Applications and challenges of next-generation sequencing in Brassica species

A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction

To explore a robust tool for advancing digital breeding practices through an artificial intelligence-driven phenotype prediction expert system, we undertook a thorough analysis of 11 non-linear regression models. Our investigation specifically emphasized the significance of Support Vector Regression (SVR) and SHapley Additive exPlanations (SHAP) in predicting soybean branching. By using branching data (phenotype) of 1918 soybean accessions and 42 k SNP (Single Nucleotide Polymorphism) polymorphic data (genotype), this study systematically compared 11 non-linear regression AI models, including four deep learning models (DBN (deep belief network) regression, ANN (artificial neural network) regression, Autoencoders regression, and MLP (multilayer perceptron) regression) and seven machine learning models (e.g., SVR (support vector regression), XGBoost (eXtreme Gradient Boosting) regression, Random Forest regression, LightGBM regression, GPs (Gaussian processes) regression, Decision Tree regression, and Polynomial regression). After being evaluated by four valuation metrics: R2 (R-squared), MAE (Mean Absolute Error), MSE (Mean Squared Error), and MAPE (Mean Absolute Percentage Error), it was found that the SVR, Polynomial Regression, DBN, and Autoencoder outperformed other models and could obtain a better prediction accuracy when they were used for phenotype prediction. In the assessment of deep learning approaches, we exemplified the SVR model, conducting analyses on feature importance and gene ontology (GO) enrichment to provide comprehensive support. After comprehensively comparing four feature importance algorithms, no notable distinction was observed in the feature importance ranking scores across the four algorithms, namely Variable Ranking, Permutation, SHAP, and Correlation Matrix, but the SHAP value could provide rich information on genes with negative contributions, and SHAP importance was chosen for feature selection. The results of this study offer valuable insights into AI-mediated plant breeding, addressing challenges faced by traditional breeding programs. The method developed has broad applicability in phenotype prediction, minor QTL (quantitative trait loci) mining, and plant smart-breeding systems, contributing significantly to the advancement of AI-based breeding practices and transitioning from experience-based to data-based breeding.

A meta-analysis of differentially expressed and regulatory genes with their functional enrichment analysis for brain transcriptome data in autism spectrum disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by persistent challenges in social interactions and repetitive behavioral patterns. It is a significant problem emerging worldwide, as one in 100 children is affected by this disorder globally. In this study, a meta-analysis was performed for the identification of differentially expressed genes (DEGs) along with the expression analysis of regulatory genes. Functional enrichment analysis was an integral part of current findings to notify the significant pathways of this complex disorder. The study was conducted with two RNA-Seq datasets, viz., GSE64018 and GSE62098, for ASD patients and control samples from the GEO database. The identification of up-regulatory and down-regulatory genes was performed by the interaction analysis of transcription factors (TF) and DEGs. As an outcome of the meta-analysis, 2543 DEGs were identified as common across both of the datasets in which 1402 DEGs exhibited upregulation and 1130 genes have shown downregulation. In network analysis, upregulatory genes have shown strong interaction while downregulatory genes exhibit weak or null interaction. Further, in the enrichment analysis of screened upregulatory DEGs, three major significant pathways were identified namely the ATP synthesis pathway, FAS signaling pathway, and the Huntington's disease pathway. The common expression of CYC 1 gene in all the identified pathways has indicated that it is an important key regulator gene for the majorly associated pathways. The study concludes that all the potential DEGs were found to show their related high expression in neurobiological regulations specifically with ASD.Communicated by Ramaswamy S. Sarma.

Multi-omics analysis revealed crucial genes and pathways associated with black carp antiviral innate immunity

Multi-omics strategy contributes as an indispensable and efficient approach for the investigation of the innate immunity in vertebrates. To explore the crucial genes and pathways involved in the antiviral innate immunity of black carp (Mylopharyngodon piceus), the comparative phosphoproteomics and transcriptomics of Mylopharyngodon piceus kidney (MPK) cells with/without GCRV infection were performed in this manuscript. In phosphoproteomics analysis, 2637 phosphosites corresponding to 1532 proteins were identified and quantified, in which 1372 proteins were identified as differentially expressed proteins (DEPs) with 683 upregulated and 689 downregulated in GCRV infected cells. Functional annotation, enrichment analysis and pathway analysis highlighted that a large number of DEPs were enriched in immune related pathways including TLR pathway and NLR pathway. In transcriptomics analysis, a total of 2936 genes were identified as differentially expressed genes (DEGs), in which 2290 and 646 genes were upregulated and downregulated respectively after GCRV infection. As expected, pathway analysis based on DEGs also showed that a large proportion of DEGs were enriched in immune related pathways including TLR and RLR pathway. A combined list of DEPs and DEGs that enriched in above pathways were imported in Cytoscape for network analysis, reconstruction and visualization. The integrative study suggested that several significant DEPs and DEGs, such as MAP3K7 (TAK1), JUN, MAP2K2, CASP8, IL8 and IRF7 might be functionally crucial in host antiviral innate immunity. Thus, this study contributes as an indispensable reference map for the further investigation of the innate immune system of black carp.

TIAs pathway genes and associated miRNA identification in Vinca minor: supporting aspidosperma and eburnamine alkaloids linkage via transcriptomic analysis

V. minor contains monomeric eburnamine-type of indole alkaloids having utilization as a neuro-medicinal plant. The biosynthetic pathway studies using miRNAs has been the focal point for plant genomic research in recent years and this technique is utilized to get an insight into a possible pathway level study in V. minor as understanding of genes in this prized medicinal plant is meagrely understood. The de novo transcriptomic analysis using Illumina Next gen sequencing has been performed in glasshouse shifted plant and transformed roots to elucidate the possible non confirmed steps of terpenoid indole alkaloids (TIAs) pathway in V. minor. A putative TIA pathway is elucidated in the study including twelve possible TIAs biosynthetic genes. The specific miRNA associated with TIAs pathway were identified and their roles were discussed for the first time in V. minor. The comparative analysis of transcriptomic data of glasshouse shifted plant and transformed roots showed that the raw reads of transformed roots were higher (83,740,316) compared to glasshouse shifted plant (67,733,538). The EST-SSR prediction showed the maximum common repeats among glasshouse shifted plant and transformed roots, although small variation was found in trinucleotide repeats restricted to glasshouse shifted plant. The study reveals overall 37 miRNAs which were observed to be true and can have a role in pathway as they can regulate the growth and alkaloid production. The identification of putative pathway genes plays an important role in establishing linkage between Aspidosperma and Eburnamine alkaloids.

Mining lycodine-type alkaloid biosynthetic genes and genetic markers from transcriptome of Lycopodiastrum casuarinoides

Objective

Lycopodiastrum casuarinoides, a fern of the Lycopodiaceae family, is a traditional Chinese medicine, which has similar efficacy to that of Huperzia serrata in treating rheumatoid arthritis (RA). However, they are different in the contents and compositions of lycopodium alkaloids. In this study, the biosynthesis related genes of lycopodium alkaloids and genetic markers are discovered in L. casuarinoides transcriptome.

Methods

The plant of L. casuarinoides was collected and was subjected to the RNA isolation, cDNA library construction, high throughput RNA sequencing and bioinformatics analysis.

Results

Totally 124, 524 high-quality unigenes were assembled from RNA sequencing reads, with an average sequence length of 601 bp. Among the L. casuarinoides transcripts, 61,304 shared the significant similarity (E-value < 10⁻⁵) with existing protein sequences in the public databases. From 124,524 unigenes, 47,538 open reading frames (ORFs) were predicted. Based on the bioinformatics analysis, all possible enzyme genes involved in the lycodine-type alkaloids biosynthetic pathway of L. casuarinoides were identified, including lysine decarboxylase (LDC), primary amine oxidase (PAO), malonyl-CoA decarboxylase, etc. Sixty-four putative cytochrome p450 (CYP) and 827 putative transcription factors were selected from the transcriptome unigenes as the candidates of lycodine-type alkaloids biosynthesis modifiers. Furthermore, 13,352 simple sequence repeats (SSRs) were identified from 124,524 unigenes, of which dinucleotide motifs AG/CT were the most abundant (50.1%). Meanwhile, we confirmed the amplification effectiveness of 25 PCR primer pairs for randomly selected SSRs.

Conclusion

We obtained the comprehensive transcriptomic information from the high throughput RNA sequencing and bioinformatics analysis, which provided a valuable resource of transcript sequences of L. casuarinoides in public databases.

Comparative Analysis of miRNA Expression Profiles Between Heat-Tolerant and Heat-Sensitive Genotypes of Flowering Chinese Cabbage Under Heat Stress Using High-Throughput Sequencing

Heat stress disturbs cellular homeostasis, thus usually impairs yield of flowering Chinese cabbage (Brassica campestris L. ssp. chinensis var. utilis Tsen et Lee). MicroRNAs (miRNAs) play a significant role in plant responses to different stresses by modulating gene expression at the post-transcriptional level. However, the roles that miRNAs and their target genes may play in heat tolerance of flowering Chinese cabbage remain poorly characterized. The current study sequenced six small RNA libraries generated from leaf tissues of flowering Chinese cabbage collected at 0, 6, and 12 h after 38 °C heat treatment, and identified 49 putative novel miRNAs and 43 known miRNAs that differentially expressed between heat-tolerant and heat-sensitive flowering Chinese cabbage. Among them, 14 novel and nine known miRNAs differentially expressed only in the heat-tolerant genotype under heat-stress, therefore, their target genes including disease resistance protein TAO1-like, RPS6, reticuline oxidase-like protein, etc. might play important roles in enhancing heat-tolerance. Gene Ontology (GO) analysis revealed that targets of these differentially expressed miRNAs may play key roles in responses to temperature stimulus, cell part, cellular process, cell, membrane, biological regulation, binding, and catalytic activities. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified their important functions in signal transduction, environmental adaptation, global and overview maps, as well as in stress adaptation and in MAPK signaling pathways such as cell death. These findings provide insight into the functions of the miRNAs in heat stress tolerance of flowering Chinese cabbage.

Non-coding RNAs: Functional roles in the regulation of stress response in Brassica crops

Brassica crops face a combination of different abiotic and biotic stresses in the field that can reduce plant growth and development by affecting biochemical and morpho-physiological processes. Emerging evidence suggests that non-coding RNAs (ncRNAs), especially microRNAs (miRNAs) and long ncRNAs (lncRNAs), play a significant role in the modulation of gene expression in response to plant stresses. Recent advances in computational and experimental approaches are of great interest for identifying and functionally characterizing ncRNAs. While progress in this field is limited, numerous ncRNAs involved in the regulation of gene expression in response to stress have been reported in Brassica. In this review, we summarize the modes of action and functions of stress-related miRNAs and lncRNAs in Brassica as well as the approaches used to identify ncRNAs.

Genome-wide characterization of ALDH Superfamily in Brassica rapa and enhancement of stress tolerance in heterologous hosts by BrALDH7B2 expression

Aldehyde dehydrogenase (ALDH) carries out oxidation of toxic aldehydes using NAD⁺/NADP⁺ as cofactors. In the present study, we performed a genome-wide identification and expression analysis of genes in the ALDH gene family in Brassica rapa. A total of 23 ALDH genes in the superfamily have been identified according to the classification of ALDH Gene Nomenclature Committee (AGNC). They were distributed unevenly across all 10 chromosomes. All the 23 Brassica rapa ALDH (BrALDH) genes exhibited varied expression patterns during treatments with abiotic stress inducers and hormonal treatments. The relative expression profiles of ALDH genes in B. rapa showed that they are predominantly expressed in leaves and stem suggesting their function in the vegetative tissues. BrALDH7B2 showed a strong response to abiotic stress and hormonal treatments as compared to other ALDH genes; therefore, it was overexpressed in heterologous hosts, E. coli and yeast to study its possible function under abiotic stress conditions. Over-expression of BrALDH7B2 in heterologous systems, E. coli and yeast cells conferred significant tolerance to abiotic stress treatments. Results from this work demonstrate that BrALDH genes are a promising and untapped genetic resource for crop improvement and could be deployed further in the development of drought and salinity tolerance in B. rapa and other economically important crops.

Augmentation of crop productivity through interventions of omics technologies in India: challenges and opportunities

With the continuous increase in the population of developing countries and decline of natural resources, there is an urgent need to qualitatively and quantitatively augment crop productivity by using new tools and technologies for improvement of agriculturally important traits. The new scientific and technological omics-based approaches have enabled us to deal with several issues and challenges faced by modern agricultural system and provided us novel opportunities for ensuring food and nutritional security. Recent developments in sequencing techniques have made available huge amount of genomic and transcriptomic data on model and cultivated crop plants including Arabidopsis thaliana, Oryza sativa, Triticum aestivum etc. The sequencing data along with other data generated through several omics platforms have significantly influenced the disciplines of crop sciences. Gene discovery and expression profiling-based technologies are offering enormous opportunities to the scientific community which can now apply marker-assisted selection technology to assess and enhance diversity in their collected germplasm, introgress essential traits from new sources and investigate genes that control key traits of crop plants. Utilization of omics science and technologies for crop productivity, protection and management has recently been receiving a lot of attention; the majority of the efforts have been put into signifying the possible applications of various omics technologies in crop plant sciences. This article highlights the background of challenges and opportunities for augmentation of crop productivity through interventions of omics technologies in India.

Transcriptomic analysis of the regulation of stalk development in flowering Chinese cabbage (Brassica campestris) by RNA sequencing

Flowering Chinese cabbage is a stalk vegetable whose quality and yield are directly related to stalk development. However, no comprehensive investigations on stalk development have been performed. To address this issue, the present study used RNA sequencing to investigate transcriptional regulation at three key stages (seedling, bolting, and flowering) of stalk development in flowering Chinese cabbage. Anatomical analysis revealed that cell division was the main mode of stalk thickening and elongation at all key stages. Among the 35,327 genes expressed in shoot apices, 34,448 were annotated and 879 were identified as novel transcripts. We identified 11,514 differentially expressed genes (DEGs) among the three stages of stalk development. Functional analysis revealed that these DEGs were significantly enriched in ‘ribosome’ and ‘plant hormone signal transduction’ pathways and were involved in hormone signal transduction, cell cycle progression, and the regulation of flowering time. The roles of these genes in stalk development were explored, and a putative gene-regulation network for the stalk flowering time was established. These findings provide insight into the molecular mechanisms of stalk development in flowering Chinese cabbage that provides a new theoretical basis for stalk vegetable breeding.

Oilseed rape: learning about ancient and recent polyploid evolution from a recent crop species

Oilseed rape (Brassica napus) is one of our youngest crop species, arising several times under cultivation in the last few thousand years and completely unknown in the wild. Oilseed rape originated from hybridisation events between progenitor diploid species B. rapa and B. oleracea, both important vegetable species. The diploid progenitors are also ancient polyploids, with remnants of two previous polyploidisation events evident in the triplicated genome structure. This history of polyploid evolution and human agricultural selection makes B. napus an excellent model with which to investigate processes of genomic evolution and selection in polyploid crops. The ease of de novo interspecific hybridisation, responsiveness to tissue culture, and the close relationship of oilseed rape to the model plant Arabidopsis thaliana, coupled with the recent availability of reference genome sequences and suites of molecular cytogenetic and high-throughput genotyping tools, allow detailed dissection of genetic, genomic and phenotypic interactions in this crop. In this review we discuss the past and present uses of B. napus as a model for polyploid speciation and evolution in crop species, along with current and developing analysis tools and resources. We further outline unanswered questions that may now be tractable to investigation.

Genomics-based strategies for the use of natural variation in the improvement of crop metabolism

Next-generation genomics holds great potential in the study of plant phenotypic variation. With several crop reference genomes now available, the affordable costs of de novo genome assembly or target resequencing offer the opportunity to mine the enormous amount of genetic diversity hidden in crop wild relatives. Wide introgressions from these wild ancestors species or land races represent a possible strategy to improve cultivated varieties. In this review, we discuss the mechanisms underlying metabolic diversity within plant species and the possible strategies (and barriers) to introgress novel metabolic traits into cultivated varieties. We show how deep genomic surveys uncover various types of structural variants from extended gene pools of major crops and highlight how this variation may be used for the improvement of crop metabolism.

Recent progress in the use of 'omics technologies in brassicaceous vegetables

Continuing advances in 'omics methodologies and instrumentation is enhancing the understanding of how plants cope with the dynamic nature of their growing environment. 'Omics platforms have been only recently extended to cover horticultural crop species. Many of the most widely cultivated vegetable crops belong to the genus Brassica: these include plants grown for their root (turnip, rutabaga/swede), their swollen stem base (kohlrabi), their leaves (cabbage, kale, pak choi) and their inflorescence (cauliflower, broccoli). Characterization at the genome, transcript, protein and metabolite levels has illustrated the complexity of the cellular response to a whole series of environmental stresses, including nutrient deficiency, pathogen attack, heavy metal toxicity, cold acclimation, and excessive and sub-optimal irradiation. This review covers recent applications of 'omics technologies to the brassicaceous vegetables, and discusses future scenarios in achieving improvements in crop end-use quality.

Next Generation Sequencing Technologies: The Doorway to the Unexplored Genomics of Non-Model Plants

Non-model plants i.e., the species which have one or all of the characters such as long life cycle, difficulty to grow in the laboratory or poor fecundity, have been schemed out of sequencing projects earlier, due to high running cost of Sanger sequencing. Consequently, the information about their genomics and key biological processes are inadequate. However, the advent of fast and cost effective next generation sequencing (NGS) platforms in the recent past has enabled the unearthing of certain characteristic gene structures unique to these species. It has also aided in gaining insight about mechanisms underlying processes of gene expression and secondary metabolism as well as facilitated development of genomic resources for diversity characterization, evolutionary analysis and marker assisted breeding even without prior availability of genomic sequence information. In this review we explore how different Next Gen Sequencing platforms, as well as recent advances in NGS based high throughput genotyping technologies are rewarding efforts on de-novo whole genome/transcriptome sequencing, development of genome wide sequence based markers resources for improvement of non-model crops that are less costly than phenotyping.

VTBuilder: a tool for the assembly of multi isoform transcriptomes

Background

Within many research areas, such as transcriptomics, the millions of short DNA fragments (reads) produced by current sequencing platforms need to be assembled into transcript sequences before they can be utilized. Despite recent advances in assembly software, creating such transcripts from read data harboring isoform variation remains challenging. This is because current approaches fail to identify all variants present or they create chimeric transcripts within which relationships between co-evolving sites and other evolutionary factors are disrupted. We present VTBuilder, a tool for constructing non-chimeric transcripts from read data that has been sequenced from sources containing isoform complexity.

Results

We validated VTBuilder using reads simulated from 54 Sanger sequenced transcripts (SSTs) expressed in the venom gland of the saw scaled viper, Echis ocellatus. The SSTs were selected to represent genes from major co-expressed toxin groups known to harbor isoform variants. From the simulated reads, VTBuilder constructed 55 transcripts, 50 of which had a greater than 99% sequence similarity to 48 of the SSTs. In contrast, using the popular assembler tool Trinity (r2013-02-25), only 14 transcripts were constructed with a similar level of sequence identity to just 11 SSTs. Furthermore VTBuilder produced transcripts with a similar length distribution to the SSTs while those produced by Trinity were considerably shorter. To demonstrate that our approach can be scaled to real world data we assembled the venom gland transcriptome of the African puff adder Bitis arietans using paired-end reads sequenced on Illumina’s MiSeq platform. VTBuilder constructed 1481 transcripts from 5 million reads and, following annotation, all major toxin genes were recovered demonstrating reconstruction of complex underlying sequence and isoform diversity.

Conclusion

Unlike other approaches, VTBuilder strives to maintain the relationships between co-evolving sites within the constructed transcripts, and thus increases transcript utility for a wide range of research areas ranging from transcriptomics to phylogenetics and including the monitoring of drug resistant parasite populations. Additionally, improving the quality of transcripts assembled from read data will have an impact on future studies that query these data. VTBuilder has been implemented in java and is available, under the GPL GPU V0.3 license, from http:// http://www.lstmed.ac.uk/vtbuilder.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0389-8) contains supplementary material, which is available to authorized users.