ORIGINAL RESEARCH published: 31 January 2022 doi: 10.3389/fpls.2022.827828 Analysis of Alternative Splicing During the Combinatorial Response to Simultaneous Copper and Iron Deficiency in Arabidopsis Reveals Differential Events in Genes Involved in Amino Acid Metabolism Estefania Mancini 1 and Antoni Garcia-Molina 2* 1 Centre for Genomic Regulation, Barcelona, Spain, 2 Centre for Research in Agricultural Genomics (CRAG), Edited by: CSIC-IRTA-UAB-UB, Barcelona, Spain Anja Schneider, Ludwig Maximilian University of Munich, Germany Copper (Cu) and iron (Fe) constitute fundamental nutrients for plant biology but are Reviewed by: often limited due to low bioavailability. Unlike responses to single Cu or Fe deprivation, Marion Eisenhut, Heinrich Heine University the consequences of simultaneous Cu and Fe deficiency have not yet been fully of Düsseldorf, Germany deciphered. Previously, it was demonstrated that Cu and Fe deficiency applied in Torsten Möhlmann, University of Kaiserslautern, Germany combination imposes transcriptome, proteome, and metabolome changes different *Correspondence: from those triggered under each deficiency individually. Here, we evaluated the effect Antoni Garcia-Molina of alternative splicing (AS) on the transcriptome of rosette leaves under single and antoni.garcia@cragenomica.es simultaneous Cu and Fe deficiency. Differentially spliced genes (DSGs) and differentially Specialty section: expressed genes (DEGs) coincided in number (2,600 approx.) although the overlapping This article was submitted to fraction was minimal (15%). Functional annotation of changes exclusively detected Plant Nutrition, under simultaneous Cu and Fe deficiency revealed that DEGs participated in general a section of the journal Frontiers in Plant Science stress responses and translation, while DSGs were involved in metabolic reactions, Received: 02 December 2021 especially amino acid biosynthesis. Interestingly, transcripts encoding central features for Accepted: 11 January 2022 tryptophan (Trp) and asparagine (Asn) synthesis – two significantly altered metabolites Published: 31 January 2022 under simultaneous Cu and Fe deficiency – underwent exclusive intron retention events Citation: Mancini E and Garcia-Molina A under the double deficiency. However, transcript and protein amounts for these enzymes (2022) Analysis of Alternative Splicing did not correlate with Trp and Asn concentration. In consequence, we propose that During the Combinatorial Response AS might act as a regulatory mechanism to modify the stability and/or functionality of to Simultaneous Copper and Iron Deficiency in Arabidopsis Reveals the enzymes and therefore fine-tune amino acid production during the combinatorial Differential Events in Genes Involved response to simultaneous Cu and Fe deficiency. in Amino Acid Metabolism. Front. Plant Sci. 13:827828. Keywords: alternative splicing, copper deficiency, iron deficiency, combinatorial stress, systems biology, doi: 10.3389/fpls.2022.827828 Arabidopsis thaliana Frontiers in Plant Science | www.frontiersin.org 1 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency INTRODUCTION interaction between Cu and Fe deficiencies uncovered specific expression patterns for transcripts related to ribosome subunit Copper (Cu) and iron (Fe) are essential nutrients for plants conformation and translation activities, and for proteins assisting because they possess suitable redox properties to sustain protein folding and degradation. At the metabolome level, the fundamental processes such as photosynthesis, respiration, and combinatorial response to double Cu and Fe deficiency provoked antioxidative defense reactions, among others (Puig et al., decreases in the total fraction of sugars and organic acids from 2007; Ravet and Pilon, 2013; Zhang, 2015). However, the the tricarboxylic acid cycle in comparison with single deficiencies, same redox properties lead to cytotoxicity when Cu and Fe and limited the increase in amino acids observed under are present in excess (Puig et al., 2007; Ravet and Pilon, single Fe deficiency. Further analysis of metabolome profiles 2013). In consequence, plants require fine-tuned mechanisms explained such trends by significant drops in the concentration to keep Cu and Fe levels within balanced ranges. Despite of phenylalanine (Phe), asparagine (Asn), tryptophan (Trp), and being abundant in soils, Cu and Fe bioavailability is often the organic acid fumarate. Moreover, loss-of-function lines of restricted due to the chelating effect of organic matter, low the cytosolic fumarase FUMARASE2 displayed improved growth insolubility in alkaline soils, or overexploitation of farmlands and photosynthesis performance in seedlings cultivated under for agricultural purposes (Morrissey and Guerinot, 2009; Cu and Fe deficient conditions, which was accompanied by Puig and Penarrubia, 2009). balanced levels of amino acids (Garcia-Molina et al., 2021). Plant responses to individual Cu or Fe scarcity have This finding confirmed the existence of specific mechanisms been extensively investigated, especially in the model exclusively operating in plants under simultaneous Cu and Fe plant Arabidopsis thaliana (hereafter Arabidopsis). The deficiency and posed fumaric acid as a central modulator of the transcription factors SQUAMOSA PROMOTER BINDING combinatorial response. PROTEIN-LIKE 7 (SPL7) and FER-LIKE IRON DEFICIENCY Alternative splicing (AS) is a post-transcriptional mechanism INDUCED TRANSCRIPTION FACTOR (FIT1) orchestrate specific to eukaryotic organisms consisting in the differential the transcriptional reprogramming under Cu and Fe limitation processing of the exons and introns in precursor mRNAs to (Colangelo and Guerinot, 2004; Yamasaki et al., 2009; Bernal generate different isoforms of the same transcript. In plants, it et al., 2012). SPL7 and IRT1 promote high-affinity uptake is estimated that AS affects up to 70% of all precursor mRNAs, systems consisting of FERRIC REDUCTION OXIDASE (FRO) encompassing multiple exons with intron retention being the metalloreductases to reduce Cu2+ and Fe3+ to Cu+ and Fe2+ most predominant event (Filichkin et al., 2010; Marquez et al., prior to transport via COPPER TRANSPORT PROTEINS 2012). The resulting transcript isoforms can display altered (COPTs) and IRON-REGULATED TRANSPORTER 1 (IRT1), stability, translational efficiency, or subcellular retention, or can respectively. In addition, the dissection of the mechanism of be translated into protein variants with divergent structures action of SPL7 and FIT1 unveiled points of cross-talk between and functions. Thus, AS acts as a central regulatory strategy to Cu and Fe homeostatic networks. For instance, SPL7 triggers the sustain plant growth and development under different conditions replacement of Cu/Zn-depending SUPEROXIDE DISMUTASE (Reddy et al., 2013; Laloum et al., 2018; Szakonyi and Duque, by the Fe-depending isoform to prioritize Cu ions in chloroplasts 2018; Chaudhary et al., 2019). Moreover, recent studies in the for PLASTOCYANINE and, thus, preserve photosynthesis field contributed in demonstrating the relevance of AS events under Cu deficient conditions (Yamasaki et al., 2009; Bernal in transcriptome responses to abiotic stress conditions as well et al., 2012). On the other hand, FIT1 promotes FRO4/5 and as part of the so-called “memory stress” program (Ding et al., COPT2 to rely on Cu-depending proteins when Fe is limiting 2014; Calixto et al., 2018; Kannan et al., 2018; Ling et al., 2018; (Colangelo and Guerinot, 2004). Huang et al., 2019). However, our understanding of the molecular mechanisms How AS is involved in the combinatorial response to involved in combinatorial responses to simultaneous Cu and simultaneous Cu and Fe deficiency still remains an open Fe deficiency is still limited. This fact is of special relevance question. Therefore, in this work we aimed to extend the holistic as molecular responses to combinatorial stress trigger patterns picture of molecular changes in response to the double Cu that largely differ from those activated under each stressor and Fe deficiency with the contribution of AS in transcript individually (Atkinson et al., 2013; Prasch and Sonnewald, 2013; regulation. Our analysis of the transcriptome data generated Rasmussen et al., 2013; Suzuki et al., 2014; Gupta et al., 2016). in Garcia-Molina et al. (2020) uncovered a specific cohort Recently, a systems biology study provided a holistic picture of genes exclusively undergoing AS during the combinatorial of transcriptome, proteome, and metabolome changes under response. These genes were related to biosynthetic pathways single and simultaneous Cu and Fe deficiencies in Arabidopsis for amino acids changing under this condition, especially adult leaves (Garcia-Molina et al., 2020). Quantitatively, the Asn and Trp. Further integration of transcriptome, proteome, combinatorial response caused half of all detected transcripts and and metabolome profiles revealed lack of correlation between proteins that significantly changed in abundance. Conditional transcripts and proteins for enzymes synthesizing Trp and networks on molecular changes under single and double Cu Asn and metabolite concentration when both Cu and Fe are and Fe deficiencies displayed important divergences in topology limiting. Accordingly, we propose that AS events might act as a and detection of communities, revealing substantial differences potential regulatory mechanism to adjust metabolic composition in co-expression of biological processes. Indeed, data mining to plant demands during the combinatorial response to double on changing transcripts and proteins as a result of the Cu and Fe deficit. Frontiers in Plant Science | www.frontiersin.org 2 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency MATERIALS AND METHODS terms were removed in REVIGO3 to obtain a small list (0.5) (Supek et al., 2011). Benjamini-Hochberg’s method was applied Data Collection for multiple testing correction in all cases. To identify metabolic Transcriptome (GEO ID: GSE125894), proteome (Pride ID: reactions targeted by alternative splicing events, differentially PXD013598), and metabolome (Supplementary Table 1) profiles spliced genes were loaded onto Mapman v.3.5.14 and the bins of adult rosette leaves reported by Garcia-Molina et al. (2020) for amino acid reactions in the category “metabolism overview” were used in this study. Briefly, 12-day-old A. thaliana (ecotype extracted (Thimm et al., 2004). Alternative splicing events were Col0) seedlings grown on soil were transferred to hydroponic visualized in Integrative Genome Viewer (Robinson et al., 2011) cultures with full 1/10 Hoagland medium (Hermans et al., according to the coverage in the RNA-Seq experiments using 2004) for 12 days and then treated with the same medium log10 -transformed read counts. or without Cu and/or Fe salts for 10 days. RNA-seq libraries (n = 2 independent replicates per treatment) were sequenced using standard Illumina HiSeq 2500 (Illumina, San Diego, RESULTS CA, United States) protocols. Proteomes (n = 4 independent replicates per treatment) were profiled by means of liquid Alternative Splicing Events During the chromatography-tandem mass spectrometry (LC-MS/MS) and Combinatorial Copper and Iron processed with MAXQUANT (Cox and Mann, 2008). Metabolite Deficiency Target a Fraction of Genes concentration (n = 4 and 7 independent replicates per treatment at 5 and 10 days, respectively) was determined by targeted gas That Are Not Differentially Expressed chromatograph coupled to a time-of-flight mass spectrometer High-throughput profiling and systemic analysis of the (GC-TOF-MS) according to the Golm Metabolome Database transcriptome, proteome, and metabolome of adult rosette (Kopka et al., 2005) using ribitol and 13 C-sorbitol as internal leaves grown under double Cu and Fe deficiency for 10 days standards for relative quantification. uncovered an array of molecular changes that were not triggered under single Cu or Fe deficiencies (Garcia-Molina et al., 2020). Analysis of Alternative Splicing To complete this picture with the contribution of AS in the combinatorial response to simultaneous Cu and Fe deficiency, The analysis of alternative splicing was conducted in R using the the transcriptome profiles generated in Garcia-Molina et al. ASpli package (Mancini et al., 2021). Sequencing reads derived (2020) were analyzed using the ASpli package (Mancini et al., from RNA-Seq files were mapped to the A. thaliana genome 2021). Reads spanning intronic and exonic bins as well as (TAIR10) using the aligner tool STAR (Dobin et al., 2012) with junctions were used to estimate the PIR or PSI (Mancini et al., default parameters, except for maximum intron length set at 2021) under each of the conditions. Differential alternative 5,000 nucleotides. Then, the transcriptome was partitioned into splicing events (DASs) were declared based on significant subgenic regions named “bins” as proposed on DEXseq (Anders changes in PIR or PSI for the interaction between Cu and Fe et al., 2012). Read counts in each bin region were recorded. Null deficiencies (p-value ≤ 0.05, two-way ANOVA). In total, 3,917 values (NA) representing lack of coverage of bins were manually DASs were identified −27.7% of these corresponded to annotated replaced by 0. Splice junction information was employed to exon skipping (ES) events, whereas 57.8% were intron retention compute the Percent of Inclusion (PSI) and Percent of Intron (IR) events and 14.40% were other minoritarian forms of AS Retention (PIR) for each bin. events. Moreover, DASs were located in 2,806 different genes Significant changes in alternative splicing events were that were further considered differentially spliced genes (DSGs) calculated from differences in PSI or PIR using a two-way (Figures 1A,B). ANOVA (p-value ≤ 0.05) for the interaction between Cu and Interestingly, although the DSG fraction represented 33.56% Fe deficiencies. Subsequently, significant changes in alternative of all potential DSGs annotated in ASpli, however, only 428 splicing events among conditions were declared using an absolute DSGs (15.25% of all DSGs) were previously reported as log2 fold-change for PSI or PIR ≥ 1 in pair-wise comparisons differentially expressed genes (DEGs) in Garcia-Molina et al. (adjusted-p-value ≤ 0.05, Tukey’s post hoc test). (2020; Supplementary Table 2) using the same cut-off for significance. Similarly, only 16.23% of the reported DEGs Bioinformatic Tools underwent significant AS events (Figure 1B). This observation Data analysis and statistical treatments were conducted in R. indicates that transcriptome rewiring by AS during single and Data transformation, Pearson correlations, and ANOVA were simultaneous Cu and Fe deficiency targets a coreset of transcripts computed using the stats and agricolae package (available at unchanged as regards of abundance. The Comprehensive R Archive Network, CRAN).1 Heatmaps To identify expression patterns in the effect of AS on the with hierarchical clustering were elaborated using the pheatmap transcriptome, DAS were used to elaborate a heatmap with package (available at CRAN; see text footnote 1). Significant hierarchical clustering. As depicted in Figure 1C, seven main enrichment in Gene Ontology terms (adjusted-p-value ≤ 0.05, clusters of DASs were detected using the Ward D2 method. With Fisher’s exact test) was carried out in Thalemine2 and redundant 1 3 https://cran.r-project.org/ http://revigo.irb.hr/ 2 4 https://bar.utoronto.ca/thalemine/ https://mapman.gabipd.org/es_ES/home Frontiers in Plant Science | www.frontiersin.org 3 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency FIGURE 1 | Analysis of differential splicing events under individual and simultaneous copper and iron deficiency. RNA-Seq read counts covering exonic and intronic regions from the transcriptome profiles of rosette leaves treated for single and double copper and iron deficiency reported in Garcia-Molina et al. (2020) were obtained with the ASpli package (see “Materials and Methods”). (A) Classification of AS events into intron retention (IR), exon skipping (ES) or other events (Other). (B) Euler diagram comparing the fraction of all genes potentially affected by AS, the differentially spliced genes (DSGs) detected and differentially expressed genes (DEGs) reported in Garcia-Molina et al. (2020). (C) Heatmap with hierarchical clustering according to the Ward D2 method with Z-mean for significant changes in percentage of intron retention or bin inclusion (represented as PSI) (p-value ≤ 0.05, two-way ANOVA) under standard conditions (control), copper (–Cu) and iron (–Fe) deficiency or double deficiency (–Cu–Fe). (D) Euler diagrams comparing the fraction of specific DEGs in Garcia-Molina et al. (2020) and specific DSGs for each treatment. Specific DEGs and DSGs were defined as the common fraction in multiple comparisons among significant changes in each of the conditions (absolute fold-change ≥ 2 in pair-wise comparisons, adjusted-p-value ≤ 0.05, Tukey’s test; Supplementary Figure 1). the exception of the two minor clusters I and VI (486 AS events, less than 10% of DEGs being DSGs – was found (Figure 1D), 12.04%) that represented DAS under both single deficiencies, further confirming that changes in transcript abundance were not the rest of the clusters included AS events specific to each of motivated by significant splicing events. the conditions, i.e., cluster II (311 AS events, 7.93%) contained changes mainly taking place during Cu deficiency, clusters III and VII (1,323 AS events, 33.77%) changes only occurring Specific Alternative Splicing Events under Fe deficiency, and clusters IV and V (1,801 AS events, Under the Combinatorial Response to 45.97%) changes specific to double Cu and Fe deficiency. Another remarkable trend was that the main fraction of all identified DAS Copper and Iron Deficiency Target (68.94%) was motivated by increases in AS rates (Figure 1C). Biosynthetic Pathways for Changing Since our analysis unveiled that DAS was mainly treatment- Amino Acids specific, the fraction of genes that specifically underwent Given the divergence in the coreset of genes that experienced AS events under each of the treatments was captured by changes in AS and transcript abundance, we interrogated means of multiple comparisons of DAS that displayed an whether different biological processes would be regulated in absolute fold-change of at least two in pair-wise comparisons each case. To this end, functional annotation of specific DEGs (adjusted-p-value ≤ 0.05, Tukey’s test; Supplementary Figure 1 and DSGs was conducted by significant enrichment of non- and Supplementary Table 3). Thus, 214 specific Cu-DSGs, redundant gene ontology (GO) terms (adjusted-p-value ≤ 0.05, 125 specific Fe-DSGs, and 1,286 specific CuFe–DSGs were Fisher’s exact test, and filter 0.5 in REVIGO, Supek et al., 2011). identified. Although Cu deficiency alone had a low impact on Cu deficiency did not lead to significant enrichments of neither transcriptome changes, the number of Cu–DSGs was twice that DSGs nor DEGs, due to the low impact of the treatment, whereas of Fe–DSGs (Supplementary Figure 1). The existence of a Fe-DEGs rendered enrichment in 12 terms mainly related to Fe combinatorial effect in simultaneous Cu and Fe deficiency was homeostasis (“Iron ion homeostasis,” “Iron ion transport,” or also demonstrated at the AS level since the number of specific “Regulation of iron ion import”), hypoxia (“Response to oxygen CuFe–DSGs was four-fold higher than the sum of those found levels,” “Response to decreased oxygen levels”), and abiotic under both single deficiencies. Again, a small overlap between stress response (“Response to abiotic stimulus”) (Figure 2). specific DSGs and specific DEGs per condition – quantified as However, 26 and four non-redundant terms were found for Frontiers in Plant Science | www.frontiersin.org 4 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency FIGURE 2 | Functional annotation of specific changes in transcriptome and alternative splicing under single and simultaneous copper and iron deficiency. Bubble plot depicting differences in specific DEGs and DSGs detected under single and double copper and iron deficiency treatments (Cu, Fe, and CuFe, respectively). Specific DEGs and DSGs were analyzed for significant gene ontology (GO) term enrichment (adjusted-p-value ≤ 0.05, Fisher’s test) and filtered for redundancy by REVIGO (filter 0.5). The size of the bubble is proportional to the –log10-transformation of the adjusted-p-value in the Fisher’s test. CuFe–DEGs and CuFe-DSGs, respectively (Figure 2). CuFe– our data suggest that DSGs detected under single Cu and Fe DEGs were related to general responses to both biotic and abiotic deficiencies might be the consequence of either the necessity to stress, (“Response to stress,” “Response to abiotic stimulus,” fine-tune isolated sets of transcripts, or aberrant splicing events “Response to biotic stimulus,” “Response to bacterium”), due to stress imposed by the treatments. In contrast, AS events translation (“Ribosome biogenesis,” “Maturation of LSU- under simultaneous Cu and Fe deficiency might rather obey a rRNA”, “Ribonucleoprotein complex subunit organization”), more general regulatory strategy aimed at adjusting plant amino nitrogen homeostasis (“Response to nitrogen compound”), acid composition. mitochondrion biology (“Mitochondrion organization,” Previously, it was shown that coincident Cu and Fe limitation “Mitochondrial transport”), or cell cycle (“Regulation of imposed a particular reconfiguration of the amino acid fraction in cell cycle”). On the other hand, CuFe-DSGs participate in adult leaves, and how seedlings tolerant to the double deficiency pathways for compound salvage and amino acid metabolism, via suppression of the cytosolic FUMARASE2 restored amino among others (Figure 2). These observations indicate that the acid levels to those under standard conditions (Garcia-Molina reprogramming of the majority of biological processes involved et al., 2020, 2021). Due to the potential prevalence of targeting in the response to single Fe and double Cu and Fe deficiencies pathways related to amino acid metabolism and the relevance takes place via changes in transcript abundance. Furthermore, of amino acids in plant homeostasis during simultaneous Cu Frontiers in Plant Science | www.frontiersin.org 5 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency TABLE 1 | Identified Mapman bins related to amino acid metabolism. Description of the bin DEG Description of the gene Amino acid metabolism.synthesis Aspartate.aspartate aminotransferase AT5G19550 ASPARTATE AMINOTRANSFERASE 2 (ASN2) Aspartate.aspartate aminotransferase AT1G72330 ALANINE AMINOTRANSFERASE 2 (ALAAT2) Serine-glycine-cysteine group.serine.phosphoserine aminotransferase AT3G19030 Unknown Serine-glycine-cysteine group.cysteine AT5G65720 Alanine-glyoxylate aminotransferase, putative Serine-glycine-cysteine group.cysteine.OASTL AT4G14880 O-ACETYLSERINE (THIOL) LYASE ISOFORM A1 (OASA1) Amino acid metabolism.degradation Glutamate family.glutamine AT5G13780 N-TERMINAL ACETYLTRANSFERASE 10 (NAA10) Description of the bin DSG Description of the gene Amino acid metabolism.synthesis GABA.Glutamate decarboxylase AT1G65960 GLUTAMATE DECARBOXYLASE 2 (GAD2) Aspartate.aspartate aminotransferase AT5G19550 ASPARTATE AMINOTRANSFERASE 2 (ASP2) Alanine.alanine aminotransferase AT1G70580 ALANINE-2-OXOGLUTARATE AMINOTRANSFER. 2 (AOAT2) Alanine.alanine-glyoxylate aminotransferase AT2G13360 ALANINE:GLYOXYLATE AMINOTRANSFERASE (AGT) Glutamate family.proline.d 1-pyrroline-5-carboxylate synt AT2G39800 DELTA1-PYRROLINE-5-CARBOXYLATE SYNTH. 1 (P5CS1) Aspartate family.asparagine.asparagine synthetase AT5G65010 ASPARAGINE SYNTHETASE 2 (ASN2) Aspartate family.methionine AT4G34840 METHYLADENOSINE NUCLEOSIDASE 2 (MTN2) Aspartate family.methionine.homocysteine S-methyl AT3G22740 HOMOCYSTEINE S-METHYLTRANSFERASE 3 (HMT3) Aspartate family.methionine.homocysteine S-methyl AT1G78140 Methyltransferase-related Aspartate family.lysine.diaminopimelate epimerase AT3G53580 Diaminopimelate epimerase family protein Aspartate family.misc.homoserine.bifunctional aspartate kinase/homoserine AT4G19710 Aspartate kinase/homoserine dehydrogenase, putative dehydrogenase Aspartate family.misc.homoserine.aspartate semialdehyde dehydrogenase AT1G14810 Semialdehyde dehydrogenase family protein Branched chain group.leucine specific.3-isopropylmalate dehydrogenase AT5G14200 3-Isopropylmalate dehydrogenase, putative Serine-glycine-cysteine group.glycine.glycine transamin AT1G70580 ALANINE-2-OXOGLUTARATE AMINOTRANSFER. 2 (AOT2) Serine-glycine-cysteine group.glycine.serine glyoxylate aminotransferase AT2G13360 ALANINE:GLYOXYLATE AMINOTRANSFERASE (AGT) Serine-glycine-cysteine group.cysteine.OASTL AT3G22460 O-ACETYLSERINE (THIOL) LYASE ISOFORM A2 (OASA2) Serine-glycine-cysteine group.cysteine.SAT AT2G17640 SERINE O-ACETYLTRANSFERASE (ATSERAT3;1) Aromatic aa.tryptophan.phosphoribosyanthranilate isom AT5G05590 PHOSPHORIBOSYLANTHRANILATE ISOMERASE 2 (PAI2) Aromatic aa.tryptophan.phosphoribosyanthranilate isom AT1G07780 PHOSPHORIBOSYLANTHRANILATE ISOMERASE 1 (PAI1) Aromatic aa.tryptophan.indole-3-glycerol phosphate synt AT5G48220 Indole-3-glycerol phosphate synthase, putative (InGPS) Aromatic aa.tryptophan.tryptophan synthase AT5G54810 TRYPTOPHAN SYNTHASE BETA-SUBUNIT 1 (TSB1) Aromatic aa.tryptophan.tryptophan synthase AT4G02610 Tryptophan synthase, alpha subunit, putative (TSA1) Histidine.glutamine amidotransferase/cyclase AT4G26900 IMIDAZOLEGLYCEROL-PHOSPHATE SYNTAHSE (HISN4) Amino acid metabolism.degradation Aspartate family.asparagine.L-asparaginase AT5G08100 L -Asparaginase/ L -asparagine amidohydrolase (ASPGA1) Branched-chain group.shared AT3G08860 Alanine-glyoxylate aminotransferase, putative (PYD4) Branched-chain group.leucine AT4G34030 3-METHYLCROTONYL-COA CARBOXYLASE (MCCB) Branched chain group.isoleucine AT5G48880 PEROXISOMAL 3-KETO-ACYL-COA THIOLASE 2 (KAT5) Aromatic aa.tryptophan AT5G65940 BETA-HYDROXYISOBUTYRYL-COA HYDROLASE 1 (CHY1) Specific differentially expressed genes (DEGs) and differentially spliced genes (DSGs) detected in the double deficiency were mapped onto the category “central metabolism” in Mapman. Bins were sorted for synthesis or degradation and presented with the bin description, the gene ID, and the description of the gene. and Fe deficiency, CuFe–DSGs were mapped into Mapman bins acid metabolism and only overlapped with CuFe–DSGs for for the category “central metabolism” (Thimm et al., 2004) to ASPARTATE AMINOTRANSFERASE 2 (ASP2) (Table 1). gain more insight as to which amino acid reactions were affected To address the relevance of AS changes in the amino acid by AS events. In this way, 28 of the 175 bins (Supplementary composition of plants, we recovered the metabolome profiles Table 4) for central metabolism mapped by specific CuFe–DSGs in response to Cu, Fe, and the double Cu and Fe deficiency were involved in biosynthetic reactions for the aromatic amino treatments after 5 and 10 days described in Garcia-Molina et al. acid Trp, for the group of serine-glycine-cysteine, or for the (2020). Data were filtered for compounds with unknown mass Asp family, as well as catabolic reactions for the branched- and metabolites that were not present in all replicates. In this chained amino acids leucine and isoleucine (Table 1). On the way, 76 metabolites were retained (Supplementary Table 1), other hand, CuFe–DEGs mapped into five bins related to amino and the median of normalized abundance was used to draw Frontiers in Plant Science | www.frontiersin.org 6 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency FIGURE 3 | Metabolome profiles in response to single and double deficiency of copper and iron. Heatmap with hierarchical clustering according to the Ward method with Z-means for the median of the relative concentration of metabolites from rosette leaves exposed to standard conditions (control, Cont), copper (–Cu), and iron (–Fe) deficiency or double deficiency (–Cu–Fe) for 5 (n = 4) or 10 days (n = 7) in Garcia-Molina et al. (2020; Supplementary Table 1). For each cluster in the heatmap the trend is depicted as the average of the Z-mean of the compounds along with the name of the metabolites. Amino acids are highlighted in bold. a heatmap with hierarchical clustering. Accordingly, four main amino acid composition to plant necessities under the double Cu patterns were identified (Figure 3). Metabolites in cluster I and Fe deficiency. (22 metabolites) accumulated under control and Cu deficient conditions overtime and displayed a pronounced increase under Transcripts Encoding Enzymes Central Fe deficiency at both 5 and 10 days of treatment, while being to Tryptophan and Asparagine decreased under simultaneous Cu and Fe deficiency (Figure 3). This pattern is of special relevance as it recapitulates the Biosynthesis Display Intron Retention behavior of fumaric acid, adenine, the amino acids Asn, Phe, Events Under Simultaneous Copper and Trp and the Trp-derivative tyramine, which were previously Iron Deficiency identified as significantly altered metabolites (SAMs) in the With the aim of dissecting the effect of AS on metabolic pathways combinatorial response to double Cu and Fe deficiency (Garcia- for amino acids exclusively changing under the combinatorial Molina et al., 2020). Compounds in cluster II (13 metabolites) Cu and Fe deficiency, we focused on those for Trp and Asn since rose in content after 5 days of Fe deficient treatment, but then they are two SAMs and the Mapman bins mapped by CuFe-DSGs remained steady under all conditions after 10 days. Cluster III allowed us to extract central features in their biosynthesis. This is (14 metabolites) included metabolites that increased under both the case of PHOSPHORIBOSYLANTHRANILATE ISOMERASE Fe deficient and double Cu and Fe deficient treatments, with a 1 and 2 (PAI1/2), INDOLE-3-GLYCEROL PHOSPHATE more remarkable increase under double Cu and Fe deficiency SYNTHASE (InGPS), TRYPTOPHAN SYNTHASE A (TSA1), (Figure 3). Finally, cluster IV (29 metabolites) contains, above and TRYPTOPHAN SYNTHASE BETA-SUBUNIT 1 (TBS1) for all, sugars (trehalose, fructose, galactose, and sorbose) and sugar- Trp (Table 1). For Asp, we found ASP2, the enzyme catalyzing alcohols (myo-inositol, xylitol, and galactitol), which decrease the conversion of oxaloacetate to Asp in the first step of Asn in content after 10 days under all treatments, with a more biosynthesis, ASPARAGINE SYNTHETASE 2 (ASN2), the main pronounced drop under both treatments lacking Fe (Figure 3). enzyme mediating the condensation of Asp and Gln to render Interestingly, cluster I – which contains the SAMs under Asn, and L-ASPARAGINASE (ASPGA1), an enzyme that can simultaneous Cu and Fe deficiency as mentioned above – degrade Asn to render Asp again (Table 1). included the main fraction of amino acids that are end products To first infer potential molecular mechanisms regulating Trp of the metabolic reactions identified by Mapman bins using and Asn biosynthetic pathways, the transcriptome, proteome, CuFe-DSGs, namely glutamine (Gln), Asn, and Trp, as well and metabolome data generated in Garcia-Molina et al. (2020) as the rest of the aromatic amino acids (Phe and tyrosine, were integrated as depicted in Figure 4. Regarding Trp Tyr), and tyramine (Figure 3). Consequently, we hypothesized biosynthesis, PAI1 and 2 showed antagonistic trends in transcript that AS could operate as a new layer in the combinatorial abundance under both Fe and double Cu and Fe deficient response to refine transcriptome changes in order to adjust conditions, as PAI1 levels dropped under both treatments, Frontiers in Plant Science | www.frontiersin.org 7 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency FIGURE 4 | Molecular changes in tryptophan and asparagine biosynthetic pathways in response to single and double deficiency of copper and iron. (A,B) Overview of the metabolic reactions involved in tryptophan (Trp, A) and asparagine (Asn, B) biosynthesis. Depicted are the metabolic intermediates and the enzymes catalyzing each of the reactions. Z-means of transcript counts (Fragments Per Kilobase Million, FPKM), proteins (LC-MS chromatography peak intensity), and metabolite (normalized concentration to 13 C-sorbitol and fresh weight) for each condition at 10 days, as reported in Garcia-Molina et al. (2020), were plotted. PAI1,2, PHOSPHORIBOSYLANTHRANILATE ISOMERASE 1 AND 2; InGPS, INDOLE-3-GLYCEROL PHOSPHATE SYNTHASE; TBS1, TRYPTOPHAN SYNTHASE BETA-SUBUNIT 1; TSA1, TRYPTOPHAN SYNTHASE A; ASP2, ASPARTATE AMINOTRANSFERASE 2; ASN2, ASPARAGINE SYNTHETASE 2; ASPGA1, L -ASPARAGINASE. TABLE 2 | Correlation among transcriptome, proteome and metabolome changes in the tryptophan and asparagine biosynthesis pathways. RNA Prot Trp (RNA/Prot) Tyramine (RNA/Prot) RNA Prot Asp (RNA/Prot) Gln (RNA/Prot) Asn (RNA/Prot) PAI1 NA −0.64/NA −0.97/NA ASP2 0.99 −0.55/−0.65 0.67/0.57 0.79/0.70 PAI2 NA −0.23/NA 0.39/NA ASN2 0.22 0.48/−0.61 0.93/0.54 0.86/0.67 InGPS −0.87 −0.58/0.18 −0.97/NA ASPGA1 NA −0.62/NA 0.60/NA 0.73/NA TSA1 −0.96 −0.84/0.76 −0.99/0.98 TSB1 0.95 0.24/0.49 0.24/0.49 Pearson correlation for pair-wise comparisons among transcript (RNA) and protein (Prot) abundance or metabolite content as indicated. Pearson correlation coefficients r > 0.65 in absolute value are highlighted in bold as relevant. whereas those for PAI2 increased (Figure 4A) – proteome under double Cu and Fe deficient conditions, except for profiles did not provide information at the protein level. TSA1 (r = −0.99 for the transcript and 0.76 for the protein; Transcript and protein amounts of the remaining intermediate Figure 4A and Table 2). However, a better correlation between enzymes, InGPS, TSA1, and TBS1, displayed changes under transcripts and proteins of intermediate enzymes and tyramine both treatments lacking Fe, though not always coincident in concentration – the degradative product of Trp – was found. This trend (absolute r > 0.85; Table 2). Indeed, all changes at the finding suggests that treatments limiting Fe as well as Cu and Fe protein level represented increases in abundance, whereas the impose the accumulation of protein for the enzymes mediating InGPS and TSA1 transcript amounts decreased (r = −0.87 and Trp biosynthesis, regardless of transcript levels, although this −0.96) and those for TSB1 increased (r = 0.95; Figure 4A response does not allow Trp accumulation in the double Cu and Table 2). However, the pattern of transcript and protein and Fe deficiency. On the other hand, both ASP2 transcript amounts of the intermediate enzymes could not explain changes and protein levels showed perfect synchronization (r = 0.99), in Trp concentration (r < 0.65) due to the drop experienced increasing under both Fe and double Cu and Fe deficient Frontiers in Plant Science | www.frontiersin.org 8 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency FIGURE 5 | Visualization of alternative splicing events in the transcripts involved in tryptophan biosynthesis under single and simultaneous copper and iron deficiency. Log10 -transformed read counts were used to represent the RNA-Seq coverage of intronic and exonic regions of PHOSPHORIBOSYLANTHRANILATE ISOMERASE 1 AND 2 (PAI1, 2), INDOLE-3-GLYCEROL PHOSPHATE SYNTHASE (InGPS), TRYPTOPHAN SYNTHASE BETA-SUBUNIT 1 (TBS1), TRYPTOPHAN SYNTHASE A (TSA1) under standard conditions (Cont) and single and double copper and iron deficiencies (–Cu, –Fe, and –Cu–Fe). Differences in the presence of intronic regions are depicted as asterisks (for changes in one replicate under –Fe or –Cu–Fe), or as orange lines (changes exclusive to –Cu–Fe conditions). Blue lines represent the gene model in TAIR10. conditions, although it did not explain the drop in Asp under the As a general trend, Fe and double Cu and Fe deficiency led double deficiency (r = −0.55 and −0.65, respectively; Figure 4B to differential coverage of intronic regions in at least one of and Table 2). Transcript levels of ASN2 exhibited the same the replicates. This is the case of PAI1 (introns 5 and 6), pattern as Gln and Asn (r = 0.93 and 0.86, respectively), although InGPS (intron 8), ASP2 (introns 1, 3, 7, and 10), and ASN2 protein levels tended to increase under single and double Cu (intron 10) (see asterisks in Figures 5, 6). In three genes, the and Fe deficiencies (Figure 4B and Table 2). Finally, ASPGA1 presence of additional introns was observed in only one replicate could only be investigated for transcript levels, which showed a for the double Cu and Fe deficiency treatment, namely TSA1 good correlation with Asn concentration (r = 0.73; Figure 4B (introns 6 and 7), ASN2 (intron 3), and ASPGA1 (intron 2) (see and Table 2). Collectively, our molecular analysis confirms asterisks in Figures 5, 6). Furthermore, we detected consistent that the specific drop in Trp and Asn concentration during IR events exclusively taking place under simultaneous Cu and simultaneous Cu and Fe deficient conditions cannot be explained Fe deficiency for InGPS (intron 6 and 9, Figure 5) in the Trp by fluctuations in transcript or protein abundance of the enzymes biosynthesis pathway and for all three selected enzymes for participating in the biosynthesis of these amino acids. Asn biosynthesis, i.e., ASP2 (intron 9), ASN2 (intron 9), and To further investigate the regulation of Trp and Asn ASPGA1 (intron 3) (Figure 6). This observation suggests that the biosynthesis, density plots were elaborated to visualize the RNA- detrimental consequences related to Fe removal and, especially, Seq coverage of intronic and exonic regions of the transcripts the double Cu and Fe deficiency causes misfunctions in the AS of the above-investigated genes (Figures 5, 6). Intron bins machinery, which increases the frequency of different transcript harbored 1–12% of total coverage, depending on the gene and isoforms due to IR events. Thus, the incapacity to increase Trp condition (Supplementary Figure 2). To track the most extreme and Asn concentrations, albeit the high levels of biosynthetic differences, coverage maps were then manually curated to filter enzymes under the double Cu and Fe deficiency, could, in part, changes in AS events motivated by differential intron and exon be attributed to the accumulation of non-functional protein composition from those due to differences in count abundance. isoforms under this condition. Frontiers in Plant Science | www.frontiersin.org 9 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency FIGURE 6 | Visualization of alternative splicing events in the transcripts involved in asparagine biosynthesis under single and simultaneous copper and iron deficiency. Log10 -transformed read counts were used to represent the RNA-Seq coverage of intronic and exonic regions of ASPARTATE AMINOTRANSFERASE 2 (ASP2), ASPARAGINE SYNTHETASE 2 (ASN2), and L-ASPARAGINASE (ASPGA1) under standard conditions (Cont) and single and double copper and iron deficiencies (–Cu, –Fe, and –Cu–Fe). Differences in the presence of intronic regions are depicted as asterisks (for changes in one replicate under –Fe or –Cu–Fe) or as orange lines (changes exclusive to –Cu–Fe conditions). Blue lines represent the gene model in TAIR10. DISCUSSION (Ding et al., 2014; Nishida et al., 2017; Kannan et al., 2018; Huang et al., 2019), while Calixto et al. (2018) reported that Transcriptome changes due to AS events in Arabidopsis adult almost half of the DEGs detected in plants cold-treated for rosette leaves exposed to single and double Cu and Fe deficiency 4 days underwent AS. Therefore, AS operates as an independent for 10 days are not coincident with the fraction of transcripts mechanism to refine plant responses to detrimental conditions changing in abundance. Even if 67.53% of the 2,637 DEGs beyond regulating gene expression. reported in Garcia-Molina et al. (2020) could be potentially In addition, changes in AS and transcript amounts resulting affected by AS, our analyses revealed that only 428 DEGs from the interaction between Cu and Fe deficiencies occurred classified as DSGs for the interaction between Cu and Fe according to different patterns. On the one hand, AS is a deficiencies (p-value ≤ 0.05, two-way ANOVA; Figure 1B). condition-dependent response mainly detected under Fe and Previous studies also uncovered minimal overlap fractions double Cu and Fe deficiencies (Figure 1C). On the other between DEGs and DSGs in response to multiple nutrient hand, although specific changes in transcripts under Fe and deficiencies for 4 days, high salt, heat, or elevated CO2 levels simultaneous Cu and Fe deficiencies were found, the major Frontiers in Plant Science | www.frontiersin.org 10 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency fraction of transcript levels displayed an increase under Fe and, therefore, amino acid synthesis would be unnecessary limitation that was more prominent during the double deficiency under this scenario. (Garcia-Molina et al., 2020). Per treatments, despite that Cu Having Mapman bins for central metabolism as a reference shortage for 10 days minimally impacted adult plants, we (Thimm et al., 2004), CuFe–DSGs retrieved genes coding for detected 200 transcripts exclusively undergoing AS under Cu enzymes involved in Gln, Asp, Leu, Ser, Gly, Leu anabolism, and deficiency, which is 10-fold the number of transcripts changing most of the central features in the Asn and Trp biosynthesis in abundance under this condition (Figure 1D). Fe deprivation pathways (Table 1). Interestingly, Gln, Asn, and Trp appeared provokes more profound physiological and molecular changes in the group of amino acids that rose in concentration under Fe than Cu, but only imposed twice the number of Fe-specific deficient conditions and decreased or minimally increased during DSGs than DEGs (262 vs. 125) (Figure 1D). However, Cu and the double deficiency (cluster I, Figure 3). Moreover, Trp and Fe deficiencies applied simultaneously led to the major fraction Asn, as well as the Trp-derivative tyramine, Phe, fumaric acid, of significant changes in AS events. Quantitatively, CuFe–DSGs and adenine, were previously categorized as significantly altered were 2-fold the number of CuFe–DEGs (1,286 vs. 727) and 6- metabolites in Garcia-Molina et al. (2020). To address regulatory to 10-fold the number of DSGs found under single deficiencies, mechanisms in the biosynthesis of metabolites changing in respectively (1,286 vs. 214 and 125) (Figure 1D). This finding response to the combinatorial deficiency, the transcriptome, provides more evidence supporting that combinatorial responses proteome and metabolome profiles previously reported were to simultaneous Cu and Fe deficiency trigger molecular analyzed in combination. Single Fe and double Cu and Fe mechanisms absent under single deficiencies. deficiency imposed similar changes in transcript and protein In line with this, functional annotation of specific amounts for the selected enzymes involved in Trp and Asn transcriptome changes related Fe-DEGs to Fe homeostasis biosynthesis, though not always coincident in trend (absolute and abiotic stress responses, whereas no significant terms for r > 0.85; Figure 4 and Table 2). This indicates that the enzyme biological processes emerged when considering Cu–DEGs, levels are not linearly dependent on the expression of the coding Cu–DSGs, and Fe–DSGs. CuFe–DEGs enriched multiple terms, transcript. Indeed, enzyme amounts always increased under Fe such as ribosome biogenesis, maturation of rRNA, response to and double Cu and Fe deficiency, regardless of the trend displayed cell cycle, oxidative stress, and both biotic and abiotic stimulus by the coding transcript. However, the increase in enzyme levels (Figure 2). However, CuFe–DSGs were involved in metabolic could explain the increase in Trp and Asn concentration under Fe reactions, more precisely in amino acid biosynthesis. This deficiency, but this is contradictory with the drop observed under fact indicates that general stress responses and adjustment simultaneous Cu and Fe deficiency. This observation could be in translational components during simultaneous Cu and attributed to either protein dysfunctionality, lack of intermediate Fe deficiency would be achieved by changes in transcript availability, or faster consumption of the end products. Further abundance, while certain aspects of plant metabolism might be analysis of the Trp pathway showed that tyramine – a degradative systematically refined by AS. product of Trp – displayed a less dramatic decay under the Amino acids play a central role in the combinatorial double Cu and Fe condition in comparison with Trp. In that case, response to simultaneous Cu and Fe deficiency in Arabidopsis. better correlations between tyramine concentration and enzyme Compared with standard and Cu deficient conditions, amino amounts were found (r > 0.75), suggesting that tyramine would acid pools tend to rise under Fe deficiency, already after accumulate under the double deficiency as result of increased 5 days of treatment, whereas under the double deficiency, Trp degradation (Figure 4 and Table 2). On the other hand, this increase is more attenuated (Garcia-Molina et al., 2020). Gln and Asp decreased in the same proportion as Asn under Metabolome profiling of Arabidopsis seedlings under double the combinatorial deficiency (Figure 4 and Table 2), ruling Cu and Fe deficiency uncovered a significant 2-fold increase out the overaccumulation of metabolic intermediates caused by in the amino acid fraction as a result of growth impairments the drop in Asn. and chloroplast misfunction. However, abrogation of Arabidopsis Mechanistically, AS regulates gene expression either by the cytosolic fumarase FUMARASE2 (FUM2) conferred improved generation of transcript isoforms with altered stability, or by growth and photosynthesis rates under simultaneous Cu and Fe the production of modified protein versions with different deficiency, and led to a barely unaltered amino acid composition functionality (Kelemen et al., 2013). In plants, IR is the most in comparison with standard conditions (Garcia-Molina et al., frequent AS event and has been well described as a phenomenon 2021). Considering the interplay of Cu and Fe in sustaining occurring during unfavorable conditions (Kalyna et al., 2011; antioxidant activities mediated by superoxide dismutases and Drechsel et al., 2013; Kwon et al., 2014; Filichkin et al., 2015; electron transport chains in chloroplast and mitochondrion Ling et al., 2018). Although we found differences in AS motivated (Kliebenstein et al., 1998; Abdel-Ghany et al., 2005; Yamasaki by differential count accumulation in introns, we described IR et al., 2009; Bernal et al., 2012), the detrimental consequences events in the Trp and Asn biosynthesis pathways under Fe and, of the simultaneous limitation of Cu and Fe would prevent especially, under double Cu and Fe deficiency (Figures 5, 6) the proper function of photosynthesis and respiration to obtain that we attributed to misfunction of the splicing machinery energy based on carbon skeletons. Given the potentiality of due to the stress conditions imposed by the treatments. IR has amino acids as energy sources (Hildebrandt et al., 2015), been proposed to act as a strategy to promote transcript decay it could be likely that protein catabolism might act as a via the interruption of the reading frame (Kalyna et al., 2011; compensatory mechanism to fulfill plant energetic demands Drechsel et al., 2013), however, the biosynthetic enzymes for Frontiers in Plant Science | www.frontiersin.org 11 January 2022 | Volume 13 | Article 827828 Mancini and Garcia-Molina Alternative Splicing Under CuFe Deficiency Trp and Asn that we analyzed increased at the protein level, FUNDING regardless of the behavior of the coding transcript (Figure 4). Consequently, we proposed that the IR events taking place in This work was also supported by grant CEX2019-000902- the Trp and Asn biosynthesis pathways during the combinatorial S funded by MCIN/AEI/10.13039/501100011033 and by the response result in the codification of protein isoforms that are CERCA Programme/Generalitat de Catalunya. more stable, though less efficient in function. Nevertheless, we are not aware of any comprehensive study addressing the functional consequences of AS for the enzyme isoforms that we have ACKNOWLEDGMENTS described here. Similarly, the necessity of a specific regulation of Trp and Asn concentration during the double Cu and Fe Marcelo Yanovsky (Instituto de Investigaciones Bioquímicas deficiency remains elusive. Therefore, the role of such AS events de Buenos Aires - Fundación Instituto Leloir, Argentina) as well as the changes in Asn and Trp concentration under was acknowledged for encouraging comments in the design the combinatorial Cu and Fe deficiency are open questions that and interpretation of the analysis carried out. Helena deserve further investigation. Kruyer was acknowledged for critically reading and proof- Taken together, our analysis sheds some new light on editing the manuscript. the systemic reprogramming of molecular changes that plants undergo during the combinatorial response to simultaneous Cu and Fe deficiency by including AS as an independent mechanism SUPPLEMENTARY MATERIAL to regulate metabolic reactions that are not adjusted at either the transcript nor the protein level. The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2022. 827828/full#supplementary-material DATA AVAILABILITY STATEMENT Supplementary Figure 1 | Analysis of differential splicing events under individual The original contributions presented in the study are included and simultaneous deficiency of copper and iron. Venn diagrams for multiple in the article/Supplementary Material, further inquiries can be comparisons among differentially splicing events per treatment according to an absolute fold-change of at least 2 in pair-wise comparisons directed to the corresponding author. (adjusted-p-value ≤ 0.05, two-way ANOVA with post hoc Tukey’s test). Supplementary Figure 2 | Primary analysis of intron retention in transcripts AUTHOR CONTRIBUTIONS involved in tryptophan and asparagine biosynthesis under single and simultaneous copper and iron deficiency. 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Bot. 69, 2659– Conflict of Interest: The authors declare that the research was conducted in the 2675. doi: 10.1093/jxb/ery062 absence of any commercial or financial relationships that could be construed as a Mancini, E., Rabinovich, A., Iserte, J., Yanovsky, M., and Chernomoretz, A. (2021). potential conflict of interest. ASpli: integrative analysis of splicing landscapes through RNA-Seq assays. Bioinformatics 37, 2609–2616. doi: 10.1093/bioinformatics/btab141 Publisher’s Note: All claims expressed in this article are solely those of the authors Marquez, Y., Brown, J. W., Simpson, C., Barta, A., and Kalyna, M. (2012). and do not necessarily represent those of their affiliated organizations, or those of Transcriptome survey reveals increased complexity of the alternative splicing the publisher, the editors and the reviewers. Any product that may be evaluated in landscape in Arabidopsis. Genome Res. 22, 1184–1195. doi: 10.1101/gr.134106. this article, or claim that may be made by its manufacturer, is not guaranteed or 111 endorsed by the publisher. Morrissey, J., and Guerinot, M. L. (2009). Iron uptake and transport in plants: the good, the bad, and the ionome. Chem. Rev. 109, 4553–4567. doi: 10.1021/ Copyright © 2022 Mancini and Garcia-Molina. This is an open-access article cr900112r distributed under the terms of the Creative Commons Attribution License (CC BY). Nishida, S., Kakei, Y., Shimada, Y., and Fujiwara, T. (2017). Genome-wide analysis The use, distribution or reproduction in other forums is permitted, provided the of specific alterations in transcript structure and accumulation caused by original author(s) and the copyright owner(s) are credited and that the original nutrient deficiencies in Arabidopsis thaliana. Plant J. 91, 741–753. doi: 10.1111/ publication in this journal is cited, in accordance with accepted academic practice. No tpj.13606 use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Plant Science | www.frontiersin.org 13 January 2022 | Volume 13 | Article 827828