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Jiao L, Jing Z, Zhang W, Su X, Yan H, Tian S. Codon Pattern and Context Analysis in Genes Triggering Alzheimer's Disease and Latent Tau Protein Aggregation Post-Anesthesia Exhibited Unique Molecular Patterns Associated with Functional Aspects. J Alzheimers Dis 2024; 97:1645-1660. [PMID: 38306048 DOI: 10.3233/jad-231142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
Background Previous reports have demonstrated post-operative dementia and Alzheimer's disease (AD), and increased amyloid-β levels and tau hyperphosphorylation have been observed in animal models post-anesthesia. Objective After surgical interventions, loss in memory has been observed that has been found linked with genes modulated after anesthesia. Present study aimed to study molecular pattern present in genes modulated post anesthesia and involved in characters progressing towards AD. Methods In the present study, 17 transcript variants belonging to eight genes, which have been found to modulate post-anesthesia and contribute to AD progression, were envisaged for their compositional features, molecular patterns, and codon and codon context-associated studies. Results The sequences' composition was G/C rich, influencing dinucleotide preference, codon preference, codon usage, and codon context. The G/C nucleotides being highly occurring nucleotides, CpGdinucleotides were also preferred; however, CpG was highly disfavored at p3-1 at the codon junction. The nucleotide composition of Cytosine exhibited a unique feature, and unlike other nucleotides, it did not correlate with codon bias. Contrarily, it correlated with the sequence lengths. The sequences were leucine-rich, and multiple leucine repeats were present, exhibiting the functional role of neuroprotection from neuroinflammation post-anesthesia. Conclusions The analysis pave the way to elucidate unique molecular patterns in genes modulated during anesthetic treatment and might help ameliorate the ill effects of anesthetics in the future.
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Affiliation(s)
- Liyuan Jiao
- Department of Anesthesiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Ziye Jing
- Department of Anesthesiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Wenjie Zhang
- Department of Anesthesiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xuesen Su
- Department of Anesthesiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Hualei Yan
- Department of Anesthesiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Shouyuan Tian
- Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Taiyuan, China
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2
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Li Y, Khandia R, Papadakis M, Alexiou A, Simonov AN, Khan AA. An investigation of codon usage pattern analysis in pancreatitis associated genes. BMC Genom Data 2022; 23:81. [PMID: 36434531 PMCID: PMC9700901 DOI: 10.1186/s12863-022-01089-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 10/10/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Pancreatitis is an inflammatory disorder resulting from the autoactivation of trypsinogen in the pancreas. The genetic basis of the disease is an old phenomenon, and evidence is accumulating for the involvement of synonymous/non-synonymous codon variants in disease initiation and progression. RESULTS The present study envisaged a panel of 26 genes involved in pancreatitis for their codon choices, compositional analysis, relative dinucleotide frequency, nucleotide disproportion, protein physical properties, gene expression, codon bias, and interrelated of all these factors. In this set of genes, gene length was positively correlated with nucleotide skews and codon usage bias. Codon usage of any gene is dependent upon its AT and GC component; however, AGG, CGT, and CGA encoding for Arg, TCG for Ser, GTC for Val, and CCA for Pro were independent of nucleotide compositions. In addition, Codon GTC showed a correlation with protein properties, isoelectric point, instability index, and frequency of basic amino acids. We also investigated the effect of various evolutionary forces in shaping the codon usage choices of genes. CONCLUSIONS This study will enable us to gain insight into the molecular signatures associated with the disease that might help identify more potential genes contributing to enhanced risk for pancreatitis. All the genes associated with pancreatitis are generally associated with physiological function, and mutations causing loss of function, over or under expression leads to an ailment. Therefore, the present study attempts to envisage the molecular signature in a group of genes that lead to pancreatitis in case of malfunction.
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Affiliation(s)
- Yuanyang Li
- Third-Grade Pharmacological Laboratory On Chinese Medicine Approved By State Administration of Traditional Chinese Medicine, Medical College of China Three Gorges, Yichang, China ,grid.254148.e0000 0001 0033 6389College of Medical Science, China Three Gorges University, Yichang, China
| | - Rekha Khandia
- grid.411530.20000 0001 0694 3745Department of Biochemistry and Genetics, Barkatullah University, Bhopal, MP 462026 India
| | - Marios Papadakis
- grid.412581.b0000 0000 9024 6397Department of Surgery II, University Hospital Witten-Herdecke, University of Witten-Herdecke, Heusnerstrasse 40, 42283 Wuppertal, Germany
| | - Athanasios Alexiou
- Department of Science and Engineering, Novel Global Community Educational Foundation, Hebersham, Australia ,AFNP Med Austria, Vienna, Austria
| | | | - Azmat Ali Khan
- grid.56302.320000 0004 1773 5396Pharmaceutical Biotechnology Laboratory, Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, 11451 Saudi Arabia
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3
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Srikulnath K, Ahmad SF, Singchat W, Panthum T. Why Do Some Vertebrates Have Microchromosomes? Cells 2021; 10:2182. [PMID: 34571831 PMCID: PMC8466491 DOI: 10.3390/cells10092182] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/17/2021] [Accepted: 08/17/2021] [Indexed: 12/27/2022] Open
Abstract
With more than 70,000 living species, vertebrates have a huge impact on the field of biology and research, including karyotype evolution. One prominent aspect of many vertebrate karyotypes is the enigmatic occurrence of tiny and often cytogenetically indistinguishable microchromosomes, which possess distinctive features compared to macrochromosomes. Why certain vertebrate species carry these microchromosomes in some lineages while others do not, and how they evolve remain open questions. New studies have shown that microchromosomes exhibit certain unique characteristics of genome structure and organization, such as high gene densities, low heterochromatin levels, and high rates of recombination. Our review focuses on recent concepts to expand current knowledge on the dynamic nature of karyotype evolution in vertebrates, raising important questions regarding the evolutionary origins and ramifications of microchromosomes. We introduce the basic karyotypic features to clarify the size, shape, and morphology of macro- and microchromosomes and report their distribution across different lineages. Finally, we characterize the mechanisms of different evolutionary forces underlying the origin and evolution of microchromosomes.
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Affiliation(s)
- Kornsorn Srikulnath
- Animal Genomics and Bioresource Research Center (AGB Research Center), Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand; (S.F.A.); (W.S.); (T.P.)
- Laboratory of Animal Cytogenetics and Comparative Genomics (ACCG), Department of Genetics, Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
- The International Undergraduate Program in Bioscience and Technology, Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
- Special Research Unit for Wildlife Genomics (SRUWG), Department of Forest Biology, Faculty of Forestry, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
- Amphibian Research Center, Hiroshima University, 1-3-1, Kagamiyama, Higashihiroshima 739-8526, Japan
| | - Syed Farhan Ahmad
- Animal Genomics and Bioresource Research Center (AGB Research Center), Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand; (S.F.A.); (W.S.); (T.P.)
- Laboratory of Animal Cytogenetics and Comparative Genomics (ACCG), Department of Genetics, Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
- The International Undergraduate Program in Bioscience and Technology, Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
- Special Research Unit for Wildlife Genomics (SRUWG), Department of Forest Biology, Faculty of Forestry, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
| | - Worapong Singchat
- Animal Genomics and Bioresource Research Center (AGB Research Center), Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand; (S.F.A.); (W.S.); (T.P.)
- Laboratory of Animal Cytogenetics and Comparative Genomics (ACCG), Department of Genetics, Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
- Special Research Unit for Wildlife Genomics (SRUWG), Department of Forest Biology, Faculty of Forestry, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
| | - Thitipong Panthum
- Animal Genomics and Bioresource Research Center (AGB Research Center), Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand; (S.F.A.); (W.S.); (T.P.)
- Laboratory of Animal Cytogenetics and Comparative Genomics (ACCG), Department of Genetics, Faculty of Science, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
- Special Research Unit for Wildlife Genomics (SRUWG), Department of Forest Biology, Faculty of Forestry, Kasetsart University, 50 Ngamwongwan, Chatuchak, Bangkok 10900, Thailand
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Dong S, Zhang L, Pang W, Zhang Y, Wang C, Li Z, Ma L, Tang W, Yang G, Song H. Comprehensive analysis of coding sequence architecture features and gene expression in Arachis duranensis. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2021; 27:213-222. [PMID: 33707864 PMCID: PMC7907404 DOI: 10.1007/s12298-021-00938-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 01/04/2021] [Accepted: 01/20/2021] [Indexed: 06/09/2023]
Abstract
Coding sequence (CDS) architecture affects gene expression levels in organisms. Codon optimization can increase the gene expression level. Therefore, understanding codon usage patterns has important implications for research on genetic engineering and exogenous gene expression. To date, the codon usage patterns of many model plants have been analyzed. However, the relationship between CDS architecture and gene expression in Arachis duranensis remains poorly understood. According to the results of genome sequencing, A. duranensis has many resistant genes that can be used to improve the cultivated peanut. In this study, bioinformatic approaches were used to estimate A. duranensis CDS architectures, including frequency of the optimal codon (Fop), polypeptide length and GC contents at the first (GC1), second (GC2) and third (GC3) codon positions. In addition, Arachis RNA-seq datasets were downloaded from PeanutBase. The relationships between gene expression and CDS architecture were assessed both under normal growth as well as nematode and drought stress conditions. A total of 26 codons with high frequency were identified, which preferentially ended with A or T in A. duranensis CDSs under the above-mentioned three conditions. A similar CDS architecture was found in differentially expressed genes (DEGs) under nematode and drought stresses. The GC1 content differed between DEGs and non-differentially expressed genes (NDEGs) under both drought and nematode stresses. The expression levels of DEGs were affected by different CDS architectures compared with NDEGs under drought stress. In addition, no correlation was found between differential gene expression and CDS architecture neither under nematode nor under drought stress. These results aid the understanding of gene expression in A. duranensis.
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Affiliation(s)
- Shuwei Dong
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Long Zhang
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Wenhui Pang
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Yongli Zhang
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Chang Wang
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Zhenyi Li
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Lichao Ma
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Wei Tang
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Guofeng Yang
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
| | - Hui Song
- Grassland Agri-Husbandry Research Center, College of Grassland Science, Qingdao Agricultural University, Qingdao, China
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Pachganov S, Murtazalieva K, Zarubin A, Taran T, Chartier D, Tatarinova TV. Prediction of Rice Transcription Start Sites Using TransPrise: A Novel Machine Learning Approach. Methods Mol Biol 2021; 2238:261-274. [PMID: 33471337 DOI: 10.1007/978-1-0716-1068-8_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
As the interest in genetic resequencing increases, so does the need for effective mathematical, computational, and statistical approaches. One of the difficult problems in genome annotation is determination of precise positions of transcription start sites. In this paper, we present TransPrise-an efficient deep learning tool for predicting positions of eukaryotic transcription start sites. TransPrise offers significant improvement over existing promoter-prediction methods. To illustrate this, we compared predictions of TransPrise with the TSSPlant approach for well-annotated genome of Oryza sativa. Using a computer with a graphics processing unit, the run time of TransPrise is 250 min on a genome of 374 Mb long.We provide the full basis for the comparison and encourage users to freely access a set of our computational tools to facilitate and streamline their own analyses. The ready-to-use Docker image with all the necessary packages, models, and code as well as the source code of the TransPrise algorithm are available at http://compubioverne.group/ . The source code is ready to use and to be customized to predict TSS in any eukaryotic organism.
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Affiliation(s)
- Stepan Pachganov
- Ugra Research Institute of Information Technologies, Khanty-Mansiysk, Russia
| | | | - Alexei Zarubin
- Tomsk National Research Medical Center of the Russian Academy of Sciences, Research Institute of Medical Genetics, Tomsk, Russia
| | | | - Duane Chartier
- International Center for Art Intelligence, Inc, Los Angeles, CA, USA
| | - Tatiana V Tatarinova
- Vavilov Institute of General Genetics, Moscow, Russia.
- Department of Biology, University of La Verne, La Verne, CA, USA.
- A.A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia.
- Siberian Federal University, Krasnoyarsk, Russia.
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6
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Pachganov S, Murtazalieva K, Zarubin A, Sokolov D, Chartier DR, Tatarinova TV. TransPrise: a novel machine learning approach for eukaryotic promoter prediction. PeerJ 2019; 7:e7990. [PMID: 31695967 PMCID: PMC6827441 DOI: 10.7717/peerj.7990] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 10/04/2019] [Indexed: 02/01/2023] Open
Abstract
As interest in genetic resequencing increases, so does the need for effective mathematical, computational, and statistical approaches. One of the difficult problems in genome annotation is determination of precise positions of transcription start sites. In this paper we present TransPrise-an efficient deep learning tool for prediction of positions of eukaryotic transcription start sites. Our pipeline consists of two parts: the binary classifier operates the first, and if a sequence is classified as TSS-containing the regression step follows, where the precise location of TSS is being identified. TransPrise offers significant improvement over existing promoter-prediction methods. To illustrate this, we compared predictions of TransPrise classification and regression models with the TSSPlant approach for the well annotated genome of Oryza sativa. Using a computer equipped with a graphics processing unit, the run time of TransPrise is 250 minutes on a genome of 374 Mb long. The Matthews correlation coefficient value for TransPrise is 0.79, more than two times larger than the 0.31 for TSSPlant classification models. This represents a high level of prediction accuracy. Additionally, the mean absolute error for the regression model is 29.19 nt, allowing for accurate prediction of TSS location. TransPrise was also tested in Homo sapiens, where mean absolute error of the regression model was 47.986 nt. We provide the full basis for the comparison and encourage users to freely access a set of our computational tools to facilitate and streamline their own analyses. The ready-to-use Docker image with all necessary packages, models, code as well as the source code of the TransPrise algorithm are available at (http://compubioverne.group/). The source code is ready to use and customizable to predict TSS in any eukaryotic organism.
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Affiliation(s)
- Stepan Pachganov
- Ugra Research Institute of Information Technologies, Khanty-Mansiysk, Russia
| | - Khalimat Murtazalieva
- Vavilov Institute for General Genetics, Moscow, Russia.,Institute of Bioinformatics, Moscow, Russia
| | - Aleksei Zarubin
- Tomsk National Research Medical Center of the Russian Academy of Sciences, Research Institute of Medical Genetics, Tomsk, Russia
| | | | - Duane R Chartier
- International Center for Art Intelligence, Inc., Los Angeles, CA, United States of America
| | - Tatiana V Tatarinova
- Vavilov Institute for General Genetics, Moscow, Russia.,Department of Biology, University of La Verne, La Verne, CA, United States of America.,A.A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia.,Siberian Federal University, Krasnoyarsk, Russia
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7
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Nakayama TJ, Rodrigues FA, Neumaier N, Marcolino-Gomes J, Molinari HBC, Santiago TR, Formighieri EF, Basso MF, Farias JRB, Emygdio BM, de Oliveira ACB, Campos ÂD, Borém A, Harmon FG, Mertz-Henning LM, Nepomuceno AL. Insights into soybean transcriptome reconfiguration under hypoxic stress: Functional, regulatory, structural, and compositional characterization. PLoS One 2017; 12:e0187920. [PMID: 29145496 PMCID: PMC5690659 DOI: 10.1371/journal.pone.0187920] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 10/27/2017] [Indexed: 11/19/2022] Open
Abstract
Soybean (Glycine max) is one of the major crops worldwide and flooding stress affects the production and expansion of cultivated areas. Oxygen is essential for mitochondrial aerobic respiration to supply the energy demand of plant cells. Because oxygen diffusion in water is 10,000 times lower than in air, partial (hypoxic) or total (anoxic) oxygen deficiency is important component of flooding. Even when oxygen is externally available, oxygen deficiency frequently occurs in bulky, dense or metabolically active tissues such as phloem, meristems, seeds, and fruits. In this study, we analyzed conserved and divergent root transcriptional responses between flood-tolerant Embrapa 45 and flood-sensitive BR 4 soybean cultivars under hypoxic stress conditions with RNA-seq. To understand how soybean genes evolve and respond to hypoxia, stable and differentially expressed genes were characterized structurally and compositionally comparing its mechanistic relationship. Between cultivars, Embrapa 45 showed less up- and more down-regulated genes, and stronger induction of phosphoglucomutase (Glyma05g34790), unknown protein related to N-terminal protein myristoylation (Glyma06g03430), protein suppressor of phyA-105 (Glyma06g37080), and fibrillin (Glyma10g32620). RNA-seq and qRT-PCR analysis of non-symbiotic hemoglobin (Glyma11g12980) indicated divergence in gene structure between cultivars. Transcriptional changes for genes in amino acids and derivative metabolic process suggest involvement of amino acids metabolism in tRNA modifications, translation accuracy/efficiency, and endoplasmic reticulum stress in both cultivars under hypoxia. Gene groups differed in promoter TATA box, ABREs (ABA-responsive elements), and CRT/DREs (C-repeat/dehydration-responsive elements) frequency. Gene groups also differed in structure, composition, and codon usage, indicating biological significances. Additional data suggests that cis-acting ABRE elements can mediate gene expression independent of ABA in soybean roots under hypoxia.
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Affiliation(s)
- Thiago J. Nakayama
- Departamento de Fitotecnia, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | - Fabiana A. Rodrigues
- Embrapa Soja, Empresa Brasileira de Pesquisa Agropecuária, Londrina, Paraná, Brazil
| | - Norman Neumaier
- Embrapa Soja, Empresa Brasileira de Pesquisa Agropecuária, Londrina, Paraná, Brazil
| | | | - Hugo B. C. Molinari
- Embrapa Agroenergia, Empresa Brasileira de Pesquisa Agropecuária, Brasília, Distrito Federal, Brazil
| | - Thaís R. Santiago
- Embrapa Agroenergia, Empresa Brasileira de Pesquisa Agropecuária, Brasília, Distrito Federal, Brazil
| | - Eduardo F. Formighieri
- Embrapa Agroenergia, Empresa Brasileira de Pesquisa Agropecuária, Brasília, Distrito Federal, Brazil
| | - Marcos F. Basso
- Embrapa Agroenergia, Empresa Brasileira de Pesquisa Agropecuária, Brasília, Distrito Federal, Brazil
| | - José R. B. Farias
- Embrapa Soja, Empresa Brasileira de Pesquisa Agropecuária, Londrina, Paraná, Brazil
| | - Beatriz M. Emygdio
- Embrapa Clima Temperado, Empresa Brasileira de Pesquisa Agropecuária, Pelotas, Rio Grande do Sul, Brazil
| | - Ana C. B. de Oliveira
- Embrapa Clima Temperado, Empresa Brasileira de Pesquisa Agropecuária, Pelotas, Rio Grande do Sul, Brazil
| | - Ângela D. Campos
- Embrapa Clima Temperado, Empresa Brasileira de Pesquisa Agropecuária, Pelotas, Rio Grande do Sul, Brazil
| | - Aluízio Borém
- Departamento de Fitotecnia, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil
| | - Frank G. Harmon
- Department of Plant and Microbial Biology, University of California-Berkeley, Berkeley, California, United States of America
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Triska M, Solovyev V, Baranova A, Kel A, Tatarinova TV. Nucleotide patterns aiding in prediction of eukaryotic promoters. PLoS One 2017; 12:e0187243. [PMID: 29141011 PMCID: PMC5687710 DOI: 10.1371/journal.pone.0187243] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2017] [Accepted: 09/05/2017] [Indexed: 01/09/2023] Open
Abstract
Computational analysis of promoters is hindered by the complexity of their architecture. In less studied genomes with complex organization, false positive promoter predictions are common. Accurate identification of transcription start sites and core promoter regions remains an unsolved problem. In this paper, we present a comprehensive analysis of genomic features associated with promoters and show that probabilistic integrative algorithms-driven models allow accurate classification of DNA sequence into “promoters” and “non-promoters” even in absence of the full-length cDNA sequences. These models may be built upon the maps of the distributions of sequence polymorphisms, RNA sequencing reads on genomic DNA, methylated nucleotides, transcription factor binding sites, as well as relative frequencies of nucleotides and their combinations. Positional clustering of binding sites shows that the cells of Oryza sativa utilize three distinct classes of transcription factors: those that bind preferentially to the [-500,0] region (188 “promoter-specific” transcription factors), those that bind preferentially to the [0,500] region (282 “5′ UTR-specific” TFs), and 207 of the “promiscuous” transcription factors with little or no location preference with respect to TSS. For the most informative motifs, their positional preferences are conserved between dicots and monocots.
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Affiliation(s)
- Martin Triska
- Children’s Hospital Los Angeles, University of Southern California, Los Angeles, CA, United States of America
- Faculty of Advanced Technology, University of South Wales, Pontypridd, Wales, United Kingdom
| | | | - Ancha Baranova
- School of Systems Biology, George Mason University, Fairfax, VA, United States of America
- Research Centre for Medical Genetics, Moscow, Russia
| | - Alexander Kel
- geneXplain GmbH, Wolfenbuettel, Germany
- Institute of Chemical Biology and Fundamental Medicine, Novosibirsk, Russia
| | - Tatiana V. Tatarinova
- School of Systems Biology, George Mason University, Fairfax, VA, United States of America
- Department of Biology, Division of Natural Sciences, University of La Verne, La Verne, CA, United States of America
- Bioinformatics Center, AA Kharkevich Institute for Information Transmission Problems RAS, Moscow, Russia
- Vavilov’s Institute for General Genetics, Moscow, Russia, Moscow, Russia
- * E-mail:
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9
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Chan KL, Tatarinova TV, Rosli R, Amiruddin N, Azizi N, Halim MAA, Sanusi NSNM, Jayanthi N, Ponomarenko P, Triska M, Solovyev V, Firdaus-Raih M, Sambanthamurthi R, Murphy D, Low ETL. Evidence-based gene models for structural and functional annotations of the oil palm genome. Biol Direct 2017; 12:21. [PMID: 28886750 PMCID: PMC5591544 DOI: 10.1186/s13062-017-0191-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Accepted: 08/07/2017] [Indexed: 11/13/2022] Open
Abstract
Background Oil palm is an important source of edible oil. The importance of the crop, as well as its long breeding cycle (10-12 years) has led to the sequencing of its genome in 2013 to pave the way for genomics-guided breeding. Nevertheless, the first set of gene predictions, although useful, had many fragmented genes. Classification and characterization of genes associated with traits of interest, such as those for fatty acid biosynthesis and disease resistance, were also limited. Lipid-, especially fatty acid (FA)-related genes are of particular interest for the oil palm as they specify oil yields and quality. This paper presents the characterization of the oil palm genome using different gene prediction methods and comparative genomics analysis, identification of FA biosynthesis and disease resistance genes, and the development of an annotation database and bioinformatics tools. Results Using two independent gene-prediction pipelines, Fgenesh++ and Seqping, 26,059 oil palm genes with transcriptome and RefSeq support were identified from the oil palm genome. These coding regions of the genome have a characteristic broad distribution of GC3 (fraction of cytosine and guanine in the third position of a codon) with over half the GC3-rich genes (GC3 ≥ 0.75286) being intronless. In comparison, only one-seventh of the oil palm genes identified are intronless. Using comparative genomics analysis, characterization of conserved domains and active sites, and expression analysis, 42 key genes involved in FA biosynthesis in oil palm were identified. For three of them, namely EgFABF, EgFABH and EgFAD3, segmental duplication events were detected. Our analysis also identified 210 candidate resistance genes in six classes, grouped by their protein domain structures. Conclusions We present an accurate and comprehensive annotation of the oil palm genome, focusing on analysis of important categories of genes (GC3-rich and intronless), as well as those associated with important functions, such as FA biosynthesis and disease resistance. The study demonstrated the advantages of having an integrated approach to gene prediction and developed a computational framework for combining multiple genome annotations. These results, available in the oil palm annotation database (http://palmxplore.mpob.gov.my), will provide important resources for studies on the genomes of oil palm and related crops. Reviewers This article was reviewed by Alexander Kel, Igor Rogozin, and Vladimir A. Kuznetsov. Electronic supplementary material The online version of this article (doi:10.1186/s13062-017-0191-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Kuang-Lim Chan
- Advanced Biotechnology and Breeding Centre, Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia.,Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia
| | - Tatiana V Tatarinova
- Department of Biology, University of La Verne, La Verne, California, 91750, USA.,Spatial Sciences Institute, University of Southern California, Los Angeles, CA, 90089, USA
| | - Rozana Rosli
- Advanced Biotechnology and Breeding Centre, Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia.,Genomics and Computational Biology Research Group, University of South Wales, Pontypridd, CF371DL, UK
| | - Nadzirah Amiruddin
- Advanced Biotechnology and Breeding Centre, Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia
| | - Norazah Azizi
- Advanced Biotechnology and Breeding Centre, Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia
| | - Mohd Amin Ab Halim
- Advanced Biotechnology and Breeding Centre, Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia
| | - Nik Shazana Nik Mohd Sanusi
- Advanced Biotechnology and Breeding Centre, Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia
| | - Nagappan Jayanthi
- Advanced Biotechnology and Breeding Centre, Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia
| | - Petr Ponomarenko
- Spatial Sciences Institute, University of Southern California, Los Angeles, CA, 90089, USA
| | - Martin Triska
- Children's Hospital Los Angeles, University of Southern California, Los Angeles, CA, 90089, USA
| | - Victor Solovyev
- Softberry Inc., 116 Radio Circle, Suite 400, Mount Kisco, NY, 10549, USA
| | - Mohd Firdaus-Raih
- Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia
| | - Ravigadevi Sambanthamurthi
- Advanced Biotechnology and Breeding Centre, Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia
| | - Denis Murphy
- Genomics and Computational Biology Research Group, University of South Wales, Pontypridd, CF371DL, UK
| | - Eng-Ti Leslie Low
- Advanced Biotechnology and Breeding Centre, Malaysian Palm Oil Board, No. 6, Persiaran Institusi, Bandar Baru Bangi, 43000 Kajang, Selangor, Malaysia.
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10
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Evolution of Brain Active Gene Promoters in Human Lineage Towards the Increased Plasticity of Gene Regulation. Mol Neurobiol 2017; 55:1871-1904. [PMID: 28233272 DOI: 10.1007/s12035-017-0427-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Accepted: 01/26/2017] [Indexed: 01/31/2023]
Abstract
Adaptability to a variety of environmental conditions is a prominent feature of Homo sapiens. We hypothesize that this feature can be explained by evolutionary changes in gene promoters active in the brain prefrontal cortex leading to a more flexible gene regulation network. The genotype-dependent range of gene expression can be broader in humans than in other higher primates. Thus, we searched for specific signatures of evolutionary changes in promoter architectures of multiple hominid genes, including the genes active in human cortical neurons that may indicate an increase of variability of gene expression rather than just changes in the level of expression, such as downregulation or upregulation of the genes. We performed a whole-genome search for genetic-based alterations that may impact gene regulation "flexibility" in a process of hominids evolution, such as (i) CpG dinucleotide content, (ii) predicted nucleosome-DNA dissociation constant, and (iii) predicted affinities for TATA-binding protein (TBP) in gene promoters. We tested all putative promoter regions across the human genome and especially gene promoters in active chromatin state in neurons of prefrontal cortex, the brain region critical for abstract thinking and social and behavioral adaptation. Our data imply that the origin of modern man has been associated with an increase of flexibility of promoter-driven gene regulation in brain. In contrast, after splitting from the ancestral lineages of H. sapiens, the evolution of ape species is characterized by reduced flexibility of gene promoter functioning, underlying reduced variability of the gene expression.
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11
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Tatarinova TV, Chekalin E, Nikolsky Y, Bruskin S, Chebotarov D, McNally KL, Alexandrov N. Nucleotide diversity analysis highlights functionally important genomic regions. Sci Rep 2016; 6:35730. [PMID: 27774999 PMCID: PMC5075931 DOI: 10.1038/srep35730] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Accepted: 09/30/2016] [Indexed: 12/15/2022] Open
Abstract
We analyzed functionality and relative distribution of genetic variants across the complete Oryza sativa genome, using the 40 million single nucleotide polymorphisms (SNPs) dataset from the 3,000 Rice Genomes Project (http://snp-seek.irri.org), the largest and highest density SNP collection for any higher plant. We have shown that the DNA-binding transcription factors (TFs) are the most conserved group of genes, whereas kinases and membrane-localized transporters are the most variable ones. TFs may be conserved because they belong to some of the most connected regulatory hubs that modulate transcription of vast downstream gene networks, whereas signaling kinases and transporters need to adapt rapidly to changing environmental conditions. In general, the observed profound patterns of nucleotide variability reveal functionally important genomic regions. As expected, nucleotide diversity is much higher in intergenic regions than within gene bodies (regions spanning gene models), and protein-coding sequences are more conserved than untranslated gene regions. We have observed a sharp decline in nucleotide diversity that begins at about 250 nucleotides upstream of the transcription start and reaches minimal diversity exactly at the transcription start. We found the transcription termination sites to have remarkably symmetrical patterns of SNP density, implying presence of functional sites near transcription termination. Also, nucleotide diversity was significantly lower near 3′ UTRs, the area rich with regulatory regions.
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Affiliation(s)
- Tatiana V Tatarinova
- Center for Personalized Medicine and Spatial Sciences Institute, University of Southern California, Los Angeles, CA, USA.,Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russian Federation
| | | | - Yuri Nikolsky
- Vavilov Institute of General Genetics, Moscow, Russia.,F1 Genomics, San Diego, CA, USA.,School of Systems Biology, George Mason University, VA, USA
| | | | - Dmitry Chebotarov
- International Rice Research Institute, Los Baños, Laguna 4031, Philippines
| | - Kenneth L McNally
- International Rice Research Institute, Los Baños, Laguna 4031, Philippines
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12
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Tatarinova TV, Lysnyansky I, Nikolsky YV, Bolshoy A. The mysterious orphans of Mycoplasmataceae. Biol Direct 2016; 11:2. [PMID: 26747447 PMCID: PMC4706650 DOI: 10.1186/s13062-015-0104-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2015] [Accepted: 12/30/2015] [Indexed: 01/08/2023] Open
Abstract
Background The length of a protein sequence is largely determined by its function. In certain species, it may be also affected by additional factors, such as growth temperature or acidity. In 2002, it was shown that in the bacterium Escherichia coli and in the archaeon Archaeoglobus fulgidus, protein sequences with no homologs were, on average, shorter than those with homologs (BMC Evol Biol 2:20, 2002). It is now generally accepted that in bacterial and archaeal genomes the distributions of protein length are different between sequences with and without homologs. In this study, we examine this postulate by conducting a comprehensive analysis of all annotated prokaryotic genomes and by focusing on certain exceptions. Results We compared the distribution of lengths of “having homologs proteins” (HHPs) and “non-having homologs proteins” (orphans or ORFans) in all currently completely sequenced and COG-annotated prokaryotic genomes. As expected, the HHPs and ORFans have strikingly different length distributions in almost all genomes. As previously established, the HHPs, indeed are, on average, longer than the ORFans, and the length distributions for the ORFans have a relatively narrow peak, in contrast to the HHPs, whose lengths spread over a wider range of values. However, about thirty genomes do not obey these rules. Practically all genomes of Mycoplasma and Ureaplasma have atypical ORFans distributions, with the mean lengths of ORFan larger than the mean lengths of HHPs. These genera constitute over 80 % of atypical genomes. Conclusions We confirmed on a ubiquitous set of genomes that the previous observation of HHPs and ORFans have different gene length distributions. We also showed that Mycoplasmataceae genomes have very distinctive distributions of ORFans lengths. We offer several possible biological explanations of this phenomenon, such as an adaptation to Mycoplasmataceae’s ecological niche, specifically its “quiet” co-existence with host organisms, resulting in long ABC transporters. Electronic supplementary material The online version of this article (doi:10.1186/s13062-015-0104-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Tatiana V Tatarinova
- Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, 90027, CA, USA. .,Spatial Sciences Institute, University of Southern California, Los Angeles, 90089, CA, USA.
| | - Inna Lysnyansky
- Mycoplasma Unit, Division of Avian and Aquatic Diseases, Kimron Veterinary Institute, POB 12, Beit Dagan, 50250, Israel.
| | - Yuri V Nikolsky
- School of Systems Biology, George Mason University, 10900 University Blvd, MSN 5B3, Manassas, VA, 20110, USA. .,Prosapia Genetics, LLC, 534 San Andres Dr., Solana Beach, CA, 92075, USA. .,Vavilov Institute of General Genetics, Moscow, Russian Federation.
| | - Alexander Bolshoy
- Department of Evolutionary and Environmental Biology and Institute of Evolution, University of Haifa, Haifa, Israel.
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13
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Sundararajan A, Dukowic-Schulze S, Kwicklis M, Engstrom K, Garcia N, Oviedo OJ, Ramaraj T, Gonzales MD, He Y, Wang M, Sun Q, Pillardy J, Kianian SF, Pawlowski WP, Chen C, Mudge J. Gene Evolutionary Trajectories and GC Patterns Driven by Recombination in Zea mays. FRONTIERS IN PLANT SCIENCE 2016; 7:1433. [PMID: 27713757 PMCID: PMC5031598 DOI: 10.3389/fpls.2016.01433] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 09/08/2016] [Indexed: 05/20/2023]
Abstract
Recombination occurring during meiosis is critical for creating genetic variation and plays an essential role in plant evolution. In addition to creating novel gene combinations, recombination can affect genome structure through altering GC patterns. In maize (Zea mays) and other grasses, another intriguing GC pattern exists. Maize genes show a bimodal GC content distribution that has been attributed to nucleotide bias in the third, or wobble, position of the codon. Recombination may be an underlying driving force given that recombination sites are often associated with high GC content. Here we explore the relationship between recombination and genomic GC patterns by comparing GC gene content at each of the three codon positions (GC1, GC2, and GC3, collectively termed GCx) to instances of a variable GC-rich motif that underlies double strand break (DSB) hotspots and to meiocyte-specific gene expression. Surprisingly, GCx bimodality in maize cannot be fully explained by the codon wobble hypothesis. High GCx genes show a strong overlap with the DSB hotspot motif, possibly providing a mechanism for the high evolutionary rates seen in these genes. On the other hand, genes that are turned on in meiosis (early prophase I) are biased against both high GCx genes and genes with the DSB hotspot motif, possibly allowing important meiotic genes to avoid DSBs. Our data suggests a strong link between the GC-rich motif underlying DSB hotspots and high GCx genes.
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Affiliation(s)
| | | | | | | | - Nathan Garcia
- National Center for Genome Resources, Santa FeNM, USA
| | | | | | | | - Yan He
- Section of Plant Biology, School of Integrative Plant Science, Cornell University, IthacaNY, USA
| | - Minghui Wang
- Section of Plant Biology, School of Integrative Plant Science, Cornell University, IthacaNY, USA
- Biotechnology Resource Center Bioinformatics Facility, Cornell University, IthacaNY, USA
| | - Qi Sun
- Biotechnology Resource Center Bioinformatics Facility, Cornell University, IthacaNY, USA
| | - Jaroslaw Pillardy
- Biotechnology Resource Center Bioinformatics Facility, Cornell University, IthacaNY, USA
| | - Shahryar F. Kianian
- Cereal Disease Laboratory, United States Department of Agriculture – Agricultural Research Service, St. PaulMN, USA
| | - Wojciech P. Pawlowski
- Section of Plant Biology, School of Integrative Plant Science, Cornell University, IthacaNY, USA
| | - Changbin Chen
- Department of Horticultural Science, University of Minnesota, St. PaulMN, USA
| | - Joann Mudge
- National Center for Genome Resources, Santa FeNM, USA
- *Correspondence: Joann Mudge,
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