import numpy as np import matplotlib.pyplot as plt import re from Bio import SeqIO from Bio.Seq import Seq import openpyxl def palindrome_control(sequenza,GC_genoma,strand): palindr = 0 sequenza = Seq(sequenza) sequenza_r = sequenza.reverse_complement() for k in range (4,8): for i in range (150): x1 = i y1 = i + k if y1 > len(sequenza): break else: window = sequenza[x1:y1] window = str(window) gc_content = 100*(window.count("C")+window.count("G"))/len(window) sequenza_r = str(sequenza_r) sub_sequenza_r= sequenza_r par = 0 while True: if re.search(window, sub_sequenza_r): ricerca = re.search(window, sub_sequenza_r) positions = ricerca.span() x2 = positions[0] y2 = positions[1] sub_sequenza_r=sub_sequenza_r[y2:] x2 += par y2 += par par += y2 if 4 <= len(sequenza)-y2-y1+1 <= 8: palindr +=1 break else: break return palindr def palindrome_finder(sequenza,file,GC_genoma,strand,score): lista_scores = [] sequenza = Seq(sequenza) sequenza_r = sequenza.reverse_complement() pattern_pause_site1 = "GG\D{8}[C,T]G" pattern_pause_site2 = "C[G,A]\D{8}CC" for k in range (4,8): for i in range (150): x1 = i y1 = i + k if y1 > len(sequenza): break else: window = sequenza[x1:y1] window = str(window) gc_content = 100*(window.count("C")+window.count("G"))/len(window) sequenza_r = str(sequenza_r) score_p = score sub_sequenza_r= sequenza_r par = 0 while True: if re.search(window, sub_sequenza_r): ricerca = re.search(window, sub_sequenza_r) positions = ricerca.span() x2 = positions[0] y2 = positions[1] sub_sequenza_r=sub_sequenza_r[y2:] x2 += par y2 += par par += y2 if 4 <= len(sequenza)-y2-y1+1 <= 8: loop = len(sequenza)-y2 - y1 file.write("\nPalindromic sequences found at coordinates ") file.write(str(x1)) file.write("-") file.write(str(y1-1)) file.write(" e ") file.write(str(len(sequenza)-y2)) file.write("-") file.write(str(len(sequenza)-x2-1)) file.write("(Sequence: ") file.write(str(window)) file.write(")") score_p += 3 if gc_content > GC_genoma+20: score_p += 2 elif gc_content > GC_genoma+10: score_p += 1 if len(window) > 4: score_p += 1 if loop < 6: score_p += 1 if strand == 1: a = x1-5 b = len(sequenza)-x2+5 seq_pause = sequenza[a:b] seq_pause = str(seq_pause) if re.search(pattern_pause_site1,seq_pause): score_p += 3 file.write(" (PAUSE-CONSENSUS PRESENT)") if strand == -1: a = x1-5 b = len(sequenza)-x2+5 seq_pause = sequenza[a:b] seq_pause = str(seq_pause) if re.search(pattern_pause_site2,seq_pause): score_p += 3 file.write(" (PAUSE-CONSENSUS PRESENT)") file.write(" (SCORE: ") file.write(str(score_p)) file.write(")") lista_scores.append(score_p) else: break if len(lista_scores) > 0: return np.max(lista_scores) else: return 0 MC = [] print("RhoTermPredict is a genome-wide predictor of transcription Rho-dependent terminators in bacterial genomes. It analyzes both the strands.\n\n") print("Input: Genome sequences file") print("Output: a xlsx file containing Rho-dependent terminators coordinates and a txt file containing informations about them") print("Genome file must be in fasta format") File_genome = input("Enter the input genome file name: ") try: for seq_record in SeqIO.parse(File_genome, "fasta"): MC.append(str(seq_record.seq)) print ("RhoTermPredict is working, please wait...") genome = MC[0] genome = genome.upper() GC_whole_genome = 100*(genome.count("G")+genome.count("C"))/len(genome) pattern1 = "C\D{11,13}C\D{11,13}C\D{11,13}C\D{11,13}C\D{11,13}C" pattern2 = "G\D{11,13}G\D{11,13}G\D{11,13}G\D{11,13}G\D{11,13}G" pattern_pause_site1 = "GG\D{8}[C,T]G" pattern_pause_site2 = "C[G,A]\D{8}CC" predictions = 0 cg_value = [] punteggi = [] num = 1 cod = 1 nuovo_file = openpyxl.Workbook() sheet = nuovo_file.active sheet.title = "predictions" #definisce un nome per il foglio di lavoro sheet["A1"] = "Region" sheet["B1"] = "Start RUT" sheet["C1"] = "End RUT" sheet["D1"] = "Strand" p = open("Informations about predictions.txt","a") p.write("Sequences of predicted Rho-dependent terminators") #positive strand scale = 0 for j in range(len(genome)): x1 = scale + j x2 = scale + j + 78 if x2 > len(genome): break else: w = genome[x1:x2] if w.count("G") > 0: numG = w.count("G") rapporto = w.count("C")/numG else: numG = 1 rapporto = (w.count("C")+1)/numG if rapporto > 1: if re.search(pattern1,w): dati = [] for g in range(50): if x2+g <= len(genome): w = genome[x1+g:x2+g] if w.count("G") > 0: numG = w.count("G") rapporto = w.count("C")/numG else: numG = 1 rapporto = (w.count("C")+1)/numG if rapporto > 1: if re.search(pattern1,w): dati.append(rapporto) else: dati.append(0) else: dati.append(0) else: break maxP = np.argmax(dati) rapporto = np.max(dati) x1 = x1 + maxP x2 = x2 + maxP scale = x2 - j - 1 s = genome[x2:x2+150] w = genome[x1:x2] score = 3 ctrl = palindrome_control(s,GC_whole_genome,1) if ctrl > 0 or re.search(pattern_pause_site1,s): sheet["A%d"%(num+1)] = "T%d"%(cod) sheet["B%d"%(num+1)] = x1 sheet["C%d"%(num+1)] = x2 sheet["D%d"%(num+1)] = "plus" num += 1 predictions += 1 scale = x2 + 150 - j - 1 cg_value.append(rapporto) if rapporto > 2: score += 3 elif rapporto > 1.50: score += 2 elif rapporto > 1.25: score += 1 p.write("\n\n\nPREDICTED REGION NUMBER ") p.write(str(cod)) p.write(" (STRAND POSITIVE) ") p.write("\n\nGenomic sequence of putative RUT site (Coordinates: ") p.write(str(x1)) p.write("-") p.write(str(x2)) p.write(", c/g = ") p.write(str(rapporto)) p.write(" ): ") p.write(str(w)) p.write("\n\nThe 150 nt long genomic region immediately downstream is ") p.write(str(s)) p.write("\n") cod += 1 final_score = 0 final_score = palindrome_finder(s,p,GC_whole_genome,1,score) par = 0 while True: if re.search(pattern_pause_site1,s): ricerca = re.search(pattern_pause_site1,s) positions = ricerca.span() x2 = positions[0] y2 = positions[1] s = s[y2:] p.write("\n\nPAUSE-CONSENSUS present at the coordinates ") p.write(str(x2)) p.write("-") p.write(str(y2)) x2 += par y2 += par else: break if final_score == 0: final_score = score + 3 punteggi.append(final_score) #negative strand scale = 0 for j in range(len(genome)): x1 = scale + j x2 = scale + j + 78 if x2 > len(genome): break else: w = genome[x1:x2] if w.count("C") > 0: numC = w.count("C") rapporto = w.count("G")/numC else: numC = 1 rapporto = (w.count("G")+1)/numC if rapporto > 1: if re.search(pattern2,w): dati = [] for g in range(50): if x2+g <= len(genome): w = genome[x1+g:x2+g] if w.count("C") > 0: numC = w.count("C") rapporto = w.count("G")/numC else: numC = 1 rapporto = (w.count("G")+1)/numC if rapporto > 1: if re.search(pattern2,w): dati.append(rapporto) else: dati.append(0) else: dati.append(0) else: break maxP = np.argmax(dati) rapporto = np.max(dati) x1 = x1 + maxP x2 = x2 + maxP scale = x2 - j - 1 s = genome[x1-150:x1] w = genome[x1:x2] score = 3 ctrl = palindrome_control(s,GC_whole_genome,-1) if ctrl > 0 or re.search(pattern_pause_site2,s): sheet["A%d"%(num+1)] = "T%d"%(cod) sheet["B%d"%(num+1)] = x1 sheet["C%d"%(num+1)] = x2 sheet["D%d"%(num+1)] = "minus" num += 1 predictions += 1 scale = x2 + 150 - j - 1 cg_value.append(rapporto) if rapporto > 2: score += 3 elif rapporto > 1.50: score += 2 elif rapporto > 1.25: score += 1 p.write("\n\n\nPREDICTED REGION NUMBER ") p.write(str(cod)) p.write(" (STRAND NEGATIVE)") p.write("\n\nGenomic sequence of putative RUT site (Coordinates: ") p.write(str(x1)) p.write("-") p.write(str(x2)) p.write(", c/g = ") p.write(str(rapporto)) p.write(" ): ") p.write(str(w)) p.write("\n\nThe 150 nt long genomic region immediately downstream is ") p.write(str(s)) p.write("\n") cod += 1 final_score = 0 final_score = palindrome_finder(s,p,GC_whole_genome,-1,score) par = 0 while True: if re.search(pattern_pause_site2,s): ricerca = re.search(pattern_pause_site2,s) positions = ricerca.span() x2 = positions[0] y2 = positions[1] s = s[y2:] p.write("\n\nPAUSE-CONSENSUS present at the coordinates ") p.write(str(x2)) p.write("-") p.write(str(y2)) x2 += par y2 += par else: break if final_score == 0: final_score = score + 3 punteggi.append(final_score) p.write("\n\n\n\n\n\nTotal number of predicted Rho-dependent terminators: ") p.write(str(predictions)) p.write("\n\n\nMean C/G content of predicted terminators: ") p.write(str(np.mean(cg_value))) p.write("\nStandard deviation: ") p.write(str(np.std(cg_value))) p.close() nuovo_file.save('Rho-dependent terminators coordinates.xlsx') print("Work finished, see output files in the current directory") except IOError: print ("File %s inexistent in the current directory!" %(File_genome))