An algorithm for annotation and classification of T. cruzi MASP sequences: towards a better understanding of the parasite genetic variability
Background Trypanosoma cruzi , the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MAS...
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| Published in | BMC genomics Vol. 26; no. 1; pp. 194 - 17 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
BioMed Central
24.02.2025
BioMed Central Ltd Springer Nature B.V BMC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1471-2164 1471-2164 |
| DOI | 10.1186/s12864-025-11384-5 |
Cover
| Abstract | Background
Trypanosoma cruzi
, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MASP), which are essential for parasite transmission and disease mechanisms. However, methodological challenges in genome assembly and annotation have limited the characterization of these gene families, particularly MASPs.
Results
We developed a bioinformatic pipeline for the automatic identification, characterization, and annotation of MASPs directly from
T. cruzi
genome assemblies. This algorithm, based on a manually curated MASP database and HMM-based identification of MASP diagnostic motifs, enables the robust classification of these molecules into canonical MASPs, MASP-related molecules (mostly pseudogenes), and chimeric sequences combining MASPs and TcMUC/TS genes. Validation against a rigorously annotated dataset demonstrated high accuracy, and allowed us to reclassify misanotated sequences and, more crucially, to accurately identify previously unrecognized canonical MASPs and MASP chimeras. This algorithm was then used to explore the MASP repertoire in the genomes of 13 parasite strains from different evolutionary lineages, revealing patterns of diversity. For instance, TcI and TcII strains exhibited higher ratios of canonical MASP/MASP-related molecules and a greater abundance of MASP chimeras, suggesting that their genomes are under strong selective pressures towards maintaining a broader panel of full-length MASP genes at the expense of pseudogenes. On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes.
Conclusions
This novel pipeline automates the annotation of MASPs, a key surface protein family unique to
T. cruzi
, improving genome annotation and enabling robust comparative analyses. It provides an essential tool for exploring the evolutionary dynamics of multigene families in
T. cruzi
and could be extended to other gene families. |
|---|---|
| AbstractList | Trypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MASP), which are essential for parasite transmission and disease mechanisms. However, methodological challenges in genome assembly and annotation have limited the characterization of these gene families, particularly MASPs. We developed a bioinformatic pipeline for the automatic identification, characterization, and annotation of MASPs directly from T. cruzi genome assemblies. This algorithm, based on a manually curated MASP database and HMM-based identification of MASP diagnostic motifs, enables the robust classification of these molecules into canonical MASPs, MASP-related molecules (mostly pseudogenes), and chimeric sequences combining MASPs and TcMUC/TS genes. Validation against a rigorously annotated dataset demonstrated high accuracy, and allowed us to reclassify misanotated sequences and, more crucially, to accurately identify previously unrecognized canonical MASPs and MASP chimeras. This algorithm was then used to explore the MASP repertoire in the genomes of 13 parasite strains from different evolutionary lineages, revealing patterns of diversity. For instance, TcI and TcII strains exhibited higher ratios of canonical MASP/MASP-related molecules and a greater abundance of MASP chimeras, suggesting that their genomes are under strong selective pressures towards maintaining a broader panel of full-length MASP genes at the expense of pseudogenes. On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes. This novel pipeline automates the annotation of MASPs, a key surface protein family unique to T. cruzi, improving genome annotation and enabling robust comparative analyses. It provides an essential tool for exploring the evolutionary dynamics of multigene families in T. cruzi and could be extended to other gene families. Trypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MASP), which are essential for parasite transmission and disease mechanisms. However, methodological challenges in genome assembly and annotation have limited the characterization of these gene families, particularly MASPs. We developed a bioinformatic pipeline for the automatic identification, characterization, and annotation of MASPs directly from T. cruzi genome assemblies. This algorithm, based on a manually curated MASP database and HMM-based identification of MASP diagnostic motifs, enables the robust classification of these molecules into canonical MASPs, MASP-related molecules (mostly pseudogenes), and chimeric sequences combining MASPs and TcMUC/TS genes. Validation against a rigorously annotated dataset demonstrated high accuracy, and allowed us to reclassify misanotated sequences and, more crucially, to accurately identify previously unrecognized canonical MASPs and MASP chimeras. This algorithm was then used to explore the MASP repertoire in the genomes of 13 parasite strains from different evolutionary lineages, revealing patterns of diversity. For instance, TcI and TcII strains exhibited higher ratios of canonical MASP/MASP-related molecules and a greater abundance of MASP chimeras, suggesting that their genomes are under strong selective pressures towards maintaining a broader panel of full-length MASP genes at the expense of pseudogenes. On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes. This novel pipeline automates the annotation of MASPs, a key surface protein family unique to T. cruzi, improving genome annotation and enabling robust comparative analyses. It provides an essential tool for exploring the evolutionary dynamics of multigene families in T. cruzi and could be extended to other gene families. Trypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MASP), which are essential for parasite transmission and disease mechanisms. However, methodological challenges in genome assembly and annotation have limited the characterization of these gene families, particularly MASPs.BACKGROUNDTrypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MASP), which are essential for parasite transmission and disease mechanisms. However, methodological challenges in genome assembly and annotation have limited the characterization of these gene families, particularly MASPs.We developed a bioinformatic pipeline for the automatic identification, characterization, and annotation of MASPs directly from T. cruzi genome assemblies. This algorithm, based on a manually curated MASP database and HMM-based identification of MASP diagnostic motifs, enables the robust classification of these molecules into canonical MASPs, MASP-related molecules (mostly pseudogenes), and chimeric sequences combining MASPs and TcMUC/TS genes. Validation against a rigorously annotated dataset demonstrated high accuracy, and allowed us to reclassify misanotated sequences and, more crucially, to accurately identify previously unrecognized canonical MASPs and MASP chimeras. This algorithm was then used to explore the MASP repertoire in the genomes of 13 parasite strains from different evolutionary lineages, revealing patterns of diversity. For instance, TcI and TcII strains exhibited higher ratios of canonical MASP/MASP-related molecules and a greater abundance of MASP chimeras, suggesting that their genomes are under strong selective pressures towards maintaining a broader panel of full-length MASP genes at the expense of pseudogenes. On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes.RESULTSWe developed a bioinformatic pipeline for the automatic identification, characterization, and annotation of MASPs directly from T. cruzi genome assemblies. This algorithm, based on a manually curated MASP database and HMM-based identification of MASP diagnostic motifs, enables the robust classification of these molecules into canonical MASPs, MASP-related molecules (mostly pseudogenes), and chimeric sequences combining MASPs and TcMUC/TS genes. Validation against a rigorously annotated dataset demonstrated high accuracy, and allowed us to reclassify misanotated sequences and, more crucially, to accurately identify previously unrecognized canonical MASPs and MASP chimeras. This algorithm was then used to explore the MASP repertoire in the genomes of 13 parasite strains from different evolutionary lineages, revealing patterns of diversity. For instance, TcI and TcII strains exhibited higher ratios of canonical MASP/MASP-related molecules and a greater abundance of MASP chimeras, suggesting that their genomes are under strong selective pressures towards maintaining a broader panel of full-length MASP genes at the expense of pseudogenes. On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes.This novel pipeline automates the annotation of MASPs, a key surface protein family unique to T. cruzi, improving genome annotation and enabling robust comparative analyses. It provides an essential tool for exploring the evolutionary dynamics of multigene families in T. cruzi and could be extended to other gene families.CONCLUSIONSThis novel pipeline automates the annotation of MASPs, a key surface protein family unique to T. cruzi, improving genome annotation and enabling robust comparative analyses. It provides an essential tool for exploring the evolutionary dynamics of multigene families in T. cruzi and could be extended to other gene families. Background Trypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MASP), which are essential for parasite transmission and disease mechanisms. However, methodological challenges in genome assembly and annotation have limited the characterization of these gene families, particularly MASPs. Results We developed a bioinformatic pipeline for the automatic identification, characterization, and annotation of MASPs directly from T. cruzi genome assemblies. This algorithm, based on a manually curated MASP database and HMM-based identification of MASP diagnostic motifs, enables the robust classification of these molecules into canonical MASPs, MASP-related molecules (mostly pseudogenes), and chimeric sequences combining MASPs and TcMUC/TS genes. Validation against a rigorously annotated dataset demonstrated high accuracy, and allowed us to reclassify misanotated sequences and, more crucially, to accurately identify previously unrecognized canonical MASPs and MASP chimeras. This algorithm was then used to explore the MASP repertoire in the genomes of 13 parasite strains from different evolutionary lineages, revealing patterns of diversity. For instance, TcI and TcII strains exhibited higher ratios of canonical MASP/MASP-related molecules and a greater abundance of MASP chimeras, suggesting that their genomes are under strong selective pressures towards maintaining a broader panel of full-length MASP genes at the expense of pseudogenes. On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes. Conclusions This novel pipeline automates the annotation of MASPs, a key surface protein family unique to T. cruzi, improving genome annotation and enabling robust comparative analyses. It provides an essential tool for exploring the evolutionary dynamics of multigene families in T. cruzi and could be extended to other gene families. Keywords: Trypanosoma cruzi, Mucin-associated surface proteins (MASP), Hidden Markov Models (HMM), Molecular signatures, Genome annotation Background Trypanosoma cruzi , the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MASP), which are essential for parasite transmission and disease mechanisms. However, methodological challenges in genome assembly and annotation have limited the characterization of these gene families, particularly MASPs. Results We developed a bioinformatic pipeline for the automatic identification, characterization, and annotation of MASPs directly from T. cruzi genome assemblies. This algorithm, based on a manually curated MASP database and HMM-based identification of MASP diagnostic motifs, enables the robust classification of these molecules into canonical MASPs, MASP-related molecules (mostly pseudogenes), and chimeric sequences combining MASPs and TcMUC/TS genes. Validation against a rigorously annotated dataset demonstrated high accuracy, and allowed us to reclassify misanotated sequences and, more crucially, to accurately identify previously unrecognized canonical MASPs and MASP chimeras. This algorithm was then used to explore the MASP repertoire in the genomes of 13 parasite strains from different evolutionary lineages, revealing patterns of diversity. For instance, TcI and TcII strains exhibited higher ratios of canonical MASP/MASP-related molecules and a greater abundance of MASP chimeras, suggesting that their genomes are under strong selective pressures towards maintaining a broader panel of full-length MASP genes at the expense of pseudogenes. On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes. Conclusions This novel pipeline automates the annotation of MASPs, a key surface protein family unique to T. cruzi , improving genome annotation and enabling robust comparative analyses. It provides an essential tool for exploring the evolutionary dynamics of multigene families in T. cruzi and could be extended to other gene families. BackgroundTrypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MASP), which are essential for parasite transmission and disease mechanisms. However, methodological challenges in genome assembly and annotation have limited the characterization of these gene families, particularly MASPs.ResultsWe developed a bioinformatic pipeline for the automatic identification, characterization, and annotation of MASPs directly from T. cruzi genome assemblies. This algorithm, based on a manually curated MASP database and HMM-based identification of MASP diagnostic motifs, enables the robust classification of these molecules into canonical MASPs, MASP-related molecules (mostly pseudogenes), and chimeric sequences combining MASPs and TcMUC/TS genes. Validation against a rigorously annotated dataset demonstrated high accuracy, and allowed us to reclassify misanotated sequences and, more crucially, to accurately identify previously unrecognized canonical MASPs and MASP chimeras. This algorithm was then used to explore the MASP repertoire in the genomes of 13 parasite strains from different evolutionary lineages, revealing patterns of diversity. For instance, TcI and TcII strains exhibited higher ratios of canonical MASP/MASP-related molecules and a greater abundance of MASP chimeras, suggesting that their genomes are under strong selective pressures towards maintaining a broader panel of full-length MASP genes at the expense of pseudogenes. On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes.ConclusionsThis novel pipeline automates the annotation of MASPs, a key surface protein family unique to T. cruzi, improving genome annotation and enabling robust comparative analyses. It provides an essential tool for exploring the evolutionary dynamics of multigene families in T. cruzi and could be extended to other gene families. Abstract Background Trypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome contains rapidly evolving multigene families, such as mucins (TcMUC), trans-sialidases (TS), and mucin-associated surface proteins (MASP), which are essential for parasite transmission and disease mechanisms. However, methodological challenges in genome assembly and annotation have limited the characterization of these gene families, particularly MASPs. Results We developed a bioinformatic pipeline for the automatic identification, characterization, and annotation of MASPs directly from T. cruzi genome assemblies. This algorithm, based on a manually curated MASP database and HMM-based identification of MASP diagnostic motifs, enables the robust classification of these molecules into canonical MASPs, MASP-related molecules (mostly pseudogenes), and chimeric sequences combining MASPs and TcMUC/TS genes. Validation against a rigorously annotated dataset demonstrated high accuracy, and allowed us to reclassify misanotated sequences and, more crucially, to accurately identify previously unrecognized canonical MASPs and MASP chimeras. This algorithm was then used to explore the MASP repertoire in the genomes of 13 parasite strains from different evolutionary lineages, revealing patterns of diversity. For instance, TcI and TcII strains exhibited higher ratios of canonical MASP/MASP-related molecules and a greater abundance of MASP chimeras, suggesting that their genomes are under strong selective pressures towards maintaining a broader panel of full-length MASP genes at the expense of pseudogenes. On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes. Conclusions This novel pipeline automates the annotation of MASPs, a key surface protein family unique to T. cruzi, improving genome annotation and enabling robust comparative analyses. It provides an essential tool for exploring the evolutionary dynamics of multigene families in T. cruzi and could be extended to other gene families. |
| ArticleNumber | 194 |
| Audience | Academic |
| Author | Balouz, Virginia Dean, Aldana Alexandra Cepeda Buscaglia, Carlos Andrés Berná, Luisa Robello, Carlos |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39994548$$D View this record in MEDLINE/PubMed |
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| Keywords | Genome annotation Mucin-associated surface proteins (MASP) Hidden Markov Models (HMM) Molecular signatures Trypanosoma cruzi |
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| Snippet | Background
Trypanosoma cruzi
, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its... Trypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its genome... Background Trypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its... BackgroundTrypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin America. Its... Abstract Background Trypanosoma cruzi, the protozoan causing Chagas disease, is responsible for a neglected tropical disease affecting millions in Latin... |
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| SubjectTerms | Algorithms Analysis Animal Genetics and Genomics Annotations Anopheles Biomedical and Life Sciences Care and treatment Chagas disease Chimeras Classification Comparative analysis Computational Biology - methods Diagnosis Disease transmission DNA sequencing Gene families Genes Genetic aspects Genetic variability Genetic Variation Genome annotation Genome, Protozoan Genomes Genomics Glycoproteins Hidden Markov Models (HMM) Life Sciences Mannose-binding protein-associated serine proteinase Markov processes Membrane Proteins - genetics Microarrays Microbial Genetics and Genomics Molecular Sequence Annotation Molecular signatures Mucin Mucin-associated surface proteins (MASP) Mucins Mucins - genetics Multigene Family Neuraminidase Nucleotide sequencing Omics of Parasites 2 Parasites Phylogeny Plant Genetics and Genomics Proteins Proteomics Protozoa Protozoan Proteins - chemistry Protozoan Proteins - classification Protozoan Proteins - genetics Pseudogenes Robustness Trypanosoma cruzi Trypanosoma cruzi - classification Trypanosoma cruzi - genetics Vector-borne diseases Virulence (Microbiology) |
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| Title | An algorithm for annotation and classification of T. cruzi MASP sequences: towards a better understanding of the parasite genetic variability |
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