Fast analysis of DNA and protein sequence on Apple IIe: restriction sites search, alignment of short sequence and dot matrix analysis.

A fast restriction sites search algorithm using a quadruplet look-ahead feature has been written in 6502 assembly language code. The search time, tested on the sequence of pBR322, is 4.1 s/kilobase using a restriction site library including 112 specificities corresponding to a total site length of over 700 bases. The search for a short sequence (less than 36 bases) within a longer one (up to 9999 bases) with a given number of mismatches or gaps allowed has also been written in assembly language. Typical run time for the search of a 12 base sequence with 1, 2 or 3 gaps allowed are 6.2, 9.4 or 13.6 s/kilobase, respectively. The dot matrix analysis needs 7.5 minutes per square kilobase when using a stringency of 15 matched bases out of 25. A 7/21 matrix of two 500 amino acid proteins is obtained in 3 minutes. These three routines are included in DPSA, a general package of programs allowing manipulation and analysis of DNA and protein sequences.     

Designing patterns for profile HMM search

MOTIVATION: Profile HMMs are a powerful tool for modeling conserved motifs in proteins. These models are widely used by search tools to classify new protein sequences into families based on domain architecture. However, the proliferation of known motifs and new proteomic sequence data poses a computational challenge for search, requiring days of CPU time to annotate an organism's proteome. RESULTS: We use PROSITE-like patterns as a filter to speed up the comparison between protein sequence and profile HMM. A set of patterns is designed starting from the HMM, and only sequences matching one of these patterns are compared to the HMM by full dynamic programming. We give an algorithm to design patterns with maximal sensitivity subject to a bound on the false positive rate. Experiments show that our patterns typically retain at least 90% of the sensitivity of the source HMM while accelerating search by an order of magnitude. AVAILABILITY: Contact the first author at the address below.     

Structural analysis of Arabidopsis thaliana chromosome 5. VIII. Sequence features of the regions of 1,081,958 bp covered by seventeen physically assigned P1 and TAC clones.

A total of 17 Pl and TAC clones each representing an assigned region of chromosome 5 were isolated from P1 and TAC genomic libraries of Arabidopsis thaliana Columbia, and their nucleotide sequences were determined. The length of the clones sequenced in this study summed up to 1,081,958 bp. As we have previously reported the sequence of 9,072,622 bp by analysis of 125 P1 and TAC clones, the total length of the sequences of chromosome 5 determined so far is now 10,154,580 bp. The sequences were subjected to similarity search against protein and EST databases and analysis with computer programs for gene modeling. As a consequence, a total of 253 potential protein-coding genes with known or predicted functions were identified. The positions of exons which do not show apparent similarity to known genes were also assigned using computer programs for exon prediction. The average density of the genes identified in this study was 1 gene per 4277 bp. Introns were observed in 74% of the potential protein genes, and the average number per gene and the average length of the introns were 4.3 and 168 bp, respectively. The sequence data and gene information are available on the World Wide Web database KAOS (Kazusa Arabidopsis data Opening Site) at http://www.kazusa.or.jp/arabi/.     

Informatics for protein identification by mass spectrometry

High throughput protein analysis (i.e., proteomics) first became possible when sensitive peptide mass mapping techniques were developed, thereby allowing for the possibility of identifying and cataloging most 2D gel electrophoresis spots. Shortly thereafter a few groups pioneered the idea of identifying proteins by using peptide tandem mass spectra to search protein sequence databases. Hence, it became possible to identify proteins from very complex mixtures. One drawback to these latter techniques is that it is not entirely straightforward to make matches using tandem mass spectra of peptides that are modified or have sequences that differ slightly from what is present in the sequence database that is being searched. This has been part of the motivation behind automated de novo sequencing programs that attempt to derive a peptide sequence regardless of its presence in a sequence database. The sequence candidates thus generated are then subjected to homology-based database search programs (e.g., BLAST or FASTA). These homology search programs, however, were not developed with mass spectrometry in mind, and it became necessary to make minor modifications such that mass spectrometric ambiguities can be taken into account when comparing query and database sequences. Finally, this review will discuss the important issue of validating protein identifications. All of the search programs will produce a top ranked answer; however, only the credulous are willing to accept them carte blanche.     

Using PC/GENE for protein and nucleic acid analysis

This paper describes a series of protein analyses using the molecular biology software package PC/GENE, which runs on an IBM or compatible microcomputer. A nucleic acid sequence was first edited and then translated into an amino acid sequence. The amino acid composition, isoelectric point, molecular weight, and other properties of the sequence were determined. Programs to predict secondary structure, alpha helix membrane associations, hydrophobic and hydrophilic regions, and surface and antigenic sites from the amino acid sequence were also used. A search was made in a data base for sequences containing a region similar to a region in the protein sequence. Sequence alignments and queries of data bases can also be performed.     

GenBank.

The GenBank (Registered Trademark symbol) sequence database incorporates DNA sequences from all available public sources, primarily through the direct submission of sequence data from individual laboratories and from large-scale sequencing projects. Most submitters use the BankIt (Web) or Sequin programs to format and send sequence data. Data exchange with the EMBL Data Library and the DNA Data Bank of Japan helps ensure comprehensive worldwide coverage. GenBank data is accessible through NCBI's integrated retrieval system, Entrez, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome and protein structure information. MEDLINE (Registered Trademark symbol) s from published articles describing the sequences are included as an additional source of biological annotation through the PubMed search system. Sequence similarity searching is offered through the BLAST series of database search programs. In addition to FTP, Email, and server/client versions of Entrez and BLAST, NCBI offers a wide range of World Wide Web retrieval and analysis services based on GenBank data. The GenBank database and related resources are freely accessible via the URL: http://www.ncbi.nlm.nih.gov     

Sequence clustering strategies improve remote homology recognitions while reducing search times

Sequence databases are rapidly growing, thereby increasing the coverage of protein sequence space, but this coverage is uneven because most sequencing efforts have concentrated on a small number of organisms. The resulting granularity of sequence space creates many problems for profile-based sequence comparison programs. In this paper, we suggest several strategies that address these problems, and at the same time speed up the searches for homologous proteins and improve the ability of profile methods to recognize distant homologies. One of our strategies combines database clustering, which removes highly redundant sequence, and a two-step PSI-BLAST (PDB-BLAST), which separates sequence spaces of profile composition and space of homology searching. The combination of these strategies improves distant homology recognitions by more than 100%, while using only 10% of the CPU time of the standard PSI-BLAST search. Another method, intermediate profile searches, allows for the exploration of additional search directions that are normally dominated by large protein sub-families within very diverse families. All methods are evaluated with a large fold-recognition benchmark.     

SW#db: GPU-Accelerated Exact Sequence Similarity Database Search

In recent years we have witnessed a growth in sequencing yield, the number of samples sequenced, and as a result–the growth of publicly maintained sequence databases. The increase of data present all around has put high requirements on protein similarity search algorithms with two ever-opposite goals: how to keep the running times acceptable while maintaining a high-enough level of sensitivity. The most time consuming step of similarity search are the local alignments between query and database sequences. This step is usually performed using exact local alignment algorithms such as Smith-Waterman. Due to its quadratic time complexity, alignments of a query to the whole database are usually too slow. Therefore, the majority of the protein similarity search methods prior to doing the exact local alignment apply heuristics to reduce the number of possible candidate sequences in the database. However, there is still a need for the alignment of a query sequence to a reduced database. In this paper we present the SW#db tool and a library for fast exact similarity search. Although its running times, as a standalone tool, are comparable to the running times of BLAST, it is primarily intended to be used for exact local alignment phase in which the database of sequences has already been reduced. It uses both GPU and CPU parallelization and was 4–5 times faster than SSEARCH, 6–25 times faster than CUDASW++ and more than 20 times faster than SSW at the time of writing, using multiple queries on Swiss-prot and Uniref90 databases     

DNABIT Compress - Genome compression algorithm

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, "DNABIT Compress" for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that "DNABIT Compress" algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases.     

GenBank.

The GenBank(R) sequence database (http://www.ncbi.nlm.nih.gov/) incorporates DNA sequences from all available public sources, primarily through the direct submission of sequence data from individual laboratories and from large-scale sequencing projects. Most submitters use the BankIt (WWW) or Sequin programs to send their sequence data. Data exchange with the EMBL Data Library and the DNA Data Bank of Japan helps ensure comprehensive worldwide coverage. GenBank data is accessible through NCBI's integrated retrieval system, Entrez , which integrates data from the major DNA and protein sequence databases along with taxonomy, genome and protein structure information. MEDLINE(R) abstracts from published articles describing the sequences are also included as an additional source of biological annotation. Sequence similarity searching is offered through the BLAST series of database search programs. In addition to FTP, e-mail and server/client versions of Entrez and BLAST, NCBI offers a wide range of World Wide Web retrieval and analysis services of interest to biologists.     

Sequence comparison between the extracellular domain of M2 protein human and avian influenza A virus provides new information for bivalent influenza vaccine design

To prevent the human and economic losses caused by human and avian influenza viruses, it is necessary to prepare safe bivalent influenza vaccines. Recent studies found that human influenza vaccines based on the extracellular domain of influenza M2 protein (M2e) induced broad-spectrum protective immunity in various antigen constructs. A prerequisite for using the M2e protein as a bivalent influenza vaccine component was to find out the sequence differences between human and non-human (avian or swine) influenza M2e proteins. Here, we completed such a comparison using 716 influenza M2e sequences available in Genbank. The results found one region on M2e protein consistent with host restriction specificities: PIRNEWGCRCN, PTRNGWECKCS and PIRNGWECRCN (aa10-20; the human, avian and swine specific M2e sequence, respectively). Interestingly, the comparison result was then validated by immunoblotting and enzyme-linked immunosorbent assay. The monoclonal antibody against the EVETPIRN sequence (aa6-13) of human M2e protein could weakly recognize avian M2e proteins bearing the EVETPTRN sequence (aa6-13) but failed to recognize avian M2e proteins bearing the EVETLTRN sequence (aa6-13). The data in this study provided useful information in the race to develop bivalent influenza vaccines against avian and human influenza A virus infection in human beings.     

MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform

A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.     

UniProt archive

UniProt Archive (UniParc) is the most comprehensive, non-redundant protein sequence database available. Its protein sequences are retrieved from predominant, publicly accessible resources. All new and updated protein sequences are collected and loaded daily into UniParc for full coverage. To avoid redundancy, each unique sequence is stored only once with a stable protein identifier, which can be used later in UniParc to identify the same protein in all source databases. When proteins are loaded into the database, database cross-references are created to link them to the origins of the sequences. As a result, performing a sequence search against UniParc is equivalent to performing the same search against all databases cross-referenced by UniParc. UniParc contains only protein sequences and database cross-references; all other information must be retrieved from the source databases.     

Microcomputer programs for DNA sequence analysis.

Computer programs are described which allow (a) analysis of DNA sequences to be performed on a laboratory microcomputer or (b) transfer of DNA sequences between a laboratory microcomputer and another computer system, such as a DNA library. The sequence analysis programs are interactive, do not require prior experience with computers and in many other respects resemble programs which have been written for larger computer systems (1-7). The user enters sequence data into a text file, accesses this file with the programs, and is then able to (a) search for restriction enzyme sites or other specified sequences, (b) translate in one or more reading frames in one or both directions in order to find open reading frames, or (c) determine codon usage in the sequence in one or more given reading frames. The results are given in table format and a restriction map is generated. The modem program permits collection of large amounts of data from a sequence library into a permanent file on the microcomputer disc system, or transfer of laboratory data in the reverse direction to a remote computer system.     

A new method to find a set of energetically optimal RNA secondary structures.

We present a computer method to determine nucleic acid secondary structures. It is based on three steps: 1) the search for all possible helical regions relied on a mathematical approach derived from the convolution theorem; it uses a tetradimensional complex vector representation of the bases along the sequence; 2) a 'tree' search for a set of minimum free energy structures, by the aid of an approximate energy evaluation to reduce the computer time requirements; 3) the exact calculation and refinement of the energies. A method to introduce the experimental data and reach an arrangement between them and the free energy minimization criterion is shown. In order to demonstrate the confidence of the program a test on four RNA sequences is performed. The method has computer time requirement proportional to N2, where N is the length of the sequence and retrieves a set of optimal free energy structures.     

A memory-efficient algorithm for multiple sequence alignment with constraints

MOTIVATION: Recently, the concept of the constrained sequence alignment was proposed to incorporate the knowledge of biologists about structures/functionalities/consensuses of their datasets into sequence alignment such that the user-specified residues/nucleotides are aligned together in the computed alignment. The currently developed programs use the so-called progressive approach to efficiently obtain a constrained alignment of several sequences. However, the kernels of these programs, the dynamic programming algorithms for computing an optimal constrained alignment between two sequences, run in (gamman2) memory, where gamma is the number of the constraints and n is the maximum of the lengths of sequences. As a result, such a high memory requirement limits the overall programs to align short sequences only. RESULTS: We adopt the divide-and-conquer approach to design a memory-efficient algorithm for computing an optimal constrained alignment between two sequences, which greatly reduces the memory requirement of the dynamic programming approaches at the expense of a small constant factor in CPU time. This new algorithm consumes only O(alphan) space, where alpha is the sum of the lengths of constraints and usually alpha < n in practical applications. Based on this algorithm, we have developed a memory-efficient tool for multiple sequence alignment with constraints. AVAILABILITY: http://genome.life.nctu.edu.tw/MUSICME.     

Comparison of protein expression lists from mass spectrometry of human blood fluids using exact peptide sequences versus BLAST

The proteins in blood were all first expressed as mRNAs from genes within cells. There are databases of human proteins that are known to be expressed as mRNA in human cells and tissues. Proteins identified from human blood by the correlation of mass spectra that fail to match human mRNA expression products may not be correct. We compared the proteins identified in human blood by mass spectrometry by 10 different groups by correlation to human and nonhuman nucleic acid sequences. We determined whether the peptides or proteins identified by the different groups mapped to the human known proteins of the Reference Sequence (RefSeq) database. We used Structured Query Language data base searches of the peptide sequences correlated to tandem mass spectrometry spectra and basic local alignment search tool analysis of the identified full length proteins to control for correlation to the wrong peptide sequence or the existence of the same or very similar peptide sequence shared by more than one protein. Mass spectra were correlated against large protein data bases that contain many sequences that may not be expressed in human beings yet the search returned a very high percentage of peptides or proteins that are known to be found in humans. Only about 5% of proteins mapped to hypothetical sequences, which is in agreement with the reported false-positive rate of searching algorithms conditions. The results were highly enriched in secreted and soluble proteins and diminished in insoluble or membrane proteins. Most of the proteins identified were relatively short and showed a similar size distribution compared to the RefSeq database. At least three groups agree on a nonredundant set of 1671 types of proteins and a nonredundant set of 3151 proteins were identified by at least three peptides.     

DsaV methyltransferase and its isoschizomers contain a conserved segment that is similar to the segment in Hhai methyltransferase that is in contact with DNA bases.

The methyltransferase (MTase) in the DsaV restriction--modification system methylates within 5'-CCNGG sequences. We have cloned the gene for this MTase and determined its sequence. The predicted sequence of the MTase protein contains sequence motifs conserved among all cytosine-5 MTases and is most similar to other MTases that methylate CCNGG sequences, namely M.ScrFI and M.SsoII. All three MTases methylate the internal cytosine within their recognition sequence. The 'variable' region within the three enzymes that methylate CCNGG can be aligned with the sequences of two enzymes that methylate CCWGG sequences. Remarkably, two segments within this region contain significant similarity with the region of M.HhaI that is known to contact DNA bases. These alignments suggest that many cytosine-5 MTases are likely to interact with DNA using a similar structural framework.