https://orcid.org/0000-0002-2387-0135
Figures
Abstract
Almond breeding programs aimed at selecting cultivars adapted to intensive orchards have recently focused on the optimization of tree architecture. This multifactorial trait is defined by numerous components controlled by processes such as hormonal responses, gravitropism and light perception. Gravitropism sensing is crucial to control the branch angle and therefore, the tree habit. A gene family, denominated IGT family after a shared conserved domain, has been described as involved in the regulation of branch angle in several species, including rice and Arabidopsis, and even in fruit trees like peach. Here we identified six members of this family in almond: LAZY1, LAZY2, TAC1, DRO1, DRO2, IGT-like. After analyzing their protein sequences in forty-one almond cultivars and wild species, little variability was found, pointing a high degree of conservation in this family. To our knowledge, this is the first effort to analyze the diversity of IGT family proteins in members of the same tree species. Gene expression was analyzed in fourteen cultivars of agronomical interest comprising diverse tree habit phenotypes. Only LAZY1, LAZY2 and TAC1 were expressed in almond shoot tips during the growing season. No relation could be established between the expression profile of these genes and the variability observed in the tree habit. However, some insight has been gained in how LAZY1 and LAZY2 are regulated, identifying the IPA1 almond homologues and other transcription factors involved in hormonal responses as regulators of their expression. Besides, we have found various polymorphisms that could not be discarded as involved in a potential polygenic origin of regulation of architectural phenotypes. Therefore, we have established that neither the expression nor the genetic polymorphism of IGT family genes are correlated to diversity of tree habit in currently commercialized almond cultivars, with other gene families contributing to the variability of these traits.
Citation: Montesinos Á, Dardick C, Rubio-Cabetas MJ, Grimplet J (2021) Polymorphisms and gene expression in the almond IGT family are not correlated to variability in growth habit in major commercial almond cultivars. PLoS ONE 16(10): e0252001. https://doi.org/10.1371/journal.pone.0252001
Editor: Sara Amancio, Universidade de Lisboa Instituto Superior de Agronomia, PORTUGAL
Received: May 7, 2021; Accepted: September 29, 2021; Published: October 13, 2021
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: Research was funded by the grants RTA2014-00062-00-00 (MJRC, JG, AM), RTI-2018-094210-R-100 (MJRC, JG, AM) and FPI-INIA CPD2016-0056 (AM) from the Spanish Research State Agency (AEI) (https://www.ciencia.gob.es/portal/site/MICINN/aei). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
In the last decade, more intensive almond orchards have become the predominant model in the Mediterranean areas, in order to increase productivity and to reduce labor cost [1]. Under this scenario, there is a growing interest in developing almond cultivars more adapted to mechanical pruning and presenting a natural branching that reduces pruning cost to achieve the desired tree structure. In consequence, optimized cultivars need to have low vigor, reasonable branching and an upright overall architecture.
Tree architecture is a highly complex trait defined by the sum of phenotypic components that influence the three-dimensional shape of the tree. It involves growth direction, growth rhythm, branching mode, position of the branches, the sexual differentiation of meristems and the length of axillary shoots [2]. Tree architecture is affected by environmental parameters such as light perception, gravity sensing, sugar availability or nutrients supply that take part in the plant physiological and hormonal regulation [3–5].
Two physiological processes that affect the plant architecture are apical dominance and the lateral bud outgrowth. Auxins act as the principal factor in the control of apical dominance. This hormone is synthesized at the apical leaves and transported throughout the plant, inhibiting lateral bud outgrowth. It promotes strigolactone (SL) biosynthesis, which is able to translocate to the bud and stop bud outgrowth [6, 7]. Cytokinins (CKs) act antagonistically to SLs, promoting Shoot Apical Meristem (SAM) differentiation and therefore bud outgrowth [8, 9]. Sugar availability has also been described as a positive regulator of bud outgrowth [10, 11]. These processes are essential for shaping the plant structure, although the overall tree habit, which is defined by the relative angle of the branches, is essentially regulated by two responses: light perception and gravitropism.
Light perception regulates both the growth and the direction of lateral branches. It is based on the ratio between red light and far red light (R:FR), captured by phytochrome photoreceptors phyA and phyB. When the R:FR is low, phyA is activated while phyB is inhibited, which sets off the inhibition of bud outgrowth, redistributing the auxin flux and focusing plant efforts in the growth of the primary axis [12–15].
Gravitropism is the main regulator of the branching angle. Its regulation occurs in specific cells called statocytes, where organelles containing large starch grains, called amyloplasts, act as gravity sensors [16]. These organelles sediment in the direction of the gravitational vector, triggering a signal which involves the opening of ion channels and the reorganization of the cytoskeleton [17–19]. This response leads to a relocation of auxin carriers PIN3 and PIN7 changing the direction of the auxin flux, which provokes a differential growth and a curvature in the opposing direction of the gravitational vector [20–22].
LAZY1 has been described extensively as an influential factor in the control of plant architecture since its characterization in Oryza sativa (rice) as a regulator of tiller angle in agravitropic mutants [23–25]. Orthologs of this gene were found in Arabidopsis thaliana and Zea mays (maize), leading to the characterization of the same family in these species [26–28]. This family also includes DRO1, which was initially reported as an influential factor of root architecture in rice [29, 30]. LAZY1 is related to TAC1, which is also involved in plant architecture regulation. TAC1 was first identified in rice mutants with increased tiller angle, and it has also been characterized in Arabidopsis [31, 32]. TAC1 differs from the rest of the family, denominated IGT family, in its lack of an EAR-like conserved domain denominated CCL domain located in the C-terminal region, which consists of 14 aminoacids [31, 33]. This conserved region is essential for the function and subcellular localization of IGT proteins. Since LAZY1 and TAC1 promote opposite phenotypes, and due to the lack of the CCL conserved domain, TAC1 has been proposed as a negative regulator of LAZY1 activity, in an upstream capacity [31, 33, 34]. However, the specific mechanism of the interaction between LAZY1 and TAC1 interaction is yet to be discovered [35].
The involvement of IGT family genes in gravitropism has been described in Arabidopsis and rice, acting as mediators between the sedimentation of statoliths gravity sensors and the relocation of auxin PIN carriers [33, 36–38]. Although a direct interaction with the phyA-phyB system is yet to be discovered, TAC1 expression is influenced by the light perception regulator COP1, which would provide for integration between light and gravity responses [39].
The analysis of the mutation br in Prunus persica (peach), which is related to vertically oriented growth of branches, led to the annotation of an ortholog of TAC1 [31]. Further studies have described the involvement of TAC1 in auxin response mechanisms within different branching genotypes in peach, proving that the mechanisms involved in the control of the growth habit are conserved to a certain point in Prunus species [40, 41].
A total of 6 members of the IGT family have been found in Prunus dulcis: LAZY1, LAZY2, DRO1, DRO2, IGT-like, TAC1. With the exception of TAC1, all of them have the five conserved regions described in Arabidopsis [33]. In this study we carried out a genomic comparison for these six genes in forty-one almond cultivars and wild species with different growth habit phenotypes. Moreover, we analyzed the gene expression of the IGT family members in fourteen selected cultivars and searched for variants in their promoter region. Posteriorly, LAZY1 and LAZY2 promoters were inspected to identify regulatory elements (REs) associated to transcription factors (TFs) that could be involved in the regulation of LAZY1 and LAZY2. Twenty-one TFs were selected due to its described function or its presence in growing shoot tips in previous studies and the analysis of their gene expression was carried out.
Material and methods
Almond tree populations
Forty-one cultivars and wild species (S1 File), whose genome had been previously obtained as part of the almond sequencing consortium [42] were selected to perform the comparative analysis of the IGT family protein sequences (S2 File). From these, twenty-seven cultivars were phenotyped for growth habit (S1 File), using a scale from 1 to 5 according UPOV guidelines: 1 = upright (< 60°), 2 = somewhat upright (60° - 80°), 3 = semi-open (80° - 100°), 4 = open (100° - 120°), 5 = weeping (> 120°) [43]. Fourteen cultivars of agronomical interest were selected to analyze the gene expression of the IGT family members. Ten out of these fourteen were chosen to analyze the expression of twenty-one transcription factors (Table 1).
Comparative genomics
The cultivar genomes were assembled against the P. dulcis Texas Genome v2.0 [42] (https://www.rosaceae.org/analysis/295). Adapter sequences were removed by processing the raw reads sequences of the 41 cultivars with Trimmomatic v0.36.6 [44]. Alignments were performed using the Bowtie2 package (Galaxy Version 2.3.4.3) [45, 46]. Variant calling to detect SNPs was performed with the FreeBayes package (Galaxy Version 1.1.0.46–0) [47]. SNPs were filtered with the PLINK package (Galaxy Version 2.0.0) [48, 49] using the following parameters: read depth (DP) = 10; alternated allele observation count (AO) = 0.2. Promoter regions of the IGT family members were analyzed up to 2,000 pb upstream the start codon. All procedures were carried out using the Galaxy platform.
Phylogenetic tree
The evolutionary history was inferred by using the Maximum Likelihood method and Poisson correction model [50]. The tree with the highest log likelihood (-5447.29) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using a JTT model, and then selecting the topology with superior log likelihood value. This analysis involved 252 amino acid sequences. There were a total of 424 positions in the final dataset. Evolutionary analyses were conducted in MEGA X [51].
Quantitative real-time PCR (qPCR)
Tissue samples for the fourteen selected cultivars were gathered at the same day from adult trees at the end of summer (late August), when one-year old branches were developed, while maintaining an active growth. Cultivars were kept at an experimental orchard in Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA) (41°43’29.4" N 0°48’27.3" W). Five cm of the tip from one-year old lateral branches were collected. Each biological replicate consisted of three tips from the same tree. RNA extraction was performed from these samples using the CTAB method described previously [52] with some modifications [53–55]. Extracted RNA was quantified using a NanoDrop® ND-1000 UV-vis spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). RNA integrity was verified by electrophoresis on a 1% agarose gel. RNA samples (2500 ng) were reverse transcribed with SuperScript III First-Strand Synthesis System (Thermo Fisher Scientific, https://www.thermofisher.com) in a total volume of 21 μL according to the manufacturer’s instructions. qPCR was performed using the Superscript III Platinum SYBR Green qRT-PCR Kit (Thermo Fisher Scientific, https://www.thermofisher.com). Each reaction was run in triplicate. Primers for the IGT family members were designed using the respective QUIAGEN CLC Genomics Workbench tool (QUIAGEN, https://digitalinsights.qiagen.com/). Actin primers were used as an internal control to normalize expression [56]. The reactions were performed using a 7900 DNA sequence detector (Thermo Fisher Scientific, https://www.thermofisher.com). In ten out of the previous fourteen cultivars (Table 1), an expression analysis for selected transcription factors (TFs) was performed in SGIker, UPV/EHU (Bizkaia, Spain) using a 48*48 Fluidigm array. Primer for the selected transcription factors (TFs) were designed using the online tool Primer3Plus [57] (http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi). Reactions were carried out using the Fluidigm BioMark HD Nanofluidic qPCR System combined with a GE 48*48 Dynamic Arrays (Fluidigm, https://www.fluidigm.com) and detection through EvaGreen fluorochrome (Bio-Rad Laboratories, https://www.bio-rad.com). CTs were obtained with Fluidigm Real-Time PCR Analysis Software version 4.1.3 (Fluidigm, https://www.fluidigm.com).
Promoter analysis
The promoter sequences of LAZY1 and LAZY2 genes, 1500–1800 bp upstream of the start codon, were analyzed in search of regulatory cis-elements. PlantCARE [58] (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) and New PLACE [59] (https://www.dna.affrc.go.jp/PLACE) were used to identify putative cis-elements and their correspondent binding factors.
Statistical analysis
Three biological replicates from different branches of the same tree were used. All the statistical analysis was carried out in R (https://cran.r-project.org/). Analysis of significance for expression analysis was performed using Kruskal-Wallis H test and comparison between means was performed with a Nemenyi test using the PMCMR R package [60].
Results and discussion
Prunus dulcis IGT family members
Six IGT family members were found in P. dulcis using BLASTp to search homologues from P. persica sequences. The P. persica nomenclature [61] was kept for P. dulcis: LAZY1 (Prudul26A025589), LAZY2 (Prudul26A030030), DRO1 (Prudul26A032079), DRO2 (Prudul26A028716), IGT-like (Prudul26A033016) and TAC1 (Prudul26A020993). The phylogenetic analysis also revealed that LAZY1 and LAZY2 peptide sequences are closely related, as well as DRO1 and DRO2. TAC1 is more similar to the rest of the members than IGT-like even without the CCL domain (Fig 1, S2 File). Although little is known about IGT-like function, the high variability could suggest a less-essential activity, or at least less selective pressure on its amino acid sequence. DRO1 and DRO2 are the most conserved members among cultivars; DRO1 shares the same protein sequence for all the different cultivars and wild species (Fig 1, S2 File). Despite the fact that polymorphisms are observed trough the different cultivars, overall, the protein sequences of the IGT Family members are highly conserved, hinting to an essential role in tree architecture regulation (Fig 1, S2 File).
Cultivars are separated into groups by IGT family protein. Only variants in homozygosis were used for tree building. Names and recorded phenotype of each cultivar and wild species are available in S1 File, while protein sequences can be found in S2 File.
IGT family protein sequence
IGT family proteins share five conserved regions in Arabidopsis, with the exception of TAC1, which lacks the CCL domain in the 3’ terminal, which comprise region V (Fig 2). While Regions I, II and V are remarkably conserved, regions III and IV differed more between members, which might indicate that their preservation is not as essential to keep their activity [33]. Furthermore, functional analysis in transgenic rescue experiments involving AtLAZY1 have shown that even proteins with mutated residues in these two regions are able to rescue the Atlazy1 branch angle phenotype [62]. In P. dulcis, a similar display of conserved regions can be seen, with Regions I, II and V extremely conserved while more variability is observed in Regions III and IV (Fig 2). The high degree of conservation that these regions keep throughout plant species highlights its importance in plant regulation.
Sequence alignment analysis was performed using T-COFFEE [63]. Red indicates higher levels of conservation. Sequences from Texas cultivar were used as model (S2 File).
Both LAZY1 and LAZY2 present mutated residues located in conserved regions in several cultivars and wild species. LAZY1 presents a mutation in Region I, I7 is replaced by a methionine (Table 2). Yoshihara and Spalding [62] reported that individuals with the residues 6 to 8 mutated showed significantly reduced ability to rescue the atlazy1 branch angle defect nor they were able to mobilize the protein correctly to the plasma membrane in Arabidopsis. Therefore, this region seems to be essential for the correct functionality of the signal peptide. However, AtLAZY1 also presents a methionine in this position on the functional protein and the residue can be found mutated in other members of the IGT family, while W6, probably the indispensable residue, is conserved throughout the members of the family, both in Arabidopsis and almond. This fact would explain why the I7M mutation in homozygosis is not correlated with the observed overall tree habit amongst cultivars (Table 2). Several cultivars present a mutation in the Region IV of LAZY2, replacing R293 for a glycine, although no relation with their phenotype was established. As described by Nakamura et al. [33], conservation of Region IV is not required to maintain protein functionality.
A repetitive region of aspartic residues in TAC1 has been previously described as influential in the protein functionality. Differences in their length may lead to effects in the tree architecture; those who have long runs of aspartic acid residues presented upright phenotypes. Additional residues could affect the functionality or stability of the protein [40]. Two different mutations can be observed in our almond cultivars. While a number of cultivars carry the insertion of an additional Asp residue, a deletion of four Asp amino acids can be observed in the wild species Prunus bucharica. Nonetheless, in both cases the mutations are presented only in heterozygosis, thus this might explain why no phenotypic variations are observed (Table 2). No mutations in conserved regions were observed for DRO1 and DRO2. This lack of alterations in their sequence can be explained because DRO1 and DRO2, unlike LAZY1 and LAZY2, are described to act mainly in roots [30]. Yet, cultivars are predominantly selected by other aerial traits, such as fruit quality or yield, not existing any artificial selection of favored polymorphisms for tree architecture. The high variability observed in the IGT-like protein sequence combined with unknown function hinders the possibility to discern if any mutated amino acid could affect its activity. After an in-silico analysis using PROVEAN [64] and SNAP platforms (Rostlab, https://www.rostlab.org/) other SNPS and indels were highlighted as possible effectors of phenotypic variance. These were marked as deleterious by these online tools, though their effects were limited to a single codon change, deletion or insertion (Table 2). Moreover, no relation between these mutations and the described phenotypes was observed.
It was not possible to establish a relation between the sequence variants and the diversity in overall tree habit, even though mutations in conserved regions were detected in LAZY1 and LAZY2 (Table 2), which correlate with previous studies indicating a relatively highly conserved structure for these proteins [33, 36]. In other species, mutations altering the phenotype produced a truncated protein or altered entire exons affecting protein functionality [61]. In our case, there are mutations modifying the protein sequence, however, none of them seem to lead to significant phenotypic impacts. In other herbaceous species these mutations lead to severe effects in cell wall structure that might be even more severe in tree, such as making the individuals that present these variants to be non-viable [61]. However, the difference in tree architecture might be related to quantitative variation of gene expression. To assess this, the expression of IGT family members was analyzed for a group of fourteen selected cultivars, in order to discover if the phenotypic differences could be due to its expression profile.
Expression profiling of IGT family members in selected almond cultivars
The expression levels of the six IGT family members were analyzed in shoot tips of fourteen almond cultivars on late August (Table 1). Expression analysis could provide an estimation of the protein activity. Previous studies in P. persica have shown than LAZY1 and TAC1 expression patterns are similar and both genes are expected to be coordinately regulated [31, 35, 41]. Since TAC1 is believed to act antagonistically to LAZY activity, it could be that high levels of LAZY1 or LAZY2 expression were influenced by high levels of TAC1 expression, or vice versa. Furthermore, in poplar (Populus trichocarpa), TAC1 overexpression has been linked to broad-crown trees, while LAZY1 expression remained constant through both narrow-crown and broad-crown trees [65]. Therefore, we used the LAZY1/TAC1 and LAZY2/TAC1 expression ratio as a descriptor of LAZY1 and LAZY2 molecular activity (Fig 3).
A, Ratio of relative gene expression between LAZY1 and TAC1. B, Ratio of relative gene expression between LAZY2 and TAC1. Cultivars abbreviatures are as follows: ‘Forastero’ (FOR), ‘Bartre’ (BAR), ‘Ferragnes’ (FER), ‘Garfi’ (GAR), ‘Garnem’ (GN), ‘Diamar’ (DIA), ‘Marinada’ (MAN), ‘Soleta’ (SOL), ‘Marcona’ (MAC), ‘Vairo’ (VAI), ‘Isabelona’ (ISA), ‘Vialfas’ (VIA), ‘Guara’ (GUA), ‘Desmayo Largueta’ (DLA). Letters above each bar indicate significance group, derived from Nemenyi’s Test.
LAZY1/TAC1 and LAZY2/TAC1 did show differences in their ratio profile between cultivars. LAZY1/TAC1 was found to have a higher ratio in ‘Garnem’ shoot tips, while upright cultivars ‘Bartre’ and ‘Ferragnes’ had the lowest levels of LAZY1/TAC1 ratio. Other cultivars like ‘Garfi’, ‘Vialfas’ and ‘Vairo’ also presented relatively elevated LAZY1/TAC1 ratios (Fig 3A). Highest levels of LAZY2/TAC1 expression ratio were found in ‘Garfi’ and ‘Vialfas’, although the ratio in ‘Garfi’ was almost 2-fold higher. Unlike ‘Garfi’, LAZY2 was not overexpressed in ‘Vialfas’ compared to the rest of cultivars, yet its lower levels of TAC1 could indicate an imbalance in the LAZY2/TAC1 ratio and, therefore, a higher LAZY2 activity. ‘Marcona’ and ‘Vairo’ presented the lowest levels of the LAZY2/TAC1 ratio (Fig 3B). It was not possible to find any transcripts of DRO2 and LAZY-like, while DRO1 expression was only detected in a reduced number of cultivars. This result is not unexpected, since DRO genes have been described acting mainly in root tissues [30].
‘Garnem’ is the only selection that is not a scion cultivar, but rather a hybrid peach x almond rootstock [66]. It has been described that the effect of IGT family members can vary within Prunus species, e.g., TAC1 silencing in plum (Prunus domestica) mimicking the pillar peach genotype leads to more acute effects on tree architecture [40]. The peach genetic background in ‘Garnem’ could explain why the LAZY1/TAC1 ratio levels are significantly higher compared to the rest of the analyzed genotypes. ‘Garfi’, the mother genotype of ‘Garnem’ shows a similar tree habit phenotype but different expression pattern. In ‘Garfi’, LAZY1/TAC1 ratio is moderate and LAZY2/TAC1 is elevated when compared with the rest of cultivars (Fig 3). However, ‘Garfi’ expression levels, while being higher than most cultivars, are quite similar for both members of the IGT family, presenting similar absolute values both ratios.
Although significant differences in gene expression were found on branches that presented vegetative growth, it was not possible to establish a correlation between expression levels and overall tree habit in these cultivars. Both ‘Garfi’ and ‘Garnem’ present an upright architecture, which would be tied to an expected predominance of LAZY expression. However, trees with more erect habits as ‘Forastero’ and ‘Bartre’ showed low or basal levels of LAZY/TAC1 ratios. Expression levels of both LAZY1 and TAC1 in P. persica have been described to be related to seasonal changes, being higher in April [41]. However, they are expected to be expressed in any growing and active tissue [31]. In Mediterranean areas, almond displays vegetative growth through late spring to end of summer [43]; hence presenting an active growth in its shoot tips during this period. Even though high levels of LAZY1 and LAZY2 are presented exclusively in upright cultivars, it does not appear to be the only factor in shaping the almond tree habit, since cultivars with lower ratios present a more upright phenotype. It is possible that the ratio values changes are too low to observe an effect in the phenotype. In poplar, differences that led to a contrasting phenotype were at least an order of magnitude higher to those observed here [65]. Though high similarity has been reported between peach and almond genomes [42, 67], we did not observe in our set of cultivars the effect on the phenotype that has been described in peach [31, 40, 41]. The lack of correlation observed in the studied phase between gene expression and phenotype accompanied by the same case observed with their protein sequence hints to the IGT family may have suffered little to no selection at all in commercial almond orchards (Table 2, Fig 2). Not being unexpected since, until recently, almond breeding has been focused on improving traits related to either flowering or the fruit [68]. Thus, other regulatory pathways must be involved in the establishment of the overall tree habit.
Analysis of variants in LAZY1 and LAZY2 promoter regions
Although it is not possible to establish any clear correlation between diversity in tree habit and the expression levels of the IGT family members, the difference in LAZY1 and LAZY2 expression between the related ‘Garfi’ and ‘Garnem’ gives us a unique opportunity to study in detail the mechanisms involved in regulating their gene expression. Since these two selections present different expression profiles while their sequences are highly similar, divergences in their promoter region and their transcription factors (TFs) binding capabilities could explain the contrast in expression.
Promoter regions of LAZY1, LAZY2 and TAC1 were analyzed in search of variants within regulatory elements (REs) that might impact their expression and their respective ratios. Two mutations that could explain the differences observed in their expression profile were found in LAZY1 and only one in LAZY2 (Table 3). No significant variants were encountered in the TAC1 promoter region.
Both LAZY1 and LAZY2 promoter regions presented a variant within a RE which is associated to the TF IPA1 (Table 3), also known as SPL9 in A. thaliana and SPL14 in O. sativa. IPA1 has been previously related with the regulation of shoot branching, acting predominantly repressing gene expression, though it has been described to also act in a promoting manner in few cases [69, 70]. In Arabidopsis, it has been reported that IPA1 downregulates genes involved in responses related to auxin signaling [71]. While LAZY1 promoter region presents the variant in a TGGGCY motif, LAZY2 has a mutated GTAC motif (Table 3). IPA1 has been described to interact with both motifs, and more specifically, directly with the second one [71]. Due to the nature of IPA1 activity, it would be conceivable that it is acting in a repressive fashion. Therefore, if a mutation obstructs its binding to a RE, LAZY1 and LAZY2 would predictably be overexpressed. The mutations described might fit with this predicted outcome, especially in the LAZY1 promoter region, where ‘Garnem’ presented the mutation, which displayed a remarkable high LAZY1/TAC1 ratio due to an overexpression of LAZY1 (Fig 3, Table 3). ‘Garfi’ also presented a mutation in the LAZY2 promoter, which could be linked to its elevated LAZY2/TAC1 ratio, though similar levels are observed in LAZY1/TAC1 ratio where no mutation was described (Fig 3, Table 3). Nevertheless, other cultivars also present the variant in this RE without showing high ratio values, indicating that the mutation does not affect gene expression by itself, possibly being affected by other factors, i.e., IPA1 expression level, protein activity or the interaction of other TFs.
Another mutation of interest was found in the LAZY1 promoter region, affecting an E-box element, which has been described as a binding region of the transcription factor RAVL1 (Table 3). The mutation exists in several selected varieties and is present in homozygosis in the cultivar ‘Ferragnes’ (Table 3), whose LAZY1/TAC1 ratio was low (Fig 3). In rice, RAVL1 has been described directly promoting genes involved in BRs and ET responses, acting in diverse metabolic processes [72, 73]. BRs act promoting branching and shoot growth [74]. The involvement of RAVL1 in regulating LAZY1 and therefore, gravity response, would place this gene at the crossover between both responses. Moreover, an ABRE element described as a binding region for the TF ABI3 could be also altered by the same mutation. Nevertheless, ABI3 is mainly involved in ABA signaling and predominantly in processes related to seed germination [75].
The mutations described in LAZY1 and LAZY2 promoter might explain the differences in their gene expression through cultivars. In particular, a mutation within a RE related to the TF IPA1 in the LAZY1 promoter may cause the high LAZY1/TAC1 ratio observed in ‘Garnem’. Other mutations could also affect the expression profile, though more knowledge is needed to characterize their effect.
Analysis of expression IPA1 homologues in P. dulcis
Due to its possible involvement in the regulation of LAZY1 and LAZY2 expression, a BLASTp search for IPA1 homologues in P. dulcis was conducted using atIPA1. Three IPA1 homologues were found: IPA1-like 1 (Prudul26A025211), IPA1-like 2 (Prudul26A009750) and IPA1-like 3 (Prudul26A016898). No non-synonymous mutations were found for any of the homologues. The expression levels of the three genes were analyzed in the shoot tips previously collected at the end of summer, in ten of the previous fourteen cultivars.
The expression profile through the ten cultivars was relatively stable for the three genes. Cultivars ‘Vairo’, ‘Marinada’ and ‘Diamar’ presented the highest expression levels (Fig 4). However, significant differences were only found in IPA1-like 2, which is overexpressed in ‘Vairo’ and repressed in ‘Garfi’. In all three homologues, ‘Garfi’ presented low expression levels compared with the rest of cultivars. A similar profile can be observed in ‘Vialfas’ (Fig 4). As it is mentioned before, IPA1 has been previously described acting as a repressor [69–71]. Therefore, the relative high ratio observed in both LAZ1/TAC1 and LAZY2/TAC1 in ‘Garfi’ might be associated with low IPA1 activity. Although ‘Vialfas’ high LAZY2/TAC1 ratio was mostly explained by TAC1 repression, a similar phenomenon could underlie its profile. Nonetheless, no REs associated to IPA1 were found in the analysis of the TAC1 promoter.
Cultivars abbreviatures are as follows: ‘Bartre’ (BAR), ‘Ferragnes’ (FER), ‘Marinada’ (MAN), ‘Garfi’ (GAR), ‘Garnem’ (GN), ‘Diamar’ (DIA), ‘Vairo’ (VAI), ‘Isabelona’ (ISA), ‘Vialfas’ (VIA), ‘Desmayo Largueta’ (DLA). Statistical analysis was performed for each gene separately. Letters above each bar indicate significance group derived from Nemenyi’s Test.
‘Garnem’ showed similar expression levels that other cultivars for all three IPA1 homologues, while displaying a remarkably high LAZY1/TAC1 ratio. This overexpression could be caused by the mutation previously described in the LAZY1 promoter, affecting a regulatory element associated to IPA1 regulatory activity (Table 3). The mutation could disrupt IPA1 interaction with the LAZY1 promoter, and hence preventing LAZY1 inhibition (Figs 3 and 4). Since no alterations were found in the LAZY2 promoter, IPA1 would be able to repress its expression, leading to the lower LAZY2/TAC1 ratio observed in ‘Garnem’.
IPA1 homologues seem to act redundantly, presenting a similar expression profile for the three genes. As it can be observed in ‘Garfi’ and ‘Vialfas’, low expression levels may be behind high LAZY1/TAC1 and LAZY2/TAC1 ratios. Therefore, confirming IPA1 genes as candidate repressors of LAZY1 and LAZY2 activity in P. dulcis.
Regulatory elements and transcription factors in LAZY1 and LAZY2 promoter regions
In order to identify TFs that might interact with REs present in LAZY1 and LAZY2 promoter regions, these regions were analyzed using New PLACE and PlantCARE online platforms. Twenty-one TFs were selected as preferred candidates, in addition to the previously described RAVL1 and ABI3, which possible RE variability was noted within the varieties (Table 4). A majority of the TFs are involved in light responses and hormonal regulation. Similar functions have been described in the REs of LAZY1, LAZY2 and TAC1 in Malus x domestica [76].
Several TFs are involved in auxin responses. While ARF1 REs are present in both promoter regions, ARF2 and IAA24 REs only are found in LAZY1 promoter; all of them act as mediators in the auxin signaling pathway [77–82]. Other hormone regulatory pathways are represented among the TFs selected. RAP2.2 and RAP2.3 belong to the Group VII of ERF (Ethylene Response Factors) and are involved in various stress responses [83–86]. RAP2.2 REs can be found extensively repeated through both promoter regions. LAZY2 promoter exhibits REs for HB5, a positive regulator of ABA and GA responses, and WUS a promotor of meristem proliferation in response to ET and auxin [87–89]. The ATAF1 RE, that falls within the LAZY1 promoter, is a key regulator of biotic and abiotic stress pathways, promoting ABA biosynthesis and regulating carbon metabolism genes or inducing the expression of genes involved in salt stress and detoxification responses [90–93]. Both promoters have REs for the TF OBP4, which is a negative regulator of cell expansion and root growth in response to ABA [94–96]. GBF6 with a RE in LAZY1 promoter, is repressed by sucrose and acts as a mediator between carbohydrates regulation and amino acid metabolism [97]. Sugars have been described as an essential part of branch outgrowth [11]. TGA4, with a RE described in both promoters, acts as a regulatory factor that mediate nitrate responses and induce root hair development in Arabidopsis roots [98, 99]. Light response TFs were also included in the selection. Both LAZY1 and LAZY2 promoters present a site for MYC2 and HB4, which are involved in R:FR regulation and shade avoidance response [100, 101]. PCL1 (RE found in LAZY2 promoter), is involved in the circadian clock [102, 103]. GT-1, found in both promoters, and its family member GTL1, only in LAZY1, have been described to modulate various metabolic processes in response to light perception [104]. LAZY2 promoter presents a RE associated to the photoreceptor phyA, core regulator of the R:FR ratio light perception [12–15]. REs for GATA14, a zing finger TF belonging to the GATA family, are found in both promoters. GATA family of TFs have been described to integrate growth and light perception in several species [105, 106]. Although LAZY1 and LAZY2 have been primarily described as regulators of gravity responses, a lack of known TFs related to gravity perception or responses was found. Only SGR5, involved in early stages of shoot gravitropism, could be found in the LAZY1 promoter [107]. LAZY1 promoter present a RE for LEAFY, which is a central regulator of inflorescence development [108]. Flower development and tree architecture has been previously linked in studies in Malus x domestica [109]. Between the TFs identified, there are a prevalence of genes related to several hormones. This points to IGT family genes being affected by numerous regulatory processes, as it could be expected hence their predicted role in a complex trait like tree habit. Gene expression was analyzed for these twenty-one TFs, not observing a connection between their levels and the previously reported LAZY1/TAC1 and LAZY2/TAC1 ratios (S1 Fig). In any case, this TFs collection influence gene expression and act in regulatory pathways differently, therefore, the lack of a wide correlation might be expected.
Conclusions
IGT family proteins are highly conserved in P. dulcis, especially within the five conserved regions and a limited number of variations found across all cultivars. Though no correlation with architectural phenotypes was observed, LAZY1 and LAZY2 did exhibit mutations with an expected impact on their functionality. In addition, despite differences in their expression profile, there was no direct relation between the overall tree habit and their expression. Although IGT family members are known to play a role in tree growth habit in other species, we do not see evidence of their influence in tree habit variability for a considerable number of almond cultivars. This is probably because no loss-of-function mutation has been selected in the set of forty-one studied major commercial almond cultivar that favor this trait, while those correlating with phenotype observed in other species alter significantly the protein structure. Until recently tree habit has not been an influential trait in almond breeding and these types of mutations were probably never selected. Furthermore, several of the mutations found in almond cultivars are present in heterozygosis, hence they could alter the phenotype if appear in homozygosis and be a foundation for possible future breeding efforts. Anyway, there are many mechanisms leading to different tree habit, and even though LAZY1 and LAZY2 are not discriminant in current almond commercial cultivars, other families of genes must be involved in the regulation of almond tree habit. However, important aspects of the regulation of the IGT family in almond have been characterized. TFs IPA1-like 1, IPA1-like 2, IPA1-like 3 seems to play a role in the regulation of LAZY1 and LAZY2 expression in addition to other TFs involved in hormonal regulation and light perception. In conclusion, almond tree habit depends on numerous factors, which outlines the necessity to better characterize the regulation of this trait and molecular mechanisms behind it both in almond orchards and other fruit trees.
Supporting information
S1 File. List of the 41 almond cultivars and wild species.
Overall tree habit phenotype for each cultivar is described categorically according UPOV guidelines.
https://doi.org/10.1371/journal.pone.0252001.s001
(XLSX)
S2 File. Protein sequences of the six IGT family members in the 41 almond cultivars and wild species.
First entry of each cultivar or wild species contains homozygous variants while second entry contains both homozygous and heterozygous variants.
https://doi.org/10.1371/journal.pone.0252001.s002
(FASTA)
S3 File. List of mutations affecting the protein sequence for the 41 almond cultivars and wild species.
HOM: mutation in both alleles; HET: mutation in only one allele.
https://doi.org/10.1371/journal.pone.0252001.s003
(XLSX)
S4 File. List of mutations affecting the promoter sequence of TAC1, LAZY1 and LAZY2 for the selected 14 almond cultivars.
HOM: mutation in both alleles; HET: mutation in only one allele.
https://doi.org/10.1371/journal.pone.0252001.s004
(XLSX)
S1 Fig. Heatmap of relative gene expression for identified transcription factors.
TFs are separated into three groups, whether they are expected to interact with both promoters or only one of them. Heatmap was constructed in R (https://cran.r-project.org/).
https://doi.org/10.1371/journal.pone.0252001.s005
(TIF)
References
- 1. Socias i Company R, Gomez Aparisi J, Alonso JM, Rubio-Cabetas MJ, Kodad O. Retos y perspectivas de los nuevos cultivares y patrones de almendro para un cultivo sostenible. ITEA Inf Tec Econ Agrar. 2009;105(2): 99–116.
- 2. Costes E, Lauri PE, Regnard JL. Analyzing Fruit Tree Architecture: Implications for Tree Management and Fruit Production. Hort. Rev. 2006;32:, 1–61.
- 3. Hollender CA, Dardick C. Molecular basis of angiosperm tree architecture. New Phytol. 2015: 541–56. pmid:25483362
- 4.
Hearn DJ. Perennial Growth, Form and Architecture of Angiosperm Trees. In: Groover A, Cronk Q., editors. Comparative and Evolutionary Genomics of Angiosperm Trees. Plant Genetics and Genomics: Crops and Models, vol 21. Springer, Chams; 2016. pp. 179–204. https://doi.org/10.1007/7397_2016_25
- 5. Hill JL, Hollender CA. Branching out: new insights into the genetic regulation of shoot architecture in trees. Curr. Opin. Plant Biol. 2019;47: 73–80. pmid:30339931
- 6. Barbier FF, Dun EA, Kerr SC, Chabikwa TG, Beveridge CA. An Update on the Signals Controlling Shoot Branching. Trends Plant Sci. 2019;24: 220–236. pmid:30797425
- 7. Bennett T, Liang Y, Seale M, Ward S, Müller D, Leyser O. Strigolactone regulates shoot development through a core signalling pathway. Biol. Open. 2016;5: 1806–1820. pmid:27793831
- 8. Dun EA, Germain A de Saint, Rameau C, Beveridge CA. Antagonistic action of strigolactone and cytokinin in bud outgrowth control. Plant Physiol. 2012;158: 487–498. pmid:22042819
- 9. Tanaka M, Takei K, Kojima M, Sakakibara H, Mori H. Auxin controls local cytokinin biosynthesis in the nodal stem in apical dominance. Plant J. 2006; 45: 1028–1036. pmid:16507092
- 10. Barbier FF, Lunn JE, Beveridge CA. Ready, steady, go! A sugar hit starts the race to shoot branching. Curr. Opin. Plant Biol. 2015;25: 39–45. pmid:25938609
- 11. Mason MG, Ross JJ, Babst BA, Wienclaw BN, Beveridge CA. Sugar demand, not auxin, is the initial regulator of apical dominance. Proc. Natl. Acad. Sci. 2014;111: 6092–6097. pmid:24711430
- 12. Casal JJ. Shade Avoidance. Arab. B. 2012;10, e0157. pmid:22582029
- 13. Finlayson SA, Krishnareddy SR, Kebrom TH, Casal JJ. Phytochrome regulation of branching in arabidopsis. Plant Physiol. 2010;152: 1914–1927. pmid:20154098
- 14. Rausenberger J, Tscheuschler A, Nordmeier W, Wüst F, Timmer J, Schäfer E, et al. Photoconversion and nuclear trafficking cycles determine phytochrome A’s response profile to far-red light. Cell. 2012;146: 813–825. pmid:21884939
- 15. Reddy SK, Finlayson SA. Phytochrome B promotes branching in Arabidopsis by suppressing auxin signaling. Plant Physiol. 2014;164: 1542–1550. pmid:24492336
- 16. Walker LM, Sack FD. Amyloplasts as possible statoliths in gravitropic protonemata of the moss Ceratodon purpureus. Planta. 1990;181: 71–77. pmid:24196676
- 17. Berut A, Chauvet H, Legue V, Moulia B, Pouliquen O, Forterre, Y. Gravisensors in plant cells behave like an active granular liquid. Proc Natl Acad Sci USA. 2018;115(20): 5123–5128. pmid:29712863
- 18. Kolesnikov YS, Kretynin SV, Volotovsky I, Kordyum EL, Ruelland E, Kravets VS. Erratum to: Molecular mechanisms of gravity perception and signal transduction in plants. Protoplasma. 2016;253: 1005. pmid:26733389
- 19. Leitz G, Kang BH, Schoenwaelder MEA. Statolith sedimentation kinetics and force transduction to the cortical endoplasmic reticulum in gravity-sensing Arabidopsis columella cells. Plant Cell. 2009; 21: 843–860. pmid:19276442
- 20. Band LR, Wells DM, Larrieu A, Sun J, Middleton AM, French AP, et al. Root gravitropism is regulated by a transient lateral auxin gradient controlled by a tipping-point mechanism. Proc Natl Acad Sci USA. 2012;109: 4668–4673. pmid:22393022
- 21. Kleine-Vehn J, Ding Z, Jones AR, Tasaka M, Morita MT, Friml J. Gravity-induced PIN transcytosis for polarization of auxin fluxes in gravity-sensing root cells. Proc Natl Acad Sci USA. 2010;107: 22344–22349. pmid:21135243
- 22. Schüler O, Hemmersbach R, Böhmer M. A Bird’s-Eye View of Molecular Changes in Plant Gravitropism Using Omics Techniques. Front Plant Sci. 2015;6: 11766. pmid:26734055
- 23. Abe K, Takahashi H, Suge H. Graviresponding sites in shoots of normal and lazy rice seedlings. Physiol Plant. 2004;92: 371–374.
- 24. Li P, Wang Y, Qian Q, Fu Z, Wang M, Zeng D, et al. LAZY1 controls rice shoot gravitropism through regulating polar auxin transport. Cell Res. 2007;17: 402–410. pmid:17468779
- 25. Yoshihara T, Iino M. Identification of the gravitropism-related rice gene LAZY1 and elucidation of LAZY1-dependent and -independent gravity signaling pathways. Plant Cell Physiol. 2007;48: 678–688. pmid:17412736
- 26. Dong Z, Jiang C, Chen X, Zhang T, Ding L, Song W, et al. Maize LAZY1 mediates shoot gravitropism and inflorescence development through regulating auxin transport, auxin signaling, and light response. Plant Physiol. 2013;163: 1306–1322. pmid:24089437
- 27. Howard TP, Hayward AP, Tordillos A, Fragoso C, Moreno MA, Tohme J, et al. Identification of the maize gravitropism gene lazy plant1 by a transposon-tagging genome resequencing strategy. PLoS One 2014;9(1). pmid:24498020
- 28. Yoshihara T, Spalding EP, Iino M. AtLAZY1 is a signaling component required for gravitropism of the Arabidopsis thaliana inflorescence. Plant J. 2013;74: 267–279. pmid:23331961
- 29. Guseman JM, Webb K, Srinivasan C, Dardick C. DRO1 influences root system architecture in Arabidopsis and Prunus species. Plant J. 2017;89: 1093–1105. pmid:28029738
- 30. Uga Y, Sugimoto K, Ogawa S, Rane J, Ishitani M, Hara N, et al. Control of root system architecture by DEEPER ROOTING 1 increases rice yield under drought conditions. Nat Genet. 2013;45: 1097–1102. pmid:23913002
- 31. Dardick C, Callahan A, Horn R, Ruiz KB, Zhebentyayeva T, Hollender C, et al. PpeTAC1 promotes the horizontal growth of branches in peach trees and is a member of a functionally conserved gene family found in diverse plants species. Plant J. 2013;75: 618–630. pmid:23663106
- 32. Yu B, Lin Z, Li H, Li X, Li J, Wang Y, et al. TAC1, a major quantitative trait locus controlling tiller angle in rice. Plant J. 2007;52: 891–898. pmid:17908158
- 33. Nakamura M, Nishimura T, Morita MT. Bridging the gap between amyloplasts and directional auxin transport in plant gravitropism. Curr Opin Plant Biol. 2019;52: 54–60. pmid:31446250
- 34. Sasaki S, Yamamoto KT. Arabidopsis LAZY1 is a peripheral membrane protein of which the Carboxy-terminal fragment potentially interacts with microtubules. Plant Biotechnol. 2015;32: 103–108.
- 35. Hollender CA, Hill JL, Waite J, Dardick C. Opposing influences of TAC1 and LAZY1 on Lateral Shoot Orientation in Arabidopsis. Sci Rep. 2020;10: 1–13. pmid:31913322
- 36. Taniguchi M, Furutani M, Nishimura T, Nakamura M, Fushita T, Iijima K, et al. The Arabidopsis LAZY1 Family Plays a Key Role in Gravity Signaling within Statocytes and in Branch Angle Control of Roots and Shoots. Plant Cell 2017; 29(8). pmid:28765510
- 37. Yoshihara T, Spalding EP. LAZY genes mediate the effects of gravity on auxin gradients and plant architecture. Plant Physiol. 2017;175(2): 959–969. pmid:28821594
- 38. Zhang N, Yu Hong, Yu Hao, Cai Y, Huang L, Xu C, et al. A core regulatory pathway controlling rice tiller angle mediated by the LAZY1-dependent asymmetric distribution of auxin. Plant Cell. 2018;30: 1461–1475. pmid:29915152
- 39. Waite JM, Dardick C. TILLER ANGLE CONTROL 1 modulates plant architecture in response to photosynthetic signals. J Exp Bot. 2018;69(20): 4935–4944. pmid:30099502
- 40. Hollender CA, Waite JM, Tabb A, Raines D, Chinnithambi S, Dardick C. Alteration of TAC1 expression in Prunus species leads to pleiotropic shoot phenotypes. Hortic Res. 2018;5: 1–9. pmid:29423231
- 41. Tworkoski T, Webb K, Callahan A. Auxin levels and MAX1–4 and TAC1 gene expression in different growth habits of peach. Plant Growth Regul. 2015;77: 279–288.
- 42. Alioto T, Alexiou KG, Bardil A, Barteri F, Castanera R, Cruz F, et al. Transposons played a major role in the diversification between the closely related almond and peach genomes: results from the almond genome sequence. The Plant J. 2020;101(2): 455–472. pmid:31529539
- 43.
Felipe AJ. El almendro: El material vegetal. Integrum, Lerida; 200.
- 44. Bolger AM, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30: 2114–2120. pmid:24695404
- 45. Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10(3): 1–10. pmid:19261174
- 46. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4): 357–9. pmid:22388286
- 47. Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. arXiv:1207.3907 [Preprint] 2012. Available from: https://arxiv.org/abs/1207.3907
- 48. Chang CC, Chow CC, Tellier LCAM, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: Rising to the challenge of larger and richer datasets. Gigascience. 2015;4(1): 1–16. pmid:25722852
- 49. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81(3): 559–75. pmid:17701901
- 50. Zuckerkandl E., Pauling L. Evolutionary Divergence and Convergence in Proteins. Evol Genes Proteins. 1965; 97–166.
- 51. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol. 2018;35: 1547–1549. pmid:29722887
- 52. Meisel L, Fonseca B, Gonzalez S, Baeza-Yates R, Cambiazo V, Campos R, et al. A rapid and efficient method for purifying high quality total RNA from peaches (Prunus persica) for functional genomics analyses. Biol Res. 2005;38(1): 83–8. pmid:15977413
- 53. Chang S, Puryear J, Cairney J. A simple and efficient method for isolating RNA from pine trees. Plant Mol Biol Rep. 1993;11: 113–116.
- 54. Salzman RA, Fujita T, Zhu-Salzman K, Hasegawa PM, Bressan RA. An Improved RNA Isolation Method for Plant Tissues Containing High Levels of Phenolic Compounds or Carbohydrates. Plant Mol Biol Report. 1999;17(1): 11–7.
- 55. Zeng Y, Yang T. RNA isolation from highly viscous samples rich in polyphenols and polysaccharides. Plant Mol Biol Report. 2002;20(4): 417.
- 56. Hosseinpour B, Sepahvand S, Aliabad KK, Bakhtiarizadeh M, Imani A, Assareh R, et al. Transcriptome profiling of fully open flowers in a frost-tolerant almond genotype in response to freezing stress. Mol Genet Genomics. 2018;293: 151–163. pmid:28929226
- 57. Untergasser A., Nijveen H, Rao X, Bisseling T, Geurts R, Leunissen JAM. Primer3Plus, an enhanced web interface to Primer3. Nucleic Acids Res. 2007;35: 71–74. pmid:17485472
- 58. Lescot M, Dehais P, Thijs G, Marchal K, Moreau Y, Van De Peer Y, et al. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 2002;30(1): 325–7. pmid:11752327
- 59. Higo K, Ugawa Y, Iwamoto M, Korenaga T. Plant cis-acting regulatory DNA elements (PLACE) database: 1999. Nucleic Acids Res. 1999;27(1): 297–300. pmid:9847208
- 60. Pohlert T. The pairwise multiple comparison of mean ranks package (PMCMR). R package. 2014;27: 9.
- 61. Waite JM, Dardick C. The roles of the IGT gene family in plant architecture: past, present, and future. Curr Opin Plant Biol. 2021;59: 101983. pmid:33422965
- 62. Yoshihara T, Spalding EP. Switching the direction of stem gravitropism by altering two amino acids in Atlazy1. Plant Physiol. 2020;182(2): 1039–51. pmid:31818902
- 63. Notredame C, Higgins DG, Heringa J. T-Coffee: A novel method for fast and accurate multiple sequence alignment. J Mol Bio. 2000;302(1): 205–217. pmid:10964570
- 64. Choi Y, Chan AP. PROVEAN web server: A tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics. 2015;31(16): 2745–7. pmid:25851949
- 65. Xu D, Qi X, Li J, Han X, Wang J, Jiang Y, et al. PzTAC and PzLAZY from a narrow-crown poplar contribute to regulation of branch angles. Plant Physiol Biochem. 2017;118: 571–578. pmid:28787659
- 66. Felipe AJ. “Felinem”, “Garnem”, and “Monegro” almond x peach hybrid rootstocks. HortScience. 2009;44(1): 196–7.
- 67. Goonetilleke SN, March TJ, Wirthensohn MG, Arus P, Walker AR, Mather DE. Genotyping by Sequencing in Almond: SNP Discovery, Linkage Mapping, and Marker Design. G3 Genes, Genomes, Genetics, 2018;8(1): 161–172. pmid:29141988
- 68. Gradziel TM. Almonds: botany, production and uses. Cabi; 2017.
- 69. Jiao Y, Wang Y, Xue D, Wang J, Yan M, Liu G, et al. Regulation of OsSPL14 by OsmiR156 defines ideal plant architecture in rice. Nat Genet. 2010;42: 541–544. pmid:20495565
- 70. Miura K, Ikeda M, Matsubara A, Song XJ, Ito M, Asano K, et al. OsSPL14 promotes panicle branching and higher grain productivity in rice. Nat Genet. 2010;42: 545–549. pmid:20495564
- 71. Lu Z, Yu H, Xiong G, Wang J, Jiao Y, Liu G, et al. Genome-wide binding analysis of the transcription activator IDEAL PLANT ARCHITECTURE1 reveals a complex network regulating rice plant architecture. Plant Cell. 2013; 25: 3743–3759. pmid:24170127
- 72. Xuan YH, Duan FY, Je B, Kim CM, Li TY, Liu JM, et al. Related to ABI3/VP1-Like 1 (RAVL1) regulates brassinosteroidmediated activation of AMT1;2 in rice (Oryza sativa). J Exp Bot. 2017;68: 727–737. pmid:28035023
- 73. Zhu XF, Yuan DP, Zhang C, Li TY, Xuan YH. RAVL1, an upstream component of brassinosteroid signalling and biosynthesis, regulates ethylene signalling via activation of EIL1 in rice. Plant Biotechnol J. 2018;16: 1399–1401. pmid:29604166
- 74. Rameau C, Bertheloot J, Leduc N, Andrieu B, Foucher F, Sakr S. Multiple pathways regulate shoot branching. Front Plant Sci. 2015;5: 1–15. pmid:25628627
- 75. Dekkers BJW, He H, Hanson J, Willems LAJ, Jamar DCL, Cueff G, et al. The Arabidopsis Delay of Germination 1 gene affects Abscisic Acid Insensitive 5 (ABI5) expression and genetically interacts with ABI3 during Arabidopsis seed development. Plant J. 2016;85(4): 451–65. pmid:26729600
- 76. Wang L, Cai W, Du C, Fu Y, Xie X, Zhu Y. The isolation of the IGT family genes in Malus × domestica and their expressions in four idiotype apple cultivars. Tree Genet Genomes. 2018;14: 1–11.
- 77. Guilfoyle TJ. The PB1 Domain in Auxin Response Factor and Aux/IAA Proteins: A Versatile Protein Interaction Module in the Auxin Response. Plant Cell Online. 2015;27: 33–43. pmid:25604444
- 78. Leyser O. Auxin Signaling. Plant Physiol. 2018;76(1): 465–479. pmid:28818861
- 79. Li G, Ma J, Tan M, Mao J, An N, Sha G, et al. Transcriptome analysis reveals the effects of sugar metabolism and auxin and cytokinin signaling pathways on root growth and development of grafted apple. BMC Genomics. 2016;17: 1–17. pmid:26818753
- 80. Luo J, Zhou JJ, Zhang JZ. Aux/IAA gene family in plants: Molecular structure, regulation, and function. Int J Mol Sci. 2018;19: 1–17. pmid:29337875
- 81. Okushima Y, Mitina I, Quach HL, Theologis A. AUXIN RESPONSE FACTOR 2 (ARF2): A pleiotropic developmental regulator. Plant J. 2005;43: 29–46. pmid:15960614
- 82. Vert G, Walcher CL, Chory J, Nemhauser JL. Integration of auxin and brassinosteroid pathways by Auxin Response Factor 2. Proc Natl Acad Sci. 2008;105: 9829–9834. pmid:18599455
- 83. Hinz M, Wilson IW, Yang J, Buerstenbinder K, Llewellyn D, Dennis ES, et al. Arabidopsis RAP2.2: An ethylene response transcription factor that is important for hypoxia survival. Plant Physiol. 2010;153: 757–772. pmid:20357136
- 84. Papdi C, Perez-Salamo I, Joseph MP, Giuntoli B, Bögre L, Koncz C, et al. The low oxygen, oxidative and osmotic stress responses synergistically act through the ethylene response factor VII genes RAP2.12, RAP2.2 and RAP2.3. Plant J. 2015;82: 772–784. pmid:25847219
- 85. Nakano T, Suzuki K, Fujimura T, Shinshi H. Genome-wide analysis of the ERF gene family in Arabidopsis and rice. Plant Physiol. 2006;140(2): 411–432. pmid:16407444
- 86. Rubio-Cabetas MJ, Pons C, Bielsa B, Amador ML, Marti C, Granell A. Preformed and induced mechanisms underlies the differential responses of Prunus rootstock to hypoxia. J Plant Physiol. 2018;228: 134–149. pmid:29913428
- 87. Johannesson H, Wang Y, Hanson J, Engstrom P. The Arabidopsis thaliana homeobox gene ATHB5 is a potential regulator of abscisic acid responsiveness in developing seedlings. Plant Mol Biol. 2003;51: 719–729. pmid:12678559
- 88. Stamm P, Topham AT, Mukhtar NK, Jackson MDB, Tome DFA, Beynon JL, et al. The transcription factor ATHB5 affects GA-mediated plasticity in hypocotyl cell growth during seed germination. Plant Physiol. 2017;173: 907–917. pmid:27872245
- 89. Shi B, Guo X, Wang Y, Xiong Y, Wang J, Hayashi K, et al. Feedback from Lateral Organs Controls Shoot Apical Meristem Growth by Modulating Auxin Transport. Dev Cell. 2018;44: 204–216. pmid:29401419
- 90. Garapati P, Feil R, Lunn JE, Van Dijck P, Balazadeh S, Mueller-Roeber B. Transcription factor arabidopsis activating factor1 integrates carbon starvation responses with trehalosemetabolism. Plant Physiol. 2015;169: 379–390. pmid:26149570
- 91. Jensen MK, Lindemose S, Masi F, Reimer JJ, Nielsen M, Perera V, et al. ATAF1 transcription factor directly regulates abscisic acid biosynthetic gene NCED3 in Arabidopsis thaliana. FEBS Open Bio. 2013;3: 321–327. pmid:23951554
- 92. Liu Y, Sun J, Wu Y. Arabidopsis ATAF1 enhances the tolerance to salt stress and ABA in transgenic rice. J Plant Res. 2016;129: 955–962. pmid:27216423
- 93. Zhao J, Missihoun TD, Bartels D. The ATAF1 transcription factor is a key regulator of aldehyde dehydrogenase 7B4 (ALDH7B4) gene expression in Arabidopsis thaliana. Planta. 2018;248: 1017–1027. pmid:30027414
- 94. Ramirez-Parra E, Perianez-Rodriguez J, Navarro-Neila S, Gude I, Moreno-Risueno MA, del Pozo JC. The transcription factor OBP4 controls root growth and promotes callus formation. New Phytol. 2017;213: 1787–1801. pmid:27859363
- 95. Rymen B, Kawamura A, Schafer S, Breuer C, Iwase A, Shibata M, et al. ABA suppresses root hair growth via the OBP4 transcriptional regulator. Plant Physiol. 2017;173: 1750–1762. pmid:28167701
- 96. Xu P, Chen H, Ying L, Cai W. AtDOF5.4/OBP4, a DOF Transcription Factor Gene that Negatively Regulates Cell Cycle Progression and Cell Expansion in Arabidopsis thaliana. Sci Rep. 2016;6: 1–13. pmid:28442746
- 97. Ma J, Hanssen M, Lundgren K, Hernandez L, Delatte T, Ehlert A, et al. The sucrose-regulated Arabidopsis transcription factor bZIP11 reprograms metabolism and regulates trehalose metabolism. New Phytol. 2011;191: 733–745. pmid:21534971
- 98. Alvarez JM, Riveras E, Vidal EA, Gras DE, Contreras-Lopez O, Tamayo KP, et al. Systems approach identifies TGA1 and TGA4 transcription factors as important regulatory components of the nitrate response of Arabidopsis thaliana roots. Plant J. 2014;80: 1–13. pmid:25039575
- 99. Canales J, Contreras-Lopez O, Alvarez JM, Gutierrez RA. Nitrate induction of root hair density is mediated by TGA1/TGA4 and CPC transcription factors in Arabidopsis thaliana. Plant J. 2017;92: 305–316. pmid:28771873
- 100. Kazan K, Manners JM. MYC2: The master in action. Mol Plant. 2013;6: 686–703. pmid:23142764
- 101. Sorin C, Salla-Martret M, Bou-Torrent J, Roig-Villanova I, Martinez-Garcia JF. ATHB4, a regulator of shade avoidance, modulates hormone response in Arabidopsis seedlings. Plant J. 2009;59: 266–277. pmid:19392702
- 102. Helfer A, Nusinow DA, Chow BY, Gehrke AR, Bulyk ML, Kay SA. LUX ARRHYTHMO encodes a nighttime repressor of circadian gene expression in the Arabidopsis core clock. Curr Biol. 2011;21: 126–133. pmid:21236673
- 103. Onai K, Ishiura M. PHYTOCLOCK 1 encoding a novel GARP protein essential for the Arabidopsis circadian clock. Genes to Cells. 2005;10: 963–972. pmid:16164597
- 104. Kaplan-Levy RN, Brewer PB, Quon T, Smyth DR. The trihelix family of transcription factors–light, stress and development. Trends Plant Sci. 2012:17(3): 163–171. pmid:22236699
- 105. 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. J Exp Bot. 2020;71: 1969–1984. pmid:31872214
- 106. Luo XM, Lin WH, Zhu S, Zhu JY, Sun Y, Fan XY, et al. Integration of Light- and Brassinosteroid-Signaling Pathways by a GATA Transcription Factor in Arabidopsis. Dev Cell. 2010;19: 872–883. pmid:21145502
- 107. Morita MT, Sakaguchi K, Kiyose SI, Taira K, Kato T, Nakamura M, et al. A C2H2-type zinc finger protein, SGR5, is involved in early events of gravitropism in Arabidopsis inflorescence stems. Plant J. 2006;47: 619–628. pmid:16813575
- 108. Schultz EA, Haughn GW. LEAFY, a homeotic gene that regulates inflorescence development in arabidopsis. Plant Cell. 1991;3: 771–781. pmid:12324613
- 109. Foster TM, Watson AE, van Hooijdonk BM, Schaffer RJ. Key flowering genes including FT-like genes are upregulated in the vasculature of apple dwarfing rootstocks. Tree Genet Genomes. 2014;10: 189–202.