by Carina S.

Cys-regulatory modules (CRMs) (2)

  • regions of non-coding DNA which regulate the transcription of neighboring genes. CREs are vital components of genetic regulatory networks, which in turn control morphogenesis, the development of anatomy, and other aspects of embryonic development, studied in evolutionary developmental biology.

  • CREs are found in the vicinity of the genes that they regulate. CREs typically regulate gene transcription by binding to transcription factors. A single transcription factor may bind to many CREs, and hence control the expression of many genes (pleiotropy).

  • CRMs are stretches of DNA, usually 100–1000 DNA base pairs in length, where a number of transcription factors can bind and regulate expression of nearby genes and regulate their transcription rates. They are labeled as cis because they are typically located on the same DNA strand as the genes they control as opposed to trans, which refers to effects on genes not located on the same strand or farther away, such as transcription factors. One cis-regulatory element can regulate several genes, and conversely, one gene can have several cis-regulatory modules. Cis-regulatory modules carry out their function by integrating the active transcription factors and the associated co-factors at a specific time and place in the cell where this information is read and an output is given.

  • CREs are often but not always upstream of the transcription site. CREs contrast with trans-regulatory elements (TREs). TREs code for transcription factors

Use of the Burrows-Wheeler transform for searching for patterns in strings (11)

(nochmal anschauen als YT-Video z.B.)

  • Find occurrences of pattern P (aca) within a string S (acaaca$)

  • S’: Burrows-Wheeler Transform of S

  • Any pattern P that appears in S is the prefix of one of the suffixes

  • P is the prefix of suffixes 4 and 5

  • The Borrws-Wheeler Transform provides an index of the suffix array, that obviates the need to search for lines beginning with aca in the sorted suffix array of acaaca$

  • Assign to each alphabetic character in S a rank that specifies the number of times that character occurs previously in S

  • Attach the rank to each alphabetic character in the original string as a superscript

  • Compute the Burrows-Wheeler Matrix: the i-th occurrence of any character in the last column has the same rank as its i-th occurrence in the first column (the Burrows_Wheeler Transform of the original string)

  • Search for aca backwards:

    • starting with the final a: rows 2-5 begin with a

    • the character preceding the final a is c

    • the character in column 1 is preceded in the full string by the character in column 7 in the same row

    • for rows 2 and 3, the a in column 1 corresponds to the c in column 7, with ranks 0 and 1

    • we now know that the first and second occurrences of c are part of a ca substring

    • we also know that it is the first two occurrences of c (ranks 0 and 1) that vegin with ca

    • both have an a in column 7, completing the pattern aca

    • the corresponding ranks are 2 and 3, indicating that the two occurrences of aca begin with the first and third appearances of a^


Carina S.


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