Below this question is a generated text representing a DNA sequence. The first line starts with '>' and is a comment, and the lines after that hold the sequence. The sequence has letters 'A', 'C', 'T', and 'G'. In your program (written in python) for this question, read the sequence using the statements: f = open('kdpF.txt') # opens a file for reading line = f.readline() # reads a single line print(line) seq = '' for line in f : # reading the rest of the lines      seq = seq + line seq = seq.replace('\n', '') # removing the newline characters seq = seq.upper() print(seq) def gcContent(sequence) :     # You do the rest     pass Also write a function gcContent(sequence), which returns the percent of the sequence which is either 'G' or 'C'. Use your function on the input sequence and print the results.     generated text DNA sequence:  >200 bp region of the chromosome of E. coli, containing gene kdpF, shortest gene ttgcagccagaattctacccttccggtatcacttttaggccattggaggtgcactat gagtgcaggcgtgataaccggcgtattgctggtgtttttattactgggttatctggt ttatgccctgatcaatgcggaggcgttctgatggctgcgcaagggttcttactgatc gccacgtttttactggtgttaatggtgc

Below this question is a generated text representing a DNA sequence. The first line starts with '>' and is a comment, and the lines after that hold the sequence. The sequence has letters 'A', 'C', 'T', and 'G'. In your program (written in python) for this question, read the sequence using the statements:

f = open('kdpF.txt') # opens a file for reading line = f.readline() # reads a single line print(line)

seq = ''
for line in f : # reading the rest of the lines

     seq = seq + line
seq = seq.replace('\n', '') # removing the newline characters seq = seq.upper()

print(seq)

def gcContent(sequence) :

    # You do the rest
    pass

Also write a function gcContent(sequence), which returns the percent of the sequence which is either 'G' or 'C'. Use your function on the input sequence and print the results.

generated text DNA sequence: 

>200 bp region of the chromosome of E. coli, containing gene kdpF, shortest gene
ttgcagccagaattctacccttccggtatcacttttaggccattggaggtgcactat
gagtgcaggcgtgataaccggcgtattgctggtgtttttattactgggttatctggt
ttatgccctgatcaatgcggaggcgttctgatggctgcgcaagggttcttactgatc
gccacgtttttactggtgttaatggtgc