PubMed Health⌕ Search

Biomedical subjects

Mark Gerstein

Publications and source records attributed to Mark Gerstein.

At least 19 recordsLinked to original sources

Network-based drug repurposing for psychiatric disorders using single-cell genomics.

Neuropsychiatric disorders lack effective treatments due to a limited understanding of the underlying cellular and molecular mechanisms. To address this, we integrated population-scale single-cell genomics data and analyzed 23 cell-type-level gene regulatory networks across schizophrenia, bipolar disorder, and autism. Our analysis revealed potential druggable transcription factors co-regulating known risk genes that converge into cell-type-specific co-regulated modules. We applied graph neural networks on those modules to prioritize novel risk genes and leveraged them in a network-based drug repurposing framework to identify 220 drug molecules with the potential for targeting specific cell types. We found evidence for 37 of these drugs in reversing disorder-associated transcriptional phenotypes. Additionally, we discovered 335 drug-cell quantitative trait loci (eQTLs), revealing genetic variation's influence on drug target expression at the cell-type level. Our results provide a single-cell network medicine resource that provides potential mechanistic insights for advancing treatment options for neuropsychiatric disorders.

Drug Repositioning↗

Patterns of nucleotide substitution, insertion and deletion in the human genome inferred from pseudogenes.

Nucleotide substitution, insertion and deletion (indel) events are the major driving forces that have shaped genomes. Using the recently identified human ribosomal protein (RP) pseudogene sequences, we have thoroughly studied DNA mutation patterns in the human genome. We analyzed a total of 1726 processed RP pseudogene sequences, comprising more than 700 000 bases. To be sure to differentiate the sequence changes occurring in the functional genes during evolution from those occurring in pseudogenes after they were fixed in the genome, we used only pseudogene sequences originating from parts of RP genes that are identical in human and mouse. Overall, we found that nucleotide transitions are more common than transversions, by roughly a factor of two. Moreover, the substitution rates amongst the 12 possible nucleotide pairs are not homogeneous as they are affected by the type of immediately neighboring nucleotides and the overall local G+C content. Finally, our dataset is large enough that it has many indels, thus allowing for the first time statistically robust analysis of these events. Overall, we found that deletions are about three times more common than insertions (3740 versus 1291). The frequencies of both these events follow characteristic power-law behavior associated with the size of the indel. However, unexpectedly, the frequency of 3 bp deletions (in contrast to 3 bp insertions) violates this trend, being considerably higher than that of 2 bp deletions. The possible biological implications of such a 3 bp bias are discussed.

Algorithms↗

Comparing protein abundance and mRNA expression levels on a genomic scale.

Attempts to correlate protein abundance with mRNA expression levels have had variable success. We review the results of these comparisons, focusing on yeast. In the process, we survey experimental techniques for determining protein abundance, principally two-dimensional gel electrophoresis and mass-spectrometry. We also merge many of the available yeast protein-abundance datasets, using the resulting larger 'meta-dataset' to find correlations between protein and mRNA expression, both globally and within smaller categories.

Animals↗

The human genome has 49 cytochrome c pseudogenes, including a relic of a primordial gene that still functions in mouse.

Using a computational approach, we have identified 49 cytochrome c (cyc) pseudogenes in the human genome. Analysis of these provides a detailed description of the molecular evolution of the cyc gene. Almost all of the pseudogenes are full-length, and we have concluded that they mostly originated from independent retrotransposition events (i.e. they are processed). Based on phylogenetic analysis and detailed sequence comparison, we have further divided these pseudogenes into two groups. The first, consisting of four young pseudogenes that were dated to be between 27 and 34 Myr old, originated from a gene almost identical to the modern human cyc gene. The second group of pseudogenes is much older and appears to have descended from ancient genes similar to modern rodent cyc genes. Thus, our results support the observation that accelerated evolution in cyc sequence had occurred in the primate lineage. The oldest pseudogene in the second group, dated to be over 80 Myr old, resembles the testis-specific cyc gene in modern rodents. It is likely that the mammalian ancestor had both the somatic and the testis-specific cyc genes. While the testis-specific gene is still functional in modern rodents, the human has lost it, retaining only a pseudogene in its place. Thus, our study may have identified a pseudogene that is a dead relic of a gene that has completely died off in the human lineage.

Amino Acid Sequence↗

ExpressYourself: A modular platform for processing and visualizing microarray data.

DNA microarrays are widely used in biological research; by analyzing differential hybridization on a single microarray slide, one can detect changes in mRNA expression levels, increases in DNA copy numbers and the location of transcription factor binding sites on a genomic scale. Having performed the experiments, the major challenge is to process large, noisy datasets in order to identify the specific array elements that are significantly differentially hybridized. This normally requires aggregating different, often incompatible programs into a multi-step pipeline. Here we present ExpressYourself, a fully integrated platform for processing microarray data. In completely automated fashion, it will correct the background array signal, normalize the Cy5 and Cy3 signals, score levels of differential hybridization, combine the results of replicate experiments, filter problematic regions of the array and assess the quality of individual and replicate experiments. ExpressYourself is designed with a highly modular architecture so various types of microarray analysis algorithms can readily be incorporated as they are developed; for example, the system currently implements several normalization methods, including those that simultaneously consider signal intensity and slide location. The processed data are presented using a web-based graphical interface to facilitate comparison with the original images of the array slides. In particular, Express Yourself is able to regenerate images of the original microarray after applying various steps of processing, which greatly facilities identification of position-specific artifacts. The program is freely available for use at http://bioinfo.mbb.yale.edu/expressyourself.

Algorithms↗

Data mining crystallization databases: knowledge-based approaches to optimize protein crystal screens.

Protein crystallization is a major bottleneck in protein X-ray crystallography, the workhorse of most structural proteomics projects. Because the principles that govern protein crystallization are too poorly understood to allow them to be used in a strongly predictive sense, the most common crystallization strategy entails screening a wide variety of solution conditions to identify the small subset that will support crystal nucleation and growth. We tested the hypothesis that more efficient crystallization strategies could be formulated by extracting useful patterns and correlations from the large data sets of crystallization trials created in structural proteomics projects. A database of crystallization conditions was constructed for 755 different proteins purified and crystallized under uniform conditions. Forty-five percent of the proteins formed crystals. Data mining identified the conditions that crystallize the most proteins, revealed that many conditions are highly correlated in their behavior, and showed that the crystallization success rate is markedly dependent on the organism from which proteins derive. Of the proteins that crystallized in a 48-condition experiment, 60% could be crystallized in as few as 6 conditions and 94% in 24 conditions. Consideration of the full range of information coming from crystal screening trials allows one to design screens that are maximally productive while consuming minimal resources, and also suggests further useful conditions for extending existing screens.

Archaeal Proteins↗

SPINE 2: a system for collaborative structural proteomics within a federated database framework.

We present version 2 of the SPINE system for structural proteomics. SPINE is available over the web at http://nesg.org. It serves as the central hub for the Northeast Structural Genomics Consortium, allowing collaborative structural proteomics to be carried out in a distributed fashion. The core of SPINE is a laboratory information management system (LIMS) for key bits of information related to the progress of the consortium in cloning, expressing and purifying proteins and then solving their structures by NMR or X-ray crystallography. Originally, SPINE focused on tracking constructs, but, in its current form, it is able to track target sample tubes and store detailed sample histories. The core database comprises a set of standard relational tables and a data dictionary that form an initial ontology for proteomic properties and provide a framework for large-scale data mining. Moreover, SPINE sits at the center of a federation of interoperable information resources. These can be divided into (i) local resources closely coupled with SPINE that enable it to handle less standardized information (e.g. integrated mailing and publication lists), (ii) other information resources in the NESG consortium that are inter-linked with SPINE (e.g. crystallization LIMS local to particular laboratories) and (iii) international archival resources that SPINE links to and passes on information to (e.g. TargetDB at the PDB).

Cooperative Behavior↗

A method to assess compositional bias in biological sequences and its application to prion-like glutamine/asparagine-rich domains in eukaryotic proteomes.

We have derived a novel method to assess compositional biases in biological sequences, which is based on finding the lowest-probability subsequences for a given residue-type set. As a case study, the distribution of prion-like glutamine/asparagine-rich ((Q+N)-rich) domains (which are linked to amyloidogenesis) was assessed for budding and fission yeasts and four other eukaryotes. We find more than 170 prion-like (Q+N)-rich regions in budding yeast, and, strikingly, many fewer in fission yeast. Also, some residues, such as tryptophan or isoleucine, are unlikely to form biased regions in any eukaryotic proteome.

Amino Acid Motifs↗

Revisiting the codon adaptation index from a whole-genome perspective: analyzing the relationship between gene expression and codon occurrence in yeast using a variety of models.

Highly expressed genes in many bacteria and small eukaryotes often have a strong compositional bias, in terms of codon usage. Two widely used numerical indices, the codon adaptation index (CAI) and the codon usage, use this bias to predict the expression level of genes. When these indices were first introduced, they were based on fairly simple assumptions about which genes are most highly expressed: the CAI was originally based on the codon composition of a set of only 24 highly expressed genes, and the codon usage on assumptions about which functional classes of genes are highly expressed in fast-growing bacteria. Given the recent advent of genome-wide expression data, we should be able to improve on these assumptions. Here, we measure, in yeast, the degree to which consideration of the current genome-wide expression data sets improves the performance of both numerical indices. Indeed, we find that by changing the parameterization of each model its correlation with actual expression levels can be somewhat improved, although both indices are fairly insensitive to the exact way they are parameterized. This insensitivity indicates a consistent codon bias amongst highly expressed genes. We also attempt direct linear regression of codon composition against genome-wide expression levels (and protein abundance data). This has some similarity with the CAI formalism and yields an alternative model for the prediction of expression levels based on the coding sequences of genes. More information is available at http://bioinfo.mbb.yale.edu/expression/codons.

Codon↗

Strategies for structural proteomics of prokaryotes: Quantifying the advantages of studying orthologous proteins and of using both NMR and X-ray crystallography approaches.

Only about half of non-membrane-bound proteins encoded by either bacterial or archaeal genomes are soluble when expressed in Escherichia coli (Yee et al., Proc Natl Acad Sci USA 2002;99:1825-1830; Christendat et al., Prog Biophys Mol Biol 200;73:339-345). This property limits genome-scale functional and structural proteomics studies, which depend on having a recombinant, soluble version of each protein. An emerging strategy to increase the probability of deriving a soluble derivative of a protein is to study different sequence homologues of the same protein, including representatives from thermophilic organisms, based on the assumption that the stability of these proteins will facilitate structural analysis. To estimate the relative merits of this strategy, we compared the recombinant expression, solubility, and suitability for structural analysis by NMR and/or X-ray crystallography for 68 pairs of homologous proteins from E. coli and Thermotoga maritima. A sample suitable for structural studies was obtained for 62 of the 68 pairs of homologs under standardized growth and purification procedures. Fourteen (eight E. coli and six T. maritima proteins) samples generated NMR spectra of a quality suitable for structure determination and 30 (14 E. coli and 16 T. maritima proteins) samples formed crystals. Only three (one E. coli and two T. maritima proteins) samples both crystallized and had excellent NMR properties. The conclusions from this work are: (1) The inclusion of even a single ortholog of a target protein increases the number of samples for structural studies almost twofold; (2) there was no clear advantage to the use of thermophilic proteins to generate samples for structural studies; and (3) for the small proteins analyzed here, the use of both NMR and crystallography approaches almost doubled the number of samples for structural studies.

Archaeal Proteins↗

The transcriptional activity of human Chromosome 22.

A DNA microarray representing nearly all of the unique sequences of human Chromosome 22 was constructed and used to measure global-transcriptional activity in placental poly(A)(+) RNA. We found that many of the known, related and predicted genes are expressed. More importantly, our study reveals twice as many transcribed bases as have been reported previously. Many of the newly discovered expressed fragments were verified by RNA blot analysis and a novel technique called differential hybridization mapping (DHM). Interestingly, a significant fraction of these novel fragments are expressed antisense to previously annotated introns. The coding potential of these novel expressed regions is supported by their sequence conservation in the mouse genome. This study has greatly increased our understanding of the biological information encoded on a human chromosome. To facilitate the dissemination of these results to the scientific community, we have developed a comprehensive Web resource to present the findings of this study and other features of human Chromosome 22 at http://array.mbb.yale.edu/chr22.

Amino Acid Sequence↗

Identification of pseudogenes in the Drosophila melanogaster genome.

Pseudogenes are copies of genes that cannot produce a protein. They can be detected from disruptions to their apparent coding sequence, caused by frameshifts and premature stop codons. They are classed as either processed pseudogenes (made by reverse transcription from an mRNA) or duplicated pseudogenes, arising from duplication in the genomic DNA and subsequent disablement. Historically, there is anecdotal evidence that the fruit fly (Drosophila melanogaster) has few pseudogenes. Investigators have linked this to a high deletion rate of genomic DNA, for which there is evidence from genetic experiments on genome size. Here, we apply a homology-based pipeline that was developed previously to identify pseudogenes in other eukaryotic genomes, to the fruit fly, so as to derive the first complete survey of its pseudogene population. We find approximately 100 pseudogenes, with at least a sixth of these as candidate processed pseudogenes. This gives a much lower proportion of pseudogenes (compared with the size of the proteome) than in the genomes of other eukaryotes for which data are available (human, nematode and budding yeast). Closest matching proteins to Drosophila pseudogenes are significantly longer than the average protein in its proteome (up to approximately 60% more than the average protein's length), in contrast to the situation in the three other eukaryotic genomes. This may be due to the persistence of fragments of longer genes. In the fly pseudogene population, we found most pseudogenes for serine proteases (which are more abundant in the Drosophila lineage compared with the other eukaryotes), immunoglobulin-motif-containing proteins and cytochromes P450. Data on the sequences and positions of the putative pseudogenes are available at: http://www.pseudogene.org/fly. The detection of a small number of pseudogenes in the Drosophila genome and the higher mean length for the closest matching proteins to pseudogenes (possibly because remnants of genes encoding longer proteins are more likely to persist) are further evidence for a high deletion rate of genomic DNA in the fruit fly. The data are useful for molecular evolution study in Drosophila.

Animals↗

MolMovDB: analysis and visualization of conformational change and structural flexibility.

The Database of Macromolecular Movements (http://MolMovDB.org) is a collection of data and software pertaining to flexibility in protein and RNA structures. The database is organized into two parts. Firstly, a collection of 'morphs' of solved structures representing different states of a molecule provides quantitative data for flexibility and a number of graphical representations. Secondly, a classification of known motions according to type of conformational change (e.g. 'hinged domain' or 'allosteric') incorporates textual annotation and information from the literature relating to the motion, linking together many of the morphs. A variety of subsets of the morphs are being developed for use in statistical analyses. In particular, for each subset it is possible to derive distributions of various motional quantities (e.g. maximum rotation) that can be used to place a specific motion in context as being typical or atypical for a given population. Over the past year, the database has been greatly expanded and enhanced to incorporate new structures and to improve the quality of data. The 'morph server', which enables users of the database to add new morphs either from their own research or the PDB, has also been enhanced to handle nucleic acid structures and multi-chain complexes.

Computer Graphics↗

Genomic analysis of gene expression relationships in transcriptional regulatory networks.

From merging several data sources, we created an extensive map of the transcriptional regulatory network in Saccharomyces cerevisiae, comprising 7419 interactions connecting 180 transcription factors (TFs) with their target genes. We integrated this network with gene-expression data, relating the expression profiles of TFs and target genes. We found that genes targeted by the same TF tend to be co-expressed, with the degree of co-expression increasing if genes share more than one TF. Moreover, shared targets of a TF tend to have similar cellular functions. By contrast, the expression relationships between the TFs and their targets are much more complicated, often exhibiting time-shifted or inverted behavior. Further information is available at http://bioinfo.mbb.yale.edu/regulation/TIG/

Gene Expression Regulation↗

Identification and characterization of over 100 mitochondrial ribosomal protein pseudogenes in the human genome.

The human (nuclear) genome encodes at least 79 mitochondrial ribosomal proteins (MRPs), which are imported into the mitochondria. Using a comprehensive approach, we find 41 of these give rise to 120 pseudogenes in the genome. The majority of the MRP pseudogenes are of processed origin and can be aligned to match the entire coding region of the functional MRP mRNAs. One processed pseudogene was found to have originated from an alternatively spliced mRNA transcript. We also found two duplicated pseudogenes that are transcribed in the cell as confirmed by screening the human EST database. We observed a significant correlation between the number of processed pseudogenes and the gene CDS length (R = -0.40; p < 0.001), i.e., the relatively shorter genes tend to have more processed pseudogenes. There is also a weaker correlation between the number of processed pseudogenes and the gene CDS GC content. Our study provides a catalogue of human MRP pseudogenes, which will be useful in the study of functional MRP genes. It also provides a molecular record of the evolution of these genes. More details are available at http://pseudogene.org/.

Animals↗