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Mark Diekhans

Publications and source records attributed to Mark Diekhans.

10 recordsLinked to original sources

HPRC2: A human pangenome reference with near-complete coverage of common genetic variation.

A pangenome reference overcomes the inherent limitation of any individual reference genome by integrating the variation present in a population. We present the Human Pangenome Reference Consortium's (HPRC) Release 2 (HPRC2), an openly available, second phase pangenome that is an approximately fivefold expansion in genome number over HPRC Release 1 (HPRC1) and measurable improvement in genome completeness, contiguity, and accuracy. Selecting samples with a principled algorithm prioritising common variant coverage, HPRC2 contributes 460 haplotypes that together capture over 99% of common variation observed in the All of Us Research Program v8 cohort. Combining high-coverage long and ultra-long reads with modern assemblers and polishers, we produce thousands of telomere-to-telomere (T2T) chromosomes, and relative to HPRC1 halve the number of structurally unreliable regions as well as individual base errors per haplotype. We complement the assemblies with whole genome multiple alignments and gene annotations, and derive formal pangenome coordinate systems for addressing off-reference variation, demonstrating that individual human genomes contain more than one hundred thousand variants not succinctly described with respect to existing reference genomes. We also present the first matched long-read backed pantranscriptome and panepigenome at this scale, provide continuous local-ancestry estimates spanning every genome, and outline a host of new tools and applications that leverage the pangenome resource for improved genomics analysis.

Journal Article↗

Regions of extreme synonymous codon selection in mammalian genes.

Recently there has been increasing evidence that purifying selection occurs among synonymous codons in mammalian genes. This selection appears to be a consequence of either cis-regulatory motifs, such as exonic splicing enhancers (ESEs), or mRNA secondary structures, being superimposed on the coding sequence of the gene. We have developed a program to identify regions likely to be enriched for such motifs by searching for extended regions of extreme codon conservation between homologous genes of related species. Here we present the results of applying this approach to five mammalian species (human, chimpanzee, mouse, rat and dog). Even with very conservative selection criteria, we find over 200 regions of extreme codon conservation, ranging in length from 60 to 178 codons. The regions are often found within genes involved in DNA-binding, RNA-binding or zinc-ion-binding. They are highly depleted for synonymous single nucleotide polymorphisms (SNPs) but not for non-synonymous SNPs, further indicating that the observed codon conservation is being driven by negative selection. Forty-three percent of the regions overlap conserved alternative transcript isoforms and are enriched for known ESEs. Other regions are enriched for TpA dinucleotides and may contain conserved motifs/structures relating to mRNA stability and/or degradation. We anticipate that this tool will be useful for detecting regions enriched in other classes of coding-sequence motifs and structures as well.

Alternative Splicing↗

The UCSC Known Genes.

The University of California Santa Cruz (UCSC) Known Genes dataset is constructed by a fully automated process, based on protein data from Swiss-Prot/TrEMBL (UniProt) and the associated mRNA data from Genbank. The detailed steps of this process are described. Extensive cross-references from this dataset to other genomic and proteomic data were constructed. For each known gene, a details page is provided containing rich information about the gene, together with extensive links to other relevant genomic, proteomic and pathway data. As of July 2005, the UCSC Known Genes are available for human, mouse and rat genomes. The Known Genes serves as a foundation to support several key programs: the Genome Browser, Proteome Browser, Gene Sorter and Table Browser offered at the UCSC website. All the associated data files and program source code are also available. They can be accessed at http://genome.ucsc.edu. The genomic coverage of UCSC Known Genes, RefSeq, Ensembl Genes, H-Invitational and CCDS is analyzed. Although UCSC Known Genes offers the highest genomic and CDS coverage among major human and mouse gene sets, more detailed analysis suggests all of them could be further improved.

Base Sequence↗

LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources.

MOTIVATION: The NCBI dbSNP database lists over 9 million single nucleotide polymorphisms (SNPs) in the human genome, but currently contains limited annotation information. SNPs that result in amino acid residue changes (nsSNPs) are of critical importance in variation between individuals, including disease and drug sensitivity. RESULTS: We have developed LS-SNP, a genomic scale software pipeline to annotate nsSNPs. LS-SNP comprehensively maps nsSNPs onto protein sequences, functional pathways and comparative protein structure models, and predicts positions where nsSNPs destabilize proteins, interfere with the formation of domain-domain interfaces, have an effect on protein-ligand binding or severely impact human health. It currently annotates 28,043 validated SNPs that produce amino acid residue substitutions in human proteins from the SwissProt/TrEMBL database. Annotations can be viewed via a web interface either in the context of a genomic region or by selecting sets of SNPs, genes, proteins or pathways. These results are useful for identifying candidate functional SNPs within a gene, haplotype or pathway and in probing molecular mechanisms responsible for functional impacts of nsSNPs. AVAILABILITY: http://www.salilab.org/LS-SNP CONTACT: rachelk@salilab.org SUPPLEMENTARY INFORMATION: http://salilab.org/LS-SNP/supp-info.pdf.

Algorithms↗

The UCSC Proteome Browser.

The University of California Santa Cruz (UCSC) Proteome Browser provides a wealth of protein information presented in graphical images and with links to other protein-related Internet sites. The Proteome Browser is tightly integrated with the UCSC Genome Browser. For the first time, Genome Browser users have both the genome and proteome worlds at their fingertips simultaneously. The Proteome Browser displays tracks of protein and genomic sequences, exon structure, polarity, hydrophobicity, locations of cysteine and glycosylation potential, Superfamily domains and amino acids that deviate from normal abundance. Histograms show genome-wide distribution of protein properties, including isoelectric point, molecular weight, number of exons, InterPro domains and cysteine locations, together with specific property values of the selected protein. The Proteome Browser also provides links to gene annotations in the Genome Browser, the Known Genes details page and the Gene Sorter; domain information from Superfamily, InterPro and Pfam; three-dimensional structures at the Protein Data Bank and ModBase; and pathway data at KEGG, BioCarta/CGAP and BioCyc. As of August 2004, the Proteome Browser is available for human, mouse and rat proteomes. The browser may be accessed from any Known Genes details page of the Genome Browser at http://genome.ucsc.edu. A user's guide is also available on this website.

California↗

Score functions for determining regional conservation in two-species local alignments.

We construct several score functions for use in locating unusually conserved regions in a genomewide search of aligned DNA from two species. We test these functions on regions of the human genome aligned to the mouse genome. These score functions are derived from properties of neutrally evolving sites on the mouse and human genome and can be adjusted to the local background rate of conservation. The aim of these functions is to try to identify regions of the human genome that are conserved by evolutionary selection because they have an important function, rather than by chance. We use them to get a very rough estimate of the amount of DNA in the human genome that is under selection.

Animals↗

Analysis of human mRNAs with the reference genome sequence reveals potential errors, polymorphisms, and RNA editing.

The NCBI Reference Sequence (RefSeq) project and the NIH Mammalian Gene Collection (MGC) together define a set of approximately 30,000 nonredundant human mRNA sequences with identified coding regions representing 17,000 distinct loci. These high-quality mRNA sequences allow for the identification of transcribed regions in the human genome sequence, and many researchers accept them as the correct representation of each defined gene sequence. Computational comparison of these mRNA sequences and the recently published essentially finished human genome sequence reveals several thousand undocumented nonsynonymous substitution and frame shift discrepancies between the two resources. Additional analysis is undertaken to verify that the euchromatic human genome is sufficiently complete--containing nearly the whole mRNA collection, thus allowing for a comprehensive analysis to be undertaken. Many of the discrepancies will prove to be genuine polymorphisms in the human population, somatic cell genomic variants, or examples of RNA editing. It is observed that the genome sequence variant has significant additional support from other mRNAs and ESTs, almost four times more often than does the mRNA variant, suggesting that the genome sequence is more accurate. In approximately 15% of these cases, there is substantial support for both variants, suggestive of an undocumented polymorphism. An initial screening against a 24-individual genomic DNA diversity panel verified 60% of a small set of potential single nucleotide polymorphisms from which successful results could be obtained. We also find statistical evidence that a few of these discrepancies are due to RNA editing. Overall, these results suggest that the mRNA collections may contain a substantial number of errors. For current and future mRNA collections, it may be prudent to fully reconcile each genome sequence discrepancy, classifying each as a polymorphism, site of RNA editing or somatic cell variation, or genome sequence error.

Computational Biology↗

Combining local-structure, fold-recognition, and new fold methods for protein structure prediction.

This article presents an overview of the SAM-T02 method for protein fold recognition and the UNDERTAKER program for ab initio predictions. The SAM-T02 server is an automatic method that uses two-track hidden Markov models (HMMS) to find and align template proteins from PDB to the target protein. The two-track HMMs use an amino acid alphabet and one of several different local structure alphabets. The UNDERTAKER program is a new fragment-packing program that can use short or long fragments and alignments to create protein conformations. The HMMs and fold-recognition alignments from the SAM-T02 method were used to generate the fragment and alignment libraries used by UNDERTAKER. We present results on a few selected targets for which this combined method worked particularly well: T0129, T0181, T0135, T0130, and T0139.

Algorithms↗

Covariation in frequencies of substitution, deletion, transposition, and recombination during eutherian evolution.

Six measures of evolutionary change in the human genome were studied, three derived from the aligned human and mouse genomes in conjunction with the Mouse Genome Sequencing Consortium, consisting of (1) nucleotide substitution per fourfold degenerate site in coding regions, (2) nucleotide substitution per site in relics of transposable elements active only before the human-mouse speciation, and (3) the nonaligning fraction of human DNA that is nonrepetitive or in ancestral repeats; and three derived from human genome data alone, consisting of (4) SNP density, (5) frequency of insertion of transposable elements, and (6) rate of recombination. Features 1 and 2 are measures of nucleotide substitutions at two classes of "neutral" sites, whereas 4 is a measure of recent mutations. Feature 3 is a measure dominated by deletions in mouse, whereas 5 represents insertions in human. It was found that all six vary significantly in megabase-sized regions genome-wide, and many vary together. This indicates that some regions of a genome change slowly by all processes that alter DNA, and others change faster. Regional variation in all processes is correlated with, but not completely accounted for, by GC content in human and the difference between GC content in human and mouse.

Animals↗

Initial sequencing and comparative analysis of the mouse genome.

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.

Animals↗