B Weimer and DJ O'Sullivan</dc:creator>
			<dc:source>BMC Genomics 2008, 9:247</dc:source>
			<dc:subject>Number of accesses: 1533</dc:subject>
			<dc:date>2008-05-27</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-247</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>247</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-05-27</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/77">
            
            <title>Mobile phone radiation might alter protein expression in human skin</title>
			<description>Background:
Earlier we have shown that the mobile phone radiation (radiofrequency modulated electromagnetic fields; RF-EMF) alters protein expression in human endothelial cell line. This does not mean that similar response will take place in human body exposed to this radiation. Therefore, in this pilot human volunteer study, using proteomics approach, we have examined whether a local exposure of human skin to RF-EMF will cause changes in protein expression in living people.
Results:
Small area of forearm's skin in 10 female volunteers was exposed to RF-EMF (specific absorption rate SAR = 1.3 W/kg) and punch biopsies were collected from exposed and non-exposed areas of skin. Proteins extracted from biopsies were separated using 2-DE and protein expression changes were analyzed using PDQuest software. Analysis has identified 8 proteins that were statistically significantly affected (Anova and Wilcoxon tests). Two of the proteins were present in all 10 volunteers. This suggests that protein expression in human skin might be affected by the exposure to RF-EMF. The number of affected proteins was similar to the number of affected proteins observed in our earlier in vitro studies.
Conclusion:
This is the first study showing that molecular level changes might take place in human volunteers in response to exposure to RF-EMF. Our study confirms that proteomics screening approach can identify protein targets of RF-EMF in human volunteers.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/77</link>		
			<dc:creator>Anu Karinen, Sirpa Hein&#228;vaara, Reetta Nylund and Dariusz Leszczynski</dc:creator>
			<dc:source>BMC Genomics 2008, 9:77</dc:source>
			<dc:subject>Number of accesses: 1396</dc:subject>
			<dc:date>2008-02-11</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-77</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>77</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-02-11</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/5/96">
            
            <title>FunnyBase: a systems level functional annotation of Fundulus ESTs for the analysis of gene expression</title>
			<description>Background:
While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes.
Results:
We describe a bioinformatics pipeline known as FunnyBase that has been used to store, annotate, and analyze 40,363 expressed sequence tags (ESTs) from the heart and liver of the fish, Fundulus heteroclitus. Primary annotations based on sequence similarity are linked to networks of systematic annotation in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and can be queried and computationally utilized in downstream analyses. Steps are taken to ensure that the annotation is self-consistent and that the structure of GO is used to identify higher level functions that may not be annotated directly. An integrated framework for cDNA library production, sequencing, quality control, expression data generation, and systems-level analysis is presented and utilized. In a case study, a set of genes, that had statistically significant regression between gene expression levels and environmental temperature along the Atlantic Coast, shows a statistically significant (P &lt; 0.001) enrichment in genes associated with amine metabolism.
Conclusion:
The methods described have application for functional genomics studies, particularly among non-model organisms. The web interface for FunnyBase can be accessed at http://genomics.rsmas.miami.edu/funnybase/super_craw4/. Data and source code are available by request at jpaschall@bioinfobase.umkc.edu.</description>
			<link>http://www.biomedcentral.com/1471-2164/5/96</link>		
			<dc:creator>Justin E Paschall, Marjorie F Oleksiak, Jeffrey D VanWye, Jennifer L Roach, J Andrew Whitehead, Gerald J Wyckoff, Kevin J Kolell and Douglas L Crawford</dc:creator>
			<dc:source>BMC Genomics 2004, 5:96</dc:source>
			<dc:subject>Number of accesses: 1123</dc:subject>
			<dc:date>2004-12-20</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-5-96</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>5</prism:volume>
					
			
							
					<prism:startingPage>96</prism:startingPage>
					
			
							
					<prism:publicationDate>2004-12-20</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/269">
            
            <title>Identification of Pou5f1, Sox2, and Nanog downstream target genes with statistical confidence by applying a novel algorithm to time course microarray and genome-wide chromatin immunoprecipitation data</title>
			<description>Background:
Target genes of a transcription factor (TF) Pou5f1 (Oct3/4 or Oct4), which is essential for pluripotency maintenance and self-renewal of embryonic stem (ES) cells, have previously been identified based on their response to Pou5f1 manipulation and occurrence of Chromatin-immunoprecipitation (ChIP)-binding sites in promoters. However, many responding genes with binding sites may not be direct targets because response may be mediated by other genes and ChIP-binding site may not be functional in terms of transcription regulation.
Results:
To reduce the number of false positives, we propose to separate responding genes into groups according to direction, magnitude, and time of response, and to apply the false discovery rate (FDR) criterion to each group individually. Using this novel algorithm with stringent statistical criteria (FDR &lt; 0.2) to a compendium of published and new microarray data (3, 6, 12, and 24 hr after Pou5f1 suppression) and published ChIP data, we identified 420 tentative target genes (TTGs) for Pou5f1. The majority of TTGs (372) were down-regulated after Pou5f1 suppression, indicating that the Pou5f1 functions as an activator of gene expression when it binds to promoters. Interestingly, many activated genes are potent suppressors of transcription, which include polycomb genes, zinc finger TFs, chromatin remodeling factors, and suppressors of signaling. Similar analysis showed that Sox2 and Nanog also function mostly as transcription activators in cooperation with Pou5f1.
Conclusion:
We have identified the most reliable sets of direct target genes for key pluripotency genes &#8211; Pou5f1, Sox2, and Nanog, and found that they predominantly function as activators of downstream gene expression. Thus, most genes related to cell differentiation are suppressed indirectly.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/269</link>		
			<dc:creator>Alexei A Sharov, Shinji Masui, Lioudmila V Sharova, Yulan Piao, Kazuhiro Aiba, Ryo Matoba, Li Xin, Hitoshi Niwa and Minoru SH Ko</dc:creator>
			<dc:source>BMC Genomics 2008, 9:269</dc:source>
			<dc:subject>Number of accesses: 1041</dc:subject>
			<dc:date>2008-06-03</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-269</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>269</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-03</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/274">
            
            <title>Highly plastic genome of Microcystis aeruginosa PCC 7806, a ubiquitous toxic freshwater cyanobacterium</title>
			<description>Background:
The colonial cyanobacterium Microcystis proliferates in a wide range of freshwater ecosystems and is exposed to changing environmental factors during its life cycle. Microcystis blooms are often toxic, potentially fatal to animals and humans, and may cause environmental problems. There has been little investigation of the genomics of these cyanobacteria.
Results:
Deciphering the 5,172,804 bp sequence of Microcystis aeruginosa PCC 7806 has revealed the high plasticity of its genome: 11.7% DNA repeats containing more than 1,000 bases, 6.8% putative transposases and 21 putative restriction enzymes. Compared to the genomes of other cyanobacterial lineages, strain PCC 7806 contains a large number of atypical genes that may have been acquired by lateral transfers. Metabolic pathways, such as fermentation and a methionine salvage pathway, have been identified, as have genes for programmed cell death that may be related to the rapid disappearance of Microcystis blooms in nature. Analysis of the PCC 7806 genome also reveals striking novel biosynthetic features that might help to elucidate the ecological impact of secondary metabolites and lead to the discovery of novel metabolites for new biotechnological applications. M. aeruginosa and other large cyanobacterial genomes exhibit a rapid loss of synteny in contrast to other microbial genomes.
Conclusion:
Microcystis aeruginosa PCC 7806 appears to have adopted an evolutionary strategy relying on unusual genome plasticity to adapt to eutrophic freshwater ecosystems, a property shared by another strain of M. aeruginosa (NIES-843). Comparisons of the genomes of PCC 7806 and other cyanobacterial strains indicate that a similar strategy may have also been used by the marine strain Crocosphaera watsonii WH8501 to adapt to other ecological niches, such as oligotrophic open oceans.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/274</link>		
			<dc:creator>Lionel Frangeul, Philippe Quillardet, Anne-Marie Castets, Jean-Fran&#231;ois Humbert, Hans CP Matthijs, Diego Cortez, Andrew Tolonen, Cheng-Cai Zhang, Simonetta Gribaldo, Jan-Christoph Kehr, Yvonne Zilliges, Nadine Ziemert, Sven Becker, Emmanuel Talla, Amel Latifi, Alain Billault, Anthony Lepelletier, Elke Dittmann, Christiane Bouchier and Nicole Tandeau de Marsac</dc:creator>
			<dc:source>BMC Genomics 2008, 9:274</dc:source>
			<dc:subject>Number of accesses: 998</dc:subject>
			<dc:date>2008-06-05</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-274</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>274</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-05</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/285">
            
            <title>Sources of variation in baseline gene expression levels from toxicogenomics study control animals across multiple laboratories</title>
			<description>Background:
The use of gene expression profiling in both clinical and laboratory settings would be enhanced by better characterization of variance due to individual, environmental, and technical factors.  Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies could yield useful information on baseline fluctuations in gene expression, although control animal data has not been available on a scale and in a form best served for data-mining.  
Results:
A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression.  Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions.  Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques.  
Conclusions:
The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state.  These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source.  Genes that are the most and least variable, gender-selective, or altered by fasting were also identified and functionally categorized.  Better characterization of gene expression variability in control animals will aid in the design of toxicogenomics studies and in the interpretation of their results. </description>
			<link>http://www.biomedcentral.com/1471-2164/9/285</link>		
			<dc:creator>Michael J Boedigheimer, Russell D Wolfinger, Michael B Bass, Pierre R Bushel, Jeff W Chou, Matthew Cooper, J. Christopher Corton, Jennifer Fostel, Susan Hester, Janice S Lee, Fenglong Liu, Jie Liu, Hui-Rong Qian, John Quackenbush, Syril Pettit and Karol L Thompson</dc:creator>
			<dc:source>BMC Genomics 2008, 9:285</dc:source>
			<dc:subject>Number of accesses: 923</dc:subject>
			<dc:date>2008-06-12</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-285</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>285</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-12</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/275">
            
            <title>Gene expression in developing watermelon fruit</title>
			<description>Background:
Cultivated watermelon form large fruits that are highly variable in size, shape, color, and content, yet have extremely narrow genetic diversity. Whereas a plethora of genes involved in cell wall metabolism, ethylene biosynthesis, fruit softening, and secondary metabolism during fruit development and ripening have been identified in other plant species, little is known of the genes involved in these processes in watermelon. A microarray and quantitative Real-Time PCR-based study was conducted in watermelon [Citrullus lanatus (Thunb.) Matsum. &amp; Nakai var. lanatus] in order to elucidate the flow of events associated with fruit development and ripening in this species. RNA from three different maturation stages of watermelon fruits, as well as leaf, were collected from field grown plants during three consecutive years, and analyzed for gene expression using high-density photolithography microarrays and quantitative PCR.
Results:
High-density photolithography arrays, composed of probes of 832 EST-unigenes from a subtracted, fruit development, cDNA library of watermelon were utilized to examine gene expression at three distinct time-points in watermelon fruit development. Analysis was performed with field-grown fruits over three consecutive growing seasons. Microarray analysis identified three hundred and thirty-five unique ESTs that are differentially regulated by at least two-fold in watermelon fruits during the early, ripening, or mature stage when compared to leaf. Of the 335 ESTs identified, 211 share significant homology with known gene products and 96 had no significant matches with any database accession. Of the modulated watermelon ESTs related to annotated genes, a significant number were found to be associated with or involved in the vascular system, carotenoid biosynthesis, transcriptional regulation, pathogen and stress response, and ethylene biosynthesis. Ethylene bioassays, performed with a closely related watermelon genotype with a similar phenotype, i.e. seeded, bright red flesh, dark green rind, etc., determined that ethylene levels were highest during the green fruit stage followed by a decrease during the white and pink fruit stages. Additionally, quantitative Real-Time PCR was used to validate modulation of 127 ESTs that were differentially expressed in developing and ripening fruits based on array analysis.
Conclusion:
This study identified numerous ESTs with putative involvement in the watermelon fruit developmental and ripening process, in particular the involvement of the vascular system and ethylene. The production of ethylene during fruit development in watermelon gives further support to the role of ethylene in fruit development in non-climacteric fruits.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/275</link>		
			<dc:creator>W Patrick Wechter, Amnon Levi, Karen R Harris, Angela R Davis, Zhangjun Fei, Nurit Katzir, James J Giovannoni, Ayelet Salman-Minkov, Alvaro Hernandez, Jyothi Thimmapuram, Yaakov Tadmor, Vitaly Portnoy and Tova Trebitsh</dc:creator>
			<dc:source>BMC Genomics 2008, 9:275</dc:source>
			<dc:subject>Number of accesses: 917</dc:subject>
			<dc:date>2008-06-05</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-275</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>275</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-05</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/268">
            
            <title>Modelling and measuring single cell RNA expression levels find considerable transcriptional differences among phenotypically identical cells</title>
			<description>Background:
Phenotypically identical cells demonstrate predictable, robust behaviours. However, there is uncertainty as to whether phenotypically identical cells are equally similar at the underlying transcriptional level or if cellular systems are inherently noisy. To answer this question, it is essential to distinguish between technical noise and true variation in transcript levels. A critical issue is the contribution of sampling effects, introduced by the requirement to globally amplify the single cell mRNA population, to observed measurements of relative transcript abundance.
Results:
We used single cell microarray data to develop simple mathematical models, ran Monte Carlo simulations of the impact of technical and sampling effects on single cell expression data, and compared these with experimental microarray data generated from single embryonic neural stem cells in vivo. We show that the actual distribution of measured gene expression ratios for pairs of neural stem cells is much broader than that predicted from our sampling effect model.
Conclusion:
Our results confirm that significant differences in gene expression levels exist between phenotypically identical cells in vivo, and that these differences exceed any noise contribution from global mRNA amplification.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/268</link>		
			<dc:creator>Tatiana Subkhankulova, Michael J Gilchrist and Frederick J Livesey</dc:creator>
			<dc:source>BMC Genomics 2008, 9:268</dc:source>
			<dc:subject>Number of accesses: 789</dc:subject>
			<dc:date>2008-06-03</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-268</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>268</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-03</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/265">
            
            <title>Genome-wide survey of allele-specific splicing in humans</title>
			<description>Background:
Accurate mRNA splicing depends on multiple regulatory signals encoded in the transcribed RNA sequence. Many examples of mutations within human splice regulatory regions that alter splicing qualitatively or quantitatively have been reported and allelic differences in mRNA splicing are likely to be a common and important source of phenotypic diversity at the molecular level, in addition to their contribution to genetic disease susceptibility. However, because the effect of a mutation on the efficiency of mRNA splicing is often difficult to predict, many mutations that cause disease through an effect on splicing are likely to remain undiscovered.
Results:
We have combined a genome-wide scan for sequence polymorphisms likely to affect mRNA splicing with analysis of publicly available Expressed Sequence Tag (EST) and exon array data. The genome-wide scan uses published tools and identified 30,977 SNPs located within donor and acceptor splice sites, branch points and exonic splicing enhancer elements. For 1,185 candidate splicing polymorphisms the difference in splicing between alternative alleles was corroborated by publicly available exon array data from 166 lymphoblastoid cell lines. We developed a novel probabilistic method to infer allele-specific splicing from EST data. The method uses SNPs and alternative mRNA isoforms mapped to EST sequences and models both regulated alternative splicing as well as allele-specific splicing. We have also estimated heritability of splicing and report that a greater proportion of genes show evidence of splicing heritability than show heritability of overall gene expression level. Our results provide an extensive resource that can be used to assess the possible effect on splicing of human polymorphisms in putative splice-regulatory sites.
Conclusion:
We report a set of genes showing evidence of allele-specific splicing from an integrated analysis of genomic polymorphisms, EST data and exon array data, including several examples for which there is experimental evidence of polymorphisms affecting splicing in the literature. We also present a set of novel allele-specific splicing candidates and discuss the strengths and weaknesses of alternative technologies for inferring the effect of sequence variants on mRNA splicing.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/265</link>		
			<dc:creator>Victoria Nembaware, Bukiwe Lupindo, Katherine Schouest, Charles Spillane, Konrad Scheffler and Cathal Seoighe</dc:creator>
			<dc:source>BMC Genomics 2008, 9:265</dc:source>
			<dc:subject>Number of accesses: 773</dc:subject>
			<dc:date>2008-06-02</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-265</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>265</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-02</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2164/9/245">
            
            <title>Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae</title>
			<description>Background:
Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number of hypothetical proteins accounted for more than 50% of the annotated genes. Considering the industrial importance of this fungus, it is therefore valuable to improve the annotation and further integrate genomic information with biochemical and physiological information available for this microorganism and other related fungi. Here we proposed the gene prediction by construction of an A. oryzae Expressed Sequence Tag (EST) library, sequencing and assembly. We enhanced the function assignment by our developed annotation strategy. The resulting better annotation was used to reconstruct the metabolic network leading to a genome scale metabolic model of A. oryzae.
Results:
Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted in assignment of new putative functions to 1,469 hypothetical proteins already present in the A. oryzae genome database. Using the substantially improved annotated genome we reconstructed the metabolic network of A. oryzae. This network contains 729 enzymes, 1,314 enzyme-encoding genes, 1,073 metabolites and 1,846 (1,053 unique) biochemical reactions. The metabolic reactions are compartmentalized into the cytosol, the mitochondria, the peroxisome and the extracellular space. Transport steps between the compartments and the extracellular space represent 281 reactions, of which 161 are unique. The metabolic model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources.
Conclusion:
A much enhanced annotation of the A. oryzae genome was performed and a genome-scale metabolic model of A. oryzae was reconstructed. The model accurately predicted the growth and biomass yield on different carbon sources. The model serves as an important resource for gaining further insight into our understanding of A. oryzae physiology.</description>
			<link>http://www.biomedcentral.com/1471-2164/9/245</link>		
			<dc:creator>Wanwipa Vongsangnak, Peter Olsen, Kim Hansen, Steen Krogsgaard and Jens Nielsen</dc:creator>
			<dc:source>BMC Genomics 2008, 9:245</dc:source>
			<dc:subject>Number of accesses: 701</dc:subject>
			<dc:date>2008-05-23</dc:date>
			<dc:identifier>doi:10.1186/1471-2164-9-245</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genomics</prism:publicationName>
					
			
							
					<prism:issn>1471-2164</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>245</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-05-23</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
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         <cc:permits rdf:resource="http://creativecommons.org/ns#Reproduction"/>
         <cc:permits rdf:resource="http://creativecommons.org/ns#Distribution"/>
         <cc:permits rdf:resource="http://creativecommons.org/ns#DerivativeWorks"/>
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