Temporal progress of gene expression analysis with RNA-Seq data: A review on the relationship between computational methods.

Analysis of differential gene expression from RNA-seq data has become a standard for several research areas. The steps for the computational analysis include many data types and file formats, and a wide variety of computational tools that can be applied alone or together as pipelines. This paper presents a review of the differential expression analysis pipeline, addressing its steps and the respective objectives, the principal methods available in each step, and their properties, therefore introducing an organized overview to this context. This review aims to address mainly the aspects involved in the differentially expressed gene (DEG) analysis from RNA sequencing data (RNA-seq), considering the computational methods. In addition, a timeline of the computational methods for DEG is shown and discussed, and the relationships existing between the most important computational tools are presented by an interaction network. A discussion on the challenges and gaps in DEG analysis is also highlighted in this review. This paper will serve as a tutorial for new entrants into the field and help established users update their analysis pipelines.

Comparative analyses of Theobroma cacao and T. grandiflorum mitogenomes reveal conserved gene content embedded within complex and plastic structures.

Unlike the chloroplast genomes (ptDNA), the plant mitochondrial genomes (mtDNA) are much more plastic in structure and size but maintain a conserved and essential gene set related to oxidative phosphorylation. Moreover, the plant mitochondrial genes and mtDNA are good markers for phylogenetic, evolutive, and comparative analyses. The two most known species in Theobroma L. (Malvaceae s.l.) genus are T. cacao, and T. grandiflorum. Besides the economic value, both species also show considerable biotechnology potential due to their other derived products, thus, aggregating additional economic value for the agroindustry. Here, we assembled and compared the mtDNA of Theobroma cacao and T. grandiflorum to generate a new genomics resource and unravel evolutionary trends. Graph-based analyses revealed that both mtDNA exhibit multiple alternative arrangements, confirming the dynamism commonly observed in plant mtDNA. The disentangled assembly graph revealed potential predominant circular molecules. The master circle molecules span 543,794 bp for T. cacao and 501,598 bp for T. grandiflorum, showing 98.9% of average sequence identity. Both mtDNA contains the same set of 39 plant mitochondrial genes, commonly found in other rosid mitogenomes. The main features are a duplicated copy of atp4, the absence of rpl6, rps2, rps8, and rps11, and the presence of two chimeric open-reading frames. Moreover, we detected few ptDNA integrations mainly represented by tRNAs, and no viral sequences were detected. Phylogenomics analyses indicate Theobroma spp. are nested in Malvaceae family. The main mtDNA differences are related to distinct structural rearrangements and exclusive regions associated with relics of Transposable Elements, supporting the hypothesis of dynamic mitochondrial genome maintenance and divergent evolutionary paths and pressures after species differentiation.

Physiological and Molecular Responses of Woody Plants Exposed to Future Atmospheric CO2 Levels under Abiotic Stresses.

Climate change is mainly driven by the accumulation of carbon dioxide (CO2) in the atmosphere in the last century. Plant growth is constantly challenged by environmental fluctuations including heat waves, severe drought and salinity, along with ozone accumulation in the atmosphere. Food security is at risk in an increasing world population, and it is necessary to face the current and the expected effects of global warming. The effects of the predicted environment scenario of elevated CO2 concentration (e[CO2]) and more severe abiotic stresses have been scarcely investigated in woody plants, and an integrated view involving physiological, biochemical and molecular data is missing. This review highlights the effects of elevated CO2 in the metabolism of woody plants and the main findings of its interaction with abiotic stresses, including a molecular point of view, aiming to improve the understanding of how woody plants will face the predicted environmental conditions. Overall, e[CO2] stimulates photosynthesis and growth and attenuates mild to moderate abiotic stress in woody plants if root growth and nutrients are not limited. Moreover, e[CO2] does not induce acclimation in most tree species. Some high-throughput analyses involving omics techniques were conducted to better understand how these processes are regulated. Finally, knowledge gaps in the understanding of how the predicted climate condition will affect woody plant metabolism were identified, with the aim of improving the growth and production of this plant species.

A Bioinformatics Tool for Efficient Retrieval of High-Confidence Terpene Synthases (TPS) and Application to the Identification of TPS in Coffea and Quillaja.

Terpenoids are a class of compounds that are found in all living organisms. In plants, some terpenoids are part of primary metabolism, but most terpenes found in plants are classified as specialized metabolites, encoded by terpene synthases (TPS). It is not obvious how to assign the putative product of a given TPS using bioinformatics tools. Phylogenetic analyses easily assign TPS into families; however members of the same TPS family can synthetize more than one terpenoid-and, in many biotechnological applications, researchers are more interested in the product of a given TPS rather than its phylogenetic profile. Automated protein annotation can be used to classify TPS based on their products, despite the family they belong to. Here, we implement an automated bioinformatics method, search_TPS, to identify TPS proteins that synthesize mono, sesqui and diterpenes in Angiosperms. We verified the applicability of the method by classifying wet lab validated TPS and applying it to find TPS proteins in Coffea arabica, C. canephora, C. eugenioides, and Quillaja saponaria. Search_TPS is a computational tool based on PERL scripts that carries out a series of HMMER searches against a curated database of TPS profile hidden Markov models. The tool is freely available at https://github.com/liliane-sntn/TPS .

MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical descriptors.

One of the main challenges in applying machine learning algorithms to biological sequence data is how to numerically represent a sequence in a numeric input vector. Feature extraction techniques capable of extracting numerical information from biological sequences have been reported in the literature. However, many of these techniques are not available in existing packages, such as mathematical descriptors. This paper presents a new package, MathFeature, which implements mathematical descriptors able to extract relevant numerical information from biological sequences, i.e. DNA, RNA and proteins (prediction of structural features along the primary sequence of amino acids). MathFeature makes available 20 numerical feature extraction descriptors based on approaches found in the literature, e.g. multiple numeric mappings, genomic signal processing, chaos game theory, entropy and complex networks. MathFeature also allows the extraction of alternative features, complementing the existing packages. To ensure that our descriptors are robust and to assess their relevance, experimental results are presented in nine case studies. According to these results, the features extracted by MathFeature showed high performance (0.6350-0.9897, accuracy), both applying only mathematical descriptors, but also hybridization with well-known descriptors in the literature. Finally, through MathFeature, we overcame several studies in eight benchmark datasets, exemplifying the robustness and viability of the proposed package. MathFeature has advanced in the area by bringing descriptors not available in other packages, as well as allowing non-experts to use feature extraction techniques.

Feature extraction approaches for biological sequences: a comparative study of mathematical features.

As consequence of the various genomic sequencing projects, an increasing volume of biological sequence data is being produced. Although machine learning algorithms have been successfully applied to a large number of genomic sequence-related problems, the results are largely affected by the type and number of features extracted. This effect has motivated new algorithms and pipeline proposals, mainly involving feature extraction problems, in which extracting significant discriminatory information from a biological set is challenging. Considering this, our work proposes a new study of feature extraction approaches based on mathematical features (numerical mapping with Fourier, entropy and complex networks). As a case study, we analyze long non-coding RNA sequences. Moreover, we separated this work into three studies. First, we assessed our proposal with the most addressed problem in our review, e.g. lncRNA and mRNA; second, we also validate the mathematical features in different classification problems, to predict the class of lncRNA, e.g. circular RNAs sequences; third, we analyze its robustness in scenarios with imbalanced data. The experimental results demonstrated three main contributions: first, an in-depth study of several mathematical features; second, a new feature extraction pipeline; and third, its high performance and robustness for distinct RNA sequence classification. Availability:https://github.com/Bonidia/FeatureExtraction_BiologicalSequences.

Genome-Wide Screening and Characterization of Non-Coding RNAs in Coffea canephora.

Coffea canephora grains are highly traded commodities worldwide. Non-coding RNAs (ncRNAs) are transcriptional products involved in genome regulation, environmental responses, and plant development. There is not an extensive genome-wide analysis that uncovers the ncRNA portion of the C. canephora genome. This study aimed to provide a curated characterization of six ncRNA classes in the Coffea canephora genome. For this purpose, we employed a combination of similarity-based and structural-based computational approaches with stringent curation. Candidate ncRNA loci had expression evidence analyzed using sRNA-seq libraries. We identified 7455 ncRNA loci (6976 with transcriptional evidence) in the C. canephora genome. This comprised of total 115 snRNAs, 1031 snoRNAs, 92 miRNA precursors, 602 tRNAs, 72 rRNAs, and 5064 lncRNAs. For miRNAs, we identified 159 putative high-confidence targets. This study was the most extensive genomic catalog of curated ncRNAs in the Coffea genus. This data might help elaborating more robust hypotheses in future comparative genomic studies as well as gene regulation and genome dynamics, helping to understand the molecular basis of domestication, environmental adaptation, resistance to pests and diseases, and coffee productivity.

Transcriptional patterns of Coffea arabica L. nitrate reductase, glutamine and asparagine synthetase genes are modulated under nitrogen suppression and coffee leaf rust.

This study evaluated the transcriptional profile of genes related to nitrogen (N) assimilation in coffee plants susceptible and resistant to rust fungi under N sufficiency and N suppression. For this purpose, we inoculated young coffee leaves with Hemileia vastatrix uredospores and collected them at 0, 12, 24 and 48 hours post-inoculation (HPI) to evaluate the relative expressions of genes encoding cytosolic glutamine synthetase (CaGS1 ), plastid glutamine synthetase (CaGS2 ), nitrate reductase (CaNR), and asparagine synthetase (CaAS). The genes exhibited distinct patterns of transcriptional modulation for the different genotypes and N nutritional regimes. The resistant genotype (I59) presented high levels of transcription in response to pathogen inoculation for CaNR and CaGS1 genes, evaluated under N sufficiency in the initial moments of infection (12 HPI). The gene CaGS1 also showed a peak at 48 HPI. The susceptible genotype (CV99) showed increased transcript rates of CaNR at 12 and 24 HPI in response to rust inoculation. The transcriptional patterns observed for CV99, under N suppression, were high levels for CaAS and CaGS2 at all post-inoculation times in response to coffee leaf rust disease. In addition, CaGS1 was up-regulated at 48 HPI for CV99. Cultivar I59 showed high transcript levels at 12 HPI for CaAS and peaks at 24 and 48 HPI for CaGS2 in inoculated samples. Consequently, total chlorophyl concentration was influenced by N suppression and by rust infection. Regarding enzyme activities in vitro for glutamine synthetase and CaNR, there was an increase in infected coffee leaves (I59) and under N sufficiency. Moreover, CV99 was modulated in both N nutritional regimes for GS activity in response to rust. Our results indicate that N transport genes trigger a differential modulation between genotypes through the action of rust disease.

Low root PIP1-1 and PIP2 aquaporins expression could be related to reduced hydration in 'Rangpur' lime plants exposed to aluminium.

In acidic soils, aluminium (Al) occurs as Al3+, which is phytotoxic. One of the most conspicuous symptoms of Al toxicity is the root growth inhibition, which can lead to low water uptake and consequent reduction in leaf hydration and gas exchange. However, fibrous xylem vessels have been observed in roots of 'Rangpur' lime plants (Citrus limonia L.) when exposed to Al, which could affect the functioning of aquaporins, ultimately reducing their expression. We confirmed a decrease of CO2 assimilation (A), stomatal conductance (gs), transpiration (E) and relative leaf water content (RWC) in 3-month-old C. limonia plants exposed to 1480 µM Al in nutrient solution for 90 days. The estimated hydraulic conductivity from soil to the leaf (KL) and leaf water potential (Ψw) also showed low values, although not consistently reduced over time of Al exposure. The relative expression of aquaporin genes belonging to PIP family (PIP1-1, PIP1-2 and PIP2) showed downregulation for ClPIP1-1 and ClPIP2 and upregulation for ClPIP1-2 in plants exposed to Al. Furthermore, ClPIP1-1 was positively correlated with A and gs in plants exposed to Al. Therefore, downregulation of ClPIP1-1 and ClPIP2 in roots of 'Rangpur' lime plants could be associated with the low leaf hydration of this species when exposed to Al.

The Terrestrial Carnivorous Plant Utricularia reniformis Sheds Light on Environmental and Life-Form Genome Plasticity.

Utricularia belongs to Lentibulariaceae, a widespread family of carnivorous plants that possess ultra-small and highly dynamic nuclear genomes. It has been shown that the Lentibulariaceae genomes have been shaped by transposable elements expansion and loss, and multiple rounds of whole-genome duplications (WGD), making the family a platform for evolutionary and comparative genomics studies. To explore the evolution of Utricularia, we estimated the chromosome number and genome size, as well as sequenced the terrestrial bladderwort Utricularia reniformis (2n = 40, 1C = 317.1-Mpb). Here, we report a high quality 304 Mb draft genome, with a scaffold NG50 of 466-Kb, a BUSCO completeness of 87.8%, and 42,582 predicted genes. Compared to the smaller and aquatic U. gibba genome (101 Mb) that has a 32% repetitive sequence, the U. reniformis genome is highly repetitive (56%). The structural differences between the two genomes are the result of distinct fractionation and rearrangements after WGD, and massive proliferation of LTR-retrotransposons. Moreover, GO enrichment analyses suggest an ongoing gene birth-death-innovation process occurring among the tandem duplicated genes, shaping the evolution of carnivory-associated functions. We also identified unique patterns of developmentally related genes that support the terrestrial life-form and body plan of U. reniformis. Collectively, our results provided additional insights into the evolution of the plastic and specialized Lentibulariaceae genomes.

An integrated analysis of mRNA and sRNA transcriptional profiles in Coffea arabica L. roots: insights on nitrogen starvation responses.

Coffea arabica L. is an important agricultural commodity, accounting for 60% of traded coffee worldwide. Nitrogen (N) is a macronutrient that is usually limiting to plant yield; however, molecular mechanisms of plant acclimation to N limitation remain largely unknown in tropical woody crops. In this study, we investigated the transcriptome of coffee roots under N starvation, analyzing poly-A+ libraries and small RNAs. We also evaluated the concentration of selected amino acids and N-source preferences in roots. Ammonium was preferentially taken up over nitrate, and asparagine and glutamate were the most abundant amino acids observed in coffee roots. We obtained 34,654 assembled contigs by mRNA sequencing, and validated the transcriptional profile of 12 genes by RT-qPCR. Illumina small RNA sequencing yielded 8,524,332 non-redundant reads, resulting in the identification of 86 microRNA families targeting 253 genes. The transcriptional pattern of eight miRNA families was also validated. To our knowledge, this is the first catalog of differentially regulated amino acids, N sources, mRNAs, and sRNAs in Arabica coffee roots.

An integrated analysis of mRNA and sRNA transcriptional profiles in Coffea arabica L. roots: insights on nitrogen starvation responses

Coffea arabica L. is an important agricultural commodity, accounting for 60% of traded coffee worldwide. Nitrogen (N) is a macronutrient that is usually limiting to plant yield; however, molecular mechanisms of plant acclimation to N limitation remain largely unknown in tropical woody crops. In this study, we investigated the transcriptome of coffee roots under N starvation, analyzing poly-A+ libraries and small RNAs. We also evaluated the concentration of selected amino acids and N-source preferences in roots. Ammonium was preferentially taken up over nitrate, and asparagine and glutamate were the most abundant amino acids observed in coffee roots. We obtained 34,654 assembled contigs by mRNA sequencing, and validated the transcriptional profile of 12 genes by RT-qPCR. Illumina small RNA sequencing yielded 8,524,332 non-redundant reads, resulting in the identification of 86 microRNA families targeting 253 genes. The transcriptional pattern of eight miRNA families was also validated. To our knowledge, this is the first catalog of differentially regulated amino acids, N sources, mRNAs, and sRNAs in Arabica coffee roots.

An integrated analysis of mRNA and sRNA transcriptional profiles in Coffea arabica L. roots: insights on nitrogen starvation responses

Coffea arabica L. is an important agricultural commodity, accounting for 60% of traded coffee worldwide. Nitrogen (N) is a macronutrient that is usually limiting to plant yield; however, molecular mechanisms of plant acclimation to N limitation remain largely unknown in tropical woody crops. In this study, we investigated the transcriptome of coffee roots under N starvation, analyzing poly-A+ libraries and small RNAs. We also evaluated the concentration of selected amino acids and N-source preferences in roots. Ammonium was preferentially taken up over nitrate, and asparagine and glutamate were the most abundant amino acids observed in coffee roots. We obtained 34,654 assembled contigs by mRNA sequencing, and validated the transcriptional profile of 12 genes by RT-qPCR. Illumina small RNA sequencing yielded 8,524,332 non-redundant reads, resulting in the identification of 86 microRNA families targeting 253 genes. The transcriptional pattern of eight miRNA families was also validated. To our knowledge, this is the first catalog of differentially regulated amino acids, N sources, mRNAs, and sRNAs in Arabica coffee roots.

Genome-wide association study reveals candidate genes influencing lipids and diterpenes contents in Coffea arabica L.

Lipids, including the diterpenes cafestol and kahweol, are key compounds that contribute to the quality of coffee beverages. We determined total lipid content and cafestol and kahweol concentrations in green beans and genotyped 107 Coffea arabica accessions, including wild genotypes from the historical FAO collection from Ethiopia. A genome-wide association study was performed to identify genomic regions associated with lipid, cafestol and kahweol contents and cafestol/kahweol ratio. Using the diploid Coffea canephora genome as a reference, we identified 6,696 SNPs. Population structure analyses suggested the presence of two to three groups (K = 2 and K = 3) corresponding to the east and west sides of the Great Rift Valley and an additional group formed by wild accessions collected in western forests. We identified 5 SNPs associated with lipid content, 4 with cafestol, 3 with kahweol and 9 with cafestol/kahweol ratio. Most of these SNPs are located inside or near candidate genes related to metabolic pathways of these chemical compounds in coffee beans. In addition, three trait-associated SNPs showed evidence of directional selection among cultivated and wild coffee accessions. Our results also confirm a great allelic richness in wild accessions from Ethiopia, especially in accessions originating from forests in the west side of the Great Rift Valley.

Diterpenes biochemical profile and transcriptional analysis of cytochrome P450s genes in leaves, roots, flowers, and during Coffea arabica L. fruit development.

Lipids are among the major chemical compounds present in coffee beans, and they affect the flavor and aroma of the coffee beverage. Coffee oil is rich in kaurene diterpene compounds, mainly cafestol (CAF) and kahweol (KAH), which are related to plant defense mechanisms and to nutraceutical and sensorial beverage characteristics. Despite their importance, the final steps of coffee diterpenes biosynthesis remain unknown. To understand the molecular basis of coffee diterpenes biosynthesis, we report the content dynamics of CAF and KAH in several Coffea arabica tissues and the transcriptional analysis of cytochrome P450 genes (P450). We measured CAF and KAH concentrations in leaves, roots, flower buds, flowers and fruit tissues at seven developmental stages (30-240 days after flowering - DAF) using HPLC. Higher CAF levels were detected in flower buds and flowers when compared to fruits. In contrast, KAH concentration increased along fruit development, peaking at 120 DAF. We did not detect CAF or KAH in leaves, and higher amounts of KAH than CAF were detected in roots. Using P450 candidate genes from a coffee EST database, we performed RT-qPCR transcriptional analysis of leaves, flowers and fruits at three developmental stages (90, 120 and 150 DAF). Three P450 genes (CaCYP76C4, CaCYP82C2 and CaCYP74A1) had transcriptional patterns similar to CAF concentration and two P450 genes (CaCYP71A25 and CaCYP701A3) have transcript accumulation similar to KAH concentration. These data warrant further investigation of these P450s as potential candidate genes involved in the final stages of the CAF and KAH biosynthetic pathways.

PlanTE-MIR DB: a database for transposable element-related microRNAs in plant genomes.

Transposable elements (TEs) comprise a major fraction of many plant genomes and are known to drive their organization and evolution. Several studies show that these repetitive elements have a prominent role in shaping noncoding regions of the genome such as microRNA (miRNA) loci, which are components of post-transcriptional regulation mechanisms. Although some studies have reported initial formation of miRNA loci from TE sequences, especially in model plants, the approaches that were used did not employ systems that would allow results to be delivered by a user-friendly database. In this study, we identified 152 precursor miRNAs overlapping TEs in 10 plant species. PlanTE-MIR DB was designed to assemble this data and deliver it to the scientific community interested in miRNA origin, evolution, and regulation pathways. Users can browse the database through a web interface and search for entries using various parameters. This resource is cross-referenced with repetitive element (Repbase Update) and miRNA (miRBase) repositories, where sequences can be checked for further analysis. All data in PlanTE-MIR DB are publicly available for download in several file formats to facilitate their understanding and use. The database is hosted at http://bioinfo-tool.cp.utfpr.edu.br/plantemirdb/ .

Homeologous genes involved in mannitol synthesis reveal unequal contributions in response to abiotic stress in Coffea arabica.

Polyploid plants can exhibit transcriptional modulation in homeologous genes in response to abiotic stresses. Coffea arabica, an allotetraploid, accounts for 75% of the world's coffee production. Extreme temperatures, salinity and drought limit crop productivity, which includes coffee plants. Mannitol is known to be involved in abiotic stress tolerance in higher plants. This study aimed to investigate the transcriptional responses of genes involved in mannitol biosynthesis and catabolism in C. arabica leaves under water deficit, salt stress and high temperature. Mannitol concentration was significantly increased in leaves of plants under drought and salinity, but reduced by heat stress. Fructose content followed the level of mannitol only in heat-stressed plants, suggesting the partitioning of the former into other metabolites during drought and salt stress conditions. Transcripts of the key enzymes involved in mannitol biosynthesis, CaM6PR, CaPMI and CaMTD, were modulated in distinct ways depending on the abiotic stress. Our data suggest that changes in mannitol accumulation during drought and salt stress in leaves of C. arabica are due, at least in part, to the increased expression of the key genes involved in mannitol biosynthesis. In addition, the homeologs of the Coffea canephora subgenome did not present the same pattern of overall transcriptional response, indicating differential regulation of these genes by the same stimulus. In this way, this study adds new information on the differential expression of C. arabica homeologous genes under adverse environmental conditions showing that abiotic stresses can influence the homeologous gene regulation pattern, in this case, mainly on those involved in mannitol pathway.

A novel linkage map of sugarcane with evidence for clustering of retrotransposon-based markers.

BACKGROUND: The development of sugarcane as a sustainable crop has unlimited applications. The crop is one of the most economically viable for renewable energy production, and CO2 balance. Linkage maps are valuable tools for understanding genetic and genomic organization, particularly in sugarcane due to its complex polyploid genome of multispecific origins. The overall objective of our study was to construct a novel sugarcane linkage map, compiling AFLP and EST-SSR markers, and to generate data on the distribution of markers anchored to sequences of scIvana_1, a complete sugarcane transposable element, and member of the Copia superfamily. RESULTS: The mapping population parents ('IAC66-6' and 'TUC71-7') contributed equally to polymorphisms, independent of marker type, and generated markers that were distributed into nearly the same number of co-segregation groups (or CGs). Bi-parentally inherited alleles provided the integration of 19 CGs. The marker number per CG ranged from two to 39. The total map length was 4,843.19 cM, with a marker density of 8.87 cM. Markers were assembled into 92 CGs that ranged in length from 1.14 to 404.72 cM, with an estimated average length of 52.64 cM. The greatest distance between two adjacent markers was 48.25 cM. The scIvana_1-based markers (56) were positioned on 21 CGs, but were not regularly distributed. Interestingly, the distance between adjacent scIvana_1-based markers was less than 5 cM, and was observed on five CGs, suggesting a clustered organization. CONCLUSIONS: Results indicated the use of a NBS-profiling technique was efficient to develop retrotransposon-based markers in sugarcane. The simultaneous maximum-likelihood estimates of linkage and linkage phase based strategies confirmed the suitability of its approach to estimate linkage, and construct the linkage map. Interestingly, using our genetic data it was possible to calculate the number of retrotransposon scIvana_1 (~60) copies in the sugarcane genome, confirming previously reported molecular results. In addition, this research possibly will have indirect implications in crop economics e.g., productivity enhancement via QTL studies, as the mapping population parents differ in response to an important fungal disease.