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Dear DNASTAR® Customers and Friends: Welcome to the second quarterly issue of DNASTAR’s electronic newsletter, in which we strive to keep you up-to-date about DNASTAR. We are very excited about a significant new development — the pending launch of ArrayStar®, our new microarray gene expression software product. The soon to be released version of ArrayStar is our latest commercial entry into this market, offering:
We’ve had a chance to show ArrayStar to many scientists at numerous labs and its been beta tested in several other labs. We’ve received very positive feedback on the ease-of-use of the software and its ability to meet the needs of most microarray bench scientists. We continue to put energy and effort into supporting Lasergene, our flagship product, but we are also very excited about the prospects of serving a whole new area of molecular biology research with ArrayStar. We would like to hear from you if you are interested in taking ArrayStar for a test drive. As always, please let me or anyone else at DNASTAR know if we can improve the way in which we are serving you.
Sincerely,
Versions of GenVision can be used on either Windows® or Macintosh® platforms. With the Windows version, GenVision is supplied as both a Plug-in for Adobe® Illustrator® CS and as a standalone. On Macintosh, GenVision is available only as a Plug-in.
GenVision is designed to work with Excel® and to take advantage of some of its graphing capability to create special effects for histogram displays. This can be useful for showing forward/reverse gene orientations and to generate customized colors for the histogram boxes.
ArrayStar will formally be launched in June. We are in the final stages of documentation and test evaluation with field users. We wanted to take a few moments of time to highlight some of the many features of the software.
Files can be imported into ArrayStar in a variety of formats. It fully supports the import of Affymetrix ArrayStar v2.0 software enables researchers to perform a wide range of analyses on their data. Multi-functional scatter plots can be generated that allow the user to select groups of genes for analysis. Much information can be extracted from the scatter plot. The scatter plot graph illustrates a group of selected genes (white) that have been selected from the overall experiment. Any combination of genes can be clustered for additional analysis. Passing the cursor over any of the genes automatically provides gene ontology and pathway information. Prompts in the lower right hand corner provide From the gene set a wide range of information can be can be quickly obtained. For example, Gene Ontology and pathway information can be easily obtained for the selected set.
The Info Pane on the right of the heat map gives information about the data displayed. A histogram of the data distribution in the heat map is above the color scale. As selections are made on the heat map, the selected genes are shown in gray within the histogram. Minimum and maximum expression level values are also shown beneath the color scale. Of particular help to users is the Actions section in the lower right corner of the screen. This provides an easy prompt to users regarding possible follow-up actions they may take while also providing them with a quick method to perform them. ArrayStar will provide users with many statistical tools and visualizations to help further the analysis of your experiments. For example, users will be able to easily generate Line Graphs that illustrate relative gene expression levels within the gene set. This can be very helpful in identifying regulation patterns and relationships. Statistical methods allow users to quickly examine relevance of actions performed. And Much, Much more! For additional information, check the DNASTAR website after May 15 for additional technical information and details. |
Each issue of the DNASTAR newsletter features a short article written by a research scientist in the field of molecular biology. The intent of the article is to provide readers with additional information from their colleagues about work they are doing using sequencing as a key element. For inquiries and additional information on the article, email DNASTAR.
Close interaction with students is one of the things that led me to accept the position I now hold at a small, undergraduate university. Providing a strong foundation for students preparing for graduate work has always been an important consideration when designing lecture material and lab exercises for my genetics course. While the primary objective is to provide students at this level with a detailed understanding of the fundamental principles of genetics, the overall rationale is to provide such understanding in the context of modern views and applications of molecular biology. To demonstrate just one practical application of sequence analysis, students extract DNA from different species of the red alga genus, Porphyra. Members of this genus have few morphological characters and are indistinguishable to the untrained eye. Students amplify (PCR) the chloroplast gene, RbcL, from their particular sample. Due to the large size of this gene (>1,400 bp), final sequencing reactions can require up to eight additional interior primers for a targeted 80% double coverage. Upon receiving their sequences, students are required to use the editing software, SeqMan, to assemble the various fragments into a single contiguous sequence. Among other things, this editing exercise helps to reinforce the importance of double coverage when it comes to resolving conflicts in sequence data. After sequences have been edited, each student shares their sequence with the class and an overall alignment is made of all classroom sequences. Students are generally surprised at the amount of variation that exists in this conservative, protein-coding gene among morphologically identical members of the same genus. I have found this point in the exercise to be a great time to introduce molecular evolution topics and to explain the long evolutionary history of Porphyra. This exercise also shows students how sequence data can be used as a powerful tool in resolving taxonomic ambiguities. To further reinforce such concepts as speciation and convergent evolution, students are asked to use the alignment software, MegAlign, to produce a phylogenetic tree from their alignments. Various explanations are entertained and discussed for the resulting tree as students are encouraged to apply previously learned genetic principles. In light of the ever-increasing field of molecular biology, I feel a great need to take my students beyond just the basic skills of obtaining sequence data. If students are going to succeed beyond the undergraduate level, exposure to fundamental DNA sequence analysis and application is important.
If you have particular Tricks for using Lasergene that you believe would benefit your colleagues, let us know so we can share them. Do you need to edit your primer?
1. After locating and selecting a primer in PrimerSelect, go to or . The will be displayed. 2. Edit the primer in any of the following ways:
3. To save your changes, enter a name in the field at the bottom of the workbench, and then click . Your edited primer will automatically be saved to your . Would you like to change the display defaults in SeqBuilder? SeqBuilder will save changes to any of the following items as part of your default layout:
1. Open any sequence file in SeqBuilder. 2. Make changes to any of the items listed above, so that your view appears as you would like it to be shown by default. 3. Go to . 4. That’s it! Any future sequence files you open in SeqBuilder will appear with the formatting you specified. Do you want to realign only a portion of your alignment?
1. Select the region of your alignment that you would like to realign by clicking and dragging over the consensus sequence. 2. Go to . A dialog will appear. 3. Select a location and name for your file, and then click . 4. A new MegAlign window will be displayed, showing only the region of your alignment that you selected. 5. Go to and select an alignment method. Your shortened sequences will be realigned and displayed in the worktable. | ||||||||||||||||
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SeqMan Pro uses DNASTAR’s unique Trace Quality Evaluation system to generate the most accurate consensus sequence possible. For projects that utilize data from automated sequencers, this system evaluates the quality of the underlying trace data, assigns a quality score (Q Score) to each peak, and then uses the Q scores both for end-trimming, and to generate the consensus sequence. To optimize your assembly by using Q Scores:
2. Click the button at the top of the window. The dialog will appear.
4. Select your vector sequences from the drop-down lists at the top of the window. Note: If your vector sequence is not in the list provided, you may add it by going to and selecting . 5. Click the button from the top of the window. 6. Select the you would like to use for end-trimming. SeqMan Pro uses averaged quality scores (Q/n) to identify regions of poor quality data. The stringencies , , and correspond to average quality score thresholds of 8, 12, and 16 respectively. Selecting allows you to specify any quality score threshold from 0-100.
8. Then, go to , and select from the left side of the window. 9. Make sure the method selected is and the method is . Click . 10. Back in the window, click the button.
11. Make sure and are both selected. Then click . All of your sequences will be trimmed based on quality, and vector sequence removed. 12. Now that your sequences have been prepared for assembly, click the button at the top of the window. You sequences will be assembled and the contigs listed in the untitled window. The consensus for each contig will be generated using Trace Quality Evaluation system. To further demonstrate the benefits of utilizing Q Scores: 1. After your sequences have been assembled, double-click on a contig listed in the window to view the alignment.
3. Use the 4. On either end of the sequence, you may grab the trim bar and move it either left or right to expose trimmed sequence, or to further trim manually. Notice the lower averaged quality scores for the trimmed portions of reads.
6. Back in the alignment view, click the arrow next to to see how SeqMan’s Trace Quality Evaluation system compares to the . Bases that appear in red on the line indicate positions where the method would have called the consensus differently.
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button from the toolbar to show the averaged Quality Scores (Q/n) assigned to each peak
