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Dive into the research topics where Mark Borodovsky is active.

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Featured researches published by Mark Borodovsky.


Nature | 1997

The complete genome sequence of the gastric pathogen Helicobacter pylori

Jean-F. Tomb; Owen White; Anthony R. Kerlavage; Rebecca A. Clayton; Granger Sutton; Robert D. Fleischmann; Karen A. Ketchum; Hans-Peter Klenk; Steven R. Gill; Brian A. Dougherty; Karen E. Nelson; John Quackenbush; Lixin Zhou; Ewen F. Kirkness; Scott N. Peterson; Brendan J. Loftus; Delwood Richardson; Robert J. Dodson; Hanif G. Khalak; Anna Glodek; Keith McKenney; Lisa M. Fitzegerald; Norman H. Lee; Mark D. Adams; Erin Hickey; Douglas E. Berg; Jeanine D. Gocayne; Teresa Utterback; Jeremy Peterson; Jenny M. Kelley

Helicobacter pylori, strain 26695, has a circular genome of 1,667,867 base pairs and 1,590 predicted coding sequences. Sequence analysis indicates that H. pylori has well-developed systems for motility, for scavenging iron, and for DNA restriction and modification. Many putative adhesins, lipoproteins and other outer membrane proteins were identified, underscoring the potential complexity of host–pathogen interaction. Based on the large number of sequence-related genes encoding outer membrane proteins and the presence of homopolymeric tracts and dinucleotide repeats in coding sequences, H. pylori, like several other mucosal pathogens, probably uses recombination and slipped-strand mispairing within repeats as mechanisms for antigenic variation and adaptive evolution. Consistent with its restricted niche, H. pylori has a few regulatory networks, and a limited metabolic repertoire and biosynthetic capacity. Its survival in acid conditions depends, in part, on its ability to establish a positive inside-membrane potential in low pH.


Nature Genetics | 2011

The genome of woodland strawberry ( Fragaria vesca )

Vladimir Shulaev; Daniel J. Sargent; Ross N. Crowhurst; Todd C. Mockler; Otto Folkerts; Arthur L. Delcher; Pankaj Jaiswal; Keithanne Mockaitis; Aaron Liston; Shrinivasrao P. Mane; Paul D. Burns; Thomas M. Davis; Janet P. Slovin; Nahla Bassil; Roger P. Hellens; Clive Evans; Tim Harkins; Chinnappa D. Kodira; Brian Desany; Oswald Crasta; Roderick V. Jensen; Andrew C. Allan; Todd P. Michael; João C. Setubal; Jean Marc Celton; Kelly P. Williams; Sarah H. Holt; Juan Jairo Ruiz Rojas; Mithu Chatterjee; Bo Liu

The woodland strawberry, Fragaria vesca (2n = 2x = 14), is a versatile experimental plant system. This diminutive herbaceous perennial has a small genome (240 Mb), is amenable to genetic transformation and shares substantial sequence identity with the cultivated strawberry (Fragaria × ananassa) and other economically important rosaceous plants. Here we report the draft F. vesca genome, which was sequenced to ×39 coverage using second-generation technology, assembled de novo and then anchored to the genetic linkage map into seven pseudochromosomes. This diploid strawberry sequence lacks the large genome duplications seen in other rosids. Gene prediction modeling identified 34,809 genes, with most being supported by transcriptome mapping. Genes critical to valuable horticultural traits including flavor, nutritional value and flowering time were identified. Macrosyntenic relationships between Fragaria and Prunus predict a hypothetical ancestral Rosaceae genome that had nine chromosomes. New phylogenetic analysis of 154 protein-coding genes suggests that assignment of Populus to Malvidae, rather than Fabidae, is warranted.


Nucleic Acids Research | 2005

GeneMark: web software for gene finding in prokaryotes, eukaryotes and viruses

John Besemer; Mark Borodovsky

The task of gene identification frequently confronting researchers working with both novel and well studied genomes can be conveniently and reliably solved with the help of the GeneMark web software (). The website provides interfaces to the GeneMark family of programs designed and tuned for gene prediction in prokaryotic, eukaryotic and viral genomic sequences. Currently, the server allows the analysis of nearly 200 prokaryotic and >10 eukaryotic genomes using species-specific versions of the software and pre-computed gene models. In addition, genes in prokaryotic sequences from novel genomes can be identified using models derived on the spot upon sequence submission, either by a relatively simple heuristic approach or by the full-fledged self-training program GeneMarkS. A database of reannotations of >1000 viral genomes by the GeneMarkS program is also available from the web site. The GeneMark website is frequently updated to provide the latest versions of the software and gene models.


Nucleic Acids Research | 2016

NCBI prokaryotic genome annotation pipeline.

Tatiana Tatusova; Michael DiCuccio; Azat Badretdin; Vyacheslav Chetvernin; Eric P. Nawrocki; Leonid Zaslavsky; Alexandre Lomsadze; Kim D. Pruitt; Mark Borodovsky; James Ostell

Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBIs Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/.


Nucleic Acids Research | 2010

Ab initio gene identification in metagenomic sequences

Wenhan Zhu; Alexandre Lomsadze; Mark Borodovsky

We describe an algorithm for gene identification in DNA sequences derived from shotgun sequencing of microbial communities. Accurate ab initio gene prediction in a short nucleotide sequence of anonymous origin is hampered by uncertainty in model parameters. While several machine learning approaches could be proposed to bypass this difficulty, one effective method is to estimate parameters from dependencies, formed in evolution, between frequencies of oligonucleotides in protein-coding regions and genome nucleotide composition. Original version of the method was proposed in 1999 and has been used since for (i) reconstructing codon frequency vector needed for gene finding in viral genomes and (ii) initializing parameters of self-training gene finding algorithms. With advent of new prokaryotic genomes en masse it became possible to enhance the original approach by using direct polynomial and logistic approximations of oligonucleotide frequencies, as well as by separating models for bacteria and archaea. These advances have increased the accuracy of model reconstruction and, subsequently, gene prediction. We describe the refined method and assess its accuracy on known prokaryotic genomes split into short sequences. Also, we show that as a result of application of the new method, several thousands of new genes could be added to existing annotations of several human and mouse gut metagenomes.


Genome Research | 2008

Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training

Vardges Ter-Hovhannisyan; Alexandre Lomsadze; Yury O. Chernoff; Mark Borodovsky

We describe a new ab initio algorithm, GeneMark-ES version 2, that identifies protein-coding genes in fungal genomes. The algorithm does not require a predetermined training set to estimate parameters of the underlying hidden Markov model (HMM). Instead, the anonymous genomic sequence in question is used as an input for iterative unsupervised training. The algorithm extends our previously developed method tested on genomes of Arabidopsis thaliana, Caenorhabditis elegans, and Drosophila melanogaster. To better reflect features of fungal gene organization, we enhanced the intron submodel to accommodate sequences with and without branch point sites. This design enables the algorithm to work equally well for species with the kinds of variations in splicing mechanisms seen in the fungal phyla Ascomycota, Basidiomycota, and Zygomycota. Upon self-training, the intron submodel switches on in several steps to reach its full complexity. We demonstrate that the algorithm accuracy, both at the exon and the whole gene level, is favorably compared to the accuracy of gene finders that employ supervised training. Application of the new method to known fungal genomes indicates substantial improvement over existing annotations. By eliminating the effort necessary to build comprehensive training sets, the new algorithm can streamline and accelerate the process of annotation in a large number of fungal genome sequencing projects.


The Plant Cell | 2010

The Chlorella variabilis NC64A Genome Reveals Adaptation to Photosymbiosis, Coevolution with Viruses, and Cryptic Sex

Guillaume Blanc; Garry A. Duncan; Irina V. Agarkova; Mark Borodovsky; James R. Gurnon; Alan Kuo; Erika Lindquist; Susan Lucas; Jasmyn Pangilinan; Juergen Polle; Asaf Salamov; Astrid Terry; Takashi Yamada; David D. Dunigan; Igor V. Grigoriev; Jean-Michel Claverie; James L. Van Etten

This report describes the genome sequence of Chlorella variabilis NC64A. Surprisingly, given that NC64A has been thought to be asexual and nonmotile, this work identifies homologs of genes involved in meiosis, gamete fusion, and flagella. Chlorella variabilis NC64A, a unicellular photosynthetic green alga (Trebouxiophyceae), is an intracellular photobiont of Paramecium bursaria and a model system for studying virus/algal interactions. We sequenced its 46-Mb nuclear genome, revealing an expansion of protein families that could have participated in adaptation to symbiosis. NC64A exhibits variations in GC content across its genome that correlate with global expression level, average intron size, and codon usage bias. Although Chlorella species have been assumed to be asexual and nonmotile, the NC64A genome encodes all the known meiosis-specific proteins and a subset of proteins found in flagella. We hypothesize that Chlorella might have retained a flagella-derived structure that could be involved in sexual reproduction. Furthermore, a survey of phytohormone pathways in chlorophyte algae identified algal orthologs of Arabidopsis thaliana genes involved in hormone biosynthesis and signaling, suggesting that these functions were established prior to the evolution of land plants. We show that the ability of Chlorella to produce chitinous cell walls likely resulted from the capture of metabolic genes by horizontal gene transfer from algal viruses, prokaryotes, or fungi. Analysis of the NC64A genome substantially advances our understanding of the green lineage evolution, including the genomic interplay with viruses and symbiosis between eukaryotes.


Current Biology | 1996

Metabolism and evolution of Haemophilus influenzae deduced from a whole-genome comparison with Escherichia coli

Roman L. Tatusov; Arcady Mushegian; Peer Bork; Nigel P. Brown; William S. Hayes; Mark Borodovsky; Kenneth E. Rudd; Eugene V. Koonin

BACKGROUND The 1.83 Megabase (Mb) sequence of the Haemophilus influenzae chromosome, the first completed genome sequence of a cellular life form, has been recently reported. Approximately 75 % of the 4.7 Mb genome sequence of Escherichia coli is also available. The life styles of the two bacteria are very different - H. influenzae is an obligate parasite that lives in human upper respiratory mucosa and can be cultivated only on rich media, whereas E. coli is a saprophyte that can grow on minimal media. A detailed comparison of the protein products encoded by these two genomes is expected to provide valuable insights into bacterial cell physiology and genome evolution. RESULTS We describe the results of computer analysis of the amino-acid sequences of 1703 putative proteins encoded by the complete genome of H. influenzae. We detected sequence similarity to proteins in current databases for 92 % of the H. influenzae protein sequences, and at least a general functional prediction was possible for 83 %. A comparison of the H. influenzae protein sequences with those of 3010 proteins encoded by the sequenced 75 % of the E. coli genome revealed 1128 pairs of apparent orthologs, with an average of 59 % identity. In contrast to the high similarity between orthologs, the genome organization and the functional repertoire of genes in the two bacteria were remarkably different. The smaller genome size of H. influenzae is explained, to a large extent, by a reduction in the number of paralogous genes. There was no long range colinearity between the E. coli and H. influenzae gene orders, but over 70 % of the orthologous genes were found in short conserved strings, only about half of which were operons in E. coli. Superposition of the H. influenzae enzyme repertoire upon the known E. coli metabolic pathways allowed us to reconstruct similar and alternative pathways in H. influenzae and provides an explanation for the known nutritional requirements. CONCLUSIONS By comparing proteins encoded by the two bacterial genomes, we have shown that extensive gene shuffling and variation in the extent of gene paralogy are major trends in bacterial evolution; this comparison has also allowed us to deduce crucial aspects of the largely uncharacterized metabolism of H. influenzae.


Proceedings of the National Academy of Sciences of the United States of America | 2010

Insights into evolution of multicellular fungi from the assembled chromosomes of the mushroom Coprinopsis cinerea (Coprinus cinereus)

Jason E. Stajich; Sarah K. Wilke; Dag Ahrén; Chun Hang Au; Bruce W. Birren; Mark Borodovsky; Claire Burns; Björn Canbäck; Lorna A. Casselton; Chi Keung Cheng; Jixin Deng; Fred S. Dietrich; David C. Fargo; Mark L. Farman; Allen C. Gathman; Jonathan M. Goldberg; Roderic Guigó; Patrick J. Hoegger; James Hooker; Ashleigh Huggins; Timothy Y. James; Takashi Kamada; Sreedhar Kilaru; Chinnapa Kodira; Ursula Kües; Doris M. Kupfer; Hoi Shan Kwan; Alexandre Lomsadze; Weixi Li; Walt W. Lilly

The mushroom Coprinopsis cinerea is a classic experimental model for multicellular development in fungi because it grows on defined media, completes its life cycle in 2 weeks, produces some 108 synchronized meiocytes, and can be manipulated at all stages in development by mutation and transformation. The 37-megabase genome of C. cinerea was sequenced and assembled into 13 chromosomes. Meiotic recombination rates vary greatly along the chromosomes, and retrotransposons are absent in large regions of the genome with low levels of meiotic recombination. Single-copy genes with identifiable orthologs in other basidiomycetes are predominant in low-recombination regions of the chromosome. In contrast, paralogous multicopy genes are found in the highly recombining regions, including a large family of protein kinases (FunK1) unique to multicellular fungi. Analyses of P450 and hydrophobin gene families confirmed that local gene duplications drive the expansions of paralogous copies and the expansions occur in independent lineages of Agaricomycotina fungi. Gene-expression patterns from microarrays were used to dissect the transcriptional program of dikaryon formation (mating). Several members of the FunK1 kinase family are differentially regulated during sexual morphogenesis, and coordinate regulation of adjacent duplications is rare. The genomes of C. cinerea and Laccaria bicolor, a symbiotic basidiomycete, share extensive regions of synteny. The largest syntenic blocks occur in regions with low meiotic recombination rates, no transposable elements, and tight gene spacing, where orthologous single-copy genes are overrepresented. The chromosome assembly of C. cinerea is an essential resource in understanding the evolution of multicellularity in the fungi.


Genome Biology | 2012

The genome of the polar eukaryotic microalga Coccomyxa subellipsoidea reveals traits of cold adaptation

Guillaume Blanc; Irina V. Agarkova; Jane Grimwood; Alan Kuo; Andrew J. Brueggeman; David D. Dunigan; James R. Gurnon; Istvan Ladunga; Erika Lindquist; Susan Lucas; Jasmyn Pangilinan; Thomas Pröschold; Asaf Salamov; Jeremy Schmutz; Donald P. Weeks; Takashi Yamada; Alexandre Lomsadze; Mark Borodovsky; Jean-Michel Claverie; Igor V. Grigoriev; James L. Van Etten

BackgroundLittle is known about the mechanisms of adaptation of life to the extreme environmental conditions encountered in polar regions. Here we present the genome sequence of a unicellular green alga from the division chlorophyta, Coccomyxa subellipsoidea C-169, which we will hereafter refer to as C-169. This is the first eukaryotic microorganism from a polar environment to have its genome sequenced.ResultsThe 48.8 Mb genome contained in 20 chromosomes exhibits significant synteny conservation with the chromosomes of its relatives Chlorella variabilis and Chlamydomonas reinhardtii. The order of the genes is highly reshuffled within synteny blocks, suggesting that intra-chromosomal rearrangements were more prevalent than inter-chromosomal rearrangements. Remarkably, Zepp retrotransposons occur in clusters of nested elements with strictly one cluster per chromosome probably residing at the centromere. Several protein families overrepresented in C. subellipsoidae include proteins involved in lipid metabolism, transporters, cellulose synthases and short alcohol dehydrogenases. Conversely, C-169 lacks proteins that exist in all other sequenced chlorophytes, including components of the glycosyl phosphatidyl inositol anchoring system, pyruvate phosphate dikinase and the photosystem 1 reaction center subunit N (PsaN).ConclusionsWe suggest that some of these gene losses and gains could have contributed to adaptation to low temperatures. Comparison of these genomic features with the adaptive strategies of psychrophilic microbes suggests that prokaryotes and eukaryotes followed comparable evolutionary routes to adapt to cold environments.

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Alexandre Lomsadze

Georgia Institute of Technology

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Svetlana Ekisheva

Georgia Institute of Technology

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William S. Hayes

Georgia Institute of Technology

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Eugene V. Koonin

University of Connecticut Health Center

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John Besemer

Georgia Institute of Technology

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Ivan Antonov

Georgia Institute of Technology

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James D. McIninch

Georgia Institute of Technology

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Kenneth E. Rudd

National Institutes of Health

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Paul D. Burns

Georgia Institute of Technology

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Ryan Mills

Georgia Institute of Technology

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