Gene expression and nucleotide composition are associated with genic methylation level in Oryza sativa

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

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.

An investigation of codon usage pattern analysis in pancreatitis associated genes

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.

Why Do Some Vertebrates Have Microchromosomes?

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.

Comprehensive analysis of coding sequence architecture features and gene expression in Arachis duranensis

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.

Prediction of Rice Transcription Start Sites Using TransPrise: A Novel Machine Learning Approach

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.

TransPrise: a novel machine learning approach for eukaryotic promoter prediction

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.

Insights into soybean transcriptome reconfiguration under hypoxic stress: Functional, regulatory, structural, and compositional characterization

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.

Nucleotide patterns aiding in prediction of eukaryotic promoters

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.

Evidence-based gene models for structural and functional annotations of the oil palm genome

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.

Evolution of Brain Active Gene Promoters in Human Lineage Towards the Increased Plasticity of Gene Regulation

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.

Nucleotide diversity analysis highlights functionally important genomic regions

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.

The mysterious orphans of Mycoplasmataceae

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.

Gene Evolutionary Trajectories and GC Patterns Driven by Recombination in Zea mays

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 GC_x) to instances of a variable GC-rich motif that underlies double strand break (DSB) hotspots and to meiocyte-specific gene expression. Surprisingly, GC_x bimodality in maize cannot be fully explained by the codon wobble hypothesis. High GC_x 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 GC_x 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 GC_x genes.