Global predictions and tests of erythroid regulatory regions

Experimental validation of predicted mammalian erythroid cis-regulatory modules

Multiple alignments of genome sequences are helpful guides to functional analysis, but predicting cis-regulatory modules (CRMs) accurately from such alignments remains an elusive goal. We predict CRMs for mammalian genes expressed in red blood cells by combining two properties gleaned from aligned, noncoding genome sequences: a positive regulatory potential (RP) score, which detects similarity to patterns in alignments distinctive for regulatory regions, and conservation of a binding site motif for the essential erythroid transcription factor GATA-1. Within eight target loci, we tested 75 noncoding segments by reporter gene assays in transiently transfected human K562 cells and/or after site-directed integration into murine erythroleukemia cells. Segments with a high RP score and a conserved exact match to the binding site consensus are validated at a good rate (50%-100%, with rates increasing at higher RP), whereas segments with lower RP scores or nonconsensus binding motifs tend to be inactive. Active DNA segments were shown to be occupied by GATA-1 protein by chromatin immunoprecipitation, whereas sites predicted to be inactive were not occupied. We verify four previously known erythroid CRMs and identify 28 novel ones. Thus, high RP in combination with another feature of a CRM, such as a conserved transcription factor binding site, is a good predictor of functional CRMs. Genome-wide predictions based on RP and a large set of well-defined transcription factor binding sites are available through servers at http://www.bx.psu.edu/.

Repression of c-kit and its downstream substrates by GATA-1 inhibits cell proliferation during erythroid maturation

Stem cell factor (SCF), erythropoietin (Epo), and GATA-1 play an essential role(s) in erythroid development. We examined how these proteins interact functionally in G1E cells, a GATA-1(-) erythroblast line that proliferates in an SCF-dependent fashion and, upon restoration of GATA-1 function, undergoes GATA-1 proliferation arrest and Epo-dependent terminal maturation. We show that SCF-induced cell cycle progression is mediated via activation of the Src kinase/c-Myc pathway. Restoration of GATA-1 activity induced G1 cell cycle arrest coincident with repression of c-Kit and its downstream effectors Vav1, Rac1, and Akt. Sustained expression of each of these individual signaling components inhibited GATA-1-induced cell cycle arrest to various degrees but had no effects on the expression of GATA-1-regulated erythroid maturation markers. Chromatin immunoprecipitation analysis revealed that GATA-1 occupies a defined Kit gene regulatory element in vivo, suggesting a direct mechanism for gene repression. Hence, in addition to its well-established function as an activator of erythroid genes, GATA-1 also participates in a distinct genetic program that inhibits cell proliferation by repressing the expression of multiple components of the c-Kit signaling axis. Our findings reveal a novel aspect of molecular cross talk between essential transcriptional and cytokine signaling components of hematopoietic development.

Initial sequence of the chimpanzee genome and comparison with the human genome

Here we present a draft genome sequence of the common chimpanzee (Pan troglodytes). Through comparison with the human genome, we have generated a largely complete catalogue of the genetic differences that have accumulated since the human and chimpanzee species diverged from our common ancestor, constituting approximately thirty-five million single-nucleotide changes, five million insertion/deletion events, and various chromosomal rearrangements. We use this catalogue to explore the magnitude and regional variation of mutational forces shaping these two genomes, and the strength of positive and negative selection acting on their genes. In particular, we find that the patterns of evolution in human and chimpanzee protein-coding genes are highly correlated and dominated by the fixation of neutral and slightly deleterious alleles. We also use the chimpanzee genome as an outgroup to investigate human population genetics and identify signatures of selective sweeps in recent human evolution.

Evaluation of regulatory potential and conservation scores for detecting cis-regulatory modules in aligned mammalian genome sequences

Techniques of comparative genomics are being used to identify candidate functional DNA sequences, and objective evaluations are needed to assess their effectiveness. Different analytical methods score distinctive features of whole-genome alignments among human, mouse, and rat to predict functional regions. We evaluated three of these methods for their ability to identify the positions of known regulatory regions in the well-studied HBB gene complex. Two methods, multispecies conserved sequences and phastCons, quantify levels of conservation to estimate a likelihood that aligned DNA sequences are under purifying selection. A third function, regulatory potential (RP), measures the similarity of patterns in the alignments to those in known regulatory regions. The methods can correctly identify 50%-60% of noncoding positions in the HBB gene complex as regulatory or nonregulatory, with RP performing better than do other methods. When evaluated by the ability to discriminate genomic intervals, RP reaches a sensitivity of 0.78 and a true discovery rate of approximately 0.6. The performance is better on other reference sets; both phastCons and RP scores can capture almost all regulatory elements in those sets along with approximately 7% of the human genome.

Mulan: multiple-sequence local alignment and visualization for studying function and evolution

Multiple-sequence alignment analysis is a powerful approach for understanding phylogenetic relationships, annotating genes, and detecting functional regulatory elements. With a growing number of partly or fully sequenced vertebrate genomes, effective tools for performing multiple comparisons are required to accurately and efficiently assist biological discoveries. Here we introduce Mulan (http://mulan.dcode.org/), a novel method and a network server for comparing multiple draft and finished-quality sequences to identify functional elements conserved over evolutionary time. Mulan brings together several novel algorithms: the TBA multi-aligner program for rapid identification of local sequence conservation, and the multiTF program for detecting evolutionarily conserved transcription factor binding sites in multiple alignments. In addition, Mulan supports two-way communication with the GALA database; alignments of multiple species dynamically generated in GALA can be viewed in Mulan, and conserved transcription factor binding sites identified with Mulan/multiTF can be integrated and overlaid with extensive genome annotation data using GALA. Local multiple alignments computed by Mulan ensure reliable representation of short- and large-scale genomic rearrangements in distant organisms. Mulan allows for interactive modification of critical conservation parameters to differentially predict conserved regions in comparisons of both closely and distantly related species. We illustrate the uses and applications of the Mulan tool through multispecies comparisons of the GATA3 gene locus and the identification of elements that are conserved in a different way in avians than in other genomes, allowing speculation on the evolution of birds. Source code for the aligners and the aligner-evaluation software can be freely downloaded from http://www.bx.psu.edu/miller_lab/.

Regulatory potential scores from genome-wide three-way alignments of human, mouse, and rat

We generalize the computation of the Regulatory Potential (RP) score from two-way alignments of human and mouse to three-way alignments of human, mouse, and rat. This requires overcoming technical challenges that arise because the complexity of the models underlying the score increases exponentially with the number of species. Despite the close evolutionary proximity of rat to mouse, we find that adding the rat sequence increases our ability to predict genomic sites that regulate gene transcription. A variant of the RP scoring scheme that accounts for local variation in neutral mutational patterns further improves our predictions.