The problem: You've just completed an amplicon sequencing run on the 454 instrument, but because the sequences are longer than any you've previously generated on 454, you suspect that you may have sequenced through your reverse primers and into non-biological sequence (e.g., sequencing adapters).

The solution: You want to find your reverse PCR primer in each of the sequences, and remove that and all bases following it. To do this, you can use scikit-bio's global nucleotide aligner.

In :
import numpy as np
import random

from skbio.alignment import global_pairwise_align_nucleotide
from skbio import DNA


First, we'll model some sequences. This is quick-and-dirty. Each sequence will contain some biological sequence (which is what we actually care about) with a mean/std length of 400/40, followed by one of four slightly different reverse primers (so representing a primer with 4-fold degeneracy), followed by some non-biological sequence with a mean/std length of 25/2. This is a reasonable representation of what we'd get off of the sequencing instrument: our reverse primer is somewhere in the sequence, but we don't know the exact start or end positions. (Note that I'm not modeling any sort of sequencing error here, and the biological sequence is random, which is not representative of what we'd have in an amplicon sequencing run.)

In :
sequences = []
num_sequences = 50
mean_biological_sequence_length = 400
std_biological_sequence_length = 40
mean_nonbiological_sequence_length = 25
std_nonbiological_sequence_length = 2
# imagine that we have four slightly different reverse primers
reverse_primers = [DNA("ACCGTCGACCGTTAGGATA"),
DNA("ACCGTGGACCGTGAGGATT"),
DNA("ACCGTCGACCGTTAGGATT"),
DNA("ACCGTGGACCGTGAGGATG")]

for i in range(num_sequences):
# determine the length for the current biological sequence. if it's less than 1, make the length 0
biological_sequence_length = int(np.random.normal(mean_biological_sequence_length,
std_biological_sequence_length))
if biological_sequence_length < 1:
biological_sequence_length = 0
# generate a random sequence of that length
biological_sequence = ''.join(np.random.choice(list('ACGT'),biological_sequence_length))

# determine the length for the current non-biological sequence. if it's less than 1, make the length 0
non_biological_sequence_length = int(np.random.normal(mean_nonbiological_sequence_length,
std_nonbiological_sequence_length))
if non_biological_sequence_length < 1:
non_biological_sequence_length = 0
# generate a random sequence of that length
non_biological_sequence = ''.join(np.random.choice(list('ACGT'), non_biological_sequence_length))

# choose one of the four reverse primers at random
reverse_primer = random.choice(reverse_primers)

# construct the observed sequence as the biological sequence, followed by the primer, followed by the
# non-biological sequence
observed_sequence = ''.join(map(str, [biological_sequence, reverse_primer, non_biological_sequence]))
seq_id = "seq%d" % i

# append the result to the sequences list

In :
print(repr(sequences))

DNA
---------------------------------------------------------------------
'id': 'seq0'
Stats:
length: 428
has gaps: False
has degenerates: False
has definites: True
GC-content: 47.66%
---------------------------------------------------------------------
0   CCTAGGAACG AACTTATATT AGCCATGAGG TAAGACGAAG GTCGAAACCC CCAATATATT
60  TCGCGGGTAA TCAATAAAAC CGCAAAGCAC CATAAGTTGG AGGTTGGAAC CCGCAGTCGG
...
360 GATGGCTCCA CTATAGAGTG TGAACAACCG TGGACCGTGA GGATGGGGGA CGCGGTCATC
420 CCGGAGCT


Now to get to the problem at hand. How do we find the primer sequence in random sequence. The answer is with global alignment. If we align the first reverse primer to the first sequence, we can get a TabularMSA object back.

Notice that in this step we get an EfficencyWarning. That's because scikit-bio currently only has a python implementation of global alignment, which is slow because it's a computationally complex algorithm. In the future, we'll have a C-based implementation which will be much faster.

In :
aln = global_pairwise_align_nucleotide(reverse_primers, sequences)

/home/evan/biocore/scikit-bio/skbio/alignment/_pairwise.py:599: EfficiencyWarning: You're using skbio's python implementation of Needleman-Wunsch alignment. This is known to be very slow (e.g., thousands of times slower than a native C implementation). We'll be adding a faster version soon (see https://github.com/biocore/scikit-bio/issues/254 to track progress on this).
"to track progress on this).", EfficiencyWarning)


We next want to find the start position of the primer sequence in the sequencing product, which we can do using the gaps boolean vector of the first sequence in the alignment (to learn about gap_vector). The following tells us where the first non-gap character in the primer alignment is, which is the position in the sequencing product where the primer match begins.

In :
gap_vector = aln.gaps()
primer_start_index = (~gap_vector).nonzero()
print(primer_start_index)

386


So, we can slice the original sequence through that position, and the result will be our sequencing product minus the reverse primer and the non-biological sequence.

In :
print(sequences[:primer_start_index])

CCTAGGAACGAACTTATATTAGCCATGAGGTAAGACGAAGGTCGAAACCCCCAATATATTTCGCGGGTAATCAATAAAACCGCAAAGCACCATAAGTTGGAGGTTGGAACCCGCAGTCGGCATCTAGGGACAGTCCCTAAGTCTCTTGTCACGGTTTACCTGCCGCCATATAGTAAAACACAGAAAGCCAAGTAGTCAAAGCAAGTCCCAGTTGGGCAACGCAGTATTGTGTCTCGTGCTGGCATAACAGTGCATCGTTATGGAGAATGCCGATTATCTAGGCACTCGTACAATCAACTGAAGCGATCGTTTATCTTTCCTTAAATCCGTCCAAGATAGTGTCCAAGTAATACAATACTCGATGGCTCCACTATAGAGTGTGAACA


Finally, if we want to do this for all of the sequences, we can embed the above steps in a loop over the DNA sequences.

In :
trimmed_sequences = []

for sequence in sequences:
aln = global_pairwise_align_nucleotide(reverse_primers, sequence)
gap_vector = aln.gaps()
primer_start_index = (~gap_vector).nonzero()

/home/evan/biocore/scikit-bio/skbio/alignment/_pairwise.py:599: EfficiencyWarning: You're using skbio's python implementation of Needleman-Wunsch alignment. This is known to be very slow (e.g., thousands of times slower than a native C implementation). We'll be adding a faster version soon (see https://github.com/biocore/scikit-bio/issues/254 to track progress on this).
"to track progress on this).", EfficiencyWarning)


We can then print the result, and we'll have acheived our goal.

In :
import skbio

print("".join(skbio.io.write((s for s in trimmed_sequences), into=[], format='fasta')))

>seq0
CCTAGGAACGAACTTATATTAGCCATGAGGTAAGACGAAGGTCGAAACCCCCAATATATTTCGCGGGTAATCAATAAAACCGCAAAGCACCATAAGTTGGAGGTTGGAACCCGCAGTCGGCATCTAGGGACAGTCCCTAAGTCTCTTGTCACGGTTTACCTGCCGCCATATAGTAAAACACAGAAAGCCAAGTAGTCAAAGCAAGTCCCAGTTGGGCAACGCAGTATTGTGTCTCGTGCTGGCATAACAGTGCATCGTTATGGAGAATGCCGATTATCTAGGCACTCGTACAATCAACTGAAGCGATCGTTTATCTTTCCTTAAATCCGTCCAAGATAGTGTCCAAGTAATACAATACTCGATGGCTCCACTATAGAGTGTGAACA
>seq1
GCAGAACTACCGAGACGGAGGTTTTCTCTAAGGTCGTCCGATATTGCGTAGGCAATACTATCCGAGAATCACGTAGAATGTCAATCGTCTTTGGTTTTACTAGCCCATTACAGGAGACCATGCGTGCATACACCCACGAGTCGATGTTGTAGTCACAGTGGTCGACACAGGACAGATACAGCATTATAGAAACGCTAAACGTGCGCCTCGGGTAAGTCTGGCGTGCGAATTTTCAAAGACCGGACTAAATAAGATTCTATTGAAAGAATCTTGGTGTTTATGTTTAGAAACGAAGGTCGGAGGTCCTGCAGGCAGCTCTGCGTGTGTGTATTCGGATGCACTCTCATCCGAAATCTTGTATATAACGTCAGTATCAGTGGTTGTTGGTCCTCTAATAGGTCCGATGG
>seq2
TTTTGACAAACAAACATTAGGCCAATCGGTAACAATAAAACGGCAACGGCAAGGATACGTCGTACATGACCACTACCGGGCAAACGCACGAAACAACGCTAGAGCGTGGCACTCGCACGGTACGTGAGCCTCTACGAAGGATTCATCGCTCTAATCGTTCCGGTGTCACGCGTAGAATAACGACTCAACCTAGGCAGTGGGGGACCTTCGCTCTGAGCCGGTTGCCAGGTGGACGCGTTAGTGGGAGAAATACCGTCAATCATGCTGGGACACCGACTGTTGGACAGAGGAGGAGTCCGGGGCGATTGCACCAGGGCGGAGAAGTATATTCGCTTACATATGGCCAACCTCAGTTCAAACTTTTCTAAACCCAATCAGAACCATGTTCCACGCTTGCGCTTTGACACGAGAGCTGGGCCCAAATGACACACT
>seq3
TGCTATTTATGCACGGCGTAGGGCTCTACGCTTGCGAGTGAGAATCTGCAAGAACATCGCTTAGACTTCCTCTCAGAAGAGTGCGTGCGATGGATCGCAGAGCGATCGGTATTGGAGAAAAGATAACTGAGGATCTCCGTTATTGGGGTGTCGCGACCGTGTAGACGACCCATGACTCCACCTGTGTCTACCGCCGACCAGCCCGAGATTCCGTACCGCAGCTGTATTACCTTGTCCACAAGCAACTTACGTTTTTGCTAGTTTCTTAACCTTGATGATACCTCGACTAGAATAGCCCCAAACTCTTTTCGAGAGCAAATCGAGACGCCTGTGTGGGTCACTGACACACGATGGGAAGGTTGGTATTGGCCACTCACCCACACAGACCCTTGGTCCCCAACTACACTGTTGATCCCCGTAGATGAGGGTGCAATGTTTATTAGATCGGTTAAGCCG
>seq4
GGTCCATTCCCCGCCCGCGTCTAAGCAGAGAGGTTTAGTGGACACACTGGCGCCTGAACCTTTGGTATACCTATGAGCAAGGGGTGAATACCAGTCCGCGGTTATCTCCGGCTGCAGTCTCGTTACGCCGAGTACTCTCCATTACTGAGCGACCTGATCATCCACCGTCAGCTAGATCCATCCTGGGGGTCGGGCCTGTAAATAAGGAGTTGCCTATTTTCTGTGCTTGGCGTAGATATTAAGTCTTTAAGTATGTTCTAGGTTTAACTCTCTCGGTCAATCCCTCCAACATGGAGCCACTAACACTTGCGTAGACACCTCATCCGGTTCGACCGCCGTGTTTCGACTTGGTCTGGCCCATACCTTACGTGAAACGCCTGTGCATTCCAGGGGCCCCCATTACG
>seq5
TGTGGTGATTTGGCATCATAACGGCGTCAAATTGAGAGGCGCGGAAATCCCGACACGCTATTAAGCACTACCTTGGTCACCCCGACTGTTCTACTGGTTGGAGGGTACGCTTAATGACCCCTGACACCACCAGCTTAAGCGCGCGGTAATACGGCATGCCACCCCCGTCGATATCCCTCTCACGGTGACGCTCCATTTCCAGTGGTTAGCACTGTTTAAAGGTGGGTCCAACGGCAGCGGGGATTGACAGTAGGGTTCAGACTCAGCATCTTCCTAAGGGGCGCGAAAGGTAACATTGCCCGAGGGTTTTCCGCTCACATATG
>seq6
GATACATTGGGTTTCGAATGCGAGAAAAGATTATCGGCCGGATGTCAGCCTGCGACTTAGAAAGTTGTGCAGGTACCGCTTGTCGGCTCCCTGTGTTTAACTTCACTCACTTATTTAATTCCCCTTAATGTGGCTCAGCGTATTGTCGAGTAACGTAGTATTTTACTCAAGAGCTTGGACACGCTTCATGCGGAGTCTACCTCTTGTTTCAAATGACGAGAGCACTAAAGATCCTGACAAGGGTAATATACGTACAAGCATGAGAAGGCGTCGTGACCACTCTTGTATTCACACGTTAGTCAAAGTTTGTAACGTGACTTAACCTCCTAAATACTCAGCCACAGGACTTAGACGGCAAATCCGGTCAGACAGTGAGCGCCTTCCCTTTGGGCGGAATCCCGAATCCTCTCCTTGCTGGCGCCC
>seq7
TCCACAATAGACCGGCGGCCGTAGTACTTAAAGTTGCGGGAATACCTTTCCCGCCTTTCCCCTAGAGGGAGAGTAAGCTAACTGGGCACCTAATCATTGTACGTCTATCCTACTGCCTTAAAGTGGTGTATGACCGTGTGGTACCCAAAAGGTTGTAGGGCCGTTCTCCATCCAGACGAAGAAGATCTAATGGGGTCAAAAGACATGTTAACATTACTATGCACAACGCCGCGCCTTTGGCGTCTGGTACGGACGAAGTTATACTAACGCGTGGTCGCTCACCAAAAAAATTCCGTAACCCGGCACTGAATATTGCAGCAATAACGTTCACGTTATTAGAGCTAGAAACCCACCACACGTGCGCGGCGCTTGACGTGGTCGGCTGCACAGGTTATCTCTCCCGGCGCACTGGGCGACCTAGCGGCCC
>seq8
TCTCGGAGTCCACGTTGGAGGAGATTCTACCATAGAAGTCGTACGCCGTATGGCAACCTATGTGGAGCCAACATAAATAATCATTTGTACTTTGGCACCGTACCTTCCTCTTTTCTCCGAGGACAGAGGATACAATGATGCAGTGTACTTACGATTATCTTGGTAAACACACGAGGGATCTCCGTTAGACGTGTGACAAAGATCGAAGCAGGGTATGATATAATTTTTTAGCTCATATACATATTTCGGATATATACATTTGAGAGAGGCCCGTTCGCTCAGCCCCGGACACTCGAATGTCTACGGTGGCCTCGCAAGGTCTGCATCTTCCATCAGACCAGTTCACAAGATACTCTTACGCAGTAACTGTCCATATGCATAGGGCGATACCTTAAACCACCGTAGGGATCGCTCTGTTTTAGCGGCGTGTATCGACTTTCTCCCTTGGGGCTAAAAACCTG
>seq9
TGTCAAGGTGTCGCTTACTCGTAAGTTCTTGGAGTCCCCAGCCGAGGACGCGTCATTCGGTAAGGGGTGTCGGTTACGTCCATTTGATCTCTATACTTGGCTATAACAGACTACCATCCGTCTGATAGGACTGTATCGGCAGTGAGGGACATTAAAGTGTCAAGGCTGTAATTGAACGTGTTGGCGTAAGTGATCCCAAGATGTACCTTTTTCAATGTGAAGCAACATTGTTAAGTCCGGCGGCGCAGTCATATATTCGAAACTCGTCATGATGGTGTCGCGCCGATTACCTACGTATCCGCAGACAAGGCGCCGTAGCTACCCCCGGAGCCCCCCGAGCTGCTTT
>seq10
TAACCGTGTTTAGGCCAAGCTGCATTGCTATGAGTGGTACATATCGACTTTGAGGATAATGCTGTTTGGTGTGTCAGGAATGAGGCGGTTCTATCCCGGTAAGATAGTATATCGGTGCCGGTTGAGGCTAACAGGAAGGTGGGGTACCCTGATAACGCACAATGAGATGCGGGCAGCCGCAACACAAGCGTCGCCGGCGCAGGACCAGACTGTGATTGACATAATCGATAAAATGTGTGCTAACATAATGACCCTCTGAACCTATGCACGCGCTCTATTGTGGGTAAACGTGGATCCATGATACAGGCTGCCCCCCCTTATCAAGATCAACGGTGCATCCATAGATATCCGATTGGTCCGGTGACGTT
>seq11
GCAAAGTAACCCGGATCAGAGCTTCCAATCACTCACGATCAACCTACCCCGGAAGTCGAGTCTTGCTTGTTTCAGCATGACGCCACGAATAGAGACGGTTTGGTATTAGCGTCAGGACGGAGAGAGAACGGAATAGCATCAATAAAGTTTTTGTATACATACATTGAATAATGTGCCGAGAAAAACTTGACATGCACAGCGCTGTGAGGCGGGGTCCAGGCGATCCCATGTGAGCTAGCAGTCCGCAGGAAGCTTTGATGTAGTTTCTCCCGCGTGTTCGGACCGTACTTCACCACGCAGTAGGCAATTGGTAGATCTGTAAACCCCAGCGTAAGGGGTAGCGCAGGATCCCAGCTGACCGGGAGTGCTATCTCAGGGTGTAGTGCATCAATGGCCAGCAGGCGTTAGTAATTGTAGCAGCACCCCCGAAGCTACA
>seq12
AGTAAACTTGAGAGCCGAAGTGGCTGACGGCTTAGTGGTATTTTCGCCCTTAACTGTTTACGGCAGTTTAGGCGGTCTTAGAGCTCCATAACGTCTTCTCCGCTCCCCGGATACCGGCTATAGTAACATGACACATCGATAGCCAAGTAGGCGGGAAATACCACTTCTTAGACGCATAATAGGGGTCAGCGCCAATTTCAGGCGGTCAGGACCCCTTCAACTAACGACGTTGCGTAACCCCGACTCTAGGGAGAGAGCCTAGTTTAGACATTATAGAGGAGAACATCACTCCGTGAAAATTAAGTTACACACTCCTCTGACAGGCGGCATTCTTCGGGAAAAGGTTCGTTCACCGTTGATGAGAGGCATCAAGTTCCACGCACGCTC
>seq13
CATCGCTAGGGTCAGCGCCCCGTGGCGCGACCTGTAGAGCTTGTGGGGAGTATTGTCGCGAGTGGTAAGCGTGTAACTAGAAATTACGGTGCTATATACTCCACGAAGTTACAGAAAACTAATGCGGCGTGACGATTGTATTTGTCAACCCTCCTAGGAGAGTTGTGTATGGATTCTACGCGCCGTTCGTAGTCCGTTGCAATGCCTGCAGTGTTCCCGGTAAGCCTCGAACCGGCGTCCCGGGTAGCAACGCATCACGTTGAATGATCAGCGATTTTTAGACCGGAGCTGTTCGAGCGGTCCAGGCACCGTAGCGGCCCGTATGGCTGGTGCCTGTATGTTTCGTTCACGACTACGGAACATCGGAAAGGGCACCTT
>seq14
GACGTATTAGATGGCTTTGCGAGTTCAAGAGCTTCGCCACTATGCATTTTGTCCAGTATTTGTCCCAGACACCCTTATGATCTACCCGCCACACGCTCGCTTGCGTTGTTCTGGTTCGCTTGTCTATGGCAAGCATAGCTTGCTTTAATGACATTCGACCGTAGTTTGGTACTCGTCTGGGAAGACTCAAGACTAGGCACACAGTGAAGGAGGAGGTAGACGCCCCGAGATCGTAGGATGGGTAGTGCGAGTATTCCTATGATCTACCTACTCGGTAAGGTGTGTACCTGGATCCACTCAGAAAACGACGGTCAAGTTCCAACATCGCTAGCTAAATATTCTCTGACACGCAGCTATTGATTTGGGAAGTGAACCACCTGGGGAAAGTGCATTAA
>seq15
ATACATGGGCATGGTTCTAAGCCCCACGTCTACGCCCGGCAAATTTCGATGTTTTGCTGTAGTGATATACTGAGTTGGCTCAAAACACGAACATAGTAAATGCTGACGATATCGACATTATGTTTGGCTTTAAAAACTCTCGGAAATATCCCCGTGGGGGTCGACATAACACATATAATGTGCAGCCCCGACCCCGACGGTGACTCTCGATCGGCGCGTCCCGCTCTCTTGTTACAACGGTGGCCCCGATTGATTGTGAGACTCCTCATGCGCGCTACCATGCTAAAAATGCTCTCTCAATAACAATGATTCTCACGAGGATAGTACCCACCGATCCCGAGTTTTATTACTGTACTCAATTGCCTACGCCCTGTAGCTGGCGCTGGTGGAGCATTGTTGTATGAAAGCTAATAGTAAACGGTGA
>seq16
TCGGGGTGATCGGTTAAGAAGTTTACGCTTGTCATCCTCTGTGGAGGGGTATCTGCACACGATAACCGGTTATCTTAAAAGCATGAATATCCCACACACTGCCTGAGACGGTGAGACGCGTGGACGCGAGCCCCTCCAAATCCCAGGAGTACAGAGTTCCCGGGCGACGCATTGAGCGTCTCGGAGGGATACAGATATCGCGGCGTTCAAATGAGAGACGTAGCTGCACGAGAAGATCAAGGTTGCCCAAGTATTTGTCGGCGACTGGTACAAGAGTGCTCTTACGTGGCTTGAAGGCGCAAACCTAGTCCCGATGCGGCGTATCTCTTGGACTGAGGGGGAGATCAACCATCAAAGACTAGCCCCAGCAAACCGATTAGTTCTAATTAAGGGTATATAAAATAGAAATCATTCTCTCCACCTCAAACAATAGACGTATACAACAGACCCGACTACGGCGTC
>seq17
CCGCGTACACGAGCCAGGTATTCCGAGACCACCTATATATAGTATTTACTGGGGCTAGAATATGGAGCATAGCCGGGACCAAGTTTGCAGTGACATTACAACGTAAGGACAACCTCAGATCCCTAGTGTTGAAAACCCTCCGTTCTGGTGCGTATTACTAACTCCTTTCCGTCCTCAGGGCGCCCCTGTGATCACCAATAGCCGAGTCTCTCACCCCGCTCTTAACTAATTTAAGTGAACGTCTTCGCTGATAGAGGGAATGAGCCCTGTATTAGCATGGGCATTTCTGTCATTTACACTTTTTTTGTAAGCGTGCGGAGGGTTAATTCGGTACACCGCAACGGCTAAGACGACATTAACCGGCCCGGCTGCC
>seq18
ATTACGCAGTAGTCCCGGTAATATGTGGTCCTCTTGCAGTAGCGCCTTATTACAACAGCCGTCGATTACTGGCAATCTTAAGTGACTTAGAGGCCCCGTCTACGGGTCATCAATTGTCGGTCAGCTATCCAATGATAAAACACGGTCGATAACCGTATGGCGAAGCGGGCCAGCCCGTTTATGGTCAGGTTCCATATATTGGACAGTGTCCGCTCTCCCAGTGAGAGCGAGTTTTATGAGTTTACCACTTAGGCTAGAATTCGCGATAGCCCAAAGTCGTCGATGTCGTGTCCTTGCCCCAGCGGGACTTATACAACAGCGGTTCTCAAAAATTTAACATAGAGTCATTTAGCCCTAATCGGGGATGACCCCTGCGGTGGCACAAGCTCATGTTCTCGCAGAAGCAAATGAC
>seq19
TGAATGTGTCCAACGCGATGAATGACGCAACCGCGAGGAGCGAAGTGAGCGGAGGTGTTCCCGGTGTTGCTGCTTGACAGCTCTAGCCATCTAGCTACGTGTAGCAAGCTTCGATTTCACGCGACCCGACCGTGAGAGGTTGGCTCACACCTTCCATGACATTGGATCTCGTTGGAGGTAGTCACGAAGGCCCACATCCGTTCGCGGGACTTAGTTAATGCATCGGGATTTATTGGCATATTGTACTTTTTTGACCCAAGGCCGCGACTTCAGGCCGCACGCCAAATCGCTACTGGCAGTACTATCGGCACAAGTGTTCGGACCCTTCGTCAATATTACACAAGTTATGAAGGAGGGGTTATTCTGGCACCGACCCGTGGTTTTACAATCT
>seq20
GGACCACATTATATAGATACCAGGATAGCCATGTCATACTCAGTTGTTTAGGGCTTGTAGCTTTGCTTCGAGGATGTATAAAAGAATGGGGCGATTGACCCAACATGTACATCAGAGAGGTACCCCACCACTTTACCATGCAGTTGTGTACCTCTTTTGCGGAGTCCCGCGGTACTAGTGTGTATTCGTTAACCGTTTATTTTGGCGAGCTTTGTTCGATTGGACCCCGTGTCCGAAGTCCGGGATTCCACGGACCGCATAGGTGTCAAGTAATCTACTAAATCGCCCGCCTTCCTACTACTGGACAAGCACTGGGATTCTAAGGAGTCCTTTTAGGTAATAATAGTCACTGTAACAGCAGAAGTTGTGTTAGGACGACTTAAGTAAGTGGTGGTTCTAGGTAAT
>seq21
TTTCGGCGAACCCTCCTGTCTGCTTGCGATCGGCATCAACCATGAAAATAACTACTTCCTAAAGCGGTAGAGGTAGAACAGGTTGGATGAGCAGATTACTGATCCACATGATCAACGGCACTAGCGCCACATCGTTACGGAGAAGAGGCGTCCGCCGAGTCCATGTGCATAGTGTTTATTCCTCTGAGAGCCCGAACTGAAAGTAAAGCCTTACTGTTAGTTTAAACGTGAGGGTTCAGAAATTGGCCACTAAGTGACCCAACTGCATGCGCCCAGCTGCCCCGACCACTGCCCCGGTTTCTTTAAGACCCAAGGAGGAAGCTCCCTGCTGGTCATGTATTACTAAAGCGAGACATCTTAGCGATAAGTAGCGGAAATTAATGACA
>seq22
AGTAGCGTACGTCATTAAAACTTTCAAAGTCCCAGTCAACGTGGCCGCCATCTGAGCCATAAGGCATACATACTGCGAGGCTCCAGTATGGTCACGAGTTTAAGCGCTCCCAAGCCCGATGGGCTTATGCTGATCCGTACATTGCGTACTCTCTATCAGCCGTACGATGGCAACGAGTTAGTGTTAGATGAATCCAGGGGCTGCCGTCAGACTGCCGTAAGCTTCCTTGCTTTGGTTGAACACTAGTGGTTTTCCTGAGTAACCTATATCAAGCTGAGGGAGTGTGCAATTATCGAGCAATACTTGAGGGCCTATGATGGACTTGTCCAAGATGTAGAGGGGGCTTCATCGTTAGGGTACAACGCAAGAGTA
>seq23
AGGCGGAGTAGAACCGGTATAGAGCTCTAGAAGGTGTTACGACCCCTGAGGGGGTATGACGATAGGTAAGGATCAACTTGAGGAGCACCGTTATGATGCGGGGTATTAATAAAGTCAGTAAATGCATGGCTCGATCGATAGTGTATTTCCTTCTATGGATTTCCTCACTCTAGGACTAAAGGGCGGCAGTGCGTAAGGGACTAATCAGTTAGGCTGCGGGAGTAATTTGACCGCTTACCCGCTTCTTTCTTCGCCCACAACAGGGAAGCGCGGTTTGAACCTGAGATTCACTTCTCCGCACTTTCTAG
>seq24
AACATCAGCTCCTCTTCTAAGCTGTTCCAACGGAATAAACGGAGTCTAACGTACGGAATGGTAAAGTCTTCGACGCGATAGTTGGATATATTGGCTTGGGGAAGTGACACGAAGGGATGAATCAATCGCCAATCACCCTACCTGGGTATTTACATTAACCGAGCGCTACAACTAAACACTGTGCACTCTCGCGGCACCAGGAATTGAGTCAAGCTTCGCACTGGCCTACCTCACAGGGGGAGGGTCATATTGTTCGGCGCAAGATACGGGGAATAGAGGCCTGACTGCGATGGAACAATTTGACTGGCTCGTATGCAGGCAATACACCACGAGATGAAACAACCCTGATCACCGTTTCCCCTCTGCGAAGCCAAGGGCCTATGCATTATCTGGCTGACATC
>seq25
GCGAGGAGAGCCCGGTTTGTAATCTGTCTACCAGTTGAAAGCCGGACAGCTAAAACTGCGTGCGGCCACTTTAGGCTCCTGGTCAGTGCGACGCGGATGGAGGCGGAATGGGGAGTGTTTACGGGCTCAACCCAGGAATGTCTCCCTAAGAAGATCGTTCTGTCACAGGATCTGTGTATACTCCCCACCGGTCTATATTAGCACGGCTCTATAGAATGAATCCGTCCCACAGAGTTCATAGTGGTCAAAGAGGAGCGACTCAGGTAGACACCCACGAATCATTTCCTGGAGATTTTACTTTGGAGACTGCTGATTTCAGCCACATGCTATCGTCTCAGGCGATCGGCCCCTACCATCTCAAGAGTTGCAGAGATCCTGTTCTCAGCCCTGTCTTGAACTGGGCCAAATTGACAACTCAGGGGAAACAGGTGGACCCCTGCTTCCCAGTGCAGACAATCTAGTCCAACTAACTTAGA
>seq26
TCGCGGGTAGACGAGCTTTGGTTACAACCTCTAGAGTGGACCGTTCGGAGGGTATCGGGCCTACTCAGACAACTCGATGCTTTATGACATTGCACCAAGACTGGTTTTAGCGCCCGAGCATGTATACGTCACATCATGAGTTTGGCTACTAAGGTCGATAGACACAAGGTCTGAACAAACAAGCATAATATTTCCCCATCTTTTGCGAAGAAAAGGCCGGCTGGTACTTGTGGCTGGGTCCACATTGGCTAGCAATTAGATTGCATACAGCTTGTACACCCGAAAGGATCTTTTGGGATAGGACGCTGAAAGCGCTGACACCAGAAAATATCTTCAGCCACCATCAAACGCTTCGCGCTTGAGGCATTTTTATAGACGACTCTGGCCCCCCCTCTGTGACAGCTTCGTAAAATTATCCTCGCAGGTGGTGCCCCCACGTT
>seq27
TACATGCGGGCTTATACTTTTGGCAGACCGCGTTGGCAGTAATCTAGGTCACATTTCAACGAGATAATAGTTAGCCGCCGCCTCGACGTTAACCTGCATTGTTAGTCAAACAAAACTGGGGTATTCGACTGGCCATCACATGTGACAGACATCCCAAACTCGTCATCACTCGCTTCCCCCCTAAGGACGGTTGATATAAGGTCATTGAAGGCAATACGGCGACGCCCACTCCAGCATTTCTACTGTGGCCGGCGACTGCTAGCCAGGTGTGCCGCTTCGGGAGTATCCCGTATAACTCGTCTAGGTATAACGATACATCGTTGTCCAATCCGGGTCATGGAGCAGCAATCTGATCAAGCCTTTTAACTCGCAGGGTGTATACTGGAGGCTCCTACCTTGACTTTGCATGATAGCGAC
>seq28
GTTGACTTGGCCTTAGGGCGAGGTGTAAGCTAAGACCAAAAGCCAACATGAAGTTATGATGTCGTATCGTCTGGATCGGGGCTGACTATCCCCTCCCCTGTTGTCCGGAGCAATGCGTCTAAACGGAGAGGCGCGGAAGATCGAGCCAAACTATCTGCTTCAGGGCTAACATCGCTTATAGGTCGCTAGAAAGTTCGTAACTCAGATTTTGCGGCTATTGCAGTCTTTTTTCTTTACAACCACTCCTGCGCACATCAGGCGACTCCTGAGAGCCTCTCAGGAGATAGACGTTGATTGGTTTGAGTGAAGTATGTATCCCATCAACCCGGTCAGCCACGCGAACGAGAGACAGCTCCGCTCGAAGCGCATCTTATGAGCA
>seq29
AACCTTTTTTTGGGCCATACCTGGATAAAAGACTCGTGATTAGGAAAACGTTGAGCCCGATATTATTGGGGGCGCTTGGGAGATTAGTAGACTGGACTGAATCAAAAGACAGGCTGCTTTATAAGACACTATGCAAGGTCATCGGAGCTACCAACTACTTAAACAGCGGGCAGATATTGTTGCATAGGTGTTATAAAGCGCACGGCACCATTGTTGAAACTCCTATTCCCTTCCAGCAAGCCATCGGGATTCGAGTACCATTCACCTAGTCACAATTGCTGAGCTTGTACGGTGGCAGTATCAGGATAGTTCAGACAGACACTTATGAGTCGTTTAAGTAGCCTTCAGCGGATTCCATCTCGCGTG
>seq30
TAATATTTGCAACCTTGCACAACGTAGCGCTCGGCCGAGAGTACTAATGCTTGCCACGTATATGATTGCCCTCATGGGTGGCCTGATAGGTTTAACATAACGCAGTAGGCGGACCACAAGCTGGAAAAGCCTTCACTCCATAGCATATATCCTCTTAGAGCGGCACATCAACGGAATACAAGCCAGTTTCCCAAAACATCTCTAGCACCTGGTGGCACTAGATGGGCTTGTGTGCGAGACTGTGACGTGAAACAGACTCCTGGCTGTCCAAACGTCAACCAGACCATAGCCAATATGCTGCGCCCGTCTCGGATCAATTTAGGCATTGCCTCACCACATTTTAATTCGATGGCGTTGTCACCGTAAACTCCGAT
>seq31
CTTCGAGAAGTTTAGTCGAACAATTGTGATAATAAACCGACCCACGTACGAACGCAGCTAACCGTCCGGCATTCCAGCGATAGACGGAAGATTAAGTAGCTCCAACGCCGCCAAGTCTAGGTCTATTCGGGATATTCGGTGTGCCGAGATAGGAGTCCACACGGAACTTTAGCCAGGTTCTGACGGATATTGGCATTGGGGCAACGAGCGCATGGAAACCCCACCTTTTGTGGTACGCTGATACCTCAGCCCTACCACCATATTCTTTAATGTCTCATGTGCCGTGAAGTACGTCTACGTTACAGTGACTGACCCTTCCCCCTTGTAATGGATTGCGGGCTGGTTGCTCAAGGCTAATGCGATCCCCGCCGGGGAAGTGTGCCACTTCGTCATGCTTCAGGGCTACAGAAAGGAATTGACCTCTAG
>seq32
TGGTAGTGGGTAAAAGGCACCTTTGAATCTGCTCATCCGAGCTAACCTCCACTAGGGCAGCAATGCAAGGGAGCTGATAACACGCCCCGTAAACCCCGTTACAGCATCATTGGACCACTATAAACCATTCGGTTTCATCTGTGTTTTATCCACGAAGCATGGCCATGTGTATAAACTGACGGATTGGCGTCCACTGTAGGGGCCGCATCGTACATAATCCATGCGTCCAGGGTGGAGACTCTGGTTGACCGTACAGGTCGTCTGTACTTTGGCCCACAGCCAACAGGAATACCTGAATCAATGTCTAGTGCTTGCCAATCATGTGATCGAGACGAGCCTAGAGCAGTTACACCTGCTTCGTAAAGGAGGCCTTCAAAGCTAAAGGTCGCTAAT
>seq33
ACGACCGTTCAAACTAGGTCGGATCCCGGCCGTAATCAGCTGTCCTGTATAGCGCGTTCTGACATAAATTATTCGTGATGTGCCAGTTGTCTGTGCCAAACCTAACCTTCCTTCTTTCGACCGTCGAGCACTCCACTTATCCTCTTAATTACGTAACAGACAGCAACTGCATACTAGATCTTCAATACATGTTTTGCGGGTACAGCCCGTCTGGCCCTGTTGCTCCGTGGAGGAAATTAATAATGGAACTCGTAAGTTACTCGCTAGTACCCATGCCTAACTTCGTTGGTTTAACTGTAGAGTCGTACTCCGGTGGAAGGTGGTGGTCAGAAGTTCGTCACGGGTCTTAAACACTGGCGTTTGAGCAGAATAGGCTCACCCTGTATCGTTAAAGATGGGTCGTCCTATCCCGTGGTTTGACCTCTCTTACCGCCTCC
>seq34
CTCTAATGCCGGTTTAATTGCCGGTAGATACATGGAATGGGCGATTGAGTGTCAAGTTCCGCATCCGAGTAGTCGTAGGGCACTTTTCCCCAGGTTGTCAGTCTTGAAGTCACAAACTCAAATGAACAAGAATCACTCCGTTGTGAGTGATGATTATGTAGATTGTGGGATCACATCCAGGTGACAAAGCATCGCATATTAGTACACCTACGGTCCTTAGACTTATGGCATGCAGCCACGCAGACATTCACAGGGTGAATTGATGCTACACTATAGTCTAGCGTATTTGCTTTAGTCCCTGGCTTCCAGTATTGGTCCTGTCCACAGCTCTACTCTGCTACCGGGCCACTTGAATCAGCTGCGCCAAGCAATCGGGCCGGATAAACCTCGCCCAGAAACA
>seq35
GAGTCCAAGATTGCTTGGCTCAGGGTGTACCATTGCAACTATACAGGCTGGACGCCGTGGGAAGGATAGAACATCATGCTTGCATGTCGGCGAATTTTTGGCCTGGATCTAAATTGGAAATATATCGATGAAGGTCTCCCTTACCTCCAGGCCGCGCCCAAAGTATATGCAGTTCGTCGTGTGAAACTGGTCAGTGGCTTCGATAGATAATCCTCGGGGCAATACGAAGAGGTGCAGAGCATTGAATAAGAGCGCAACTAGTCATTTGGCTTTCACAGGATGGAGCTGAAATCTT
>seq36
CGTAAGCGTGCCTACGACTGTCGCATCAGAGTTTCAGACGACGTATGATCCTACCTCAATGGCGCATGAATGACGTGCAGACCGGGGCGCGTCACATGTCCTAACGAACACGCGATGTTTTAAGCTCACCTACCAGTTGGCGACTTGTCAAACCTAATGATGCTACCCGGCTAATGGCCCGCTATTTGACCTGGCGGCACAACGCTTGGTGGGTACTGAGTGGGGGAATTTGGTGACGCCAATTAATCGGTTATGGTTATTGGTTACCTAGAGCCCAACCCGCCTTGTAGATTAGGCGGCACGGACGACAGGGTAGCTCTACTTCTGGAAGATCCCCCAGCTTATACCGACCTCATCAATTGGCTGAGAGGAACTGGGGAACCGACTAGTTAACGAGACCACGCCTCGTCGGGGGTGCC
>seq37
AAGGCGCTTTTCGATCGATAATTTCCAATTGGGTCGACATCTTGGATCGAGCGAAGTACATGGGCCGTTCTACGTATATGGCCATTGGCCTCTCGACTATGCCACCTTGCCATTTCCTCTACCTCCATAGGCGCTAGGTTTAATAATATAGTTAAATTCAGACTCCTTTTATGCTACCTTTAGTGAGGACCCGCCCAGAATAGGGAACACGCGACTGTGGACGCGTGAAGTGTGCTTTATTACGTCGTCCGGTGGTGAGTGTCGACAGATGCAAATATATGAGGTAAATAGCCGCTCACATCAACTGCTCCGGTTACGGGCCTAGGTTTGGGGGCGACAACGCTTCTTCTTGACCAACATAGGCTATCAC
>seq38
CCACCCGTTCGACCGTCTGTTGTTGAGACAAGGGGCGCGGGTAGGTACAGCGTGAGTTCGTAAGCGGCAACGCTTGCGTGAGCGCGTTTTGTGTCATTCTTGAAGCCACCGCAAGGTAGCTTCGCCAAATAAATGACAAGATCAGCGCTTTACTGGGGTGCTCGTAGCTTACTCCGGTAGACAGCTAACTTTCACCCGGCCTTGCATAGCCTTGATCTCGCTAAACTCGACCGGTCTTAAGACACGCGACTCAACAACATTCCATCCTGCAATCGTCGCGCTAGAAACCTAAGTTATAATTTATTAAGTGCATACCTGCATGTCGAGCTACGAGTTCTTTGCTCCTTGGAGGTGGAGATCGAACTGGCCGTTCGATACCTTATGTCGATCTCGGCTATCAAGTCAACCCC
>seq39
CACGGTGGCGTTATTGATTACTGGGTCGGCGCGATTTACGGTTTGATAAGTCGGCTTTCGCTCGTGTTAGTCACTATATGGCCGGTACAACCGTGAGGTGCAGATTTATTTCACAGATCCGGTGCGATAAATGGTTTGTAAGGGTTCTCATTAGCACAGGGTAAAAGTAAAGGCGGTAGCCCCAAGGTGGCCCCCCAGACAGACTAGGATGATGTGTGCGACCCTGACAATTATGAACAGTGACAATCAGGCATCGTAATGCCCTTAGAGGCCTTGGTACCACTAGGCGTCCGGATCCCCAGTGGTTGACTAACAAACAAATAGTTAGGCTTAGAATTTGCGAGATTCCGTCCGACCTGGAGTATGCCATCTCTCAAGTCCACACTG
>seq40
TGAAAGAACGTTTCTAGCCATTAAATGCACCAACAACCGCCCAAGATAACTCTATGAAACGGACCCGATTGTGAAACAATAACCCCCCCAATAGTGCGCTCTACTGAAAGACGGTTCCAGCCTAATTGACAGTGTACCCATGCCTAGCTGGCATTACCCTATGATTGATACGATCATAACCATACCGGTGTCCATCTTATAGACCGTAGACGATTTGGAGATCACCAGCGCAAAGAAGCATAACCTTTTTACTAAACGTGATTGCCAATCGCCAACTTATGTTGCCCGATGACAATAGAAGGCTGGCCTGTATGGCTTTTATACTGGCTCTTGTTCATTCGTGCTCCCGCCGAAGCTAGGTCACACTCTATGCTCCGCAAGGACAGAATCGCTAAA
>seq41
TTTACGGATAGCCTAACCCAGTCGTCACCACATCGAGTTAGTAACCGGAAGCAAGCGACCTGACCAGACTTCCTCGGCTATGTCATATACATTAGTGCTAAGTCCCGTAGTCGCGGGTAAGTACTCCCCTCCACGTACCGATTACTTGGTTATCAGCTACTAATTCTCCGTCTCTTTGTATCAAATGGAATGTATCTCAGGAATTGGTTGACCCAGGCCATGCTAGCCCCCGGTGTTATTGGACTAGACTTGTTTCTGATATCCACGCTTCGGTAGCAGATGACTATAAACGCGCGGAGTCGGTGGCCTGGCACTGCTGGCG
>seq42
TTTTTAATTTTGCAGTAAAGCTTCCCAAATCTGCGCGTCGCTTGATACATTGTCGGGACAAGCGCGTGCGCTGCGATGTCCTTTGCCTCCGTTGACCCGCGAACGTGGGATAATACGCGGTATTGCCCACCCGCTCGGCGGGAGGCCTACCGTTCTAGTTTGTGTACATATGGGTGTAAGCCCGCTTCGGCCCGCAGTAGTTTTTTCACCTGGCAAGCGATAACGCCCCCCATTCTCACCATATATAGAGTAACCGTTGAGAAGTTCAATTCTTTTCTCGTA
>seq43
TGCCCCGTAGGGCCCGGAAAATCACCACCATTGGGGCGAGAAGTCTGATACAATATGGCGACGAGATGGGATTCGTAAGGATACAAAGCTTCGACCTTCAATTCTACACGCTGTAACAGCGCCTCATTCCGGAGGTCTCTCGTTTTGATGCGCACGGCAGAATACTCAATAGGGCCCGTTTCTCACTGTTTGTAATAACCGCTCGCATCATCAGCGCTAACTCCTTGGTACGCAAGCCTGATCACTTTTTTTCTACCAGGCGGCTTTTTACTGCCGGATCTGGACCTCTCGCCGAGGTCTCCGCCGGCTAACTTAGCGGTACATACATAGACCTAGG
>seq44
TCACCGAATTCACCTTGAAGCACTCTGTACATGCGTACATTTCGATTAGGTCGCAGCCCTACTCATACCGTTAACTAGCGGCATGCAGACAGCCTCGTCCTCTAAATCTGTAAACCTGGACCATATTCGAAAGGGCTCGACCTTCAAAAAAGTAAGGATTAACGACAGGCTCCTTAATTCCGAGTTACCTCCATCCACGAGCGTACGGGCGACCAGACATCCTAGGGGTTTAGCAAATCCTGACACCGAATTATCTGAGACCCCTAGTACGGAGCGAAAGTGCTCACCGAAAGCAAGCCAGGGTTTAGTGCCTTCTAGATCCCGCCGATTACCTCGGCCACGTACAGCACTGCCCGTCGTGCAGCCGCTTGAGGGTGATAGACTCCTATAGGGTGTTTA
>seq45
CCTGATTAGCTTGTCTGGATGGGGCCCACCTCCAGAGTTCCTCCACTGGAACCAGCCTTCGAATACCGCTTTCTATTAATACGCCTAGGAAGCCGTAGATGGGGACCCTCCCCAACACGAAATAAGATTCAGGCATAGCTTTGGATACAGTCCCGTTTCGGTAGATGGGTTGACGGGCGGGTTAAGACGGCAAATACGTTGAATCTACTCTACGGTTAGATGGCTGGGTGGTAGCTTGTGTGACACTTAGAAAATGCAGAGATGCAAACTAGGAGTAATTCCCCGGATCCGTACAATCCTTGGGCATACAAGAGGAGAAAAACCTTCCGAATCCGGCATTCCGGTAGGACAGTCACGGCAATGCGGGTGCGGGACATGTGGTTAACCGGT
>seq46
GTTCATCCGGGTCTTGCTGGAAAGCGCGCGGAACTTACGACGGACCGACGGCATGAAATCTTGGTTGTGCGGGGAACTGTGGCGTGTGTTAGCGGGCTAACGACAGGGTTAAACCAGATTTGACGCCTTGAGGGTAGAAGCGTGCTTTGTTGAAGATTAATGCGCTTGTCGGGTTTCGCGGTTTGGACGCTCGAAACCCTCCACGCATGCATTCTAAAGTGTATATCGAGGTCGGACTGAATGGCAACATGGTAGTTAATTTGTACGCCACTACCCAGGAGTCAGCTCCGAAACCAGTGCACCGCGCACGGTGGCTTAGTTGCACGCGAGGGGCCATGGACCGGCTCCTCTCTTGTACTATCCCACAGAAATCGCGGTGGTATACCCCTA
>seq47
GATGTCGTACGTGCAGCTACTTTATCTGACCGCAATGGCGTAAGTCGGACGCTGAAGGGATGCCCCGTGTCCTGCTGCTTGATCAAAATTGTGGTAGGCTATTGTGATAAAGATTACCGTTTCTCTCTCCAAGCTTTAATCACGCAGTCCTTCAACGGACCCCCTGTTTGGTATACTATGACACAAGGCCTAATTTCCGGGACCAGTACGTGAGGAGACTAAACAGTTTGGCCTTCTTACGTCCAACCCGCTTGTAATCCTTCGCCCGAGACTTCGTTCCCTCTCTAGCTCTCACTACTGCGGATCTCATAACTATAACTAAGCCCATGGATAAACATACCGAAGCAAATATTGCTCATTCGCTATCCTGGATCCTGCTGCGTAGCGGGGATCGGATTCATGGCCTGGCTTCCATCCCTGTG
>seq48
AACCTGCGCACTTGATCTTCACTCTTACTCTAACTGCATTATCTTAATAAGGGTGACGCCAAGTTCTAGCGCAGAGGCAGCCGGGACTGCATTTAAAACCTGACATTTGGCATACATCTCTCGAGTTACAGTTCATGATCCTTTATAATGTTACGCGCGGTCAGTATGTGGCCTCCGCTACAAACGCTGATATACGGAAACACAGCTCCGTGGAGGCTGAGAGGGTAAGGCTTCCTCAGTTTTTTCCGGTTCAGTCACAGCTCCAGAGGACTACGCAACATCGTTCGGAAACTTGCAACCATTGGGGCATGGCGGCCTCAGGATTACAAGACCGTCCGAAGCGCCCAGATGCTAGCAGCGATACACGTTATTTAATTGGC
>seq49
CCAGGAGGGACAAGGCAGCGTTATACCGGACAGTCGACACCAAGAAAGACCGCGACCTAGTTAAAGTCAGAGGTTATGATGTGGCGTGGAGTTGCCCTTGGCGTTGCCCGCATCAGAAGTCTGCGTGGGTAGTGCTCAGGCCACCCATCTCGTAGAAGAACCACGTGCTGACACGATCGGTCTGGGCGCCTCGCATTAGTTCAACGGACCGCTGGGTTTGAAAGTATGGACTGGACGACCGACTCACAGTGTAGCGGTAGTATCGGTCGCCGTACGGTATCCCAGCTAGTGGCGGATCTTGACGGACACTACAGCCTGTGTTGTTCACGTGTAATTTATTAGCGCTACCCATAAGAGATTGTGGAGCGAATTGTGATCACTGAG