Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships

Pairwise sequence comparison methods have been assessed using proteins whose relationships are known reliably from their structures and functions, as described in the scop database [Murzin, A. G., Brenner, S. E., Hubbard, T. & Chothia C. (1995) J. Mol. Biol. 247, 536–540]. The evaluation tested the programs blast [Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. (1990). J. Mol. Biol. 215, 403–410], wu-blast2 [Altschul, S. F. & Gish, W. (1996) Methods Enzymol. 266, 460–480], fasta [Pearson, W. R. & Lipman, D. J. (1988) Proc. Natl. Acad. Sci. USA 85, 2444–2448], and ssearch [Smith, T. F. & Waterman, M. S. (1981) J. Mol. Biol. 147, 195–197] and their scoring schemes. The error rate of all algorithms is greatly reduced by using statistical scores to evaluate matches rather than percentage identity or raw scores. The E-value statistical scores of ssearch and fasta are reliable: the number of false positives found in our tests agrees well with the scores reported. However, the P-values reported by blast and wu-blast2 exaggerate significance by orders of magnitude. ssearch, fasta ktup = 1, and wu-blast2 perform best, and they are capable of detecting almost all relationships between proteins whose sequence identities are >30%. For more distantly related proteins, they do much less well; only one-half of the relationships between proteins with 20–30% identity are found. Because many homologs have low sequence similarity, most distant relationships cannot be detected by any pairwise comparison method; however, those which are identified may be used with confidence.

DNase I-hypersensitive sites I and II of the human growth hormone locus control region are a major developmental activator of somatotrope gene expression

High-level expression of the human growth hormone (hGH) gene is limited to somatotrope and lactosomatotrope cells of the anterior pituitary. We previously identified a locus control region (LCR) for the hGH gene composed of four tissue-specific DNase I-hypersensitive sites (HS) located between −14.6 kb and −32 kb 5′ to the hGH transcription start site that is responsible for establishing a physiologically regulated chromatin domain for hGH transgene expression in mouse pituitary. In the present study we demonstrated that the LCR mediates somatotrope and lactosomatotrope restriction on an otherwise weakly and diffusely expressed hGH transgene. The subregion of the LCR containing the two pituitary-specific HS, HSI and HSII (−14.6 to −16.2 kb relative to the hGH promoter and denoted HSI,II), was found to be sufficient for mediating somatotrope and lactosomatotrope restriction, for appropriately timed induction of hGH transgene expression between embryonic days 15.5 and 16.5, and for selective extinction of hGH expression in mature lactotropes. When studied by cell transfection, the HSI,II fragment selectively enhanced transcription in a presomatotrope-derived cell line, although at levels (2- to 3-fold) well below that seen in vivo. The LCR activity of the HSI,II element was therefore localized by scoring transgene expression in fetal founder pituitaries at embryonic day 18.5. The data from these studies indicated that a 404-bp segment of the HSI,II region encodes a critical subset of LCR functions, including the establishment of a productive chromatin environment, cell-specific restriction and enhancement of expression, and appropriately timed induction of the hGH transgene during embryonic development.

The estimation of statistical parameters for local alignment score distributions

The distribution of optimal local alignment scores of random sequences plays a vital role in evaluating the statistical significance of sequence alignments. These scores can be well described by an extreme-value distribution. The distribution’s parameters depend upon the scoring system employed and the random letter frequencies; in general they cannot be derived analytically, but must be estimated by curve fitting. For obtaining accurate parameter estimates, a form of the recently described ‘island’ method has several advantages. We describe this method in detail, and use it to investigate the functional dependence of these parameters on finite-length edge effects.

PCR candidate region mismatch scanning: adaptation to quantitative, high-throughput genotyping

Linkage and association analyses were performed to identify loci affecting disease susceptibility by scoring previously characterized sequence variations such as microsatellites and single nucleotide polymorphisms. Lack of markers in regions of interest, as well as difficulty in adapting various methods to high-throughput settings, often limits the effectiveness of the analyses. We have adapted the Escherichia coli mismatch detection system, employing the factors MutS, MutL and MutH, for use in PCR-based, automated, high-throughput genotyping and mutation detection of genomic DNA. Optimal sensitivity and signal-to-noise ratios were obtained in a straightforward fashion because the detection reaction proved to be principally dependent upon monovalent cation concentration and MutL concentration. Quantitative relationships of the optimal values of these parameters with length of the DNA test fragment were demonstrated, in support of the translocation model for the mechanism of action of these enzymes, rather than the molecular switch model. Thus, rapid, sequence-independent optimization was possible for each new genomic target region. Other factors potentially limiting the flexibility of mismatch scanning, such as positioning of dam recognition sites within the target fragment, have also been investigated. We developed several strategies, which can be easily adapted to automation, for limiting the analysis to intersample heteroduplexes. Thus, the principal barriers to the use of this methodology, which we have designated PCR candidate region mismatch scanning, in cost-effective, high-throughput settings have been removed.

Identification of protein oligomerization states by analysis of interface conservation

The discrimination of true oligomeric protein–protein contacts from nonspecific crystal contacts remains problematic. Criteria that have been used previously base the assignment of oligomeric state on consideration of the area of the interface and/or the results of scoring functions based on statistical potentials. Both techniques have a high success rate but fail in more than 10% of cases. More importantly, the oligomeric states of several proteins are incorrectly assigned by both methods. Here we test the hypothesis that true oligomeric contacts should be identifiable on the basis of an increased degree of conservation of the residues involved in the interface. By quantifying the degree of conservation of the interface and comparing it with that of the remainder of the protein surface, we develop a new criterion that provides a highly effective complement to existing methods.

Multiple DNA and protein sequence alignment based on segment-to-segment comparison.

In this paper, a new way to think about, and to construct, pairwise as well as multiple alignments of DNA and protein sequences is proposed. Rather than forcing alignments to either align single residues or to introduce gaps by defining an alignment as a path running right from the source up to the sink in the associated dot-matrix diagram, we propose to consider alignments as consistent equivalence relations defined on the set of all positions occurring in all sequences under consideration. We also propose constructing alignments from whole segments exhibiting highly significant overall similarity rather than by aligning individual residues. Consequently, we present an alignment algorithm that (i) is based on segment-to-segment comparison instead of the commonly used residue-to-residue comparison and which (ii) avoids the well-known difficulties concerning the choice of appropriate gap penalties: gaps are not treated explicity, but remain as those parts of the sequences that do not belong to any of the aligned segments. Finally, we discuss the application of our algorithm to two test examples and compare it with commonly used alignment methods. As a first example, we aligned a set of 11 DNA sequences coding for functional helix-loop-helix proteins. Though the sequences show only low overall similarity, our program correctly aligned all of the 11 functional sites, which was a unique result among the methods tested. As a by-product, the reading frames of the sequences were identified. Next, we aligned a set of ribonuclease H proteins and compared our results with alignments produced by other programs as reported by McClure et al. [McClure, M. A., Vasi, T. K. & Fitch, W. M. (1994) Mol. Biol. Evol. 11, 571-592]. Our program was one of the best scoring programs. However, in contrast to other methods, our protein alignments are independent of user-defined parameters.

Glial cell line-derived neurotrophic factor promotes the survival and morphologic differentiation of Purkinje cells.

Glial cell line-derived neurotrophic factor (GDNF) promotes survival of midbrain dopaminergic neurons and motoneurons. Expression of GDNF mRNA in cerebellum raises the possibility that cells within this structure might also respond to GDNF. To examine potential trophic activities of GDNF, dissociated cultures of gestational day 18 rat cerebellum were grown for < or = 21 days in the presence of factor. GDNF increased Purkinje cell number without affecting the overall number of neurons or glial cells. A maximal response (50% above control) was elicited with GDNF at 1 pg/ml. Effects of GDNF on Purkinje cell differentiation were examined by scoring the morphologic maturation of cells in treated and control cultures. GDNF increased the proportion of Purkinje cells that displayed relatively mature morphologies, characterized by dendritic thickening and the development of spines and filopodial extensions. Morphologic maturation of the overall neuronal population was unaffected. In sum, our data indicate that GDNF is a potent survival and differentiation factor for Purkinje cells, the efferent neurons of cerebellar cortex. Together with its other actions, these findings raise the possibility that GDNF might be a critical trophic factor at multiple loci in neuronal circuits that control motor function.