- Open Access
CisOrtho: A program pipeline for genome-wide identification of transcription factor target genes using phylogenetic footprinting
© Bigelow et al; licensee BioMed Central Ltd. 2004
- Received: 21 January 2004
- Accepted: 12 March 2004
- Published: 12 March 2004
All known genomes code for a large number of transcription factors. It is important to develop methods that will reveal how these transcription factors act on a genome wide level, that is, through what target genes they exert their function.
We describe here a program pipeline aimed at identifying transcription factor target genes in whole genomes. Starting from a consensus binding site, represented as a weight matrix, potential sites in a pre-filtered genome are identified and then further filtered by assessing conservation of the putative site in the genome of a related species, a process called phylogenetic footprinting. CisOrtho has been successfully used to identify targets for two homeodomain transcription factors in the genomes of the nematodes Caenorhabditis elegans and Caenorhabditis briggsae.
CisOrtho will identify targets of other nematode transcription factors whose DNA binding specificity is known and can be easily adapted to search other genomes for transcription factor targets.
- Transcription Factor Binding Site
- Position Weight Matrix
- Homeodomain Transcription Factor
- Phylogenetic Footprinting
- Transcription Factor Target
Transcription factors are among the most common regulatory proteins in a cell. They subserve a variety of functions during development and homeostasis, yet in most cases the full spectrum of target genes regulated by a given transcription factor is unknown. The identification of transcription factor target genes is a challenging task since most transcription factors have the inherent capacity to tolerate a significant amount of variation in their cis- regulatory binding sites . These variations, which are usually experimentally determined, are commonly represented by a weight matrix with which genomes can be searched [2–4]. However, the usually sparse and widely varying data on transcription factor binding sites together with the large search space of a genome leads to many false hits, thus necessitating further filtering. This can be done by imposing the criteria of conservation of the cis-regulatory sequence in a related species that has diverged long enough ago to cause only functionally relevant DNA sequences to be conserved ("phylogenetic footprinting") [1, 5–13]. We describe here a program pipeline that will identify targets of a transcription factor with a defined cis-regulatory target specificity, using two invertebrate model system genomes, those of C. elegans and C. briggsae [14, 15].
CisOrtho is written in ANSI C++ with the use of the SGI Standard Template Library http://www.sgi.com/tech/stl/ and a supporting freely available options-parsing interface Opt-3.19 (http://nis-www.lanl.gov/~jt/Software/ or from http://dev.wormbase.org/CisOrtho). It consists of 1541 lines of code in 11 source files. The program has two parameters which affect either size (memory) or runtime: Ngenes, number of ortholog-matched gene pairs to consider; D, number of total hits per gene to be reported. Memory is approximately Ngenes* D* 200 bytes; runtime is approximately linear in Ngenes, D and the length of DNA to be searched. For exhaustive settings (Ngenes = 12000, D = 10), total memory is 23.2 MB and runtime 17 minutes on a 2.8 GHz Xeon processor. A more typical run (Ngenes = 500, D = 3) takes 3.9 MB and 42 seconds. Since memory requirement does not depend on the length of DNA to be searched, a search on the Human and Mouse genome would be feasible on a machine with 256 MB.
Identification of non-exonic regions
Scanning window scoring procedure
Starting with the input of experimentally defined binding sites of a dimeric homeodomain transcription factor complex composed of the TTX-3 and CEH-10 proteins (ASW and OH, submitted), we first use the hidden Markov model software package HMMER  with the command 'hmmbuild --null <background-frequency-file> --prior <prior-frequency-file> <output-position-weight-matrix> <input-binding-site-alignment>.' The position weight matrix is an n × 4 matrix where n is the length of the transcription factor binding site alignment input used (in our case, either 14 or 16 nucleotides). The matrix is defined as:
where the effective frequency is determined as the normalized, prior-adjusted, weighted sum of counts of each nucleotide in the alignment columns, in which the sequence weights are determined using a tree-based scheme. We use the resulting position weight matrix as input to CisOrtho. Then, CisOrtho finds approximately the N (option -t) highest scoring hits, with the restriction that no single gene has more than D (option -d) hits. The score for a given sequence window is simply the sum of the n cells of the position weight matrix corresponding to the position and nucleotide of the sequence window. For example, the sequence AACTCG would be given the score m1A+ m2A+ m3C+ m4T+ m5C+ m6Gfor a 4 × 6 position weight matrix |m ij |. This scoring scheme is simply the log-odds scoring used by the original HMMER software, adapted as a scanning window algorithm via CisOrtho. We note that known target genes of TTX-3 do not contain clustered binding sites (ASW and OH, submitted) which allowed us to eschew clustering of binding sites as a search criteria. It is possible that previously described searches for transcription factor targets which used the clustering criteria [2, 3] may result in too many false-negative results.
The effect of options -t and -d warrants further comment. To find approximately N (option -t) highest-scoring hits in a large amount of DNA, CisOrtho must first estimate the raw minimum score cutoff which yields this many hits. Technically, this is achieved by scoring every 100th sequence window, finding the top N/100 hits, and using the lowest score of those as the cutoff in the full search. Since the criterion for acceptance is a raw score cutoff, the actual number of hits retrieved in the whole sequence cannot be controlled precisely, but depends on the statistics of the sequence and position weight matrix. Furthermore, since no gene is allowed more than D associated hits (option -d), the total number retrieved will be lower if there is a lot of clustering and thus many genes have more than D actual hits. If the user wants to perform an exhaustive search, the special value of zero for -t indicates using no score cutoff, thus accepting all windows as hits. Likewise, the -d option can be set to an arbitrarily high value (in the downloaded software). These settings may be of interest in preliminary runs to determine the clustering behavior of the hits. More restrictive settings should then be used based on the results of the preliminary run.
Orthology-based filtering and HTML tables
Validation of the procedure
TTX-3 is a LIM homeodomain transcription factor that we have previously shown to be required for interneuron differentiation in C. elegans . More recently, we found that TTX-3 binds together with the Paired-type homeodomain transcription factor CEH-10 to a 16 base pair target site, conserved in seven direct TTX-3/CEH-10 target genes (ASW and OH, submitted). We have used CisOrtho to identify new target genes of the TTX-3/CEH-10 homeodomain proteins on a genome-wide level, using as an input the experimentally determined, 16 bp TTX-3/CEH-10 consensus binding site (ASW and OH, submitted). We sorted the list of hit-pairs that CisOrtho provided by average score between the two species. We have experimentally verified hits from this list using either or both of two criteria: When fused to a heterologous reporter gene, the putative target should be expressed in the same neuron type as the ttx-3 gene and the reporter gene should not be expressed in that neuron in ttx-3 null mutant animals . We have generated 15 new reporter gene fusions for the top 26 hits. 14 of these reporter gene fusions satisfy the experimental criteria to represent targets of TTX-3/CEH-10 (ASW and OH, submitted). We have also generated reporter fusions to lower scoring hit-pairs. For example, 11 out of 17 tested predicted sites that ranked between 42 and 112 in the hit-score list were experimentally confirmed to be TTX-3 targets (ASW and OH, submitted).
We have also made use of the C. elegans/C. briggsae mismatch feature of CisOrtho and generated reporter fusions to predicted binding sites with a low score yet almost perfect conservation between C. elegans and C. briggsae. 13/22 tested sites from this "low-mismatch" list fulfilled the experimental criteria to be TTX-3/CEH-10 targets (ASW and OH, submitted). We also note many cases in which conserved binding sites are located in introns (first intron or later introns); in most cases examined by reporter gene fusions, these sites were functional. Finally, we note that the representation of the starting matrix did not significantly change upon inclusion of new, experimentally verified TTX-3/CEH-10 target sites. Taken together, CisOrtho has been successfully used to identify new target genes for a transcription factor.
CisOrtho is complementary to but also extends previous approaches to identify transcription factor targets. Previously described phylogenetic footprinting approaches undertook an unbiased search for phylogenetically conserved sequence patches in non-coding regions, assumed to be transcription factor binding sites [6–8], [11–13]. Providing a complement to these approaches, CisOrtho undertakes a more targeted search, finding phylogenetically conserved regulatory targets of defined transcription factors whose DNA binding site specificity is known. CisOrtho extends previously described approaches to identify target genes for specific transcription factors which did not utilize the phylogenetic footprinting aspect for filtering [2, 3], or – in cases where phylogenetic footprinting was used – were not conducted in an unbiased, genome wide manner [10, 18]. CisOrtho rather takes advantage of GFF files to allow appropriate annotation and subsequent searching of all genomic non-coding sequence space and produces a user-friendly output from the search. While we have limited our approach to the genomes of C. elegans and C. briggsae, CisOrtho can as easily be applied to other genomes that are annotated in the commonly used GFF format.
CisOrtho is available through a web interface at http://www.wormbase.org/cisortho (Fig. 2). For users who want to run the program locally, or with a wider range of parameters or different inputs, CisOrtho is freely available as precompiled executables for Windows (win32) and Mac OS X, and as a source code distribution for Unix/Linux with traditional 'configure' script and Makefiles. Also provided in the distribution is the Perl script snip.plx, which initially isolates the non-exonic genomic sequence to be searched by CisOrtho, according to GFF (General Feature Format) genome annotation files. Users experienced in Perl may modify this script to output genomic sequence based on different criteria. For example, if a user wanted to search only 3' regions of genes, this could be implemented by editing snip.plx.
We thank Jack Chen for assistance in installing the website, and Lincoln Stein for generously providing web hosting on WormBase. This work was funded by the NIH.
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