MITOCHONDRIAL DNA ISOLATION

PROCEDURE

Grind in mortar and pestle or Waring blender with 5-7 volumes buffer A per g tissue. Use MCE at 350 l/L, and if necessary, with 5 ml 1 M DIECA/L.
Squeeze through cheesecloth, two layers of Miracloth.
Centrifuge 10 min at 1000 g
Decant supernatant and centrifuge 10 min at 15,900 g.
Resuspend each pellet in a few drops of buffer G with paint brush; combine; bring to about 10 ml/50 g, 15 ml/75 g.
Centrifuge 10 min at 1000 g; pour off most; swirl pellet to remove fluffy layer; combine.
Bring supernatant to 10 mM MgCl2 (100 l 1M/10 ml). Bring to 20 g DNase/ml (100 l 2mg/ml/10 ml).
60 min. 4 C.
Underlay shelf buffer, 20 ml/10-15 ml; always use 20 ml or more.
Centrifuge 20 min at 12000 g.
Resuspend in small volume shelf buffer with brush; bring to about 10 ml/50-100 g.
Centrifuge 10 min at 15900 g.
Resuspend pellets in NN (lysis) buffer (4-5 ml/50-75 g).
Add SDS to 0.5% (250 l of 10%/5 ml NN). Swirl thoroughly.
Add proteinase K to 100 g/ml (25 l of 20 mg/ml/5 ml NN). Swirl gently.
60 min. 37 C.
Add equal volume of 3:1 water-saturated phenol, chloroform-isoamyl alcohol mixture. Emulsify ca. 5 min.
Centrufuge 10 min at 7000 g.
Collect supernatant; repeat 17 and 18: 3 total extractions.
Final supernatant; add 0.1 volume 8 M Ammonium acetate; then add 2 volumes of absolute ethanol.
60 min, -80 C; 10 min at 8000-9000 g; drain; add equal volume 70% ethanol; let sit 10 min; 10 min at 8000-9000 g; drain dry. Vacuum dry pellet, 30 min. Two small corex tubes are better than one 30 ml Corex.
Add 100-500 l 0.1X NTE, 10 l RNase mixture. Typically use 500 l per 50 g tissue.
Hydrate 30 min., 37 C.

Column Chromatography

Column In TLC, the stationary phase is a thin layer of silica gel or alumina in glass, metal or plastic plate. Column chromatography works in a much larger scale for the packaging of the same material in a vertical column of glass. Different sizes of chromatography columns used, and if you have the link at the bottom of the section Organic Chemistry site, at the University of Colorado, you will find images of several columns. In the school laboratory, it is often convenient to use as an ordinary burette column chromatography.
Using column Suppose you want to separate a mixture of two compounds of colors - yellow, blue. The mixture looks green. You want to make a concentrated solution of the mixture, preferably on the solvent used in Stoubtsy. The first time you turn on the tap in order to have a solvent in the column to drain so that at the same level with the top of the packing material, then carefully add the solution to the top of the column. Then open the valve again to the color mixing is absorbed in the upper packaging material, so it may look as follows:
Explaining what happens This means that you have read the explanation of what happens during the thin-layer chromatography. If you do not, go to the first in the top of the page and return to this issue later.
Blue, obviously, more polar than the yellow - it even has the possibility of hydrogen bonding.You can say this because the blue does not travel through the column very quickly. This means that it must absorb more energy for silica or alumina in yellow. Less polar yellow to spend most of their time in the solvents and, thus, is washed through the column much faster.
Washing process connection through the column using a solvent known as elution. Thinner sometimes referred to as eluent.
What to do if you want to pick up the blue compound, too?
Will take years to wash the blue through rate that moves at the moment! However, there is no reason why you can not change the course of elution solvent.
Suppose that we replace the solvent was used for the polar solvent, the yellow once again were collected. This will have two consequences, both of which accelerate the blue through the column.
Polar solvents compete for a place in the silica gel or aluminum with blue. Any space is temporarily occupied by solvent molecules on the surface of the stationary phase is not available for blue molecules stick, and it is usually going to hold them together with solvent.
There will be more involvement between the polar solvent molecules and polar molecules in blue.It will seek to attract any blue molecules in the stationary phase of the decision once again.
The end result is that the more polar solvents, the blue to spend more time on the decision and, thus, is moving faster.
Why not use this alternative solvent in the first place? The answer is that when both compounds in a mixture of rapid passage through the column from the beginning, would probably not be as good a separation.
What to do if all they have a mixture of colorless? If you use column chromatography for purification of organic food preparation, it is likely that the product you want to be colorless, colored, even if one or more impurities. Assume that the worst of all, colorless.
As you know, when the creature that he had reached the bottom of the column?
There are no quick and easy way to do it! What it does is collect what comes out of the bottom of the column in a series of labeled tubes. What is the size of each sample, obviously, depend on how popular column - you can collect samples of 1 cm3 or 5 cm3 samples or all that is necessary.
Can then take one drop of each solution and make a thin layer chromatogram it. You can put a drop on the base with a drop of pure sample of a substance does. By doing this several times, you can determine which of the samples collected in the bottom of the column containing the desired product, and only the desired product.
Once you know it, you can combine all the samples containing pure product, and then remove the solvent. (How not to be separated from the solvent product is not directly related to this topic and may vary depending on their specific nature - so I did not even attempt to summarize).

antiviral protein

Researchers have shown how an antiviral protein produced by the immune system, dubbed tetherin, tames HIV and other viruses by literally putting them on a leash, to prevent their escape from infected cells. The insights, reported in the October 30th issue of the journal Cell, a Cell Press publication, allowed the research team to design a completely artificial protein -- one that did not resemble native tetherin in its sequence at all -- that could nonetheless put a similar stop to the virus.

"Tetherin is essentially a rod with anchors at either end that are critical for

its function," says Paul Bieniasz of Howard Hughes Medical Institute and the

Aaron Diamond AIDS Research Center at The Rockefeller University. Either one of

those anchors gets incorporated into the envelope surrounding HIV or other

viruses as they bud through the plasma membrane of an infected cell. "

One anchor gets into the virus and the other in the cell membrane to inevitably form a tether.

"We showed we could design a completely different protein with the same

configuration -- a rod with lipid anchors at either end -- and it worked very

well,"

he continued. The finding helped to confirm that tetherin is capable of acting all on its own, he added.

They also explain tetherin's broad specificity to protect against many viruses. "It is just targeting lipids," Bieniasz said. "It's not about viral proteins." That's conceptually important, he continued, because there is no specific interaction between tetherin and any viral protein, which makes it a more difficult problem for viruses to evolve resistance. Rather than tweaking an existing protein-coding gene, "the virus has to make the more difficult adjustment of acquiring a new gene antagonist [of tetherin]."

Unfortunately, many viruses have managed to do just that. In the case of HIV, a protein called Vpu counteracts tetherin. They now show it does so by sequestering the host protein, which prevents its incorporation into the virus. The new insight into tetherin's and Vpu's modes of action, however, may lead to the development of Vpu blockers that could free up the innate host defense and inhibit HIV's spread, Bieniasz suggests.

Bieniasz said there is some possibility that tetherin exists in different forms that might explain differences among people in the progression of HIV or other viral infections. However, the only common variation they've seen in the tetherin gene so far does not appear to affect its function. The tetherin sequence does vary quite a lot from one species to the next, he added, as is often the case due to strong selection when host defense genes meet viral inhibitors.

To place the findings in context, Bieniasz says it is worth noting that tetherin is encoded by just one of more than 900 genes that get switched "on" in response to interferon, a cell signaling protein of the immune system.

"There are hundreds of interferon-induced genes," he said. "The functions are

known for only a very small number -- less than a dozen. There are potentially a

large number of antiviral mechanisms we still know nothing about."

Going forward, his team intends to look more closely at many of those others, and Bieniasz suspects more surprising mechanisms will be in store.

Inefficient Selection: New Evolutionary Mechanism Accounts For Some Of Human Biological Complexity

A careful analysis of thousands of genes and the proteins they encode show that humans are biologically complex, at least in part, by the way humans evolved to deal with redundancies resulting from the duplicate genes.



"We found a specific evolutionary mechanism to account for a portion of the
intricate biological complexity of our species, "said Ariel Fernandez, professor of
of bioengineering at Rice University. "It's a defense mechanism, a process that
allows us to address the fitness consequences of inefficient selection. It
enables some of our proteins to be more specialized in time, and in turn
makes us more complex. "



Fernandez is the author of a paper scheduled to appear in the December issue of the journal Genome Research. The line of research is available.

Fernandez said the study draws from past performance by its own research group and from the seminal work of Michael Lynch, distinguished professor of biology at Indiana University and recently elected to the National Academy of Sciences. Lynch's work has shown that natural selection is less effective in humans, compared with simple creatures such as bacteria. This "inefficiency of selection" is derived from the smaller population size of humans compared with unicellular organisms.



"In all organisms, genes are duplicated from time to time, for reasons not
fully understand, "said Fernandez." When working efficiently, natural selection
eliminates many of these copies, which are called 'paralogs. In our previous
work, we saw an unusual number of gene copies had survived in the human
genome, which makes sense given the inefficiency of selection in humans. "

In previous research on protein structure, the team of Fernandez noted that some proteins are packaged worse than others. Moreover, they found that the least efficient Packed proteins are structurally stable only when coupled with associated proteins to form complexes.



Proteins "These poorly packed are potential troublemakers when gene duplication
happens, "said Fernandez." The more copies of paralogs encodes the protein that
the body needs. This is called an "imbalance of doses, and that can make us sick.
For example, the imbalance in the doses have been implicated in Alzheimer's disease and other
diseases.

Given the inefficiency of selection, Fernandez knew that badly packed paralogs encoding proteins could remain in the human genome for a while. So he and graduate student decided to examine whether Jianpeng Chen had kept duplicates of genes in the genome of time for random genetic mutations affect the difference paralogs. Fernandez and Chen, now a senior researcher in Beijing, China, Cross-examined databases on genomics, protein structure, regulation and protein expression in these paralogs microRNA problematic.



"The longer these duplicated genes become inefficient due to the selection, the
more likely to undergo a random mutation, "said Fernandez." Parties
gene acts to regulate the expression of proteins - by binding with microRNAs, for
example. We found numerous cases where the random mutations had caused paralogs
as opposed to express, so that eliminated the harmful dose
imbalances ".

Lynch said that one aspect of research that is potentially revolutionary Fernandez is the trend of proteins to develop a more open structure in complex organisms.



"This observation is consistent with the general theory that large agencies with
relatively small size of the population - compared with microbes - are subject to
vagaries of random genetic drift and therefore the accumulation of very slightly
deleterious mutations,

Lynch said.

At first, he said, the accumulation of these mutations may promote stability slight breakdown of proteins. This in turn opens the door to interactions with other proteins that can restore a measure of that lost stability.



"These are the roots potential for the emergence of novel protein-protein
interactions, which are the hallmark of evolution in the complex, multicellular
species, "Lynch said." In other words, the origins of some key aspects of the
evolution of complexity can be caused completely adaptive
processes.

Fernandez said the research reveals how increasingly specialized proteins can evolve. He drew an analogy to a company hired two delivery drivers initially covering the same parts of the city, but eventually specialize in offering only specific neighborhoods.



"Over time, even if times become tough, you can not dismiss any of them
because each of them became so specialized that your company needs both, "

He said.

The simplest is a creature, less specialized proteins it has. Humans and other mammals in order many specialized proteins needed to build the specialized tissues of the skin, skeleton and organs. Even more specialized proteins are required to maintain and regulate them. This complexity requires making a duplicate original of all trades of genes retained, but this will not happen unless the selection is inefficient. This is often a point of controversy between supporters of evolution and intelligent design.

Fernandez and Chen looked duplicated genes in the human genome and found that the poorer focused on a protein was most likely that distinguish paralogs through specialization.



"This supports the case of evolution, because it shows that you can drive
complexity, with random mutations in the duplicated genes, "said Fernandez." But this
also means that random drift must prevail over Darwinian selection. In other
words, if Darwinian selection has been ruthlessly efficient in humans - as it is in
bacteria and unicellular eukaryotes - then our level of complexity not
possible ".

The research is supported by the National Institutes of Health.

Phylogenetic tree

A phylogenetic tree or evolutionary tree is a tree showing the evolutionary relationships among various biological species or other entities that are believe to have a common ancestor. In a phylogenetic tree, each node with descendants represents the most recent common ancestor of the descendants, and The Edge lengths in some trees correspond to time estimates. Each node is called a taxonomic unit. Internal nodes are generally called hypothetical taxonomic units (HTUs) as they can not be directly observed.

A rooted phylogenetic tree is a directed tree with a unique node Corresponding to the (usually imputed) most recent common ancestor of all the entities at the leaves of the tree. The most common method for rooting trees is the use of an uncontroversial outgroup - close enough to allow inference from sequence or trait data, but far enough to be a clear outgroup.

Unrooted trees illustrates the relatedness of leaf nodes without making assumptions about common ancestry. While unrooted trees can always be generated from rooted ones by simply omitting the root, root can not be inferred from an unrooted tree without some means of Identifying ancestry, this is normally done by including an outgroup in the input data or introducing additional assumptions about the relative rates of evolution on each branch, such as an application of the molecular clock hypothesis. Figure 1 depicts an unrooted phylogenetic tree for myosin, a superfamily of proteins.

Both rooted and unrooted phylogenetic trees can be either bifurcating or multifurcating, and either labeled or unlabeled. A bifurcating tree has exactly two descendants Arising from each internal node, while a tree multifurcating may have more than two. A labeled tree has specific values assigned to its leaves, while an unlabeled tree, sometimes called a tree shape, only defines a topology. The number of possible trees for a given number of leaf nodes depends on the specific type of tree, but there are always more multifurcating than bifurcating trees, more labeled than unlabeled trees, and more rooted than unrooted trees. The last distinction is the most biologically relevant; it Arises Because there are many places on an unrooted tree to put the root. Among labeled bifurcating trees, the number of unrooted trees with n leaves is equal to the number of rooted trees with n - 1 leaves.

A dendrogram is a broad term for the Diagrammatic representation of a phylogenetic tree.

A cladogram is a tree formed using cladistic methods. This type of tree only represents a branching pattern, ie, its branch lengths do not represent time.

A phylogram is a phylogenetic tree that explicitly represents number of character changes through its branch lengths.

An ultrametric tree or chronogram is a phylogenetic tree that explicitly represents evolutionary time through its branch lengths.

Phylogenetic trees among a nontrivial number of input sequences are constructed using computational phylogenetics methods. Distance-matrix methods such as neighbor-joining or UPGMA, Which calculate genetic distance from multiple sequence alignments, are simplest to implement, but do not invoke an evolutionary model. Many sequence alignment methods such as ClustalW also create trees by using the simpler algorithms (ie those based on distance) of tree construction. Maximum parsimony is another simple method of estimating phylogenetic trees, but implies an implicit model of evolution (ie parsimony). More advanced methods use the optimality criterion of maximum likelihood, often within a Bayesian Framework, and apply an explicit model of evolution to phylogenetic tree estimation. Identifying the optimal tree using many of these techniques is NP-hard, so heuristic search and optimization methods are used in combination with tree-scoring functions to identify a reasonably good tree that fits the data.

Tree-building methods can be assessed on the basis of several criteria:

* Efficiency (how long does it take to compute the answer, how much memory does it need?)
* Power (does it make good use of the data, or is information being wasted?)
* Consistency (will it converge on the same answer Repeatedly, if each time given different data for the same model problem?)
* Robustness (does it cope well with Violations of the assumptions of the underlying model?)
* Falsifiability (does it alert us when it is not good to use, ie when assumptions are violated?)

Tree-building techniques have also gained the attention of mathematicians. Trees can also be built using T-theory.

Tree View X

TreeView X is an open source program to display phylogenetic trees on Linux, Unix, Mac OS X and Windows. You can read and display NEXUS and Newick format tree files (such as output by PAUP *, ClustalX, TREE-PUZZLE, and other programs). It offers a subset of the functionality of the TreeView version available for Mac and Windows Classic (which is roughly equivalent to version 0.95 of TreeView).
Download
Linux

To run the TreeView X you have to download and install wxWidgets. To recommend wxGTK Linux. Please use the stable version, not the development version. The X TreeView was then built with wxGTK 2.4.2. I placed a copy on this server.
Executable RPM (based on Red Hat 8) TV-0.5-1.i386.rpm
Note that the RPM does not support SVG images. To obtain this support will have to compile the source code. The reason for this is that SVG support is a "contribution" to wxWidgets and is not packaged in the RPM of wxGTK.
Source (tar.gz) TV-0.5.1.tar.gz
wxWidgets 2.4.2 for GTK (see wxWidgets.org for the latest version). You can get the RPM for wxGTK 2.4.2 here.
Unix

TreeView X should not rely on any Unix that supports wxWidgets. I've built for Solaris 8 wxWidgets 2.x running Motif or X11.
Source (tar.gz) TV-0.5.1.tar.gz
Windows

Installer executable (setup.exe)
Source (TV-0.5.zip)
Mac OS X 10.3 (Panther)

Unlike the Linux version, the version of Mac OS X works best with the edge of the "bleeding", the development version of wxWidgets. The next version was built with wxWidgets 2.5.3.
Executables (dmg) TreeView0.5.0.dmg
Source (tar.gz) TV-0.5.tar.gz
Previous versions

Platform release Filetype file
Linux binary RPM 0.4-0.4-1.i386.rpm TV
Linux source RPM 0.4-0.4-1.src.rpm TV
Linux 0.4 Source (gzipped tar file) TV-0.4.tar.gz
Windows binary installer 0.4 tv-0.4.zip
TV 0.4 Mac binary-0.4.zip

Sequence Extractor

Extract the sequence of clicks generate restriction map and Recovery preliminary map DNA sequences. Translated protein and intron / Exon borders as shown. Extractor use DNA sequences to build structures in silicon.

Features:
The adoption of template sequences in GenBank, EMBL, FASTA, or raw form.
Shows the reverse and forward translations included in the EMBL gene bank or Log In.
Using protein sequence included in the EMBL gene bank and enter the computing new translations (and avoid the need to obtain the correct genetic code).
For FASTA and the transfer of RAW files can show a framework for reading, and reading frames, or one of three all six reading frames.
The identification of sites can be demonstrated, and a summary of the positions of the restriction site is available.
Preliminary locations have steel in order to show forward and backward directions the template, and a summary of the preliminary sites is available.
Sites can be pre-minus can be found.
HTML in the entry on the JavaScript code. This code allows you to point to restrict the location of primer, or a translation (of the EMBL gene bank or translation) to find out more information about the location and characteristics.
You can click the two labels restrict the site to rise to the sequence between them to appear in a separate window. Use this function to obtain a series of restriction fragment Abstract.
You can double the figure for the paint (one to alleviate the tendency to forward one to alleviate the opposite direction) to produce a product recovery is expected to appear in a separate window. Sequence of primers is included in the product.
If the template is a Gene Bank and EMBL sequence record you can download the highest coding sequences, coding sequences marked with the letters, and the translation of the figure by using the links supplied

NTSYSpc, Numerical Taxonomy System

Version 2.2 for Windows NT/2000/XP & Vista
NTSYSpc can be used to detect the pattern and structure of multivariate data. For example, you may want to verify that a sample of data points indicates that the samples can come from two or more special populations or to calculate phylogenetically tree using neighbor joining or UPGMA methods to build dendrograms . With equal interest is the discovery that a change in some subsets of variables are interrelated (recovered). Origin as NTSYS program in 1960, but over the years has been completely redesigned and greatly expanded use a computer.

The data may be descriptive information about collections of objects or directly measured similarities or differences between all pairs of objects. Species descriptions and used items depends on demand abundances and morphological characters, species presence and absence of property, etc. NTSYSpc can transform data, evaluation of DUI similarities between objects, and prepare a summary analysis using group relations, coordination and analysis several factors. Many of the results can be shown by numerical and graphical. The software is designed for classroom and research.

Version 2.2 for Windows is easy to use, but still has speed and functionality than previous versions. There is an interactive way (with "fill in blank" forms of entry) and the batch mode with a simple command language (useful for simulation and analysis of multiple data sets). The program makes use of the Windows environment and allows long file names and processing of large datasets. Land options window allows you to customize plots (specify titles, fonts, sizes, colors, sizes, line widths, background colors, borders, and many other aspects of what is plotted). There is also a print preview mode. NTS data files are ASCII files that can be shared with other programs. Long lines of data are maintained. A spreadsheet-like editor is included information that makes it easy to create and edit data files. It can also be used as a ASCII text editor for very large files. Matrices can be read by Excel, CSV and XLS files, and the tree can be read from one type of file. Another alternative is provided for the production of MATLAB files M.

Some features include NTSYSpc are listed below.
Similarity and difference: the correlation distance, association coefficients, 34 and 11 genetic distance coefficients.
Clustering: UPGMA and SAHN methods other hierarchical (allows connections). Proximity switch method (including new version of unweighted). Some types of consensus trees.
Graph theoretic methods: the minimum time, which includes trees. Graphics (ineradicable trees) from the neighbor to switch method.
Coordination: The main components and basic coordinates analysis, correspondence analysis, metric and non-metric multidimensional scale analysis, singular value-decompositions, projections on the axes and the method of Burnaby. Canonical variates analysis. Several programs for analysis, common principal components analysis, partial least squares, multiple correlation and canonical correlation are also included.
Interactive graphics: phenograms, phylogenetically trees, 2D scatter plots, compared to DUI / similarity matrices, the outlines of the Fourier plots, plots Procrustes and the prospect of 3-D plots.
Multivariate Tests: canonical variates analysis, tests for homogeneity of Covariance matrices, tests for the number of dimensions, generalized multivariate multiple regression analysis. There are also provisions for the Bootstrap, jackknife and simulation experiments.
Geometric Morphometrics: includes specialized modules for Procrustes analysis configuration lay important plot the results of the Procrustes analysis, Fourier analysis (including 2D and 3D ellipsoid) shapes of the contour, plot outlines and Fourier coefficients, and calculation of 2D and 3D partial results and evaluations of all stays uniform.
Other: includes comparison of matrices of cophenetic correlation, Mantel test, 3-way Mantel test, data standardization and transformations of the matrix (simple functions, delete, and move now matrix). Matrices can be split or combined.

Requirements: Windows NT/2000/ME/XP/Vista. Works with about 9 MB of disk space after installation is complete.