Python Programming for Biology: Bioinformatics and Beyond


Sequencing for biochemical analysis



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[Tim J. Stevens, Wayne Boucher] Python Programming

Sequencing for biochemical analysis

Although  the  advances  in  fast  and  relatively  low-cost  DNA  sequencing  technology  were

initially  driven  by  the  desire  to  acquire  and  assemble  genome  sequences,  there  are  an

increasing  number  of  methods  that  rely  upon  mapping  many  short  DNA  reads  to  a

complete, or nearly complete, genomic sequence. This might be done to find differences in

sequences  compared  to  the  reference  genome,  i.e.  finding  sequence  polymorphisms.

However, it is also common to use high-throughput methods for the biochemical analysis

of cells. For example, the DNA sequences could be a large complement of cDNAs, which

are prepared using reverse transcription from messenger RNA, to show which genes were

actually  being  read  in  a  given  sample  or  cells;  this  method  is  called  RNA-seq.

Alternatively  the  DNA  could  be  fragments  of  genomic  origin  that  have  been  specially

selected in some way. Chromatin immumoprecipitation sequencing or ChIP-seq is such an

example, where genomic DNA is chemically cross-linked to proteins that are bound to the

chromosomes before it is cut into small fragments. Here the cross-linking is not specific

for  any  particular  kind  of  DNA-binding  protein,  but  the  fragments  of  DNA  with  their

associated proteins are purified using antibodies that bind to and select only one kind of

protein.  The  end  result  is  to  produce  a  sample  of  DNA  sequences  that  were  in  close

contact with a specific type of protein when it was functioning inside cells. Reversing the

DNA-protein cross-links then allows the associated DNA to be sequenced, thus indicating

where in the chromosomes the protein was originally present. ChIP-seq is frequently used

to  see  which  DNA  sequences  are  associated  with  modified  histone

1

 proteins  (usually



methylate or acetylate), and this in turn indicates which sections of the DNA are active or

inactive for transcription.




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