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ESCRT regulates surface expression of the Kir2.1 potassium channel

The Kir2.1 potassium channel is targeted by endoplasmic reticulum–associated degradation in yeast. To identify other Kir2.1 quality control factors, a novel yeast screen was performed. ESCRT components were among the strongest hits from the screen. Consistent with these data, ESCRT also regulates Kir2.1 stability in human cells.

INTRODUCTION
Protein quality control (PQC) was initially described to reflect the fact that secreted proteins with various defects were unable to exit the endoplasmic reticulum (ER). Specifically, defects in protein glycosylation, folding, or assembly or protein aggregation led to ER retention (Hurtley and Helenius, 1989). More recently, it has become appreciated that PQC operates throughout the eukaryotic secretory pathway to ensure that toxic or misfolded proteins do not accumulate (Arvan et al., 2002;Apaja et al., 2010). In turn, regulated protein degradative systems provide a means to fine tune wild-type protein levels and thus their activities. Therefore even folded and functional proteins may be destroyed if existing levels are toxic or do not match cellular needs. If PQC or the regulated protein degradation system is defective or if the PQC machinery fails to recognize an aberrant protein, one of many human diseases may result (Gestwicki and Garza, 2012;Guerriero and Brodsky, 2012).
As noted, secretory pathway PQC begins in the ER, and proteins that fail to pass this step can be destroyed by ER-associated degradation (ERAD). ERAD substrates are first recognized by molecular chaperones and chaperone-like lectins, which target them for ubiquitination (Aebi et al., 2010;Claessen et al., 2012;Hebert and Molinari, 2012). During ubiquitination, ERAD substrates are retrotranslocated to the cytoplasm and delivered to and degraded by the 26S proteasome (Mehnert et al., 2010;Smith et al., 2011). If the ERAD machinery is overwhelmed or if aberrant proteins accumulate, the unfolded protein response is induced, and in some cases misfolded species can escape and advance to the Golgi. In these circumstances, ERAD substrates are returned to the ER (Vashist et al., 2001;Haynes et al., 2002;Taxis et al., 2002), or in yeast a Golgi quality control system, which is absent in mammalian cells, recognizes and delivers substrates to the vacuole for degradation via the multivesicular body (MVB) pathway (Chang and Fink, 1995;Hong et al., 1996;Spear and Ng, 2003;Wang and Ng, 2010;Coughlan et al.,

Kir2.1 is an ERAD substrate
The Kir2.1 potassium channel most likely encounters multiple PQC checkpoints as it travels through the secretory pathway to the plasma membrane. For example, an ATS-1 disease-causing mutation in the channel, Δ314-315, prevents channel trafficking from the Golgi apparatus to the plasma membrane by virtue of its inability to associate with the AP-1 clathrin-associated adaptor . To gain a more comprehensive understanding of the Kir2.1 biosynthetic trafficking and degradation pathways, we refined a yeast expression system. To this end, a doubly tagged (myc and hemagglutinin [HA]) version of Kir2.1 was expressed under the control of a constitutive promoter. Analysis of Kir2.1 localization by indirect immunofluorescence microscopy primarily showed a perinuclear staining that colocalized with the ER-resident chaperone Kar2 (BiP; Figure  1A). Sucrose gradient centrifugation analysis indicated that a significant amount of Kir2.1 comigrated with Kar2 ( Figure 1B, lanes 1-6). However, a fraction of Kir2.1 also comigrated with the plasma membrane protein Pma1 (lanes 9-11). These data suggest that whereas the majority of Kir2.1 is ER localized, a small pool advances to the plasma membrane. Thus the yeast expression system provides a model to explore PQC steps encountered by Kir2.1 as it travels through the secretory pathway.
Next the involvement of ERAD was assessed. For these studies, Kir2.1 stability was analyzed by cycloheximide chase in wild-type and mutant strains. We found that the channel was rapidly degraded, becoming almost undetectable within 90 min ( Figure 2A). In pdr5Δ yeast, which allows studies with proteasome inhibitors, MG132 partially stabilized Kir2.1 from degradation ( Figure 2A). Further, the AAA-ATPase, Cdc48, which extracts ERAD substrates from this case selected substrates are endocytosed and targeted to the lysosome (Huotari and Helenius, 2011). For example, the diseaseassociated ΔF508 mutant form of the cystic fibrosis transmembrane conductance regulator (CFTR) is an ERAD substrate but is also less stable than wild-type CFTR when delivered to the plasma membrane by low-temperature correction. Genome-and protein-wide screens revealed a significant number of factors required for the disposal of ΔF508 CFTR from the plasma membrane (Trzcinska-Daneluti et al., 2009;Okiyoneda et al., 2010), and for many substrates quality control at the plasma membrane also follows the MVB pathway (Jenness et al., 1997;Arvan et al., 2002;Apaja et al., 2010;Keener and Babst, 2013;Zhao et al., 2013). There are multiple mechanisms to ensure that unwanted secreted proteins are destroyed, but it is generally unclear how these systems cooperate and which pathway might be most important for the PQC of a given substrate.
To begin to investigate these questions, we reengineered and optimized a yeast expression system for the Kir2.1 potassium channel because relatively small changes in the amount of active, plasma membrane-resident Kir2.1 can be detected (Tang et al., 1995;Nakamura and Gaber, 1998;Minor et al., 1999). Like other inward-rectifying potassium channels, Kir2.1 is formed by the tetrameric assembly of identical subunits; each subunit has a potassium selectivity sequence, which is flanked by two transmembrane domains. The N-and C-termini form a large regulatory structure that surrounds the central pore (Schwalbe et al., 2002). Tetrameric Kir2 potassium channels function primarily in heart, skeletal muscle, and neurons and consist of five family members-Kir2.1-2.4 and 2.6 (de Boer et al., 2010;Hibino et al., 2010). Kir2.1 is responsible for controlling membrane excitability in many cell types, especially in heart and skeletal muscle, and lossof-function mutations in Kir2.1 result in Anderson-Tawil syndrome (ATS-1), a disorder characterized by periodic paralysis, long QT ventricular arrhythmias, and skeletomuscular dysplasia (Plaster et al., 2001). Gain-of-function mutations in Kir2.1 lead to short QT syndrome, which can also cause cardiac arrhythmias (Priori et al., 2005). These cases illustrate the importance of maintaining proper Kir2.1 levels. However, the factors necessary to support Kir2.1 trafficking and stability have not been explored in significant detail-hence our desire to identify these components using a systems-level approach.
We discovered that Kir2.1 in yeast traffics to the plasma membrane but resides predominately in the ER, where most of the protein is targeted for ERAD. Maximal Kir2.1 degradation required the AAA-ATPase Cdc48, the ER-associated E3 ubiquitin ligases Hrd1 and Doa10, and the cytoplasmic Hsp70 chaperone Ssa1. Because Kir2.1 supports the growth of trk1Δtrk2Δ yeast on lowpotassium medium (Tang et al., 1995;Nakamura and Gaber, 1998), this system also provided a unique opportunity to identify the spectrum of PQC and trafficking factors necessary to maintain active Kir2.1 at the plasma membrane. Of interest, ERAD-requiring factors were absent from the list of yeast mutants that significantly improved growth on low potassium, suggesting that the level of functional Kir2.1 is not regulated by ERAD. In contrast, most endosomal sorting complex required for transport (ESCRT) components were isolated. These data indicate that the plasma membrane and Golgi quality control systems regulate Kir2.1 residence at the plasma membrane. Consistent with this hypothesis, ESCRT also regulated Kir2.1 residence at the plasma membrane in human cultured cells. Together our results provide the first genomic analysis of the myriad degradative systems that operate on a single protein.  (Roberg et al., 1997). The gradient was fractionated from the top (fraction 1) to the bottom of the tubes (fraction 13). The migration of Kir2.1, the ER chaperone, Kar2/BiP, and the plasma membrane protein Pma1 were evaluated by Western blot analysis.
domains (Plemper et al., 1997;Brodsky et al., 1999;Hill and Cooper, 2000; Figure 2D). These observations suggest that Kir2.1 folds poorly in yeast and is recognized as an ERAD substrate by the cytosolic Hsp70, Ssa1. As described later, Kir2.1 is also targeted for ERAD in mammalian cells.
Nearly all ERAD substrates in yeast are ubiquitinated by the E3 ligases Hrd1 and/ or Doa10 (Claessen et al., 2012). To investigate whether Kir2.1 was degraded in an Hrd1-and/or Doa10-dependent manner, we expressed Kir2.1 in hrd1Δ, doa10Δ, hrd1Δdoa10Δ, and HRD1DOA10 strains. We found that Kir2.1 was stabilized to a similar level when either HRD1 or DOA10 was deleted, and when the genes encoding both E3s were absent, the protein was further stabilized ( Figure 3A). We next asked whether deletion of the E3 ubiquitin ligases led to a decrease in Kir2.1 ubiquitination. Kir2.1 was immunoprecipitated from wildtype or hrd1Δdoa10Δ yeast and ubiquitin levels were examined by immunoblotting. As anticipated, deleting HRD1 and DOA10 led to ∼40% reduction in Kir2.1 ubiquitination ( Figure 3, B and C). Also as anticipated, an analysis of Kir2.1 residence by density centrifugation (see earlier discussion) in the hrd1Δdoa10Δ strain established that the protein accumulated primarily in the ER and to some extent in the Golgi; however, there was no significant increase in the plasma membrane pool, as defined by comigration with Pma1 (Supplemental Figure S1). Because Kir2.1 degradation is Ssa1 dependent (see earlier discussion), we anticipated the requirement for Doa10, which adds ubiquitin onto ERAD substrates with misfolded cytoplasmic domains, that is, ERAD-C substrates (Vashist and Ng, 2004;Carvalho et al., 2006;Denic et al., 2006). The more surprising Hrd1 dependence suggested that Kir2.1 folding defects are also recognized within the membrane (Sato et al., 2009). Thus the Kir2.1 folding lesions in yeast are complex.

A yeast genomic screen identifies regulators of Kir2.1 biogenesis
To identify the spectrum of factors that affect Kir2.1 PQC, we performed a genomic screen. For these studies, we took advantage of the ability of Kir2.1 to rescue the growth of a yeast strain lacking the Trk1 and Trk2 potassium transporters (Tang et al., 1995;Nakamura and Gaber, 1998). A synthetic gene array (SGA) query strain was engineered in which TRK1 and TRK2 were deleted and Kir2.1 was expressed. In low-potassium medium, growth of the strain correlates with Kir2.1 activity (Tang et al., 1995;Nakamura and Gaber, 1998). Thus PQC factors can be identified in an SGA screen as mutants that enhance cell growth in a Kir2.1-dependent manner. We ultimately determined that expressing Kir2.1 from a TEF promoter on a centromeric plasmid (Supplemental Figure S2A) and then the ER membrane and into the cytosol (Wolf and Stolz, 2012), was required for degradation, since Kir2.1 was completely stabilized in a temperature-sensitive mutant, cdc48-2, at a nonpermissive temperature ( Figure 2B). Combined with the data in Figure 1, these results establish Kir2.1 as an ERAD substrate in yeast.
To determine whether Hsp70 chaperones facilitate the ERAD of Kir2.1, we expressed the protein in the temperature-sensitive Ssa1 mutant ssa1-45. The cytosolic Hsp70, Ssa1, is required for the degradation of ERAD substrates with misfolded cytosolic domains (Hill and Cooper, 2000;Zhang et al., 2001;Han et al., 2007;Nakatsukasa et al., 2008), and in line with these data, Kir2.1 degradation was attenuated at the nonpermissive temperature in the ssa1-45 strain ( Figure 2C). In contrast, Kir2.1 degradation was unaffected in a kar2-1 mutant, which is required for the ERAD of substrates with misfolded lumenal FIGURE 2: Kir2.1 degradation is proteasome and cytosolic chaperone dependent. Cycloheximide chase reactions were performed, and lysates were blotted with anti-HA antibody to measure Kir2.1 stability over time. (A) A pdr5Δ yeast strain was pretreated for 20 min with 100 μM MG-132 () or dimethylsulfoxide (). Data represent means ± SE of three independent experiments. The degradation of Kir2.1 was also measured in (B) CDC48 () or cdc48-2 () mutant yeast, (C) SSA1 () or ssa1-45 () mutant yeast, and (D) KAR2 (▪) or kar2-1 () mutant yeast. Data represent means ± SE of four to six independent experiments. In each experiment, representative Western blots are shown at the bottom. potassium ([K + ] < 10 mM; Nakamura and Gaber, 1998). A total of 271 strains that exhibited significantly increased growth on low potassium were identified (see Figure  4A for one example). To focus our efforts, we eliminated 36 strains with mutated genes that compromised select biosynthetic pathways or represented characterized transcription and translation factors. In addition, 20 strains containing dubious open reading frames were not considered further.
Fresh isolates of the remaining 215 strains were crossed to the query strain containing either a vector control or the Kir2.1 expression vector and rescreened under a higher level of stringency to eliminate possible false positives. Added into this analysis were strains lacking genes that encode members of protein complexes (e.g., ESCRT; see later discussion) that featured prominently in the preliminary screen. The 95 strongest hits from this second-round screen were selected and ranked by measuring growth in liquid culture in 96-well plates. The ratio of the doubling time of a vectoronly control strain to the same strain expressing Kir2.1 was calculated to produce a growth score. The analysis identified 54 deletion strains that reproducibly increased growth in a Kir2.1-dependent manner, each having a significantly higher growth score than the query strain containing the vectoronly control ( Figure 4B, Table 1, and Supplemental Table S1). To our surprise, genes required for ERAD were completely absent from this list, suggesting that the modest increase in growth when DOA10 was deleted (Supplemental Figure S2) was below our cutoff. Instead, nearly all of the identified genes are associated with secretory pathway function at or beyond the Golgi. For example, a member of the phosphatidylinositol 3-kinase complex (Vps38) that regulates carboxypeptidase Y (CPY) sorting and interacts with the retromer complex represented the strongest hit (Kihara et al., 2001;Burda et al., 2002). Also prominent among the hits were a large number of ESCRT proteins (Did2, Vps36, Vps27, Vps22, Vps2, Vps23, Vps37, Mvb12, and Vta1).
ESCRT is involved in Golgi and plasma membrane quality control (Li et al., 1999;Reggiori and Pelham, 2002;Apaja et al., 2010;Okiyoneda et al., 2010;Wang et al., 2011), so we directly examined the role of select ESCRT members in Kir2.1 protein biogenesis. First, a VPS23-null strain (vps23Δ) strain, which also lacked TRK1 and TRK2, was constructed, and after introduction of the Kir2.1 expression vector, the yeast were rescreened on low-potassium medium. Improved growth by Kir2.1 in the trk1Δtrk2Δvps23Δ strain was quite prominent but was significantly decreased in a trk1Δtrk2ΔVPS23 background ( Figure 5A). To confirm that rescue on low-potassium medium was associated with Kir2.1 activity, we created a well-characterized loss-of-function mutation in Kir2.1, replacing the potassium selectivity filter 144 GYG 146 sequence with 144 AAA 146 (Tinker et al., 1996). After the expression plasmid was introduced into cells, the inactive channel was unable to rescue growth, even though it propagation on medium lacking potassium at pH 4 (Nakamura and Gaber, 1998) and 30°C (Supplemental Figure S2B) provided the optimal set of conditions to screen for genes that, when mutated, would augment growth on low potassium. As a control, we found that the residence of Kir2.1, as measured in sucrose gradient analyses as in Figure 1, was unaffected when cells were propagated at pH 4 (unpublished data).
Having established that the system may detect PQC factors for Kir2.1, we conducted a genomic screen. First, the query strain was crossed to the yeast deletion collection using established SGA methodology (Tong and Boone, 2006). Next the resulting haploid strains, which each lacked one of 4848 nonessential yeast genes, were screened on selective medium at pH 4 in the absence of added

Proteasome-and ESCRT-dependent degradation of Kir2.1 in human cells
The results presented in the preceding sections indicate that Kir2.1 is an ERAD substrate in yeast but that later steps in the secretory pathway play a more profound role in controlling the population of active Kir2.1 at the plasma membrane. To examine whether these phenomena were evident in mammalian cells, we examined Kir2.1 stability in HeLa cells.
Cycloheximide chase analysis confirmed that Kir2.1 was degraded by the 26S proteasome, as it was in yeast, although to a lesser extent ( Figure 6, A and B). Because the majority of wild-type Kir2.1 turnover was proteasome independent, we next examined whether Kir2.1 was degraded in the lysosome. Consistent with a role for lysosomal degradation in controlling Kir2.1 levels, leupeptin increased Kir2.1 steady-state levels, as reported (Jansen et al., 2008;Nalos et al., 2011;Figure 6, C and D). Further, leupeptin addition augmented colocalization with a late endosomal/lysosomal marker, CD63 ( Figure 6E). In metabolic pulse-chase experiments, treatment with leupeptin again stabilized Kir2.1 in HeLa cells (Supplemental Figure S6) and, as anticipated, MG132 addition led to more modest effects (unpublished data).
To determine whether ESCRT was required for the lysosome dependent degradation of Kir2.1, we depleted the ESCRT components Tsg101 (an ESCRT-I component that is the yeast Vps23 homologue; Rothman and Stevens, 1986;Robinson et al., 1988;Babst et al., 2000) and HRS (an ESCRT-0 component that is a homologue was expressed at similar levels as wild-type Kir2.1 ( Figure 5, A and B). To ensure that Kir2.1-mediated rescue was unaffected by the presence of embedded epitopes, we expressed an untagged form of Kir2.1 in trk1Δtrk2Δ cells that restored growth on low-potassium medium to a similar extent as that observed for the doubly tagged Kir2.1 construct (Supplemental Figure S4).
A disease-associated mutation triggers the ERAD of Kir2.1 To test whether a disease-causing trafficking mutation makes the channel susceptible to PQC at an early point in the secretory pathway, we introduced the ATS-1 mutation Δ314-315, which blocks Golgi export . As expected, the mutant failed to rescue growth of trk1Δtrk2Δ yeast on low potassium. Because the Δ314-315 mutant protein was expressed at significantly lower levels than wild-type Kir2.1 ( Figure 5, A and B), we then assessed whether the mutation targets the channel for proteasomal-or vacuolar-dependent degradation. MG132 stabilized Kir2.1Δ314-315 in the pdr5Δ yeast strain, but degradation was unaffected when vacuolar proteases were inactivated (Supplemental Figure S5). These results reflect other observations that Kir2.1Δ314-315 is stabilized when the proteasome is inhibited in HeLa cells (unpublished data; see later discussion). Together the data suggest either that defects in the progression of the Andersen-Tawil mutant protein beyond the Golgi result in retrieval to the ER and proteasomal degradation, or the protein exhibits an ER folding defect as well as a defect in AP1-mediated trafficking. Haploid progeny were plated on selective medium with either 0 or 100 mM KCl, as indicated. Medium containing 100 mM KCl serves as a control for equal growth among the different mutant strains. Circles represent negative controls in which a strain was absent and used as a plate identifier. Boxes represent strains that showed significantly increased growth compared with average colony growth on the plate at 0 mM K + . (B) The Kir2.1 growth score of each hit was calculated based on the doubling time of the strains with an empty vector control divided by the doubling time of strains expressing the Kir2.1 expression vector. The medium contained a final concentration of 2.5 mM K + . The growth score values were then normalized to vps38Δ, which was the strongest hit. All strains are deleted for TRK1 and TRK2, as well as the indicated gene. Error bars SD of three independent measurements.
onstrate that ESCRT-dependent targeting of Kir2.1 to the vacuole/ lysosome regulates the levels of Kir2.1 at the plasma membrane. These results are also the first to implicate ESCRT in the regulation of a Kir potassium channel.

DISCUSSION
We demonstrated that Kir2.1 is subject to PQC at multiple levels in both yeast and human cells. An initial characterization of Kir2.1 in yeast revealed a majority of the channel residing in the ER, of yeast Vps27; Robinson et al., 1988;Komada et al., 1997;Bilodeau et al., 2002). Treatments with targeted small interfering RNAs (siRNAs) led to nearly complete absence of Tsg101 and ∼50% decrease in the amount of HRS (Figure 6, F and G). In parallel, there was a corresponding increase in Kir2.1 abundance ( Figure 6H). Addition of leupeptin did not lead to a further increase in Kir2.1 when the ESCRT components were knocked down, consistent with delivery to and degradation of the channel in the lysosome ( Figure  6I). Our collective data from the yeast and human cell models dem-  transporter levels and function (Makuc et al., 2004). It is unknown whether a Kir2.1 cofactor exists in mammals, but a yeast-based screen provides a route to identify this putative factor, as well as intragenic mutations that affect Kir2.1 function and PQC. Numerous ESCRT components were identified in the screen (Table 1 and Supplemental Table S1). Substrate selection in the MVB pathway begins with the recognition and clustering of ubiquitinated cargo by ESCRT-0 (e.g., Vps27, which was identified in the screen; Bilodeau et al., 2002;Wollert and Hurley, 2010;Mayers et al., 2011). ESCRT-I (Vps23, Vps37, and Mvb12 were represented in the screen) and ESCRT-II (Vps22 and Vps36 were isolated) are then recruited and confine cargo at the site of vesicle formation, which initiates vesicle invagination before ESCRT-III (e.g., Vps2, Table 1) is recruited (Teo et al., 2004(Teo et al., , 2006Gill et al., 2007;Kostelansky et al., 2007;Wollert and Hurley, 2010). Association of ESCRT-III leads to cargo deubiquitination (McCullough et al., 2006) and vesicle maturation (Wollert et al., 2009;Wollert and Hurley, 2010). In yeast the Vps4-Vta1 complex (Vta1, Table 1) then aids in disassembly of the ESCRT complex to complete vesicle formation (Babst et al., 1998;Azmi et al., 2008).
We also identified other factors that regulate Golgi trafficking and vacuolar function ( Table 1). Deletion of VPS38, which encodes a component of phosphatidylinositol 3-kinase complex II (PI3KII), most strongly affected Kir2.1-dependent rescue. PI3K is a member of two complexes, PI3KI and PI3KII. PI3KI localizes primarily to the vacuole and is involved in autophagy, whereas PI3KII resides in the Golgi and endosome and regulates protein trafficking from the endosome to the Golgi (Burda et al., 2002;Obara et al., 2006). Deletion of the genes encoding Vps38 and another component of the PI3K complexes, Vps30, compromises retromer activity (Burda et al., 2002). Retromer functions in the recovery of proteins from the endosome to the Golgi (Seaman et al., 1998), and all five members of the retromer complex (Vps5, Vps17, Vps26, Vps29, and Vps35) are represented within the 20 strongest hits in the screen. Although the mechanism is undefined, deletion of retromer increases plasma membrane residence of other membrane proteins in yeast, flies, and worms (Kim et al., 2007;Korolchuk et al., 2007;Dang et al., 2011). More recently, the receptor activator of NF-κB (RANK), which is involved in osteoclast formation, was shown to be inhibited by retromer-mediated transport from the endosome to the Golgi, thereby increasing RANK at the plasma membrane in murine osteoclasts (Xia et al., 2013). Inhibition of retromer may cause a factor that would normally antagonize Kir2.1 plasma membrane residence, such as a Golgi retention factor, to be degraded, or retromer may aid in retrieving a population of Kir2.1 that traffics through an endosomal intermediate en route to the plasma membrane.
Additional proteins that regulate the trafficking/localization of proteins at the Golgi and endosome were identified as weaker hits. These include Golgi-associated GTPases (Arl1, Arl3, Ypt6) that regulate Golgi-endosome trafficking (Li and Warner, 1996;Luo and Chang, 1997;Behnia et al., 2004). Ypt6 interacts with Vps52 in the Golgi-associated retrograde protein (GARP) complex, which retrieves proteins from the endosome to the Golgi; two GARP components were among the hits (Vps52 and Vps53; Conibear and Stevens, 2000;Siniossoglou and Pelham, 2002). Other protein where it is targeted for ERAD. In contrast, our genomic screen revealed that the abundance of active Kir2.1 at the plasma membrane is controlled by vacuolar targeting factors. These data suggest that a larger, permanently misfolded population of Kir2.1 is delivered to the ERAD pathway, which may be unable to mature or become active. By contrast, the pool of Kir2.1 that migrates beyond the ER appears to be in a folding-competent state, in which it is regulated by ESCRT and associated factors (see later discussion). In one model, this population may transiently adopt misfolded conformations, and defects in ESCRT-mediated degradation could then rescue this protein pool so it functions at the plasma membrane. The notion of an unstable population of maturing and even functional ion transporters is not new (Hill and Cooper, 2000;Helliwell et al., 2001;Lu et al., 2007;Apaja et al., 2010), but our data represent the first hint of the relative strengths of unique quality control mechanisms that may act on a single protein in the secretory pathway.
To some extent the studies in HeLa cells validated the use of yeast as a model to identify the pathways that affect Kir2.1 biogenesis. Kir2.1 is regulated by both ERAD and ESCRT-mediated lysosomal degradation, as in yeast, but the relative contribution of each is inverted. In yeast, the majority of Kir2.1 was degraded by ERAD, with a minor Kir2.1 population being targeted to the vacuole. Based on our calculations, rescue of trk1Δtrk2Δ yeast growth requires very few active Kir2.1 channels on the surface, so the screen provides a sensitive method to detect this minor pool. Nevertheless, rapid ERAD-mediated turnover precluded our ability to reproducibly measure changes in Kir2.1 organellar residence in the mutant strains (unpublished data). In contrast, Kir2.1 is primarily degraded in the lysosome in HeLa cells, whereas a smaller population of Kir2.1 is targeted for ERAD, and based on this fact, significant changes in the intraorganellar pool were evident ( Figure 6).
One explanation for the relative instability of Kir2.1 in yeast may be unique lipid compositions. Lipids such as cholesterol and phosphatidylinositol 4,5-bisphosphate (PI-4,5-bisP) alter Kir2.1 function and may influence its stability (Huang et al., 1998;Romanenko et al., 2004). Yeast lack cholesterol (but contain ergosterol), and the levels of PI-4,5-bisP might differ significantly between yeast and human cells. In addition, yeast could lack a Kir2.1 cofactor, which stabilizes the protein. For example, a yeast screen was used to identify cofactors for a rodent monocarboxylate transporter that increased   1 and 3; open bars) to determine the magnitude of the leupeptin response. The data represent means ± SE of six to eight independent trials. *p < 0.05, **p < 0.01, ***p < 0.001. CFTR mutant that resides at the plasma membrane (Okiyoneda et al., 2010). Future work will uncover whether these and other chaperones operate at multiple quality control networks for Kir2.1 and other ion transporters.

Yeast strains and growth conditions
Yeast strains were propagated at 26°C, and standard methods for growth, media preparation, and transformation were used unless indicated otherwise (Adams et al., 1998). Yeast with plasmids containing constitutive promoters (GPD or TEF) were grown in selective medium and harvested at the OD 600 indicated in each experiment. Yeast harboring plasmids containing the MET25 promoter were maintained on medium containing 0.5 mM methionine to inhibit protein synthesis. To induce Kir2.1 expression, cells were grown to log phase in selective medium supplemented with methionine, collected by centrifugation and washed in sterile water, and then resuspended in selective medium lacking methionine for 1-2 h. After induction, cells were used as described for each experiment. For low-potassium growth assays and the SGA screen, 20 mM MES (2-(N-morpholino)ethanesulfonic acid) and the indicated concentration of potassium were added. Medium was also prepared at the desired pH with Tris-HCl. A complete list of the strains used in this study is presented in Supplemental Table S2.
For growth assays, 5-ml cultures were grown to log phase in synthetic complete medium lacking leucine (SC-Leu) but containing 100 mM KCl at 30°C, and 1 OD 600 of cells was collected by centrifugation. The yeast were resuspended in 500 μl of sterile water. Cells were serially diluted 10-fold, plated using a 32-pin manifold onto SC-Leu medium containing 0, 10, 25, or 100 mM KCl, and grown at 30°C for 2 d. Plates were imaged using an Epson Perfection 3490 Photo Scanner. To assay protein expression, an equal number of cells was taken from the plates, and total protein was precipitated with 10% trichloroacetic acid and resolved by SDS-PAGE before Western blot analysis (Zhang et al., 2001). Kir2.1 was detected using an anti-HA-horseradish peroxidase (HRP)-conjugated antibody, and blots were probed with anti-glucose-6-phosphate dehydrogenase (G6PD) antiserum to provide a loading control. The G6PD primary antibody was decorated with donkey HRP-conjugated anti-rabbit immunoglobulin G secondary antibody. The Supersignal Chemiluminescent Substrate (Pierce, Rockford, IL) was used to develop the blots, and the signals were quantified using a Kodak 440CF Image Station and the associated Kodak 1D software (Eastman Kodak, Rochester, NY).
Strain YAK01 (Supplemental Table S2) was constructed from Y7029 by homologous recombination (Brachmann et al., 1998). The NAT cassette was PCR amplified using primers oAK01 and oAK02 (Supplemental Table S3), which also contained homology to the TRK2 locus, and the PCR product was used to delete TRK2 in Y7029. The URA3 cassette from pRS426 (Mumberg et al., 1995) was PCR amplified using primers oAK05 and oAK06 (Supplemental Table S3), which contained homology to the TRK1 locus. The product was then used to delete TRK1 in Y7029. YAK02 and YAK03 were constructed from AK01 by mating this strain with a vps23Δ and a doa10Δ mutant from the yeast deletion collection (Invitrogen, Carlsbad, CA), respectively. All constructed strains were confirmed by growth on selective medium and by PCR using specific primers (Supplemental Table S3). CDC48 and cdc48-2 were constructed by mating cdc48-2 (Li et al., 2011) to ybr074Δ (Invitrogen), and the identity of the desired genotype was confirmed by plating on medium containing G418 (Research Products International, Mount Prospect, IL) and sequencing after PCR amplification of the locus. complexes involved in trafficking within the Golgi, such as the TRAPP complex (Tca17, Trs85; Sacher et al., 2000;Montpetit and Conibear, 2009) and the conserved oligomeric Golgi (COG) complex (Cog5, Cog6, Cog7, Cog8; Ram et al., 2002;Ungar et al., 2002), were among the 18 weakest hits, but whether these play a direct or indirect role in Kir2.1 trafficking is unclear. Nevertheless, these data are consistent with Golgi accumulation of the Kir2.1 Andersen-Tawil mutant .
The rescue of a trk1Δtrk2Δ strain on low potassium when each of the identified genes was deleted was mediated by Kir2.1 function and is not simply a result of the deleted gene making the yeast more tolerant to potassium-poor medium. For each hit, we showed that the introduction of a vector control was unable to improve growth to the same level as a strain expressing Kir2.1. However, a screen for mutants that exhibited increased sensitivity to cationic drugs identified Arl1, the COG complex, the GARP complex, and retromer (Barreto et al., 2011), suggesting that some of hits from our screen may alter the localization of other yeast potassium channels in addition to Kir2.1. Many of our hits also lead to increased CPY secretion (Bonangelino et al., 2002). However, the strains that increase CPY secretion do not completely overlap with the hits identified in this study; thus Kir2.1 localization is regulated differently than this soluble, vacuolar-resident protein (see Supplemental Table S1). In fact, there is more overlap with genes identified in a screen for mutants that rescue the localization of a defective form of the plasma membrane ATPase Pma1 (e.g., Vps38, Vps36, Vps29, Vps13, Vps35, Vps27, and Bsd2; Luo and Chang, 1997). A screen was also performed in which another inward-rectifying potassium channel, Kir3.2, was mutated so that it was sodium selective, and strains expressing the protein were crossed to a subset of the deletion collection (Haass et al., 2007). The resulting haploids were screened on medium containing high sodium, and seven genes associated with COPII-dependent transport and lipid biogenesis were identified that, when mutated, reduced sodium-mediated toxicity.
Our data contribute to a growing number of substrates that are regulated by the PQC machinery at the Golgi and plasma membrane in yeast (Chang and Fink, 1995;Hong et al., 1996;Jenness et al., 1997;Haynes et al., 2002;Spear and Ng, 2003;Coughlan et al., 2004;Wang and Ng, 2010) and mammals (Armstrong et al., 1990;Ashok and Hegde, 2009;Apaja et al., 2010;Okiyoneda et al., 2010). It is worthwhile to note that the population of an unrelated potassium channel, KCa3.1, at the plasma membrane is also regulated by ESCRT and that mutant forms of this channel are subject to ERAD (Balut et al., 2012). Therefore in the future it will be interesting to determine whether ESCRT is used for the targeted destruction of all or only a subset of potassium and perhaps other ion channels. In addition, we found that a core collection of Hsp70 and Hsp40 molecular chaperones aid in the identification of Kir2.1 as an ERAD substrate in the ER. Studies in mammalian cells identified Hsc70, Hsp90, and Hsp40s as important for the recognition of the collected by centrifugation and washed with solution A (2 M sorbitol, 0.5 M KPO 4 , pH 7) and resuspended in 500 μl of solution A supplemented with 60 ng/ml 100T Zymolyase (MP Biomedicals, Solon, OH) and 25 mM 2-mercaptoethanol and were incubated at 37°C for 30 min. The spheroplasts were pelleted at 3000 rpm for 3 min, washed with solution A, and resuspended in 800 μl of solution A. The cell suspension (30 μl) was added to a microscope slide well (pretreated with 1 mg/ml polylysine) and incubated at room temperature for 30 min. The liquid was aspirated, and the wells were washed once with phosphate-buffered saline (PBS)/0.1% bovine serum albumin (BSA) and twice with PBS/0.1% BSA/0.1% NP40 and then incubated with the following primary antibodies at 4°C: anti-HA at a 1:250 dilution and anti-Kar2 at a 1:500 dilution. The slides were next washed once with PBS/0.1% BSA, once with PBS/0.1%BSA/0.1% NP40, and once with PBS/0.1% BSA and were incubated with the appropriate secondary antibodies (Alexa Fluor 568 goat anti-rabbit and Alexa Fluor 488 goat anti-mouse; Molecular Probes, Eugene, OR) in PBS/0.1% BSA for 1 h at room temperature. The slides were again washed as described, and coverslips were mounted using ProLong Gold Antifade mounting media (Invitrogen). Images were captured on an Olympus BX60 microscope (Olympus, Tokyo, Japan) fitted with a Hamamatsu C4742-95 digital camera (Hamamatsu, Bridgewater, NJ), using QED Imaging software (Media Cybernetics, Silver Spring, MD).

Biochemical assays
Kir2.1 degradation was assayed by cycloheximide chase analysis as described (Buck et al., 2010). In brief, cells expressing Kir2.1 under the control of the GPD promoter were grown in selective medium with shaking to log phase (OD 600 0.4-1.2), and 100 μg/ml of cycloheximide (Sigma-Aldrich) was added to stop protein translation. The yeast were incubated at 30°C in a shaking water bath, and temperature-sensitive mutants were incubated at 37°C for 10 min before performing the chase at 37°C. The cdc48-2 temperature-sensitive strain and the isogenic wild type were incubated at 39°C for 2 h before the start of the chase, and the incubation was continued at 39°C. A 1-ml aliquot of the culture was collected at the indicated time points, and pelleted cells were washed with ice-cold water containing protease inhibitors, flash-frozen in liquid nitrogen, and stored at −80°C. Total protein was precipitated from samples as described (Zhang et al., 2001) and immediately resolved by SDS-PAGE before Western blot analysis, as described.
To measure the relative amount of Kir2.1 ubiquitination, cells harboring the pRS426MET25-Kir2.1 plasmid were grown to an OD 600 of 1.0 in 50-ml cultures of selective medium containing 0.5 mM methionine. The yeast were collected by centrifugation, washed in sterile water, and resuspended in the same medium lacking methionine for 2 h. After induction, the cells were collected by centrifugation and quick frozen in liquid nitrogen and stored at −80°C until use. Immunoprecipitations were preformed essentially as described (Ahner et al., 2007). In brief, cells were broken by glassbead lysis, and membranes were collected by centrifugation. The membranes were then treated with SDS buffer to liberate Kir2.1, and after dilution into a Triton X-100-containing buffer an anti-HA antibody conjugated to agarose beads (Pierce) was added and the slurry was incubated overnight with rocking at 4°C. The beads were washed, and SDS sample buffer was used to liberate the bound proteins. The released proteins were subjected to SDS-PAGE and Western blot analysis to detect total Kir2.1 and the ubiquitinated Kir2.1 fraction.
The intracellular residence of Kir2.1 was determined by sedimentation in a sucrose gradient essentially as described (Sullivan

Plasmid construction
Mouse Kir2.1 in pcDNA3.1 was modified with an internal HA tag that was positioned so that it faced the extracellular space (Ma et al., 2001). To create a yeast Kir2.1-HA expression construct with a C-terminal myc tag (myc-Kir2.1-HA), the Kir2.1 coding sequence within the pcDNA3.1 vector was PCR amplified using the PCR Master Mix reagent (Fermentas, Waltham, MA). The amplified Kir2.1 sequence was purified using the PureLink PCR purification kit (Invitrogen) and ligated into the pGEM-T easy vector (Promega, Madison, WI). The pGEM-T-Kir2.1 plasmids were sequenced to identify clones that contained the correct Kir2.1 insert. The insert was removed from pGEM-T using EcoRI, the fragment was gel purified using PureLink Quick Gel Extraction Kit (Invitrogen), and the isolated species was ligated into the EcoRI site of yeast plasmids containing either constitutive (TEF, GPD) or regulated (MET25) promoters (Mumberg et al., 1994(Mumberg et al., , 1995. The myc-Kir2.1-HA insert was then cloned into digested pRS vectors containing different promoters and genes for auxotrophic selection (Mumberg et al., 1994(Mumberg et al., , 1995 using SmaI and XhoI. The cut vector was treated with Antarctic phosphatase (New England BioLabs, Ipswich, MA), and the digested vectors were run on a 1% agarose gel and purified with PureLink Quick Gel Extraction Kit (Invitrogen). The cut vectors and inserts were finally ligated using T4 DNA Ligase (Fermentas). Kir2.1-AAA and Kir2.1Δ314-315 were made by two-stage PCR mutagenesis (Vallejo et al., 1994). The Kir2.1 mutated cassettes were then inserted into the PRS415TEF vectors as described. All isolated inserts were subject to DNA sequence analysis.

Genetic screening conditions
The query strain (YAK01) was mated to the MATa strain deletion collection (Invitrogen) as described (Tong and Boone, 2006). In brief, the query strain was plated onto SC-Leu plates using a 96-pin manifold (Aladin Enterprises, Brisbane, CA). Strains in the deletion collection were then plated over the query strain, and the plates were incubated at 30°C for 1 d. The cells were next plated onto SC-Leu containing 200 mg/l G418 (Research Products International), 100 mg/l clonNAT (Werner BioAgents, Jena, Germany), and 100 mM KCl to select for diploids and to maintain a potassium-sensitive phenotype and were incubated at 30°C for 2 d. The resulting diploid cells were plated onto sporulation medium and kept at room temperature for 5 d. Finally, the spores were inoculated on diploid selection media lacking histidine, arginine, and uracil and containing 50 mg/l canavanine (Sigma-Aldrich, St. Louis, MO) and were incubated at 30°C for 2 d. This step was repeated two additional times with 1-d incubations to select against any remaining diploids. The final haploid strains, each expressing Kir2.1 but deleted for TRK1, TRK2, and one of 4847 genes in the collection, were screened on SC-Leu medium lacking any added potassium and were examined after 2 d at 30°C.
Colonies that grew significantly better than the average colony size on the plate were verified by growth in liquid medium at 30°C in a 96-well plate. Initial cultures were grown in 200 μl of SC-Leu medium containing 100 mM KCl. A total of 5 μl of the initial cultures was pipetted into 195 μl of SC-Leu medium lacking KCl and grown at 30°C with shaking. The OD 600 was measured every 1-2 h with a Thermo Scientific (Waltham, MA) Multiskan Go plate reader to obtain the doubling times. All experiments were performed in triplicate.

Indirect immunofluorescence in yeast
Yeast cells expressing Kir2.1 were grown to an OD 600 of 0.5-0.8 and fixed with 3.7% formaldehyde for 1 h at 30°C. The cells were then To monitor Kir2.1 stability by cycloheximide chase analysis, a final concentration of 50 μg/ml cycloheximide (Sigma-Aldrich) in the presence or absence of 15 μg/ml MG132 (Peptides International, Louisville, KY) was added to cells expressing Kir2.1-HA to stop protein translation and inhibit the proteasome, respectively. The cells were incubated at 37°C and harvested with 100 μl of lysis buffer (50 mM Tris, pH 7.2, 1% Triton X-100, 150 mM NaCl, cOmplete Mini protease inhibitor cocktail [Roche Diagnostics]), and the protein concentration was measured by bicinchoninic acid (Thermo Scientific). Equal amounts of protein were resolved by SDS-PAGE before Western blot analysis.
To assess the turnover of Kir2.1 using a metabolic pulse-chase protocol, HeLa cells were transfected with pcDNA3.1 HA-Kir2.1 and treated with 100 μM leupeptin immediately after transfection and again 6 h later. The following day, fresh leupeptin was added to DMEM lacking cysteine and methionine (Sigma-Aldrich), and cells were starved for 45 min, followed by a 1-h pulse with 125 μCi/ml EasyTag Express 35 S protein labeling mix (PerkinElmer). After the pulse, the cells were chilled to 4°C using an ice-cold metal plate and washed three times for 5 min each with DMEM containing 5 mM cysteine and methionine and 10 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid, pH 7.4. The cells were then incubated with prewarmed chase media supplemented with 0.2% dimethylsulfoxide or 100 μM leupeptin. Leupeptin was readded at 3 and 6 h of the chase. At each measured time point, the cells were cooled by washing with ice-cold PBS, followed by solubilization with 500 μl of detergent solution (50 mM Tris, pH 8, 100 mM EDTA, pH 8, 0.4% sodium deoxycholate, 1% Nonidet P-40, protease inhibitors [1 mM phenylmethylsulfonyl fluoride, 1 μg/ml leupeptin, and 0.5 μg/ml pepstatin A]). The resulting lysates were centrifuged for 10 min at 17,000 × g in a refrigerated microcentrifuge, and the postnuclear supernatants were transferred to a fresh tube containing 10 μg of mouse anti-HA (12CA5; Roche) and rotated overnight at 4°C. Antibody-Kir2.1 complexes were captured using fixed Staphylococcus aureus (Pansorbin; Calbiochem, San Diego, CA) and washed three times with 10 mM Tris-HCl, 0.15 M NaCl, 1% Triton X-100, 1% Nonidet P-40, and 0.1% SDS, pH 7.4. Samples were eluted with SDS sample buffer supplemented with 5% βmercaptoethanol and electrophoresed using 10% SDS-PAGE. The gels were dried and exposed to a phosphorimager screen before analysis using Image J.

Statistical analysis
To analyze experiments performed in HeLa cells (Figure 6), statistical analysis was performed using Prism (GraphPad, La Jolla, CA). Statistical significance was determined by one-way analysis of variance (ANOVA) and Tukey's post hoc test in G and two-way ANOVA and Bonferroni post tests in H.

Antibodies
The following primary antibodies were used for studies in yeast: HRP-conjugated rat monoclonal anti-HA high-affinity (3F10; Roche), anti-HA mouse monoclonal (Roche), G6PD rabbit polyclonal antibody (Sigma-Aldrich), a ubiquitin (P4D1) mouse monoclonal antibody from Santa Cruz (Dallas, TX; sc-8017), and a polyclonal rabbit anti-Kar2 (Brodsky and Schekman, 1993). A polyclonal rabbit anti-Pma1 was a gift from Amy Chang (University of Michigan, Ann Arbor, MI). The following secondary antibodies were used in yeast: HRP-conjugated goat anti-mouse and goat anti-rabbit antibodies (Jackson ImmunoResearch, West Grove, PA) and Alexa Fluor 568 goat anti-rabbit and Alexa Fluor 488 goat anti-mouse (Invitrogen, et al., 2003). A 40-ml culture was grown to an OD 600 of 0.8, and the cells were harvested by centrifugation, resuspended in 10 mM Tris-HCl, pH 7.5, 1 mM EDTA, and 10% sucrose, and then disrupted by agitation with glass beads. The cell lysates were cleared of debris by low-speed centrifugation and the resulting lysate (300 μl) was layered at the top of a 11 ml 30-70% sucrose gradient and centrifuged at 100,000 × g in a Beckman SW41 rotor for 14 h at 4°C. Fractions were collected by pippeting from the top of the tube. The presence of specific proteins was analyzed by SDS-PAGE and Western blot.

Analysis of Kir2.1 in HeLa Cells
HeLa cells were cultured in DMEM with 10% FBS, 100 U/ml penicillin/streptomycin, and 2 mM glutamine at 37°C and 5% CO 2 . XtremeGENE9 transfection reagent (Roche, Indianapolis, IN) was used as per the manufacturer's guidelines to transfect mouse Kir2.1 in pcDNA3.1 (pcDNA3.1-HA-Kir2.1). To knock down the expression of ESCRT proteins, HeLa cells plated in six-well dishes were cotransfected with 1 μg of pcDNA3.1-HA-Kir2.1 and 2 μg of siRNA using XtremeGENE siRNA transfection reagent (Roche, Penzberg, Germany). The siRNAs for human TSG101 (CCAAAUA-CUUCCUACAUGC), human HRS (HGS; GAACCCACACGUCGC-CUUG), and a scramble control (ON-TARGETplus nontargeting siRNA #1) were obtained from Invitrogen. After 54 h a final concentration of 100 μM leupeptin was added where indicated. After another 18 h the cells were washed with PBS and collected in 1% Triton in PBS with Protease Inhibitor Cocktail (P8340; Sigma-Aldrich). Lysates were rotated for 1 h at 4°C, followed by centrifugation at 13,000 rpm in a microcentrifuge for 5 min at 4°C. Supernatants were incubated with loading buffer for 30 min at room temperature, and proteins were analyzed by SDS-PAGE and Western blot.
For immunoblot analysis, the cells were washed with PBS and collected in 1% Triton X-100 in PBS with Protease Inhibitor Cocktail and then incubated with rotation for 1 h at 4°C and centrifuged (13,000 rpm, 5 min, 4°C in a microcentrifuge) to pellet-insoluble material. Supernatant protein concentration was determined by BCA Protein Assay Kit (Pierce), and proteins were resolved by SDS-PAGE, transferred to a nitrocellulose membrane, and probed with the appropriate primary and HRP-conjugated secondary antibodies. SuperSignal West Pico Chemiluminescent Substrate was used to detect the signal from the HRP-conjugated antibody, and the chemiluminescent signal was visualized by fluorography. Densitometric measurements were made in the linear range using ImageJ (National Institutes of Health, Bethesda, MD).


extfieldsofstudy: Medicine Biology

text:
RNA-Seq transcriptome analysis of Spirodela dormancy without reproduction

Background Higher plants exhibit a remarkable phenotypic plasticity to adapt to adverse environmental changes. The Greater Duckweed Spirodela, as an aquatic plant, presents exceptional tolerance to cold winters through its dormant structure of turions in place of seeds. Abundant starch in turions permits them to sink and escape the freezing surface of waters. Due to their clonal propagation, they are the fastest growing biomass on earth, providing yet an untapped source for industrial applications. Results We used next generation sequencing technology to examine the transcriptome of turion development triggered by exogenous ABA. A total of 208 genes showed more than a 4-fold increase compared with 154 down-regulated genes in developing turions. The analysis of up-regulated differential expressed genes in response to dormancy exposed an enriched interplay among various pathways: signal transduction, seed dehydration, carbohydrate and secondary metabolism, and senescence. On the other side, the genes responsible for rapid growth and biomass accumulation through DNA assembly, protein synthesis and carbon fixation are repressed. Noticeably, three members of late embryogenesis abundant protein family are exclusively expressed during turion formation. High expression level of key genes in starch synthesis are APS1, APL3 and GBSSI, which could artificially be reduced for re-directing carbon flow from photosynthesis to create a higher energy biomass. Conclusions The identification and functional annotation of differentially expressed genes open a major step towards understanding the molecular network underlying vegetative frond dormancy. Moreover, genes have been identified that could be engineered in duckweeds for practical applications easing agricultural production of food crops.

Background
Plants, unlike animals, do not have a fur or can seek shelter to survive under food shortage and cold weather. Consequently, they adapt to dormancy to avoid adverse environments, such as poor nutrition, chilling temperature, and drought. Dormancy is a complex state of plant development, in which the plant body exhibits little or no growth. They recover their growth once the conditions are favorable.
There are mainly two types of plant dormancy by forming seeds or buds. Seed dormancy has been observed for many plants species including our major crops [1][2][3]. Winter dormant buds are found for instance in woody plants, bulbs, rhizomes and tubers of herbaceous plants [4]. Studies on the molecular mechanisms of bud dormancy transitions in perennial woody plants have been conducted, including pear [5], oak [6], and poplar [7].
Spirodela polyrhiza, a floating aquatic monocot, develops a specific dormant organ called turion during its life cycle, which alternates between periods of clonal propagation and dormancy. Its leaf, stem and bud are extremely compact in form of a round-shaped frond, resembling a single leaf. Large numbers of Spirodela plants can be maintained like cell cultures under totally controlled medium and environmental conditions. They reproduce vegetatively through budding of fronds (growth phase) during spring and summer [8] and transition to turions (dormant phase), when there is shortage of nutrition in the fall or the temperature drops in the winter [9]. Noticeably, fronds perform photosynthesis and turions function as storage for starch and germinate in the following spring [10][11][12][13]. Turion cells exhibit dense intercellular space, thick cell wall and are also rich in anthocyanins [14]. Therefore, turions provide a unique system to study both bud and seed dormancy because they reproduce like buds without sexual hybridization but functionally are equivalent to seeds that could generate a progeny plant in the growing season. Previous studies have shown that addition of ABA into growth medium quickly leads to turion formation after 5 days of treatment in the laboratory [13,15,16]. Only 3 days after ABA treatment, the Spirodela primordium is irreversibly committed to turion development [15]. The ease of growth and its direct contact with water make Spirodela a model system to gain molecular insights into plant dormancy [17].
At the molecular level, some studies on turion development have already been performed. For example, the transcript level of D-myo-inositol-3-phosphate synthase is rapidly induced within 15 min of ABA application, an enzyme that plays a key role in the inositol metabolism of the cell wall [18,19]. The expression of the key enzyme ADP-glucose pyrophosphorylase (APL) for starch production [13] is significantly changed during turion formation. Still, not much information is known about the global transcriptome profiling for turion formation in this model system. To further uncover the regulation of gene expression as the phase switches, we took advantage of RNA deep sequencing, and compared the transcriptome between fronds and developing turions. A more comprehensive understanding of the gene repertoire and its regulation during turion formation has also great potential for industrial applications including the redirection of carbon flow into higher energy products.

Sample preparation
Spirodela polyrhiza 7498 was grown in half-strength Schenk and Hildebrandt basal salt mixture (Sigma, S6765) with 1% sucrose liquid medium under 16-hrs light, 8-hrs dark photoperiod. Plant tissues from four biological replicates for fronds without ABA treatment and developing turions with 3-day 10 μM ABA were collected and frozen in liquid nitrogen. 10 μg of total RNA was extracted for each sample by RNA-easy Qiagen kit with RLC buffer due to second metabolites. Ribosomal RNA was depleted with a kit from Epicenter (MRZPL116) in order to increase the coverage of other RNA classes. Vegetative fronds and turions with 14 days ABA treatment were fixed, embedded, and examined under transmission electron microscope as described [13,20].

Library construction and sequence quality control
We started with~300 ng rRNA-depleted total RNA, fragmented the RNA, performed reverse transcription and size-selected the cDNA, used Emulsion PCR to amplify the complex gene libraries and prevent formation of chimeric cDNA products. All steps followed the manufacturer's guide (SOLiD™ total RNA-Seq kit). To minimize potential experimental batch effect, eight samples were barcoded, pooled, and evenly distributed into three lanes. The singleend reads with the size of 75 bp were generated with our in-house SOLiD 5500 platform. The Exact Call Chemistry (ECC) module was utilized in the sequencing run, which is an optional kit that is used to further enhance sequencing accuracy by generating reference-free bases directly. After quality trimming with score of 20, reads with a minimum length of 40 bp were saved.

Read mapping and quantifying gene expression
The remaining reads were mapped to the reference genome Spirodela polyrhiza 7498 (http://www.waks man.rutgers.edu/spirodela/genome; GenBank Accession #ATDW01000000), which was recently sequenced, assembled, and annotated, by using TopHat 2 [21] with Bowtie [22]. TopHat is a fast splice junction mapper for RNA-Seq reads. It aligns RNA-Seq reads to reference genomes using the ultra high-throughput short read aligner Bowtie, and then analyzes the mapping results to identify splice junctions between exons. Gene expression levels were normalized using fragments per kilobase of exon per million mapped reads (FPKM). Transcript abundance and differential gene expression were calculated with Cufflinks [23]. DE genes were defined, as when their absolute value of log2 fold change was higher than 2 and their P value was less than 0.01.
To test the validity of our measurements, we used independent data obtained in a separate study under the same induction conditions as in this study from the expression of ADP-glucose pyrophosphorylase genes with qRT-PCR [13]. We also used northern blot data of the expression of the tur4 gene obtained in yet another study [24].

Functional annotation and cis-element predictions
For each DE gene, GO annotation was obtained with the program of blast2go, which uses a blast algorithm to assign GO terms to sequences based on similarity [25]. GO enrichment was performed in two groups of gene sets, respectively, one of highly expressed transcripts in turions, the other one of highly expressed transcripts in fronds based on the whole gene set of the Spirodela genome using GOseq, which adjusts the bias from gene lengths [26]. The cis-acting regulatory DNA elements were predicted by signal scan search from PLACE database [27]. PLACE is a database of motifs found in plant cis-acting regulatory DNA elements, all from previously published reports. We dissected 1-kb regions upstream of DE genes and scanned them for potential pairs of TFs and cis-elements.

Calibration and selection of tissue samples
A comprehensive study for turion formation has been done using abscisic acid (ABA) induction [14,15,17,28,29]. Three days after ABA induction, the Spirodela primordium is committed to turion development, which cannot be reversed. All primary biosynthesis of protein, mRNA and DNA are shut down resulting in the onset of the dormant state [28]. To calibrate our growing conditions with previous investigations, we used transmission electron microscopy (TEM) to investigate different developmental stages. We chose fronds and developing turions with 3 days after ABA treatment instead of 14 days because 14-day treatment is not a key transition state and RNA purification is greatly hampered by high content of starch, but mature turions with 14-days treatment provide a more complete structural image through TEM. Turion cells have thicker cell walls, multiple smaller vacuoles and distorted plastids filled with abundant starch granules, whereas frond cells differ with having well-shaped chloroplasts consistent with previous observations ( Figure 1). Therefore, growing conditions and turion induction appear to be reproducible.

Mapping RNA-Seq reads
We used eight samples in total, with each condition having four biological replicates. To eliminate potentially technical variation from biological replicates, they were multiplexed, pooled, and sequenced with the SOLiD 5500 platform. A total of 15~41 million quality reads per sample were generated after filtering raw reads ( Table 1).
The high quality reads were mapped to chloroplast [30], mitochondria [31], and nuclear genomes [32], respectively. We could clearly divide sequence reads into these three classes. Surprisingly, there was an abundance of organellederived transcripts with 28~39% of total reads. With this depth of data we could assemble sequences for complete plastid and mitochondrial transcriptomes. The high proportion of organelle reads stresses the important roles of their transcripts, provides us with their expression profiles and facilitates the phylogenetic analysis [33]. Based on the combined reads of nuclear and organelle RNAs, more than 89% of our RNA-Seq reads were mappable. It also suggests that part of previously unmapped reads in other studies remained undetected because of their organellar origin [5,[34][35][36]. We still found that 1~9% of total reads were derived from ribosomal RNA, which is an indication that the protocol for the depletion of ribosomal RNA from samples was reasonably successful. Such efficiency is critical for mainly uncovering the desired transcriptome with complete coverage and in a cost-effective manner [37].
Among the total reads, 53-61% originated from nuclear DNA, lower than in other cases with about 80% of mappable sequences [34,36]. The reason could be the method we used through ribosomal RNA removal rather than polyA selection. In case of polyA selection, organelle transcripts are automatically removed due to the lack of the polyA tail in organelle transcripts, whereas most of them were captured by our method of ribosomal RNA removal. Excluding the abundant organelle and rDNA reads, nuclear reads corresponded to 29~72X coverage for all annotated genes (Table 1), demonstrating that the depth used in our study was sufficient to cover the Spirodela nuclear transcriptome.

Identification and validation of differentially expressed genes
Comparison of frond and developing turion samples provided us with 362 differentially expressed (DE) genes. A total of 117 had greater than 10-fold difference in mRNA levels and 208 genes were up-regulated and expressed at higher levels in developing turions than in fronds, whereas 154 genes were down-regulated, indicating lower expression in turions than in fronds (Table 2). Previous studies had indicated that a small number of biological replicates might not be robust enough because it is impossible to know whether expression patterns are specific to individuals or are characteristic for the total population. Even for RNA deep sequencing, a sufficient number of biological replicates are still required to have confidence in the measurements [38][39][40]. Because two biological replicates usually are not sufficient to account for sample variability, we increased this number to four independent biological replicates. The coefficient of variation to the power of two (CV 2 ), a normalized measure of cross-replicate variability that can be useful for evaluating the quality of RNA-Seq data, was calculated to exhibit the biological variation ( Figure 2). As expected, the data showed that the abundance of the genes varied between replicate RNA samples, especially for ones with lower FPKM values. In addition, four biological replicates allowed us to take variation within the target population into account and also counteract random technical variations [23,41].
To test the validity of our measurements, we compared the RNA-Seq data of the three transcripts of ADP-glucose pyrophosphorylases (APLs) for starch synthesis with the developmental expression of these genes studied previously, which were done with qRT-PCR [13]. Indeed, the correlation co-efficient of 0.992 indicated that the two independent measurements were consistent and showed similar patterns: APL1 (GenBank Accession #JN180634) was highly expressed in fronds and APL3 (GenBank Accession #JN180636) showed the most abundance in developing turions. However, APL2 (GenBank Accession #JN180635) was not identified as DE gene due to only 1.5 times of difference at the time point of 0 and 3 rd day by the threshold value of 4 ( Figure 3). We also compared the RNA-seq data of a fourth gene, tur4, with its developmental expression after ABA treatment [24]. The tur4 gene has the Gene ID Spipo7G0013500 in the sequenced genome of Spirodela. Although the tur4 gene responded to ABA treatment within hours, it appeared to return to nearly normal levels of expression thereafter. Northern blot analysis showed no induction at day 3 after ABA treatment, whereas we could still detect a 2-fold increase in tur4 expression with RNA-Seq, indicating that our method is more sensitive than Northern blot analysis. However, based on the developmental profile of the APLs and tur4 results, we found a cut-off for DE genes at 4-fold expressional changes the most meaningful.

Response to ABA stimulus
The plant hormone abscisic acid (ABA) plays a major role as a signal in seed development and plant dormancy [42,43] and regulates many important aspects, such as the synthesis of seed storage proteins, starch and lipids [44,45]. In Spirodela, the exogenous ABA could easily trigger the dormant state (turions) from growth phase (fronds) [15]. We found 25 up-regulated DE genes belonging to gene families of "response to abscisic acid stimulus" and "negative regulation of abscisic acid mediated signaling pathway" (Table 3 and Additional file 1: Table S1). The pathway of ABA signal transduction and response seemed to be interwoven with enzyme metabolism (kinase, synthase, and phosphatase) and other signaling pathways (transporter, ethylene). Northern blot analysis shows that ABA rapidly up-regulates tur4 transcriptional level that encodes a peroxidase, which could stimulate turion formation and growth inhibition [24].

Growth inhibition
Dormancy is generally defined by the lack of visible growth. The shoot apices cease active growth in perennial plants when a state of dormancy is reached. The seed dormancy is observed in seeds with a quiescent phase preventing germination. The same phenomenon was investigated for Spirodela in the presence and absence of growth. When we looked at DE genes associated with Spirodela growth by RNA-Seq data, we found genes of histone H3 (Spipo9G0039400, Spipo0G0046100 and Spipo13G0007500) and H4 (Spipo28G0019000), ribosomal protein (Spi-po1G0126300), expansins (Spipo22G0026300), aquaporins (Spipo11G0033800, Spipo17G0045100), ribulose-1, 5-bisphosphate carboxylase oxygenases (RuBisCO) (Spipo 19G0027700, Spipo23G0013400) for carbon fixation were down-regulated in turions (Table 4). In eukaryotic cells, DNA replication requires the synthesis of histone proteins to package newly replicated DNA into nucleosomes.
Expansins are a key endogenous regulator of plant cell enlargement [46]. Aquaporins support cell growth and especially contributes to cell expansion and cell division. The gene that is highly expressed in fronds (69 times higher than in turions) is aquaporin (Spipo11G0033800)  ( Table 4). Over-expression of aquaporin stimulates cell growth in tobacco [47] or in Arabidopsis [48]. These results further confirm our knowledge that fronds are mainly responsible for rapid growth through actively DNA assembly, protein synthesis and carbon fixation, leading to a quick biomass increase, in comparison to the turions, where these processes are greatly decreased. Previous studies also suggested this mechanism of the turion formation by measuring DNA, RNA and protein content, which showed that DNA, protein and RNA biosynthesis were  On the other hand, we found some specific mRNAs were increased in developing turions, for example LEAs. Although there were five members of LEA genes (Spipo14G0001200, Spipo5G0015500, Spipo0G0166800, Spipo1G0033500, Spipo26G0007700) with increased expression in turions, the LEA gene (Spipo0G0166800) was the most up-regulated DE gene; two other LEA genes (Spi po5G0015500 and Spipo14G0001200) were exclusively expressed in developing turions (Table 5). Indeed, the promoter of these LEA genes would be ideal to ensure expression of other coding regions exclusively in turions through transgenic approaches. Additionally, LEA was found to protect other proteins against desiccation, cold, and high salinity [49] and especially accumulates when plant seeds desiccate [50]. Given their high induction, they provide valuable markers for dormancy in general. In response to dehydration, endogenous ABA levels increased dramatically followed by induction of LEA [51]. As expected, when Spirodela fronds are destined to dormant turions triggered by ABA, desiccation is an indispensable step, in which LEA proteins play pivotal roles to preserve the cellular structures and nutrients in turions.

Genes involved in carbon partitioning
Starch is the major carbon reserve in plant storage organs, and ABA has a signaling role by inducing starch biosynthetic gene expression and co-ordinate carbohydrate partitioning [52]. In our study, four genes (Spi-po12G0062400, Spipo18G0038500, Spipo16G0027000 and Spipo27G0011300) (Additional file 1: Table S1) participating in starch biosynthesis were significantly enhanced in developing turions. The RNA-seq data was consistent with the qRT-PCR experiment of the key enzyme of largesubunit ADP-glucose pyrophosphorylase 3 (APL3) for starch biosynthesis that was highly expressed during turion development [13]. The RNA-Seq study for Landoltia punctata also revealed gene expression involved in starch biosynthesis was up-regulated under nutrient starvation [53]. Another way to accumulate starch content is to redirect carbon flow to starch biosynthesis. We found seven genes participate in the degradation of lipids by alpha-(Spipo0G0156600, Spipo0G0180000, Spipo0G0156500, Spipo5G0040500) or beta-oxidation (Spipo0G0179100, Spipo3G0031300, Spipo1G0110400), which probably allocate carbon to starch rather than fatty acids to achieve denser turions that sink to the bottom of streams during seasons (Additional file 1: Table S1). Previously, it has been shown that the carbon flow into seeds can be rebalanced between different macromolecules with different energy content [54]. Reallocation of carbon is critical for the improvement of oil production in novel crops in the future. In oilseed species, numerous biotechnological approaches have been carried out that were aimed to maximize the flow of carbon into oil by over-expression of enzymes of the TAG assembling network [55]. Although one might argue that turions would no longer be able to sink in water when filled with lipids, in those applications biomass would be accumulated under constant temperature. Another way to investigate the balance of carbon partitioning can be derived from the average FPKM value (Fragments Per Kilobase of transcript per Million mapped reads) of all the key genes encoding both pathways. The genes encoding for lipid production were expressed relatively low with FPKM of 28 and 22 in fronds and turions, respectively. Therefore, the level of lipids remains low throughout development (Additional file 1: Table  S2). Given the high level of starch in turions, genes in lipid production are not induced, whereas the ones for starch biosynthesis are during turion formation, providing us with a correlation between metabolic products and the regulation of the corresponding pathways. Given this correlation, we hypothesize that we could redirect carbon flow into lipids by blocking key genes of such as AGPS1, AGPL3, GBSSI and ACCase4, GPAT1, DGAT2, and over-express transcripts of the lipid pathway (Additional file 1: Table S2) together with turion-specific promoters, like LEAs (Spipo14G0001200, Spipo5G0015500, Spipo0G0166800) ( Table 5).

Turion-specific pathays
We found that the transcriptome also closely links the turion phenotypic variation with a thick cell wall and abundant secondary metabolites like pigment. The expressions of eight members of the UDP-glycosyltransferase superfamily (Spipo2G0010600, Spipo2G0043800, Spipo16G0044000, Spipo2G0039000, Spipo14G0034300, Spipo2G0124000, Spipo5G0014300, Spipo2G0077900) and two of the cellulose synthases (Spipo28G0017100, Spipo7G0044000) involved in cell call biosynthesis were increased (Additional file 1: Table S1). Three dihydroflavonol reductases (Spipo 7G0010700, Spipo10G0000200, Spipo14-G0054900) and one flavonoid 3' , 5'-hydroxylase (Spipo-0G0155000) involved in the anthocyanin pathway were up-regulated (Additional file 1: Table S1). In addition, we found the average FPKM value for all key enzymes of lignin biosynthesis were 23 in fronds but 41 in turions, which may explain the rigidity of cell wall in turion cells to defend water pressure at the bottom of waters (Additional file 1: Table S2).
To gain a broad overview into the biological functions for DE genes, we next performed an analysis of gene ontology (GO) enrichment (Methods). We found a total of 24 enriched pathways (p < 0.01) in developing turions, whereas no enriched GO was found in fronds under the null hypothesis of the entire gene set of Spirodela (Young et al., 2010). The clustered DE genes were mainly related to response to ABA, fatty acid oxidation, and ion transportation. The GO functions of leaf senescence and cell wall modification were also highlighted ( Table 6).

Transcriptional regulation of differentially expressed genes
Transcription factors (TFs) are crucial components of regulatory systems, which initiate vital changes in gene expression. Thus, we examined TF gene models and found nine TFs were significantly changed including two ABAresponsive element binding factors (bZIP, Spipo4G0008600 and Spipo2G0055800), four Ethylene-responsive element binding factors (ERFs, Spipo0G0155100, Spipo3G0031800, Spipo20G0027700 and Spipo11G0028200), two heat shock TFs (HSFs, Spipo8G0037600 and Spipo9G0002000), and one WRKY TF (Spipo8G0045500) ( Table 5 and Additional file 1: Table S1).

ABA-responsive element binding factor
The bZIP trancription factors regulate plant development through a basic region and a leucine zipper dimerization motif that binds to DNA [56,57]. In the complete sequence of Spirodela genome [32], an exhaustive search of the bZIP superfamily was performed and 41 members identified. Among them, seven genes belong to the ABA-responsive element binding factors (ABFs), i.e., the bZIP superfamily group A due to their structural features with conserved regions C1-C2, basic regions, and leucine zippers (Figure 4) [56,58]. This group is thought to play a central role in controlling ABA-responsive gene expression in seeds and vegetative tissues via binding to ABA-responsive-elements (ABREs). For example, ABI5, one member of ABFs, induces LEA expression by binding to its promoters during seed  [58]. Here, all seven genes showed differentially increased expression levels, whereas only SpABF1 (Spipo4G0008600) was defined as a DE gene due to a significant change (Table 5). Noticeably, SpbZIP (Spipo2G0055800), another bZIP transcription factor, was significantly decreased in developing turions (Table 5). It shared leucine residues in the basic domain but missing other 2 conserved regions, corresponding to bZIP group I in Arabidopsis. Studies of group I genes from several species indicate that they might play a role in vascular development [56]. SpbZIP might positively regulate xylem and phloem development, too. Because both structure and function of turions are equivalent to seeds, less vascular tissue is needed in turions compared to fronds and the expression of SpbZIP is decreased accordingly. Thus, we conclude that a specific subset of bZIP transcription factors are involved in turion formation.

Other TFs involved in ABA-mediated gene expression
In addition to ABF TFs, other TFs were also identified to be involved in turion development. Ethylene-responsive element binding factors (ERFs) are transcription factors that are specific to plants. A highly conserved DNA binding domain, known as the ERF domain interacting directly with the GCC box in the ethylene-responsive-element (ERE), is the unique feature of this protein family [59] ( Figure 5). ERFs also play a role in a variety of developmental processes such as flower, seed development [60], and fruit ripening [61]. We identified 57 ERF genes in the Spirodela genome, where SpERF1 (Spipo0G0155100), SpERF2 (Spipo3G0031800), and SpERF3 (Spipo20G0027700) were significantly up-regulated and SpERF4 (Spipo11G0028200) down-regulated in response to turion development (Table 5). It had been reported that AtERF1, AtERF2, ATERF5 functioned as activators of GCC box-dependent transcription in Arabidopsis leaves, but AtERF3 and AtERF4 acted as repressors [57,59]. It also was shown that ERF2 and ERF4 enhanced the transcription of a reporter gene in tobacco protoplasts [62]. The three highly up-regulated ERFs in Spirodela turions should therefore play an important role in turion development.
Heat shock transcription factors (HSFs) are transcriptional activators of heat shock genes. An increasing number of studies indicated that some HSFs appeared during the maturation stage of the seed, when cell division ceased and seeds adapted to desiccation and long-term survival [63]. Here, the increased expression of two HSFs (Spipo9G0002000 and Spipo8G0037600) ( Table 5) might also indicate an important function for turion desiccation and survival during long periods of winter.
WRKY transcription factors (TFs) are key regulators of many plant processes, including the responses to biotic and abiotic stresses, senescence, seed dormancy, and seed germination [64]. In vivo and in vitro promoter-binding studies showed that WRKY TFs could either activate or repress the expression of downstream ABFs through W-box sequences present in their promoters [65]. However, whether the Spirodela WRKY TF (Spipo8G0045500) ( Table 5) is a repressor or activator needs to be further investigated.
Together, the significant changes in the expressions of ABFs, ERFs, HSF and WRKY TF reflected their obligatory regulation during turion development. Their involvement in the transition from fronds to turions and their control Figure 4 Alignment of ABF domain from Spirodela. The amino acid sequences of bZIP protein sequence from Spirodela were aligned and the conserved regions were demonstrated here. The consensus amino acids were labeled from conserved regions and highlight as motif 1 and motif 2, the primary structure of bZIP domains (basic region and leucine zipper). All members contain these four domains except SpbZIP, which only has a basic region and a leucine zipper. SpABF1-Spipo4G0008600; SpABF2-Spipo6G0055300; SpABF3-Spipo15G0021000; SpABF4-Spipo4G0111500; SpABF5-Spipo7G0034500; SpABF6-Spipo3G0017700; SpABF7-Spipo13G0002500; SpbZIP-Spipo2G0055800.  of spatial and temporal expression of target genes provides us also with new tools to create specialized traits through tailoring of chimeric genes.

cis-element
Control of gene expression is achieved through the binding of transcription factors to specific cis-elements in promoter regions of target genes [66]. To predict potential pairs of TFs and cis-elements, we scanned a 1-kb region upstream of DE genes with the PLACE database [27]. We found 30 up-regulated DE genes containing the cis-element of ABAresponsive element (ABRE: YACGTGGC) and 119 with ethylene-responsive element (ERE: GCCGCC) (Additional file 1: Table S1). These target genes of ABFs and ERFs are associated with seed dehydration (like late embryogenesis abundant proteins), regulatory transcription factor, protein kinases and phosphatases (like CPK, MAPK), carbohydrate and secondary metabolism (like cellulose synthase and stachyose synthase), and senescence-associated proteins (like Glutathione-S-transferase).

Discussion
ABA is essential for seed maturation and also enforces a period of seed dormancy so that the seeds do not germinate prematurely during unseasonably conditions. The same behavior is seen in dormant Spirodela turions that are induced by low temperature, limited nutrition, or exogenous ABA. The external stimuli rapidly induce both Ca 2+ influx and endogenous ABA synthesis [67]. In maturing seed, ABA-regulated genes include those required for the synthesis of storage reserves and the acquisition of desiccation tolerance. Ca 2+ can act as secondary messenger to activate the expression of cascade components of calciumdependent protein kinase (CPK) and mitogen-activated protein kinase (MAPK). The structure of CPK shows there are four Ca 2+ -binding EF hand domains allowing the protein to function as a Ca 2+ sensor. In addition to Ca 2+ , reversible phosphorylation also regulates kinase activity [68].
A number of studies have demonstrated that MAPKs in Arabidopsis are associated with hormone biosynthesis and signaling including ethylene and ABA [43]. Both of CPK and MAPK could phosphorylate a wide range of target proteins, including other kinases and/or transcription factors [44,57], in particular SpERF of Spipo0G0155100, Spipo3G0031800 and Spipo20G0027700, SpABF of Spi-po4G0008600 and Spipo2G0055800, SpHSF of Spipo-8G0037600 and Spipo9G0002000, and SpWRKY of Spipo8G0045500 (Table 5). The activation of TFs ultimately regulates their target genes to cease cell division but begin to accumulate secondary metabolites. As shown in flowering seeds, aspects of reserve accumulation and late embryogenesis abundant (LEA) gene expression are controlled largely by the coordinated action of transcription factors [44]. Taken together, we generated a model summarizing the signal transduction leading to Spirodela dormancy based on integration of our results and previous knowledge ( Figure 6).

Conclusions
Many studies have been concerned with seed development in plants. Seeds are the product of sexual reproduction and the segregation of Mendelian traits. They also represent a dormant state in the life cycle of the plant and they compartmentalize nutrients for growth in the absence of photosynthesis. Agriculture could not exist without these properties of plants. Here, we studied a plant that propagates by clonal division and can undergo dormancy without forming seeds. The aquatic plant Spirodela could not survive on water surface without human intervention, when the water freezes. It simply switches to dormancy and accumulates starch that allows it to sink to the bottom of the water to escape the ice. Besides low temperature, however, the same switch can be achieved with the hormone ABA that has been shown to perform the same change for seed maturation. Using such an induction with Spirodela, we can study genes that regulate dormancy. Here, we isolated total RNA, excluded ribosomal RNA before and at the onset of dormancy, sequenced them with nextgeneration technology, and identified the transcripts by mapping them back to the genome sequence. The detailed analysis of the transcriptional landscape of differentially expressed genes provides the first comprehensive view at the dormancy of aquatic plants. On the other hand, research studies have been initiated with the goal of developing duckweed species as an alternative to algae for oil production with the fact of fast growth and quick biomass accumulation [69]. The expression data for lipid and starch biosynthesis together with the turion-specific transcriptional genes from our RNA-Seq data would be the ideal targets to develop duckweeds into oil crops.

Additional file
Additional file 1: Table S1. Annotation for 362 up-or down-regulated DE genes with FPKM values and fold changes. The genes discussed in main text were labeled as bold. The genes with cis-element of ABRE or ERE were indicated with "YES". GO annotations involved in ABA response or starch biosynthesis or fatty acid oxidation were also marked accordingly.


Neuroprotection by diarylpropionitrile in mice with spinal cord injury.

The initial impact of spinal cord injury (SCI) often results in inflammation leading to irreversible damage with consequent loss of locomotor function. Minimal recovery is achieved once permanent damage has occurred. Using a mouse model of SCI we observed a transitory increase followed by a rapid decline in gene expression and protein levels of nuclear factor erythroid 2-related factor 2 (Nrf2), a master regulator of cellular anti-oxidative genes. Immediate treatment with diarylpropionitrile (DPN), a non-steroidal selective estrogen receptor ß ligand, resulted in a significant increase in Nrf2 levels, and reduction of inflammation and apoptosis compared to untreated SCI animals. Furthermore, DPN-treatment improved locomotor function within 7 days after induction of SCI. DPN acted through activation of PI3K/ Akt pathway, known to be involved in down-regulation of apoptosis and up-regulation of cell survival in injured tissues. These findings suggest that immediate activation of cellular anti-oxidative stress mechanisms should provide protection against irreversible tissue damage and its profound detrimental effect on locomotor function associated with SCI.

Pathogenesis of spinal cord injury (SCI)
is characterized as being biphasic, consisting of primary injury which causes the initial spinal cord trauma and is considered irreversible, and secondary injury which refers to the molecular and biochemical events that occur following the primary injury (Rowland et al., 2008). Earlier studies suggested that local inflammatory response and oxidative stress following SCI are the major contributors to further damage (David et al., 2012).
Thus resident microglia in the central nervous system as well as infiltrating macrophages from the periphery may further contribute to inflammation by releasing proinflammatory cytokines, such as interleukin-1β (IL-1β), as well as building up reactive oxygen species (ROS) (Pajoohesh-Ganji and Byrnes, 2011). Inflammatory response resulting from astrogliosis around the injury site inhibits the tissue repair process (Rolls et al., 2009), and the primary function of neuroprotection after SCI is to counteract the mechanisms of inflammation and oxidative stress to minimize their pathological effects. One mechanism of neural repair and prevention of cell death is via the estrogen signaling pathway through binding to estrogen receptors ERα or ERβ for the activation of downstream kinases, such as PI3K/Akt. Treatment of SCI with 17β-estradiol, which binds to both ERα and ERβ, attenuates the inflammatory response and reduces neuronal cell death (Tiwari-Woodruff et al., 2007).
Diarylpropionitrile (DPN) (2,3-bis(4-hydroxyphenyl)-propionitrile), a non-steroidal selective high affinity ligand of ERβ (80-300 folds over ERα) (Carroll et al., 2012), has neuroprotective effects in a number of neurological diseases (Kumar et al., 2013). DPN has been shown to exert anti-inflammatory role in neuroprotection by attenuating inflammatory cytokines IL-1β and IL-6 expression in mouse brain during neuroinflammation (Brown et al., 2010). DPN also increases the expression of a panel of bioenergetic enzymes and antioxidant proteins in primary rat cultured hippocampal neurons (Irwin et al., 2012). Nuclear factor erythroid 2-related factor 2 (Nrf2) has been recognized for its role in detoxification during the buildup of ROS and in the activation of phase II anti-oxidative genes in a number of CNS diseases and disorders , as well as in traumatic brain injury (Jin et al., 2008(Jin et al., , 2009 and SCI (Mao et al., 2010;Wang et al., 2012). In this study, we examined the ameliorating effects of DPN in mice from the early stage of SCI up to 7 days by measuring the mRNA expressions and protein levels of Nrf2 and of proteins involved in inflammation, apoptosis, and the pathway related to DPN neuroprotection for SCI.

Animals and preparation of SCI
A total of 114 C57Bl/6 female 3-5 month-old mice (30-35 g) were supplied by the Department of Laboratory Animal Medicine, UCLA. These mice were housed at 20-22 °C, in relative humidity of 40-60 %, and with illumination from 6 a.m. to 6 p.m. and allowed ad libitum access to food and water. The standard environmental enrichment for mice included social housing (3 animals/ cage) in traditional wire-topped cages (800 cm 2 ) with 1-cm layer of wood chip bedding. Animal care, handling and treatments were carried out according to the rules and regulations of UCLA Animal Research Committee and Department of Laboratory Animal Medicine. Mice were anesthetized with inhalation of isoflurane in oxygen-rich air. After dorsal midline incision and exposure of the lumbar vertebrae, laminectomy was performed at the L1/L2 level to expose the spinal cord. Moderate crush SCI was made using No.5 Dumont forceps (Fine Science Tools) ground down to a tip width of 0.4 mm and modified with a spacer so that at maximal closure a 0.4 mm space remained (Faulkner et al., 2004). The behavior was tested before and every 24 h after performing SCI.

Drug administration
After induction of SCI, animals were immediately subcutaneously injected laterally to the injury site with 8 mg DPN (Tocris Bioscience, Ellisville, MO)/kg of body weight (Tiwari-Woodruff et al., 2007), or with vehicle (Miglyol 812 N liquid oil; gift from Sasol North America, Houston, TX) and this treatment was repeated every 24 h until tissue collection. Normal mice were used as controls for comparison with DPNtreated and -untreated SCI animals. Tissue samples from three mice for each experiment were collected at 6, 12, 24, 48, 72 h and 7 days after induction of SCI.

Nrf2 and IL-1β mRNA expression in the injured spinal cord of mice as detected by Real-Time PCR
The region of injured spinal cord tissue was dissected, immediately frozen in liquid nitrogen and stored at -80 °C until processed. Total tissue RNA was prepared using RNeasy Mini kit (Qiagen, CA) and cDNA synthesis was performed using RETROscript ® reverse transcription kit (Ambion, TX) as previously described (Kumar et al., 2009). Quantitative (q)-PCR was conducted in SsoAdvanced TM SYBR ® Green Supermix (Bio-Rad, CA) containing 300 nM of each of the following primers; Cyclophilin A (PPIA) forward: 5'-CGAGCTGTTTGCAGACAAA G-3' and reverse 5'-TCTGTGAAAGGAGG AACCCTTA-3' primers; Nrf2 forward 5'-TGGAGAACATTGTCGAGCTG-3' and reverse 5'-CCGCCTTTTCAGTAGATGGA-3' primers; or IL-1β forward 5'-GTGAAATG CCACCTTTTGACA-3'; and reverse 5'CAA AGGTTTGGAAGCAGCC-3' primers (Kumar et al., 2009). Thermocycling (CFX96, Bio-Rad, CA) of triplicate samples was performed as follows: 5 min at 95 °C; 45 cycles of 30 s at 95 °C, 30 s at 60 °C and 30 s at 72 °C; followed by a melting curve analysis of 1 min at 95 °C, 1 min at 55 °C, 60 cycles of 5 s with temperature increase of 0.5 °C/ cycle starting from 65 °C to 95 °C. The expression level of the gene of interest was normalized to that of PPIA using the formula 2 -∆∆CT . The results were analyzed using Bio-Rad CFX manager software (Bio-Rad, CA).

Score of locomotor function of mouse hind limbs
Recovery of locomotor function was evaluated to assess the gross voluntary use of the hind limbs using open field locomotor test every 24 h after SCI induction. The behavior of animals was observed for 5 min by three individuals blinded to the experimental conditions. A simple six-point scale was used, which is found to be more appropriate for the model of upper lumbar SCI (Herrmann et al., 2008), and animals received a score for voluntary movement of each hind limb. In brief, the scale involves closely monitoring limb movement, weightbearing capability, coordinated and proper gait, movement in all joints of the hind limb, full weight support and appropriate limb position. Left and right hind limbs were scored separately and averaged.

Statistical analysis
Data were expressed as mean ± SEM. Statistical analysis was performed using oneway analysis of variance (ANOVA) followed by Student-Newman-Keul's post hoc test. P < 0.05 is considered statistically significant different among control, SCI, and DPN-treated groups.

RESULTS
Gene expression of Nrf2, involved in detoxifying ROS, was detected in mouse spinal cord tissues within 12 h after SCI, then continuously declined after 24 h until day 7 ( Figure 1A) and treatment with DPN resulted in enhancing Nrf2 gene expression, starting from 6 h up to day 7. There is a concomitant significant elevation of Nrf2 protein levels from 24 h to day 7 compared to non DPNtreated SCI group ( Figure 1B). After 6 h post SCI, increased mRNA and protein levels of IL-1β were detected in spinal cord tissues compared with normal controls. With DPN treatment, IL-1β mRNA ( Figure 1C) and protein ( Figure 1D) levels significantly decline after 6 h and 12 h respectively. Similarly, levels of the apoptosis protein, activated caspase-3, show a significant increase in SCI group compared to normal control, starting from 6 h to day 7, which was attenuated by DPN treatment after 24 h (Figure 2). After 12 h following SCI, phosphorylated-PI3K (p-PI3K) and phosphorylated-Akt (p-Akt) levels are significantly higher in DPNtreated mice compared to untreated SCI group ( Figure 3). As for the open field locomotor test, DPN-treated SCI mice show significant elevation of locomotor score after 48 h compared to untreated SCI group and continuously improved till the end of the test period (Figure 4).

DISCUSSION
In this study, we demonstrate that oxidative stress and inflammation (as evidenced by transient induction of anti-oxidative Nrf2 gene expression and a more sustained stimulation of inflammatory cytokine IL-1β mRNA and protein levels) occurred within 6-12 hours from the induction of SCI, which induced neuronal apoptotic death and dysfunction in open field locomotor activity. Treatment with DPN, a ligand of ERβ, immediately following SCI resulted in elevation of Nrf2 level, attenuation of IL-1β and activated caspase-3 levels, and improvement of locomotor function. Wang et al. (2012) have demonstrated that Nrf2-deficient mice are more susceptible to oxidative stress and show more severe neurological dysfunctions and spinal cord edema after SCI. Moreover, administration of Nrf2-activator sulforaphane provides a neuroprotective effect in SCI rats (Benedict et al., 2012). Sribnick et al. (2005) demonstrated that estrogen treatment in SCI rats attenuated inflammatory response by reducing the levels of IL-1β and NF-κB. Kumar et al. (2013) showed a decrease in activated caspase-3 after DPN treatment in experimental autoimmune encephalomyelitis mice and that DPN increases oligodendrocyte progenitor cell numbers and improves myelination. The improvement in locomotor function in DPN-treated SCI mice in our study was similar to that reported with estrogen (Sribnick et al., 2010). DPN-induced neuroprotection is dependent on kinase activities, including the PI3K/Akt signaling pathway (Mannella and Brinton, 2006). DPN treatment of SCI mice elevated levels of p-PI3K and p-Akt compared to untreated SCI animals. Activation of PI3K/Akt pathway mediates cell survival in a multiple sclerosis animal model (Kumar et al., 2013). In addition, PI3K/Akt pathway plays a key role in the regulation of Nrf2-dependent neuroprotection by inducing Nrf2 to translocate into the nucleus and activate anti-oxidative genes , and inhibition of PI3K with wortmanin attenuates Nrf2 expression (Zou et al., 2013). Besides its anti-oxidative effects through the activation of PI3K/Akt pathway, DPN likely mediates neuroprotection against SCI through its direct interaction with ERβ. To clarify whether ERβ plays a significant role in the neuroprotective effects of DPN, Zhao et al. (2011) implemented (R,R)-THC, a specific ERβ inhibitor, to confirm that the neuroprotective effects of DPN against Aβ 1-42 neurotoxicity are mediated through ERβ pathway in rat cultured hippocampal neurons. The findings from this study indicated that the oxidative stress, apoptosis and inflammatory processes accompanying SCI can, in part, be ameliorated by the immediate DPN administration, leading to partial restoration of locomotor function.