First, we added pseudo-Restriction Enzyme sites representing the TOPO and att recognition sequences to the Common Enzymes file. This is the file containing the default set of enzymes that are automatically displayed in the Map tab of all open sequences.

Second, we added a large number of Invitrogen vectors that are installed in the /Applications/MacVector 11/Common Vectors/Invitrogen/ folder. These include a selection of “Entry” and “Destination” vectors. Others can be downloaded from the Invitrogen web site – you can use MacVector’s Auto-Annotation function to quickly annotate additional vectors with common TOPO and Gateway features.

A typical Gateway cloning vector with att and TOPO sites highlighted.

Its then very easy to simulate a TOPO or Gateway cloning experiment to create a constructed molecule with the identical sequence at the junctions to the one you would get in the lab. To clone a PCR fragment, simply select the region in a source molecule (or from an external text editor) and copy it to the clipboard, then select the TopoTA/BLNT site in the vector and click on the Ligate button. A Ligation dialog opens showing you the compatible blunt ends.

This gives you the option of flipping the source fragment if you wish. Note that this also works for TA cloning as well as ZERO-BLUNT cloning manipulations, even though the dialog does not show the overhanging T-A ends.

When Ligate is clicked, the fragment gets inserted into the vector. To perform a Gateway cloning, you can select the two att sites (attL1 and attL2) and copy the fragment to the clipboard.

Then open a suitable target/destination vector – these typically have attR1 and attR2 sites.

Now when you click on the Ligate button you’ll see the core recombination sequences of the att sites shown as overhanging ends.

Note that there is a single residue difference between the core sequences of the attL1/attR1 and attL2/attR2 sites;

The single T-C mismatch between the two core sequences ensures that the att recombination can only occur in one orientation. MacVector understands this and will automatically flip the source fragment if needed so that it becomes inserted in the biologically correct orientation. Finally, clicking Ligate inserts the fragment into the target vector.

For a more in-depth discussion of the new Gateway and TOPO cloning functionality in MacVector, download the Gateway and TOPO Cloning Tutorial from our web site.

Here’s the idea – over time you build up a collection of plasmids and sequence fragments of the genes and vectors you work with the most. Perhaps you always like to make your favorite gene appears as a striped red box. Now, when you get a new sequence, just run the auto annotation algorithm (Database | Auto Annotate Sequence) and point it at a folder containing your annotated sequences. The algorithm not only finds the matching features and copies them onto your bare sequence, but it also copies the graphic appearance symbol information. Lets look at an example.

MacVector 11 comes with a large set of pre-annotated vectors. You can find them in the /Applications/MacVector 11/Common Vectors/ folder. We’ve also included an /Annotated Fragments/ folder here with a started set of genes and replication origins you’ll find on many cloning vectors. Here’s a composite graphic image of a selection of those fragments.

There is a plain text copy of pBR322 in /MacVector 11/Tutorial Files/AutoAnnotation/pBR322Ascii.txt. If you open this file in MacVector and toggle its topology to linear, you’ll see there are no features assigned to the plasmid.

The next step is to invoke Database | Auto Annotate Sequence, then click on the Choose… button to select the /MacVector 11/Common Vectors/Annotated Fragments/ folder. Finally, click on the OK button and the algorithm will search through all of the files in the folder looking for matching features. When complete, a report is displayed – when you close that, you’ll see the newly annotated sequence.

In this case, pBR322 has picked up the tetracycline and ampiciliin resistance CDS features, along with the rop gene and replication origin.

Prefer a different way of graphically displaying the features? Try repeating the analysis, but selecting the /MacVector 11/Common Vectors/NEB/ folder – this contains a selection of vectors available from New England Biolabs, formatted to match the appearance in their catalog.

This time, when the algorithm completes, the features take on the typical appearance seen in the catalog. Note that the CDS features have not been duplicated – MacVector realizes the features already exist and just replaces the graphic symbols. You can also optionally set the algorithm to ignore duplicate features completely, in which case the sequence appearance would have been left unchanged.

You can use the Auto Annotation function to scan any folder containing DNA sequences. They don’t have to be in MacVector format, although features from GenBank or EMBL files will be given the default appearance for the feature type. There is a certain amount of fuzziness built into the algorithm – it can handle mismatches and even a few gaps and still identify matching features. We’ll be posting a more detailed tutorial in the next week with more information about the different parameters and limitations of the algorithm. In the meantime, take it for a spin and build up a collection of curated sequences containing all your favorite genes formatted for that great visual impact in your presentations.

• ClustalW – we also call this the “standard” Multiple Sequence Alignment (MSA)
• Align to Reference
• Pustell Matrix (also known as a Dot Plot)
• Internet BLAST
• Align to Folder
• Contig Assembly

ClustalW/Multiple Sequence Alignment (MSA)

If you have two or more related sequences (DNA or Protein) and you want to examine the relationship between them, use this function. Choose File->New->Protein Alignment (or File->New->Nucleic Acid Alignment) to create an empty MSA window. Add sequences to the alignment by using the Edit->Add Sequences from File menu item then click on the Align toolbar button to automatically align the sequences using ClustalW. Click on the Prefs toolbar button to control the appearance and behavior of the data in each of tabs that represent different views or analyses of the alignment. This functionality is most suited for protein alignments, or for nucleic acid sequences where you are interested in examining phylogenetic relationships. If you wish to compare two or more DNA sequences, you should definitely consider if one of the other alignment functions may be more suitable.

Align to Reference

The Align to Reference Editor window

Use this if you have a reference sequence and you want to align one or more DNA sequences against it. A typical use would be in resequencing e.g. sequencing a cloned PCR fragment to check no errors were introduced, sequencing across end junctions, scanning for successful mutagenesis clones etc. In each case, open the file that represents the parent or “reference” sequence, then choose Analyze->Align to Reference. In the window that opens, click on the “+” button to add sequences from disk – these can be in any format that MacVector can read – typically ABI or SCF chromatogram files, but you can add plain sequences as well. When you click on the Align button, choose the Sequence Confirmation algorithm – this is tuned to expect the small insertions/deletions you would expect in raw chromatogram files. Compared to ClustalW, Align to Reference has the advantage that it will automatically “flip” sequences to guarantee optimal alignment.

Align to Reference can also be used to align cDNA clones against a genome sequence. The steps are similar – use the genomic sequence as the reference, then add one or more cDNA clones to the alignment. Again, these can be chromatogram files. Now choose the cDNA Alignment algorithm when you Align – this is tuned to expect large insertions representing the intron regions.

Pustell Matrix

Repetitive sequence elements identified using a dot plot

This “Dot Plot” function is great for identifying weak regions of similarity between two sequences. It is not designed to show full-length alignments between two sequences, but instead shows shorter segments of direct or inverted similarity. You can use this to identify shorter regions of similarity, then copy those sections to new sequence windows for more in depth analysis using ClustalW or Align to Reference. Dot Plots are also the best way of identifying sequence rearrangements – the display clearly shows insertions and deletions (the main diagonal will be broken and have an offset) and even inversions (the inverted diagonal will run bottom left to top right and be colored blue). Finally you can use it to identify repetitive regions which appear as parallel diagonals offset from the main diagonal. Pustell Matrix can be used not only to compare DNA:DNA and Protein:Protein, but you can also use it to compare DNA:Protein where the algorithm will translate the DNA in all 6 frames before aligning to the protein.

Internet BLAST

Use this to identify and align a test sequence to the databases at the NCBI using the popular BLAST algorithm. One slightly hidden function in MacVector is that you can select sequences in the “hitlist” and then choose Database->Retrieve to Disk or Database->Retrieve to Desktop to download the matching sequences from the NCBI. You don’t even need to select the entire line – just select part of a line and use the Retrieve menu item.

Align to Folder

This allows you to scan a local folder full of sequences (in any format MacVector can recognize) and align them using the FastA alignment algorithm. Its kind of like a local BLAST, but more sensitive. Like the Pustell Matrix, you can choose to search DNA with Protein and vice versa. Many users like this function because the text alignment output also shows the features in the test sequence. This can be very useful for demonstrating the differences between your sequence and other sequences for patent purposes.

Contig Assembly

This requires our optional Assembler add-on. Use this if you want to align two or more DNA sequences with the idea of assembling them into a longer sequence with a consensus. Its is primarily designed for de novo sequencing, where you have no reference or scaffold sequence to align the individual sequences to. The MacVector implementation uses the popular phred, phrap and cross_match algorithms from the University of Washington that use quality values for improved accuracy of assembly. While you can use this for resequencing, you should consider whether the Align to Reference function might be a better choice.

Tutorials

There are tutorials for Sequence Confirmation and Contig Assembly in the Documentation folder of your MacVector installation. You can also download copies from our website.

So there we have at least five ways to align sequences using MacVector. Now if I can just find another 4 ways of skinning a catfish (or even just ONE thats easier than my current method) then I’ll be all set.

There are probably as many different approaches to software bugs as there are software applications. And none of them are perfect – I can’t think of a single application or OS that hasn’t crashed on me at least once over the years. So given that bugs are a reality in most (all?) software products, what is the best approach to reducing their impact once the product has been released? As a Product Manager over the past 10+ years, I’ve been involved in 20 to 30 major releases and probably twice as many minor ones across a variety of products and platforms. They all had one thing in common – within 2 weeks of release, at least one customer reported a bug that, had we known about it before release, we would have fixed before it went out.

At one company I was at, the policy was to “test, test, test” with the QA department somewhat removed from the R&D department.  A huge battery of mostly manual tests was run on every release. If a single line of code was changed, all had to be run again, on every combination of OS and platform supported. Each round of testing took a minimum of a week with every developer pulled off coding to help. Finally, the product was released and, inevitably, a bug report would come in almost straight away.. But, because of the extended release cycle, fixing that bug would take all of the developers and testers time for two weeks, during which time other bug reports would come in. In this way, four months pass before a patch was released, during which time no progress has been made on the next major release. This starts a vicious cycle where at the release post mortem, the QA department insists on more testing for the next version, so that release gets delayed even longer and when the inevitable bug reports come in, an even longer delay before that patch is released.

At MacVector, Inc, we’ve taken a more streamlined approach. We certainly do a lot of testing, but we rely on a much tighter integration between the QA and R+D departments to only retest areas that the developer believes would have been affected by the bug fix. That reduces our bug fix development cycle time dramatically, so we can have patch releases posted on the web site within a week of the initial report. The risks, of course, are those “Whack-a-Mole” bug fixes where the code to fix one bug reveals another bug elsewhere in the application. But if that happens, we know we can turn around a second bug fix in a week or so, not the six months that my old company took.

So the take home lessons are (a) check back to the MacVector web site often to pick up any new patches and (b) I really need to find out where those ants are coming from…