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Mihaela Pertea

Publications and source records attributed to Mihaela Pertea.

At least 19 recordsLinked to original sources
PubMed2025

Comprehensive Transcriptome Annotation of Thousands of HIV-1 Genomes.

Alternative splicing in HIV-1 has been a central focus of decades of research, uncovering key mechanisms of viral gene regulation, immune evasion, and therapeutic response - yet, no reference resource has existed to support transcriptome-wide analysis, limiting adoption of modern computational methods. We present HIV Atlas (https://ccb.jhu.edu/HIV_Atlas), the first reference-quality annotation of HIV-1 and SIV transcriptional diversity. We manually curated transcriptomes for HIV-1HXB2 and SIVmac239 and developed Vira, an automated annotation-transfer method specifically designed to address unique challenges of viral genome biology, to generate high-quality annotations for 2,077 complete HIV-1 genomes. Using the resources presented in our work, we evaluated conservation of splice sites, revealing near-perfect preservation of major donors and acceptors. Furthermore, using several public datasets, we demonstrate how HIV Atlas enhances methodology, improves the quality and novelty of results, and opens novel avenues for research, supporting more accurate and comprehensive analyses of bulk, single-cell, and spatial RNA-seq in HIV-1 studies.

Journal Article↗
PubMed2025

Efficient evidence-based genome annotation with EviAnn.

For many years, machine learning-based ab initio gene finding approaches have been central components of eukaryotic genome annotation pipelines, and they remain so today. The reliance on these approaches was originally sustained by the high cost and low availability of gene expression data, a primary source of evidence for gene annotation along with protein homology. However, innovations in modern sequencing technologies have revolutionized the acquisition of gene expression data, allowing scientists to rely more heavily on this class of evidence. In addition, proteins found in a multitude of well-annotated genomes represent another invaluable resource for gene annotation. Existing annotation packages often underutilize these data sources, which prompted us to develop EviAnn (Evidence-based Annotator), a novel evidence-based eukaryotic gene annotation system. EviAnn takes a strongly data-driven approach, building the exon-intron structure of genes from transcript alignments or protein-sequence homology rather than from purely ab initio gene finding techniques. We show that when provided with the same input data, EviAnn consistently outperforms current state-of-the-art packages including BRAKER3, MAKER2, and FINDER, while utilizing considerably less computer time. Annotation of a mammalian genome can be completed in less than an hour on a single multi-core server. EviAnn is freely available under an open-source license from https://github.com/alekseyzimin/EviAnn_release and from Bioconda as "eviann".

Journal Article↗
PubMed2025

OpenSpliceAI: An efficient, modular implementation of SpliceAI enabling easy retraining on non-human species.

The SpliceAI deep learning system is currently one of the most accurate methods for identifying splicing signals directly from DNA sequences. However, its utility is limited by its reliance on older software frameworks and human-centric training data. Here we introduce OpenSpliceAI, a trainable, open-source version of SpliceAI implemented in PyTorch to address these challenges. OpenSpliceAI supports both training from scratch and transfer learning, enabling seamless retraining on species-specific datasets and mitigating human-centric biases. Our experiments show that it achieves faster processing speeds and lower memory usage than the original SpliceAI code, allowing large-scale analyses of extensive genomic regions on a single GPU. Additionally, OpenSpliceAI's flexible architecture makes for easier integration with established machine learning ecosystems, simplifying the development of custom splicing models for different species and applications. We demonstrate that OpenSpliceAI's output is highly concordant with SpliceAI. In silico mutagenesis (ISM) analyses confirm that both models rely on similar sequence features, and calibration experiments demonstrate similar score probability estimates.

Journal Article↗
PubMed2007

Draft genome sequence of the sexually transmitted pathogen Trichomonas vaginalis.

We describe the genome sequence of the protist Trichomonas vaginalis, a sexually transmitted human pathogen. Repeats and transposable elements comprise about two-thirds of the approximately 160-megabase genome, reflecting a recent massive expansion of genetic material. This expansion, in conjunction with the shaping of metabolic pathways that likely transpired through lateral gene transfer from bacteria, and amplification of specific gene families implicated in pathogenesis and phagocytosis of host proteins may exemplify adaptations of the parasite during its transition to a urogenital environment. The genome sequence predicts previously unknown functions for the hydrogenosome, which support a common evolutionary origin of this unusual organelle with mitochondria.

Animals↗
PubMed2006

JIGSAW, GeneZilla, and GlimmerHMM: puzzling out the features of human genes in the ENCODE regions.

BACKGROUND: Predicting complete protein-coding genes in human DNA remains a significant challenge. Though a number of promising approaches have been investigated, an ideal suite of tools has yet to emerge that can provide near perfect levels of sensitivity and specificity at the level of whole genes. As an incremental step in this direction, it is hoped that controlled gene finding experiments in the ENCODE regions will provide a more accurate view of the relative benefits of different strategies for modeling and predicting gene structures. RESULTS: Here we describe our general-purpose eukaryotic gene finding pipeline and its major components, as well as the methodological adaptations that we found necessary in accommodating human DNA in our pipeline, noting that a similar level of effort may be necessary by ourselves and others with similar pipelines whenever a new class of genomes is presented to the community for analysis. We also describe a number of controlled experiments involving the differential inclusion of various types of evidence and feature states into our models and the resulting impact these variations have had on predictive accuracy. CONCLUSION: While in the case of the non-comparative gene finders we found that adding model states to represent specific biological features did little to enhance predictive accuracy, for our evidence-based 'combiner' program the incorporation of additional evidence tracks tended to produce significant gains in accuracy for most evidence types, suggesting that improved modeling efforts at the hidden Markov model level are of relatively little value. We relate these findings to our current plans for future research.

Computational Biology↗
PubMed2005

Genomic sequence of the pathogenic and allergenic filamentous fungus Aspergillus fumigatus.

Aspergillus fumigatus is exceptional among microorganisms in being both a primary and opportunistic pathogen as well as a major allergen. Its conidia production is prolific, and so human respiratory tract exposure is almost constant. A. fumigatus is isolated from human habitats and vegetable compost heaps. In immunocompromised individuals, the incidence of invasive infection can be as high as 50% and the mortality rate is often about 50% (ref. 2). The interaction of A. fumigatus and other airborne fungi with the immune system is increasingly linked to severe asthma and sinusitis. Although the burden of invasive disease caused by A. fumigatus is substantial, the basic biology of the organism is mostly obscure. Here we show the complete 29.4-megabase genome sequence of the clinical isolate Af293, which consists of eight chromosomes containing 9,926 predicted genes. Microarray analysis revealed temperature-dependent expression of distinct sets of genes, as well as 700 A. fumigatus genes not present or significantly diverged in the closely related sexual species Neosartorya fischeri, many of which may have roles in the pathogenicity phenotype. The Af293 genome sequence provides an unparalleled resource for the future understanding of this remarkable fungus.

Allergens↗
PubMed2005

Sequence, annotation, and analysis of synteny between rice chromosome 3 and diverged grass species.

Rice (Oryza sativa L.) chromosome 3 is evolutionarily conserved across the cultivated cereals and shares large blocks of synteny with maize and sorghum, which diverged from rice more than 50 million years ago. To begin to completely understand this chromosome, we sequenced, finished, and annotated 36.1 Mb ( approximately 97%) from O. sativa subsp. japonica cv Nipponbare. Annotation features of the chromosome include 5915 genes, of which 913 are related to transposable elements. A putative function could be assigned to 3064 genes, with another 757 genes annotated as expressed, leaving 2094 that encode hypothetical proteins. Similarity searches against the proteome of Arabidopsis thaliana revealed putative homologs for 67% of the chromosome 3 proteins. Further searches of a nonredundant amino acid database, the Pfam domain database, plant Expressed Sequence Tags, and genomic assemblies from sorghum and maize revealed only 853 nontransposable element related proteins from chromosome 3 that lacked similarity to other known sequences. Interestingly, 426 of these have a paralog within the rice genome. A comparative physical map of the wild progenitor species, Oryza nivara, with japonica chromosome 3 revealed a high degree of sequence identity and synteny between these two species, which diverged approximately 10,000 years ago. Although no major rearrangements were detected, the deduced size of the O. nivara chromosome 3 was 21% smaller than that of japonica. Synteny between rice and other cereals using an integrated maize physical map and wheat genetic map was strikingly high, further supporting the use of rice and, in particular, chromosome 3, as a model for comparative studies among the cereals.

Arabidopsis↗
PubMed2005

Genome sequence of Theileria parva, a bovine pathogen that transforms lymphocytes.

We report the genome sequence of Theileria parva, an apicomplexan pathogen causing economic losses to smallholder farmers in Africa. The parasite chromosomes exhibit limited conservation of gene synteny with Plasmodium falciparum, and its plastid-like genome represents the first example where all apicoplast genes are encoded on one DNA strand. We tentatively identify proteins that facilitate parasite segregation during host cell cytokinesis and contribute to persistent infection of transformed host cells. Several biosynthetic pathways are incomplete or absent, suggesting substantial metabolic dependence on the host cell. One protein family that may generate parasite antigenic diversity is not telomere-associated.

Algorithms↗
PubMed2005

Efficient decoding algorithms for generalized hidden Markov model gene finders.

BACKGROUND: The Generalized Hidden Markov Model (GHMM) has proven a useful framework for the task of computational gene prediction in eukaryotic genomes, due to its flexibility and probabilistic underpinnings. As the focus of the gene finding community shifts toward the use of homology information to improve prediction accuracy, extensions to the basic GHMM model are being explored as possible ways to integrate this homology information into the prediction process. Particularly prominent among these extensions are those techniques which call for the simultaneous prediction of genes in two or more genomes at once, thereby increasing significantly the computational cost of prediction and highlighting the importance of speed and memory efficiency in the implementation of the underlying GHMM algorithms. Unfortunately, the task of implementing an efficient GHMM-based gene finder is already a nontrivial one, and it can be expected that this task will only grow more onerous as our models increase in complexity. RESULTS: As a first step toward addressing the implementation challenges of these next-generation systems, we describe in detail two software architectures for GHMM-based gene finders, one comprising the common array-based approach, and the other a highly optimized algorithm which requires significantly less memory while achieving virtually identical speed. We then show how both of these architectures can be accelerated by a factor of two by optimizing their content sensors. We finish with a brief illustration of the impact these optimizations have had on the feasibility of our new homology-based gene finder, TWAIN. CONCLUSIONS: In describing a number of optimizations for GHMM-based gene finders and making available two complete open-source software systems embodying these methods, it is our hope that others will be more enabled to explore promising extensions to the GHMM framework, thereby improving the state-of-the-art in gene prediction techniques.

Algorithms↗
PubMed2005

The genome of the basidiomycetous yeast and human pathogen Cryptococcus neoformans.

Cryptococcus neoformans is a basidiomycetous yeast ubiquitous in the environment, a model for fungal pathogenesis, and an opportunistic human pathogen of global importance. We have sequenced its approximately 20-megabase genome, which contains approximately 6500 intron-rich gene structures and encodes a transcriptome abundant in alternatively spliced and antisense messages. The genome is rich in transposons, many of which cluster at candidate centromeric regions. The presence of these transposons may drive karyotype instability and phenotypic variation. C. neoformans encodes unique genes that may contribute to its unusual virulence properties, and comparison of two phenotypically distinct strains reveals variation in gene content in addition to sequence polymorphisms between the genomes.

Alternative Splicing↗
PubMed2004

Insight into the genome of Aspergillus fumigatus: analysis of a 922 kb region encompassing the nitrate assimilation gene cluster.

Aspergillus fumigatus is the most ubiquitous opportunistic filamentous fungal pathogen of human. As an initial step toward sequencing the entire genome of A. fumigatus, which is estimated to be approximately 30 Mb in size, we have sequenced a 922 kb region, contained within 16 overlapping bacterial artificial chromosome (BAC) clones. Fifty-four percent of the DNA is predicted to be coding with 341 putative protein coding genes. Functional classification of the proteins showed the presence of a higher proportion of enzymes and membrane transporters when compared to those of Saccharomyces cerevisiae. In addition to the nitrate assimilation gene cluster, the quinate utilisation gene cluster is also present on this 922 kb genomic sequence. We observed large scale synteny between A. fumigatus and Aspergillus nidulans by comparing this sequence to the A. nidulans genetic map of linkage group VIII.

Aspergillus fumigatus↗
PubMed2004

Computational gene prediction using multiple sources of evidence.

This article describes a computational method to construct gene models by using evidence generated from a diverse set of sources, including those typical of a genome annotation pipeline. The program, called Combiner, takes as input a genomic sequence and the locations of gene predictions from ab initio gene finders, protein sequence alignments, expressed sequence tag and cDNA alignments, splice site predictions, and other evidence. Three different algorithms for combining evidence in the Combiner were implemented and tested on 1783 confirmed genes in Arabidopsis thaliana. Our results show that combining gene prediction evidence consistently outperforms even the best individual gene finder and, in some cases, can produce dramatic improvements in sensitivity and specificity.

Arabidopsis↗
PubMed2003

GlimmerM, Exonomy and Unveil: three ab initio eukaryotic genefinders.

We present three programs for ab initio gene prediction in eukaryotes: Exonomy, Unveil and GlimmerM. Exonomy is a 23-state Generalized Hidden Markov Model (GHMM), Unveil is a 283-state standard Hidden Markov Model (HMM) and GlimmerM is a previously-described genefinder which utilizes decision trees and Interpolated Markov Models (IMMs). All three are readily re-trainable for new organisms and have been found to perform well compared to other genefinders. Results are presented for Arabidopsis thaliana. Cases have been found where each of the genefinders outperforms each of the others, demonstrating the collective value of this ensemble of genefinders. These programs are all accessible through webservers at http://www.tigr.org/software.

Arabidopsis↗
PubMed2002

Sequence of Plasmodium falciparum chromosomes 2, 10, 11 and 14.

The mosquito-borne malaria parasite Plasmodium falciparum kills an estimated 0.7-2.7 million people every year, primarily children in sub-Saharan Africa. Without effective interventions, a variety of factors-including the spread of parasites resistant to antimalarial drugs and the increasing insecticide resistance of mosquitoes-may cause the number of malaria cases to double over the next two decades. To stimulate basic research and facilitate the development of new drugs and vaccines, the genome of Plasmodium falciparum clone 3D7 has been sequenced using a chromosome-by-chromosome shotgun strategy. We report here the nucleotide sequences of chromosomes 10, 11 and 14, and a re-analysis of the chromosome 2 sequence. These chromosomes represent about 35% of the 23-megabase P. falciparum genome.

Animals↗
PubMed2002

Genome sequence of the human malaria parasite Plasmodium falciparum.

The parasite Plasmodium falciparum is responsible for hundreds of millions of cases of malaria, and kills more than one million African children annually. Here we report an analysis of the genome sequence of P. falciparum clone 3D7. The 23-megabase nuclear genome consists of 14 chromosomes, encodes about 5,300 genes, and is the most (A + T)-rich genome sequenced to date. Genes involved in antigenic variation are concentrated in the subtelomeric regions of the chromosomes. Compared to the genomes of free-living eukaryotic microbes, the genome of this intracellular parasite encodes fewer enzymes and transporters, but a large proportion of genes are devoted to immune evasion and host-parasite interactions. Many nuclear-encoded proteins are targeted to the apicoplast, an organelle involved in fatty-acid and isoprenoid metabolism. The genome sequence provides the foundation for future studies of this organism, and is being exploited in the search for new drugs and vaccines to fight malaria.

Animals↗
PubMed2002

Genome sequence and comparative analysis of the model rodent malaria parasite Plasmodium yoelii yoelii.

Species of malaria parasite that infect rodents have long been used as models for malaria disease research. Here we report the whole-genome shotgun sequence of one species, Plasmodium yoelii yoelii, and comparative studies with the genome of the human malaria parasite Plasmodium falciparum clone 3D7. A synteny map of 2,212 P. y. yoelii contiguous DNA sequences (contigs) aligned to 14 P. falciparum chromosomes reveals marked conservation of gene synteny within the body of each chromosome. Of about 5,300 P. falciparum genes, more than 3,300 P. y. yoelii orthologues of predominantly metabolic function were identified. Over 800 copies of a variant antigen gene located in subtelomeric regions were found. This is the first genome sequence of a model eukaryotic parasite, and it provides insight into the use of such systems in the modelling of Plasmodium biology and disease.

Animals↗
PubMed2002

Computational gene finding in plants.

Automated methods for identifying protein coding regions in genomic DNA have progressed significantly in recent years, but there is still a strong need for more accurate computational solutions to the gene finding problem. Large-scale genome sequencing projects depend greatly on gene finding to generate accurate and complete gene annotation. Improvements in gene finding software are being driven by the development of better computational algorithms, a better understanding of the cell's mechanisms for transcription and translation, and the enormous increases in genomic sequence data. This paper reviews some of the most widely used algorithms for gene finding in plants, including technical descriptions of how they work and recent measurements of their success on the genomes of Arabidopsis thaliana and rice.

Algorithms↗