Genome organization and characteristics of soybean microRNAs
© Turner et al.; licensee BioMed Central Ltd. 2012
Received: 6 December 2011
Accepted: 23 March 2012
Published: 4 May 2012
microRNAs (miRNAs) are key regulators of gene expression and play important roles in many aspects of plant biology. The role(s) of miRNAs in nitrogen-fixing root nodules of leguminous plants such as soybean is not well understood. We examined a library of small RNAs from Bradyrhizobium japonicum-inoculated soybean roots and identified novel miRNAs. In order to enhance our understanding of miRNA evolution, diversification and function, we classified all known soybean miRNAs based on their phylogenetic conservation (conserved, legume- and soybean-specific miRNAs) and examined their genome organization, family characteristics and target diversity. We predicted targets of these miRNAs and experimentally validated several of them. We also examined organ-specific expression of selected miRNAs and their targets.
We identified 120 previously unknown miRNA genes from soybean including 5 novel miRNA families. In the soybean genome, genes encoding miRNAs are primarily intergenic and a small percentage were intragenic or less than 1000 bp from a protein-coding gene, suggesting potential co-regulation between the miRNA and its parent gene. Difference in number and orientation of tandemly duplicated miRNA genes between orthologous genomic loci indicated continuous evolution and diversification. Conserved miRNA families are often larger in size and produce less diverse mature miRNAs than legume- and soybean-specific families. In addition, the majority of conserved and legume-specific miRNA families produce 21 nt long mature miRNAs with distinct nucleotide distribution and regulate a more conserved set of target mRNAs compared to soybean-specific families. A set of nodule-specific target mRNAs and their cognate regulatory miRNAs had inverse expression between root and nodule tissues suggesting that spatial restriction of target gene transcripts by miRNAs might govern nodule-specific gene expression in soybean.
Genome organization of soybean miRNAs suggests that they are actively evolving. Distinct family characteristics of soybean miRNAs suggest continuous diversification of function. Inverse organ-specific expression between selected miRNAs and their targets in the roots and nodules, suggested a potential role for these miRNAs in regulating nodule development.
KeywordsmicroRNA Soybean Genome organization Evolution Nodulation
microRNAs (miRNAs) are a class of small RNAs that regulate gene expression primarily in a post transcriptional manner [1–3]. Genes encoding miRNAs are transcribed by RNA polymerase II, and the transcript may be capped and polyadenylated, and may even contain introns [1, 4]. In plants, primary miRNA (pri-miRNA) transcripts are processed into mature and active 21–24 nt forms in the nucleus by Dicer-Like (DCL) enzymes in a two-step process. First, pri-miRNAs are cleaved into miRNA precursors (pre-miRNAs) that typically have a hairpin-like structure. Then, the pre-miRNA is cleaved to give rise to the miRNA/miRNA* duplex, a highly complementary short double-stranded RNA molecule with characteristic 2 nt 3’ overhangs. miRNA/miRNA* duplexes are methylated on the 2’ OH group of the last nucleotide (3’ end) by HEN1 and are translocated to the cytoplasm. Methylation is thought to protect miRNA-duplexes from degradation [1, 5]. In the cytoplasm, miRNA* is generally degraded and the mature miRNA molecule is incorporated into a RNA-induced silencing complex (RISC), composed of different proteins including the catalytic protein ARGONAUTE (AGO). This complex either directs the cleavage of complementary target mRNAs [2, 3, 6] or inhibits their translation  primarily depending on the extent of sequence complementarity between the miRNA and the target mRNA. The majority of conserved miRNAs regulate transcription factors and signaling elements, although a number of other classes of target genes are being discovered [1, 8–11]. miRNAs play crucial roles in many aspects of plant development including organ morphogenesis or patterning primarily by regulating hormone signaling [3, 7]. They also play a role in response to abiotic stresses [12–14] and resistance against pathogenic organisms .
The availability of complete genome sequence for a number of plant species has allowed a better understanding of miRNA evolution and genome organization. Two mutually non-exclusive models have been proposed for miRNA origin; miRNA genes arise from inverted duplication of protein-coding genes (that eventually become target of the miRNA) or are born randomly from the numerous inverted repeats in the genome [4, 7]. Resulting miRNA/target pairs would then be selected through evolution. Evolutionary forces such as duplication, inversion, mutation, amplification, and other types of genetic drift that shape the genome might be the primary events in the origin and evolution of miRNA genes. Identification of numerous young miRNA genes with low expression and few if any targets supports the hypothesis of a rapid birth-death model . The presence of deeply conserved and species-specific miRNAs, in various plant species, points towards a continuous, rapid and uneven evolutionary process of miRNA genes [4, 7]. miRNA genes are grouped into families, based on paralogous family members producing identical or nearly identical mature sequences .
We previously identified a set of miRNAs from soybean (Glycine max) by sequencing two libraries of small RNAs, one from Bradyrhizobium japonicum-inoculated and the other from mock-inoculated roots . Subsequently, a number of miRNAs have been identified in soybean [19–24] and other legumes such as M. truncatula[25–27], Phaseolus vulgaris[12, 28] and Arachis hypogaea. The identification of nodulation-regulated and legume-specific miRNAs has suggested important roles for these molecules in nodule development [21, 25, 26, 30]. Indeed, the crucial role of miRNAs in nodule development has been demonstrated in both M. truncatula[31, 32] and soybean .
The complete genome sequence of soybean was recently released. It is a 1.1 gigabase genome with approximately 46,430 protein coding genes. Two whole genome duplication events, suggested to have occurred at approximately 59 and 13 million years ago, resulted in a highly duplicated genome with nearly 75% of the genes present in multiple copies [34–36]. In the present study, we identified a number of novel miRNAs and additional family members for known miRNAs. In addition, we compiled all miRNA sequences available in soybean and performed a comprehensive analysis of miRNA distribution in the genome as well as their family organization, mature sequence diversity and target prediction. Expression analysis of selected miRNAs and targets in different soybean organs revealed regulation of organ-specific target gene expression by miRNAs. Overall, our results have provided novel insights on miRNA evolution, diversification and regulation in soybean.
We previously identified a number of soybean miRNAs through high throughput sequencing of a small RNA library and examining WGS and EST sequences for potential precursors . We speculated that when the complete genome sequence of soybean is available, additional novel miRNAs might be discovered. It was indeed the case and here, we report the identification of a number of novel miRNAs and previously unknown family members for conserved miRNAs in the recently released soybean genome sequence .
Identification of novel miRNAs families and family members in soybean
Summary of soybean miRNAs identified in this study
Soybean miRNA family ID
Number of family members
Identified in this study
Soybean miRNA genes are primarily intergenic
Diversity of duplicated miRNA genes in paralogous genomic regions indicates continuous evolution
Conserved miRNA families are larger in size compared to legume- or soybean-specific families
The majority of conserved and legume-specific miRNA families produce 21 nt mature sequences and have distinct nucleotide distribution compared to soybean-specific families
The size of the mature sequence is also closely related to the level of conservation of miRNA families in Arabidopsis ; most of the conserved families produced 21 nt long mature miRNAs whereas most of the species-specific families produced 22 nt long mature miRNAs. In soybean, the majority of conserved and legume-specific families produce 21 nt long mature miRNAs while about half the number of soybean-specific families produce 22 nt mature miRNAs (Figure 3B). Mature sequence length was statistically different between conserved and soybean-specific families (Student’s T-test, P = 0.01) as well as conserved and legume-specific families (Student’s T-test, P = 0.03). A preference for U in the 5’end of mature miRNAs has been identified in plants [42, 44]. In soybean as well, there was a preference for U at the 5’ end of miRNAs (Additional file 2: Figure S3) irrespective of the conservation class. The identity of the first base seemed to be a family-specific characteristic. For example, among the conserved families, miR159, miR390 and miR395 had a preference for A at the 5’ end of mature miRNAs (Additional file 1: Table S1, sheet1). In soybean, a preference for C as the 19th base was previously reported . This was indeed true for conserved families but not for the legume- and soybean-specific families (Additional file 2: Figure S3). In conclusion, mature sequence length and nucleotide preference at the 19th position of mature miRNA sequence was found to be distinct between conserved, legume-specific and soybean-specific families.
Conserved miRNA families produce less diverse mature sequences compared to legume- or soybean-specific families
The ultimate determinant of the range of targets regulated by a particular miRNA depends on complementarity between mature miRNAs and mRNA targets. We examined the number of different mature miRNAs produced by different miRNA families. In 46% of conserved miRNA families, mature miRNAs produced by different members were identical in sequence. For example, miR164 has 12 family members, but all of them produce identical mature miRNAs (Additional file 3: Table S1, Sheet2). On the other hand, in legume- and soybean-specific miRNA families, mature miRNAs from each family member was often distinct in sequence. For example, 6 legume-specific miRNA families had two family members each and in 5 of these families, each family member produced a distinct mature miRNA. Similarly, in 3 of the 4 soybean-specific miRNA families that had 3 family members, each family member produced a distinct mature miRNA (Additional file 3: Table S1, Sheet2). On average, each mature miRNA sequence was encoded by 2.6, 1.1 and 1.1 members respectively in conserved, legume-specific and soybean-specific miRNA families. Differences in diversity of mature sequence per loci were statistically significant between conserved families and both legume- and soybean-specific families (Student’s T-test, P = 0.002 and 0.002 respectively). There seems to be a correlation between the diversity in mature miRNA sequence and the level of conservation of miRNA families.
Conserved and legume-specific miRNAs might regulate a large number of genes with similar function whereas soybean-specific miRNAs might regulate fewer genes with diverse functions
Average number of targets per mature sequence in conserved, legume-specific and soybean-specific miRNA families
Average number of targets predicted per mature sequence
Mature sequences with predicted targets1
Principal predicted function
Disease resistance proteins
Dual targeting by legume-specific miRNAs might initiate tasiRNA production
In some cases, miRNAs from two different families appeared to target the same gene at different positions (Additional file 4: Table S3). Often these miRNA pairs appeared to regulate a family of genes. For example, miR2109 and miR1510 were predicted to target the same 5 genes, but at different positions (~570 and 600nt apart) and all of them are annotated as potential disease-resistance genes. This observation suggested potential generation of trans-acting siRNAs (tasiRNAs) from these target genes via the “two-hit model” [9, 45, 46]. We examined all available small RNA libraries from soybean (NCBI GEO archive) for generation of tasiRNAs (i.e. ‘phased’ reads from both strands) from these target genes. We examined the number of reads in phase (21nt) with the predicted miRNA cleavage site. The number of reads in phase was compared to total number of reads from the same strand. Among all soybean targets predicted to be regulated by two different miRNAs, three (Glyma09g07290, Glyma09g39260 and Glyma16g27790 – all encoding pentatrichopeptide repeat-containing proteins and potential targets of miR1508 and miR4413) produced phased reads whose abundance was above the median number of reads from other positions (data not shown). Perhaps, regulation by multiple miRNAs is a mechanism for fine-tuning gene expression, either as a fail-safe mechanism or to generate tasiRNAs rather than a random coincidence. Indeed, during the preparation of this manuscript, a large scale analysis of small RNAs and degradomes of M. truncatula and other legumes identified and validated the production of phased siRNAs from NBS-LRR genes  either through initiation by 22nt miRNAs  or the two-hit model [9, 45, 46].
Validation of predicted targets by RLM-RACE
Validation of selected miRNA targets by a modified 5’RACE assay
Target name and function
TRANSCRIPTION FACTOR NF-Y ALPHA-RELATED
5’ UAGGCAACUCAUCCUUGGCUC 3’
| | | | | | | | | | | | | | | | | | (A/G)GCCGUUCAGUAGGAACCGA(A)
TRANSCRIPTION FACTOR NF-Y ALPHA-RELATED
5’ CAGGCAAAUCAUCCUUGGCUU 3’
| | | | | | | | | | | | | | | | | |
TRANSCRIPTION FACTOR NF-Y ALPHA-RELATED
5’ CUGGCAAAUCAUCCUUGGCUU 3’
| | | | | | | | | | | | | | | | | |
TRANSCRIPTION FACTOR NF-Y ALPHA-RELATED
5’ UAGGCAAUCCAUCCUUGGCUC 3’
| | | | | | | | | | | | | | | | |
LRR;TIRdomain; NB-ARCdomain;Apoptotic ATPase
5’ AUGGAACCGGUGGAAUUGGCAA 3’
| | | | | | | | | | | | | | | | |
LRR;TIRdomain; NB-ARCdomain;Apoptotic ATPase
5’ AUGGAACUGGUGGAAUUGGCAA 3’
| | | | | | | | | | | | | | | | |
In conclusion, soybean miRNA genes are primarily intergenic, but a small percentage was also intragenic or close to protein-coding genes suggesting co-regulation of miRNAs and protein-coding genes. Differences in the orientation and number of tandem duplications and clustering of soybean miRNA genes between paralogous loci, indicated recent and continuous evolution and diversification of soybean miRNAs. Family size, diversity, length and nucleotide distribution of mature miRNAs, and the number and range of targets regulated were distinct between conserved, legume-specific and soybean-specific miRNA families. Interestingly, legume-specific families presented characteristic of both conserved and soybean-specific families, depending on the criteria considered, but seem more closely related to soybean-specific families.
Organ-specific/preferred expression of soybean miRNAs
We observed clearly distinct organ-specific/preferred expression of these miRNAs. For example, miR156a and miR169g appeared to be preferentially expressed in aerial organs (Figure 4A and B) whereas miR4416a, miR4416b, gma-new-miR13587 and gma-new-miR50841 had a preferential expression in root organs (Figure 4C-F). Among the four miRNAs with preferential expression in the root, gma-new-miR50841 was also highly expressed in the nodules. miR169c, miR2118/2218 and miR4412 were expressed in all organs and did not seem to have a clear organ specificity (Figure 4G-I). Among the miRNAs belonging to the same family, both miR4416a and miR4416b had root-preferred expression profiles. In contrast, miR169c and miR169g had clearly distinct organ-specific expression profiles; while miR169c was expressed at high levels in the root, stem, leaves and flowers, miR169g was expressed primarily in leaf and flowers.
In conclusion, different organ specificities in miRNA expression were identified, four miRNAs being specific to root organs including one that was expressed in roots and nodules.
Potential regulation of organ-specific target gene expression by miRNAs
Identification of novel miRNAs and family members
We previously identified 55 families of soybean miRNAs through high throughput sequencing of a small RNA library and analyzing the data using WGS and EST sequences . Using conserved miRNAs as ‘internal control’ we estimated that a number of miRNA family members were not identified primarily due to non-availability of either genome sequence data or assembly. Indeed, re-examination of our library with the recently released soybean genome assembly (http://www.phytozome.net; Glyma1.0; ), allowed us to identify 5 new miRNAs and 109 novel family members for previously known miRNAs. We used the criteria defined to annotate plant miRNAs  and our results have significantly enhanced our knowledge on the organization, evolution and diversity of soybean miRNA families. For example, in the three miRNA families that play a crucial role in auxin signaling (miR160, miR164 and miR393), only one family member had been identified previously (miRBase V17). Our results show that these three miRNA families have 6, 12 and 11 members respectively in soybean (Additional file 1: Table S1). Such knowledge is crucial for complete understanding of redundancy and diversity between miRNA family members in the regulation of plant growth and development. With high levels of conservation in mature sequences, what is the need for larger families of miRNAs? Is there diversification of function among family members or does one member play a major role and functional redundancy exists among family members? There is evidence for both possibilities. In Arabidopsis, the three family members of miR164 have overlapping expression domains and individual loss of function mutants in each of these miRNAs have distinct phenotypes whereas the triple mutant has additive phenotypes [50, 51]. On the other hand, miR159a and b single mutants do not have obvious developmental phenotypes but the double mutant exhibits severe developmental defects, suggesting functional redundancy among family members . In addition, we have identified five novel (previously undescribed) miRNAs and all of them seem to be soybean-specific although reads with significant identity to gma-new-miR13587 were also present in a M. truncatula sRNA library (MIRMED; ; Subramanian, unpublished results). It is noteworthy that gma-new-miR11602 was independently identified in soybean by Kulcheski et al.  and reads corresponding to mature sequences of all 5 novel miRNAs identified in our study were present in multiple soybean small RNA libraries (NCBI GEO archive) suggesting that these are indeed genuine miRNAs. Three of them (gma-new-miR21193, gma-new-miR13587, gma-new-miR50841) had high abundance in root or nodule libraries (data not shown) consistent with our qPCR data on gma-new-miR13587 and gma-new-miR50841.
Genome organization of soybean miRNAs
We identified four miRNA families that have tandemly duplicated members: MIR159, MIR169, MIR395, three conserved families, and MIR-Seq14 that is soybean-specific. In addition to these tandem duplications, we also observed four miRNA clusters (groups of miRNAs located within 5Kb of each other with no protein coding genes in between) involving members from different families (Additional file 4: Table S3). miRNA clustering is often conserved among distantly related angiosperms . Clusters of miRNAs in plant genomes generally contain conserved miRNAs of the same family, in contrast to animals where miRNAs with unrelated sequences are often included in the same clusters . In all families with tandemly repeated miRNAs in soybean, the number and/or orientation of miRNA and miRNA-like genes in paralogous genomic loci was different (Figure 2 and Additional file 2: Figure S2), suggesting that miRNA evolution and diversification was not only due to whole genome duplication events, but also independent local duplication of miRNA genes. However, even though duplication/clustering of miRNA genes can be found in distantly related angiosperms, it does not seem to be a generally conserved phenomenon. For example, like in soybean, clusters of MIR159 genes have been identified in maize and sorghum as well , whereas miR159 family is encoded by three unclustered genes in Arabidopsis . Similarly, MIR395 is organized in clusters in different plant species such as Arabidopsis and rice but not in M. truncatula[26, 59]. MIR169 is also organized in cluster in several species including rice  and Arabidopsis  and its organization highly conserved with G. max.
Continuous evolution and diversification of soybean miRNAs
miRNA genes are evolving rapidly; evolutionary dynamics also influences miRNA family size, diversity of mature sequences among family members, length of mature sequence and the number of targets regulated . The notion that many plant miRNA families are conserved but others are lineage specific has been clearly supported by comparisons of miRNA inventories, especially between two closely related Brassicaceae plants, A.thaliana and A. lyrata[16, 42, 43]. miRNA genes that are deeply conserved among plant lineage tend to belong to families that have several members, possess quite conserved mature sequences that are shorter (primarily 21nt) and usually regulate a conserved set of genes; In contrast, the less-conserved miRNAs are a much larger category, usually represented by a few members with higher mature sequence diversity, longer mature miRNAs (primarily 22nt) and often with fewer or no targets. It is hypothesized that some less conserved miRNA families may be nonfunctional and evolutionarily transient [7, 16, 42, 43, 62]. In soybean as well, conserved, legume-specific and soybean-specific gene families had distinct characteristics that were in agreement with the above observations in Arabidopsis.
Generation of secondary siRNAs by legume miRNA families
A number of legume-specific miRNAs members seemed to target disease resistance genes. It is consistent with the fact that disease resistant genes are often highly species- or plant-family-specific. In addition, miR2109 and miR1510, both legume-specific miRNAs co-target five different disease-resistance genes. We also found other pairs of miRNAs that appear to co-target several genes and each pair tended to target genes encoding proteins of similar function (e.g. miR1508 and miR4413 targeting genes encoding PPR-repeat containing proteins). This suggests an extra layer of regulation that might finely tune expression of these genes. For example, these miRNAs might regulate the targets in different tissues, in response to different pathogens or could act to generate tasiRNAs from these loci . Indeed we observed a higher than median production of phased siRNAs from genes encoding three PPR repeat-containing proteins. Consistent with our results, a recent publication also reported two of these genes as phased siRNA-producing loci . Interesting hypotheses on the significance of tasi-RNA generation form R-genes include formation of a gradient to delineate functional boundaries, organ/cell type-specific silencing of gene families and even a possible role in unequal meiotic crossover frequencies often observed in specific gene families.
Potential regulation of nodule-specific gene expression by miRNAs
We also identified a set of soybean miRNAs and corresponding targets that had inverse expression pattern between nodule and roots, and are therefore potentially involved in the regulation of the nodulation process. In M. truncatula, restriction of MtHAP2-1 expression to the meristem by miR169a was shown to be crucial for proper nodule development in M. truncatula. Despite the absence of a meristem in soybean nodules, two targets of miR169, Glyma10g10240 and Glyma17g05920, which encode HAP proteins were highly expressed in the nodules (Figure 5E-F). More interestingly, the expression of miR169 genes was very low in nodules. Similarly, gma-new-miR13587 was highly expressed in the roots, but poorly in nodules and three of its potential targets presented an inverse expression pattern (Figure 5A-C). These observations suggested that nodule-specific expression of genes could be regulated by the presence or absence of miRNAs in a particular organ in soybean.
In conclusion, our study examined the organization of miRNA families in soybean genome and identified possible evolutionary mechanisms associated with functional diversification. The study also provides a comprehensive overview of miRNA diversity and family characteristics in soybean. Consistent with recent reports in Arabidopsis, family size, diversity, length and nucleotide distribution of mature sequences, and the range of targets regulated by them were distinct between conserved and legume- or soybean-specific miRNA families. Finally, inverse expression patterns of specific miRNA-target pairs in different tissues (e.g. roots vs nodules) suggested regulation of organ-specific gene expression by miRNAs in soybean.
Material and methods
Plant growth and B. japonicum treatment (adapted from ).
Soybean (Glycine max cv. Williams82) seeds were surface-sterilized with 10% clorox for 4 minutes followed by 70% ethanol for 2 minutes. They were then rinsed 6 times with sterile deionized water and planted in 4” pots (about 15 seeds per pot) filled with 1:2 (v/v) mixture of sterilized perlite and vermiculite (Hummert International, St Louis, MO). Pots were watered regularly with Â¼ x nitrogen free plant nutrient solution (N- PNS) and maintained in a controlled environment plant growth chamber (16 h light; 25°C; 30% relative humidity). B. japonicum cells (USDA110) were grown and 12 days old seedlings inoculated as described in Subramanian et al..
Small RNA isolation, library construction and sequencing are described in Subramanian et al.. Bioinformatics assisted analyses were essentially same as Subramanian et al. except that prediction of precursor sequences was performed using complete chromosome assembly of soybean (Glyma1; http://www.phytozome.net;[36). Reads with perfect match to the genome in more than 35 positions were also discarded from further analysis. In Arabidopsis, it has been suggested that reads with matches to more than 20 positions in the genome are more likely to be repeat sequences or transposons rather than miRNAs . Compared to an estimated 1.15 fold duplication in Arabidopsis , soybean genome has a 2.55 fold duplication. To account for this higher duplication in soybean, we increased this number to 35. [64, 65]. In addition, potential miRNAs were selected based on criteria for annotation of plant miRNAs described by Meyers et al. . The primary criterion is evidence for precise excision of the miRNA/miRNA* duplex with a two nucleotides overhang in 3’ end. The most abundant strand, therefore considered as the miRNA, should have no more than 4 mismatches with its corresponding miRNA* (especially within the duplex), including a maximum of 1 asymmetrical bulge of 1 or 2 nucleotides. The duplex should represent a minimum of ~25% observed reads from the stem-loop region of the precursor. In the absence of miRNA*, a significant abundance of the miRNA strand is required (we used a threshold of 10 reads in our library of ~350,000 reads). Presence of the potential miRNA sequence in multiple/independent smallRNA libraries also strengthens the validation. Secondary criteria were defined to strengthen plant miRNA annotation, but are not sufficient by themselves. These include conservation in sequence with established miRNAs with a maximum of 3 nucleotides mismatch with the potential miRNA and prediction of potential target genes in the genome. Potential precursor sequences confirming to the above criteria were annotated as miRNAs. Representative sequences were assigned to each miRNA locus based on read abundance and uniqueness of the mature sequence for each locus. The most represented mature sequence was generally selected as representative ID by default. Exceptions were made if this particular sequence was included in another mature sequence, meaning exact same sequence except for additional nucleotides in 3’ and/or 5’ end, and had a read count corresponded to at least 10% of the total abundance in a particular locus. In that case, the longer mature sequence was selected as representative ID1 and the shorter sequence as representative ID2.
List of soybean miRNAs
A list of all miRNAs identified in soybean was established, including miRNAs identified in this study, those already available in miRbase, valid miRNAs listed in Zhang et al. and plant miRNA data base  and the publicly available sequences from articles published during the preparation of this manuscript [22–24]. We examined all of these miRNAs if they fit the criteria established by the community for annotation of plant miRNAs . Only those miRNAs that passed the criteria were included in subsequent analyses. Similarly, all miRNA loci/genes predicted to produce 24nt mature miRNA species were also excluded from further analysis due to their ambiguity being long-miRNAs (lmiRNAs) or heterochromatic-siRNAs (hc-siRNAs).
The position of miRNA genes in the soybean genome (Glyma109) was identified using BLAST searches. Diagrammatic representation of genome organization of miRNAs was obtained using circos software . The relative position of miRNA genes with respect to protein-coding genes was identified using a custom perlscript (available upon request). Illustrations of genome elements were obtained using the soybean genome browser at soybase.org. Phylogenetic trees were constructed using MEGA4  after CLUSTALW alignment of miRNA precursor sequences. The evolutionary history was inferred using the Neighbor-Joining method  and the optimal tree is shown (Figure 2 and Additional file 2: Figure S2). The evolutionary distances were computed using the Maximum Composite Likelihood method  and are in the units of the number of base substitutions per site. Positions containing gaps and missing data in all sequences were eliminated from the dataset (Complete deletion option).
The miRNAs were clustered into families using miRBase criteria: 0 to 2 mismatches being typical, but up to 4 was considered acceptable. One adjustment was made compared to the suggested family ID given by miRBase: based on mature sequence similarities with members of both miR2118 and miR2218 families, members of these families were designated as belonging to the miR2118/2218 family. For each miRNA family, the number of family members, number and size of each unique mature sequence were analyzed. A 2 tail heteroscedastic (Two-sample unequal variance) Student’s T-test was used to analyze the difference between conserved, legume and soybean-specific families for those characteristics and number of target predicted.
Target prediction and validation
The criteria used for target identification were: maximum 1 mismatch between the 2nd and 9th nt, no mismatch at the 10th and 11th nts, maximum 4 mismatches after the 12th nt with no more than 2 consecutive mismatches and a calculated minimum free energy of at least 70% of a perfect complement between miRNA and its target (referred as target prediction score) [8, 9].
Targets were validated using a modified 5’RLM-RACE (RNA ligase-mediated rapid amplification of 5’ cDNA ends) assay. First, polyA mRNA was isolated from total RNA using PolyAtract mRNA isolation systems (Promega Z5300). 5’RLM-RACE was performed on the resulting mRNA preparation using Generacer Kit (Invitrogen, Carlsbad, CA, product No.450168) omitting calf intestinal phosphatase and tobacco acid pyrophosphatase steps to allow ligation of RNA adapter to cleaved transcripts. Nested PCR was performed (Primer sequences for PCR and nested-PCR in Additional file 4: Table S5) following cDNA synthesis and PCR products were gel purified using “Wizard SV gel and PCR clean up system” (Promega, Madison, WI, product No. A9682) and then cloned using “TOPO TA Cloning kit for sequencing” (Invitrogen, Carlsbad, CA, product No. K4575) and sequenced (Beckman Coulter Genomics, Boston, MA).
Tissue harvest and RNA isolation
For expression analysis in different soybean organs, samples were collected from: root, stem and young leaves of 12 days old plants, 14dpi mature nodules, flowers and young pods. A biological replicate that included the tissues of minimum 10 plants and three technical replicates were performed. All tissues were immediately frozen in liquid N2 and stored at −80°C. All root tissues harvested were first washed thoroughly and blot dried.
RNA extraction was performed using Trizol (Invitrogen, Carlsbad, CA). Approximately 1 g of tissue powder was mixed with 10 ml of Trizol and centrifuged (5000xg, 10 min) to remove debris. The supernatant was transferred to a new tube, mixed well with 2 ml of chloroform and centrifuged (5000xg, 10 min). Chloroform extraction was repeated twice with the aqueous phase containing RNA. The resulting supernatant was precipitated overnight at −20°C with an equal volume of isopropanol. After centrifugation (12000xg,10 min), the RNA pellet was washed with 10 ml of 70% ethanol and resuspended in 50 μl of DEPC-treated water. RNA quality was estimated using a Nanodrop ND-1000 spectrophotometer (Nanodrop, Wilmington, DE) and by running an aliquot on an agarose gel.
Gene expression analysis by RT qPCR for miRNAs and target genes
cDNA synthesis for miRNA gene expression was performed with 2 μg RNA, using hairpin primers specific to each mature miRNA sequence essentially as described by Varkonyi et al. (Additional file 3: Table S5) using M-MuLV reverse transcriptase (NEB, Ipswich, MA) and miR1515 as reference gene .
cDNA synthesis for target genes was performed using oligo-dT and M-MuLV reverse transcriptase (NEB, Ipswich, MA ). 2 μg RNA were mixed with 1 μl of 10 μM oligodT and dNTP mix (10 mM each) to a final volume of 16.5 μl. The mixture was incubated at 75°C for 5 minutes followed by 5 minutes on ice. Subsequently, 0.5 μl of the enzyme with corresponding buffer and 0.25 μl of RNase out (Invitrogen, Carlsbad, CA) were added and cDNA synthesis carried out at 42°C for 1 h. Finally, the enzyme was inactivated by incubating 95°C for 5 minutes.
qPCR assays were performed using a Stratagene MX3000P equipment (Stratagene, La Jolla, CA) and SYBR premix (Clontech, Mountain View, CA). For miRNA gene expression, one cycle of 95°C for 10 seconds, 45 cycles of the following: 95°C for 5 seconds , 60°C for 10 seconds and 72°C for 1 second were performed and followed by standard dissociation curve assay (95°C for 1 minute, 55°C for 30 seconds and 95°C for 30 seconds). For target gene expression, one cycle of 95°C for 10 seconds, 40 cycles of the following: 95°C for 5 seconds and 64°C for 20 seconds were performed and followed by standard dissociation curve assay (95°C for 1 minute, 55°C for 30 seconds and 95°C for 30 seconds). List of primers used for qPCR are presented in (Additional file 3: Table S5) and dissociation curves and linearity of amplification in (Additional file 2: Figure S4). We considered a variation in expression level when a difference of at least two fold was observed.
We thank Monish Chitraker (miRNA BLAST search), Natalie J Krier and Sajag Adhikari (miRNA folding analysis) and Shivaram Poigai (qPCR assays) for technical assistance. We thank Drs. Gary Stacey and Paul Rushton for critical comments on the manuscript.
Data for gene expression assays were obtained using instruments available at the South Dakota State University Functional Genomics Core Facility supported in part by the National Science Foundation/EPSCoR Grant No. 0091948 and by the State of South Dakota. Research in the authors’ laboratories is supported by funds from USDA-AFRI (S.S and O.Y), DOE Sun Grant Initiative (S.S), South Dakota Soybean Research and Promotion Council (S.S) and South Dakota State University and Agricultural Experiment station (S.S).
Note added in proof: After completion of data analysis for the manuscript, miRbasev18 was released. Please see Table S1 for IDs assigned by the authors, corresponding miRbase 18 IDs and suggested IDs for new miRNA loci.
- Chen X: MicroRNA biogenesis and function in plants. FEBS Lett. 2005, 579 (26): 5923-5931. 10.1016/j.febslet.2005.07.071.View ArticlePubMedGoogle Scholar
- Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004, 116 (2): 281-297. 10.1016/S0092-8674(04)00045-5.View ArticlePubMedGoogle Scholar
- Jones-Rhoades MW, Bartel DP, Bartel B: MicroRNAS and their regulatory roles in plants. Annu Rev Plant Biol. 2006, 57: 19-53. 10.1146/annurev.arplant.57.032905.105218.View ArticlePubMedGoogle Scholar
- Tang G: Plant microRNAs: an insight into their gene structures and evolution. Semin Cell Dev Biol. 2010, 21 (8): 782-789. 10.1016/j.semcdb.2010.07.009.View ArticlePubMedGoogle Scholar
- Yu B, Yang Z, Li J, Minakhina S, Yang M, Padgett RW, Steward R, Chen X: Methylation as a crucial step in plant microRNA biogenesis. Science. 2005, 307 (5711): 932-935. 10.1126/science.1107130.View ArticlePubMedGoogle Scholar
- Zhu JK: Reconstituting plant miRNA biogenesis. Proc Natl Acad Sci U S A. 2008, 105 (29): 9851-9852. 10.1073/pnas.0805207105.PubMed CentralView ArticlePubMedGoogle Scholar
- Chen X: Small RNAs and their roles in plant development. Annu Rev Cell Dev Biol. 2009, 25: 21-44. 10.1146/annurev.cellbio.042308.113417.View ArticlePubMedGoogle Scholar
- Schwab R, Palatnik JF, Riester M, Schommer C, Schmid M, Weigel D: Specific effects of microRNAs on the plant transcriptome. Dev Cell. 2005, 8 (4): 517-527. 10.1016/j.devcel.2005.01.018.View ArticlePubMedGoogle Scholar
- Allen E, Xie Z, Gustafson AM, Carrington JC: microRNA-directed phasing during trans-acting siRNA biogenesis in plants. Cell. 2005, 121 (2): 207-221. 10.1016/j.cell.2005.04.004.View ArticlePubMedGoogle Scholar
- Rajagopalan R, Vaucheret H, Trejo J, Bartel DP: A diverse and evolutionarily fluid set of microRNAs in Arabidopsis thaliana. Genes Dev. 2006, 20 (24): 3407-3425. 10.1101/gad.1476406.PubMed CentralView ArticlePubMedGoogle Scholar
- Rhoades MW, Reinhart BJ, Lim LP, Burge CB, Bartel B, Bartel DP: Prediction of plant microRNA targets. Cell. 2002, 110 (4): 513-520. 10.1016/S0092-8674(02)00863-2.View ArticlePubMedGoogle Scholar
- Arenas-Huertero C, Perez B, Rabanal F, Blanco-Melo D, De la Rosa C, Estrada-Navarrete G, Sanchez F, Covarrubias AA, Reyes JL: Conserved and novel miRNAs in the legume Phaseolus vulgaris in response to stress. Plant Mol Biol. 2009, 70 (4): 385-401. 10.1007/s11103-009-9480-3.View ArticlePubMedGoogle Scholar
- Sunkar R, Zhu JK: Novel and stress-regulated microRNAs and other small RNAs from Arabidopsis. Plant Cell. 2004, 16 (8): 2001-2019. 10.1105/tpc.104.022830.PubMed CentralView ArticlePubMedGoogle Scholar
- Jones-Rhoades MW, Bartel DP: Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol Cell. 2004, 14 (6): 787-799. 10.1016/j.molcel.2004.05.027.View ArticlePubMedGoogle Scholar
- Navarro L, Dunoyer P, Jay F, Arnold B, Dharmasiri N, Estelle M, Voinnet O, Jones JD: A plant miRNA contributes to antibacterial resistance by repressing auxin signaling. Science. 2006, 312 (5772): 436-439. 10.1126/science.1126088.View ArticlePubMedGoogle Scholar
- Fahlgren N, Jogdeo S, Kasschau KD, Sullivan CM, Chapman EJ, Laubinger S, Smith LM, Dasenko M, Givan SA, Weigel D: MicroRNA gene evolution in Arabidopsis lyrata and Arabidopsis thaliana. Plant Cell. 2010, 22 (4): 1074-1089. 10.1105/tpc.110.073999.PubMed CentralView ArticlePubMedGoogle Scholar
- Meyers BC, Axtell MJ, Bartel B, Bartel DP, Baulcombe D, Bowman JL, Cao X, Carrington JC, Chen X, Green PJ: Criteria for annotation of plant MicroRNAs. Plant Cell. 2008, 20 (12): 3186-3190. 10.1105/tpc.108.064311.PubMed CentralView ArticlePubMedGoogle Scholar
- Subramanian S, Fu Y, Sunkar R, Barbazuk WB, Zhu JK, Yu O: Novel and nodulation-regulated microRNAs in soybean roots. BMC Genomics. 2008, 9: 160-10.1186/1471-2164-9-160.PubMed CentralView ArticlePubMedGoogle Scholar
- Joshi T, Yan Z, Libault M, Jeong DH, Park S, Green PJ, Sherrier DJ, Farmer A, May G, Meyers BC: Prediction of novel miRNAs and associated target genes in Glycine max. BMC Bioinformatics. 2010, 11 (Suppl 1): S14-10.1186/1471-2105-11-S1-S14.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang B, Pan X, Stellwag EJ: Identification of soybean microRNAs and their targets. Planta. 2008, 229 (1): 161-182. 10.1007/s00425-008-0818-x.View ArticlePubMedGoogle Scholar
- Wang Y, Li P, Cao X, Wang X, Zhang A, Li X: Identification and expression analysis of miRNAs from nitrogen-fixing soybean nodules. Biochem Biophys Res Commun. 2009, 378 (4): 799-803. 10.1016/j.bbrc.2008.11.140.View ArticlePubMedGoogle Scholar
- Wong CE, Zhao YT, Wang XJ, Croft L, Wang ZH, Haerizadeh F, Mattick JS, Singh MB, Carroll BJ, Bhalla PL: MicroRNAs in the shoot apical meristem of soybean. J Exp Bot. 2011, 62 (8): 2495-2506. 10.1093/jxb/erq437.View ArticlePubMedGoogle Scholar
- Song QX, Liu YF, Hu XY, Zhang WK, Ma B, Chen SY, Zhang JS: Identification of miRNAs and their target genes in developing soybean seeds by deep sequencing. BMC Plant Biol. 2011, 11: 5-10.1186/1471-2229-11-5.PubMed CentralView ArticlePubMedGoogle Scholar
- Kulcheski FR, de Oliveira LF, Molina LG, Almerao MP, Rodrigues FA, Marcolino J, Barbosa JF, Stolf-Moreira R, Nepomuceno AL, Marcelino-Guimaraes FC: Identification of novel soybean microRNAs involved in abiotic and biotic stresses. BMC Genomics. 2011, 12: 307-10.1186/1471-2164-12-307.PubMed CentralView ArticlePubMedGoogle Scholar
- Jagadeeswaran G, Zheng Y, Li YF, Shukla LI, Matts J, Hoyt P, Macmil SL, Wiley GB, Roe BA, Zhang W: Cloning and characterization of small RNAs from Medicago truncatula reveals four novel legume-specific microRNA families. New Phytol. 2009, 184 (1): 85-98. 10.1111/j.1469-8137.2009.02915.x.View ArticlePubMedGoogle Scholar
- Lelandais-Briere C, Naya L, Sallet E, Calenge F, Frugier F, Hartmann C, Gouzy J, Crespi M: Genome-wide Medicago truncatula small RNA analysis revealed novel microRNAs and isoforms differentially regulated in roots and nodules. Plant Cell. 2009, 21 (9): 2780-2796. 10.1105/tpc.109.068130.PubMed CentralView ArticlePubMedGoogle Scholar
- Szittya G, Moxon S, Santos DM, Jing R, Fevereiro MP, Moulton V, Dalmay T: High-throughput sequencing of Medicago truncatula short RNAs identifies eight new miRNA families. BMC Genomics. 2008, 9: 593-10.1186/1471-2164-9-593.PubMed CentralView ArticlePubMedGoogle Scholar
- Valdes-Lopez O, Yang SS, Aparicio-Fabre R, Graham PH, Reyes JL, Vance CP, Hernandez G: MicroRNA expression profile in common bean (Phaseolus vulgaris) under nutrient deficiency stresses and manganese toxicity. New Phytol. 2010, 187 (3): 805-818. 10.1111/j.1469-8137.2010.03320.x.View ArticlePubMedGoogle Scholar
- Zhao CZ, Xia H, Frazier TP, Yao YY, Bi YP, Li AQ, Li MJ, Li CS, Zhang BH, Wang XJ: Deep sequencing identifies novel and conserved microRNAs in peanuts (Arachis hypogaea L.). BMC Plant Biol. 2010, 10: 3-10.1186/1471-2229-10-3.PubMed CentralView ArticlePubMedGoogle Scholar
- Simon SA, Meyers BC, Sherrier DJ: MicroRNAs in the rhizobia legume symbiosis. Plant Physiol. 2009, 151 (3): 1002-1008. 10.1104/pp.109.144345.PubMed CentralView ArticlePubMedGoogle Scholar
- Combier JP, Frugier F, de Billy F, Boualem A, El-Yahyaoui F, Moreau S, Vernie T, Ott T, Gamas P, Crespi M: MtHAP2-1 is a key transcriptional regulator of symbiotic nodule development regulated by microRNA169 in Medicago truncatula. Genes Dev. 2006, 20 (22): 3084-3088. 10.1101/gad.402806.PubMed CentralView ArticlePubMedGoogle Scholar
- Boualem A, Laporte P, Jovanovic M, Laffont C, Plet J, Combier JP, Niebel A, Crespi M, Frugier F: MicroRNA166 controls root and nodule development in Medicago truncatula. Plant J. 2008, 54 (5): 876-887. 10.1111/j.1365-313X.2008.03448.x.View ArticlePubMedGoogle Scholar
- Li H, Deng Y, Wu T, Subramanian S, Yu O: Misexpression of miR482, miR1512, and miR1515 increases soybean nodulation. Plant Physiol. 2010, 153 (4): 1759-1770. 10.1104/pp.110.156950.PubMed CentralView ArticlePubMedGoogle Scholar
- Gill N, Findley S, Walling JG, Hans C, Ma J, Doyle J, Stacey G, Jackson SA: Molecular and chromosomal evidence for allopolyploidy in soybean. Plant Physiol. 2009, 151 (3): 1167-1174. 10.1104/pp.109.137935.PubMed CentralView ArticlePubMedGoogle Scholar
- Walling JG, Shoemaker R, Young N, Mudge J, Jackson S: Chromosome-level homeology in paleopolyploid soybean (Glycine max) revealed through integration of genetic and chromosome maps. Genetics. 2006, 172 (3): 1893-1900.PubMed CentralView ArticlePubMedGoogle Scholar
- Schmutz J, Cannon SB, Schlueter J, Ma J, Mitros T, Nelson W, Hyten DL, Song Q, Thelen JJ, Cheng J: Genome sequence of the palaeopolyploid soybean. Nature. 2010, 463 (7278): 178-183. 10.1038/nature08670.View ArticlePubMedGoogle Scholar
- Reinhart BJ, Weinstein EG, Rhoades MW, Bartel B, Bartel DP: MicroRNAs in plants. Genes Dev. 2002, 16 (13): 1616-1626. 10.1101/gad.1004402.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang Z, Yu J, Li D, Liu F, Zhou X, Wang T, Ling Y, Su Z: PMRD: plant microRNA database. Nucleic Acids Res. 2010, 38 (Database issue): D806-813.PubMed CentralView ArticlePubMedGoogle Scholar
- Chellappan P, Xia J, Zhou X, Gao S, Zhang X, Coutino G, Vazquez F, Zhang W, Jin H: siRNAs from miRNA sites mediate DNA methylation of target genes. Nucleic Acids Res. 2010, 38 (20): 6883-6894. 10.1093/nar/gkq590.PubMed CentralView ArticlePubMedGoogle Scholar
- Wu L, Zhang Q, Zhou H, Ni F, Wu X, Qi Y: Rice MicroRNA effector complexes and targets. Plant Cell. 2009, 21 (11): x3421-3435. 10.1105/tpc.109.070938.View ArticleGoogle Scholar
- Wu L, Zhou H, Zhang Q, Zhang J, Ni F, Liu C, Qi Y: DNA methylation mediated by a microRNA pathway. Mol Cell. 2010, 38 (3): 465-475. 10.1016/j.molcel.2010.03.008.View ArticlePubMedGoogle Scholar
- Ma Z, Coruh C, Axtell MJ: Arabidopsis lyrata small RNAs: transient MIRNA and small interfering RNA loci within the Arabidopsis genus. Plant Cell. 2010, 22 (4): 1090-1103. 10.1105/tpc.110.073882.PubMed CentralView ArticlePubMedGoogle Scholar
- Hofmann NR: MicroRNA evolution in the genus Arabidopsis. Plant Cell. 2010, 22 (4): 994-10.1105/tpc.110.220411.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang B, Pan X, Cannon CH, Cobb GP, Anderson TA: Conservation and divergence of plant microRNA genes. Plant J. 2006, 46 (2): 243-259. 10.1111/j.1365-313X.2006.02697.x.View ArticlePubMedGoogle Scholar
- Axtell MJ, Jan C, Rajagopalan R, Bartel DP: A two-hit trigger for siRNA biogenesis in plants. Cell. 2006, 127 (3): 565-577. 10.1016/j.cell.2006.09.032.View ArticlePubMedGoogle Scholar
- Montgomery TA, Howell MD, Cuperus JT, Li D, Hansen JE, Alexander AL, Chapman EJ, Fahlgren N, Allen E, Carrington JC: Specificity of ARGONAUTE7-miR390 interaction and dual functionality in TAS3 trans-acting siRNA formation. Cell. 2008, 133 (1): 128-141. 10.1016/j.cell.2008.02.033.View ArticlePubMedGoogle Scholar
- Zhai J, Jeong DH, De Paoli E, Park S, Rosen BD, Li Y, Gonzalez AJ, Yan Z, Kitto SL, Grusak MA: MicroRNAs as master regulators of the plant NB-LRR defense gene family via the production of phased, trans-acting siRNAs. Genes Dev. 2011, 25 (23): 2540-2553. 10.1101/gad.177527.111.PubMed CentralView ArticlePubMedGoogle Scholar
- Chen HM, Chen LT, Patel K, Li YH, Baulcombe DC, Wu SH: 22-Nucleotide RNAs trigger secondary siRNA biogenesis in plants. Proc Natl Acad Sci U S A. 2010, 107 (34): 15269-15274. 10.1073/pnas.1001738107.PubMed CentralView ArticlePubMedGoogle Scholar
- Libault M, Farmer A, Joshi T, Takahashi K, Langley RJ, Franklin LD, He J, Xu D, May G, Stacey G: An integrated transcriptome atlas of the crop model Glycine max, and its use in comparative analyses in plants. Plant J. 2010, 63 (1): 86-99.PubMedGoogle Scholar
- Guo HS, Xie Q, Fei JF, Chua NH: MicroRNA directs mRNA cleavage of the transcription factor NAC1 to downregulate auxin signals for arabidopsis lateral root development. Plant Cell. 2005, 17 (5): 1376-1386. 10.1105/tpc.105.030841.PubMed CentralView ArticlePubMedGoogle Scholar
- Sieber P, Wellmer F, Gheyselinck J, Riechmann JL, Meyerowitz EM: Redundancy and specialization among plant microRNAs: role of the MIR164 family in developmental robustness. Development. 2007, 134 (6): 1051-1060. 10.1242/dev.02817.View ArticlePubMedGoogle Scholar
- Monteys AM, Spengler RM, Wan J, Tecedor L, Lennox KA, Xing Y, Davidson BL: Structure and activity of putative intronic miRNA promoters. RNA. 2010, 16 (3): x495-505. 10.1261/rna.1731910.View ArticleGoogle Scholar
- Hinske LC, Galante PA, Kuo WP, Ohno-Machado L: A potential role for intragenic miRNAs on their hosts' interactome. BMC Genomics. 2010, 11: 533-10.1186/1471-2164-11-533.PubMed CentralView ArticlePubMedGoogle Scholar
- Baskerville S, Bartel DP: Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA. 2005, 11 (3): 241-247. 10.1261/rna.7240905.PubMed CentralView ArticlePubMedGoogle Scholar
- Brown JW, Marshall DF, Echeverria M: Intronic noncoding RNAs and splicing. Trends Plant Sci. 2008, 13 (7): 335-342. 10.1016/j.tplants.2008.04.010.View ArticlePubMedGoogle Scholar
- Merchan F, Boualem A, Crespi M, Frugier F: Plant polycistronic precursors containing non-homologous microRNAs target transcripts encoding functionally related proteins. Genome Biol. 2009, 10 (12): R136-10.1186/gb-2009-10-12-r136.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang L, Chia JM, Kumari S, Stein JC, Liu Z, Narechania A, Maher CA, Guill K, McMullen MD, Ware D: A genome-wide characterization of microRNA genes in maize. PLoS Genet. 2009, 5 (11): e1000716-10.1371/journal.pgen.1000716.PubMed CentralView ArticlePubMedGoogle Scholar
- Allen RS, Li J, Stahle MI, Dubroue A, Gubler F, Millar AA: Genetic analysis reveals functional redundancy and the major target genes of the Arabidopsis miR159 family. Proc Natl Acad Sci U S A. 2007, 104 (41): 16371-16376. 10.1073/pnas.0707653104.PubMed CentralView ArticlePubMedGoogle Scholar
- Guddeti S, Zhang DC, Li AL, Leseberg CH, Kang H, Li XG, Zhai WX, Johns MA, Mao L: Molecular evolution of the rice miR395 gene family. Cell Res. 2005, 15 (8): 631-638. 10.1038/sj.cr.7290333.View ArticlePubMedGoogle Scholar
- Zhao B, Ge L, Liang R, Li W, Ruan K, Lin H, Jin Y: Members of miR-169 family are induced by high salinity and transiently inhibit the NF-YA transcription factor. BMC Mol Biol. 2009, 10: 29-10.1186/1471-2199-10-29.PubMed CentralView ArticlePubMedGoogle Scholar
- Li Y, Fu Y, Ji L, Wu C, Zheng C: Characterization and expression analysis of the Arabidopsis mir169 family. Plant Science. 2010, 178 (3): 271-280. 10.1016/j.plantsci.2010.01.007.View ArticleGoogle Scholar
- Bartel DP: MicroRNAs: target recognition and regulatory functions. Cell. 2009, 136 (2): 215-233. 10.1016/j.cell.2009.01.002.PubMed CentralView ArticlePubMedGoogle Scholar
- Grant D, Cregan P, Shoemaker RC: Genome organization in dicots: genome duplication in Arabidopsis and synteny between soybean and Arabidopsis. Proc Natl Acad Sci U S A. 2000, 97 (8): 4168-4173. 10.1073/pnas.070430597.PubMed CentralView ArticlePubMedGoogle Scholar
- Shoemaker RC, Polzin K, Labate J, Specht J, Brummer EC, Olson T, Young N, Concibido V, Wilcox J, Tamulonis JP: Genome duplication in soybean (Glycine subgenus soja). Genetics. 1996, 144 (1): 329-338.PubMed CentralPubMedGoogle Scholar
- Jackson SA, Rokhsar D, Stacey G, Shoemaker R, Schmutz J, Grimwood J: Toward a Reference Sequence of the Soybean Genome: A Multiagency Effort. Crop science. 2006, 46 (Supplement_1): S-55-S-61.View ArticleGoogle Scholar
- Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, Jones SJ, Marra MA: Circos: an information aesthetic for comparative genomics. Genome Res. 2009, 19 (9): 1639-1645. 10.1101/gr.092759.109.PubMed CentralView ArticlePubMedGoogle Scholar
- Tamura K, Dudley J, Nei M, Kumar S: MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Mol Biol Evol. 2007, 24 (8): 1596-1599. 10.1093/molbev/msm092.View ArticlePubMedGoogle Scholar
- Saitou N, Nei M: The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol. 1987, 4 (4): 406-425.PubMedGoogle Scholar
- Tamura K, Nei M, Kumar S: Prospects for inferring very large phylogenies by using the neighbor-joining method. Proc Natl Acad Sci U S A. 2004, 101 (30): 11030-11035. 10.1073/pnas.0404206101.PubMed CentralView ArticlePubMedGoogle Scholar
- Varkonyi-Gasic E, Wu R, Wood M, Walton EF, Hellens RP: Protocol: a highly sensitive RT-PCR method for detection and quantification of microRNAs. Plant Methods. 2007, 3: 12-10.1186/1746-4811-3-12.PubMed CentralView ArticlePubMedGoogle Scholar
- Subramanian S, Stacey G, Yu O: Endogenous isoflavones are essential for the establishment of symbiosis between soybean and Bradyrhizobium japonicum. Plant J. 2006, 48 (2): 261-273. 10.1111/j.1365-313X.2006.02874.x.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.