<?xml version = '1.0' encoding = 'UTF-8'?>
<?xml-stylesheet href="/rss/styledrssBMC.css" type="text/css"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns="http://purl.org/rss/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:extra="http://www.biomedcentral.com/xml/schemas/extra/" xmlns:prism="http://prismstandard.org/namespaces/1.2/basic/" xmlns:cc="http://web.resource.org/cc/">
	<channel rdf:about="http://www.biomedcentral.com/rss">
		<extra:info rdf:parseType="Literal">
			<html:div xmlns:html="http://www.w3.org/1999/xhtml" style="font:14px Verdana, Geneva, Arial, Helvetica, sans-serif">
				<html:span style="font-weight:bold">This is an RSS newsfeed from BioMed Central</html:span>
				<html:br/>
				<html:span style="font-size: 12px;">It is intended to be used with an RSS reader. For more information about RSS newsfeeds from BioMed Central, visit <html:br/><html:a href="http://www.biomedcentral.com/info/about/rss/" style="color:#3333CC; font-size:12px;">http://www.biomedcentral.com/info/about/rss/</html:a><html:br/>
				</html:span>
			</html:div>
		</extra:info>
		<title>BMC Genetics - Most viewed articles</title>
		<link>http://www.biomedcentral.com/bmcgenet/mostviewed/</link>
		<description>Most viewed articles in last 30 days from BMC Genetics (ISSN 1471-2156) published by 
				
				BioMed Central
		</description>
        <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
         <items>
            <rdf:Seq>
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/9/36"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/9/40"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/9/41"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/9/47"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/9/42"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/9/27"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/9/48"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/5/26"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/9/46"/>			    
            
				    <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2156/9/45"/>			    
            
            </rdf:Seq>
        </items>
    </channel>
    
		<item rdf:about="http://www.biomedcentral.com/1471-2156/9/36">
            
            <title>PGA: power calculator for case-control genetic association analyses</title>
			<description>Background:
Statistical power calculations inform the design and interpretation of genetic association studies, but few programs are tailored to case-control studies of single nucleotide polymorphisms (SNPs) in unrelated subjects.
Results:
We have developed the "Power for Genetic Association analyses" (PGA) package which comprises algorithms and graphical user interfaces for sample size and minimum detectable risk calculations using SNP or haplotype effects under different genetic models and study constrains. The software accounts for linkage disequilibrium and statistical multiple comparisons. The results are presented in graphs or tables and can be printed or exported in standard file formats.
Conclusion:
PGA is user friendly software that can facilitate decision making for association studies of candidate genes, fine-mapping studies, and whole-genome scans. Stand-alone executable files and a Matlab toolbox are available for download at: http://dceg.cancer.gov/bb/tools/pga</description>
			<link>http://www.biomedcentral.com/1471-2156/9/36</link>		
			<dc:creator>Idan Menashe, Philip S Rosenberg and Bingshu E Chen</dc:creator>
			<dc:source>BMC Genetics 2008, 9:36</dc:source>
			<dc:subject>Number of accesses: 822</dc:subject>
			<dc:date>2008-05-13</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-9-36</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>36</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-05-13</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2156/9/40">
            
            <title>Characterization, expression profiles, intracellular distribution and association analysis of porcine PNAS-4 gene with production traits</title>
			<description>Background:
In a previous screen to identify differentially expressed genes associated with embryonic development, the porcine PNAS-4 gene had been found. Considering differentially expressed genes in early stages of muscle development are potential candidate genes to improve meat quality and production efficiency, we determined how porcine PNAS-4 gene regulates meat production. Therefore, this gene has been sequenced, expression analyzed and associated with meat production traits.
Results:
We cloned the full-length cDNA of porcine PNAS-4 gene encoding a protein of 194 amino acids which was expressed in the Golgi complex. This gene was mapped to chromosome 10, q11&#8211;16, in a region of conserved synteny with human chromosome 1 where the human homologous gene was localized. Real-time PCR revealed that PNAS-4 mRNA was widely expressed with highest expression levels in skeletal muscle followed by lymph, liver and other tissues, and showed a down-regulated expression pattern during prenatal development while a up-regulated expression pattern after weaning. Association analysis revealed that allele C of SNP A1813C was prevalent in Chinese indigenous breeds whereas A was dominant allele in Landrace and Large White, and the pigs with homozygous CC had a higher fat content than those of the pigs with other genotypes (P &lt; 0.05).
Conclusion:
Porcine PNAS-4 protein tagged with green fluorescent protein accumulated in the Golgi complex, and its mRNA showed a widespread expression across many tissues and organs in pigs. It may be an important factor affecting the meat production efficiency, because its down-regulated expression pattern during early embryogenesis suggests involvement in increase of muscle fiber number. In addition, the SNP A1813C associated with fat traits might be a genetic marker for molecular-assisted selection in animal breeding.</description>
			<link>http://www.biomedcentral.com/1471-2156/9/40</link>		
			<dc:creator>Delin Mo, Zhengmao Zhu, Marinus FW te Pas, Xinyun Li, Shulin Yang, Heng Wang, Huanling Wang and Kui Li</dc:creator>
			<dc:source>BMC Genetics 2008, 9:40</dc:source>
			<dc:subject>Number of accesses: 486</dc:subject>
			<dc:date>2008-06-30</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-9-40</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>40</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-06-30</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2156/9/41">
            
            <title>Variation at the Calpain 3 gene is associated with meat tenderness in zebu and composite breeds of cattle</title>
			<description>Background:
Quantitative Trait Loci (QTL) affecting meat tenderness have been reported on Bovine chromosome 10. Here we examine variation at the Calpain 3 (CAPN3) gene in cattle, a gene located within the confidence interval of the QTL, and which is a positional candidate gene based on the biochemical activity of the protein.
Results:
We identified single nucleotide polymorphisms (SNP) in the genomic sequence of the CAPN3 gene and tested three of these in a sample of 2189 cattle. Of the three SNP genotyped, the CAPN3:c.1538+225G>T had the largest significant additive effect, with an allele substitution effect in the Brahman of &#945; = -0.144 kg, SE = 0.060, P = 0.016, and the polymorphism explained 1.7% of the residual phenotypic variance in that sample of the breed. Significant haplotype substitution effects were found for all three breeds, the Brahman, the Belmont Red, and the Santa Gertrudis. For the common haplotype, the haplotype substitution effect in the Brahman was &#945; = 0.169 kg, SE = 0.056, P = 0.003. The effect of this gene was compared to Calpastatin in the same sample. The SNP show negligible frequencies in taurine breeds and low to moderate minor allele frequencies in zebu or composite animals.
Conclusion:
These associations confirm the location of a QTL for meat tenderness in this region of bovine chromosome 10. SNP in or near this gene may be responsible for part of the overall difference between taurine and zebu breeds in meat tenderness, and the greater variability in meat tenderness found in zebu and composite breeds. The evidence provided so far suggests that none of these tested SNP are causative mutations.</description>
			<link>http://www.biomedcentral.com/1471-2156/9/41</link>		
			<dc:creator>William Barendse, Blair E Harrison, Rowan J Bunch and Merle B Thomas</dc:creator>
			<dc:source>BMC Genetics 2008, 9:41</dc:source>
			<dc:subject>Number of accesses: 446</dc:subject>
			<dc:date>2008-07-01</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-9-41</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>41</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-07-01</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2156/9/47">
            
            <title>Culture creates genetic structure in the Caucasus: Autosomal, mitochondrial, and Y-chromosomal variation in Daghestan</title>
			<description>Background:
Near the junction of three major continents, the Caucasus region has been an important thoroughfare for human migration. While the Caucasus Mountains have diverted human traffic to the few lowland regions that provide a gateway from north to south between the Caspian and Black Seas, highland populations have been isolated by their remote geographic location and their practice of patrilocal endogamy.  We investigate how these cultural and historical differences between highland and lowland populations have affected patterns of genetic diversity. We test 1) whether the highland practice of patrilocal endogamy has generated sex-specific population relationships, and 2) whether the history of migration and military conquest associated with the lowland populations has left Central Asian genes in the Caucasus, by comparing genetic diversity and pairwise population relationships between Daghestani populations and reference populations throughout Europe and Asia for autosomal, mitochondrial, and Y-chromosomal markers. 
Results:
We found that the highland Daghestani populations had contrasting histories for the mitochondrial DNA and Y-chromosome data sets. Y-chromosomal haplogroup diversity was reduced among highland Daghestani populations when compared to other populations and to highland Daghestani mitochondrial DNA haplogroup diversity. Lowland Daghestani populations showed Turkish and Central Asian affinities for both mitochondrial and Y-chromosomal data sets. Autosomal population histories are strongly correlated to the pattern observed for the mitochondrial DNA data set, while the correlation between the mitochondrial DNA and Y-chromosome distance matrices was weak and not significant. 
Conclusions:
The reduced Y-chromosomal diversity exhibited by highland Daghestani populations is consistent with genetic drift caused by patrilocal endogamy. Mitochondrial and Y-chromosomal phylogeographic comparisons indicate a common Near Eastern origin of highland populations.  Lowland Daghestani populations show varying influence from Near Eastern and Central Asian populations. </description>
			<link>http://www.biomedcentral.com/1471-2156/9/47</link>		
			<dc:creator>Elizabeth E Marchani, W. Scott Watkins, Kazima Bulayeva, Henry C Harpending and Lynn B Jorde</dc:creator>
			<dc:source>BMC Genetics 2008, 9:47</dc:source>
			<dc:subject>Number of accesses: 439</dc:subject>
			<dc:date>2008-07-17</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-9-47</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>47</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-07-17</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2156/9/42">
            
            <title>Combining identity by descent and association in genetic case-control studies</title>
			<description>Background:
In human case-control association studies, one of the chi-square tests typically carried out is based on a 2 &#215; 3 table of genotypes (homogeneity of three genotype frequencies in case and control individuals). We formulate the two degrees of freedom associated with a given genotype distribution in terms of two biologically relevant parameters, (1) the probability F that an individual's two alleles are identical by descent (IBD) and (2) the frequency p of one of the alleles.
Results:
Imposing the restriction, F &#8805; 0, makes some of the genotype frequencies invalid thereby reducing noise. We propose a new statistical association test, the FP test, by focusing on allele frequency differences between case and control individuals while allowing for suitable IBD probabilities. Power calculations show that (1) the practice of generally carrying out two association tests (allele and genotype test) has an increased type I error and (2) our test is more powerful than conventional genotype and allele tests under recessive trait inheritance, and at least as powerful as these conventional tests under dominant inheritance.
Conclusion:
For dominant and recessive modes of inheritance, any apparent power gain by an allele test when carried out in conjunction with a genotype test tends to be purchased entirely by an increased rate of false positive results due to omission of a multiple testing correction. As an alternative to these two standard association tests, our FP test represents a convenient and more powerful alternative.</description>
			<link>http://www.biomedcentral.com/1471-2156/9/42</link>		
			<dc:creator>Qingrun Zhang, Shuang Wang and Jurg Ott</dc:creator>
			<dc:source>BMC Genetics 2008, 9:42</dc:source>
			<dc:subject>Number of accesses: 435</dc:subject>
			<dc:date>2008-07-05</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-9-42</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>42</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-07-05</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2156/9/27">
            
            <title>Improved detection of global copy number variation using high density, non-polymorphic oligonucleotide probes</title>
			<description>Background:
DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500 K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1 kb to over 3 Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay.
Results:
In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3 M independent NspI restriction enzyme fragments in the 200 bp to 1100 bp size range, which is a several fold increase in marker density as compared to the 500 K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries.
Conclusion:
Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization.</description>
			<link>http://www.biomedcentral.com/1471-2156/9/27</link>		
			<dc:creator>Fan Shen, Jing Huang, Karen R Fitch, Vivi B Truong, Andrew Kirby, Wenwei Chen, Jane Zhang, Guoying Liu, Steven A McCarroll, Keith W Jones and Michael H Shapero</dc:creator>
			<dc:source>BMC Genetics 2008, 9:27</dc:source>
			<dc:subject>Number of accesses: 418</dc:subject>
			<dc:date>2008-03-28</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-9-27</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>27</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-03-28</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2156/9/48">
            
            <title>Multitrait Analysis of Quantitative 
Trait Loci Using Bayesian Composite Space Approach
</title>
			<description>Background:
Multitrait analysis of quantitative trait loci can capture the maximum information of experiment. The maximum-likelihood approach and the least-square approach have been developed to jointly analyze multiple traits, but it is difficult for them to include multiple QTL simultaneously into one model.
Result: In this article, we have successfully extended Bayesian composite space approach, which is an efficient model selection method that can easily handle multiple QTL, to multitrait mapping of QTL. There are many statistical innovations of the proposed method compared with Bayesian single trait analysis. The first is that the parameters for all traits are updated jointly by vector or matrix; secondly, for QTL in the same interval that control different traits, the correlation between QTL genotypes is taken into account; thirdly, the information about the relationship of residual error between the traits is also made good use of. The superiority of the new method over separate analysis was demonstrated by both simulated and real data. The computing program was written in FORTRAN and it can be available for request.
Conclusion:
The results suggest that the developed new method is more powerful than separate analysis.</description>
			<link>http://www.biomedcentral.com/1471-2156/9/48</link>		
			<dc:creator>Ming Fang, Dan Jiang, Li JUN Pu, Hui JIANG Gao, Peng Ji, Hong YI Wang and Run QING Yang</dc:creator>
			<dc:source>BMC Genetics 2008, 9:48</dc:source>
			<dc:subject>Number of accesses: 322</dc:subject>
			<dc:date>2008-07-18</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-9-48</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>48</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-07-18</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2156/5/26">
            
            <title>Most of the extant mtDNA boundaries in South and Southwest Asia were likely shaped during the initial settlement of Eurasia by anatomically modern humans</title>
			<description>Background:
Recent advances in the understanding of the maternal and paternal heritage of south and southwest Asian populations have highlighted their role in the colonization of Eurasia by anatomically modern humans. Further understanding requires a deeper insight into the topology of the branches of the Indian mtDNA phylogenetic tree, which should be contextualized within the phylogeography of the neighboring regional mtDNA variation. Accordingly, we have analyzed mtDNA control and coding region variation in 796 Indian (including both tribal and caste populations from different parts of India) and 436 Iranian mtDNAs. The results were integrated and analyzed together with published data from South, Southeast Asia and West Eurasia.
Results:
Four new Indian-specific haplogroup M sub-clades were defined. These, in combination with two previously described haplogroups, encompass approximately one third of the haplogroup M mtDNAs in India. Their phylogeography and spread among different linguistic phyla and social strata was investigated in detail. Furthermore, the analysis of the Iranian mtDNA pool revealed patterns of limited reciprocal gene flow between Iran and the Indian sub-continent and allowed the identification of different assemblies of shared mtDNA sub-clades.
Conclusions:
Since the initial peopling of South and West Asia by anatomically modern humans, when this region may well have provided the initial settlers who colonized much of the rest of Eurasia, the gene flow in and out of India of the maternally transmitted mtDNA has been surprisingly limited. Specifically, our analysis of the mtDNA haplogroups, which are shared between Indian and Iranian populations and exhibit coalescence ages corresponding to around the early Upper Paleolithic, indicates that they are present in India largely as Indian-specific sub-lineages. In contrast, other ancient Indian-specific variants of M and R are very rare outside the sub-continent.</description>
			<link>http://www.biomedcentral.com/1471-2156/5/26</link>		
			<dc:creator>Mait Metspalu, Toomas Kivisild, Ene Metspalu, J&#252;ri Parik, Georgi Hudjashov, Katrin Kaldma, Piia Serk, Monika Karmin, Doron M Behar, M Thomas P Gilbert, Phillip Endicott, Sarabjit Mastana, Surinder S Papiha, Karl Skorecki, Antonio Torroni and Richard Villems</dc:creator>
			<dc:source>BMC Genetics 2004, 5:26</dc:source>
			<dc:subject>Number of accesses: 307</dc:subject>
			<dc:date>2004-08-31</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-5-26</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>5</prism:volume>
					
			
							
					<prism:startingPage>26</prism:startingPage>
					
			
							
					<prism:publicationDate>2004-08-31</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2156/9/46">
            
            <title>Systematic genetic array analysis links the Saccharomyces cerevisiae 
SAGA/SLIK and NuA4 component Tra1 to multiple cellular processes 


</title>
			<description>Background:
Tra1 is an essential 437-kDa component of the Saccharomyces cerevisiae SAGA/SLIK and NuA4 histone acetyltransferase complexes. It is a member of a group of key signaling molecules that share a carboxyl-terminal domain related to phosphatidylinositol-3-kinase but unlike many family members, it lacks kinase activity. To identify genetic interactions for TRA1 and provide insight into its function we have performed a systematic genetic array analysis (SGA) on tra1SRR3413, an allele that is defective in transcriptional regulation.
Results:
The SGA analysis revealed 114 synthetic slow growth/lethal (SSL) interactions for tra1SRR3413. The interacting genes are involved in a range of cellular processes including gene expression, mitochondrial function, and membrane sorting/protein trafficking. In addition many of the genes have roles in the cellular response to stress. A hierarchal cluster analysis revealed that the pattern of SSL interactions for tra1SRR3413 most closely resembles deletions of a group of regulatory GTPases required for membrane sorting/protein trafficking. Deletion of SMI1, one of the genes identified in the SGA analysis and with defined roles in cell wall function and stress response shares several phenotypes with tra1SRR3413. Also consistent with a role for Tra1 in cellular stress, the sensitivity of the tra1SRR3413 strain to calcofluor white was enhanced by the protein kinase inhibitor staurosporine, a phenotype shared with the ada components of the SAGA/SLIK complex. Through analysis of a GFP-Tra1 fusion we show that Tra1 is principally localized to the nucleus. 
Conclusions:
We have demonstrated a genetic association of Tra1 with the processes of membrane sorting and protein trafficking. The identity of the SSL genes also connects Tra1 with cellular stress, a result confirmed by the sensitivity of the tra1SRR3413 strain to a variety of stress conditions. Based upon the nuclear localization of GFP-Tra1 and the finding that deletion of the ada components of the SAGA complex result in similar phenotypes as tra1SRR3413, we suggest that the effects of tra1SRR3413 are mediated, at least in part, through its role in the SAGA complex. </description>
			<link>http://www.biomedcentral.com/1471-2156/9/46</link>		
			<dc:creator>Stephen MT Hoke, Julie Guzzo, Brenda Andrews and Christopher J Brandl</dc:creator>
			<dc:source>BMC Genetics 2008, 9:46</dc:source>
			<dc:subject>Number of accesses: 304</dc:subject>
			<dc:date>2008-07-10</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-9-46</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>46</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-07-10</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
	
		<item rdf:about="http://www.biomedcentral.com/1471-2156/9/45">
            
            <title>High density linkage disequilibrium maps of chromosome 14 in Holstein and Angus cattle</title>
			<description>Background:
Linkage disequilibrium (LD) maps can provide a wealth of information on specific marker-phenotype relationships, especially in areas of the genome where positional candidate genes with similar functions are located. A recently published high resolution radiation hybrid map of bovine chromosome 14 (BTA14) together with the bovine physical map have enabled the creation of more accurate LD maps for BTA14 in both dairy and beef cattle.
Results:
Over 500 Single Nucleotide Polymorphism (SNP) markers from both Angus and Holstein animals had their phased haplotypes estimated using GENOPROB and their pairwise r2 values compared. For both breeds, results showed that average LD extends at moderate levels up to 100 kilo base pairs (kbp) and falls to background levels after 500 kbp. Haplotype block structure analysis using HAPLOVIEW under the four gamete rule identified 122 haplotype blocks for both Angus and Holstein. In addition, SNP tagging analysis identified 410 SNPs and 420 SNPs in Holstein and Angus, respectively, for future whole genome association studies on BTA14. Correlation analysis for marker pairs common to these two breeds confirmed that there are no substantial correlations between r-values at distances over 10 kbp. Comparison of extended haplotype homozygosity (EHH), which calculates the LD decay away from a core haplotype, shows that in Holstein there is long range LD decay away from the DGAT1 region consistent with the selection for milk fat % in this population. Comparison of EHH values for Angus in the same region shows very little long range LD.
Conclusion:
Overall, the results presented here can be applied in future single or haplotype association analysis for both populations, aiding in confirming or excluding potential polymorphisms as causative mutations, especially around Quantitative Trait Loci regions. In addition, knowledge of specific LD information among markers will aid the research community in selecting appropriate markers for whole genome association studies.</description>
			<link>http://www.biomedcentral.com/1471-2156/9/45</link>		
			<dc:creator>Elisa Marques, Robert D Schnabel, Paul Stothard, Davood Kolbehdari, Zhiquan Wang, Jeremy F Taylor and Stephen S Moore</dc:creator>
			<dc:source>BMC Genetics 2008, 9:45</dc:source>
			<dc:subject>Number of accesses: 282</dc:subject>
			<dc:date>2008-07-08</dc:date>
			<dc:identifier>doi:10.1186/1471-2156-9-45</dc:identifier>
			
			
							
					<prism:publicationName>BMC Genetics</prism:publicationName>
					
			
							
					<prism:issn>1471-2156</prism:issn>
					
			
							
					<prism:volume>9</prism:volume>
					
			
							
					<prism:startingPage>45</prism:startingPage>
					
			
							
					<prism:publicationDate>2008-07-08</prism:publicationDate>
					

            <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/"/>
        </item>
		
	<cc:License rdf:about="http://creativecommons.org/licenses/by/2.0/">
         <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"/>
	</cc:License>
</rdf:RDF>
