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Functional genomics is transforming the way biological research is done in the 21st century. Functional genomics brings together high-throughput genetics with multiparallel analyses of gene transcripts, proteins, and metabolites to answer the ultimate question posed by all genome-sequencing projects: what is the biological function of each and every gene? Functional genomics is driving a shift in the research paradigm away from vertical analysis of single genes, proteins, or metabolites, towards horizontal analysis of full suites of genes, proteins, and metabolites. By identifying and measuring many, if not all of the molecular players that participate in a given biological process, functional genomics offers the prospect of obtaining a truly holistic picture of life. This review describes the tools that are currently being used for functional genomics work and considers the impact that this new discipline is likely to have in the future. [ABSTRACT FROM AUTHOR]

Abstract Background Single nucleotide polymorphisms (SNPs) are the most common type of sequence variation among plants and are often functionally important. We describe the use of 454 technology and high resolution melting analysis (HRM) for high throughput SNP discovery in tetraploid alfalfa (Medicago sativa L.), a species with high economic value but limited genomic resources. Results The alfalfa genotypes selected from M. sativa subsp. sativa var. 'Chilean' and M. sativa subsp. falcata var. 'Wisfal', which differ in water stress sensitivity, were used to prepare cDNA from tissue of clonally-propagated plants grown under either well-watered or water-stressed conditions, and then pooled for 454 sequencing. Based on 125.2 Mb of raw sequence, a total of 54,216 unique sequences were obtained including 24,144 tentative consensus (TCs) sequences and 30,072 singletons, ranging from 100 bp to 6,662 bp in length, with an average length of 541 bp. We identified 40,661 candidate SNPs distributed throughout the genome. A sample of candidate SNPs were evaluated and validated using high resolution melting (HRM) analysis. A total of 3,491 TCs harboring 20,270 candidate SNPs were located on the M. truncatula (MT 3.5.1) chromosomes. Gene Ontology assignments indicate that sequences obtained cover a broad range of GO categories. Conclusions We describe an efficient method to identify thousands of SNPs distributed throughout the alfalfa genome covering a broad range of GO categories. Validated SNPs represent valuable molecular marker resources that can be used to enhance marker density in linkage maps, identify potential factors involved in heterosis and genetic variation, and as tools for association mapping and genomic selection in alfalfa.

Abstract Background Legumes (Leguminosae or Fabaceae) play a major role in agriculture. Transcriptomics studies in the model legume species, Medicago truncatula, are instrumental in helping to formulate hypotheses about the role of legume genes. With the rapid growth of publically available Affymetrix GeneChip Medicago Genome Array GeneChip data from a great range of tissues, cell types, growth conditions, and stress treatments, the legume research community desires an effective bioinformatics system to aid efforts to interpret the Medicago genome through functional genomics. We developed the Medicago truncatula Gene Expression Atlas (MtGEA) web server for this purpose. Description The Medicago truncatula Gene Expression Atlas (MtGEA) web server is a centralized platform for analyzing the Medicago transcriptome. Currently, the web server hosts gene expression data from 156 Affymetrix GeneChip® Medicago genome arrays in 64 different experiments, covering a broad range of developmental and environmental conditions. The server enables flexible, multifaceted analyses of transcript data and provides a range of additional information about genes, including different types of annotation and links to the genome sequence, which help users formulate hypotheses about gene function. Transcript data can be accessed using Affymetrix probe identification number, DNA sequence, gene name, functional description in natural language, GO and KEGG annotation terms, and InterPro domain number. Transcripts can also be discovered through co-expression or differential expression analysis. Flexible tools to select a subset of experiments and to visualize and compare expression profiles of multiple genes have been implemented. Data can be downloaded, in part or full, in a tabular form compatible with common analytical and visualization software. The web server will be updated on a regular basis to incorporate new gene expression data and genome annotation, and is accessible at: http://bioinfo.noble.org/gene-atlas/. Conclusions The MtGEA web server has a well managed rich data set, and offers data retrieval and analysis tools provided in the web platform. It's proven to be a powerful resource for plant biologists to effectively and efficiently identify Medicago transcripts of interest from a multitude of aspects, formulate hypothesis about gene function, and overall interpret the Medicago genome from a systematic point of view.

Abstract Background Membrane transporters play crucial roles in living cells. Experimental characterization of transporters is costly and time-consuming. Current computational methods for transporter characterization still require extensive curation efforts, especially for eukaryotic organisms. We developed a novel genome-scale transporter prediction and characterization system called TransportTP that combined homology-based and machine learning methods in a two-phase classification approach. First, traditional homology methods were employed to predict novel transporters based on sequence similarity to known classified proteins in the Transporter Classification Database (TCDB). Second, machine learning methods were used to integrate a variety of features to refine the initial predictions. A set of rules based on transporter features was developed by machine learning using well-curated proteomes as guides. Results In a cross-validation using the yeast proteome for training and the proteomes of ten other organisms for testing, TransportTP achieved an equivalent recall and precision of 81.8%, based on TransportDB, a manually annotated transporter database. In an independent test using the Arabidopsis proteome for training and four recently sequenced plant proteomes for testing, it achieved a recall of 74.6% and a precision of 73.4%, according to our manual curation. Conclusions TransportTP is the most effective tool for eukaryotic transporter characterization up to date.

Abstract Background Most vascular flowering plants have the capacity to form symbiotic associations with arbuscular mycorrhizal (AM) fungi. The symbiosis develops in the roots where AM fungi colonize the root cortex and form arbuscules within the cortical cells. Arbuscules are enveloped in a novel plant membrane and their establishment requires the coordinated cellular activities of both symbiotic partners. The arbuscule-cortical cell interface is the primary functional interface of the symbiosis and is of central importance in nutrient exchange. To determine the molecular events the underlie arbuscule development and function, it is first necessary to identify genes that may play a role in this process. Toward this goal we used the Affymetrix GeneChip® Medicago Genome Array to document the M. truncatula transcript profiles associated with AM symbiosis, and then developed laser microdissection (LM) of M. truncatula root cortical cells to enable analyses of gene expression in individual cell types by RT-PCR. Results This approach led to the identification of novel M. truncatula and G. intraradices genes expressed in colonized cortical cells and in arbuscules. Within the arbuscule, expression of genes associated with the urea cycle, amino acid biosynthesis and cellular autophagy was detected. Analysis of gene expression in the colonized cortical cell revealed up-regulation of a lysine motif (LysM)-receptor like kinase, members of the GRAS transcription factor family and a symbiosis-specific ammonium transporter that is a likely candidate for mediating ammonium transport in the AM symbiosis. Conclusion Transcript profiling using the Affymetrix GeneChip® Medicago Genome Array provided new insights into gene expression in M. truncatula roots during AM symbiosis and revealed the existence of several G. intraradices genes on the M. truncatula GeneChip®. A laser microdissection protocol that incorporates low-melting temperature Steedman's wax, was developed to enable laser microdissection of M. truncatula root cortical cells. LM coupled with RT-PCR provided spatial gene expression information for both symbionts and expanded current information available for gene expression in cortical cells containing arbuscules.

Abstract Background Medicago truncatula is a model legume species that is currently the focus of an international genome sequencing effort. Although several different oligonucleotide and cDNA arrays have been produced for genome-wide transcript analysis of this species, intrinsic limitations in the sensitivity of hybridization-based technologies mean that transcripts of genes expressed at low-levels cannot be measured accurately with these tools. Amongst such genes are many encoding transcription factors (TFs), which are arguably the most important class of regulatory proteins. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is the most sensitive method currently available for transcript quantification, and one that can be scaled up to analyze transcripts of thousands of genes in parallel. Thus, qRT-PCR is an ideal method to tackle the problem of TF transcript quantification in Medicago and other plants. Results We established a bioinformatics pipeline to identify putative TF genes in Medicago truncatula and to design gene-specific oligonucleotide primers for qRT-PCR analysis of TF transcripts. We validated the efficacy and gene-specificity of over 1000 TF primer pairs and utilized these to identify sets of organ-enhanced TF genes that may play important roles in organ development or differentiation in this species. This community resource will be developed further as more genome sequence becomes available, with the ultimate goal of producing validated, gene-specific primers for all Medicago TF genes. Conclusion High-throughput qRT-PCR using a 384-well plate format enables rapid, flexible, and sensitive quantification of all predicted Medicago transcription factor mRNAs. This resource has been utilized recently by several groups in Europe, Australia, and the USA, and we expect that it will become the 'gold-standard' for TF transcript profiling in Medicago truncatula.

The conservation of GOLVEN (GLV)/ROOT MERISTEM GROWTH FACTOR (RGF) peptide encoding genes across plant genomes capable of forming roots or root-like structures underscores their potential significance in the terrestrial adaptation of plants. This study investigates the function and role of GOLVEN peptide-coding genes in Medicago truncatula. Five out of fifteen GLV/RGF genes were notably upregulated during nodule organogenesis and were differentially responsive to nitrogen deficiency and auxin treatment. Specifically, the expression of MtGLV9 and MtGLV10 at nodule initiation sites was contingent upon the NODULE INCEPTION transcription factor. Overexpression of these five nodule-induced GLV genes in hairy roots of M. truncatula and application of their synthetic peptide analogues led to a decrease in nodule count by 25-50%. Uniquely, the GOLVEN10 peptide altered the positioning of the first formed lateral root and nodule on the primary root axis, an observation we term 'noduletaxis'; this decreased the length of the lateral organ formation zone on roots. Histological section of roots treated with synthetic GOLVEN10 peptide revealed an increased cell number within the root cortical cell layers without a corresponding increase in cell length, leading to an elongation of the root likely introducing a spatiotemporal delay in organ formation. At the transcription level, the GOLVEN10 peptide suppressed expression of microtubule-related genes and exerted its effects by changing expression of a large subset of Auxin responsive genes. These findings advance our understanding of the molecular mechanisms by which GOLVEN peptides modulate root morphology, nodule ontogeny, and interactions with key transcriptional pathways., (© 2024 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

Alfalfa ( Medicago sativa L.) forage quality is adversely affected by lignin deposition in cell walls at advanced maturity stages. Reducing lignin content through RNA interference or antisense approaches has been shown to improve alfalfa forage quality and digestibility. We employed a multiplex CRISPR/Cas9-mediated gene-editing system to reduce lignin content and alter lignin composition in alfalfa by targeting the COUMARATE 3-HYDROXYLASE (MsC3H) gene, which encodes a key enzyme in lignin biosynthesis. Four guide RNAs (gRNAs) targeting the first exon of MsC3H were designed and clustered into a tRNA-gRNA polycistronic system and introduced into tetraploid alfalfa via Agrobacterium -mediated transformation. Out of 130 transgenic lines, at least 73 lines were confirmed to contain gene-editing events in one or more alleles of MsC3H . Fifty-five lines were selected for lignin content/composition analysis. Amongst these lines, three independent tetra-allelic homozygous lines ( Msc3h-013, Msc3h-121 , and Msc3h-158 ) with different mutation events in MsC3H were characterized in detail. Homozygous mutation of MsC3H in these three lines significantly reduced the lignin content and altered lignin composition in stems. Moreover, these lines had significantly lower levels of acid detergent fiber and neutral detergent fiber as well as higher levels of total digestible nutrients, relative feed values, and in vitro true dry matter digestibility. Taken together, these results showed that CRISPR/Cas9-mediated editing of MsC3H successfully reduced shoot lignin content, improved digestibility, and nutritional values without sacrificing plant growth and biomass yield. These lines could be used in alfalfa breeding programs to generate elite transgene-free alfalfa cultivars with reduced lignin and improved forage quality., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Wolabu, Mahmood, Chen, Torres-Jerez, Udvardi, Tadege, Cong, Wang and Wen.)

Gene functional descriptions offer a crucial line of evidence for candidate genes underlying trait variation. Conversely, plant responses to environmental cues represent important resources to decipher gene function and subsequently provide molecular targets for plant improvement through gene editing. However, biological roles of large proportions of genes across the plant phylogeny are poorly annotated. Here we describe the Joint Genome Institute (JGI) Plant Gene Atlas, an updateable data resource consisting of transcript abundance assays spanning 18 diverse species. To integrate across these diverse genotypes, we analyzed expression profiles, built gene clusters that exhibited tissue/condition specific expression, and tested for transcriptional response to environmental queues. We discovered extensive phylogenetically constrained and condition-specific expression profiles for genes without any previously documented functional annotation. Such conserved expression patterns and tightly co-expressed gene clusters let us assign expression derived additional biological information to 64 495 genes with otherwise unknown functions. The ever-expanding Gene Atlas resource is available at JGI Plant Gene Atlas (https://plantgeneatlas.jgi.doe.gov) and Phytozome (https://phytozome.jgi.doe.gov/), providing bulk access to data and user-specified queries of gene sets. Combined, these web interfaces let users access differentially expressed genes, track orthologs across the Gene Atlas plants, graphically represent co-expressed genes, and visualize gene ontology and pathway enrichments., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Alfalfa (Medicago sativa L.) is a perennial flowering plant in the legume family that is widely cultivated as a forage crop for its high yield, forage quality and related agricultural and economic benefits. Alfalfa is a photoperiod sensitive long-day (LD) plant that can accomplish its vegetative and reproductive phases in a short period of time. However, rapid flowering can compromise forage biomass yield and quality. Here, we attempted to delay flowering in alfalfa using multiplex CRISPR/Cas9-mediated mutagenesis of FLOWERING LOCUS Ta1 (MsFTa1), a key floral integrator and activator gene. Four guide RNAs (gRNAs) were designed and clustered in a polycistronic tRNA-gRNA system and introduced into alfalfa by Agrobacterium-mediated transformation. Ninety-six putative mutant lines were identified by gene sequencing and characterized for delayed flowering time and related desirable agronomic traits. Phenotype assessment of flowering time under LD conditions identified 22 independent mutant lines with delayed flowering compared to the control. Six independent Msfta1 lines containing mutations in all four copies of MsFTa1 accumulated significantly higher forage biomass yield, with increases of up to 78% in fresh weight and 76% in dry weight compared to controls. Depending on the harvesting schemes, many of these lines also had reduced lignin, acid detergent fibre (ADF) and neutral detergent fibre (NDF) content and significantly higher crude protein (CP) and mineral contents compared to control plants, especially in the stems. These CRISPR/Cas9-edited Msfta1 mutants could be introduced in alfalfa breeding programmes to generate elite transgene-free alfalfa cultivars with improved forage biomass yield and quality., (© 2023 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

Three PHO2 -like genes encoding putative ubiquitin-conjugating E2 enzymes of Medicago truncatula were characterized for potential roles in phosphorous (P) homeostasis and symbiotic nitrogen fixation (SNF). All three genes, MtPHO2A, B and C , contain miR399-binding sites characteristic of PHO2 genes in other plant species. Distinct spatiotemporal expression patterns and responsiveness of gene expression to P- and N-deprivation in roots and shoots indicated potential roles, especially for MtPHO2B , in P and N homeostasis. Phenotypic analysis of pho2 mutants revealed that MtPHO2B is integral to Pi homeostasis, affecting Pi allocation during plant growth under nutrient-replete conditions, while MtPHO2C had a limited role in controlling Pi homeostasis. Genetic analysis also revealed a connection between Pi allocation, plant growth and SNF performance. Under N-limited, SNF conditions, Pi allocation to different organs was dependent on MtPHO2B and, to a lesser extent, MtPHO2C and MtPHO2A. MtPHO2A also affected Pi homeostasis associated with nodule formation. Thus, MtPHO2 genes play roles in systemic and localized, i.e., nodule, P homeostasis affecting SNF., Competing Interests: Authors RH, IT-J, WS and MU are/were employed by the Noble Research Institute, LLC. All the authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Huertas, Torres-Jerez, Curtin, Scheible and Udvardi.)

The perennial native switchgrass adapts better than other plant species do to marginal soils with low plant-available nutrients, including those with low phosphorus (P) content. Switchgrass roots and their associated microorganisms can alter the pools of available P throughout the whole soil profile making predictions of P availability in situ challenging. Plant P homeostasis makes monitoring of P limitation via measurements of plant P content alone difficult to interpret. To address these challenges, we developed a machine-learning model trained with high accuracy using the leaf tissue chemical profile, rather than P content. By applying this learned model in field trials across two sites with contrasting extractable soil P, we observed that actual plant available P in soil was more similar than expected, suggesting that adaptations occurred to alleviate the apparent P constraint. These adaptations come at a metabolic cost to the plant that have consequences for feedstock chemical components and quality. We observed that other biochemical signatures of P limitation, such as decreased cellulose-to-lignin ratios, were apparent, indicating re-allocation of carbon resources may have contributed to increased P acquisition. Plant P allocation strategies also differed across sites, and these differences were correlated with the subsequent year's biomass yields., (© 2022. The Author(s).)