Statistical and Machine Learning Approaches to Predict Gene Regulatory Networks From Transcriptome Datasets

Statistical and machine learning (ML)-based methods have recently advanced in construction of gene regulatory network (GRNs) based on high-throughput biological datasets. GRNs underlie almost all cellular phenomena; hence, comprehensive GRN maps are essential tools to elucidate gene function, thereby facilitating the identification and prioritization of candidate genes for functional analysis. High-throughput gene expression datasets have yielded various statistical and ML-based algorithms to infer causal relationship between genes and decipher GRNs. This review summarizes the recent advancements in the computational inference of GRNs, based on large-scale transcriptome sequencing datasets of model plants and crops. We highlight strategies to select contextual genes for GRN inference, and statistical and ML-based methods for inferring GRNs based on transcriptome datasets from plants. Furthermore, we discuss the challenges and opportunities for the elucidation of GRNs based on large-scale datasets obtained from emerging transcriptomic applications, such as from population-scale, single-cell level, and life-course transcriptome analyses

A metabolome genome-wide association study implicates histidine N-pi-methyltransferase as a key enzyme in N-methylhistidine biosynthesis in Arabidopsis thaliana

A genome-wide association study (GWAS), which uses information on single nucleotide polymorphisms (SNPs) from many accessions, has become a powerful approach to gene identification. A metabolome GWAS (mGWAS), which relies on phenotypic information based on metabolite accumulation, can identify genes that contribute to primary and secondary metabolite contents. In this study, we carried out a mGWAS using seed metabolomic data from Arabidopsis thaliana accessions obtained by liquid chromatography–mass spectrometry to identify SNPs highly associated with the contents of metabolites such as glucosinolates. These SNPs were present in genes known to be involved in glucosinolate biosynthesis, thus confirming the effectiveness of our analysis. We subsequently focused on SNPs detected in an unknown methyltransferase gene associated with N-methylhistidine content. Knockout and overexpression of A. thaliana lines of this gene had significantly decreased and increased N-methylhistidine contents, respectively. We confirmed that the overexpressing line exclusively accumulated histidine methylated at the pi position, not at the tau position. Our findings suggest that the identified methyltransferase gene encodes a key enzyme for N-methylhistidine biosynthesis in A. thaliana

Highly Efficient CRISPR-Associated Protein 9 Ribonucleoprotein-Based Genome Editing in Euglena gracilis

Euglena gracilis, a unicellular phytoflagellate microalga, is a promising biomaterial for foods, feeds, and biofuels. However, targeted mutagenesis in this species has been a long-standing challenge. We recently developed a transgene-free, highly efficient, genome editing method for E. gracilis using CRISPR/Cas9 ribonucleoproteins (RNPs). Our method achieved mutagenesis rates of approximately 80% or more through an electroporation-based direct delivery of Cas9 RNPs. Therefore, this method is suitable for basic research and industrial applications, such as the breeding of Euglena. For complete details on the use and execution of this protocol, please refer to Nomura et al. (2019)

TriMEDB: A database to integrate transcribed markers and facilitate genetic studies of the tribe Triticeae

<p>Abstract</p> <p>Background</p> <p>The recent rapid accumulation of sequence resources of various crop species ensures an improvement in the genetics approach, including quantitative trait loci (QTL) analysis as well as the holistic population analysis and association mapping of natural variations. Because the tribe Triticeae includes important cereals such as wheat and barley, integration of information on the genetic markers in these crops should effectively accelerate map-based genetic studies on Triticeae species and lead to the discovery of key loci involved in plant productivity, which can contribute to sustainable food production. Therefore, informatics applications and a semantic knowledgebase of genome-wide markers are required for the integration of information on and further development of genetic markers in wheat and barley in order to advance conventional marker-assisted genetic analyses and population genomics of Triticeae species.</p> <p>Description</p> <p>The Triticeae mapped expressed sequence tag (EST) database (TriMEDB) provides information, along with various annotations, regarding mapped cDNA markers that are related to barley and their homologues in wheat. The current version of TriMEDB provides map-location data for barley and wheat ESTs that were retrieved from 3 published barley linkage maps (the barley single nucleotide polymorphism database of the Scottish Crop Research Institute, the barley transcript map of Leibniz Institute of Plant Genetics and Crop Plant Research, and HarvEST barley ver. 1.63) and 1 diploid wheat map. These data were imported to CMap to allow the visualization of the map positions of the ESTs and interrelationships of these ESTs with public gene models and representative cDNA sequences. The retrieved cDNA sequences corresponding to each EST marker were assigned to the rice genome to predict an exon-intron structure. Furthermore, to generate a unique set of EST markers in Triticeae plants among the public domain, 3472 markers were assembled to form 2737 unique marker groups as contigs. These contigs were applied for pairwise comparison among linkage maps obtained from different EST map resources.</p> <p>Conclusion</p> <p>TriMEDB provides information regarding transcribed genetic markers and functions as a semantic knowledgebase offering an informatics facility for the acceleration of QTL analysis and for population genetics studies of Triticeae.</p

Genomic traces of Japanese malting barley breeding in two modern high-quality cultivars, ‘Sukai Golden’ and ‘Sachiho Golden’

Two modern high-quality Japanese malting barley cultivars, ‘Sukai Golden’ and ‘Sachiho Golden’, were subjected to RNA-sequencing of transcripts extracted from 20-day-old immature seeds. Despite their close relation, 2,419 Sukai Golden-specific and 3,058 Sachiho Golden-specific SNPs were detected in comparison to the genome sequences of two reference cultivars: ‘Morex’ and ‘Haruna Nijo’. Two single nucleotide polymorphism (SNP) clusters respectively showing the incorporation of (1) the barley yellow mosaic virus (BaYMV) resistance gene rym5 from six-row non-malting Chinese landrace Mokusekko 3 on the long arm of 3H, and (2) the anthocyanin-less ant2 gene from a two-row Dutch cultivar on the long arm of 2H were detected specifically in ‘Sukai Golden’. Using 221 recombinant inbred lines of a cross between ‘Ishukushirazu’ and ‘Nishinochikara’, another BaYMV resistance rym3 gene derived from six-row non-malting Japanese cultivar ‘Haganemugi’ was mapped to a 0.4-cM interval on the proximal region of 5H. Haplotype analysis of progenitor accessions of the two modern malting cultivars revealed that rym3 of ‘Haganemugi’ was independently introduced into ‘Sukai Golden’ and ‘Sachiho Golden’. Residual chromosome 5H segments of ‘Haganemugi’ surrounding rym3 were larger in ‘Sukai Golden’. Available results suggest possibilities for malting quality improvement by minimizing residual segments surrounding rym3

Genetic Factors Associated with Heading Responses Revealed by Field Evaluation of 274 Barley Accessions for 20 Seasons

Heading time is a key trait in cereals affecting the maturation period for optimal grain filling before harvest. Here, we aimed to understand the factors controlling heading time in barley (Hordeum vulgare). We characterized a set of 274 barley accessions collected worldwide by planting them for 20 seasons under different environmental conditions at the same location in Kurashiki, Japan. We examined interactions among accessions, known genetic factors, and an environmental factor to determine the factors controlling heading response. Locally adapted accessions have been selected for genetic factors that stabilize heading responses appropriate for barley cultivation, and these accessions show stable heading responses even under varying environmental conditions. We identified vernalization requirement and PPD-H1 haplotype as major stabilizing mechanisms of the heading response for regional adaptation in Kurashiki

Cellular and transcriptomic analyses reveal two-staged chloroplast biogenesis underpinning photosynthesis build-up in the wheat leaf

Background The developmental gradient in monocot leaves has been exploited to uncover leaf developmental gene expression programs and chloroplast biogenesis processes. However, the relationship between the two is barely understood, which limits the value of transcriptome data to understand the process of chloroplast development. Results Taking advantage of the developmental gradient in the bread wheat leaf, we provide a simultaneous quantitative analysis for the development of mesophyll cells and of chloroplasts as a cellular compartment. This allows us to generate the first biologically-informed gene expression map of this leaf, with the entire developmental gradient from meristematic to fully differentiated cells captured. We show that the first phase of plastid development begins with organelle proliferation, which extends well beyond cell proliferation, and continues with the establishment and then the build-up of the plastid genetic machinery. The second phase is marked by the development of photosynthetic chloroplasts which occupy the available cellular space. Using a network reconstruction algorithm, we predict that known chloroplast gene expression regulators are differentially involved across those developmental stages. Conclusions Our analysis generates both the first wheat leaf transcriptional map and one of the most comprehensive descriptions to date of the developmental history of chloroplasts in higher plants. It reveals functionally distinct plastid and chloroplast development stages, identifies processes occurring in each of them, and highlights our very limited knowledge of the earliest drivers of plastid biogenesis, while providing a basis for their future identification