Abstract

Rhizomes are organs of fundamental importance to plant competitiveness and invasiveness. We have identified genes expressed at substantially higher levels in rhizomes than other plant parts, and explored their functional categorization, genomic organization, regulatory motifs, and association with quantitative trait loci (QTLs) conferring rhizomatousness. The finding that genes with rhizome-enriched expression are distributed across a wide range of functional categories suggests some degree of specialization of individual members of many gene families in rhizomatous plants. A disproportionate share of genes with rhizome-enriched expression was implicated in secondary and hormone metabolism, and abiotic stimuli and development. A high frequency of unknown-function genes reflects our still limited knowledge of this plant organ. A putative oligosaccharyl transferase showed the highest degree of rhizome-specific expression, with several transcriptional or regulatory protein complex factors also showing high (but lesser) degrees of specificity. Inferred by the upstream sequences of their putative rice (Oryza sativa) homologs, sorghum (Sorghum bicolor) genes that were relatively highly expressed in rhizome tip tissues were enriched for cis-element motifs, including the pyrimidine box, TATCCA box, and CAREs box, implicating the gibberellins in regulation of many rhizome-specific genes. From cDNA clones showing rhizome-enriched expression, expressed sequence tags forming 455 contigs were plotted on the rice genome and aligned to QTL likelihood intervals for ratooning and rhizomatous traits in rice and sorghum. Highly expressed rhizome genes were somewhat enriched in QTL likelihood intervals for rhizomatousness or ratooning, with specific candidates including some of the most rhizome-specific genes. Some rhizomatousness and ratooning QTLs were shown to be potentially related to one another as a result of ancient duplication, suggesting long-term functional conservation of the underlying genes. Insight into genes and pathways that influence rhizome growth set the stage for genetic and/or exogenous manipulation of rhizomatousness, and for further dissection of the molecular evolution of rhizomatousness.

Rhizomes are organs of fundamental importance to plant competitiveness and invasiveness, playing two contrasting roles in agricultural ecology. As a primary means of dispersal, rhizomes are an essential component of “weediness” for many of our most noxious weeds, including Sorghum halepense L. Pers. (Johnsongrass), Cynodon dactylon L. Pers. (bermudagrass), and Cyperus spp. (nutsedge). S. halepense and C. dactylon were introduced to the United States as prospective crops but became major weeds, largely due to their aggressive rhizomes. The threat of other such escapes restricts improvement of several crops. For example, the rhizomatous grasses Oryza longistaminata (sexually compatible with rice [Oryza sativa]) and Saccharum spontaneum (sexually compatible with sugarcane [Saccharum officinarum]) harbor many genes of potential value for improving rice and sugarcane, respectively. They cannot, however, be legally grown in the United States due to the threat of their becoming weedy escapes.

By contrast, rhizomes are advantageous in establishment and persistence of dense, productive stands of forage and turfgrasses, including Cynodon spp. (bermudagrass), Paspalum spp. (bahia and dallisgrass), Pennisetum/Cenchrus spp. (buffelgrass), and many others. Such grasses are cultivated on more than 60 million acres in the southern United States alone (Burton, 1989), and have an estimated value of $3 billion per year in the United States as forage and a national economic impact estimated at $24 billion annually (Barnes and Baylor, 1995) via meat, dairy, and fiber (wool) production. These species, together with wild perennial grasses, form a dense subterranean “net” that plays a major role in erosion control. Failure to recognize this role was partly responsible for the Dust Bowl epochs that have periodically crippled the economies of various parts of the United States.

Botanically, rhizomes are modified subterranean stems that are diageotropic (i.e. orient their growth perpendicular to the force of gravity; Gizmawy et al., 1985) but retain the ability to spawn geotropic shoots that can become independent ramets. Rhizomes and tillers both develop from axillary buds at the lowermost nodes of the erect leafy shoot of the plant. These basal buds exhibit a clear positional gradient, with acropetally increasing tendency to develop into tillers rather than rhizomes, both in S. halepense and in Agropyron repens (Gizmawy et al., 1985).

Several lines of evidence suggest that an overlapping set of genes may account for much of the genetic variation in growth and development of rhizomes across diverse taxa. We have previously reported on the identification of quantitative trait loci (QTLs) responsible for several aspects of rhizome growth, in a cross between cultivated Sorghum bicolor L. Moench and a rhizomatous relative Sorghum propinquum (Paterson et al., 1995). The chromosomal locations harboring most QTLs responsible for rhizomatousness in Sorghum corresponded to the regions containing QTLs for rhizomatousness in Oryza (Hu et al., 2003), suggesting that analysis of this trait in botanical models will extrapolate broadly to a wide range of cultivated and weedy Poaceae cereals. Recently, QTL mapping of traits associated with perennialism in a cross between annual maize (Zea mays) and perennial teosinte (Zea diploperennis) suggested additional correspondence (Westerbergh and Doebley, 2004).

Little is known of the molecular mechanisms related to initiation and elongation of rhizomes, although several well-described gene functions associated with tillering mechanisms in the Poaceae may also have some relevance to rhizomes. For example, a putative bHLH transcription factor, teosinte branched1, accounts partly for morphological differences in axillary branching between maize and teosinte (Hubbard et al., 2002). The rice MONOCULM1 (MOC1) gene isolated from tillering mutants encodes a GRAS family protein (Li et al., 2003). Anatomical and histological features of moc1 mutants advanced an expectation that MOC1 would play a key role in axillary bud initiation and promotion of tiller outgrowth. It remains to be determined the degree to which mechanisms of initiation and elongation of (diageotropic) rhizome tissues parallel molecular mechanisms determining tiller formation.

We have sampled the population of genes that are highly expressed in rhizomes relative to other plant parts, and have explored this sample for functions, genomic organization, regulatory motifs, and proximity to QTLs conferring rhizomatousness. We have compared these genes to random surveys of the rhizotranscriptome in S. halepense and S. propinquum. Insight into genes and pathways that influence rhizome growth set the stage for genetic and/or exogenous manipulation of rhizomatousness, and for further dissection of the molecular evolution of rhizomatousness.

RESULTS

Isolation of Rhizome-Enriched Genes

Two cDNA libraries derived from the rhizome tip (RT; distal 1 cm of the young rhizome) tissues of S. halepense (pSH) and S. propinquum (pSP), respectively, were studied. A total of 18,432 clones per library were analyzed by hybridizations of macroarrays with labeled cDNAs from RT, mature rhizome internodes (RMI), and pooled aboveground (AG) tissues. Relative expression levels of the cDNA clones ranged from 6.33 to 0.40 normalized units, with a mean value of 1.00 in all tissues (Table I  

Table I.

Expression profile of cDNA clones using macroarrays


Genotype

No. of Tested Clones

Tissuea  

Expression Rangeb  

Mean ± sd  
pSH 18,432 RT 6.33–0.42 1.00 ± 0.30
RMI 4.55–0.58 1.00 ± 0.22
AG 5.70–0.56 1.00 ± 0.22
pSP 18,432 RT 6.25–0.43 1.00 ± 0.26
RMI 4.10–0.40 1.00 ± 0.29


AG
3.87–0.51
1.00 ± 0.19

Genotype

No. of Tested Clones

Tissuea  

Expression Rangeb  

Mean ± sd  
pSH 18,432 RT 6.33–0.42 1.00 ± 0.30
RMI 4.55–0.58 1.00 ± 0.22
AG 5.70–0.56 1.00 ± 0.22
pSP 18,432 RT 6.25–0.43 1.00 ± 0.26
RMI 4.10–0.40 1.00 ± 0.29


AG
3.87–0.51
1.00 ± 0.19
a

Each tissue (RT, RMI, and AG) was used to extract mRNAs as templates for target synthesis.

b

Expression data were calculated from normalized signal intensity for each clone (described in “Materials and Methods”) detected by phosphorimage scanning.

Table I.

Expression profile of cDNA clones using macroarrays


Genotype

No. of Tested Clones

Tissuea  

Expression Rangeb  

Mean ± sd  
pSH 18,432 RT 6.33–0.42 1.00 ± 0.30
RMI 4.55–0.58 1.00 ± 0.22
AG 5.70–0.56 1.00 ± 0.22
pSP 18,432 RT 6.25–0.43 1.00 ± 0.26
RMI 4.10–0.40 1.00 ± 0.29


AG
3.87–0.51
1.00 ± 0.19

Genotype

No. of Tested Clones

Tissuea  

Expression Rangeb  

Mean ± sd  
pSH 18,432 RT 6.33–0.42 1.00 ± 0.30
RMI 4.55–0.58 1.00 ± 0.22
AG 5.70–0.56 1.00 ± 0.22
pSP 18,432 RT 6.25–0.43 1.00 ± 0.26
RMI 4.10–0.40 1.00 ± 0.29


AG
3.87–0.51
1.00 ± 0.19
a

Each tissue (RT, RMI, and AG) was used to extract mRNAs as templates for target synthesis.

b

Expression data were calculated from normalized signal intensity for each clone (described in “Materials and Methods”) detected by phosphorimage scanning.

). For each of the two clone sets, expression levels in RT and RMI were correlated (r = 0.51, 061 for pSH and pSP, respectively). Expression levels in RT more closely resembled AG (r = 0.41, 0.34) than did RMI (r = 0.30, 0.30).

Based on the relative expression levels of RT versus RMI (RT/RMI) and AG (RT/AG) tissues, 192 clones (approximately 1%) with the highest ratios from each library were selected as candidate rhizome-enriched genes. Selected as negative controls were 48 clones (approximately 0.3%) with the lowest ratios from each library (Table II  

Table II.

Expression profile of clone sets constructed on the basis of relative expression ratio


Genotype

Relative Expression Ratio

No. of Selected Clones

Expression Range

Mean ± sd  
pSH RT/RMI High 192 6.66–1.69 1.96 ± 0.50
Low 48 0.45–0.19 0.39 ± 0.06
RT/AG High 192 8.48–1.78 2.10 ± 0.68
Low 48 0.42–0.24 0.36 ± 0.05
pSP RT/RMI High 192 3.96–1.69 1.89 ± 0.27
Low 48 0.50–0.27 0.44 ± 0.05
RT/AG High 192 4.22–1.83 2.18 ± 0.36


Low
48
0.48–0.31
0.44 ± 0.03

Genotype

Relative Expression Ratio

No. of Selected Clones

Expression Range

Mean ± sd  
pSH RT/RMI High 192 6.66–1.69 1.96 ± 0.50
Low 48 0.45–0.19 0.39 ± 0.06
RT/AG High 192 8.48–1.78 2.10 ± 0.68
Low 48 0.42–0.24 0.36 ± 0.05
pSP RT/RMI High 192 3.96–1.69 1.89 ± 0.27
Low 48 0.50–0.27 0.44 ± 0.05
RT/AG High 192 4.22–1.83 2.18 ± 0.36


Low
48
0.48–0.31
0.44 ± 0.03
Table II.

Expression profile of clone sets constructed on the basis of relative expression ratio


Genotype

Relative Expression Ratio

No. of Selected Clones

Expression Range

Mean ± sd  
pSH RT/RMI High 192 6.66–1.69 1.96 ± 0.50
Low 48 0.45–0.19 0.39 ± 0.06
RT/AG High 192 8.48–1.78 2.10 ± 0.68
Low 48 0.42–0.24 0.36 ± 0.05
pSP RT/RMI High 192 3.96–1.69 1.89 ± 0.27
Low 48 0.50–0.27 0.44 ± 0.05
RT/AG High 192 4.22–1.83 2.18 ± 0.36


Low
48
0.48–0.31
0.44 ± 0.03

Genotype

Relative Expression Ratio

No. of Selected Clones

Expression Range

Mean ± sd  
pSH RT/RMI High 192 6.66–1.69 1.96 ± 0.50
Low 48 0.45–0.19 0.39 ± 0.06
RT/AG High 192 8.48–1.78 2.10 ± 0.68
Low 48 0.42–0.24 0.36 ± 0.05
pSP RT/RMI High 192 3.96–1.69 1.89 ± 0.27
Low 48 0.50–0.27 0.44 ± 0.05
RT/AG High 192 4.22–1.83 2.18 ± 0.36


Low
48
0.48–0.31
0.44 ± 0.03
). Of the 768 selected candidate rhizome-enriched genes, 71 (9%) clones with high RT/RMI ratios also had high RT/AG ratios. The resulting 697 unique cDNA clones from putatively rhizome-enriched genes and 192 controls were sequenced from both ends. Assembly with phred and phrap produced 343 and 393 sequences from the pSP and pSH libraries, respectively (accession nos. DN551694DN551965, DN552280DN552796). Phrap assembly using both libraries formed a 534-member set of nonoverlapping sequences.

We also included in our analysis sequences from a prior study (Y. Si and A.H. Paterson, unpublished data), in which differential display (DD; Liang and Pardee, 1992) was used to identify transcripts present in young rhizomes but absent in rhizome-derived shoots developing into tillers. Slot-blot hybridization analysis showed that these pSHR (S. halepense rhizomes) clones tended to be highly expressed in rhizome tissues but rare in other tissues (Y. Si and A.H. Paterson, unpublished data). Among 103 rhizome-specific fragments amplified from DD, 75 were successfully cloned, sequenced, and deposited in GenBank (accession nos. BQ479097 and BQ479098, BQ656181BQ656248, and BQ789583BQ789587). pSHR clone lengths average only 267 bp and are largely composed of the generally less conserved 3′ untranslated regions. Therefore, to facilitate computational analysis, a search of the GenBank Sorghum (taxonomy ID 4557) database was performed. A total of 67 longer sorghum cDNA sequences identified by best homology were substituted for relatively short DD pSHR clones and analyzed along with the remaining eight original pSHR sequences.

Functional Categorization of Rhizome-Enriched Genes

A set of 2,616 sequence contigs composed of randomly selected expressed sequence tags (ESTs) from S. halepense (rhiz1 = pSH) and S. propinquum (rhiz2 = pSP) libraries were downloaded from the Comparative Grass Genomics Center database (ftp://cggc.agtec.uga.edu/SorghumUnigene/fasta_file/) for comparisons to differentially expressed rhizome genes. All sequences with a significant match in the plant and/or embryophyta databases were divided into 15 categories based on their putative biochemical and physiological roles (Table III  

Table III.

Functional categorization of rhizome tissue-derived ESTsa


Functional Categories

High RT/RMI

Low RT/RMI

High RT/AG

Low RT/AG

pSHR

Random Rhizomeb  
No. of tested contigs and singlets 295c 56 242c 66 67 2,616
No homology 10.85 ± 3.55 8.93 ± 6.38 6.20 ± 3.04 10.61 ± 7.43 17.91 ± 5.16 2.91 ± 0.64
Unknown function 31.86 ± 5.32 30.36 ± 10.55 29.75 ± 5.76 30.30 ± 11.09 20.90 ± 4.83 44.65 ± 1.91
Miscellaneous 2.37 ± 1.74 1.79 ± 2.95 1.65 ± 1.61 1.52 ± 2.95 0.00 ± 0.00 2.29 ± 0.57
Primary metabolism 10.85 ± 3.55 8.93 ± 6.38 9.50 ± 3.70 12.12 ± 7.87 13.43 ± 4.38 12.35 ± 1.26
Secondary/hormone metabolism 4.41 ± 2.34 7.14 ± 5.76 11.16 ± 3.97 1.52 ± 2.95 5.97 ± 2.90 4.13 ± 0.76
Chromatin and DNA metabolism 1.69 ± 1.47 0.00 ± 0.00 2.48 ± 1.96 3.03 ± 4.14 2.99 ± 2.15 0.96 ± 0.37
Protein synthesis/processing 9.49 ± 3.34 26.79 ± 10.11 8.26 ± 3.47 7.58 ± 6.38 14.93 ± 4.67 10.24 ± 1.16
Gene expression/RNA metabolism 4.41 ± 2.34 1.79 ± 2.95 3.31 ± 2.25 3.03 ± 4.14 5.97 ± 3.02 3.10 ± 0.66
Transporter/trafficking 5.76 ± 2.66 8.93 ± 6.38 8.26 ± 3.47 9.09 ± 6.94 7.46 ± 3.30 7.00 ± 0.98
Signal transduction 4.07 ± 2.25 3.57 ± 4.14 3.72 ± 2.38 4.55 ± 5.03 2.99 ± 2.14 3.33 ± 0.69
Cell wall structure/metabolism 2.37 ± 1.74 0.00 ± 0.00 2.07 ± 1.79 1.52 ± 2.95 2.99 ± 2.15 1.72 ± 0.50
Cell division 0.68 ± 0.94 0.00 ± 0.00 0.41 ± 0.81 1.52 ± 2.95 1.49 ± 1.54 0.46 ± 0.26
Cytoskeleton 1.02 ± 1.14 0.00 ± 0.00 1.65 ± 1.61 0.00 ± 0.00 0.00 ± 0.00 1.68 ± 0.49
Defense and cell rescue 2.37 ± 1.74 0.00 ± 0.00 2.48 ± 1.96 3.03 ± 4.14 0.00 ± 0.00 1.26 ± 0.43
Abiotic stimuli/development
7.80 ± 3.06
1.79 ± 2.95
9.09 ± 3.62
10.61 ± 7.43
2.99 ± 2.08
3.94 ± 0.75

Functional Categories

High RT/RMI

Low RT/RMI

High RT/AG

Low RT/AG

pSHR

Random Rhizomeb  
No. of tested contigs and singlets 295c 56 242c 66 67 2,616
No homology 10.85 ± 3.55 8.93 ± 6.38 6.20 ± 3.04 10.61 ± 7.43 17.91 ± 5.16 2.91 ± 0.64
Unknown function 31.86 ± 5.32 30.36 ± 10.55 29.75 ± 5.76 30.30 ± 11.09 20.90 ± 4.83 44.65 ± 1.91
Miscellaneous 2.37 ± 1.74 1.79 ± 2.95 1.65 ± 1.61 1.52 ± 2.95 0.00 ± 0.00 2.29 ± 0.57
Primary metabolism 10.85 ± 3.55 8.93 ± 6.38 9.50 ± 3.70 12.12 ± 7.87 13.43 ± 4.38 12.35 ± 1.26
Secondary/hormone metabolism 4.41 ± 2.34 7.14 ± 5.76 11.16 ± 3.97 1.52 ± 2.95 5.97 ± 2.90 4.13 ± 0.76
Chromatin and DNA metabolism 1.69 ± 1.47 0.00 ± 0.00 2.48 ± 1.96 3.03 ± 4.14 2.99 ± 2.15 0.96 ± 0.37
Protein synthesis/processing 9.49 ± 3.34 26.79 ± 10.11 8.26 ± 3.47 7.58 ± 6.38 14.93 ± 4.67 10.24 ± 1.16
Gene expression/RNA metabolism 4.41 ± 2.34 1.79 ± 2.95 3.31 ± 2.25 3.03 ± 4.14 5.97 ± 3.02 3.10 ± 0.66
Transporter/trafficking 5.76 ± 2.66 8.93 ± 6.38 8.26 ± 3.47 9.09 ± 6.94 7.46 ± 3.30 7.00 ± 0.98
Signal transduction 4.07 ± 2.25 3.57 ± 4.14 3.72 ± 2.38 4.55 ± 5.03 2.99 ± 2.14 3.33 ± 0.69
Cell wall structure/metabolism 2.37 ± 1.74 0.00 ± 0.00 2.07 ± 1.79 1.52 ± 2.95 2.99 ± 2.15 1.72 ± 0.50
Cell division 0.68 ± 0.94 0.00 ± 0.00 0.41 ± 0.81 1.52 ± 2.95 1.49 ± 1.54 0.46 ± 0.26
Cytoskeleton 1.02 ± 1.14 0.00 ± 0.00 1.65 ± 1.61 0.00 ± 0.00 0.00 ± 0.00 1.68 ± 0.49
Defense and cell rescue 2.37 ± 1.74 0.00 ± 0.00 2.48 ± 1.96 3.03 ± 4.14 0.00 ± 0.00 1.26 ± 0.43
Abiotic stimuli/development
7.80 ± 3.06
1.79 ± 2.95
9.09 ± 3.62
10.61 ± 7.43
2.99 ± 2.08
3.94 ± 0.75
a

Values are percentages of unique sequences per treatment in each category ± approximate 95% confidence limits.

b

Randomly sampled EST-based contigs from rhizome cDNA libraries, i.e. S. halepense and S. propinquum.

c

Each of 71 clones with high RT/RMI as well as high RT/AG was assigned to both ratios.

Table III.

Functional categorization of rhizome tissue-derived ESTsa


Functional Categories

High RT/RMI

Low RT/RMI

High RT/AG

Low RT/AG

pSHR

Random Rhizomeb  
No. of tested contigs and singlets 295c 56 242c 66 67 2,616
No homology 10.85 ± 3.55 8.93 ± 6.38 6.20 ± 3.04 10.61 ± 7.43 17.91 ± 5.16 2.91 ± 0.64
Unknown function 31.86 ± 5.32 30.36 ± 10.55 29.75 ± 5.76 30.30 ± 11.09 20.90 ± 4.83 44.65 ± 1.91
Miscellaneous 2.37 ± 1.74 1.79 ± 2.95 1.65 ± 1.61 1.52 ± 2.95 0.00 ± 0.00 2.29 ± 0.57
Primary metabolism 10.85 ± 3.55 8.93 ± 6.38 9.50 ± 3.70 12.12 ± 7.87 13.43 ± 4.38 12.35 ± 1.26
Secondary/hormone metabolism 4.41 ± 2.34 7.14 ± 5.76 11.16 ± 3.97 1.52 ± 2.95 5.97 ± 2.90 4.13 ± 0.76
Chromatin and DNA metabolism 1.69 ± 1.47 0.00 ± 0.00 2.48 ± 1.96 3.03 ± 4.14 2.99 ± 2.15 0.96 ± 0.37
Protein synthesis/processing 9.49 ± 3.34 26.79 ± 10.11 8.26 ± 3.47 7.58 ± 6.38 14.93 ± 4.67 10.24 ± 1.16
Gene expression/RNA metabolism 4.41 ± 2.34 1.79 ± 2.95 3.31 ± 2.25 3.03 ± 4.14 5.97 ± 3.02 3.10 ± 0.66
Transporter/trafficking 5.76 ± 2.66 8.93 ± 6.38 8.26 ± 3.47 9.09 ± 6.94 7.46 ± 3.30 7.00 ± 0.98
Signal transduction 4.07 ± 2.25 3.57 ± 4.14 3.72 ± 2.38 4.55 ± 5.03 2.99 ± 2.14 3.33 ± 0.69
Cell wall structure/metabolism 2.37 ± 1.74 0.00 ± 0.00 2.07 ± 1.79 1.52 ± 2.95 2.99 ± 2.15 1.72 ± 0.50
Cell division 0.68 ± 0.94 0.00 ± 0.00 0.41 ± 0.81 1.52 ± 2.95 1.49 ± 1.54 0.46 ± 0.26
Cytoskeleton 1.02 ± 1.14 0.00 ± 0.00 1.65 ± 1.61 0.00 ± 0.00 0.00 ± 0.00 1.68 ± 0.49
Defense and cell rescue 2.37 ± 1.74 0.00 ± 0.00 2.48 ± 1.96 3.03 ± 4.14 0.00 ± 0.00 1.26 ± 0.43
Abiotic stimuli/development
7.80 ± 3.06
1.79 ± 2.95
9.09 ± 3.62
10.61 ± 7.43
2.99 ± 2.08
3.94 ± 0.75

Functional Categories

High RT/RMI

Low RT/RMI

High RT/AG

Low RT/AG

pSHR

Random Rhizomeb  
No. of tested contigs and singlets 295c 56 242c 66 67 2,616
No homology 10.85 ± 3.55 8.93 ± 6.38 6.20 ± 3.04 10.61 ± 7.43 17.91 ± 5.16 2.91 ± 0.64
Unknown function 31.86 ± 5.32 30.36 ± 10.55 29.75 ± 5.76 30.30 ± 11.09 20.90 ± 4.83 44.65 ± 1.91
Miscellaneous 2.37 ± 1.74 1.79 ± 2.95 1.65 ± 1.61 1.52 ± 2.95 0.00 ± 0.00 2.29 ± 0.57
Primary metabolism 10.85 ± 3.55 8.93 ± 6.38 9.50 ± 3.70 12.12 ± 7.87 13.43 ± 4.38 12.35 ± 1.26
Secondary/hormone metabolism 4.41 ± 2.34 7.14 ± 5.76 11.16 ± 3.97 1.52 ± 2.95 5.97 ± 2.90 4.13 ± 0.76
Chromatin and DNA metabolism 1.69 ± 1.47 0.00 ± 0.00 2.48 ± 1.96 3.03 ± 4.14 2.99 ± 2.15 0.96 ± 0.37
Protein synthesis/processing 9.49 ± 3.34 26.79 ± 10.11 8.26 ± 3.47 7.58 ± 6.38 14.93 ± 4.67 10.24 ± 1.16
Gene expression/RNA metabolism 4.41 ± 2.34 1.79 ± 2.95 3.31 ± 2.25 3.03 ± 4.14 5.97 ± 3.02 3.10 ± 0.66
Transporter/trafficking 5.76 ± 2.66 8.93 ± 6.38 8.26 ± 3.47 9.09 ± 6.94 7.46 ± 3.30 7.00 ± 0.98
Signal transduction 4.07 ± 2.25 3.57 ± 4.14 3.72 ± 2.38 4.55 ± 5.03 2.99 ± 2.14 3.33 ± 0.69
Cell wall structure/metabolism 2.37 ± 1.74 0.00 ± 0.00 2.07 ± 1.79 1.52 ± 2.95 2.99 ± 2.15 1.72 ± 0.50
Cell division 0.68 ± 0.94 0.00 ± 0.00 0.41 ± 0.81 1.52 ± 2.95 1.49 ± 1.54 0.46 ± 0.26
Cytoskeleton 1.02 ± 1.14 0.00 ± 0.00 1.65 ± 1.61 0.00 ± 0.00 0.00 ± 0.00 1.68 ± 0.49
Defense and cell rescue 2.37 ± 1.74 0.00 ± 0.00 2.48 ± 1.96 3.03 ± 4.14 0.00 ± 0.00 1.26 ± 0.43
Abiotic stimuli/development
7.80 ± 3.06
1.79 ± 2.95
9.09 ± 3.62
10.61 ± 7.43
2.99 ± 2.08
3.94 ± 0.75
a

Values are percentages of unique sequences per treatment in each category ± approximate 95% confidence limits.

b

Randomly sampled EST-based contigs from rhizome cDNA libraries, i.e. S. halepense and S. propinquum.

c

Each of 71 clones with high RT/RMI as well as high RT/AG was assigned to both ratios.

). For all clone sources, the “unknown function” category, composed of sequences with no significant hit to the plant protein database but a significant match to non-self sequences in the embryophyta database, was the most abundant. Curiously, a significantly higher fraction of the randomly selected rhizome EST sequences showed unknown function than all differentially expressed groups.

Among functional categories, there was striking and statistically significant enrichment of genes involved with secondary and hormone metabolism in the high RT/AG group, and protein synthesis and processing in the low RT/RMI selected group. Genes related to abiotic stimuli and development were significantly enriched in high RT/RMI relative to low RT/RMI and to the random set, but both high and low RT/AG resembled high RT/RMI.

Genes Expressed at High Levels in RT

Genes showing the 50 highest expression levels in RT relative to RMI and AG tissues are described in Supplemental Tables S1 (RT/RMI) and S2 (RT/AG), respectively. (The corresponding genes with the lowest expression ratios are described in Supplemental Table S3.) The pSH clone identified as c083, encoding a putative oligosaccharyl transferase (STT3), showed the highest relative expression ratios in both RT/RMI (6.66) and RT/AG (8.48) treatments.

Several high RT/RMI and/or high RT/AG expression candidates corresponded to transcriptional or regulatory protein complex factors. Five candidates (and their putative protein products), c298 (zinc-finger [DHHC-type] family protein), c110 (ribosomal protein S11), c243 (nuclear RNA-binding protein), c171 (mitogen-activated protein kinase), and c257 (26S proteasome regulatory particle triple-A ATPase subunit), map to QTL interval QRn5; AQDK006 and QRl7; sorghum regrowth on LG-C (chromosome 1) corresponding to rice chromosome 1; and the latter two to RAAB CQE43 on rice chromosome 6, respectively. A total of 10 other possible transcription factors did not show significant sequence homology with rice or were located outside rhizome-related QTL regions.

The clone set selected based on relative expression ratio data was compared to pSHR clones isolated by DD (Y. Si and A.H. Paterson, unpublished data) and their derived sequences using the local BLASTn program. Ten pSHR clones (approximately 13%) showed significant homology (E < 10−25) with macroarray-selected genes: five high RT/RMI (c155, c179 twice, c202, and s177), four high RT/AG (c121, c328, and s021 twice), and, curiously, one low RT/RMI (s010). The relatively low 13% match between the two clone sets, although much higher than would be expected if each method were randomly sampling the transcriptome, probably reflects differences related to the methods; in particular, DD-PCR may be more sensitive to identification of differentially expressed low-abundance transcripts. The incongruous low RT/RMI clone is not especially surprising in that the pSHR clones were selected based on DD-PCR products present from a mRNA pool including both mature rhizomes and tips but absent from rhizome-derived shoots. Five of the 10 matching clones showed significant homology with genes deposited in the plant protein database, e.g. cytochrome P450, ubiquinol-cytochrome c reductase, lipase class 3 family protein, and Golgi-associated protein se-wap41 (two matches).

Identifying Rice Homologs

A total of 453 of the 609 unique sequences (330 high RT/RMI and/or RT/AG, 79 low RT/RMI and/or RT/AG, and eight pSHR and 36 pSHR derived) could be plotted on the rice pseudomolecules and aligned with genetically defined intervals of sorghum (Fig. 1  
Figure 1.

Associations between sorghum and rice rhizomatous and ratooning QTLs and candidate differentially expressed ESTs. Rice chromosome 1 and the corresponding sorghum QTL are shown in the printed volume; figures for the remaining chromosomes are available in Supplemental Figure S1. Comparative maps with QTLs by Hu et al. (2003) are modified according to physical data from TIGR release 2 rice pseudomolecules. In Figure 1 and/or its supplements, lines drawn to rice chromosome crossbars show BLASTn-supported locations of sorghum-rice anchor markers (as described in text). Additional anchor markers with inferred genetic positions based on either the Paterson et al. (1995) or high-density sorghum map (Bowers et al., 2003) are indicated by §. Loci added by BLASTn to the TIGR release 3 physical assembly are indicated by *. Anchor markers connected by dashed lines reflect changed positions, relative to the report by Hu et al. (2003), as determined based on the current rice pseudomolecules. ♦ indicates best BLASTn hits are to other genomic positions. Other observed discrepancies in colinearity of the Rice-IRRI RD23/Olong F2 QTL 2003 population mapped markers and the TIGR version 2 physical assembly are indicated by RM and OSR markers located to the right of the rice chromosome. For example, the physical map order of three markers, OSR13-OSR16-RM36, flanking the Rhz2 locus deviates from the genetic order of OSR16-RM36-OSR16.

; Supplemental Fig. S1). The rhizome-derived cDNA sequences were widely distributed throughout the genome, showing no obvious bias correlating with either the species or differential expression.

Comparison of Putative cis-Acting Regulatory Elements

To compare putative cis-acting regulatory elements between genes expressed at high and low levels in RT, 1-kb upstream regions from the ATG translation start site were retrieved from the rice pseudomolecules. Putative upstream promoter regions could be retrieved for 395 loci, including 153 high RT/RMI, 24 low RT/RMI, 148 high RT/AG, 31 low RT/AG, and 39 pSHR. Using the PLACE database, about 70,985 candidate cis-acting regulatory elements were identified from both strands of the 395 kb of putative promoter sequences. The average number of each type of cis-acting regulatory elements from each class of genes was calculated. Because some promoter regions have many copies of one type of cis-acting regulatory element, we further categorized elements found in two or more copies per gene, only one copy per gene, or absent. Elements found in significantly different proportions between treatments are shown in Table IV  

Table IV.

Summary of selected cis-acting regulatory elements located on putative promoter sequences (i.e. within 1,000 bp in the 5′ direction of the ATG translation start site) of rice pseudomolecules


 

 

High RT/RMIa  

Low RT/RMI

High RT/AG

Low RT/AG

pSHR
No. of tested clones 153 24 148 31 39
Total promoter length (bp) 153,000 24,000 148,000 31,000 39,000
No. of cis-elementsb 27,245 4,340 26,797 5,521 7,082
Pyrimidine box (CCTTTT) Total (%)c 64.7 ± 7.6d 37.5 ± 19.4 54.7 ± 8.0 54.8 ± 17.5 43.6 ± 15.6
Two or more (%)e 24.8 8.3 21.6 32.3 23.1
One (%)f 39.9 29.2 33.1 22.6 20.5
NC II box (ATAGAA) Total (%) 52.3 ± 7.9 37.5 ± 19.4 46.6 ± 8.0 41.9 ± 17.4 66.7 ± 14.8
Two or more (%) 22.9 20.8 10.8 6.5 20.5
One (%) 29.4 16.7 35.8 35.5 46.2
RY repeat box (CATGCA) Total (%) 42.5 ± 7.8 33.3 ± 18.9 37.8 ± 7.8 32.3 ± 16.5 51.3 ± 15.7
Two or more (%) 17.6 16.7 14.2 12.9 20.5
One (%) 24.8 16.7 23.6 19.4 30.8
CArG box (CWWWWWWWWG) Total (%) 47.7 ± 7.9 45.8 ± 19.9 46.6 ± 8.0 22.6 ± 14.7 43.6 ± 15.6
Two or more (%) 20.9 20.8 14.9 3.2 20.5
One (%) 26.8 25.0 31.8 19.4 23.1
GARE box (TAACAAR) Total (%) 28.8 ± 7.2 41.7 ± 19.7 25.1 ± 7.7 32.3 ± 16.5 23.1 ± 13.2
Two or more (%) 8.5 8.3 7.4 0.0 2.6
One (%) 20.3 33.3 27.7 32.3 20.5
TATCCA box (TATCCA) Total (%) 44.4 ± 7.9 29.2 ± 18.2 38.5 ± 7.8 48.4 ± 17.6 35.9 ± 15.1
Two or more (%) 11.1 0.0 9.5 9.7 12.8
One (%) 33.3 29.2 29.1 38.7 23.1
I box (GATAAG) Total (%) 41.2 ± 7.8 25.0 ± 17.3 41.9 ± 7.9 41.9 ± 17.4 43.6 ± 15.6
Two or more (%) 12.4 8.3 9.5 3.2 10.3
One (%) 28.8 16.7 32.4 38.7 33.3
CAREs box (CAACTC) Total (%) 37.9 ± 7.7 33.3 ± 18.9 46.6 ± 8.0 29.0 ± 16.0 41.0 ± 15.4
Two or more (%) 9.8 4.2 9.5 3.2 15.4

One (%)
28.1
29.2
37.2
25.8
25.6

 

 

High RT/RMIa  

Low RT/RMI

High RT/AG

Low RT/AG

pSHR
No. of tested clones 153 24 148 31 39
Total promoter length (bp) 153,000 24,000 148,000 31,000 39,000
No. of cis-elementsb 27,245 4,340 26,797 5,521 7,082
Pyrimidine box (CCTTTT) Total (%)c 64.7 ± 7.6d 37.5 ± 19.4 54.7 ± 8.0 54.8 ± 17.5 43.6 ± 15.6
Two or more (%)e 24.8 8.3 21.6 32.3 23.1
One (%)f 39.9 29.2 33.1 22.6 20.5
NC II box (ATAGAA) Total (%) 52.3 ± 7.9 37.5 ± 19.4 46.6 ± 8.0 41.9 ± 17.4 66.7 ± 14.8
Two or more (%) 22.9 20.8 10.8 6.5 20.5
One (%) 29.4 16.7 35.8 35.5 46.2
RY repeat box (CATGCA) Total (%) 42.5 ± 7.8 33.3 ± 18.9 37.8 ± 7.8 32.3 ± 16.5 51.3 ± 15.7
Two or more (%) 17.6 16.7 14.2 12.9 20.5
One (%) 24.8 16.7 23.6 19.4 30.8
CArG box (CWWWWWWWWG) Total (%) 47.7 ± 7.9 45.8 ± 19.9 46.6 ± 8.0 22.6 ± 14.7 43.6 ± 15.6
Two or more (%) 20.9 20.8 14.9 3.2 20.5
One (%) 26.8 25.0 31.8 19.4 23.1
GARE box (TAACAAR) Total (%) 28.8 ± 7.2 41.7 ± 19.7 25.1 ± 7.7 32.3 ± 16.5 23.1 ± 13.2
Two or more (%) 8.5 8.3 7.4 0.0 2.6
One (%) 20.3 33.3 27.7 32.3 20.5
TATCCA box (TATCCA) Total (%) 44.4 ± 7.9 29.2 ± 18.2 38.5 ± 7.8 48.4 ± 17.6 35.9 ± 15.1
Two or more (%) 11.1 0.0 9.5 9.7 12.8
One (%) 33.3 29.2 29.1 38.7 23.1
I box (GATAAG) Total (%) 41.2 ± 7.8 25.0 ± 17.3 41.9 ± 7.9 41.9 ± 17.4 43.6 ± 15.6
Two or more (%) 12.4 8.3 9.5 3.2 10.3
One (%) 28.8 16.7 32.4 38.7 33.3
CAREs box (CAACTC) Total (%) 37.9 ± 7.7 33.3 ± 18.9 46.6 ± 8.0 29.0 ± 16.0 41.0 ± 15.4
Two or more (%) 9.8 4.2 9.5 3.2 15.4

One (%)
28.1
29.2
37.2
25.8
25.6
a

Each of 31 clones with high RT/RMI as well as high RT/AG was assigned as each of both ratios.

b

Total number of cis-acting regulatory elements from both strands of rice pseudomolecules.

c

Percentage of the indicated element family found per putative promoter region.

d

The range about the average indicates 95% confidence limits for P.

e

Percentage of promoter regions in which two or more copies of the element were found.

f

Percentage of promoter regions in which only a single copy of the element was found.

Table IV.

Summary of selected cis-acting regulatory elements located on putative promoter sequences (i.e. within 1,000 bp in the 5′ direction of the ATG translation start site) of rice pseudomolecules


 

 

High RT/RMIa  

Low RT/RMI

High RT/AG

Low RT/AG

pSHR
No. of tested clones 153 24 148 31 39
Total promoter length (bp) 153,000 24,000 148,000 31,000 39,000
No. of cis-elementsb 27,245 4,340 26,797 5,521 7,082
Pyrimidine box (CCTTTT) Total (%)c 64.7 ± 7.6d 37.5 ± 19.4 54.7 ± 8.0 54.8 ± 17.5 43.6 ± 15.6
Two or more (%)e 24.8 8.3 21.6 32.3 23.1
One (%)f 39.9 29.2 33.1 22.6 20.5
NC II box (ATAGAA) Total (%) 52.3 ± 7.9 37.5 ± 19.4 46.6 ± 8.0 41.9 ± 17.4 66.7 ± 14.8
Two or more (%) 22.9 20.8 10.8 6.5 20.5
One (%) 29.4 16.7 35.8 35.5 46.2
RY repeat box (CATGCA) Total (%) 42.5 ± 7.8 33.3 ± 18.9 37.8 ± 7.8 32.3 ± 16.5 51.3 ± 15.7
Two or more (%) 17.6 16.7 14.2 12.9 20.5
One (%) 24.8 16.7 23.6 19.4 30.8
CArG box (CWWWWWWWWG) Total (%) 47.7 ± 7.9 45.8 ± 19.9 46.6 ± 8.0 22.6 ± 14.7 43.6 ± 15.6
Two or more (%) 20.9 20.8 14.9 3.2 20.5
One (%) 26.8 25.0 31.8 19.4 23.1
GARE box (TAACAAR) Total (%) 28.8 ± 7.2 41.7 ± 19.7 25.1 ± 7.7 32.3 ± 16.5 23.1 ± 13.2
Two or more (%) 8.5 8.3 7.4 0.0 2.6
One (%) 20.3 33.3 27.7 32.3 20.5
TATCCA box (TATCCA) Total (%) 44.4 ± 7.9 29.2 ± 18.2 38.5 ± 7.8 48.4 ± 17.6 35.9 ± 15.1
Two or more (%) 11.1 0.0 9.5 9.7 12.8
One (%) 33.3 29.2 29.1 38.7 23.1
I box (GATAAG) Total (%) 41.2 ± 7.8 25.0 ± 17.3 41.9 ± 7.9 41.9 ± 17.4 43.6 ± 15.6
Two or more (%) 12.4 8.3 9.5 3.2 10.3
One (%) 28.8 16.7 32.4 38.7 33.3
CAREs box (CAACTC) Total (%) 37.9 ± 7.7 33.3 ± 18.9 46.6 ± 8.0 29.0 ± 16.0 41.0 ± 15.4
Two or more (%) 9.8 4.2 9.5 3.2 15.4

One (%)
28.1
29.2
37.2
25.8
25.6

 

 

High RT/RMIa  

Low RT/RMI

High RT/AG

Low RT/AG

pSHR
No. of tested clones 153 24 148 31 39
Total promoter length (bp) 153,000 24,000 148,000 31,000 39,000
No. of cis-elementsb 27,245 4,340 26,797 5,521 7,082
Pyrimidine box (CCTTTT) Total (%)c 64.7 ± 7.6d 37.5 ± 19.4 54.7 ± 8.0 54.8 ± 17.5 43.6 ± 15.6
Two or more (%)e 24.8 8.3 21.6 32.3 23.1
One (%)f 39.9 29.2 33.1 22.6 20.5
NC II box (ATAGAA) Total (%) 52.3 ± 7.9 37.5 ± 19.4 46.6 ± 8.0 41.9 ± 17.4 66.7 ± 14.8
Two or more (%) 22.9 20.8 10.8 6.5 20.5
One (%) 29.4 16.7 35.8 35.5 46.2
RY repeat box (CATGCA) Total (%) 42.5 ± 7.8 33.3 ± 18.9 37.8 ± 7.8 32.3 ± 16.5 51.3 ± 15.7
Two or more (%) 17.6 16.7 14.2 12.9 20.5
One (%) 24.8 16.7 23.6 19.4 30.8
CArG box (CWWWWWWWWG) Total (%) 47.7 ± 7.9 45.8 ± 19.9 46.6 ± 8.0 22.6 ± 14.7 43.6 ± 15.6
Two or more (%) 20.9 20.8 14.9 3.2 20.5
One (%) 26.8 25.0 31.8 19.4 23.1
GARE box (TAACAAR) Total (%) 28.8 ± 7.2 41.7 ± 19.7 25.1 ± 7.7 32.3 ± 16.5 23.1 ± 13.2
Two or more (%) 8.5 8.3 7.4 0.0 2.6
One (%) 20.3 33.3 27.7 32.3 20.5
TATCCA box (TATCCA) Total (%) 44.4 ± 7.9 29.2 ± 18.2 38.5 ± 7.8 48.4 ± 17.6 35.9 ± 15.1
Two or more (%) 11.1 0.0 9.5 9.7 12.8
One (%) 33.3 29.2 29.1 38.7 23.1
I box (GATAAG) Total (%) 41.2 ± 7.8 25.0 ± 17.3 41.9 ± 7.9 41.9 ± 17.4 43.6 ± 15.6
Two or more (%) 12.4 8.3 9.5 3.2 10.3
One (%) 28.8 16.7 32.4 38.7 33.3
CAREs box (CAACTC) Total (%) 37.9 ± 7.7 33.3 ± 18.9 46.6 ± 8.0 29.0 ± 16.0 41.0 ± 15.4
Two or more (%) 9.8 4.2 9.5 3.2 15.4

One (%)
28.1
29.2
37.2
25.8
25.6
a

Each of 31 clones with high RT/RMI as well as high RT/AG was assigned as each of both ratios.

b

Total number of cis-acting regulatory elements from both strands of rice pseudomolecules.

c

Percentage of the indicated element family found per putative promoter region.

d

The range about the average indicates 95% confidence limits for P.

e

Percentage of promoter regions in which two or more copies of the element were found.

f

Percentage of promoter regions in which only a single copy of the element was found.

.

Three cis-acting regulatory elements, the pyrimidine box (CCTTTT), the TATCCA box (TATCCA), and the I box (GATAAG), showed significantly higher abundance in high RT/RMI than low RT/RMI. In particular, the pyrimidine box (Mena et al., 2002), an element of a tripartite GA-responsive complex (GARC), was much more abundant in the promoters of high RT/RMI (64.7%) than low RT/RMI (37.5%) genes. In contrast, the GA-responsive element (TAACAAR) was higher in low RT/RMI.

In the comparison of high and low RT/AG, two cis-acting regulatory elements, CArG motif-binding MADS domain proteins (Tang and Perry, 2003) and CAACTC regulatory element (a novel GAREGARE; Sutoh and Yamauchi, 2003), were found at higher percentages (both 46.6%) in high RT/AG.

The promoters of pSHR genes were enriched relative to the other gene sets for two cis-elements, NC II known as a plastid atpB gene promoter (Kapoor and Sugiura, 1999), and RY repeat element found in the RY/G box, a complex containing the two RY repeats and the G box of the Brassica napus napin promoter (Ezcurra et al., 2000).

Relationship of Rhizome-Enriched Genes to QTLs for Rhizomatousness and Ratooning

The proximity of genes with rhizome-enriched expression to QTLs that explain genetic variation in rhizomatousness provides one means by which to prioritize candidates for further study. Using genetic markers previously described (Hu et al., 2003), we aligned 21 sorghum QTLs in 13 nonoverlapping regions (Paterson et al., 1995) with the rice pseudomolecules. Eight of these sorghum QTL regions correspond to eight of the 12 rice QTLs for rhizomatousness (Hu et al., 2003). (One case of apparent correspondence between rice QRl7 and a sorghum QTL, reported by Hu et al. [2003], no longer shows correspondence based on improvements to both the sorghum map and the rice sequence.) Similarly, among 11 previously reported QTLs influencing rice ratooning ability (RAAB; Tan et al., 1997; Ishimaru et al., 2001; Cai and Morishima, 2002) or main stem and tiller regeneration after cutting, six and four showed overlap with rhizomatousness QTLs of sorghum and rice, respectively. Of special interest is the rice chromosome 6 location of QTL AQF082 that clearly shows alignment with both the interval corresponding to the sorghum regrowth trait and the tiller number trait included in the rice QRi6 locus.

A comprehensive assessment (Supplemental Table S4) shows highly expressed rhizome genes to be slightly enriched in the rice rhizome QTL likelihood intervals of Hu et al. (2003), with a total of 29 (6.4%) high RT/RMI and/or RT/AG genes versus three (3.7%) of the low expression ratio genes being located within the QTL likelihood intervals. Highly expressed rhizome genes were also somewhat enriched in the RAAB QTL regions, with 28 (8.5%) high RT/RMI and/or high RT/AG and three (3.7%) low ratio selected clones found in 10 of the 11 inferred intervals. The Hu et al. (2003) intervals and RAAB intervals also contained two (4.3%) and eight (17.4%) pSHR-related sequences, respectively.

Of special interest are cases in which genes that were differentially expressed in rhizomes also mapped to QTL likelihood intervals. Two of the five annotated candidates with the greatest RT/RMI ratios could be associated with QTL intervals. The putative oligosaccharyl transferase identified as c083, showing the highest relative expression ratios in both RT/RMI (6.66) and RT/AG (8.48), failed to map to The Institute for Genomic Research (TIGR) release 2 pseudomolecules but could be located to the QRn5 likelihood interval using TIGR release 3 rice assembly. c087, with a RT/RMI ratio of 2.70 and a high RT/AG ratio of 2.59, maps to the rice chromosome 4 RAAB AQDK002 locus with correspondence to sorghum QTLs for rhizomatousness, seedling tillers, and regrowth traits. Among the five clones with the highest RT/AG ratios, three located to rhizomatous QTL intervals, including c083 as described above. Candidate s036, with RT/AG expression ratio of 3.38 and encoding a putative monosaccharide transporter, locates to the rice Rhiz3 QTL likelihood interval on rice chromosome 4 and corresponding sorghum LG-D (chromosome 6) QTLs affecting subterranean rhizomatousness, regrowth, and seedling tillers. The comparative map infers that s125, a putative AER-encoding gene, is also found within this sorghum LG-D/chromosome 6 QTL interval.

An interesting candidate not shown in Supplemental Table S2 because of its more moderate (1.76) RT/RMI expression ratio is c272, which gave a best BLASTx match to the maize and wheat (Triticum aestivum) GAI gene orthologs. The best hit location on the rice chromosome 3 pseudomolecule, between markers ORS31 and RM55, does not show clear association with any rhizome trait QTL; however, the second best hit was located within the QRl1 locus (rhizome length traits) and the corresponding sorghum QTL for regrowth.

Paleohomeologs of Ancient Duplication

The discovery that rice is a paleopolyploid (Paterson et al., 2003, 2004) raises the question of whether ancient correspondence in the locations of rhizomatousness QTLs might be found. Such correspondence may perhaps represent single genes with important functions or represent clusters of genes with related functions that have undergone independent but convergent mutations to account for genetic variation in sorghum and rice, respectively.

We found correspondence between rice QTLs located on ancient duplicated segments of rice chromosomes 2 and 4 and rice chromosomes 2 and 6, together with the corresponding regions of the sorghum genome (Fig. 2  
Figure 2.

Ancient correspondence between rice paleohomeologous regions associated with rhizomatousness, tillering, and/or ratooning QTLs in rice and/or sorghum. Duplicated rice chromosomal regions were identified by synteny between protein-encoding genes reported by Paterson et al. (2004). For genetic marker positions, see “Materials and Methods” or Figure 1.

). In the first case, the rice QRbn2 QTL for rhizome number per plant on chromosome 2 and a region on chromosome 4 affecting several measures of rhizomatousness, as well as tillering and ratooning ability, correspond closely to one another and also to sorghum QTLs for regrowth on sorghum chromosome 4, and regrowth, seedling tillers, and rhizomatousness on sorghum chromosome 6. Additional supporting evidence that this region harbors a conserved gene(s) responsible for tillering is provided by Feltus et al. (2006), who reported a significant correspondence probability for overlap of tillering QTLs between a sorghum interspecific and intraspecific population, as well as alignment with the maize chromosome 10 QTL interval for looseness of tillers (Westerbergh and Doebley, 2004).

Whereas the central region of rice chromosome 2 is related by ancient duplication with rice chromosome 4, its more terminal region is related to the central region of rice chromosome 6 and to corresponding regions of sorghum LG-F (chromosome 4) and LG-I (chromosome 10). In the upper part of the chromosome (Fig. 2), the sorghum LG-I (chromosome 10) QTL intervals for rhizomatousness and regrowth correspond very closely to the rice chromosome 6 QRi6 and RAAB AQF082 loci. In turn, these correspond to a rice QTL for rhizome dry weight (Qrdw2) and to a sorghum LG-F (chromosome 4) rhizomatousness QTL. In the lower part of the chromosome, correspondence is found between the rice chromosome 6 RAAB CQE43 locus and the sorghum LG-F (chromosome 4) QTL interval for the regrowth trait. Because sorghum LG-I (chromosome 10) appears to bridge a rearrangement shared by rice chromosome 2 and sorghum LG-F (chromosome 4), there is also a tenuous association of the lower end of the chromosome with the sorghum LG-I (chromosome 10) rhizomatousness and regrowth QTL intervals.

DISCUSSION

We have screened the Sorghum transcriptome for genes that are differentially expressed in rhizomes, and explored their functional categorization, genomic organization, regulatory motifs, and association with QTLs conferring rhizomatousness. The relative lack of information about the rhizotranscriptome is reflected in the high abundance of rhizome-expressed genes with unknown function or no match in GenBank, especially in genes of relatively low expression levels (such as the 2,616 randomly sampled genes). We identified specific genes and motifs, general pathways, and exogenous regulatory agents that warrant further investigation as mechanisms by which to enhance turf and forage grasses and control noxious weeds, through either genetic approaches or application of exogenous growth regulators.

While gene expression patterns in the two distinct regions of the rhizome that we studied were similar in many cases, expression levels in RT more closely resembled aboveground plant parts than did those of RMI. This was consistent with our expectation, in that RMI is largely a storage organ while RT and AG are actively growing.

The finding that genes with rhizome-enriched expression are distributed across a wide range of functional categories suggests some degree of specialization of individual members of many gene families, perhaps in concert with ancient duplication of the transcriptome (Paterson et al., 2003, 2004) followed by subfunctionalization of expression patterns (Adams et al., 2003). This may explain some of the apparent incongruities with existing data. For example, contig382, a putative lipid transfer protein, showed high relative expression ratios of 1.90 (RT/RMI) and 2.85 (RT/AG) in the rhizomes. While lipid transfer proteins had previously been reported to be expressed predominantly in aerial tissues, other members of this small multigene family are likely to have different functions in plants (Kader, 1996). Further exploration of the rhizome, an organ that is common to many wild plants but is usually absent from well-studied row crops, may reveal functions of an appreciable number of previously cryptic plant genes.

Developmental and environmental responses of aerial and subterranean plant tissues differ in the types and/or levels of hormones and signaling proteins involved. Enrichment of the RT/AG set for genes implicated in secondary and hormone metabolism is consistent with this expectation. Similarly, the statistically significant abundance of abiotic stimuli and development genes in high RT/RMI and high RT/AG sets is consistent with the different developmental states of the respective tissues and need for response to distinctively different (aerial versus subterranean) environmental cues.

One way to prioritize rhizome-enriched candidates for further studies aimed at identifying the genetic factors determining rhizomatousness would be to select those mapping near QTLs. Building on prior evidence of correspondence between QTLs influencing rhizomatousness of rice and sorghum (Hu et al., 2003), the correspondence that we report here with RAAB (main stem and tiller regeneration after cutting; Tan et al., 1997; Ishimaru et al., 2001; Cai and Morishima, 2002), together with a report on QTLs influencing perenniality in wild relatives of maize (Westerbergh and Doebley, 2004), lend further support to cross-taxon correspondence in the genetic control of rhizomatousness.

While we recognize the hazards of building functional hypotheses based on candidate gene studies, a few such hypotheses of special merit are suggested. For instance, the Rhz3 interval between RM119 and RM274 harbors at least 201 rhizome EST-verified genes (Supplemental Table S4). Three of these were among the genes with most highly enriched rhizome expression: a monosaccharide transporter (high RT/AG), porphyromonas-type peptidyl-Arg deiminase family protein (PPAD; high RT/AG), and β-keto acyl reductase (high RT/RMI). Monosaccharide transporters with six transmembrane domains, which have transport activity for some monosaccharides in an energy-dependent manner, were predominantly expressed in the sclerenchyma and xylem cells in young rice roots (Toyofuku et al., 2000). Enhanced activity of monosaccharide transporters in rhizomes might be important to cell wall formation as well as to providing a carbon source for reserve carbohydrates. Other roles of monosaccharide transporters have been related to senescence pathways in aerial tissues (Quirino et al., 2001) and may prove relevant to the perennial nature of rhizomes. Little is known of the functions of PPAD in plants. The related PAD from Porphyromonas gingivalis catalyzes the deimination of the guanidino group of carboxyl-terminal Arg residues on a variety of peptides to yield ammonia and a citrulline residue (McGraw et al., 1999). Further study is necessary to elucidate the catalytic role(s) of PPAD in plant RT, if any. The β-keto acyl reductase, one component of acyl-CoA elongase, is involved in fatty acid elongation, especially synthesis of suberin monomers with chain lengths up to C26, in the cuticular wax biosynthetic pathway (Xu et al., 2002). The activity of acyl-CoA elongase showed the highest activity in maize root tips but significantly decreased along the length of roots because new apoplastic cell wall spaces were necessary to be modified by the incorporation of biopolymer suberin (Schreiber et al., 2005). Our finding that c279, putatively encoding a β-keto acyl reductase, was enriched in RT relative to mature rhizomes (RT/RMI of 1.87) was consistent with previous maize data. While much work remains to identify the specific gene(s) responsible for Rhz3, monosaccharide transporters and β-keto acyl reductase stand as interesting candidates worthy of further study.

Another case worthy of further study is c083, encoding a putative oligosaccharyl transferase with the highest degree of rhizome-specific expression (both RT/AG and RT/RMI) among all genes studied and located near QRn5, which contributes to rhizome length and number, rhizome branching, and rhizome internode number and length.

The c173 sequence, a putative a 60S ribosomal protein L17, mapped to the QRn10 locus accounting for variation in rice rhizome number, internode number, dry weight, and length, and sorghum rhizome number, rhizomatousness, and seedling tillers (Fig. 1). The second best BLASTn hit (data not shown) locates c173 to rice chromosome 3, in a region that aligns with a sorghum QTL for height of the main culm and tillers (Lin et al., 1995). Differential production of transcripts in plant tissues has been reported for ribosomal subunit proteins (Gao et al., 1994), and their silencing can delay development and stunt and inhibit lateral root growth (Popescu and Tumer, 2004). This information, in combination with the paleohomeolog and phenotypic relationships and its high RT/RMI expression value, provides good reason to further investigate c173.

Correspondence of QTL locations between ancient duplicated chromosomal segments in both rice and sorghum suggests that the functions of key determinants of genetic variation in rhizomatousness may have been conserved over long periods of time. Most, if not all, cereal crops shared a common paleopolyploid ancestor perhaps 70 million years ago (e.g. Paterson et al., 2004), with sorghum diverging from rice perhaps 41 to 47 million years ago. We refine previously known correspondence between sorghum and rice QTLs affecting rhizomatousness (Hu et al., 2003), extending this correspondence to six of the 11 rice ratooning QTLs (Tan et al., 1997; Ishimaru et al., 2001; Cai and Morishima, 2002) and revealing the subset of cases that are further supported by the modern descendants of paleoduplicated chromosomal segments. While it remains unknown whether these correspondences represent single genes that have independently evolved polymorphisms in rice and sorghum or clusters of functionally related genes in which polymorphisms in different members may account for phenotypic variation, this information provides still additional clues to support identification of genes playing direct roles in rhizomatousness.

Several lines of evidence pointed to GAs as probable key regulators of rhizome gene expression and development. Rhizomes develop from axillary buds at the lowermost nodes of the erect leafy shoot of the plant. Although auxin is recognized as an inhibitor of lateral bud growth, Chatfield et al. (2000) suggested that cytokinin may act independently as a key hormone for regulation of initiation and early outgrowth of axillary buds, such as those leading to rhizomes. After early outgrowth, however, elongation of rhizomes could be largely dependent upon GAs (Richards et al., 2001). Three cis-acting regulatory elements related to GA responses, the pyrimidine box, the TATCCA box, and the CAREs box, all were enriched in abundance in the 5′ upstream regions of high RT/RMI or high RT/AG genes. Together, these three elements compose the conserved cis-element GARC required for GA induction. Although it is most often found to be tripartite, there are variations of GARC (Gubler and Jacobsen, 1992). Mena et al. (2002) reported that the BPBF protein, a transcription factor of DOF (DNA-binding with one finger) up-regulated by GA treatment, binds specifically to the pyrimidine-box motif (CCTTTT). Their results showed that the DOF class of transcription factors was not only an activator of reserve protein-encoding genes during development but also played a part in the control of postgermination hydrolase genes. We found the 1-kb upstream sequences of the putative orthologs of eight high RT/RMI selections (c016, c027, c261, c263, c275, s045, s147, s168, s192, s207) to encode variations of a tripartite GARC. Mapping within sorghum QTL intervals characterized by all five measured traits were the four genes functionally categorized as a superoxide dismutase, a ripening-regulated protein, a CTP synthase, and an unknown protein. A fifth gene with the tripartite GARC, mapped to a rice chromosome 4 ratooning QTL and putatively encodes a PAZ/piwi domain-containing protein that belongs to the Argonaute protein family. Members of this family are reported to act in posttranscriptional gene silencing and have been shown to be crucial to plant development (Vauchere et al., 2004). Another gene shown to be under GA regulation and exhibiting tissue specificity is cathepsin B-like Cys proteinase (Martinez et al., 2003), putatively encoded by c136 that was among both the highest RT/RMI and RT/AG genes.

Members of the GRAS gene family, GAI/RGA and orthologs, play major roles in signaling of GAs. GAI/RGA are probably best known for their influence on stem elongation, a feature brought to the forefront by the dwarfed, high grain-yielding Green Revolution wheat varieties (Peng et al., 1999). In Arabidopsis, the GAI/RGA gene may function as a negative signal pathway of GA responses (Peng et al., 1997; Silverstone et al., 1998), repressing GA-mediated growth response in GA deficiency but derepressing with binding of GAs to GAI and RGI to result in GA-mediated plant growth (Richards et al., 2001). If the altered structure of the gai mutant protein prevents binding to GAs but still represses GA-mediated growth responses, then the gai protein could constitutively repress plant growth (Richards et al., 2001). We found one contig that closely matched the Os-GRAS-17 gene (subfamily LISCL). The second best hit, corresponding to the Os-GRAS-1 gene (Tian et al., 2004), falls within the QRl1 locus affecting rice rhizome length and rhizome internode length and corresponding to regions influencing sorghum regrowth, panicle length, and spikelet number (Lin et al., 1995). Expression was enriched in RT relative to RMI. The GAI ortholog located near QRl1 is thus an attractive candidate to explore as a potential determinant of rhizome length.

Our cis-element analysis also revealed significant differences between high and low RT/AG genes for the CArG box, a DNA-binding domain recognized by MADS proteins. The MADS genes encode a family of transcription factors with well-described roles in floral development. More recent attention has been given to the expression and effect of this class of genes on angiosperm vegetative tissues. Strong correlations between gene cladistic assignment, expression patterns, and functions have been found for MADS-box genes (for review, see Becker and Theissen, 2003). A few MADS-box genes that may be relevant to the rhizome would be STMADS11-like, ANR1 clade, and TM3-like. For example, ANR1 MADS-box genes regulate lateral root growth and architecture in response to nutritional cues (Gan et al., 2005). Kim et al. (2002) proposed that expression in sweet potato (Ipomoea batatas) of IbMADS3 and IbMADS4, new members of the STMADS clade, might increase both the proliferative potential of vegetative tissues as well as facilitate tuber initiation. As rhizomes are also diageotropic, it is also interesting that a MADS-box AGL20 gene was uncovered as a gravity-regulated gene (Moseyko et al., 2002). Although we did not isolate putative MADS-box genes themselves, the significantly higher occurrence of genes with the cis-regulatory DNA-binding site for MADS-box proteins in our high RT/AG versus the low RT/AG selections suggests that they may be important regulators of rhizomatous traits.

In closing, the expression patterns, physical localizations, relationship to rhizome QTLs between two species, and putative cis-acting regulatory elements of rhizome-enriched genes in sorghum provide clues to shed further light on the identities of rhizome-specific genes.

MATERIALS AND METHODS

cDNA Library Construction and Manipulation

Apical tips (terminal 2–3 cm) were dissected from freshly dug rhizomes of naturalized Sorghum halepense and field-sown Sorghum propinquum plants and immediately frozen in liquid nitrogen. Total RNA was extracted using ice-cold RNA extraction buffer containing 200 mm Tris-HCl, pH 8.5, 1.5% SDS, 300 mm LiCl, 10 mm dithiothreitol, 5 mm thiourea, and 1 mm aurintricarboxylic acid. mRNAs were isolated using the PolyATract mRNA isolation system (Promega). cDNA from S. halepense and S. propinquum was cloned into the Uni-ZAP XR vector (pSH library) and lambda ZAP II vector (pSP library), respectively, according to the manufacturer's instructions (Stratagene), as described in further detail separately (Pratt et al., 2005). Mass excision of pBluescript phagemid from the lambda ZAP II vector was performed using ExAssist helper phage with the SOLR strain of Escherichia coli according to the manufacturer's instructions (Stratagene). For each library, 18,432 colonies were picked by QBot (Genetix) and stored in 48 384-well microtiter plates.

Preparation and Hybridization of Macroarrays

Each library was double-spot inoculated in a 2 × 2 grid pattern by a QBot (Genetix) on 22.5- × 22.5-cm nylon Hybond N+ membranes (Amersham Biosciences). Individual membranes contained 4,608 clones (i.e. clones from 12 384-well plates) with six replicates made for each of the four membranes representing a complete library. Membranes were placed on Q-trays (Genetix) containing Luria-Bertani broth with 1.5% agarose and 50 μg/mL ampicillin, incubated for 18 h at 37°C, and then subjected to alkaline lysis fixation (Nizetic et al., 1991).

Three mRNA sources were studied: the apical 2 to 3 cm of RT, RMI, and AG from S. halepense. mRNAs were extracted as described above from each tissue, quantified by spectrophotometry, and 10 μg labeled using SuperScript II (Invitrogen) with 1 μg of oligo(dT)12-18 and 32P-dCTP at 6,000 Ci/mmol (Amersham) according to the manufacturer's protocol. Labeled first-strand cDNA was purified using Sephadex G-50 beads (Sigma-Aldrich) and assayed by a scintillation counter for specific activity. Membranes were prehybridized for 1 h and hybridized in a solution of 35 mL containing 0.5 m sodium phosphate, pH 7.2, 7% SDS, 1 mm EDTA, and 1% (w/v) bovine serum albumin (Church and Gilbert, 1984) at 65°C for 20 to 22 h. Hybridized membranes were washed twice with 0.25× SSPE and 0.25% SDS at 65°C and 12 rpm for 30 min, followed by a brief rinse with 2× SSC. Washed membranes were placed into phosphorimager cassettes and exposed for 20 h. After data acquisition, membranes were stripped of bound targets by immersion in a boiling 0.5% SDS solution, followed by 5 min of vigorous shaking.

Scoring Image Analysis

Exposed screens were scanned and signal intensity for each clone recorded by a STORM 820 PhosphorImager. Individual signal intensities as determined by ImageQuant software (Molecular Dynamics) reflect that of the clone and filter background resulting from aligning a 96 × 96 grid on the imaged filter such that each spot occurs within one square. Signal from each probe was subsequently normalized by dividing each individual signal by the average of the field in which each square was located (a field equals one-sixth of the entire filter area, or 1,536 clones). Normalized signal for each clone was averaged with its duplicate on the same filter, then averaged again with an additional two signal values for the same clone from a replicate hybridization using an independent mRNA extraction, labeling, and hybridization. Thus, the expression level of a given clone is based on the average of four signal values per tissue source, including both technical and biological replicates.

DNA Sequencing and Contig Assembly

Clones selected on the basis of differential expression ratios (as described in text) were rearrayed into 96-well microtiter plates. Deep 96-well plates containing 1,300 μL of Luria-Bertani broth with 50 μg/mL ampicillin per well were inoculated and grown for 20 h at 37°C and 200 rpm. Plasmids were extracted using an alkaline lysis method (Marra et al., 1997) modified for the 96-well format. Sequencing reactions were performed using the ABI PRISM BigDye Terminator cycle sequencing kit (version 3.1; Applied Biosystems). Reactions were set up in 96-well PCR plates with each reaction containing 0.665 μL of DMSO, 1.33 μL of 5× buffer, 26 pm oligoprimer (forward sequence 5′-TGTAAAACGACGGCCAGT-3′; reverse complement sequence by a modified M13 primer 5′-CAGGAAACAGCTATGACC-3′), 0.68 μL of BigDye, and 4.5 μL of template DNA. Cycle sequencing used a PTC225 thermocycler (MJ Research) programmed as: 5 min preheat at 94°C followed by 75 cycles of 94°C, denature for 20 s, 50°C annealing for 5 s, 60°C extension for 4 min, with a final hold at 4°C. Preparation of extension products was according to manufacturer's instructions (Applied Biosystems), followed by passage though Sephadex filter plates (Krakowski et al., 1995) into MicroAmp Optical 96-well plates (Applied Biosystems). High-throughput sequencing was achieved using an ABI 3730 automated DNA analyzer (Applied Biosystems). Trace files were processed using phred, followed by phrap assembly into contigs by clustering a minimum continuous 100 bp with phred score >20 (Ewing and Green, 1998; Ewing et al., 1998). Assemblies were viewed and edited with Consed (Gordon et al., 1998).

Comparative Physical Mapping and Genetic Position Predictions

Comparative mapping was carried out by combining the genetic alignment between the Rice-IRRI RD23/Olong F2 QTL 2003 map and rhizomatous sorghum (Sorghum bicolor) genomic regions (Hu et al., 2003) with physical data obtained from TIGR release 2 rice (Oryza sativa) pseudomolecules. Along with 37 sorghum-rice anchor markers, the GenBank accession numbers for 195 genetic markers mapping to either Rice-IRRI RD23/Olong F2 QTL 2003 (for rhizomatous traits) or for RAAB the Rice-JRGP Nip/Kas F2 QTL 2000, Rice-JNIG W1944/Peik QTL 2002, or Rice-IGCN ZYQ18/JX17 DH QTL 1998 populations were obtained through Gramene (Ware et al., 2002) or the National Center for Biotechnology Information (NCBI). Their locations are inferred based on BLASTn-identified pseudomolecule coordinates of available genetic markers. Physical coordinates for markers RM163, RM164, and RM253 were acquired directly from the reported Gramene Rice-GR TIGR Assm IRGSP Seq 2004. BLASTn against the GenBank Sorghum (taxonomy ID 4557) sequence database (downloaded August 28, 2004) was performed for those pSHR clones (as described in text) failing to identify putative homologous loci in the rice pseudomolecules. Sorghum ESTs with the longest sequence and best homology (E < e−25) to the pSHR clones were selected for mapping and further bioinformatics experiments. Physical coordinates on the rice pseudomolecules for the sorghum genetic markers and sorghum sequence queries were identified by the in-house Perl script blast_booster as the best BLASTn hit meeting minimum criteria of 50-bp alignment with 80% identity. Inferred genetic positions of the sorghum clone sequences assumed a linear relationship between genetic and physical distance for intervals defined by two consecutive markers. Named sequences shown mapping to the same position identified coordinates of within 10 kb of one another on the rice pseudomolecule.

Gene Annotation

BLASTx, tBLASTx, and BLASTn were used for sequence similarity searches with the default matrix BLOSUM62 and cutoff E values of 10−10 for BLASTx and tBLASTx and 10−25 for BLASTn. Stand-alone BLASTs were performed against the NCBI plant protein and embryophyta databases (downloaded August 28, 2004). Sequences were manually grouped into 15 functional categories based on putative biochemical and physiological role(s) inferred with the Gene Ontology Consortium database (http://www.geneontology.org) obtained from querying the Perl-based Inter-ProScan Version 3.3 implementation (ftp://ftp.ebi.ac.uk/pub/software/unix/iprscan). The confidence limit for a binomial proportion (P = 95%) was used to evaluate the differences between treatments in frequencies of clones involved in each functional category.

Promoter Analysis

Rice genes showing significant homology (E < e−10) with selected sorghum genes were identified from the rice protein database using BLASTx. The 1-kb regions upstream from the ATG translation start site containing putative promoter sequences were retrieved by either of two methods. Sequence tags of 100 bp immediately downstream from the rice ATG start codon were manually separated and used as BLASTn queries to locate their physical addresses in TIGR release 2 rice pseudomolecules. The adjacent 1-kb sequences upstream of the identified start site were retrieved from the pseudomolecules by an in-house Perl script. For genes in which the downstream 100-bp query tag identified sequences containing introns, the upsteam 1-kb sequence was obtained by searching the TIGR rice genome annotation .1kUpstream site (http://www.tigr.org.tdb/e2kq/osa1/data_download.shtml).

To uncover putative cis-acting regulatory elements located in the promoter regions, the identified 1-kb sequences were submitted for analysis to the PLACE (http://dna.affrc.go.jp/PLACE) database (Higo et al., 1999). The confidence limit for a binomial proportion (P = 95%) was used to evaluate differences between treatments in frequencies between cis-acting regulatory elements.

Sequence data from this article can be found in the GenBank/EMBL data libraries under accession numbers DN551694 to DN551965, DN552280 to DN552796, BQ479097, BQ479098, BQ656181 to BQ656248, and BQ789583 to BQ789587.

Supplemental Data

The following materials are available in the online version of this article.

  • Supplemental Figure S1. More associations between sorghum and rice rhizomatous and ratooning QTLs and candidate differentially expressed ESTs.

  • Supplemental Table S1. Profile of clones selected for enrichment by high RT/RMI ratios.

  • Supplemental Table S2. Profile of clones selected for enrichment by high RT/AG ratios.

  • Supplemental Table S3. Profile of clones selected for low expression in the rhizome tip relative to mature rhizome (low ratio of RT/RMI) and aboveground (low ratio of RT/AG), respectively.

  • Supplemental Table S4. Distribution of rhizome-enriched genes on the rice pseudomolecules.

ACKNOWLEDGMENTS

We thank Dr. Thomas Wicker for providing useful software.

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Author notes

1

This work was supported in part by the U.S. Department of Agriculture Cooperative State Research, Education, and Extension Service National Research Initiative (grant no. 01–35320–10964 to A.H.P. and W.K.V.), the National Science Foundation (grant no. DBI–0115903 to A.H.P.), and the Korean government (MOEHRD, Basic Research Promotion Fund; Korea Research Foundation grant no. KRF–2004–214–M01–2004–000–10060–0 to C.S.J.).

2

These authors contributed equally to the paper.

3

Present address: Institute of Life Science and Natural Resources, Korea University, Anam-Dong, Seongbuk-Gu, Seoul 136–713, Korea.

*

Corresponding author; e-mail paterson@uga.edu; fax 706–583–0160.

The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Andrew H. Paterson (paterson@uga.edu).

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