#Marta Pla Diaz, May 26 (2021), for python2.7 # Using as input the files generated in the previous script: "sense_genes_pangenome.py", where the reading frame of each gene is obtained according to the gff files of each # genome references used, with this script you will obtain 2 output files. In one file will be each gene besides of the number of stop codons that have each gene traslated separated by # commaa, and in the other file will be the number of codons truncated by gene and by strain (also separated by comma). Then you should load this two files in excel, #indicating the separation of each cell by commas and then put the order of the strains as header according to the list below marked with *** #inputs needed: the outputs of the script: "get_name_and_gene_sense.py" that have this ending: ".._genes_sense.txt" #This function importa list of the files of the directory in which run you this script from os import listdir #This function get all the files that are in the path where you run this script def ls(ruta = '.'): return listdir(ruta) #This function get a python dictionary with the gene reading frame and its name def pauta_lectura_de_gff(nomfichero_gff_Nichols): dicc_pauta_genes = {} fich = open(nomfichero_gff_Nichols, 'r') for line in fich: # con este if quitamos los retornos de carro if line.endswith('\n'): # Alternativa a if line[-1] == "\n" line = line[:len(line) - 1] if line.endswith('\r'): # Alternativa a if line[-1] == "\n" line = line[:len(line) - 1] line_div = line.split(" ") nombre_gen = line_div[0] dicc_pauta_genes[nombre_gen] = line_div[1] return dicc_pauta_genes #function that loads a dictionary with the genetic code def codigo_genetico(): dicc_genetic_code = {"ATA":"I", "ATC":"I", "ATT":"I", "ATG":"M", "ACA":"T", "ACC":"T", "ACG":"T", "ACT":"T", "AAC":"N", "AAT":"N", "AAA":"K", "AAG":"K", "AGC":"S", "AGT":"S", "AGA":"R", "AGG":"R", "CTA":"L", "CTC":"L", "CTG":"L", "CTT":"L", "CCA":"P", "CCC":"P", "CCG":"P", "CCT":"P", "CAC":"H", "CAT":"H", "CAA":"Q", "CAG":"Q", "CGA":"R", "CGC":"R", "CGG":"R", "CGT":"R", "GTA":"V", "GTC":"V", "GTG":"V", "GTT":"V", "GCA":"A", "GCC":"A", "GCG":"A", "GCT":"A", "GAC":"D", "GAT":"D", "GAA":"E", "GAG":"E", "GGA":"G", "GGC":"G", "GGG":"G", "GGT":"G", "TCA":"S", "TCC":"S", "TCG":"S", "TCT":"S", "TTC":"F", "TTT":"F", "TTA":"L", "TTG":"L", "TAC":"Y", "TAT":"Y", "TAA":"STOP", "TAG":"STOP", "TGC":"C", "TGT":"C", "TGA":"STOP", "TGG":"W",} return dicc_genetic_code #Function that opens the file with the alignment of complete genomes to be processed and from which we obtain the sequences def abrir_fichero(nomfichero_align): secuencias = [] fich = open(nomfichero_align, 'r') seq = "" for line in fich: if line.endswith('\n'): line = line[:len(line) - 1] if line.endswith('\r'): line = line[:len(line) - 1] if line.startswith(">"): if seq != "": secuencias.append(seq) seq = "" secuencias.append(line) else: secuencias.append(line) else: seq = seq + line secuencias.append(seq) return secuencias #This function create a python dictionary with the sequences in which the name of the genome is saved as a key and the genome # sequence as the value def crear_diccionario(lista): diccionario = {} contador = 0 while contador < len(lista): if lista[contador].startswith(">"): new_clave = str(lista[contador].replace(">", "")) diccionario[new_clave] = "" clave = new_clave contador = contador + 1 else: diccionario[clave] = lista[contador] contador = contador + 1 return diccionario def procesar_genes_traduccion(dicc_pauta_genes_Nichols,dicc_genetic_code,lista_genomas, dicc_seq, dicc_final_stops, pauta_gen, dicc_final_truncados, nom_gen_cons): contador_genomas = 0 while contador_genomas < len(lista_genomas): genoma = lista_genomas[contador_genomas] seq = dicc_seq[genoma] seq = seq.upper() if pauta_gen == "-": reverse_seq = reversa_complementaria(seq) contador_codon_base1 = 0 contador_codon_base2 = 1 contador_codon_base3 = 2 contador_truncados = 0 contador_stops = 0 conta_codon = 0 while contador_codon_base3 < len(reverse_seq): codon = str(reverse_seq[contador_codon_base1]) + str(reverse_seq[contador_codon_base2]) + str(reverse_seq[contador_codon_base3]) contador_codon_base1 += 3 contador_codon_base2 += 3 contador_codon_base3 += 3 if "N" in codon or "-" in codon or "Y" in codon or "B" in codon or "M" in codon or "R" in codon or "S" in codon: contador_truncados += 1 else: aa_cons = dicc_genetic_code[codon] if aa_cons == "STOP": contador_stops += 1 conta_codon += 1 if nom_gen_cons in dicc_final_stops: dicc_final_stops[nom_gen_cons] = dicc_final_stops[nom_gen_cons] + "," + str(contador_stops) else: dicc_final_stops[nom_gen_cons] = str(contador_stops) if nom_gen_cons in dicc_final_truncados: dicc_final_truncados[nom_gen_cons] = dicc_final_truncados[nom_gen_cons] + "," + str(contador_truncados) else: dicc_final_truncados[nom_gen_cons] = str(contador_truncados) else: contador_codon_base1 = 0 contador_codon_base2 = 1 contador_codon_base3 = 2 contador_truncados = 0 contador_stops = 0 conta_codon = 0 while contador_codon_base3 < len(seq): codon = str(seq[contador_codon_base1]) + str(seq[contador_codon_base2]) + str( seq[contador_codon_base3]) contador_codon_base1 += 3 contador_codon_base2 += 3 contador_codon_base3 += 3 if "N" in codon or "-" in codon or "Y" in codon or "B" in codon or "M" in codon or "R" in codon or "S" in codon: contador_truncados += 1 else: aa_cons = dicc_genetic_code[codon] if aa_cons == "STOP": contador_stops += 1 conta_codon += 1 if nom_gen_cons in dicc_final_stops: dicc_final_stops[nom_gen_cons] = dicc_final_stops[nom_gen_cons] + "," + str(contador_stops) else: dicc_final_stops[nom_gen_cons] = str(contador_stops) if nom_gen_cons in dicc_final_truncados: dicc_final_truncados[nom_gen_cons] = dicc_final_truncados[nom_gen_cons] + "," + str(contador_truncados) else: dicc_final_truncados[nom_gen_cons] = str(contador_truncados) contador_truncados = 0 contador_stops = 0 contador_genomas+=1 return dicc_final_truncados, dicc_final_stops #This function generate the final file which contains all the genes annotated in each ref genome used # and the numbers of stop codons or truncated codons per strain for each gene def archivo_final(dicc_final_truncados, dicc_final_stops): nom_fichero_final_cod_stop = "num_codones_stop_per_gene" nom_fichero_final_cod_trunc = "num_codones_trunc_per_gene" print "\n---> Generando el fichero con el numero de codones de stop por gen y cepa...\n" fich = open(nom_fichero_final_cod_stop, "w") for gen in dicc_final_stops: fich.write(str(gen) + "," + str(dicc_final_stops[gen]) + "\n") print "\n---> Generando el fichero con el numero de codones truncados por gen y cepa...\n" fich = open(nom_fichero_final_cod_trunc, "w") for gen in dicc_final_truncados: fich.write(str(gen) + "," + str(dicc_final_truncados[gen]) + "\n") #This function calculate the complementary reverse sequence of a sequence def reversa_complementaria(seq): complement = {'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A', 'N': 'N', '-': '-', 'Y': 'Y', 'B': 'B', 'M': 'M', 'R': 'R', 'S': 'S' } return ''.join([complement[base] for base in seq[::-1]]) def main(): #To change it each time: nomfichero_gensense_Nichols = "genes_pangenome_25_05_21_genes_sense.txt" #nomfichero_gensense_BosniaA = "BosniaA_NCBI_genes_sense.txt" #nomfichero_gensense_CDC2 = "CDC2_NCBI_genes_sense.txt" #nomfichero_gensense_SS14 = "SS14_NCBI_genes_sense.txt" dicc_pauta_genes_Nichols = pauta_lectura_de_gff(nomfichero_gensense_Nichols) lista_genomas = ["SamoaD_real", "94A_SS14_mapp","CZ34_SS14_mapp","CZ27_SS14_mapp","SW8_SS14_mapp","NKNP1_CDC2_map", "R8-KOS-007_CDC2_map","IND1_CDC2_map","133_CDC2_map","C3_SS14_mapp","UZ1974_SS14_mapp", "WP0022.7.scab_CDC2_map","GHA1_CDC2_map","NL11_SS14_mapp","UW824B_SS14_mapp","Nichols_real", "AU16_SS14_mapp","PT_SIF1242_SS14_mapp","UW370B_SS14_mapp","CW59__Nichols_mapp","CDC2_real", "MexicoA_real","AR2_SS14_mapp","WP0022.7.liq_CDC2_map","Chicago_real","SJ003_CDC2_map","K3_SS14_mapp", "BAL73_Nichols_mapp","AGU007_CDC2_map","Fribourg_real","K363_real","PT_SIF1156_SS14_mapp", "NE20_Nichols_mapp","OKA_2116_CDC2_map","HATO_CDC2_map","Gauthier_real","SS14_real","SEA86_Nichols_mapp", "BAK_2117_CDC2_map","GRA2_SS14_mapp","CW82_Nichols_mapp","SHD-R_SS14_mapp","CZ33_SS14_mapp","NE17_SS14_mapp", "CW85_SS14_mapp","94B_SS14_mapp","PT_SIF1196_SS14_mapp","PD28_SS14_mapp","BosniaA_real","W86_Nichols_mapp", "SW1_SS14_mapp","W86_SS14_mapp","CW86_Nichols_mapp","NL10_SS14_mapp","Boe_92_CDC2_map","LMNP-1_real", "NL16_SS14_mapp","AU17_SS14_mapp","NE15_SS14_mapp","SW4_SS14_mapp","SW6_SS14_mapp","NE19_SS14_mapp", "AU15_SS14_mapp","CHS119_CDC2_map","K403_real","CW65__Nichols_mapp","CW84_SS14_mapp","Sea_81-4_real", "BAL3_Nichols_mapp","SJ219_SS14_mapp","Iraq B_real","UW116B_SS14_mapp","P3_SS14_mapp","UW337B_SS14_mapp", "CDC_2575_real","NIC2_Nichols_mapp","R3-SAL-007_CDC2_map","CW83_Nichols_mapp","NL14_Nichols_mapp", "PT_SIF1020_SS14_mapp"] dicc_genetic_code = codigo_genetico() lista_archivos = ls() dicc_final_stops ={} dicc_final_truncados ={} for i in lista_archivos: if i.endswith(".fas"): nom_gen= str(i) nom_gen_cons = nom_gen[:len(nom_gen) - 4] pauta_gen = dicc_pauta_genes_Nichols[nom_gen] secuencias = abrir_fichero(nom_gen) dicc_seq = crear_diccionario(secuencias) dicc_final_truncados, dicc_final_stops =procesar_genes_traduccion(dicc_pauta_genes_Nichols,dicc_genetic_code,lista_genomas, dicc_seq, dicc_final_stops,pauta_gen, dicc_final_truncados, nom_gen_cons) archivo_final(dicc_final_truncados, dicc_final_stops) if __name__ == '__main__': main()