Nucleic acid sequence analysis experiment
Analysis against nucleic acid sequences is the process of searching for genes in nucleic acid sequences, identifying the location of genes and the location of functional sites, and labeling known sequence patterns. Source: Guangdong Pharmaceutical University Laboratory Instruction Manual.
Operation method
Nucleic acid sequence analysis
Principle
Analysis of nucleic acid sequences is the process of searching for genes in nucleic acid sequences, identifying the location of genes and the location of functional sites, and labeling known sequence patterns. In this process, the identification of a DNA sequence as a gene requires multiple lines of evidence. In general, gene coding and regulatory regions are unlikely to be found in regions where repetitive fragments occur frequently; a DNA fragment is very likely to be an exonic fragment if its hypothetical product has high sequence similarity to a known protein or the product of another gene; and there is a statistical regularity in the occurrence of the so-called Statistical regularity in a DNA sequence, so-called "codon preference", is also strong evidence that this DNA is a protein coding region; other evidence includes matching the pattern of "template" sequences, matching the pattern of simple sequences such as TATA Box, etc. In general, the determination of the location of a gene and the identification of a protein coding region is a very important task. In general, determining the location and structure of genes requires a combination of several methods and follows certain rules: for eukaryotic sequences, repeat sequence analysis should be performed before prediction to tag and remove the repeats; when choosing a prediction program, attention should be paid to the species-specificity of the program; it is necessary to find out whether the program applies to genome or cDNA sequences; many programs have requirements on the length of sequences, and some programs are only applicable to sequence lengths; some programs only apply to the genome or cDNA sequences; many programs have requirements on the length of sequences. Some programs are only applicable to long sequences, but not to residual sequences such as EST.
Materials and Instruments
Computer Move I. Experimental content Common Problems 1. Repeat sequence analysis For eukaryotic nucleic acid sequences, a simple large number of repetitive sequences should be flagged and removed prior to gene identification, because in many cases repetitive sequences can be very disruptive to prediction programs, especially those involving database searches. For more product details, please visit Aladdin Scientific website.
BioEdit Software
1. Use Entrez or SRS to search for the mRNA, genomic DNA, exon and 5'-regulatory region (promoter) of human leptin, and then link and extract the content of the sequence, and read the explanation of the sequence format to understand its meaning;
2. Use BioEdit software to perform basic analyses of the above nucleic acid sequences, such as molecular mass, base composition, base distribution, sequence transformation, and restriction enzyme digestion analysis, and learn about other functions of BioEdit from the "help" section of the software;
3. Use BioEdit software to analyze the human leptin mRNA sequence in a readable frame;
4. use the NCBI query system to analyze the genome sequence and gene expression profiling of leptin;
5. use Blast2 to compare the mRNA sequence of leptin with its exon or genome sequence.
Experimental Methods
1. Call the Internet browser and enter the Entrez URL in its address bar: http: //www.ncbi.nlm.nih.gov/Entrez;
2. Select nucleotide in the selection bar after Search;
3. enter homo sapiens leptin in the input field;
4. Click go to display the sequence acceptance number and sequence name, etc;
5. Find the human leptin (obesity homolog, mouse) mRNA sequence (hint: NM_000230), click on the sequence acceptor number to display the sequence details;
6. Save the sequence in FASTA format;
7. find the sequence acceptor number and sequence identification number of human leptin genomic DNA (Contig) based on the gene location information from NM_000230, click on the sequence acceptor number to display the sequence details;
8. enter homo sapiens leptin exon in the input field to find the exon sequence of human leptin;
9. enter homo sapiens leptin promoter in the input field to find the human leptin 5' regulatory region sequence;
10. retrieve the nucleic acid sequences of mRNA, genomic DNA, exon and 5' promoter of human leptin by SRS information query system according to the above steps;
11. input the above nucleic acid sequences into BioEdit and DNAClub software for basic sequence analysis;
12. Open the BioEdit software, click on the "help" column and read the "contents";
13. Input the mRNA sequence of human leptin into BioEdit software for readable frame analysis: Open BioEdit software → input the sequence of human leptin mRNA in FASTA format into the analysis box → click on the sequence description in the sequence description box on the left side → click on the sequence column → select nucleic acid → click on "find next ORF" → view the start of the ORF → click on the "help" column, read "contents". find next ORF→view the start codon position and coding region range (58→561);
14. Use the NCBI query system to analyze the genome sequence of human leptin and the electronic expression profiling of the gene with reference to the textbook;
15. Comparison of human leptin mRNA sequence with its exon or genome sequence: call the Internet browser and enter the Blast2 URL (http://www.ncbi.nlm.nih.gov/Entrezgorf/bl2/html) in its address bar → compare the human leptin mRNA and exon sequences with the human leptin mRNA and exon sequences. mRNA and exon sequences in FASTA format into sequence2 and sequence1 analysis boxes respectively, or enter the GI version numbers of human leptin mRNA and genomic sequences into the GI version number boxes of sequence2 and sequence1 → click Align to display detailed information on the comparison of the two sequences → search for the position of each exon in the sequence of mRNA and genomic sequences, and find the position of each exon in the sequence. Find the position of each exon in the mRNA sequence.
2. Database search
Using an unknown nucleic acid sequence as a query sequence and searching the database for existing sequences that are similar to it is an effective means of sequence analysis prediction. The principles and techniques of sequence comparison and searching have been specifically introduced in theoretical classes. However, it is worth noting that the conclusions made by similarity analysis may lead to the circulation of errors; a certain percentage of sequences are difficult to find suitable homology partners in the database. For EST sequences, sequence search would be a very effective means of prediction.
3. Statistical characterization of coding regions
Statistically gained experience shows that the frequency of codon usage in DNA is not evenly distributed; certain codons are used at a higher frequency while others occur less frequently. This results in a detectable statistical specificity of sequences in the coding region, the so-called "codon preference". Statistical analysis of unknown sequences using this property can reveal rough locations of coding regions. Techniques in this category include: two-codon counting (counting the frequency of occurrence of two consecutive codons); nucleotide periodicity analysis (analyzing the pattern of periodic occurrences of the same nucleotide in positions 3,6,9,... patterns of periodic occurrences at positions); homogeneity/complexity analysis (statistical counting of long homopolymers); and open readable frame analysis.
4. promoter analysis
Promoters are important sequence signals necessary for gene expression, and identifying them is important for gene recognition. There are some programs that characterize the sequence of promoters based on experimentally obtained transcription factor binding properties and use them sequentially as the basis for promoter prediction, but the actual results are not very satisfactory, with serious omissions and false positives. Overall, promoters remain a difficult problem worthy of continued research and exploration.
5. Intron/exon splice sites
Splice sites generally have more obvious sequence features, but the problem of variable splicing should be noted. Since the annotation of variable splices in the database is very incomplete, it is difficult to assess the sensitivity and accuracy of the splice site identification program in predicting splice sites. Analyzing splice sites in conjunction with the coding characteristics of the flanks can help to provide an indication of the effectiveness of splice site identification.
6. Translation initiation sites
For eukaryotes, if the transcription start site is known and there are no introns interrupting the 5' untranslated region, the "Kozak's rule" can locate the start codon in most cases. Prokaryotes generally do not have splicing processes, but finding the correct start codon in an open reading frame is still difficult. In this case, due to the presence of multiple cis-antimanipulators, promoter localization does not play a key role as in eukaryotes. For prokaryotes, the key is the localization of the ribosome binding site, and multiple programs can provide the solution.
7. Translation termination signals
PolyA and translation termination signals are not as important as initiation signals, but can also assist in delimiting genes.
8. Other comprehensive gene prediction tools
In addition to the programs mentioned above, there are many other tools for gene prediction, most of which combine various aspects of analysis to provide an overall analysis and prediction of genes. The integrated analysis of multiple information helps to improve the reliability of prediction, but there are some limitations: the limitation of the scope of application of the species; for multiple genes or some genes, some predicted gene structures are unreliable; the accuracy of prediction is relatively low for many newly discovered genes; it is very sensitive to errors in the sequences; and it has poor effect on complex gene syntax such as variable splicing, overlapping genes and promoters.
9. tRNA gene recognition
tRNA gene identification is simpler than identification of genes coding for proteins, and the problem of predicting tRNA genes by theoretical methods has largely been solved. tRNAscan-SE is a tool that integrates several identification and analysis programs, and through a screening process that analyzes the conserved sequence patterns of promoter elements, the analysis of the secondary structure of the tRNAs, the analysis of the transcriptional control elements, and the removal of a large majority of false positives, is claimed to be able to identify 99% of true tRNA genes.