James W. Brown - Principles of Microbial Diversity

Здесь есть возможность читать онлайн «James W. Brown - Principles of Microbial Diversity» — ознакомительный отрывок электронной книги совершенно бесплатно, а после прочтения отрывка купить полную версию. В некоторых случаях можно слушать аудио, скачать через торрент в формате fb2 и присутствует краткое содержание. Жанр: unrecognised, на английском языке. Описание произведения, (предисловие) а так же отзывы посетителей доступны на портале библиотеки ЛибКат.

Principles of Microbial Diversity: краткое содержание, описание и аннотация

Предлагаем к чтению аннотацию, описание, краткое содержание или предисловие (зависит от того, что написал сам автор книги «Principles of Microbial Diversity»). Если вы не нашли необходимую информацию о книге — напишите в комментариях, мы постараемся отыскать её.

Every speck of dust, drop of water, and grain of soil and each part of every plant and animal contain their own worlds of microbes. Designed as a key text for upper-level undergraduates majoring in microbiology, genetics, or biology,
provides a solid curriculum for students to explore the enormous range of biological diversity in the microbial world. Within these richly illustrated pages, author and professor James W. Brown provides a practical guide to microbial diversity from a phylogenetic perspective in which students learn to construct and interpret evolutionary trees from DNA sequences. He then offers a survey of the «tree of life» that establishes the necessary basic knowledge about the microbial world. Finally, the author draws the student's attention to the universe of microbial diversity with focused studies of the contributions that specific organisms make to the ecosystem.
Principles of Microbial Diversity

Principles of Microbial Diversity — читать онлайн ознакомительный отрывок

Ниже представлен текст книги, разбитый по страницам. Система сохранения места последней прочитанной страницы, позволяет с удобством читать онлайн бесплатно книгу «Principles of Microbial Diversity», без необходимости каждый раз заново искать на чём Вы остановились. Поставьте закладку, и сможете в любой момент перейти на страницу, на которой закончили чтение.

Тёмная тема
Сбросить

Интервал:

Закладка:

Сделать

One common way to estimate evolutionary distances from similarity is the Jukes and Cantor method, which uses the following equation:

As shown graphically in Fig 41 similarity and distance are very closely - фото 35

As shown graphically in Fig. 4.1, similarity and distance are very closely related initially (e.g., 0.90 similarity ≈ 0.10 distance) but level off to 0.25 similarity, where evolutionary distance is infinite. This makes sense; for two sequences that are very similar, the probable frequency of more than one change at a single site is low, requiring only a small correction, whereas two sequences that have changed beyond all recognition (infinite evolutionary distance) are still approximately 25% similar just because there are only four bases and so approximately one of the four will match entirely by chance.

Figure 41The Jukes and Cantor equation plotted as observed sequence similarity - фото 36

Figure 4.1The Jukes and Cantor equation plotted as observed sequence similarity (from the similarity matrix) versus estimated evolutionary distance. doi:10.1128/9781555818517.ch4.f4.1

To convert a similarity matrix to a distance matrix, just convert each value in the similarity matrix to evolutionary distance using either the graph or the equation. In our example:

Generating a tree from a distance matrix In the neighborjoining method the - фото 37

Generating a tree from a distance matrix

In the neighbor-joining method, the structure of the tree is determined first and then the branch lengths are fit to this skeleton.

Solving the tree structure

The tree starts out with a single internal node and a branch out to each sequence: an n- pointed star, where n is the number of sequences in the alignment. The pair of sequences with the smallest evolutionary distance separating them is joined onto a single branch (i.e., the neighbors are joined, hence the name of the method), and then the process is repeated after merging these two sequences in the distance matrix by averaging their distances from every other sequence in the matrix.

Using our distance matrix, the tree starts out like this (remember that we are sorting out the structure of the tree, not yet the branch lengths).

The closest neighbors in the distance matrix are A and B 011 evolutionary - фото 38

The closest neighbors in the distance matrix are A and B (0.11 evolutionary distance), so these branches are joined:

The distances to A and B from each of the other sequences are then averaged to - фото 39

The distances to A and B from each of the other sequences are then averaged to reduce the distance matrix:

In this case the averages are trivial the average of 030 and 030 is of - фото 40

In this case, the averages are trivial; the average of 0.30 and 0.30 is, of course, 0.30, and so forth. This is not usually the case. Then the process is repeated. The closest neighbors in the reduced matrix are D with C (0.17):

Once again the distance matrix is reduced by averaging But be sure to average - фото 41

Once again, the distance matrix is reduced by averaging. But be sure to average from the original distance matrix, not the previously reduced matrix:

Note that the value listed for AB with CD 0265 is the average of four - фото 42

Note that the value listed for A/B with C/D (0.265) is the average of four values in the original matrix: A to C (0.30), A to D (0.23), B to C (0.30), and B to D (0.23). If averaged AB/C (0.30) and AB/D (0.23) were averaged from the reduced matrix, the same number would be obtained in this case, but usually this is a more complex average and the numbers do not come out the same.

Once again, the smallest number in the matrix represents the nearest neighbors, in this case A/B with C/D (0.265), so these two branches are joined:

Each node on this tree has only three branches connecting to it all of the - фото 43

Each node on this tree has only three branches connecting to it; all of the nodes are completely resolved. This means that the structure of the tree has been determined. If there were more sequences, it would be necessary to reduce the matrix (joining A/B with C/D) and repeat the process until all of the nodes were resolved. The internal nodes have been arbitrarily labeled w, x, y , and z for reference when sorting out branch lengths (below).

Determining branch length

The next step is to determine the lengths of the branches on this tree. Basically, this is done by going through each node and finding where along the branch it is by figuring out the average difference in length along each of two branches. By choosing various sets of three sequences in a tree, the branch lengths can be sorted out just like a puzzle.

Branches w /A and w /B ( w is the common node between A and B)

In our example, the distance between A and B is 0.11, and so the lengths of the two branches connecting them (A/ w and w /B) must add up to 0.11. But where along this branch is the node ( w )? If you look at the distance from any other sequence (C, D, or F) to A and to B, it is always the same. For example, C/A is 0.30 and so is C/B. This means that node w must be midway between A and B; each branch, then, has a length of 0.055. For example, with C used as reference:

Branches x C and x D C and D are also simple neighbors so we can easily - фото 44

Branches x /C and x /D

C and D are also simple neighbors, so we can easily solve these two connecting branches as well. The distance between C and D is 0.17. However, the distance to either C or D from elsewhere in the tree differs; this means that the node connecting C and D is not equidistant between them. In fact, this difference in distance between C and D varies a bit depending on which reference we use. These differences occur because we can only estimate evolutionary distance. As a result, we use the average (although most computer algorithms would use a least-squares average):

Therefore 007 is the difference in branch length between AC and AD This - фото 45

Therefore, 0.07 is the difference in branch length between A/C and A/D

This value 008 is the average amount by which x C is longer than x D - фото 46

This value, 0.08, is the average amount by which x /C is longer than x /D. Because the total length of C/D (think of this as C/ x /D) is 0.170 and x /C is 0.08 longer than x /D, then:

Читать дальше
Тёмная тема
Сбросить

Интервал:

Закладка:

Сделать

Похожие книги на «Principles of Microbial Diversity»

Представляем Вашему вниманию похожие книги на «Principles of Microbial Diversity» списком для выбора. Мы отобрали схожую по названию и смыслу литературу в надежде предоставить читателям больше вариантов отыскать новые, интересные, ещё непрочитанные произведения.


Отзывы о книге «Principles of Microbial Diversity»

Обсуждение, отзывы о книге «Principles of Microbial Diversity» и просто собственные мнения читателей. Оставьте ваши комментарии, напишите, что Вы думаете о произведении, его смысле или главных героях. Укажите что конкретно понравилось, а что нет, и почему Вы так считаете.

x