An easy-to-use qPCR resource, Bio-Rad’s Real-Time PCR iPhone application includes the Real-Time PCR Applications Guide for researchers who want to learn more about designing, analyzing, and optimizing real-time PCR experiments. Another feature is the qPCR Doctor, an interactive troubleshooting tool for resolving problems relating to real-time PCR assays. The Real-Time PCR iPhone Application also includes a qPCR Assay Design section which provides guidance for designing a qPCR assay, information on validating and optimizing your qPCR assay, and different methods for analyzing qPCR data. This application puts three of Bio-Rad’s best real-time PCR resources at your fingertips.
Posts Tagged ‘SNP Analysis’
A couple of months ago we told you about the collaborative cross project which strives to increase the SNP count among the lab mouse population by interbreeding five classic inbred mouse strains and three wild-derived strains (see Adding Lab Mice to Your Spice Cupboard).
This week, th collaborative cross project has announced that three articles have been published online in-advance in Genome Research utilizing strains from the emerging Collaborative Cross mouse strains.
The three studies are as follows:
1. Collaborative Cross strains facilitate mapping of causative loci
In this work, Aylor and colleagues performed an experiment called the “the pre-CC study,” the first genetic data and analysis from the emerging strains of the CC. Their investigation revealed that the genomes of CC strains are genetically diverse and contain balanced contributions from each founding strain. Highlighting the statistical power provided by the CC, Aylor et al. utilized ancestry information of the CC strains to map genetic loci for a Mendelian trait (white head-spotting), a complex trait (body weight), and a molecular trait (gene expression in the liver), demonstrating the ancestry-based approach to be superior to established marker-based methods for trait loci discovery.
Reference: Aylor DL et al. Genetic analysis of complex traits in the emerging collaborative cross. Genome Res. doi: 10.1101/gr.111310.110
2. Breeding effects in the Collaborative Cross
The development of the Collaborative Cross presents a unique opportunity to investigate how the breeding of inbred strains affects genetic structure and the diversity of phenotypes. In this paper, Philip et al. have evaluated the range of many traits in late inbreeding populations of the CC, including such phenotypes as body weight, tail length, heart weight, and behavioral traits. Despite the influence of breeding selection in the CC lines, detection of major genetic loci regulating trait variation remained possible. This analysis revealed the scope of phenotypic variation that will be present in the finished strains of the CC.
Reference: Philip VM et al. Genetic analysis in the Collaborative Cross breeding population. Genome Res. doi: 10.1101/gr.113886.110
3. Mapping host susceptibility to fungal infection
Aspergillosis is a serious disease in humans, particularly in immune-compromised individuals, caused by infection with the fungus Aspergillus. The mouse has been an important model for studying Aspergillus infection, but classical laboratory strains of mice used in these studies arose from a small set of founders and lack most of the genetic variation present in wild mice, limiting researchers’ ability to identify additional genetic loci relevant to disease.
In this study, Durrant and colleagues utilized inbred mouse strains from the Collaborative Cross, taking advantage of the genetic contribution of wild-derived strains, to identify novel loci that confer susceptibility to infection with the fungus Aspergillus. By integrating genetic variation data from the genomes of the founding strains of the CC, Durrant et al. further refined the genetic loci associated with Aspergillus susceptibility to suggest specific candidate genes.
Reference: Durrant C et al. Collaborative Cross mice and their power to map host susceptibility to Aspergillus fumigatus infection. Genome Res. doi: 10.1101/gr.118786.110
source: EurekAlert! press release
If variety is the spice of life, then genetic variability among species is king of the spice rack. While there are tens of thousands of protein-coding genes in the human genome, (estimates range from 23,000 to 30,000), there are tens of millions of single nucleotide polymorphisms (SNP) that exponentially influence the diversity of our gene pool. Initiatives such as the International Hap Map Project provide valuable data on common patterns of human genetic variation and are an important resources for scientists studying mechanisms of human health and disease.
On the other hand, there is a plethora of scientific information on health and disease obtained through studies involving the common laboratory mouse. Considering the importance of genetic variety among humans, it is therefore suprising to learn that the majority of mouse strains used in the laboratory have very little genetic variablity from strain to strain. In a recent paper published in Nature Genetics, the authors estimate that standard laboratory mouse strains carry about 12 million SNPs, which is a fraction of the SNP variation likely to be found among wild-caught mice.
In an effort to compare the genomic data among the various lab strains of mice, the team created the Mouse Phylogeny Viewer which allows researchers to compare the differences and similarities between strains and select the ones most likely to provide the basis for experimental results that can be more effectively extrapolated to the diverse human population.
The authors also suggest that increasing genetic diversity among the lab mouse population would greatly aide in the translatability of data obtained in mice to humans. As such, the authors launched the Collaborative Cross project which has interbred five classic inbred mouse strains and three wild-derived strains and has increased the SNP count from 12 million to 45 million among the lab mouse population.
Reference: Yang et al.: Subspecific origin and haplotype diversity in the laboratory mouse. Nature Genetics, advance online publication Sunday, May 29, 2011.
Sources: Jackson Laboratory
The world of personal genomics is becoming more accessible to the masses and the amount of information available to the general public is truly stunning. Today 5AM Solutions, a life science software engineering firm, announced the release of SNPTips, a Firefox browser plug-in that connects a user’s 23andMe personal genetic information to web content with a single mouse click.
Personal genetic testing services such as 23andMe provide genetic testing for individuals outside of a physician’s office. These services typically probe a person’s genome for thousands of single nucleotide polymorphisms (SNPs) that represent potentially important or interesting genomics differences between one person and another. 23andMe provides tools and reports for interpreting this information. For a user interested in connecting his or her genetic information with the treasury of literature and information on the World Wide Web, there’s no clear way to make the link. Which is why 5AM created SNPTips.
“SNPTips links your 23andMe raw data to SNP IDs that are mentioned in across a sea of web content. With the click of a mouse, you can view your personal genotype at any SNP mentioned the web – such as a genetics blog or journal article. SNPTips also includes smart links to other web resources, like SNPedia, Google Scholar, and NHGRI’s dbSNP – so you can delve deeper with a single click,” said Will FitzHugh, 5AM’s Chief Science Officer. “We started with 23andMe because it’s the market leader in personal genetics. We anticipate expanding SNPTips in the future to support other personal genetics services and browsers.”
“Our company works to make the web the place for life science collaboration,” said 5AM’s President & CEO, Brent Gendleman. “SNPTips brings that ability directly to consumers of personal genomic information. People can translate their genetic information into what they want to know, right through the browser. It can’t get more convenient than that.”
“The very existence of 23andMe allowed us to innovate and meet a need that leveraged what they do, extending it in a simple way through a common mechanism – the browser. SNPTips represents a way to extend their work, furthering people’s ability to tackle the complexity of genomics in a way that is straightforward and consumable by a wide audience,” said Gendleman.
SNPTips makes use of a person’s complete 23andMe SNP raw data profile, and requires that a user safeguard the use of that information by employing it only on a machine under his or her control. SNPTips does not move any personal information across the Internet.
SNPTips is available for free at http://snptips.com and requires a Firefox 3.6+ browser.
About 5AM Solutions
5AM Solutions develops innovative software solutions for academic, government, commercial, and non-profit life sciences organizations. The company helps evolve the way biomedical researchers work and collaborate by using software to reveal new insights hidden in vast amounts of data, facilitate translational research, and solve workflow challenges. The company’s solutions can overcome IT-based roadblocks to discovery and accelerate progress toward the ultimate goal of better health and improved patient outcomes.
For information on SNPTips, visit http://www.snptips.com. To install on a Firefix 3.6+ browser, simply click the Install Now button, and follow the directions on the website to configure. SNPTips is free, and is released under the Creative Commons Attribution-ShareAlike 3.0 Unported license.
SNPTips is not affiliated with 23andMe. SNPTips is a product and a trademark of 5AM Solutions, Inc. 5AM Solutions makes no claims regarding, and is not responsible for, 23andMe’s content, products, or services. Visit http://www.23andme.com for information on 23andMe.
source:PRWeb press release
Double stranded DNA (dsDNA) melts at a temperature that is determined by its length (i.e. the number of base pairs) and nucleotide sequence composition. In general, longer strands of DNA and strands consisting of more “G”s and “C”s melt at higher temperatures than shorter strands and strands consisting of “A”s and “T”s. As such, every dsDNA molecule has a unique melting fingerprint which can be used to differentiate one strand of DNA from another. Over the past 10-15 years great advances have been made in utilizing this feature in DNA-based research. One example is the discrimination of Single Nucleotide Polymorphisms (SNP) which occurs when a single nucleotide differs between members of a species or paired chromosomes in an individual. SNPs play an important role in the development of disease and can serve as significant biomarkers under various conditions. Because SNPs involve the substitution of a single nucleotide within a DNA fragment, the resulting DNA fragment has a different melting temperature then its native form. When DNA melting analysis is coupled with a technique such as real-time PCR the result is a powerful tool for detecting SNPs from small amounts of starting material.
Precision Melt Analysis software imports and analyzes data files generated from Bio-Rad Laboratories’ CFX96 or CFX384 real-time PCR detection system to genotype samples based on the thermal denaturation properties of double-stranded DNA. The software can be used for a variety of genotyping applications, including scanning for new gene variants, screening DNA samples for SNPs, identifying insertions/deletions or other unknown mutations, and determining the percentage of methylated DNA in unknown samples. Use the default analysis settings to automatically normalize data and assign a genotype to each sample based on its melt characteristics — there is no need to include genotype controls to assign cluster labels.
Precision Melt Analysis software saves analysis time by assigning sample genotypes automatically based on cluster analysis, or manually using multiple data view options to tailor the software to the appropriate analysis. Use the normalized melt curves plot feature to generate a basic representation of the different clusters based on curve shifting (for homozygotes) and curve shape change (for heterozygotes). Difference curve plots of a sample fluorescence versus a selected control at each temperature transition provide a convenient visual aid to interpret the data.
Precision Melt Analysis software enables data comparison between multiple file runs by combining data into a single Melt Study. Develop a standard library of melt-curve runs to analyze an unlimited number of melt experiments without having to export data.
Precision Melt Analysis software makes it easy for you to:
* Streamline your data analysis using the customizable default analysis settings
* Utilize the multiple data view options to manually assign sample genotypes by tailoring the software to the appropriate analysis
* Examine results from a number of melt files, without having to export data, using the Melt Study module
* Analyze multiple experiments from a single plate using the Well Groups feature
* Publish your data in several formats by easily exporting data to Microsoft Excel or as an image
For more information, check out the Precision Melt Analysis Software Flier and the Precision Melt Analysis Software instruction manual or contact your sales rep at 1-800-4-BIO-RAD (1-800-424-6723) for details.