python - 如何在 biopython entrez.esearch 中下载完整的基因组序列

Question

我必须从 NCBI(GenBank(完整)格式)下载完整的基因组序列。我感兴趣的是“完整基因组”而不是“全基因组”。

我的脚本:

from Bio import Entrez
Entrez.email = "asiakXX@wp.pl"
gatunek='Escherichia[ORGN]'
handle = Entrez.esearch(db='nucleotide',
     term=gatunek, property='complete genome' )#title='complete genome[title]')
result = Entrez.read(handle)

结果我只得到基因组的小片段，大小约为 484 bp:

LOCUS       NZ_KE350773              484 bp    DNA     linear   CON 23-AUG-2013
DEFINITION  Escherichia coli E1777 genomic scaffold scaffold9_G, whole genome
       shotgun sequence.

我知道如何通过 NCBI 网站手动完成，但它非常耗时，我在那里使用的查询:

escherichia[orgn] AND complete genome[title]

结果我得到了多个基因组，大小范围约为 5,154,862 bp，这是我需要通过 ENTREZ.esearch 完成的。

Answer 1

你的问题很明确，但完整的答案很长。我提供的代码为每个所需的大肠杆菌基因组序列生成一个 .fasta 文件，是的，只有 NCBI 中的“Complete Genomes”。

您会看到 NCBI 中只有 六个 完整的大肠杆菌引用基因组 (http://www.ncbi.nlm.nih.gov/genome/167):

为了帮助您，这里是指向他们基因组的 Genbank/Refseq 链接:

1. http://www.ncbi.nlm.nih.gov/nuccore/NC_000913.3

2. http://www.ncbi.nlm.nih.gov/nuccore/NC_002695.1

3. http://www.ncbi.nlm.nih.gov/nuccore/NC_011750.1

4. http://www.ncbi.nlm.nih.gov/nuccore/NC_011751.1

5. http://www.ncbi.nlm.nih.gov/nuccore/NC_017634.1

6. http://www.ncbi.nlm.nih.gov/nuccore/NC_018658.1

这是我将完整基因组序列解析为 .FASTA 文件的代码...

# Imports
from Bio import Entrez
from Bio import SeqIO

#############################
# Retrieve NCBI Data Online #
#############################

Entrez.email     = "asiak@wp.pl"             # Always tell NCBI who you are
genomeAccessions = ['NC_000913', 'NC_002695', 'NC_011750', 'NC_011751', 'NC_017634', 'NC_018658']
search           = " ".join(genomeAccessions)
handle           = Entrez.read(Entrez.esearch(db="nucleotide", term=search, retmode="xml"))
genomeIds        = handle['IdList']
records          = Entrez.efetch(db="nucleotide", id=genomeIds, rettype="gb", retmode="text")

###############################
# Generate Genome Fasta files #
###############################

sequences   = []  # store your sequences in a list
headers     = []  # store genome names in a list (db_xref ids)

for i,record in enumerate(records):

    file_out = open("genBankRecord_"+str(i)+".gb", "w")    # store each genomes .gb in separate files
    file_out.write(record.read())
    file_out.close()

    genomeGenbank   = SeqIO.read("genBankRecord"+str(i)+".gb", "genbank")  # parse in the genbank files
    header         = genome.features[0].qualifiers['db_xref'][0]          # name the genome using db_xfred ID
    sequence       = genome.seq.tostring()                                # obtain genome sequence

    headers.append('>'+header)  # store genome name in list                                     
    sequences.append(sequence)  # store sequence in list

    fasta_out = open("genome"+str(i)+".fasta","w")     # store each genomes .fasta in separate files
    fasta_out.write(header)    # >header ... followed by:
    fasta_out.write(sequence)  # sequence ... 
    fasta_out.close()          # close that .fasta file and move on to next genome
records.close()

让我知道进展如何!安迪