GATA transcription factors (TFs) are widespread eukaryotic regulators whose DNA-binding domain is a class IV zinc finger motif (CX2CX17-20CX2C) followed by a basic region. Due to the low cost of genome sequencing, multiple strains of specific species have been sequenced: e.g., number of plant genomes in the Plant Genome Database (http://www.plantgenome.info/) is 2,174 originated from 713 plant species. Thus, we investigated GATA TFs of 19 Arabidopsis thaliana genome-widely to understand intraspecific features of Arabidopsis GATA TFs with the pipeline of GATA database (http://gata.genefamily.info/). Numbers of GATA genes and GATA TFs of each A. thaliana genome range from 29 to 30 and from 39 to 42, respectively. Four cases of different pattern of alternative splicing forms of GATA genes among 19 A. thaliana genomes are identified. 22 of 2,195 amino acids (1.002%) from the alignment of GATA domain amino acid sequences display variations across 19 ecotype genomes. In addition, maximally four different amino acid sequences per each GATA domain identified in this study indicate that these position-specific amino acid variations may invoke intraspecific functional variations. Among 15 functionally characterized GATA genes, only five GATA genes display variations of amino acids across ecotypes of A. thaliana, implying variations of their biological roles across natural isolates of A. thaliana. PCA results from 28 characteristics of GATA genes display the four groups, same to those defined by the number of GATA genes. Topologies of bootstrapped phylogenetic trees of Arabidopsis chloroplasts and common GATA genes are mostly incongruent. Moreover, no relationship between geographical distribution and their phylogenetic relationships was found. Our results present that intraspecific variations of GATA TFs in A. thaliana are conserved and evolutionarily neutral along with 19 ecotypes, which is congruent to the fact that GATA TFs are one of the main regulators for controlling essential mechanisms, such as seed germination and hypocotyl elongation.
Citation: Kim M, Xi H, Park J (2021) Genome-wide comparative analyses of GATA transcription factors among 19 Arabidopsis ecotype genomes: Intraspecific characteristics of GATA transcription factors. PLoS ONE 16(5): e0252181. https://doi.org/10.1371/journal.pone.0252181
Editor: Rajesh Mehrotra, Birla Institute of Technology and Science, INDIA
Received: May 9, 2020; Accepted: May 11, 2021; Published: May 26, 2021
Copyright: © 2021 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All GATA TFs identified in this study can be accessed at http://arabidopsis.gata.genefamily.info/.
Funding: This research was fully supported by InfoBoss Research Grant (IBI-0001; http://www.infoboss.co.kr/) to J.P. The funder provided support in the form of salaries for authors [JP], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.
Competing interests: This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Due to the rapid development of sequencing technologies, many sequencing techniques beyond Sanger sequencing, called as next generation sequencing (NGS) technologies, have been established and commercialized [1–3]. Among them, sequencers made by Illumina (HiSeq/NovaSeq) are one of the major sequencing platforms frequently used, producing a huge number of raw reads of which length is 151 bp maximumly with extremely low cost [4,5]. From the first phase of NGS technologies, it promoted whole genome sequencing projects with the aid of a new algorithm of genome assembly, de bruijn algorithm [6–11]. As an example, the cucumber genome, the first plant genome assembled from Illumina data, was successfully published in 2009 . After that, many plant genomes have been sequenced with NGS technologies including third generation technology, such as PacBio. It guaranteed much longer contig sequences than those from Illumina data once enough amount of DNA (from 8 to 16 ug) containing long read DNA can be prepared .
These new sequencing technologies have resulted in lower sequencing costs, which have changed the trends of whole genome projects: one is increasing number of academically valuable whole genomes [14–17] which provide interesting insights to understand the evolutionary history of plants, beyond economically important species. Another is deciphering many genomes of various strains in one species to identify genetic variations at an intraspecific level [18–25]. The other is genome-wide association studies that investigate genetic variants identified from a large number of individuals’ genomes to find the relationship between genotypes and phenotypes [26–28]. In addition, whole genome sequencing is performed for high-throughput genotyping [29–31].
This trend has uncovered genome-wide sequence variations, including single nucleotide polymorphisms, insertions and deletions, and copy number variations, to find disease-related sequence variations on human for developing individual-specific medicines [32–35], to illuminate evolutionary histories inside species , to map biological features to specific variations [24,36,37], or to develop molecular markers to distinguish the origin of species [26,29,38]. Till now more than 10,000 human genomes re-sequenced [39–49] as well as more than 1,700 A. thaliana [5,18–20,50–53] and 4,000 rice genomes [26,29,54–61] are available. Moreover, the current release of the Plant Genome Database (http://www.plantgenome.info; Park et al., in preparation) [62,63] presents that 103 plant species have more than one whole genome sequences, reflecting that resequencing of additional cultivars or individuals is a recent trend of plant genome projects. However, due to technical reasons, most of the resequenced genomes are usually not provided as assembled sequences as well as do not contain gene models (e.g., Oryza sativa  and Populus trichocarpa ), which is a huddle to investigate variations of gene families in detail.
A transcription factor (TF) is a protein that controls the rate of transcriptions by binding to specific DNA sequences including promoter regions of a certain gene. Plant TF plays important roles such as controlling flower developments , circadian clock , carbon and nitrogen regulatory network , and disease resistance .
Plant GATA TF family, which is one of the major TF families in plant species [68–72], contains one or sometimes more highly conserved type IV zinc finger motifs (CX2X18,20CX2C) followed by a basic region that can bind to a consensus sequence (WGATAR; W = T or A; R = G or A) [73–75]. Because Arabidopsis is a model plant, the biological functions of many GATA TFs have been characterized. For example, AtGATA8 (BME3) is a positive regulator of Arabidopsis seed germination , AtGATA18 (HAN) is required to position proembryo boundary in the early embryo of Arabidopsis , and AtGATA25 (ZIM) is involved in hypocotyl and petiole elongation .
Even though many genome-wide identifications of GATA TFs in plant species [73,79–87], there is no investigation of intraspecific variations of GATA TFs, which may be fundamental data for understanding subtle differences among natural isolates. Fortunately, the genome project of resequencing A. thaliana with Illumina technology provided a gene model of 18 A. thaliana genomes . In addition, reinvestigation of A. thaliana GATA TFs is also needed because the previous research of genome-wide GATA TF identification was conducted in 2004 , when the version gene model of A. thaliana was older than the current version (TAIR 10.1) . Taken together, we investigated GATA TFs from 19 A. thaliana genomes including reference genome (A. thaliana Col0) and analyzed them in the aspects of intraspecific variations of chromosomal distribution, amino acid sequences, and phylogenetic relationships.
Along with 19 A. thaliana natural isolate genomes, the number of GATA genes and GATA TFs per genome range from 29 to 30 and from 39 and 42, respectively, presenting differences among 19 A. thaliana. Four genome-wide distribution patterns of GATA TFs were identified. Besides type IVb and IVc defined in previous studies [75,89], an additional type, CX4CX18CX2C (in AtGATA29), named as type IV4, was rescued. Two alternative splicing forms, AtGATA11a and AtGATA15b, were identified only in one A. thaliana genome, Col0 and Kn0, respectively. In detail, 22 out of 2,195 amino acid positions (1.002%) from 13 out of 41 conserved GATA TFs (31.71%) display amino acid variations across 19 A. thaliana genomes. 15 out of 30 A. thaliana GATA genes (50.00%) have been studied about theirs biological functions. Interestingly, GATA genes in subfamily II including seven characterized GATA genes presented the largest amino acid variations implying subtle variations of biological functions across natural isolates of A. thaliana. Chromosomal distributions of GATA genes on 19 A. thaliana genomes display biased distribution. PCA results based on 28 characteristics of GATA genes present four groups, same to those defined by the number of GATA genes. Topologies of bootstrapped phylogenetic trees of Arabidopsis chloroplast genomes and GATA genes are mostly incongruent and no relationship between geographical distribution and their phylogenetic relationships. Our genome-wide identification of GATA genes in 19 A. thaliana provides diverse characteristics of intra-species variations of GATA TFs.
Material and methods
Collection and preprocess of 19 Arabidopsis genome sequences
We utilized nineteen A. thaliana genomes sequences deposited from the Plant Genome Database (Release 2.6; http://www.plantgenome.info/; Park et al, in preparation) [62,63], which collected genome sequences from several repositories including the NCBI genome database (http://genome.ncbi.nlm.nih.gov/) and standardized based on the GenomeArchive® (http://www.genomearchive.info/; Park et al, in preparation) . We used the gene models of nineteen Arabidopsis genomes  for systematic studies.
Identification of GATA TFs from 19 Arabidopsis whole genome sequences
Amino acid sequences from nineteen A. thaliana genomes were subjected to InterProScan  to identify GATA TFs. The pipeline for identifying A. thaliana GATA TFs implemented at the GATA Database (http://gata.genefamily.info/; Park et al., in submission), which is an automated pipeline for identifying GATA TFs with GATA DNA-binding motif InterPro term (IPR000679) and post process to filter out false positive results and for analyzing various analyses including domain sequence analysis, gene family analysis, as well as phylogenetic analysis. GATA Database was constructed and maintained as one of the members of the Gene Family Database (http://www.genefamily.info/; InfoBoss, Inc.; Park et al., in preparation).
Investigation of exon structure and alternative splicing forms of GATA TFs
Based on the Plant Genome Database (http://www.plantgenome.info/; Park et al., in preparation) [62,63], exon structure and alternative splicing forms of GATA TFs were retrieved. Diagrams of exon structure and alternative splicing forms of GATA TFs were drawn primarily based on the diagram generated by the GATA Database (http://gata.genefamily.info; Park et al., in preparation) with adding additional information manually.
Assembly of complete chloroplast genomes of A. thaliana based on public NGS raw reads
Raw sequences downloaded from NCBI SRA (S1 Table) were used for chloroplast de novo genome assembly with Velvet v1.2.10  after filtering raw reads using Trimmomatic v0.33 . After obtaining the first draft of the chloro-plast genome sequences, gaps were filled with GapCloser v1.12  and all bases from the assembled sequences wereconfirmed by checking each base in the alignment (view mode in SAMtools 1.9 ) against the assembled chloro-plast genome generated with BWA v0.7.17 . All these bio-informatic processes were conducted under the environment of Genome Information System (GeIS; http://geis.infoboss.co.kr/; Park et al., in preparation).
Construction of phylogenetic tree of GATA TFs
Phylogenetic tree based on amino acid sequences of GATA domains was constructed with neighbor joining (NJ) method (bootstrap repeat is 10,000) by MEGA X  based on sequence alignment calculated by ClustalW 2.1  under the environment of the GATA Database (http://gata.genefamily.info/; Park et al., in preparation). For drawing phylogenetic trees based on complete chloroplast genomes, we used MAFFT v7.450  for aligning 19 complete chloroplast genomes including that of A. lyrata and drew a neighbor-joining phylogenetic tree with 10,000 bootstrap repeats using MEGA X , the maximum-likelihood phylogenetic tree with 1,000 bootstrap repeats using IQ-TREE v1.6.2 , and Bayesian inference tree (number of generations is 1,100,000) using MrBayes v3.2.7 .
Identification of GATA TFs from 19 A. thaliana genomes
We identified 566 GATA genes (773 GATA TFs) from 19 A. thaliana genomes available in public using the pipeline of GATA database (http://gata.genefamily.info/; Park et al., in preparation; Table 1 and S2 Table). Gene models of 19 A. thaliana genomes contain alternative splicing forms, so that numbers of GATA TFs are larger than those of GATA genes (Table 1), presenting potential functional differentiation of GATA TFs: e.g. expression levels of alternative forms of one GATA gene (OsGATA23) are different in the same condition . Numbers of GATA genes and GATA TFs of each A. thaliana genome range from 29 to 30 and 39 to 42, respectively (Table 1). The absence and presence of the AtGATA24 gene in each A. thaliana genome caused the differences of the number of GATA genes (Table 1). Its function is controlling cryptochrome1-dependent response to excess light . The existence of AtGATA24 homologs in Arabidopsis lyrata (EFH59549.1 and EFH67905.1) and Arabidopsis halleri (Araha.17146s0001.1 and Araha.2389s0021.1) genomes identified using BLAST search (S1 Fig) indicates that four accessions which do not contain AtGATA24 might miss this gene due to assembly errors.
The conserved GATA genes from 19 A. thaliana genomes, such as AtGATA2 and AtGATA4, presented various exon structures along with A. thaliana genomes (Fig 1). Lengths of 5’ untranslated regions (UTRs) of AtGATA2 and AtGATA4 gene are different from each other, ranging from 86 bp (18 genomes except Col0) to 261 bp (Col0; Fig 1A) and 10 bp (No0) to 335 bp (Col0; Fig 1B), respectively. In addition, the first and second exons of both GATA genes along with nineteen A. thaliana genomes show slightly different lengths (Fig 1). Finally, 3’ and 5’ UTRs of both genes also present differences (Fig 1). Interestingly, the Col0 genome displays longer UTRs in comparison to the remaining ecotypes (Fig 1). These variations of exon and intron structure including UTRs were also identified in the other gene families, including polyol transporter  and Lipocalin  gene families. Even though previous studies display inter-species variations of exon-intron structure in the gene family, they support that these intraspecific variations of the GATA TF family can be considered as fundamental data to understand microevolutionary mechanisms in the gene family, especially for TF families.
(A) shows gene structure of AtGATA2 genes from 19 A. thaliana genomes. (B) displays gene structure of AtGATA4 genes from 19 A. thaliana genomes. Yellow boxes indicate translated regions and black boxes display untranslated regions. Numbers around boxes display relative positions of translated, untranslated, and exons. Names of A. thaliana genomes are printed in the left part of each gene diagram. Dotted and solid lines indicate the conserved and different structure of GATA genes including exon, intron, and untranslated regions, respectively.
Alternative splicing forms of GATA genes from 19 A. thaliana genomes
The Numbers of GATA genes which have alternative splicing forms range from 8 to 10 per each A. thaliana genome (see # of GATA genes having alternative splicing forms in Table 2), which account for 29.68% of 566 GATA genes from 19 A. thaliana genomes (Table 2). The average number of alternative splicing forms of GATA genes for each A. thaliana genome ranges from 1.34 (A. thaliana Hi0, Ler0, Mt0, and Ws0) to 1.40 (A. thaliana Kn0 and Col0; Table 2; Average number of alternative splicing forms of GATA genes). The numbers of total alternative splicing forms of A. thaliana Kn0 and Col0 GATA genes are the largest among 19 A. thaliana genomes (Table 2) because AtGATA15 in A. thaliana Kn0 has two alternative splicing forms and AtGATA11 in A. thaliana Col0 has three alternative splicing forms; while AtGATA15 of A. thaliana genomes except A. thaliana Kn0 has one and AtGATA11 of A. thaliana genomes except A. thaliana Col0 has two. Interestingly, translation start positions of two alternative splicing forms of AtGATA15 are different in A. thaliana Kn0 (Fig 2A), resulting length of amino acids of AtGATA15a is longer than that of AtGATA15b by acquiring MLDPTEKVIDSES (Fig 2B). It is caused by subtle differences in length of the first exon, invoking another start codon in the first exon of AtGATA15a was considered as the start position of this protein. In addition, AtGATA11 of A. thaliana Col0 presents that the translation start site of three alternative splicing forms are the same to each other; while the transcript start site of AtGATA11c is different from those of AtGATA11a and AtGATA11b (Fig 3). Taken together, the differences identified among 19 ecotyeps, such as number of average alternative splicing forms of each ecotype genome, are caused by the three GATA genes (AtGATA11, AtGATA15, and AtGATA24) implies the importance of GATA TFs in A. thaliana, such as regulation of seed germination .
(A) shows gene structure of two alternative splicing forms of AtGATA15 gene in A. thaliana Kn0 genome. Black- or orange-colored boxes indicate untranslated and coding regions in exons, respectively. Black lines mean intron regions. Numbers around exon boxes present relative base pair position started from a transcript start position of the AtGATA15 gene. The chromosomal position of the AtGATA15 gene is displayed on the top of the diagram. (B) exhibits protein sequences of alternative splicing forms of the AtGATA15 gene. Black dots with numbers present the position of amino acids. The amino acids marked in blue letters indicate AtGATA15a specific amino acids.
It shows alternative splicing forms of GATA genes in A. thaliana Col0. Black and orange color thick boxes indicate exons and lines means intron. Black- or orange-colored boxes indicate untranslated and coding regions in exons, respectively. Numbers around exon boxes present relative base pair position started from a transcript start position of each gene. Yellow star indicates one of the alternative splicing forms of GATA gene without GATA domain.
Interestingly, AtGATA11, AtGATA25, and AtGATA26 have three alternative splicing forms, which are the largest number of alternative splicing forms among 19 A. thaliana genomes (Fig 3). Translated sequences derived from two alternative splicing forms of the AtGATA25 gene (AtGATA25b and AtGATA25c) are 309 aa long, while AtGATA25a is 317 aa (Fig 3). In addition, the numbers of exons of the AtGATA25c are 8 but the rests are 7 (Fig 3). Three alternative splicing forms of AtGATA25 gene present the same start and end positions of ORFs and only the sixth exon from the translation start site shows different lengths: one is 60 bp in length and the other is 84 bp (Fig 3). Three alternative splicing forms of the AtGATA26 gene present different protein lengths, different from those of the AtGATA25 gene; 526 aa (AtGATA26a), 514 aa (AtGATA26c), and 510 aa (AtGATA26b). In addition, AtGATA26a from Hi0 present 515 aa, shorter than those of AtGATA26a from the rest of A. thaliana genomes. The number of exons of AtGATA26a is 9 and the other two are 8 (Fig 3). Two alternative splicing forms except for AtGATA26a have the same transcription start site, while the transcription end site of the three alternative splicing forms is different from each other (Fig 3). In addition, the eighth exons of the three alternative splicing forms present a different length: that of AtGATA26a is the shortest and that of AtGATA26c is the longest (Fig 3).
The significance of the average number of alternative splicing forms of the GATA gene presents divergence of their biological functions: e.g., OsGATA23 showing different expression levels of different alternative splicing forms . Including this case, we can deduce the several points from the average number of alternative splicing forms of GATA genes: i) differences of start methionine (e.g., AtGATA15) can affect their biological function: mineralocorticoid receptor A and B forms of human which present different transcriptional activities by alternative translation sites , ii) exon configuration which shows different exon-intron junctions also affects their functions in the cell: one typical example is OsGATA23 which contains two alternative splicing forms of which numbers of exons and their lengths are different and shows different expression levels for each different alternative splicing form . It indicates that the average number of alternative splicing forms of GATA genes along with subfamilies may reflect subfamily-specific functional diversity.
We also identified that one alternative splicing form (At3g21175.3) of the AtGATA24 gene missed the GATA domain (Fig 3), found in all 15 A. thaliana genomes except for A. thaliana Hi0, Ler0, Mt0, and Ws0. Twelve GATA genes from three Populus species, P. tremula, P. tremuloides, and P. tremula x alba 717-1B4) also miss the GATA domain (Kim et al., in preparation), which is the same phenomenon to that of A. thaliana. We excluded these GATA TFs without DNA-binding domain for further analyses; however, these GATA TFs without DNA-binding domain can also negatively regulate target transcripts by competing with normal GATA TFs  because GATA TFs require additional accessory proteins for regulating target genes. Taken together, an average number of alternative splicing forms along with GATA gene families can be an indicator to show a degree of precise regulation of GATA genes’ functions.
Identification and characteristics of GATA subfamilies in 19 A. thaliana genomes
Seven subfamilies of GATA genes were identified based on the most previous studies of the plant GATA gene family , among which three (V, VI, and VII) are monocot-specific and the rest four are common. Based on many genome-wide identification studies of GATA genes in plant genomes [73,79–82,84–87], the number of GATA genes in subfamily I has the largest except Brassica napus  and that of subfamily IV is the smallest in dicot species (Table 3). Interestingly, GATA genes from two more monocot genomes, Triticum aestivum  and Phyllostachys edulis  have been identified, presenting that only three or four subfamilies identified from dicots were mentioned (Table 3). Two GATA genes (PeGATA6 and PeGATA11) from P. edulis and two GATA genes (TaGATA-A2 and TaGATA-A11) from T. aestivum contain two or three GATA domains [79,87], which should be classified into subfamily VI based on the study of Oryza sativa , indicating that new criteria for classifying subfamilies of GATA genes should be established again against available hundreds of plant genomes.
There are four types of distribution of GATA TFs along with four subfamilies identified in 19 A. thaliana genomes (Table 4). The largest one (Type 1), which is from thirteen out of 19 A. thaliana genomes except for A. thaliana Col0, Hi0, Ler0, Mt0, Ws0, and Kn0, presents 14 GATA genes (19 GATA TFs) in subfamily I, 11 (11 GATA TFs) in subfamily II, 3 (7 GATA TFs) in subfamily III, and 2 (4 GATA TFs) in subfamily IV (Table 5). The second largest one (Type 2) found in four A. thaliana genomes, such as Hi0, Ler0, Mt0, and Ws0, shows 2 GATA genes (5 GATA TFs) in subfamily III because of the absence of the AtGATA24 gene. The third type (Type 3) from the A. thaliana Kn0 genome displays one more GATA TF in subfamily II in comparison to Type 1 because the AtGATA15 gene has one more alternative splicing form than the rest of A. thaliana genomes. In addition, this additional alternative splicing form is uniquely identified in subfamily II among 19 A. thaliana genomes. The last form (Type 4) found in A. thaliana Col0 shows that numbers of GATA TFs except for subfamily I are the same as those of the Type 1; number of GATA TFs in subfamily I of A. thaliana Col0 is 20 because of AtGATA11a, unique GATA TF among 19 A. thaliana genomes.
Subfamily III shows the highest ratio between GATA TFs and GATA genes, ranging from 2.33 to 2.50 (Table 4); while subfamily II is the lowest (1.00 to 1.09). In subfamily IV, only one of two GATA genes has alternative splicing forms. These results suggest together with the previous studies showing diversified functions of alternative splicing forms of TFs [101,115] that subfamily III may have diverse functions in comparison to the rest of subfamilies. In the case of subfamily II, except A. thaliana Kn0, there is no alternative splicing form found in A. thaliana genomes. No alternative splicing form of GATA subfamily II is also found in the recent Glycine max genome release of which gene model covers alternative splicing forms. However, four Populus genomes (Populus trichocarpa, Populus euphratica, Populus tremuloides, and Populus tremula x alba 717-1B4) present maximally three alternative splicing forms in subfamily II (Kim et al, in preparation). Taken together, A. thaliana subfamily II may not be functionally diversified in comparison to Populus species . In addition, O. sativa, a monocot species, also shows that subfamily II contains alternative splicing forms (OsGATA8) .
A. thaliana GATA genes belonging to subfamilies I, II, and IV contain a single GATA domain with CX2CX18CX2C form (Type IVb); while GATA genes in subfamily III exhibit a single GATA domain with CX2CX20CX2C form (Type IVc; Fig 4) [73,75]. Except two GATA domain types, we identified additional domain types: CX4CX18CX2C type which contains four amino acids in the first cysteine-cysteine is designated as type IV4 . Type IV4 (CX4CX18CX2C) is considered as an unusual pattern of the GATA domain because of four amino acids in the first two cysteines which have a role in binding zinc molecule. Based on the previous study which tested the ability of DNA binding with zero to five amino acids between two cysteines in C2H2 zinc finger TFs of which three-dimensional structure is almost similar to that of GATA TFs except for two histidines binding to zinc ion and shorter length of the linkers between two cysteines and two histidines . It is similar to the conventional GATA domain as well as is found in many GATA genes: AtGATA29 in A. thaliana, 28035.m000366 gene in Ricinus communis , GmGATA50 gene in G. max , and eight GATA genes from Populus species (PdGATA20, PeGATA19, PeGATA20, PeGATA23, PpGATA21, PpGATA22, PtaaGATA20, and PtrGATA10; Kim et al., under revision). CX15CX2C type designed as type IVp is a partial GATA domain identified in AtGATA26a. The partial GATA domain in AtGATA26a was caused by alternative splicing forms so that AtGATA26b and AtGATA26c have intact GATA domain. In addition, AtGATA26a without additional known functional domain was expressed in leaves of cold assimilated A. thaliana . Moreover, the third GATA domain of the OsGATA24 gene in O. sativa covers partial GATA domain only with two latter cysteines  and MdGATA27 gene (CX14CX2C) and MdGATA35 gene (CX21CX2C) in Malus domestica  present three cysteines, the same form of AtGATA26a (Table 5). P. edulis genome presents five GATA genes of which domain is partial type (Table 5), which is the largest number among 12 species (Table 5). Taken together, type IVp can be defined as [CX2-4C]X12-21[CX2C], indicating that one of the amino acid patterns inside brackets can be omitted, and it may retain DNA-binding function.
(A) is the phylogenetic analysis of A. thaliana Col0 GATA domains. This is made of a neighbor-joining tree of GATA domain amino acid sequences from A. thaliana Col0 GATA TFs. Bootstrap values calculated from 10,000 replicates are shown on the tree except that those values are lower than 50. The scale bar corresponds to 0.10 estimated amino acid substitutions per site. (B) is protein domain organization of the corresponding GATA TFs. Black boxes with four different patterns indicate GATA domains with four different types. Type IVb, IVc, IV4, and IVp mean CX2CX18CX2C, CX2CX20CX2C, CX4CX18CX2C, and partial forms, respectively. Yellow- and orange-colored boxes indicate functional domains of TIFY and CCT, respectively. Subfamily names were displayed at the right side. Definitions of each box were presented in the right-top side. (C) shows GATA domain sequence types along with each GATA TF and A. thaliana genome. The X-axis of the matrix presents ecotypes of A. thaliana and Y-axis means each GATA TFs. Four different colors, white, yellow, orange, and green, indicate different amino acids in each Arabidopsis GATA TFs and the blue color presents heterogeneous amino acid in a specific position caused by heterogeneous nucleotide. Dark grey color means missed GATA TFs along with 19 ecotypes.
All subfamily III GATA TFs from 19 A. thaliana genomes contain two additional domains (Fig 4B): one is CCT domain (IPR010402) found in CONSTANS in A. thaliana  which is involved in circadian clock and flowering control, and the other is TIFY domain (IPR010399) which mediates homo- and heteromeric interactions between TIFY proteins and other specific TFs [120,121]. In contrast, some of GATA TFs in subfamily III from other plant species do not contain CCT and/or TIFY domains: 13 GATA TFs from six Populus species (Kim et al., in preparation) and 29838.m001723 gene in R. communis . Some of Populus GATA TFs (Kim et al., in preparation) and OsGATA19b in O. sativa  lost CCT and/or TIFY domains by alternative splicing events. There are no GATA TFs without CCT and/or TIFY domains in 19 A. thaliana genomes, suggesting that two subfamilies from subfamily III, named as subfamilies IIIa and IIIb, can be defined as GATA TFs with or without CCT and/or TIFY domains, respectively.
Comparison of GATA domain sequences from 19 A. thaliana genomes
Among distinct 43 A. thaliana GATA TFs, GATA domain sequences of 30 GATA TFs are identical including two cases, i) AtGATA15b uniquely identified in A. thaliana Kn0 genome and AtGATA11a only from A. thaliana Col0 and ii) AtGATA24a and AtGATA24b missed in A. thaliana Hi0, Ler0, Mt0, and Ws0 genomes (Fig 4C). Thirteen out of 43 distinct GATA TFs (30.23%) have multiple forms of GATA domain sequences. The AtGATA14 gene has four forms among 19 A. thaliana genomes, which is the largest number among the 13 GATA TFs (Fig 4C). AtGATA13, AtGATA17, and AtGATA18 genes have three forms and the rest nine GATA TFs contain two forms of GATA domains in 19 A. thaliana genomes (Fig 4C). Among nine GATA TFs with two GATA domain forms, the AtGATA6 gene presents one heterozygous amino acid in A. thaliana Mt0 genome because one nucleotide inside the AtGATA6 gene is a heterozygous base (K = G or T; Fig 4C and Table 6), causing critical amino acid changes from cysteine (C) to glycine (G) in the first conserved cysteine of GATA domain (Fig 5). It indicates that A. thaliana Mt0 may have two duplicated AtGATA6 genes with mutation or AtGATA6 on Mt0 genome is heteroallele. In addition, five heteroallele cases identified in AtGATA17, AtGATA20, and AtGATA30 are also identified without changing amino acids (Table 6). Moreover, all 11 GATA TFs in subfamilies III and IV are identical, presenting low diversity among 43 GATA TFs. Different diversity of GATA domain sequences in four subfamilies indicates different evolutionary speed.
It shows amino acid patterns of GATA domains of GATA TFs from 19 A. thaliana genomes. Purple colored GATA gene name indicates GATA TFs found only in Kn0 genome and grey colored GATA gene names mean that some A. thaliana genomes do not have GATA gene. Blue colored GATA gene name presents uniquely found in A. thaliana Col0 genome. Colors on aligned amino acids of the GATA domain indicate the number of amino acids in that position. Black and purple boxes under the alignment indicate the position of beta-sheet and alpha helixes, respectively. Black and purple border boxes indicate an area of the beta sheet and alpha helix areas.
Two out of 19 A. thaliana genomes, A. thaliana Rsch4 and Wu0, present identical patterns of GATA domain sequences of 41 GATA TFs, while those of the other A. thaliana genomes are different from each other (Fig 4C). All 39 GATA TFs in the A. thaliana Hi0 genome present abundant GATA domain patterns among 19 A. thaliana genomes; while A. thaliana Col0, Edi0, Ct1, Can0, Kn0, No0, Oy0, and Ws0 genomes contain one minor domain sequence (Fig 4C). Here, not all GATA TFs of the A. thaliana Col0 genome are abundant patterns, suggesting that the virtual genome of A. thaliana which contains all types of A. thaliana GATA genes should be constructed for understanding intra-species features of GATA genes in A. thaliana.
In detail, 22 out of 2,195 amino acids (1.002%) originated from GATA domain sequences of 41 GATA TFs except for AtGATA11a and AtGATA15b have variations across the 19 A. thaliana genomes (Fig 5). Five amino acids of GATA domains originated from heterozygous bases are not changed in contrast to the heterozygous bases found in the AtGATA6 gene: three amino acids in the AtGATA30 gene (A. thaliana Po0 and Mt0) and one amino acid in AtGATA17 (A. thaliana Sf2) and AtGATA20 gene (A. thaliana Hi0). These six amino acids from heterozygous bases suggest additional analyses of at least A. thaliana Mt0, Po0, Hi0, and Sf2 genomes to probe the reason why they have heterozygous bases in GATA genes.
Amino acid variations of GATA domain sequences within 19 A. thaliana genomes are not so high; most of the amino acids are conserved (Fig 5). It is reasonable because the GATA domain is critical to recognize specific DNA sequences (WGATAR) [73,74]. The number of heterozygous amino acids among 19 ecotypes identified in alpha helix and four beta sheets (Fig 5) of GATA TF and the number of those amino acids outside alpha helix and beta sheet structure is exactly the same, as 11. Maximally two amino acids are found in a certain position of the GATA domain (Fig 5). One amino acid, glutamine (E), in the end of the GATA domain of the AtGATA21 gene is only found in A. thaliana Ler0 genome caused by missing two alanines (A) near to the end of the domain (a red color amino acid in Fig 5). However, we confirmed that glutamine after GATA domain were found in other A. thaliana genomes indicating that the GATA domain of AtGATA21 from the Ler0 genome should not include this glutamine. All GATA genes having alternative splicing forms do not present any amino acid changes in the GATA domain except the AtGATA10 gene. AtGATA10 genes originated from three genomes, A. thaliana Bur0, Rsch4, and Au0, show threonine (T) instead of isoleucine (I) in the second beta sheet (Fig 5). Except for AtGATA11a and AtGATA15b, subfamily I contains 10 heterozygous amino acids among 19 A. thaliana genomes, while subfamily II has 11 heterozygous amino acids. It shows that the frequency of heterozygous amino acids in subfamily II (1.86%) is larger than that of subfamily I (1.01%), presenting high diversity of heterozygous amino acids in the GATA domain in subfamily II. There is no heterozygous amino acid in both subfamilies III and IV. These results indicate different evolutionary histories of the GATA domain in each subfamily.
Amino acids in a specific position of the GATA domain were grouped based on properties of amino acids: Inside alpha helix and beta sheets, two out of eleven amino acid changes (18.18%) present the same group of amino acid which may not affect the three-dimensional structure of GATA domain (Fig 5). It is interesting that amino acid changes found in 19 A. thaliana genomes may affect the three-dimensional structure of the GATA domain. While five out of eleven amino acid changes found outside of alpha helix and beta sheets show the same properties of amino acids, which can be explained that these areas are not important to form the three-dimensional structure of the GATA domain so that amino acid changes can change their properties easily.
In detail, three amino acid changes are in the alpha helix structure, while eight amino acid changes were identified inside four beta sheets (Fig 5 and Table 6). Two out of the three heterogeneous amino acids in alpha helix display lysine (K) or asparagine (N) identified in AtGATA30 and histidine (H) or tyrosine (Y) found in AtGATA23, changing a property of amino acids (Fig 5 and Table 6). Especially for the case of lysine or asparagine, the helical penalty increased from 0.26 kcal/mol to 0.66 kcal/mol , potentially disturbing the formation of alpha helix structure. Five out of eight amino acid changes were located in the boundary of beta sheets, which may be tolerable for allowing different properties of amino acids because they are directly linked to linker amino acids of which lengths are relatively short (2 to 4 amino acids). There are three out of eight amino acid changes inside the beta sheet structure of GATA domains: one is arginine (R) at the third amino acid of the third beta sheet at AtGATA14 gene containing amino acid change to lysine (K). Both arginine and lysine have the same characteristics having electrically charged side chains in their residue. The rest two are isoleucine (I) at third amino acids in the second beta sheet of AtGATA10a and AtGATA10b covering threonine (T) change. Threonine has polar uncharged residue, while isoleucine has a hydrophobic side chain. Because the three-dimensional structure of beta sheets faces with another beta sheet, differences of proletaries of threonine and isoleucine may not affect their three-dimensional structure severely. Taken together, amino acid changes in the GATA domain will not affect severely their basic three-dimensional structure, presenting that amino acid changes found in 19 A. thaliana genomes do not affect the DNA-binding function of GATA TFs, however there is a possibility for these variations to affect DNA binding affinity subtlely, which can affect regulatory gene networks supported by the previous studies [123,124].
Characterized biological functions of GATA TFs in Col0 and their distribution among 19 A. thaliana genomes
15 out of 30 A. thaliana Col0 GATA genes have been studied about their biological functions (Table 7). Five GATA genes belong to subfamily I and seven are from subfamily II and the remaining three GATA genes are in subfamily III. AtGATA1, AtGATA2, AtGATA3, and AtGATA4 (subfamily I) genes may be involved in the regulation of some of the light-responsive genes . AtGATA8 (BME3; subfamily I) gene is a positive regulator of Arabidopsis seed germination . AtGATA18 (HAN; subfamily II) gene is required to position the proembryo boundary in the early Arabidopsis embryo  and AtGATA21 (GNC) and AtGATA22 (GNL/CGA1) genes in subfamily II regulate chloroplast development, growth, and division [126,127]. In addition, AtGATA15, AtGATA16, AtGATA17, and AtGATA30 play roles of cytokinin-regulated development . Interestingly, only these five GATA genes belonging to Subfamily II have amino acid variations across 19 A. thaliana genomes also supported by one of the results of this study that subfamily II presents the largest number of amino acid variations (Fig 4). It also implies subtle variations of their biological functions, e.g. different DNA binding sequences. AtGATA24 (ZML1) and AtGATA28 (ZML2) genes in subfamily III mediate cryptochrome1-dependent response  and AtGATA25 (ZIM; subfamily III) gene is involved in hypocotyl and petiole elongation .
Fourteen out of 15 characterized GATA genes were also found in the other 18 A. thaliana genomes, indicating that biological functions of GATA genes in A. thaliana may be conserved and essential to their life cycle. However, one GATA gene, AtGATA24, is missed in the gene model of A. thaliana Hi0, Ler0, Mt0, and Ws0 genomes. Based on characterized functions of AtGATA24 (ZIM1) and AtGATA28 (ZIM2) genes, two GATA genes may present redundant or co-operational manners, which can explain the missed phenomenon on four A. thaliana genomes. However, it requires additional experimental researches to probe this hypothesis: e.g., both GATA genes contain CCT domains, related to protein-protein interactions , inferring that in the case that AtGATA24 and AtGATA28 genes form hetero-dimers, both genes are essential for elongating petiole and hypocotyl cells. Another possibility to explain this phenomenon is that gene models of four A. thaliana genomes may missed this gene in some reason; however, it may not be occurred easily because the same gene prediction program to predict genes of the eighteen A. thaliana genomes was used . In addition, A. lyrata (EFH59549.1) and A. helleri (Araha.17146s0001.1), which are neighbor species of A. thaliana, also have AtGATA24 gene, indicating that functional redundant of AtGATA24 and AtGATA28 genes should be probed in the near future.
Chromosomal distribution of GATA genes of 19 A. thaliana genomes
Several characteristics have been confirmed by the chromosome distribution of GATA genes in nineteen A. thaliana genomes (Fig 6). Chromosomes I and II contain only three GATA genes; while chromosomes III, IV, and V cover 10, 8, and 6 GATA genes, respectively. One exception is the AtGATA24 gene on chromosome III, missed in A. thaliana Hi0, Ler0, Mt0, and Ws0 genomes. Based on the density of GATA genes on chromosomes, chromosomes III and IV present similar density (chromosome III is 2.35 Mb/gene and chromosome IV is 2.32 Mb/gene); while chromosome I displays 10.14 Mb/gene, the lowest density.
Gradient purple bars indicate the chromosome of A. thaliana Col0. The left bar indicates the length of the chromosome. Red, green, sky blue, and gray GATA gene names mean subfamilies I, II, III, and IV, respectively. An array of small squares beside chromosomes presents the existence of GATA genes among 18 A. thaliana genomes: yellow color means existence and white color is non-existence case.
GATA genes in subfamily I are distributed in all five chromosomes and those of subfamily II are in chromosomes II to V. GATA genes belonging to subfamilies III and IV, containing a small number of GATA genes, are distributed in chromosomes I, III, and IV, and IV and V, respectively. Biased distribution of GATA genes along with chromosomes is also found in G. max  and Solanum lycopersicum .
Four pairs of GATA genes can be grouped because the distance between two GATA genes is less than 170 kb: AtGATA10 and AtGATA11 genes (distance is only 1,638 bp), which can be a candidate for gene duplication, AtGATA6 and AtGATA18 genes (distance is 61 kb), AtGATA7 and AtGATA19 genes (distance is 120 kb), and AtGATA24 and AtGATA29 genes (distance is 167 kb). Interestingly, except AtGATA10 and AtGATA11 genes, members of three pairs are belonging to different subfamilies, reflecting that three pairs of GATA genes are nearly located coincidentally.
Principle component analysis of Arabidopsis GATA genes
To understand the relationship of 19 A. thaliana ecotypes based on the GATA genes identified in this study, we extracted 28 characteristics from properties of the whole genome, number of GATA genes, GATA subfamily, number of alternative splicing forms of GATA genes, and amino acid changes and conducted principal component analysis (PCA) using the R package (see Materials and Methods). The result of PCA displays four distinct groups clearly (Fig 7), which is corresponding to four types defined in Table 4. In detail, Col0 (blue circle in Fig 7) and Kn0 (red circle in Fig 7) are completely separated, caused by one additional GATA TFs, AtGATA11a and AtGATA15b, respectively. It indicates that the power of characteristics related to the number of GATA genes can be dominant to be classified them into four groups (Fig 7). Once additional studies investigating intraspecific variations of GATA genes using plant genomes are available, we can know whether this trend is general across the plant species or not.
It shows the two-dimensional model of 19 Arabidopsis ecotypes derived from principal components analysis of 28 characteristics of GATA genes identified from 19 Arabidopsis ecotypes. Gray, purple, blue, and red circles are corresponding to Type 1, 2, 3, and 4 mentioned in Table 4, respectively. The ecotype name colored blue represents the specific dot.
Phylogenetic relationship of Arabidopsis GATA genes among 19 ecotypes
Based on nine common Arabidopsis GATA genes across 19 ecotypes as well as those of A. lyrata, we constructed bootstrapped phylogenetic trees of maximum-likelihood (ML), neighbor-joining (NJ), and Bayesian inference (BI) based on the concatenated alignment of the nine common GATA genes (Fig 7B). In addition, we also assembled the complete chloroplast genome of 15 ecotypes excluding Col0, Ler0, and Tsu0 because of available complete chloroplast genomes [142–144] as well as Sf0 due to lack of NGS raw reads in NCBI. In total, eighteen complete Arabidopsis chloroplast genomes together with that of A. lyrata were utilized for constructing the phylogenetic trees (Fig 7A).
Interestingly, both trees show almost completely incongruent except the terminal clade containing Col0 and Wil2, which forms one clade with high supportive values in chloroplast genome tree (Fig 7A) and with high supportive value of BI tree in the GATA gene tree (Fig 7B). Supportive values of the chloroplast tree present a high in most clades (Fig 8A); while those of the GATA gene tree do not, indicating that concatenated common GATA gene sequences are not enough to solve phylogenetic relationships of 19 ecotypes of A. thaliana (Fig 8B). In addition, the four types which are defined based on the number of GATA genes (Table 4) and are the same as the groups identified in PCA (Fig 7) were mapped on both phylogenetic trees (Fig 8). It displays no clear relationship between these types and clades (Fig 8), indicating that the presents and absences of GATA TFs are not related to evolutionary history.
(A) is a bootstrapped maximum-likelihood phylogenetic tree of 18 A. thaliana and A. lyrata chloroplast genomes. (B) presents a bootstrapped maximum-likelihood phylogenetic tree of concatenated common GATA genes across 19 A. thaliana ecotypes and A. lyrata. Numbers on branches in both phylogenetic trees indicate supporting values of maximum-likelihood, neighbor-joining, and Bayesian inference tree, respectively. The scale bars of both trees indicate estimated DNA substitutions per site. Gray, purple, blue, and red circles are corresponding to Types 1, 2, 3, and 4 mentioned in Fig 8 and Table 4, respectively. The dotted straight and curved lines connect the same ecotype in both trees.
To find the relationship among the geographical distribution of Arabidopsis ecotypes and phylogenetic relationships of Arabidopsis chloroplast genomes and their GATA genes, we selected countries which contain more than one ecotype: four ecotypes (Ler0, No0, Po0, and Wu0) derived from Germany, three ecotypes (Rsch4, Wil2, Ws0) from Russia, and two ecotypes (Can0 and Sf2) derived from Sapin (S2 Fig). Ler0, No0, Po0, and Wu0 from Germany are not clustered in the phylogenetic tree of GATA genes (Fig 8B). No0 and Wu0 ecotypes were clustered only in the chloroplast phylogenetic tree (Fig 8A); while all four German ecotypes were not clustered in the GATA gene tree (Fig 8B). Three and two ecotypes from Russia and Spain, respectively, were not clustered in both three (Fig 8). It indicates that there is no clear relationship among the geographical distribution of Arabidopsis ecotypes and phylogenetic relationships of Arabidopsis chloroplast genomes and their GATA genes.
Till now, there have been no intra-species genome-wide comparative analyses in the plant GATA gene family. We conducted comparative analyses using 19 A. thaliana genomes to unravel the characteristics of the GATA gene family: Only subfamily III presents differences number of GATA genes among 19 A. thaliana genomes; while alternative splicing forms of GATA genes in both subfamilies II and III present differences at the genome level. 13 out of 41 A. thaliana GATA TFs except two unique GATA TFs, AtGATA11a and AtGATA15b present different amino acids along with other 18 A. thaliana genomes and, interestingly, half of these variable amino acids are found in structural elements, including alpha helix and beta sheets. AtGATA24 (ZIM1) gene is missed in four A. thaliana genomes, A. thaliana Hi0, Ler0, Mt0, and Ws0, requiring additional experiments to show whether that gene is replaceable to AtGATA28 (ZIM2) gene or not. Moreover, the differences of an average number of alternative splicing forms of GATA genes along with subfamilies may represent subfamily-specific functional diversity. PCA result presents the four groups clearly (Fig 7), which is the same as the four types defined based on the number of GATA genes (Table 4). To understand phylogenetic relationships of Arabidopsis GATA genes and chloroplast genomes, we constructed bootstrapped phylogenetic trees, showing mostly incongruent. Moreover, there is no clear relationship between geographical distribution and their phylogenetic relationships of chloroplast genomes and GATA genes. Taken together, we successfully identified the genome-wide intraspecific variations of GATA TFs among 19 ecotypes and they are evolutionarily neutral, which can be explained by the fact that GATA TFs have essential regulatory roles for survival, such as seed germination  and hypocotyl elongation .
To date, more than 1,700 A. thaliana genomes are available [5,18–20,50–53] and more than 4,000 O. sativa genomes [26,29,54–61] are available, but their sequences were not processed as independent genome sequence: only raw sequences and/or sequence variations including single nucleotide polymorphisms and insertions and deletions are available. Once these genome sequences can be applied for this genome-wide identification method of GATA TFs, they will provide high-resolution intraspecific variations of the GATA gene family, which will provide insights into the evolution of GATA TFs within species with comparing with various researches especially for investigating intraspecific variations of their organelle genomes of diverse plant species [145–184]. In addition, these intraspecific variations of GATA TFs may provide the molecular mechanisms of intraspecific phenotypic variations in the aspect of the gene regulation network. One genome-wide association study using B. napa identified deletion region on the genome which contains one TF, orthologs to the HAG1 (At5g61420) controlling aliphatic glucosinolate biosynthesis in A. thaliana . Another example is chickpea bZIP TF which can control its height based on QTL analysis . It indicates that the existence or absence of TFs among cultivars or individuals of the sample species as well as their intraspecific amino acid variations can explain and predict intraspecific variations of phenotypes. We expect that our approach will contribute to understanding the intraspecific characteristics of the GATA gene family in detail as well as provide additional evidence of their biological roles including variable practical phenotypes inside the species.
S1 Fig. BLAST results of AtGATA24 homologs in A. lyrata and A. halleri.
(A) displays AtGATA24 homologs of A. lyrata. (B) shows AtGATA24 homologs of A. halleri.
S2 Fig. The geographical location of 19 A. thaliana genomes.
The red circle means the geographical location of the species. The red circle containing a yellow star implies a not-precise location due to the lack of GPS coordination in Russia.
S1 Table. List of SRA raw reads of 17 A. thaliana ecotypes deposited in NCBI, which were used for assembling complete chloroplast genomes.
We special thanks to Dr. Suhyeon Park for supporting statistical analyses conducted in this study and for discussing about biological meaning of the results presented in this paper.
- 1. Metzker ML. Sequencing technologies—the next generation. Nature reviews genetics. 2010;11(1):31. pmid:19997069
- 2. Goodwin S, McPherson JD, McCombie WR. Coming of age: ten years of next-generation sequencing technologies. Nature Reviews Genetics. 2016;17(6):333. pmid:27184599
- 3. Bleidorn C. Third generation sequencing: technology and its potential impact on evolutionary biodiversity research. Systematics and biodiversity. 2016;14(1):1–8.
- 4. Van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C. Ten years of next-generation sequencing technology. Trends in genetics. 2014;30(9):418–26. pmid:25108476
- 5. Ossowski S, Schneeberger K, Clark RM, Lanz C, Warthmann N, Weigel D. Sequencing of natural strains of Arabidopsis thaliana with short reads. Genome research. 2008;18(12):2024–33. pmid:18818371
- 6. Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience. 2012;1(1):18. pmid:23587118
- 7. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome research. 2008;18(5):821–9. pmid:18349386
- 8. Jackman SD, Vandervalk BP, Mohamadi H, Chu J, Yeo S, Hammond SA, et al. ABySS 2.0: resource-efficient assembly of large genomes using a Bloom filter. Genome research. 2017;27(5):768–77. pmid:28232478
- 9. Liu Y, Schmidt B, Maskell DL. Parallelized short read assembly of large genomes using de Bruijn graphs. BMC bioinformatics. 2011;12(1):354. pmid:21867511
- 10. Georganas E, Buluç A, Chapman J, Oliker L, Rokhsar D, Yelick K, editors. Parallel de bruijn graph construction and traversal for de novo genome assembly. SC’14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis; 2014: IEEE.
- 11. Li D, Liu C-M, Luo R, Sadakane K, Lam T-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31(10):1674–6. pmid:25609793
- 12. Huang S, Li R, Zhang Z, Li L, Gu X, Fan W, et al. The genome of the cucumber, Cucumis sativus L. Nature genetics. 2009;41(12):1275. pmid:19881527
- 13. Rhoads A, Au KF. PacBio sequencing and its applications. Genomics, proteomics & bioinformatics. 2015;13(5):278–89. pmid:26542840
- 14. Albert VA, Barbazuk WB, Depamphilis CW, Der JP, Leebens-Mack J, Ma H, et al. The Amborella genome and the evolution of flowering plants. Science. 2013;342(6165):1241089. pmid:24357323
- 15. Marchant DB, Sessa EB, Wolf PG, Heo K, Barbazuk WB, Soltis PS, et al. The C-Fern (Ceratopteris richardii) genome: insights into plant genome evolution with the first partial homosporous fern genome assembly. Scientific reports. 2019;9(1):1–14. pmid:30626917
- 16. Zhang J, Fu X-X, Li R-Q, Zhao X, Liu Y, Li M-H, et al. The hornwort genome and early land plant evolution. Nature plants. 2020;6(2):107–18. pmid:32042158
- 17. Price DC, Goodenough UW, Roth R, Lee J-H, Kariyawasam T, Mutwil M, et al. Analysis of an improved Cyanophora paradoxa genome assembly. DNA Research. 2019;26(4):287–99. pmid:31098614
- 18. Long Q, Rabanal FA, Meng D, Huber CD, Farlow A, Platzer A, et al. Massive genomic variation and strong selection in Arabidopsis thaliana lines from Sweden. Nature genetics. 2013;45(8):884. pmid:23793030
- 19. Zou Y-P, Hou X-H, Wu Q, Chen J-F, Li Z-W, Han T-S, et al. Adaptation of Arabidopsis thaliana to the Yangtze River basin. Genome biology. 2017;18(1):239. pmid:29284515
- 20. Alonso-Blanco C, Andrade J, Becker C, Bemm F, Bergelson J, Borgwardt KM, et al. 1,135 genomes reveal the global pattern of polymorphism in Arabidopsis thaliana. Cell. 2016;166(2):481–91. pmid:27293186
- 21. Li J-Y, Wang J, Zeigler RS. The 3,000 rice genomes project: new opportunities and challenges for future rice research. GigaScience. 2014;3(1):8. pmid:24872878
- 22. Lin Y-C, Wang J, Delhomme N, Schiffthaler B, Sundström G, Zuccolo A, et al. Functional and evolutionary genomic inferences in Populus through genome and population sequencing of American and European aspen. Proceedings of the National Academy of Sciences. 2018;115(46):E10970–E8. pmid:30373829
- 23. Nakamura N, Hirakawa H, Sato S, Otagaki S, Matsumoto S, Tabata S, et al. Genome structure of Rosa multiflora, a wild ancestor of cultivated roses. Dna Research. 2017;25(2):113–21.
- 24. Evans LM, Slavov GT, Rodgers-Melnick E, Martin J, Ranjan P, Muchero W, et al. Population genomics of Populus trichocarpa identifies signatures of selection and adaptive trait associations. Nature genetics. 2014;46(10):1089. pmid:25151358
- 25. Consortium IBGS. A physical, genetic and functional sequence assembly of the barley genome. Nature. 2012;491(7426):711. pmid:23075845
- 26. Huang X, Sang T, Zhao Q, Feng Q, Zhao Y, Li C, et al. Genome-wide association studies of 14 agronomic traits in rice landraces. Nature genetics. 2010;42(11):961. pmid:20972439
- 27. Yang W, Guo Z, Huang C, Duan L, Chen G, Jiang N, et al. Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice. Nature communications. 2014;5:5087. pmid:25295980
- 28. Yano K, Yamamoto E, Aya K, Takeuchi H, Lo P-c, Hu L, et al. Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nature genetics. 2016;48(8):927. pmid:27322545
- 29. Huang X, Kurata N, Wang Z-X, Wang A, Zhao Q, Zhao Y, et al. A map of rice genome variation reveals the origin of cultivated rice. Nature. 2012;490(7421):497. pmid:23034647
- 30. Huang X, Feng Q, Qian Q, Zhao Q, Wang L, Wang A, et al. High-throughput genotyping by whole-genome resequencing. Genome research. 2009;19(6):1068–76. pmid:19420380
- 31. Zhao K, Tung C-W, Eizenga GC, Wright MH, Ali ML, Price AH, et al. Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nature communications. 2011;2:467. pmid:21915109
- 32. Kumar D. From evidence-based medicine to genomic medicine. Genomic medicine. 2007;1(3–4):95–104. pmid:18923934
- 33. Wang HL, Lopategui J, Amin MB, Patterson SD. KRAS mutation testing in human cancers: the pathologist’s role in the era of personalized medicine. Advances in anatomic pathology. 2010;17(1):23–32. pmid:20032635
- 34. Kerr KM. Personalized medicine for lung cancer: new challenges for pathology. Histopathology. 2012;60(4):531–46. pmid:21916947
- 35. Moch H, Blank P, Dietel M, Elmberger G, Kerr K, Palacios J, et al. Personalized cancer medicine and the future of pathology. Virchows Archiv. 2012;460(1):3–8. pmid:22143935
- 36. Fahrenkrog AM, Neves LG, Resende MF Jr, Vazquez AI, de los Campos G, Dervinis C, et al. Genome-wide association study reveals putative regulators of bioenergy traits in Populus deltoides. New Phytologist. 2017;213(2):799–811. pmid:27596807
- 37. Li X, Zhang R, Patena W, Gang SS, Blum SR, Ivanova N, et al. An indexed, mapped mutant library enables reverse genetics studies of biological processes in Chlamydomonas reinhardtii. The Plant Cell. 2016;28(2):367–87. pmid:26764374
- 38. Wu GA, Terol J, Ibanez V, López-García A, Pérez-Román E, Borredá C, et al. Genomics of the origin and evolution of Citrus. Nature. 2018;554(7692):311. pmid:29414943
- 39. Li R, Li Y, Fang X, Yang H, Wang J, Kristiansen K, et al. SNP detection for massively parallel whole-genome resequencing. Genome research. 2009;19(6):1124–32. pmid:19420381
- 40. Li R, Zhu H, Ruan J, Qian W, Fang X, Shi Z, et al. De novo assembly of human genomes with massively parallel short read sequencing. Genome research. 2010;20(2):265–72. pmid:20019144
- 41. Clarke L, Zheng-Bradley X, Smith R, Kulesha E, Xiao C, Toneva I, et al. The 1000 Genomes Project: data management and community access. Nature methods. 2012;9(5):459. pmid:22543379
- 42. Seo J-S, Rhie A, Kim J, Lee S, Sohn M-H, Kim C-U, et al. De novo assembly and phasing of a Korean human genome. Nature. 2016;538(7624):243. pmid:27706134
- 43. Ahn S-M, Kim T-H, Lee S, Kim D, Ghang H, Kim D-S, et al. The first Korean genome sequence and analysis: full genome sequencing for a socio-ethnic group. Genome research. 2009;19(9):1622–9. pmid:19470904
- 44. Kim J-I, Ju YS, Park H, Kim S, Lee S, Yi J-H, et al. A highly annotated whole-genome sequence of a Korean individual. Nature. 2009;460(7258):1011. pmid:19587683
- 45. Nagasaki M, Yasuda J, Katsuoka F, Nariai N, Kojima K, Kawai Y, et al. Rare variant discovery by deep whole-genome sequencing of 1,070 Japanese individuals. Nature communications. 2015;6:8018. pmid:26292667
- 46. Merker JD, Wenger AM, Sneddon T, Grove M, Zappala Z, Fresard L, et al. Long-read genome sequencing identifies causal structural variation in a Mendelian disease. Genetics in Medicine. 2018;20(1):159. pmid:28640241
- 47. Jain M, Koren S, Miga KH, Quick J, Rand AC, Sasani TA, et al. Nanopore sequencing and assembly of a human genome with ultra-long reads. Nature biotechnology. 2018;36(4):338. pmid:29431738
- 48. Nik-Zainal S, Davies H, Staaf J, Ramakrishna M, Glodzik D, Zou X, et al. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature. 2016;534(7605):47. pmid:27135926
- 49. Pleasance ED, Cheetham RK, Stephens PJ, McBride DJ, Humphray SJ, Greenman CD, et al. A comprehensive catalogue of somatic mutations from a human cancer genome. Nature. 2010;463(7278):191. pmid:20016485
- 50. Ashelford K, Eriksson ME, Allen CM, D’Amore R, Johansson M, Gould P, et al. Full genome re-sequencing reveals a novel circadian clock mutation in Arabidopsis. Genome biology. 2011;12(3):R28. pmid:21429190
- 51. Cao J, Schneeberger K, Ossowski S, Günther T, Bender S, Fitz J, et al. Whole-genome sequencing of multiple Arabidopsis thaliana populations. Nature genetics. 2011;43(10):956. pmid:21874002
- 52. Gan X, Stegle O, Behr J, Steffen JG, Drewe P, Hildebrand KL, et al. Multiple reference genomes and transcriptomes for Arabidopsis thaliana. Nature. 2011;477(7365):419–23. pmid:21874022
- 53. Schmitz RJ, Schultz MD, Urich MA, Nery JR, Pelizzola M, Libiger O, et al. Patterns of population epigenomic diversity. Nature. 2013;495(7440):193. pmid:23467092
- 54. Xu J, Zhao Q, Du P, Xu C, Wang B, Feng Q, et al. Developing high throughput genotyped chromosome segment substitution lines based on population whole-genome re-sequencing in rice (Oryza sativa L.). BMC genomics. 2010;11(1):656.
- 55. Sabot F, Picault N, El-Baidouri M, Llauro C, Chaparro C, Piegu B, et al. Transpositional landscape of the rice genome revealed by paired-end mapping of high-throughput re-sequencing data. The Plant Journal. 2011;66(2):241–6. pmid:21219509
- 56. Lim J-H, Yang H-J, Jung K-H, Yoo S-C, Paek N-C. Quantitative trait locus mapping and candidate gene analysis for plant architecture traits using whole genome re-sequencing in rice. Molecules and cells. 2014;37(2):149. pmid:24599000
- 57. Subbaiyan GK, Waters DL, Katiyar SK, Sadananda AR, Vaddadi S, Henry RJ. Genome-wide DNA polymorphisms in elite indica rice inbreds discovered by whole-genome sequencing. Plant Biotechnology Journal. 2012;10(6):623–34. pmid:22222031
- 58. Qiu J, Zhu J, Fu F, Ye C-Y, Wang W, Mao L, et al. Genome re-sequencing suggested a weedy rice origin from domesticated indica-japonica hybridization: a case study from southern China. Planta. 2014;240(6):1353–63. pmid:25187076
- 59. Waters DL, Henry RJ. Australian wild rice reveals pre-domestication origin of polymorphism deserts in rice genome. PLoS One. 2014;9(6):e98843. pmid:24905808
- 60. Xu X, Liu X, Ge S, Jensen JD, Hu F, Li X, et al. Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes. Nature biotechnology. 2012;30(1):105.
- 61. 3 RGP. The 3,000 rice genomes project. GigaScience. 2014;3(1):2047-217X-3-7.
- 62. Park J, Kim Y, Xi H, editors. Plant Genome Database: An integrated platform for plant genomes. 19th International Botanical Congress; 2017.
- 63. Park J, Xi H, Kim Y, editors. Plant Genome Database Release 2.5: A Standardized Plant Genome Repository for 233 species. Plant and Animal Genome XXVI Conference (PAG 2018); 2018.
- 64. Singh KB, Foley RC, Oñate-Sánchez L. Transcription factors in plant defense and stress responses. Current opinion in plant biology. 2002;5(5):430–6. pmid:12183182
- 65. Gendron JM, Pruneda-Paz JL, Doherty CJ, Gross AM, Kang SE, Kay SA. Arabidopsis circadian clock protein, TOC1, is a DNA-binding transcription factor. Proceedings of the National Academy of Sciences. 2012;109(8):3167–72. pmid:22315425
- 66. Santos LA, de Souza SR, Fernandes MS. OsDof25 expression alters carbon and nitrogen metabolism in Arabidopsis under high N-supply. Plant biotechnology reports. 2012;6(4):327–37.
- 67. Ramírez V, Coego A, López A, Agorio A, Flors V, Vera P. Drought tolerance in Arabidopsis is controlled by the OCP3 disease resistance regulator. The Plant Journal. 2009;58(4):578–91. pmid:19175769
- 68. Saleh A. Plant AP2/ERF transcription factors. Genetika. 2003;35(1):37–50.
- 69. Nakashima K, Takasaki H, Mizoi J, Shinozaki K, Yamaguchi-Shinozaki K. NAC transcription factors in plant abiotic stress responses. Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms. 2012;1819(2):97–103. pmid:22037288
- 70. Eulgem T, Rushton PJ, Robatzek S, Somssich IE. The WRKY superfamily of plant transcription factors. Trends in plant science. 2000;5(5):199–206. pmid:10785665
- 71. Xu K, Chen S, Li T, Ma X, Liang X, Ding X, et al. OsGRAS23, a rice GRAS transcription factor gene, is involved in drought stress response through regulating expression of stress-responsive genes. BMC plant biology. 2015;15(1):141. pmid:26067440
- 72. Tian C, Wan P, Sun S, Li J, Chen M. Genome-wide analysis of the GRAS gene family in rice and Arabidopsis. Plant molecular biology. 2004;54(4):519–32. pmid:15316287
- 73. Reyes JC, Muro-Pastor MI, Florencio FJ. The GATA family of transcription factors in Arabidopsis and rice. Plant physiology. 2004;134(4):1718–32. pmid:15084732
- 74. Merika M, Orkin SH. DNA-binding specificity of GATA family transcription factors. Molecular cellular biology. 1993;13(7):3999–4010. pmid:8321207
- 75. Park J-S, Kim H-J, Kim S-O, Kong S-H, Park J-J, Kim S-R, et al. A comparative genome-wide analysis of GATA transcription factors in fungi. Genomics & Informatics. 2006;4(4):147–60.
- 76. Liu PP, Koizuka N, Martin RC, Nonogaki H. The BME3 (Blue Micropylar End 3) GATA zinc finger transcription factor is a positive regulator of Arabidopsis seed germination. The Plant Journal. 2005;44(6):960–71. pmid:16359389
- 77. Nawy T, Bayer M, Mravec J, Friml J, Birnbaum KD, Lukowitz W. The GATA factor HANABA TARANU is required to position the proembryo boundary in the early Arabidopsis embryo. Developmental cell. 2010;19(1):103–13. pmid:20643354
- 78. Shikata M, Matsuda Y, Ando K, Nishii A, Takemura M, Yokota A, et al. Characterization of Arabidopsis ZIM, a member of a novel plant-specific GATA factor gene family. Journal of experimental botany. 2004;55(397):631–9. pmid:14966217
- 79. Liu H, Li T, Wang Y, Zheng J, Li H, Hao C, et al. TaZIM-A1 negatively regulates flowering time in common wheat (Triticum aestivum L.). Journal of integrative plant biology. 2018.
- 80. Zhang C, Hou Y, Hao Q, Chen H, Chen L, Yuan S, et al. Genome-wide survey of the soybean GATA transcription factor gene family and expression analysis under low nitrogen stress. PLoS One. 2015;10(4):e0125174. pmid:25886477
- 81. Zhang Z, Zou X, Huang Z, Fan S, Qun G, Liu A, et al. Genome-wide identification and analysis of the evolution and expression patterns of the GATA transcription factors in three species of Gossypium genus. Gene. 2018. pmid:30253181
- 82. Chen H, Shao H, Li K, Zhang D, Fan S, Li Y, et al. Genome-wide identification, evolution, and expression analysis of GATA transcription factors in apple (Malus× domestica Borkh.). Gene. 2017;627:460–72. pmid:28669931
- 83. Qi Y, Chunli Z, Tingting Z, Xiangyang X. Bioinformatics Analysis of GATA Transcription Factor in Pepper. Chinese Agricultural Science Bulletin. 2017;2017(17):5.
- 84. Ao T, Liao X, Xu W, Liu A. Identification and characterization of GATA gene family in Castor Bean (Ricinus communis). Plant Diver Resour. 2015;37:453–62.
- 85. Yuan Q, Zhang C, Zhao T, Yao M, Xu X. A Genome-Wide Analysis of GATA Transcription Factor Family in Tomato and Analysis of Expression Patterns. INTERNATIONAL JOURNAL OF AGRICULTURE BIOLOGY. 2018;20(6):1274–82.
- 86. Zhang Z, Ren C, Zou L, Wang Y, Li S, Liang Z. Characterization of the GATA gene family in Vitis vinifera: genome-wide analysis, expression profiles, and involvement in light and phytohormone response. Genome. 2018;61(10):713–23. pmid:30092656
- 87. Wang T, Yang Y, Lou S, Wei W, Zhao Z, Lin C, et al. Genome-wide analysis of GATA factors in moso bamboo (Phyllostachys edulis) unveils that PeGATAs regulate shoot rapid-growth and rhizome development. bioRxiv. 2019:744003.
- 88. Consortium IAI, Doherty C, Friesner J, Gregory B, Loraine A, Megraw M, et al. Arabidopsis bioinformatics resources: The current state, challenges, and priorities for the future. Plant Direct. 2019;3(1):e00109. pmid:31245752
- 89. Teakle G, Gilmartin P. Two forms of type IV zinc-finger motif and their kingdom-specific distribution between the flora, fauna and fungi. Trends in biochemical sciences. 1998;23(3):100–2. pmid:9581501
- 90. Park J, Xi H, editors. Genome Archive (R): Standardized Genome Repository for Supporting Large-Scale Genome Analyses. Plant and Animal Genome XXVI Conference (January 13–17, 2018); 2018: PAG.
- 91. Jones P, Binns D, Chang H-Y, Fraser M, Li W, McAnulla C, et al. InterProScan 5: genome-scale protein function classification. Bioinformatics. 2014;30(9):1236–40. pmid:24451626
- 92. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20. pmid:24695404
- 93. Zhao Q-Y, Wang Y, Kong Y-M, Luo D, Li X, Hao P, editors. Optimizing de novo transcriptome assembly from short-read RNA-Seq data: a comparative study. BMC bioinformatics; 2011: Springer.
- 94. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25(16):2078–9. pmid:19505943
- 95. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint arXiv:13033997. 2013.
- 96. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Molecular biology and evolution. 2018;35(6):1547–9. pmid:29722887
- 97. Thompson JD, Gibson TJ, Higgins DG. Multiple sequence alignment using ClustalW and ClustalX. Current protocols in bioinformatics. 2003;(1):2.3. 1–2.3. 22.
- 98. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Molecular biology and evolution. 2013;30(4):772–80. pmid:23329690
- 99. Nguyen L-T, Schmidt HA, Von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Molecular biology and evolution. 2015;32(1):268–74. pmid:25371430
- 100. Huelsenbeck JP, Ronquist F. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics. 2001;17(8):754–5. pmid:11524383
- 101. Gupta P, Nutan KK, Singla-Pareek SL, Pareek A. Abiotic stresses cause differential regulation of alternative splice forms of gata transcription factor in rice. Frontiers in plant science. 2017;8:1944. pmid:29181013
- 102. Shaikhali J, de Dios Barajas-Lopéz J, Ötvös K, Kremnev D, Garcia AS, Srivastava V, et al. The CRYPTOCHROME1-dependent response to excess light is mediated through the transcriptional activators ZINC FINGER PROTEIN EXPRESSED IN INFLORESCENCE MERISTEM LIKE1 and ZML2 in Arabidopsis. The Plant Cell. 2012:tpc. 112.100099.
- 103. Kong W, Sun T, Zhang C, Qiang Y, Li Y. Micro-Evolution Analysis Reveals Diverged Patterns of Polyol Transporters in Seven Gramineae Crops. Frontiers in genetics. 2020;11:565. pmid:32636871
- 104. Sánchez D, Ganfornina MD, Gutiérrez G, Marín A. Exon-intron structure and evolution of the Lipocalin gene family. Molecular biology and evolution. 2003;20(5):775–83. pmid:12679526
- 105. Pascual-Le Tallec L, Demange C, Lombes M. Human mineralocorticoid receptor A and B protein forms produced by alternative translation sites display different transcriptional activities. European journal of endocrinology. 2004;150(4):585–90. pmid:15080790
- 106. Kelemen O, Convertini P, Zhang Z, Wen Y, Shen M, Falaleeva M, et al. Function of alternative splicing. Gene. 2013;514(1):1–30. pmid:22909801
- 107. Zhu W, Guo Y, Chen Y, Wu D, Jiang L. Genome-Wide Identification and Characterization of GATA Family Genes in Brassica Napus. 2020.
- 108. An Y, Zhou Y, Han X, Shen C, Wang S, Liu C, et al. The GATA transcription factor GNC plays an important role in photosynthesis and growth in poplar. Journal of experimental botany. 2020;71(6):1969–84. pmid:31872214
- 109. Huang Q, Shi M, Wang C, Hu J, Kai G. Genome-wide Survey of the GATA Gene Family in Camptothecin-producing Plant Ophiorrhiza Pumila. 2021.
- 110. Jiang L, Yu X, Chen D, Feng H, Li J. Identification, phylogenetic evolution and expression analysis of GATA transcription factor family in maize (Zea mays). International Journal of Agriculture and Biology. 2020;23(3):637–43.
- 111. Yu R, Chang Y, Chen H, Feng J, Wang H, Tian T, et al. Genome-wide identification of the GATA gene family in potato (Solanum tuberosum L.) and expression analysis. Journal of Plant Biochemistry and Biotechnology. 2021:1–12.
- 112. Yu C, Li N, Yin Y, Wang F, Gao S, Jiao C, et al. Genome-wide identification and function characterization of GATA transcription factors during development and in response to abiotic stresses and hormone treatments in pepper. Journal of Applied Genetics. 2021:1–16. pmid:33624251
- 113. Peng W, Li W, Song N, Tang Z, Liu J, Wang Y, et al. Genome-Wide Characterization, Evolution, and Expression Profile Analysis of GATA Transcription Factors in Brachypodium distachyon. International journal of molecular sciences. 2021;22(4):2026. pmid:33670757
- 114. Niu L, Chu HD, Tran CD, Nguyen KH, Pham HX, Le DT, et al. The GATA gene family in chickpea: structure analysis and transcriptional responses to abscisic acid and dehydration treatments revealed potential genes involved in drought adaptation. Journal of Plant Growth Regulation. 2020;39(4):1647–60.
- 115. Hartmann B, Castelo R, Miñana B, Peden E, Blanchette M, Rio DC, et al. Distinct regulatory programs establish widespread sex-specific alternative splicing in Drosophila melanogaster. Rna. 2011;17(3):453–68. pmid:21233220
- 116. Syed NH, Kalyna M, Marquez Y, Barta A, Brown JW. Alternative splicing in plants–coming of age. Trends in plant science. 2012;17(10):616–23. pmid:22743067
- 117. Nagaoka M, Kondo Y, Uno Y, Sugiura Y. Influence of amino acid numbers between two ligand cysteines of zinc finger proteins on affinity and specificity of DNA binding. Biochemical and biophysical research communications. 2002;296(3):553–9. pmid:12176016
- 118. Schulze WX, Schneider T, Starck S, Martinoia E, Trentmann O. Cold acclimation induces changes in Arabidopsis tonoplast protein abundance and activity and alters phosphorylation of tonoplast monosaccharide transporters. The Plant Journal. 2012;69(3):529–41. pmid:21988472
- 119. Suárez-López P, Wheatley K, Robson F, Onouchi H, Valverde F, Coupland G. CONSTANS mediates between the circadian clock and the control of flowering in Arabidopsis. Nature. 2001;410(6832):1116. pmid:11323677
- 120. Chini A, Fonseca S, Chico JM, Fernández-Calvo P, Solano R. The ZIM domain mediates homo-and heteromeric interactions between Arabidopsis JAZ proteins. The Plant Journal. 2009;59(1):77–87. pmid:19309455
- 121. Melotto M, Mecey C, Niu Y, Chung HS, Katsir L, Yao J, et al. A critical role of two positively charged amino acids in the Jas motif of Arabidopsis JAZ proteins in mediating coronatine-and jasmonoyl isoleucine-dependent interactions with the COI1 F-box protein. The Plant Journal. 2008;55(6):979–88. pmid:18547396
- 122. Pace CN, Scholtz JM. A helix propensity scale based on experimental studies of peptides and proteins. Biophysical journal. 1998;75(1):422–7. pmid:9649402
- 123. Harper AL, Trick M, Higgins J, Fraser F, Clissold L, Wells R, et al. Associative transcriptomics of traits in the polyploid crop species Brassica napus. Nature biotechnology. 2012;30(8):798. pmid:22820317
- 124. Kujur A, Upadhyaya HD, Bajaj D, Gowda C, Sharma S, Tyagi AK, et al. Identification of candidate genes and natural allelic variants for QTLs governing plant height in chickpea. Scientific reports. 2016;6(1):1–9. pmid:28442746
- 125. Teakle GR, Manfield IW, Graham JF, Gilmartin PM. Arabidopsis thaliana GATA factors: organisation, expression and DNA-binding characteristics. Plant Molecular Biology. 2002;50(1):43–56. pmid:12139008
- 126. Bi YM, Zhang Y, Signorelli T, Zhao R, Zhu T, Rothstein S. Genetic analysis of Arabidopsis GATA transcription factor gene family reveals a nitrate-inducible member important for chlorophyll synthesis and glucose sensitivity. The Plant Journal. 2005;44(4):680–92. pmid:16262716
- 127. Chiang Y-H, Zubo YO, Tapken W, Kim HJ, Lavanway AM, Howard L, et al. Functional characterization of the GATA transcription factors GNC and CGA1 reveals their key role in chloroplast development, growth, and division in Arabidopsis. Plant Physiology. 2012;160(1):332–48. pmid:22811435
- 128. Ranftl QL, Bastakis E, Klermund C, Schwechheimer C. LLM-domain containing B-GATA factors control different aspects of cytokinin-regulated development in Arabidopsis thaliana. Plant physiology. 2016;170(4):2295–311. pmid:26829982
- 129. Zhao Y, Medrano L, Ohashi K, Fletcher JC, Yu H, Sakai H, et al. HANABA TARANU is a GATA transcription factor that regulates shoot apical meristem and flower development in Arabidopsis. The Plant Cell. 2004;16(10):2586–600. pmid:15367721
- 130. Zhang X, Zhou Y, Ding L, Wu Z, Liu R, Meyerowitz EM. Transcription repressor HANABA TARANU controls flower development by integrating the actions of multiple hormones, floral organ specification genes, and GATA3 family genes in Arabidopsis. The Plant Cell. 2013;25(1):83–101. pmid:23335616
- 131. Kanei M, Horiguchi G, Tsukaya H. Stable establishment of cotyledon identity during embryogenesis in Arabidopsis by ANGUSTIFOLIA3 and HANABA TARANU. Development. 2012;139(13):2436–46. pmid:22669825
- 132. Hudson D, Guevara D, Yaish MW, Hannam C, Long N, Clarke JD, et al. GNC and CGA1 modulate chlorophyll biosynthesis and glutamate synthase (GLU1/Fd-GOGAT) expression in Arabidopsis. PLoS One. 2011;6(11):e26765. pmid:22102866
- 133. Bastakis E, Hedtke B, Klermund C, Grimm B, Schwechheimer C. LLM-domain B-GATA transcription factors play multifaceted roles in controlling greening in Arabidopsis. The Plant Cell. 2018;30(3):582–99. pmid:29453227
- 134. Mara CD, Irish VF. Two GATA transcription factors are downstream effectors of floral homeotic gene action in Arabidopsis. Plant Physiology. 2008;147(2):707–18. pmid:18417639
- 135. Richter R, Behringer C, Zourelidou M, Schwechheimer C. Convergence of auxin and gibberellin signaling on the regulation of the GATA transcription factors GNC and GNL in Arabidopsis thaliana. Proceedings of the National Academy of Sciences. 2013;110(32):13192–7. pmid:23878229
- 136. Richter R, Behringer C, Müller IK, Schwechheimer C. The GATA-type transcription factors GNC and GNL/CGA1 repress gibberellin signaling downstream from DELLA proteins and PHYTOCHROME-INTERACTING FACTORS. Genes & Development. 2010;24(18):2093–104. pmid:20844019
- 137. Richter R, Bastakis E, Schwechheimer C. Cross-repressive interactions between SOC1 and the GATAs GNC and GNL/CGA1 in the control of greening, cold tolerance, and flowering time in Arabidopsis. Plant Physiology. 2013;162(4):1992–2004. pmid:23739688
- 138. Zubo YO, Blakley IC, Franco-Zorrilla JM, Yamburenko MV, Solano R, Kieber JJ, et al. Coordination of chloroplast development through the action of the GNC and GLK transcription factor families. Plant physiology. 2018;178(1):130–47. pmid:30002259
- 139. Klermund C, Ranftl QL, Diener J, Bastakis E, Richter R, Schwechheimer C. LLM-domain B-GATA transcription factors promote stomatal development downstream of light signaling pathways in Arabidopsis thaliana hypocotyls. The Plant Cell. 2016;28(3):646–60. pmid:26917680
- 140. Naito T, Kiba T, Koizumi N, Yamashino T, Mizuno T. Characterization of a unique GATA family gene that responds to both light and cytokinin in Arabidopsis thaliana. Bioscience, Biotechnology, and Biochemistry. 2007;71(6):1557–60. pmid:17587690
- 141. Nishii A, Takemura M, Fujita H, Shikata M, Yokota A, Kohchi T. Characterization of a novel gene encoding a putative single zinc-finger protein, ZIM, expressed during the reproductive phase in Arabidopsis thaliana. Bioscience, biotechnology, and biochemistry. 2000;64(7):1402–9. pmid:10945256
- 142. Sato S, Nakamura Y, Kaneko T, Asamizu E, Tabata S. Complete structure of the chloroplast genome of Arabidopsis thaliana. DNA research. 1999;6(5):283–90. pmid:10574454
- 143. Stadermann KB, Holtgräwe D, Weisshaar B. Chloroplast genome sequence of Arabidopsis thaliana accession Landsberg erecta, assembled from single-molecule, real-time sequencing data. Genome Announcements. 2016;4(5). pmid:27660776
- 144. Park J, Xi H, Kim Y. The complete chloroplast genome of Arabidopsis thaliana isolated in Korea (Brassicaceae): an investigation of intraspecific variations of the chloroplast genome of Korean A. Thaliana. International journal of genomics. 2020;2020. pmid:32964010
- 145. Kim Y, Yi J-S, Min J, Xi H, Kim DY, Son J, et al. The complete chloroplast genome of Aconitum coreanum (H. Lév.) Rapaics (Ranunculaceae). Mitochondrial DNA Part B. 2019;4(2):3404–6. pmid:33366014
- 146. Choi YG, Yun N, Park J, Xi H, Min J, Kim Y, et al. The second complete chloroplast genome sequence of the Viburnum erosum (Adoxaceae) showed a low level of intra-species variations. Mitochondrial DNA Part B. 2020;5(1):271–2.
- 147. Oh S-H, Suh HJ, Park J, Kim Y, Kim S. The complete chloroplast genome sequence of Goodyera schlechtendaliana in Korea (Orchidaceae). Mitochondrial DNA Part B. 2019;4(2):2692–3. pmid:33365686
- 148. Min J, Park J, Kim Y, Kwon W. The complete chloroplast genome of Artemisia fukudo Makino (Asteraceae): providing insight of intraspecies variations. Mitochondrial DNA Part B. 2019;4(1):1510–2.
- 149. Wang W, Chen S, Zhang X. Whole-genome comparison reveals heterogeneous divergence and mutation hotspots in chloroplast genome of Eucommia ulmoides Oliver. International journal of molecular sciences. 2018;19(4):1037. pmid:29601491
- 150. Park J, Kim Y. The second complete chloroplast genome of Dysphania pumilio (R. Br.) mosyakin & clemants (Amranthaceae): intraspecies variation of invasive weeds. Mitochondrial DNA Part B. 2019;4(1):1428–9.
- 151. Jeon J-H, Park H-S, Park JY, Kang TS, Kwon K, Kim YB, et al. Two complete chloroplast genome sequences and intra-species diversity for Rehmannia glutinosa (Orobanchaceae). Mitochondrial DNA Part B. 2019;4(1):176–7.
- 152. Cho M-S, Kim Y, Kim S-C, Park J. The complete chloroplast genome of Korean Pyrus ussuriensis Maxim. (Rosaceae): providing genetic background of two types of P. ussuriensis. Mitochondrial DNA Part B. 2019;4(2):2424–5. pmid:33365570
- 153. Park J, Kim Y, Lee K. The complete chloroplast genome of Korean mock strawberry, Duchesnea chrysantha (Zoll. & Moritzi) Miq.(Rosoideae). Mitochondrial DNA Part B. 2019;4(1):864–5.
- 154. Kim Y, Heo K-I, Park J. The second complete chloroplast genome sequence of Pseudostellaria palibiniana (Takeda) Ohwi (Caryophyllaceae): intraspecies variations based on geographical distribution. Mitochondrial DNA Part B. 2019;4(1):1310–1.
- 155. Park J, Kim Y, Xi H, Oh Y-j, Hahm KM, Ko J. The complete chloroplast genome of common camellia tree, Camellia japonica L. (Theaceae), adapted to cold environment in Korea. Mitochondrial DNA Part B. 2019;4(1):1038–40.
- 156. Kim Y, Heo K-I, Nam S, Xi H, Lee S, Park J. The complete chloroplast genome of candidate new species from Rosa rugosa in Korea (Rosaceae). Mitochondrial DNA Part B. 2019;4(2):2433–5. pmid:33365574
- 157. Heo K-I, Park J, Kim Y, Kwon W. The complete chloroplast genome of Potentilla stolonifera var. quelpaertensis Nakai. Mitochondrial DNA Part B. 2019;4(1):1289–91.
- 158. Oh S-H, Suh HJ, Park J, Kim Y, Kim S. The complete chloroplast genome sequence of a morphotype of Goodyera schlechtendaliana (Orchidaceae) with the column appendages. Mitochondrial DNA Part B. 2019;4(1):626–7.
- 159. Kwon W, Kim Y, Park J. The complete mitochondrial genome of Korean Marchantia polymorpha subsp. ruderalis Bischl. & Boisselier: inverted repeats on mitochondrial genome between Korean and Japanese isolates. Mitochondrial DNA Part B. 2019.
- 160. Park J, Xi H, Kim Y, Heo K-I, Nho M, Woo J, et al. The complete chloroplast genome of cold hardiness individual of Coffea arabica L. (Rubiaceae). Mitochondrial DNA Part B. 2019;4(1):1083–4.
- 161. Park J, Kim Y, Xi H, Nho M, Woo J, Seo Y. The complete chloroplast genome of high production individual tree of Coffea arabica L. (Rubiaceae). Mitochondrial DNA Part B. 2019;4(1):1541–2.
- 162. Park J, Kim Y, Xi H, Heo . The complete chloroplast genome of ornamental coffee tree, Coffea arabica L.(Rubiaceae). Mitochondrial DNA Part B. 2019;4(1):1059–60.
- 163. Min J, Kim Y, Xi H, Heo K-I, Park J. The complete chloroplast genome of coffee tree, Coffea arabica L.‘Typica’ (Rubiaceae). Mitochondrial DNA Part B. 2019;4(2):2240–1. pmid:33365492
- 164. Park J, Kim Y, Xi H, Heo K-I. The complete chloroplast genome of coffee tree, Coffea arabica L.‘Blue Mountain’ (Rubiaceae). Mitochondrial DNA Part B. 2019;4(2):2436–7. pmid:33365575
- 165. Park J, Kim Y, Xi H. The complete chloroplast genome sequence of male individual of Korean endemic willow, Salix koriyanagi Kimura (Salicaceae). Mitochondrial DNA Part B. 2019;4(1):1619–21.
- 166. Park J, Kim Y, Xi H, Jang T, Park J-H. The complete chloroplast genome of Abeliophyllum distichum Nakai (Oleaceae), cultivar Ok Hwang 1ho: insights of cultivar specific variations of A. distichum. Mitochondrial DNA Part B. 2019;4(1):1640–2.
- 167. Park J, Min J, Kim Y, Xi H, Kwon W, Jang T, et al. The complete chloroplast genome of a new candidate cultivar, Dae Ryun, of Abeliophyllum distichum Nakai (Oleaceae). Mitochondrial DNA Part B. 2019;4(2):3713–5. pmid:33366156
- 168. Min J, Kim Y, Xi H, Jang T, Kim G, Park J, et al. The complete chloroplast genome of a new candidate cultivar, Sang Jae, of Abeliophyllum distichum Nakai (Oleaceae): initial step of A. distichum intraspecies variations atlas. Mitochondrial DNA Part B. 2019;4(2):3716–8. pmid:33366157
- 169. Kim Y, Park J, Chung Y. The comparison of the complete chloroplast genome of Suaeda japonica Makino presenting different external morphology (Amaranthaceae). Mitochondrial DNA Part B. 2020;5(2):1616–8.
- 170. Park J, Kim Y, Lee G-H, Park C-H. The complete chloroplast genome of Selaginella tamariscina (Beauv.) Spring (Selaginellaceae) isolated in Korea. Mitochondrial DNA Part B. 2020;5(2):1654–6.
- 171. Park J, Kim Y, Xi H, Heo K-I, Min J, Woo J, et al. The complete chloroplast genomes of two cold hardness coffee trees, Coffea arabica L. (Rubiaceae). Mitochondrial DNA Part B. 2020;5(2):1619–21.
- 172. Park J, Oh S-H. A second complete chloroplast genome sequence of Fagus multinervis Nakai (Fagaceae): intraspecific variations on chloroplast genome. Mitochondrial DNA Part B. 2020;5(2):1868–9.
- 173. Park J, Suh Y, Kim S. A complete chloroplast genome sequence of Gastrodia elata (Orchidaceae) represents high sequence variation in the species. Mitochondrial DNA Part B. 2020;5(1):517–9. pmid:33366628
- 174. Heo K-I, Park J, Xi H, Min J. The complete chloroplast genome of Agrimonia pilosa Ledeb. isolated in Korea (Rosaceae): investigation of intraspecific variations on its chloroplast genomes. Mitochondrial DNA Part B. 2020;5(3):2264–6. pmid:33367001
- 175. Park J, Min J, Kim Y, Chung Y. The Comparative Analyses of Six Complete Chloroplast Genomes of Morphologically Diverse Chenopodium album L.(Amaranthaceae) Collected in Korea. International Journal of Genomics. 2021;2021. pmid:33996994
- 176. Heo K-I, Park J, Kim Y. The complete chloroplast genome of new variety candidate in Korea, Potentilla freyniana var. chejuensis (Rosoideae). Mitochondrial DNA Part B. 2019;4(1):1354–6.
- 177. Park J, Bae Y, Kim B-Y, Nam G-H, Park J-M, Lee BY, et al. The complete chloroplast genome of Campanula takesimana Nakai from Dokdo Island in Korea (Campanulaceae). Mitochondrial DNA Part B. 2021;6(1):135–7. pmid:33521286
- 178. Suh H-J, Min J, Park J, Oh S-H. The complete chloroplast genome of Aruncus dioicus var. kamtschaticus (Rosaceae). Mitochondrial DNA Part B. 2021;6(3):1256–8. pmid:33829101
- 179. Lee B, Park J. The complete chloroplast genome of Zoysia matrella (L.) Merr. isolated in Korea (Poaceae): investigation of intraspecific variations on chloroplast genomes. Mitochondrial DNA Part B. 2021;6(2):572–4. pmid:33628934
- 180. Oh S-H, Park J. The complete chloroplast genome of Euscaphis japonica (Thunb.) Kanitz (Staphyleaceae) isolated in Korea. Mitochondrial DNA Part B. 2020;5(3):3751–3. pmid:33367094
- 181. Park J, Kim Y, Kwon W, Xi H, Kwon M. The complete chloroplast genome of tulip tree, Liriodendron tulifipera L.(Magnoliaceae): investigation of intra-species chloroplast variations. Mitochondrial DNA Part B. 2019;4(2):2523–4. pmid:33365610
- 182. Park J, Kim Y, Kwon W, Nam S, Song MJ. The second complete chloroplast genome sequence of Nymphaea alba L.(Nymphaeaceae) to investigate inner-species variations. Mitochondrial DNA Part B. 2019;4(1):1014–5.
- 183. Park J, Kim Y, Xi H. The complete chloroplast genome of aniseed tree, Illicium anisatum L.(Schisandraceae). Mitochondrial DNA Part B. 2019;4(1):1023–4.
- 184. Park J, Kim Y, Xi H, Oh YJ, Hahm KM, Ko J. The complete chloroplast genome of common camellia tree in Jeju island, Korea, Camellia japonica L.(Theaceae): intraspecies variations on common camellia chloroplast genomes. Mitochondrial DNA Part B. 2019;4(1):1292–3.