The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSIBLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.

/pdf/gapped-blast-and-psi-blast-a-new-generation-of-protein-2ybl67x5yx.pdf

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved for the alignment of divergent protein sequences. Firstly, individual weights are assigned to each sequence in a partial alignment in order to down-weight near-duplicate sequences and up-weight the most divergent ones. Secondly, amino acid substitution matrices are varied at different alignment stages according to the divergence of the sequences to be aligned. Thirdly, residue-specific gap penalties and locally reduced gap penalties in hydrophilic regions encourage new gaps in potential loop regions rather than regular secondary structure. Fourthly, positions in early alignments where gaps have been opened receive locally reduced gap penalties to encourage the opening up of new gaps at these positions. These modifications are incorporated into a new program, CLUSTAL W which is freely available.

/pdf/clustal-w-improving-the-sensitivity-of-progressive-multiple-2na2s9sq2h.pdf

Clustal w: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice

CLUSTAL X is a new windows interface for the widely-used progressive multiple sequence alignment program CLUSTAL W. The new system is easy to use, providing an integrated system for performing multiple sequence and profile alignments and analysing the results. CLUSTAL X displays the sequence alignment in a window on the screen. A versatile sequence colouring scheme allows the user to highlight conserved features in the alignment. Pull-down menus provide all the options required for traditional multiple sequence and profile alignment. New features include: the ability to cut-and-paste sequences to change the order of the alignment, selection of a subset of the sequences to be realigned, and selection of a sub-range of the alignment to be realigned and inserted back into the original alignment. Alignment quality analysis can be performed and low-scoring segments or exceptional residues can be highlighted. Quality analysis and realignment of selected residue ranges provide the user with a powerful tool to improve and refine difficult alignments and to trap errors in input sequences. CLUSTAL X has been compiled on SUN Solaris, IRIX5.3 on Silicon Graphics, Digital UNIX on DECstations, Microsoft Windows (32 bit) for PCs, Linux ELF for x86 PCs, and Macintosh PowerMac.

/pdf/the-clustal-x-windows-interface-flexible-strategies-for-3qez0eyvqt.pdf

The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools.

We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.

https://www.science-open.com/document_file/00d79e6c-98e4-425c-9fd1-3a85d5fdefbc/PubMedCentral/00d79e6c-98e4-425c-9fd1-3a85d5fdefbc.pdf

MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Cells keep their DNA tidy by wrapping it into structures called nucleosomes. Each of these structures contains a short section of DNA wound around a cluster of proteins called histones. Not only do nucleosomes keep the genetic code organized, they also control whether the proteins that can switch genes on or off have access to the DNA. When genes turn on, the nucleosomes unwrap, exposing sections of genetic code called 'gene regulatory elements'. These elements attract the proteins that help read and copy nearby genes so the cell can make new proteins. Determining which regulatory elements are exposed at any given time can provide useful information about what is happening inside a cell, but the procedure can be expensive. The most popular way to map which regulatory elements are exposed is using a technique called Assay for Transposase-Accessible Chromatin using sequencing, or ATAC-seq for short. The 'transposase' in the acronym is an enzyme that cuts areas of DNA that are not wound around histones and prepares them for detection by DNA sequencing. Unfortunately, the data from ATAC-seq are often noisy (there are random factors that produce a signal that is detected but is not a ‘real’ result), so more sequencing is required to differentiate between real signal and noise, increasing the expense of ATAC-seq experiments. Furthermore, although ATAC-seq can identify unspooled sections of DNA, it cannot provide a direct connection between active genes and unwrapped DNA. To find the link between unspooled DNA and active genes, Henikoff et al. adapted a technique called CUT&Tag. Like ATAC-seq, it also uses transposases to cut the genome, but it allows more control over where the cuts occur. When genes are switched on, the proteins reading them leave chemical marks on the histones they pass. CUT&Tag attaches a transposase to a molecule that recognizes and binds to those marks. This allowed Henikoff et al. to guide the transposases to unspooled regions of DNA bordering active genes. The maps of gene regulatory elements produced using this method were the same as the best ATAC-seq maps. And, because the transposases could only access gaps near active genes, the data provided evidence that genes switching on leads to regulatory elements in the genome unwrapping. This new technique is simple enough that Henikoff et al. were able to perform it from home on the countertop of a laundry room. By tethering the transposases to histone marks it was possible to detect unspooled DNA that was active more efficiently than with ATAC-seq. This lowers laboratory costs by reducing the cost of DNA sequencing, and may also improve the detection of gaps between nucleosomes in single cells.

Efficient chromatin accessibility mapping in situ by nucleosome-tethered tagmentation

The Blocks Database World Wide Web (http://www.blocks.fhcrc.org ) and Email (blocks@blocks.fhcrc.org) servers provide tools for the detection and analysis of protein homology based on alignment blocks representing conserved regions of proteins. During the past year, searching has been augmented by supplementation of the Blocks Database with blocks from the Prints Database, for a total of 4754 blocks from 1163 families. Blocks from both the Blocks and Prints Databases and blocks that are constructed from sequences submitted to Block Maker can be used for blocks-versus-blocks searching of these databases with LAMA, and for viewing logos and bootstrap trees. Sensitive searches of up-to-date protein sequence databanks are carried out via direct links to the MAST server using position-specific scoring matrices and to the BLAST and PSI-BLAST servers using consensus-embedded sequence queries. Utilizing the trypsin family to evaluate performance, we illustrate the superiority of blocks-based tools over expert pairwise searching or Hidden Markov Models.

https://genome.weizmann.ac.il/~pietro/papers/BLOCKS_SUPERIOR_PERFORMANCE.pdf

Superior performance in protein homology detection with the Blocks Database servers

The Blocks Database contains multiple alignments of conserved regions in protein families which can be searched by e-mail (blocks@blocks.fhcrc.org) and World Wide Web (http://blocks.fhcrc.org/ ) servers to classify protein and nucleotide sequences. Recent enhancements to the servers include: (i) improved calculation of position-specific scoring matrices from blocks; (ii) availability of the Prints protein fingerprint database for searching in Blocks format; (iii) a representative sequence biased towards the Blocks of a protein family; (iv) a tree constructed from the Blocks of a protein family; (v) links to related World Wide Web pages for a family; and (vi) the new Local Alignment of Multiple Alignments (LAMA) method to search a block against a database of blocks.

/pdf/recent-enhancements-to-the-blocks-database-servers-3q0slusinn.pdf

Recent enhancements to the Blocks Database servers

The “point” centromere of budding yeast is genetically defined by an ∼125-bp sequence. Recent fluorescence measurements of kinetochore clusters have suggested that this sequence specifies multiple centromere histone 3 (CenH3) nucleosomes. However, high-resolution mapping demonstrates that there is only one CenH3 nucleosome per centromere, providing biochemical confirmation of the point centromere model.

https://www.genetics.org/content/genetics/190/4/1575.full.pdf

“Point” Centromeres of Saccharomyces Harbor Single Centromere-Specific Nucleosomes

Targeting induced local lesions in genomes (TILLING) is a general strategy for identifying induced point mutations that can be applied to almost any organism. In this chapter, we describe the basic methodology for high-throughput TILLING. Gene segments are amplified using fluorescently tagged primers, and products are denatured and reannealed to form heteroduplexes between the mutated sequence and its wild-type counterpart. These heteroduplexes are substrates for cleavage by the endonuclease CEL I. Following cleavage, products are analyzed on denaturing polyacrylamide gels using the LI-COR DNA analyzer system. High-throughput TILLING has been adopted by the Arabidopsis TILLING Project (ATP) to provide allelic series of point mutations for the general Arabidopsis community.

Jorja G. Henikoff

Papers

Efficient chromatin accessibility mapping in situ by nucleosome-tethered tagmentation

Superior performance in protein homology detection with the Blocks Database servers

Recent enhancements to the Blocks Database servers

“Point” Centromeres of Saccharomyces Harbor Single Centromere-Specific Nucleosomes

High-throughput TILLING for Arabidopsis.