Skip to main content
PeerJ logoLink to PeerJ
. 2019 Sep 25;7:e7739. doi: 10.7717/peerj.7739

Identification of genes encoding ALMT and MATE transporters as candidate aluminum tolerance genes from a typical acid soil plant, Psychotria rubra (Rubiaceae)

Akira Iguchi 1,, Kazutsuka Sanmiya 2, Kenta Watanabe 3
Editor: Joseph Gillespie
PMCID: PMC6765359  PMID: 31579611

Abstract

To understand how tropical plants have adapted to acid soils, we analyzed the transcriptome of seedlings of Psychotria rubra, a typical species found on acid soils. Using RNA-seq, we identified 22,798 genes, including several encoding proteins of the Al3+-activated malate transporter (ALMT) and multidrug and toxic compound extrusion (MATE) families. Molecular phylogenetic analysis of ALMTs and MATEs revealed the grouping of those from P. rubra, which may be useful to select targets for elucidating the molecular basis of P. rubra adaptation to acid soils in the future. The transcriptome datasets obtained in this study would help us to further understand the physiological and ecological aspects of soil adaptation of Psychotria species.

Keywords: Psychotria, Plant, Acid soils, Transcriptome, MATE, ALMT

Introduction

Understanding how plants adapt to various soils is essential in plant biology (Hiradate, Ma & Matsumoto, 2007) because plants are sessile and need to grow roots in settled soils. Adaptation to acid soils is an important issue because acid soils cover a considerable part of Earth’s arable land and prevent agriculture of most plants (Von Uexküll & Mutert, 1995). In acid soils, aluminum is toxic to root tip growth, and various aspects, from molecular to physiological, of the mechanisms of aluminum toxicity have been explored in detail (reviewed in Ma, 2007).

Proteins of the Al3+-activated malate transporter (ALMT) and multidrug and toxic compound extrusion (MATE) families are likely involved in plant adaptation to acid soils (Delhaize, Gruber & Ryan, 2007; Delhaize, Ma & Ryan, 2012; Ma, 2007; Ma, Chen & Shen, 2014). ALMTs and MATEs release organic acids (malate and citrate, respectively), which bind Al3+ and detoxify it. ALMTs and MATEs related to aluminum tolerance have been identified in model and agricultural plants (wheat: Sasaki et al., 2004; barley: Delhaize et al., 2004; Furukawa et al., 2007; maize: Maron et al., 2010; Arabidopsis: Hoekenga et al., 2006; Liu et al., 2009), but the composition of those families in non-model wild plants has hardly been explored.

Psychotria (Rubiaceae) is a highly diversified genus comprising more than 1,600 species distributed in all tropical and some subtropical regions (Hamilton, 1989; Davis et al., 2001; Razafimandimbison et al., 2014). Because Psychotria species adapt to several types of soils (e.g., soils with high concentrations of nickel; Merlot et al., 2014), the genus is an ideal target to use to understand how adaptation of wild plants to different types of soils has evolved. In this study, we report ALMTs and MATEs of P. rubra, which grows on acid soils (Miyawaki, 1989).

Materials and Methods

Sampling, RNA extraction, RNA-seq library preparation, and sequencing

Seeds of P. rubra were collected on Mt. Nago-dake, in the north of Okinawa Island, and seedlings were grown in a greenhouse of the National Institute of Technology, Okinawa College (Fig. 1). RNA was extracted from the seedlings (three–five cm height) using an RNeasy Plant Mini kit (Qiagen, Hilden, Germany). An RNA-seq library was prepared using a TruSeq Stranded mRNA Sample Prep Kit (Illumina, San Diego, CA, USA). The library was sequenced (100-bp paired-end reads) on an Illumina HiSeq 2500 platform. The above procedures on RNA-seq were outsourced to Hokkaido System Science Corporation, Japan.

Figure 1. Psychotria rubra.

Figure 1

(A) Shrub on Mount Nago-dake, Okinawa, Japan. (B) Seedlings.

De novo assembly and annotation of transcriptome sequences

FASTQ files were filtered, the reads with poor-quality bases (Q < 20) and those shorter than 20-bp were excluded, and adapter sequences were removed in cutadapt v. 1.9.1 software (Martin, 2011). PCR duplicates that arose during library preparation were removed by ConDeTri software (Smeds & Künstner, 2011). The remaining paired-end reads were assembled in Trinity v. 2.8.4 software (Grabherr et al., 2011) with the default options. Open reading frames of >150 amino acids were identified by using TransDecoder software (Haas et al., 2013) and the results of BLASTP searches within the Swiss-Prot database (e-value <1e−5). Redundant amino acid sequences were removed in CD-HIT v. 4.7 software (−c 0.95; Li & Godzik, 2006). The remaining sequences were used as queries in BLASTP searches (e-value <1e−5) of Arabidopsis thaliana sequences (TAIR10; Swarbreck et al., 2007) and selected sequences assumed to be P. rubra itself. Basic information on sequences was obtained in SeqKit v. 0.9.3 software (Shen et al., 2016). Sequence data are accessible under the DNA Data Bank of Japan (DDBJ) Sequence Read Archive (accession: DRA008339). The raw data has been also available at Figshare (https://doi.org/10.6084/m9.figshare.7848425.v2).

Extraction of ALMTs and MATEs of P. rubra and molecular phylogenetic analysis

We searched for P. rubra ALMTs and MATEs by BLASTP (e-value <1e−5) using sequences of TaALMT1 (UniProt database ID: Q76LB1) and HvAACT1 (UniProt ID: A7M6U2; this was the first MATE identified in barley (Furukawa et al., 2007) as queries). We then performed BLASTP searches against the Swiss-Prot database (e-value <1e−5) with each ALMT and MATE of P. rubra and selected the top 10 hits for each. The amino acid sequences of ALMTs and MATEs from P. rubra and related sequences from Swiss-Prot and other studies (Dreyer et al., 2012; Liu et al., 2016) were aligned in MAFFT v. 7.407 software (Katoh & Standley, 2013). We excluded four P. rubra ALMT sequences (Prub_02169, Prub_02171, Prub_08405, Prub_08554) from the following analysis because of poor alignment. We selected only plant MATEs, including HvAACT1 and those from (Liu et al., 2016), for the following analysis. Neighbor-joining trees of ALMTs and MATEs were constructed in MEGA7 software (Kumar, Stecher & Tamura, 2016) with the following settings: Poisson model, Uniform rates, and Pairwise deletion. To evaluate the confidence of phylogenetic trees, bootstrap tests were performed with 1,000 replicates.

Results and Discussion

Our RNA-seq analysis of P. rubra yielded 57,110,261 paired-end reads, of which 53,994,410 remained after filtering. De novo assembly of the remaining reads resulted in 131,578 contigs (Table 1), in which we found 24,687 non-redundant amino acid sequences; 22,798 of them were expected to originate from P. rubra itself as indicated by BLASTP analysis of TAIR10 (the remaining 1,889 sequences were almost no-hit in Swiss-Prot database or included those from microorganisms, etc). Among these 22,798 sequences, 19,701 ones were hit against Swiss-Prot database, and gene ontology (GO) numbers were found in 1,0348 ones. From these sequences, we found 14 ALMTs and 12 MATEs (Table 2).

Table 1. Summary of de novo assembly.

Number of contigs 131,578
Total bases (bp) 161,583,381
Longest contig length (bp) 16,195
Shortest contig length (bp) 185
Average contig length (bp) 1,228
N50 2,007

Table 2. Summary of blastp of TaALMT1 and HvAACT1 against P. rubra amino acid sequences and annotation of P. rubra sequences from the Swiss-Prot database.

Gene name Sequence ID % identity e-value Bit score Annotate description (Swiss-prot) Accession no. (Swiss-prot) e-value (Swiss-prot)
TaALMT1 Prub_08163 45.966 1.05E−110 334 Aluminum-activated malate transporter 2 (AtALMT2) Q9SJE8 3.67E−166
TaALMT1 Prub_08164 49.477 4.78E−90 277 Aluminum-activated malate transporter 2 (AtALMT2) Q9SJE8 1.12E−133
TaALMT1 Prub_10125 43.902 1.19E−77 251 Aluminum-activated malate transporter 12 (AtALMT12) (Quick anion channel 1) O49696 0
TaALMT1 Prub_08553 36.111 3.39E−63 214 Aluminum-activated malate transporter 9 (AtALMT9) Q9LS46 0
TaALMT1 Prub_16333 33.333 6.06E−57 197 Aluminum-activated malate transporter 9 (AtALMT9) Q9LS46 0
TaALMT1 Prub_03305 51.19 5.72E−53 176 Aluminum-activated malate transporter 10 (AtALMT10) O23086 3.21E−59
TaALMT1 Prub_02168 33.772 4.74E−23 98.6 Putative aluminum-activated malate transporter 3 (AtALMT3) Q9LPQ8 1.74E−74
TaALMT1 Prub_02171 27.801 1.10E−22 98.6 Aluminum-activated malate transporter 9 (AtALMT9) Q9LS46 1.99E−141
TaALMT1 Prub_16334 39.655 1.03E−19 86.3 Aluminum-activated malate transporter 9 (AtALMT9) Q9LS46 6.62E−51
TaALMT1 Prub_08405 30.108 2.45E−19 88.6 Aluminum-activated malate transporter 9 (AtALMT9) Q9LS46 9.01E−62
TaALMT1 Prub_08554 51.852 6.42E−12 63.2 Aluminum-activated malate transporter 9 (AtALMT9) Q9LS46 3.20E−27
TaALMT1 Prub_02170 39.062 4.77E−11 62 Aluminum-activated malate transporter 9 (AtALMT9) Q9LS46 7.28E−32
TaALMT1 Prub_02169 30 2.57E−07 51.6 Aluminum-activated malate transporter 4 (AtALMT4) Q9C6L8 1.57E−73
TaALMT1 Prub_02167 38.129 3.26E−07 50.8 Aluminum-activated malate transporter 9 (AtALMT9) Q9LS46 3.96E−26
HvAACT1 Prub_03062 57.752 0 537 Protein DETOXIFICATION 42 (AtDTX42) (Aluminum-activated citrate transporter) (AtMATE) (FRD-like protein) (Multidrug and toxic compound extrusion protein 42) (MATE protein 42) Q9SYD6 0
HvAACT1 Prub_17943 55.955 0 536 Protein DETOXIFICATION 42 (AtDTX42) (Aluminum-activated citrate transporter) (AtMATE) (FRD-like protein) (Multidrug and toxic compound extrusion protein 42) (MATE protein 42) Q9SYD6 0
HvAACT1 Prub_17944 59.432 0 531 Protein DETOXIFICATION 42 (AtDTX42) (Aluminum-activated citrate transporter) (AtMATE) (FRD-like protein) (Multidrug and toxic compound extrusion protein 42) (MATE protein 42) Q9SYD6 0
HvAACT1 Prub_17945 55.894 3.61E−168 485 Protein DETOXIFICATION 42 (AtDTX42) (Aluminum-activated citrate transporter) (AtMATE) (FRD-like protein) (Multidrug and toxic compound extrusion protein 42) (MATE protein 42) Q9SYD6 0
HvAACT1 Prub_03064 63.372 4.58E−147 429 Protein DETOXIFICATION 43 (AtDTX43) (Multidrug and toxic compound extrusion protein 43) (MATE protein 43) (Protein FERRIC REDUCTASE DEFECTIVE 3) (AtFRD3) (Protein MANGANESE ACCUMULATOR 1) Q9SFB0 1.12E−160
HvAACT1 Prub_03541 41.322 1.43E−120 368 Protein DETOXIFICATION 45, chloroplastic (AtDTX45) (Multidrug and toxic compound extrusion protein 45) (MATE protein 45) Q9SVE7 0
HvAACT1 Prub_18165 39.506 2.75E−114 350 Protein DETOXIFICATION 45, chloroplastic (AtDTX45) (Multidrug and toxic compound extrusion protein 45) (MATE protein 45) Q9SVE7 0
HvAACT1 Prub_03065 54.4 6.52E−55 186 Protein DETOXIFICATION 42 (AtDTX42) (Aluminum-activated citrate transporter) (AtMATE) (FRD-like protein) (Multidrug and toxic compound extrusion protein 42) (MATE protein 42) Q9SYD6 3.65E−69
HvAACT1 Prub_03063 53.441 4.31E−52 179 Protein DETOXIFICATION 42 (AtDTX42) (Aluminum-activated citrate transporter) (AtMATE) (FRD-like protein) (Multidrug and toxic compound extrusion protein 42) (MATE protein 42) Q9SYD6 1.00E−66
HvAACT1 Prub_14684 43.541 4.14E−37 137 Protein DETOXIFICATION 44, chloroplastic (AtDTX44) (Multidrug and toxic compound extrusion protein 44) (MATE protein 44) Q84K71 4.41E−94
HvAACT1 Prub_14685 38.174 2.44E−22 96.7 Protein DETOXIFICATION 44, chloroplastic (AtDTX44) (Multidrug and toxic compound extrusion protein 44) (MATE protein 44) Q84K71 4.59E−53
HvAACT1 Prub_18629 23.25 7.67E−14 73.6 Protein DETOXIFICATION 46, chloroplastic (AtDTX46) (Multidrug and toxic compound extrusion protein 46) (MATE protein 46) (Protein EDS5 HOMOLOGUE) Q8W4G3 0

Using 14 ALMTs from P. rubra as queries in a BLASTP search against the Swiss-Prot database, we found 14 homologs, all of plant origin (mainly from Arabidopsis). Using a similar approach, we found 13 homologs of MATEs (six from Arabidopsis and seven from non-plant organisms). Molecular phylogenetic analysis did not detect P. rubra orthologs of TaALMT1 (UniProt ID: Q76LB1) (Fig. 2). ScALMT1 (accession number: ABA62397) from rye (Secale cereale) is the only known clear ortholog of TaALMT1 (Delhaize, Gruber & Ryan, 2007). ALMT1 of Arabidopsis (UniProt ID: Q9SJE9), encoded by an aluminum tolerance gene (Hoekenga et al., 2006), is clearly distinct from TaALMT1 (Delhaize, Gruber & Ryan, 2007). Thus, ALMTs related to aluminum tolerance may have multiple origins. Molecular phylogenetic analysis of MATEs revealed no clear orthologs of HvAACT1 (UniProt ID: A7M6U2) in P. rubra (Fig. 3).

Figure 2. Phylogenetic tree of ALMTs of P. rubra and related proteins.

Figure 2

Sequences of P. rubra are shown using red shades. For sequences other than P. rubra ALMTs, the labels show the UniProt database ID and ALMT type, and ones from Dreyer et al. (2012). Number at each node is the bootstrap value.

Figure 3. Phylogenetic tree of MATEs of P. rubra and related proteins.

Figure 3

Sequences of P. rubra are shown using red shades. For sequences other than P. rubra MATEs, the labels are UniProt database IDs, and ones from Liu et al. (2016). Number at each node is the bootstrap value.

Expression and functional analyses of ALMTs and MATEs of P. rubra would be useful for understanding their roles in soil adaptation of Psychotria (e.g., with and without Al treatment). Another aluminum tolerance mechanism of plants (different from releasing organic acids), aluminum accumulation, has been reported in several species of the Rubiaceae (Jansen et al., 2003). Genes related to this function are also good targets for future studies to explain the molecular basis of acid soil adaptation of P. rubra.

Conclusions

We succeeded in identifying transcriptome sequences including ALMTs and MATEs from P. rubra in this study. Comparative transcriptome analysis of several Psychotria species would help us to clarify the physiological and ecological aspects of diversification of this genus (e.g., adaptation to metalliferous soils; Merlot et al., 2014). In particular, Psychotria manillensis, which is closely related to P. rubra, is reportedly adapted to non-acid soils (Miyawaki, 1989). Thus, comparative analysis of P. rubra and P. manillensis should help to explain how soil adaptation–related genes are involved in adaptive evolution of Psychotria species.

Acknowledgments

We thank students of Department of Bioresources Engineering, National Institute of Technology, Okinawa College for their help in maintaining seedlings in a greenhouse.

Funding Statement

This study was supported by a grant from the Nissei Science Foundation to Akira Iguchi (No. 03) and JSPS KAKENHI Grants to Kenta Watanabe (Nos. JP26840130 and JP18K14782). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Additional Information and Declarations

Competing Interests

The authors declare there are no competing interests.

Author Contributions

Akira Iguchi conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.

Kazutsuka Sanmiya and Kenta Watanabe performed the experiments, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.

DNA Deposition

The following information was supplied regarding the deposition of DNA sequences:

Sequence data are accessible at the DNA Data Bank of Japan (DDBJ) Sequence Read Archive: DRA008339.

Data Availability

The following information was supplied regarding data availability:

The raw data is available at Figshare: Iguchi, Akira (2019): Transcriptome of Psychotria rubra (Rubiaceae). figshare. Dataset. https://doi.org/10.6084/m9.figshare.7848425.v2.

References

  • Davis et al. (2001).Davis AP, Bridson D, Jarvis C, Govaerts R. The typification and characterization of the genus Psychotria L. (Rubiaceae) Botanical Journal of the Linnean Society. 2001;135:35–42. doi: 10.1111/j.1095-8339.2001.tb02366.x. [DOI] [Google Scholar]
  • Delhaize, Gruber & Ryan (2007).Delhaize E, Gruber BD, Ryan PR. The roles of organic anion permeases in aluminium resistance and mineral nutrition. FEBS Letters. 2007;581:2255–2262. doi: 10.1016/j.febslet.2007.03.057. [DOI] [PubMed] [Google Scholar]
  • Delhaize, Ma & Ryan (2012).Delhaize E, Ma JF, Ryan PR. Transcriptional regulation of aluminium tolerance genes. Trends in Plant Science. 2012;17:341–348. doi: 10.1016/j.tplants.2012.02.008. [DOI] [PubMed] [Google Scholar]
  • Delhaize et al. (2004).Delhaize E, Ryan PR, Hebb DM, Yamamoto Y, Sasaki T, Matsumoto H. Engineering high-level aluminum tolerance in barley with the ALMT1 gene. Proceedings of the National Academy of Sciences of the United States of America. 2004;101:15249–15254. doi: 10.1073/pnas.0406258101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Dreyer et al. (2012).Dreyer I, Gomez-Porras JL, Riaño Pachón DM, Hedrich R, Geiger D. Molecular evolution of slow and quick anion channels (SLACs and QUACs/ALMTs) Frontiers in Plant Science. 2012;3:263. doi: 10.3389/fpls.2012.00263. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Furukawa et al. (2007).Furukawa J, Yamaji N, Wang H, Mitani N, Murata Y, Sato K, Ma JF. An aluminum-activated citrate transporter in barley. Plant and Cell Physiology. 2007;48:1081–1091. doi: 10.1093/pcp/pcm091. [DOI] [PubMed] [Google Scholar]
  • Grabherr et al. (2011).Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Chen Z. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnology. 2011;29:644–652. doi: 10.1038/nbt.1883. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Haas et al. (2013).Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, MacManes MD. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nature Protocols. 2013;8:1494–1512. doi: 10.1038/nprot.2013.084. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Hamilton (1989).Hamilton CW. A revision of Mesoamerican Psychotria subgenus Psychotria (Rubiaceae), part I: introduction and species 1-16. Annals of the Missouri Botanical Garden. 1989;76:67–111. doi: 10.2307/2399343. [DOI] [Google Scholar]
  • Hiradate, Ma & Matsumoto (2007).Hiradate S, Ma JF, Matsumoto H. Strategies of plants to adapt to mineral stresses in problem soils. Advances in Agronomy. 2007;96:65–132. doi: 10.1016/S0065-2113(07)96004-6. [DOI] [Google Scholar]
  • Hoekenga et al. (2006).Hoekenga OA, Maron LG, Piñeros MA, Cançado GM, Shaff J, Kobayashi Y, Matsumoto H. AtALMT1, which encodes a malate transporter, is identified as one of several genes critical for aluminum tolerance in Arabidopsis. Proceedings of the National Academy of Sciences of the United States of America. 2006;103:9738–9743. doi: 10.1073/pnas.0602868103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Jansen et al. (2003).Jansen S, Watanabe T, Dessein S, Smets E, Robbrecht E. A comparative study of metal levels in leaves of some Al-accumulating Rubiaceae. Annals of Botany. 2003;91:657–663. doi: 10.1093/aob/mcg071. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Katoh & Standley (2013).Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Molecular Biology and Evolution. 2013;30:772–780. doi: 10.1093/molbev/mst010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kumar, Stecher & Tamura (2016).Kumar S, Stecher G, Tamura K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Molecular Biology and Evolution. 2016;33:1870–1874. doi: 10.1093/molbev/msw054. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Li & Godzik (2006).Li W, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22:1658–1659. doi: 10.1093/bioinformatics/btl158. [DOI] [PubMed] [Google Scholar]
  • Liu et al. (2016).Liu J, Li Y, Wang W, Gai J, Li Y. Genome-wide analysis of MATE transporters and expression patterns of a subgroup of MATE genes in response to aluminum toxicity in soybean. BMC Genomics. 2016;17:223. doi: 10.1186/s12864-016-2559-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Liu et al. (2009).Liu J, Magalhaes JV, Shaff J, Kochian LV. Aluminum-activated citrate and malate transporters from the MATE and ALMT families function independently to confer Arabidopsis aluminum tolerance. The Plant Journal. 2009;57:389–399. doi: 10.1111/j.1365-313X.2008.03696.x. [DOI] [PubMed] [Google Scholar]
  • Ma (2007).Ma JF. Syndrome of aluminum toxicity and diversity of aluminum resistance in higher plants. International Review of Cytology. 2007;264:225–252. doi: 10.1016/S0074-7696(07)64005-4. [DOI] [PubMed] [Google Scholar]
  • Ma, Chen & Shen (2014).Ma JF, Chen ZC, Shen RF. Molecular mechanisms of Al tolerance in gramineous plants. Plant and Soil. 2014;381:1–12. doi: 10.1007/s11104-014-2073-1. [DOI] [Google Scholar]
  • Maron et al. (2010).Maron LG, Piñeros MA, Guimarães CT, Magalhaes JV, Pleiman JK, Mao C, Kochian LV. Two functionally distinct members of the MATE (multi-drug and toxic compound extrusion) family of transporters potentially underlie two major aluminum tolerance QTLs in maize. The Plant Journal. 2010;61:728–740. doi: 10.1111/j.1365-313X.2009.04103.x. [DOI] [PubMed] [Google Scholar]
  • Martin (2011).Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. Journal. 2011;17:10–12. doi: 10.14806/ej.17.1.200. [DOI] [Google Scholar]
  • Merlot et al. (2014).Merlot S, Hannibal L, Martins S, Martinelli L, Amir H, Lebrun M, Thomine S. The metal transporter PgIREG1 from the hyperaccumulator Psychotria gabriellae is a candidate gene for nickel tolerance and accumulation. Journal of Experimental Botany. 2014;65:1551–1564. doi: 10.1093/jxb/eru025. [DOI] [PubMed] [Google Scholar]
  • Miyawaki (1989).Miyawaki A. Vegetation of Japan 10 Okinawa/Ogasawara. Shibundo; Tokyo: 1989. [in Japanese] [Google Scholar]
  • Razafimandimbison et al. (2014).Razafimandimbison SG, Taylor CM, Wikström N, Pailler T, Khodabandeh A, Bremer B. Phylogeny and generic limits in the sister tribes Psychotrieae and Palicoureeae (Rubiaceae): evolution of schizocarps in Psychotria and origins of bacterial leaf nodules of the Malagasy species. American Journal of Botany. 2014;101:1102–1126. doi: 10.3732/ajb.1400076. [DOI] [PubMed] [Google Scholar]
  • Sasaki et al. (2004).Sasaki T, Yamamoto Y, Ezaki B, Katsuhara M, Ahn SJ, Ryan PR, Matsumoto H. A wheat gene encoding an aluminum-activated malate transporter. The Plant Journal. 2004;37:645–653. doi: 10.1111/j.1365-313X.2003.01991.x. [DOI] [PubMed] [Google Scholar]
  • Shen et al. (2016).Shen W, Le S, Li Y, Hu F. SeqKit: a cross-platform and ultrafast toolkit for FASTA/Q file manipulation. PLOS ONE. 2016;11:e0163962. doi: 10.1371/journal.pone.0163962. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Smeds & Künstner (2011).Smeds L, Künstner A. ConDeTri-a content dependent read trimmer for Illumina data. PLOS ONE. 2011;6:e26314. doi: 10.1371/journal.pone.0026314. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Swarbreck et al. (2007).Swarbreck D, Wilks C, Lamesch P, Berardini TZ, Garcia-Hernandez M, Foerster H, Radenbaugh A. The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Research. 2007;36:D1009–D1014. doi: 10.1093/nar/gkm965. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Von Uexküll & Mutert (1995).Von Uexküll HR, Mutert E. Global extent, development and economic impact of acid soils. Plant and Soil. 1995;171:1–15. doi: 10.1007/BF00009558. [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The following information was supplied regarding data availability:

The raw data is available at Figshare: Iguchi, Akira (2019): Transcriptome of Psychotria rubra (Rubiaceae). figshare. Dataset. https://doi.org/10.6084/m9.figshare.7848425.v2.


Articles from PeerJ are provided here courtesy of PeerJ, Inc

RESOURCES