Bioenergy sorghum nodal root bud development: morphometric, transcriptomic and gene regulatory network analysis
Data from: Sorghum bicolor TX08001 nodal root tissue development gene expression profiling
bioenergy sorghum↗
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Testing for the Genomic Footprint of Conflict Between Life Stages in an Angiosperm and Moss Species
Abstract The maintenance of genetic variation by balancing selection is of considerable interest to evolutionary biologists. An important but understudied potential driver of balancing selection is antagonistic pleiotropy between diploid and haploid stages of the plant life cycle. Despite sharing a common genome, sporophytes (2n) and gametophytes (n) may undergo differential or even opposing selection. Theoretical work suggests antagonistic pleiotropy between life stages can generate balancing selection and maintain genetic variation. Despite the potential for far-reaching consequences of gametophytic selection, empirical tests of its pleiotropic effects (neutral, synergistic, or antagonistic) on sporophytes are generally lacking. Here, we examined the population genomic signals of selection across life stages in the angiosperm Rumex hastatulus and the moss Ceratodon purpureus. We compared gene expression between life stages and sexes, combined with neutral diversity statistics and the analysis of the distribution of fitness effects. In contrast to what would be predicted under balancing selection due to antagonistic pleiotropy, we found that unbiased genes between life stages were under stronger purifying selection, likely explained by a predominance of synergistic pleiotropy between life stages and strong purifying selection on broadly expressed genes. In addition, we found that 30% of candidate genes under balancing selection in R. hastatulus were located within inversion polymorphisms. Our findings provide novel insights into the genome-wide characteristics and consequences of plant gametophytic selection.
Evolutionary Biology↗
FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi
mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.
59 BASIC BIOLOGICAL SCIENCES↗
Genome-wide characterization of the soybean DOMAIN OF UNKNOWN FUNCTION 679 membrane protein gene family highlights their potential involvement in growth and stress response
The DMP (DUF679 membrane proteins) family is a plant-specific gene family that encodes membrane proteins. The DMP family genes are suggested to be involved in various programmed cell death processes and gamete fusion during double fertilization in Arabidopsis. However, their functional relevance in other crops remains unknown. This study identified 14 genes from the DMP family in soybean (Glycine max) and characterized their physiochemical properties, subcellular location, gene structure, and promoter regions using bioinformatics tools. Additionally, their tissue-specific and stress-responsive expressions were analyzed using publicly available transcriptome data. Phylogenetic analysis of 198 DMPs from monocots and dicots revealed six clades, with clade-I encoding senescence-related AtDMP1/2 orthologues and clade-II including pollen-specific AtDMP8/9 orthologues. The largest clade, clade-III, predominantly included monocot DMPs, while monocot- and dicot-specific DMPs were assembled in clade-IV and clade-VI, respectively. Evolutionary analysis suggests that soybean GmDMPs underwent purifying selection during evolution. Using 68 transcriptome datasets, expression profiling revealed expression in diverse tissues and distinct responses to abiotic and biotic stresses. The genes Glyma.09G237500 and Glyma.18G098300 showed pistil-abundant expression by qPCR, suggesting they could be potential targets for female organ-mediated haploid induction. Furthermore, cis-acting regulatory elements primarily related to stress-, hormone-, and light-induced pathways regulate GmDMPs, which is consistent with their divergent expression and suggests involvement in growth and stress responses. Overall, our study provides a comprehensive report on the soybean GmDMP family and a framework for further biological functional analysis of DMP genes in soybean or other crops.
59 BASIC BIOLOGICAL SCIENCES↗
Mechanisms of metabolic adaptation in the duckweed Lemna gibba: an integrated metabolic, transcriptomic and flux analysis
Abstract Background Duckweeds are small, rapidly growing aquatic flowering plants. Due to their ability for biomass production at high rates they represent promising candidates for biofuel feedstocks. Duckweeds are also excellent model organisms because they can be maintained in well-defined liquid media, usually reproduce asexually, and because genomic resources are becoming increasingly available. To demonstrate the utility of duckweed for integrated metabolic studies, we examined the metabolic adaptation of growing Lemna gibba cultures to different nutritional conditions. Results To establish a framework for quantitative metabolic research in duckweeds we derived a central carbon metabolism network model of Lemna gibba based on its draft genome. Lemna gibba fronds were grown with nitrate or glutamine as nitrogen source. The two conditions were compared by quantification of growth kinetics, metabolite levels, transcript abundance, as well as by 13 C-metabolic flux analysis. While growing with glutamine, the fronds grew 1.4 times faster and accumulated more protein and less cell wall components compared to plants grown on nitrate. Characterization of photomixotrophic growth by 13 C-metabolic flux analysis showed that, under both metabolic growth conditions, the Calvin-Benson-Bassham cycle and the oxidative pentose-phosphate pathway are highly active, creating a futile cycle with net ATP consumption. Depending on the nitrogen source, substantial reorganization of fluxes around the tricarboxylic acid cycle took place, leading to differential formation of the biosynthetic precursors of the Asp and Gln families of proteinogenic amino acids. Despite the substantial reorganization of fluxes around the tricarboxylic acid cycle, flux changes could largely not be associated with changes in transcripts. Conclusions Through integrated analysis of growth rate, biomass composition, metabolite levels, and metabolic flux, we show that Lemna gibba is an excellent system for quantitative metabolic studies in plants. Our study showed that Lemna gibba adjusts to different nitrogen sources by reorganizing central metabolism. The observed disconnect between gene expression regulation and metabolism underscores the importance of metabolic flux analysis as a tool in such studies.
59 BASIC BIOLOGICAL SCIENCES↗
Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling
The accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as flux balance analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy. Relative gene expression levels derived from multiple transcriptomic and proteomic datasets were integrated into FBA predictions of a multi-tissue, diel model of Arabidopsis thaliana’s central metabolism. This integration dramatically improved the agreement of flux predictions with experimentally based flux maps from 13 C metabolic flux analysis compared with a standard parsimonious FBA approach. Disagreement between FBA predictions and MFA flux maps was measured using weighted averaged percent error values, and for parsimonious FBA this was 169%–180% for high light conditions and 94%–103% for low light conditions, depending on the gene expression dataset used. This fell to 10%-13% and 9%-11% upon incorporating expression data into the modeling process, which also substantially altered the predicted carbon and energy economy of the plant.
59 BASIC BIOLOGICAL SCIENCES↗
Enhanced Resistance Pines for Improved Renewable Biofuel and Chemical Production (Technical Report)
We completed phenotyping constitutive and inducible oleoresin flow across two seasons, constitutive resin canal number and density and wood terpene content in our ADEPT2 and CCLONES populations. We completed genetic association between 19 oleoresin phenotypes and a total of 523,192 SNP markers from ADEPT2 and 13,883 SNP markers in CCLONES using four mixed linear models. A total of 293 significant SNPs (FDR = 0.20) were identified. We used the MENTOR tool to mine mechanistic connections from a multiplex network constructed from poplar multi-omic data to construct a conceptual model for a subset of these significant SNPs. Our model contains 6 transcriptional regulators in addition to 3 monoterpene synthases. To generate more lines of evidence for these significant SNPs, we completed a time course RNAseq experiment after inducing vascular zone cells to differentiate into new resin canals with a methyl jasmonate treatment, a single nuclei RNAseq that identified differentiating resin canal epithelial cells and are completing analysis for a QTL study in a hybrid pine population. The time course identified 4634 significantly down and 1890 significantly up regulated transcripts after treatment with methyl jasmonate, an inducer of new resin canal formation in the vascular cambial meristem. To analyze this large set of differentially regulated genes, we created a predictive expression network and analyzed it with random walk restart using 6 seed genes coding for transcription factors regulating xylem differentiation in poplar. Of the top ranked 200 transcripts, 119 transcripts were significant differentially expressed supporting these transcripts as potential candidates regulating resin canal formation. Analysis of single nuclei sequencing of shoot tips that contain differentiating resin canals, identified 10 clusters. One cluster was highly enriched in transcripts coding for 9 of the enzymes in the MEP pathway 3 prenyl synthetases, and 3 monoterpene synthases strongly suggesting that this cluster represents resin canal epithelial cells. We are mining the additional transcripts to create a trajectory analysis. In summary, we have identified > 10 novel genes that are strongly supported candidates for further analysis in breeding lines and for genetic engineering over- and under- expressing lines to increase wood terpene content to improve resistance to insect and fungal pathogens while simultaneously increasing terpene supplies for renewable chemicals and biofuels.
59 BASIC BIOLOGICAL SCIENCES↗
Transcriptomics of Temporal- versus Substrate-Specific Wood Decay in the Brown-Rot Fungus Fibroporia radiculosa
Brown-rot fungi lack many enzymes associated with complete wood degradation, such as lignin-attacking peroxidases, and have developed alternative mechanisms for rapid wood breakdown. To identify the effects of culture conditions and wood substrates on gene expression, we grew Fibroporia radiculosa in submerged cultures containing Wiley milled wood (5 days) and solid wood wafers (30 days), using aspen, pine, and spruce as a substrate. The comparative analysis revealed that wood species had a limited effect on the transcriptome: <3% of genes were differentially expressed between different wood species substrates. The comparison between gene expression during growth on milled wood and wood wafer conditions, however, indicated that the genes encoding plant cell wall-degrading enzymes, such as glycoside hydrolases and peptidases, were activated during growth on wood wafers, confirming previous reports. On the other hand, it was shown for the first time that the genes encoding Fenton chemistry enzymes, such as hydroquinone biosynthesis enzymes and oxidoreductases, were activated during submerged growth on ground wood. This illustrates the diversity of wood-decay reactions encoded in fungi and activated at different stages of this process.
59 BASIC BIOLOGICAL SCIENCES↗
Plasmid-encoded gene expression of pathogenic bacteria by antibiotic induction as detected by MALDI-TOF-TOF mass spectrometry and top-down proteomic analysis
Not Available
Fagerquist, Clifton K. (ORCID:0000000225983686)↗
Properties, Physiological Functions and Involvement of Basidiomycetous Alcohol Oxidase in Wood Degradation
Extensive research efforts have been devoted to describing yeast alcohol oxidase (AO) and its promoter region, which is vastly applied in studies of heterologous gene expression. However, little is known about basidiomycetous AO and its physiological role in wood degradation. This review describes several alcohol oxidases from both white and brown rot fungi, highlighting their physicochemical and kinetic properties. Moreover, the review presents a detailed analysis of available AO-encoding gene promoter regions in basidiomycetous fungi with a discussion of the manipulations of culture conditions in relation to the modification of alcohol oxidase gene expression and changes in enzyme production. The analysis of reactions catalyzed by lignin-modifying enzymes (LME) and certain lignin auxiliary enzymes (LDA) elucidated the possible involvement of alcohol oxidase in the degradation of derivatives of this polymer. Combined data on lignin degradation pathways suggest that basidiomycetous AO is important in secondary reactions during lignin decomposition by wood degrading fungi. With numerous alcoholic substrates, the enzyme is probably engaged in a variety of catalytic reactions leading to the detoxification of compounds produced in lignin degradation processes and their utilization as a carbon source by fungal mycelium.
59 BASIC BIOLOGICAL SCIENCES↗
Functional analysis of Salix purpurea genes support roles for ARR17 and GATA15 as master regulators of sex determination
Abstract The Salicaceae family is of growing interest in the study of dioecy in plants because the sex determination region (SDR) has been shown to be highly dynamic, with differing locations and heterogametic systems between species. Without the ability to transform and regenerate Salix in tissue culture, previous studies investigating the mechanisms regulating sex in the genus Salix have been limited to genome resequencing and differential gene expression, which are mostly descriptive in nature, and functional validation of candidate sex determination genes has not yet been conducted. Here, we used Arabidopsis to functionally characterize a suite of previously identified candidate genes involved in sex determination and sex dimorphism in the bioenergy shrub willow Salix purpurea . Six candidate master regulator genes for sex determination were heterologously expressed in Arabidopsis, followed by floral proteome analysis. In addition, 11 transcription factors with predicted roles in mediating sex dimorphism downstream of the SDR were tested using DAP‐Seq in both male and female S. purpurea DNA. The results of this study provide further evidence to support models for the roles of ARR17 and GATA15 as master regulator genes of sex determination in S. purpurea , contributing to a regulatory system that is notably different from that of its sister genus Populus . Evidence was also obtained for the roles of two transcription factors, an AP2 / ERF family gene and a homeodomain‐like transcription factor, in downstream regulation of sex dimorphism.
60 APPLIED LIFE SCIENCES↗
Targeted inhibition of MASTL kinase activity induces apoptosis in breast cancer
Microtubule-associated serine/threonine kinase-like (MASTL) (or Greatwall kinase (GWL)) is an important cell cycle regulating kinase that regulates the G2-M transition. Uncontrolled MASTL activity is implicated in breast cancer progression. To date, very few inhibitors have been reported against this protein. Here, structure-based computational modeling indicates that the natural product flavopiridol (FLV) binds strongly to MASTL and these results are validated using molecular dynamics simulation studies. Further, an in vitro kinase assay reveals an EC 50 (effective concentration) value of FLV to be 82.1 nM and a better IC 50 compared to the positive reference compound, staurosporine. FLV is found to inhibit MASTL kinase activity, arresting the cell growth in the G1 phase and inducing apoptosis in breast cancer cells. Consistent with these results differential gene expression obtained using RNA sequencing studies, and validated by RT PCR and immunoblot analysis, indicate that MASTL inhibition induces cell cycle arrest and apoptotic-related genes. Furthermore, metastasis- and inflammation- related genes are downregulated. Thus, the deregulation of MASTL signaling pathways on targeted inhibition of its kinase activity is revealed. This study lays a strong foundation for investigating FLV as a lead compound in breast cancer therapeutics.
60 APPLIED LIFE SCIENCES↗
Biomass formation and sugar release efficiency of Populus modified by altered expression of a NAC transcription factor
Woody biomass is an important feedstock for biofuel production. Manipulation of wood properties that enable efficient conversion of biomass to biofuel reduces cost of biofuel production. Wood cell wall composition is regulated at several levels that involve expression of transcription factors such as wood-/secondary cell wall-associated NAC domains (WND or SND). In Arabidopsis thaliana, SND1 regulates cell wall composition through activation of its down-stream targets such as MYBs. The functional aspects of SND1 homologs in the woody Populus have been studied through transgenic manipulation. In this study, we investigated the role of PdWND1B, Populus SND1 sequence ortholog, in wood formation using transgenic manipulation through over-expression or silencing under the control of a vascular-specific 4-coumarate-CoA ligase (4CL) promoter. As compared with control plants, PdWND1B-RNAi plants were shorter in height, with significantly reduced stem diameter and dry biomass, whereas there were no significant differences in growth and productivity of PdWND1B over-expression plants. Conversely, PdWND1B over-expression lines showed a significant reduction in cellulose and increase in lignin content, whereas there was no significant impact on lignin content of downregulated lines. Stem carbohydrate composition analysis revealed a decrease in glucose, mannose, arabinose, and galactose, but an increase in xylose in the over-expression lines. Transcriptome analysis revealed upregulation of several downstream transcription factors and secondary cell wall related structural genes in the PdWND1B over-expression lines, partly explaining the observed phenotypic changes in cell wall chemistry. Relative to the control, glucose release efficiency and ethanol production from stem biomass was significantly reduced in over-expression lines. Our results show that PdWND1B is an important factor determining biomass productivity, cell wall chemistry and its conversion to biofuels in Populus.
09 BIOMASS FUELS↗
A robust method of nuclei isolation for single-cell RNA sequencing of solid tissues from the plant genus Populus
Single-cell transcriptome analysis has been extensively applied in humans and animal models to uncover gene expression heterogeneity between the different cell types of a tissue or an organ. It demonstrated its capability to discover key regulatory elements that determine cell fate during developmental programs. Single-cell analysis requires the isolation and labeling of the messenger RNA (mRNA) derived from each cell. These challenges were primarily addressed in mammals by developing microfluidic-based approaches. For plant species whose cells contain cell walls, these approaches have generally required the generation of isolated protoplasts. Many plant tissues’ secondary cell wall hinders enzymatic digestion required for individual protoplast isolation, resulting in an unequal representation of cell types in a protoplast population. This limitation is especially critical for cell types located in the inner layers of a tissue or the inner tissues of an organ. Consequently, single-cell RNA sequencing (scRNA-seq) studies using microfluidic approaches in plants have mainly been restricted to Arabidopsis roots, for which well-established procedures of protoplast isolation are available. Here we present a simple alternative approach to generating high-quality protoplasts from plant tissue by characterizing the mRNA extracted from individual nuclei instead of whole cells. We developed the protocol using two different plant materials with varying cellular complexity levels and cell wall structure, Populus shoot apices, and more lignified stems. Using the 10× Genomics Chromium technology, we show that this procedure results in intact mRNA isolation and limited leakage, with a broad representation of individual cell transcriptomes.
54 ENVIRONMENTAL SCIENCES↗
Too dim, too bright, and just right: Systems analysis of the Chlamydomonas diurnal program under limiting and excess light
Photosynthetic organisms coordinate their metabolism and growth with diurnal light, which can range in intensity from limiting to excessive. Little is known about how light intensity impacts the diurnal program in Chlamydomonas reinhardtii, or how diurnal rhythms in gene expression and metabolism shape photoprotective responses at different times of day. To address these questions, we performed a systems analysis of synchronized Chlamydomonas populations acclimated to low, moderate, and high diurnal light. Transcriptomic and proteomic data revealed that the Chlamydomonas rhythmic gene expression program is resilient to limiting and excess light: genome-wide, waves of transcripts, and proteins peak at the same times in populations acclimated to stressful light intensities as in populations acclimated to moderate light. Yet, diurnal photoacclimation gives rise to hundreds of gene expression changes, even at night. Time course measurements of photosynthetic efficiency and pigments responsive to excess light showed that high light-acclimated cells partially overcome photodamage in the latter half of the day prior to cell division. Although gene expression and photodamage are dynamic over the diurnal cycle, Chlamydomonas populations acclimated to low and high diurnal light maintain altered photosystem abundance, thylakoid architecture, and non-photochemical quenching capacity through the night phase. This suggests that cells remember or anticipate the light intensities that they have typically encountered during the day. The integrated data constitute an excellent resource for understanding photoacclimation in eukaryotes under environmentally relevant conditions.
Dupuis, Sunnyjoy↗
Microbial inoculum effects on the rumen epithelial transcriptome and rumen epimural metatranscriptome in calves
Manipulation of the rumen microbial ecosystem in early life may affect ruminal fermentation and enhance the productive performance of dairy cows. The objective of this experiment was to evaluate the effects of dosing three different types of microbial inoculum on the rumen epithelium tissue (RE) transcriptome and the rumen epimural metatranscriptome (REM) in dairy calves. For this objective, 15 Holstein bull calves were enrolled in the study at birth and assigned to three different intraruminal inoculum treatments dosed orally once weekly from three to six weeks of age. The inoculum treatments were prepared from rumen contents collected from rumen fistulated lactating cows and were either autoclaved (control; ARF), processed by differential centrifugation to create the bacterial-enriched inoculum (BE), or through gravimetric separation to create the protozoal-enriched inoculum (PE). Calves were fed 2.5 L/d pasteurized waste milk 3x/d from 0 to 7 weeks of age and texturized starter until euthanasia at 9 weeks of age, when the RE tissues were collected for transcriptome and microbial metatranscriptome analyses, from four randomly selected calves from each treatment. The different types of inoculum altered the RE transcriptome and REM. Compared to ARF, 9 genes were upregulated in the RE of BE and 92 in PE, whereas between BE and PE there were 13 genes upregulated in BE and 114 in PE. Gene ontology analysis identified enriched GO terms in biological process category between PE and ARF, with no enrichment between BE and ARF. The RE functional signature showed different KEGG pathways related to BE and ARF, and no specific KEGG pathway for PE. We observed a lower alpha diversity index for RE microbiome in ARF (observed genera and Chao1 (p < 0.05)). Five microbial genera showed a significant correlation with the changes in host gene expression: Roseburia (25 genes), Entamoeba (two genes); Anaerosinus, Lachnospira, and Succiniclasticum were each related to one gene. sPLS-DA analysis showed that RE microbial communities differ among the treatments, although the taxonomic and functional microbial profiles show different distributions. Co-expression Differential Network Analysis indicated that both BE and PE had an impact on the abundance of KEGG modules related to acyl-CoA synthesis, type VI secretion, and methanogenesis, while PE had a significant impact on KEGGs related to ectoine biosynthesis and D-xylose transport. Our study indicated that artificial dosing with different microbial inocula in early life alters not only the RE transcriptome, but also affects the REM and its functions.
59 BASIC BIOLOGICAL SCIENCES↗
Kingdom-Wide Analysis of Fungal Protein-Coding and tRNA Genes Reveals Conserved Patterns of Adaptive Evolution
Protein-coding genes evolved codon usage bias due to the combined but uneven effects of adaptive and nonadaptive influences. Studies in model fungi agree on codon usage bias as an adaptation for fine-tuning gene expression levels; however, such knowledge is lacking for most other fungi. Our comparative genomics analysis of over 450 species supports codon usage and transfer RNAs (tRNAs) as coadapted for translation speed and this is most likely a realization of convergent evolution. Rather than drift, phylogenetic reconstruction inferred adaptive radiation as the best explanation for the variation of interspecific codon usage bias. Although the phylogenetic signals for individual codon and tRNAs frequencies are lower than expected by genetic drift, we found remarkable conservation of highly expressed genes being codon optimized for translation by the most abundant tRNAs, especially by inosine-modified tRNAs. As an application, we present a sequence-to-expression neural network that uses codons to reliably predict highly expressed transcripts. The kingdom Fungi, with over a million species, includes many key players in various ecosystems and good targets for biotechnology. Collectively, our results have implications for better understanding the evolutionary success of fungi, as well as informing the biosynthetic manipulation of fungal genes.
59 BASIC BIOLOGICAL SCIENCES↗
Anaerobic Fungal Mevalonate Pathway Genomic Biases Lead to Heterologous Toxicity Underpredicted by Codon Adaptation Indices
Anaerobic fungi are emerging biotechnology platforms with genomes rich in biosynthetic potential. Yet, the heterologous expression of their biosynthetic pathways has had limited success in model hosts like E. coli. We find one reason for this is that the genome composition of anaerobic fungi like P. indianae are extremely AT-biased with a particular preference for rare and semi-rare AT-rich tRNAs in E coli, which are not explicitly predicted by standard codon adaptation indices (CAI). Native P. indianae genes with these extreme biases create drastic growth defects in E. coli (up to 69% reduction in growth), which is not seen in genes from other organisms with similar CAIs. However, codon optimization rescues growth, allowing for gene evaluation. In this manner, we demonstrate that anaerobic fungal homologs such as PI.atoB are more active than S. cerevisiae homologs in a hybrid pathway, increasing the production of mevalonate up to 2.5 g/L (more than two-fold) and reducing waste carbon to acetate by ~90% under the conditions tested. This work demonstrates the bioproduction potential of anaerobic fungal enzyme homologs and how the analysis of codon utilization enables the study of otherwise difficult to express genes that have applications in biocatalysis and natural product discovery.
60 APPLIED LIFE SCIENCES↗