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DOI 10.1007/s00425-009-0994-3
ORIGINAL ARTICLE
Genome-wide survey of rice microRNAs and microRNA–target pairs in the root of a novel auxin-resistant mutant
Yijun Meng · Fangliang Huang · Qingyun Shi ·
Junjie Cao · Dijun Chen · Jinwei Zhang · Jun Ni ·
Ping Wu · Ming Chen
Received: 31 May 2009 / Accepted: 10 July 2009
? Springer-Verlag 2009
Abstract Auxin is one of the central hormones in plants, and auxin response factor (ARF) is a key regulator in the early auxin response. MicroRNAs (miRNAs) play an essen-tial role in auxin signal transduction, but knowledge remains limited about the regulatory network between miRNAs and protein-coding genes (e.g. ARFs) involved in auxin signal-ling. In this study, we used a novel auxin-resistant rice mutant with plethoric root defects to investigate the miRNA expression patterns using microarray analysis. A number of miRNAs showed reduced auxin sensitivity in the mutant compared with the wild type, consistent with the auxin-resistant phenotype of the mutant. Four miRNAs with sig-ni W cantly altered expression patterns in the mutant were fur-ther con W rmed by Northern blot, which supported our microarray data. Clustering analysis revealed some novel auxin-sensitive miRNAs in roots. Analysis of miRNA dupli-cation and expression patterns suggested the evolutionary conservation between miRNAs and protein-coding genes. MiRNA promoter analysis suggested the possibility that most plant miRNAs might share the similar transcriptional mechanisms with other non-plant eukaryotic genes tran-scribed by RNA polymerase II. Auxin response elements were proved to be more frequently present in auxin-related miRNA promoters. Comparative analysis of miRNA and protein-coding gene expression datasets uncovered many reciprocally expressed miRNA–target pairs, which could provide some hints for miRNA downstream analysis. Based on these W ndings, we also proposed a feedback circuit between miRNA(s) and ARF(s). The results presented here could serve as the basis for further in-depth studies of plant miRNAs involved in auxin signalling.
Keywords Auxin response element · Auxin response factor · Auxin signalling · Microarray · MicroRNA–target pairs · Rice root
Abbreviations
-NAA -Naphthalene acetic acid
ARF Auxin response factor
AuxRE Auxin response element
EMS Ethyl methanesulfonate
GO Gene Ontology
IAA3-Indole acetic acid
MiRNA MicroRNA
MT osaxr mutant
osaxr Oryza sativa auxin resistant
TF Transcription factor
TSS Transcription start site
WT Wild type
Introduction
Auxin plays a central role in plant growth and development (Leyser 2002), and the mechanisms of auxin-mediated gene regulation have been intensively studied in Arabidopsis
Electronic supplementary material The online version of this article (doi:10.1007/s00425-009-0994-3) contains supplementary material, which is available to authorized users.
Y. Meng · F. Huang · D. Chen · J. Zhang · J. Ni ·
P. Wu · M. Chen (&)
State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University,
310058 Hangzhou, People’s Republic of China
e-mail: mchen@https://www.doczj.com/doc/ea2798329.html,
Q. Shi · J. Cao · D. Chen · M. Chen
Department of Bioinformatics, College of Life Sciences, Zhejiang University, 310058 Hangzhou,
People’s Republic of China
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thaliana (Dharmasiri and Estelle 2004; Teale et al. 2006). Auxin response factors (ARFs) are the key transcription factors (TFs) in the early auxin response. They bind speci W-cally to the auxin response elements (AuxREs) and modu-late the transcription of the early auxin response genes (Guilfoyle and Hagen 2007).
MicroRNAs (miRNAs) are RNA species about 21 nucle-otides in length, involved in post-transcriptional regulation mostly through their cleavage e V ects on target transcripts in plants (Voinnet 2009). In Arabidopsis, certain miRNAs are involved in ARF-mediated auxin signalling. For instance, miR167 represses ARF6 and ARF8 at the post-transcrip-tional level (Ru et al. 2006; Wu et al. 2006), and ARF8 can modulate the transcription of certain GH3-like genes (Tian et al. 2004). These GH3-like genes catalyse the conjugation between endogenous auxin and speci W c complexes (e.g. amino acids), suggesting their essential role in balancing the level of active 3-indole acetic acid (IAA) (Staswick et al. 2005). This miR167-ARF8-GH3 pathway is conserved in rice (Yang et al. 2006). So far, 243 rice miRNAs have been discovered (miRBase Release 10.1) (Gri Y ths-Jones et al. 2006), whereas the understanding of their regulatory role remains limited.
Most research on plant miRNAs has focused on their downstream regulatory pathways, but little has been reported on their transcriptional mechanisms. Lee et al. (2004) reported that RNA polymerase II transcribes human miRNAs which suggests that miRNAs and protein-coding genes may share similar transcriptional mechanisms. Cis-acting element studies of miRNA promoters are still restricted to bioinformatics analysis (Zhou et al. 2007). Comparative analysis of both the miRNA and protein-cod-ing gene promoters has uncovered W ve cis-acting elements (e.g. AuxREs) in miRNA promoters, and a negative feed-back model between miRNAs and TFs has been proposed (Megraw et al. 2006). However, there has been little sys-tematic analysis of rice miRNAs involved in auxin signal-ling, and the auxin-speci W c regulatory network between miRNAs and their targets remains to be determined.
Here, a novel auxin-resistant rice mutant with plethoric root defects was used to investigate miRNA expression pat-terns by microarray analysis. A number of miRNAs showed greatly reduced auxin sensitivity in the mutant compared with the wild type, consistent with the auxin-resistant phe-notype of the mutant. Analysis of miRNA duplication and expression patterns suggested the evolutionary conserva-tion between miRNAs and protein-coding genes. We selected promoters of the auxin-related miRNAs for in-depth analysis. A number of potential miRNA–target pairs were identi W ed in the rice roots based on the comparative analysis of miRNA and protein-coding gene expression datasets, which could serve as a repository for in-depth miRNA downstream analysis. These W ndings led us to propose a feedback circuit between miRNA(s) and ARF(s), revealing the complexity of the regulatory network between miRNAs and their targets involved in auxin signalling. Materials and methods
Mutant library generation and screening
Rice (Oryza sativa L. ssp. indica cv. Kasalath, kindly pro-vided by Hongxuan Lin (Shanghai Institute of Plant Physi-ology and Ecology, Shanghai Institute for Biological Sciences, The Chinese Academy of Sciences, China), seeds were treated with 0.6% (V/V) ethyl methanesulfonate (EMS, Sigma, Shanghai, China) solution for 12h at 26°C in a shaker. The treated seeds were rinsed with distilled water at least six times for 4h in the shaker, and then the seeds were germinated in distilled water for 2days. Seed germination rate was assessed to optimise the EMS treat-ment intensity. The seedlings were grown in the W eld for harvesting, and the W rst-generation seeds were used for mutant screening after being germinated in distilled water for 2days. After germination, seedlings were transferred to plastic nets X oating on Yoshida nutrient solution (Yoshida et al. 1976) in plastic pots. The seedlings were grown in a growth chamber under 30°C (day)/22°C (night) and 12-h light (450 mol photons m?2s?1)/12-h dark regime. Ten-day-old seedlings were screened based on their root pheno-types.
Seedling treatments and physiological experiments Seeds were germinated in distilled water for 2days. After germination, seedlings were transferred to plastic nets X oat-ing on Yoshida nutrient solution (Yoshida et al. 1976) in plastic pots. Seedlings were grown in a growth chamber under 30°C (day)/22°C (night) and 12-h light (450 mol photons m?2s?1)/12-h dark regime. For miRNA microarray analysis and Northern blot, 7-day-old seedlings were treated with 30 M IAA for 3h. For microarray anal-ysis of protein-coding genes, 7-day-old seedlings were treated with 10 M IAA for 3h. For real-time quantitative PCR, 7-day-old seedlings were treated with 10 M -naph-thalene acetic acid ( -NAA), 10 M IAA, or 10 M 2, 4-D for 3h. For auxin sensitivity analysis, seedlings were treated with 1 M -NAA for 7 days.
Real-time qRT-PCR analysis
Real-time qRT-PCR was performed by using the Universal Probe Library and LightCycler480 Probe Master Kit on the LightCycler480 machine (Roche, Shanghai, China), fol-lowing the manufacturer’s instructions. The ampli W cation
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programme was performed at 95°C for 10s, 60°C for 25s, and 72°C for 1s. A triplicate quantitative assay was per-formed on each cDNA sample. The relative quanti W cation of each sample was determined by normalisation to the amount of rice actin cDNA detected in the same sample. The primers for OsIAA20 were 5? CATCCTCGGCTCA TACGC 3? (forward) and 5? ATCGTGCCCATCCTCTTG 3? (reverse). The primers for rice actin were 5? CAACACC CCTGCTATGTACG 3? (forward) and 5? CATCACCAGA GTCCAACACAA 3? (reverse).
MicroRNA microarray assay
Total RNA was isolated from 7-day-old seedling roots by using the miRNeasy Mini Kit (Qiagen) according to the manufacturer’s manual. The microarray assay was per-formed by LC Sciences (https://www.doczj.com/doc/ea2798329.html,). The assay started with a 2–5 g total RNA sample, which was size fractionated using a YM-100 Microcon centrifugal W lter (Millipore, Bejing, China). [Note: Although the miR-Vana kit (Ambion, Austin, TX, USA) is widely used for low-molecular weight RNA (<200 nt) isolation, no signi W-cant di V erence exists using the YM-100 W lter as indicated by the technical support of LC Sciences, Hangzhou, China.] The small RNAs (<300 nt) isolated were 3?-extended with a poly(A) tail using poly(A) polymerase. An oligonu-cleotide tag was then ligated to the poly(A) tail for subse-quent X uorescent dye staining; two di V erent tags (Cy3 and Cy5) were used for our dual-sample experiments. Hybrid-isation was performed overnight on a Para X o micro X uidic chip using a micro-circulation pump (Atactic Technologies, Houston, TX, USA) (Gao et al. 2004; Zhu et al. 2007). On the micro X uidic chip, each detection probe consisted of a chemically modi W ed nucleotide coding segment comple-mentary to the target miRNA or other RNA (control or cus-tomer-de W ned sequences) and a spacer segment of polyethylene glycol extending the coding segment away from the substrate. The detection probes were made by in situ synthesis using PGR (photo-generated reagent). Each chip contained 115 probes for detecting all known miRNAs in rice with 24 repeats. The hybridisation melting tempera-tures were balanced by chemical modi W cations of the detec-tion probes. Hybridisation was performed with 100 L 6￡SSPE bu V er (0.90M NaCl, 60mM Na2HPO4, 6mM EDTA, pH 6.8) containing 25% formamide at 34°C. Subse-quent hybridisation detection used X uorescence labelling with tag-speci W c Cy3 and Cy5 dyes. Hybridisation images were collected using GenePix 4000B (Molecular Device, Sunnyvale, CA, USA) and digitised using Array-Pro image analysis software (Media Cybernetics, Bethesda, MD, USA). Data were analysed by W rst subtracting the back-ground and then normalising the signals using a LOWESS W lter (Bolstad et al. 2003). For two-colour experiments, the ratio of the two sets of detected signals (log2 transformed, balanced) and P values of the t tests were calculated; di V er-entially detected signals were those with P values <0.01.
A V ymetrix microarray assay
Total RNA was isolated from 7-day-old seedling roots by using Trizol (Invitrogen, Beijing, China) according to the manufacturer’s manual. RNA samples were processed according to the procedure recommended by A V ymetrix’s manual. Single-stranded and then double-stranded cDNA were synthesised using the SuperScript double-stranded cDNA synthesis kit (Invitrogen). A portion of the resulting double-stranded cDNA served as the template for generat-ing biotin-tagged cRNA using the GeneChip IVT labelling kit (A V ymetrix, Shanghai, China). A total of 15 g of the resulting biotin-tagged cRNA was fragmented to a size range of 35–200 bases following the instructions. Subse-quently, 10 g of this fragmented target cRNA was hybri-dised at 45°C with rotation for 16h to probe sets present on an A V ymetrix rice genome array. The GeneChip arrays were washed and then stained using streptavidin–phycoery-thrin on an A V ymetrix Fluidics Station 450 followed by scanning on a GeneChip Scanner 3000. Hybridisation data were analysed using GeneChip Operating Software 1.2 and dChip software (Li and Wong 2001).
MicroRNA Northern blot
Total RNA was isolated from 7-day-old seedling roots using Trizol (Invitrogen) according to the manufacturer’s instructions. A total of 30 g of total RNA was used for loading and were dissolved in a 15% (w/v) Tris-borate-EDTA PAGE gel with 8M urea by electrophoresis at 300V for 5h. The low-molecular-weight RNAs on the PAGE gel were then electro-blotted onto a Hybond-N+ membrane (Amersham Biosciences, Hong Kong). The membrane was UV cross-linked and hybridised using Den-hardt’s solution (USB Corp., Cleveland, OH, USA). Anti-sense oligonucleotide probes were prepared by end-labelling with 32P- ATP using T4 polynucleotide kinase (TaKaRa, Otsu, Shiga, Japan) according to the manufac-turer’s instructions. Hybridisation was carried out at 50°C, and the blot was reused after washing and stripping. The original protocol was obtained from Bartel’s lab, see (http:/ /https://www.doczj.com/doc/ea2798329.html,/bartel/pub/protocols.html) for details. Clustering analysis
Data normalisation was carried out using a cyclic LOWESS method (Bolstad et al. 2003). The normalisation served to remove system-related variations, such as sample amount variations, di V erent labelling dyes and signal gain
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di V erences of scanners so that biological variations could be validly revealed. Among 243 miRNAs (miRBase Release 10.1), 118 members with detectable expression data for 12 experimental combinations (two samples￡two treatments￡three biological replicates) were recruited, and the expression data averaged from three biological rep-licates were used for clustering analysis. Then, the miRNA expression pro W le was sorted using a hierarchical clustering method (Eisen et al. 1998) and the heatmap was drawn with R language (Ihaka and Gentleman 1996). For the clustering analysis, we used the program heatplus provided by Bio-conductor (https://www.doczj.com/doc/ea2798329.html,).
Duplication and expression pattern analysis
All miRNAs in the clustering analysis were marked on the rice chromosomes except for osa-miR156j, osa-miR166j, osa-miR396e and osa-miR444, which had no available locus information (miRBase Release 10.1). Gene duplica-tion segments (500kb) containing these miRNAs were retrieved from TIGR (https://www.doczj.com/doc/ea2798329.html,/tdb/e2k1/osa1/ segmental_dup/index.shtml). MicroRNAs with similar expression patterns, located in duplication segment pairs, were linked. Because the expression levels of miRNAs with the same mature sequences were indistinguishable, they were considered to have the same expression pattern. MicroRNA promoter selection and cis-acting
element analysis
MiRNA promoters were obtained mainly following by the rule mentioned previously (Zhou et al. 2007). First, when a precursor (pre-) miRNA [all sequence information on pre-miRNAs including the 5?W rst nucleotide was retrieved from miRBase, miRBase Release 10.1; https://www.doczj.com/doc/ea2798329.html,/cgi-bin/sequences/mirna_summary.pl?org=osa)] and its closest upstream gene were unidirectional—if the distance between them was longer than 2,400bp—the 2,000-bp sequence upstream of the pre-miRNA was retrieved. Otherwise, the sequence between the site 400bp downstream of the upstream gene and the W rst nucleotide of the miRNA precursor was used. Second, when a pre-miRNA and its closest upstream gene were convergent—if the distance between them was longer than 4,000bp—the 2,000-bp sequence upstream of the precursor was obtained. Otherwise, the sequence from the precursor to the middle point between the upstream gene and the precursor was retrieved. AuxREs in miRNA promoters were searched by our in-house tool written with Perl language, and the distri-bution patterns of other cis-acting elements were analysed by using PlantCARE (http://bioinformatics.psb.ugent.be/ webtools/plantcare/html) (Lescot et al. 2002). These results were used for further analysis.Distribution pattern analysis of TSS, TATA-box
and CAAT-box
Both the transcription start site (TSS) and the TATA-box in miRNA promoters were searched by using TSSP (http://www. https://www.doczj.com/doc/ea2798329.html,/berry.phtml?topic=tssp&group=programs& subgroup=promoter) (Shahmuradov et al. 2003). Considering the result, the CAAT-box was selected from the search results produced by PlantCARE (Lescot et al. 2002). The distribution patterns of the three cis-acting elements were depicted by scatter plot using R language (Ihaka and Gentle-man 1996) and simulated by the trend curves using the non-linear-W tting loess method (Cleveland and Devlin 1988).
Target prediction and functional classi W cation
Target prediction was performed by using miRU (http:// https://www.doczj.com/doc/ea2798329.html,/miRNA/miRU.htm) (Zhang 2005) and CSRDB (https://www.doczj.com/doc/ea2798329.html,/smrnas/) (Johnson et al. 2007). To obtain comprehensive results, the strin-gency of the miRU prediction was set to be the lowest [score for each 20 nt: 3.5, G:U wobble pairs: 7, indels: 2, other mismatches: 5, and dataset 1: TIGR Rice Genome mRNA (OSA1 release 5, 01/23/2007)]. Putative targets were classi W ed based on their functions by using Gene Ontology (GO) annotations. GO annotations were mainly obtained from TIGR (https://www.doczj.com/doc/ea2798329.html,/ data_download.shtml), and about 55% of the targets were annotated. Some GO annotations were obtained from GRAMENE (https://www.doczj.com/doc/ea2798329.html,/protein/index.html# browse). BLAST provided by Gene Ontology was used (https://www.doczj.com/doc/ea2798329.html,/cgi-bin/amigo/go.cgi?search_ constraint=terms&action=replace_tree) to annotate the remaining targets according to the information for Arabid-opsis. Finally, 123 genes remained unannotated. A Perl script was developed to obtain the GO annotations of a gene from Gene Ontology. The targets were classi W ed mainly based on the W rst o V spring node annotations belong-ing to molecular function, biological process, or cellular component, depicted with pie charts. Because many targets have two or more GO hits, the number of total hits can be bigger than that of the total targets. The percentage was derived from speci W c hits divided by total hits.
Results
MicroRNA microarray analysis in the auxin-resistant mutant
A rice (O. sativa L. ssp. indica cv. Kasalath) mutant with plethoric root defects was isolated from an EMS-generated mutant library. It was impaired in lateral root, adventitious
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root and root cap development (Fig.1a, g). For wild-type (WT) seedlings, the root elongation was greatly inhibited and the root hairs proliferated towards the root tip under 7-day 1 M -NAA treatment (Fig.1b, d); however, these features were not observed in the mutant (Fig.1c, e). More-over, the induction of OsIAA20 (Jain et al. 2006), an early auxin response gene, was remarkably inhibited in the mutant after transient auxin treatment (Fig.1h). Based on the phenotype characterised above, the mutant was desig-nated as osaxr (O. sativa auxin resistant).
Fig.
1The root phenotype of the auxin-resistant rice mutant osaxr . a Seven-day-old
seedlings of wild type (WT ) (left ) and osaxr (right ) under normal culture conditions. The lateral root and adventitious root defects of osaxr are shown. b The root phenotype of 7-day-old WT under 1 M -naphthalene acetic acid ( -NAA ) treatment. c The root phenotype of 7-day-old osaxr under 1 M -NAA treatment. d The root hairs of 7-day-old WT under 1 M -NAA treatment. e The root hairs of 7-day-old osaxr under 1 M -NAA treatment. f The root cap structure of 7-day-old WT under normal culture conditions. g The root cap structure of 7-day-old osaxr under normal culture con-ditions. h Real-time qRT-PCR analysis of OsIAA20 expression in rice roots. The relative expres-sion levels of OsIAA20 were averaged from three biological replicates. The error bars repre-sent standard errors. CK normal culture conditions, NAA 10 M -NAA treatment for 3h, IAA 10 M 3-indole acetic acid treat-ment for 3h, 2, 4-D 10 M 2, 4-dichlorophenoxyacetic acid treatment for 3h
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So far, a number of miRNAs have been reported to be involved in auxin signalling or root development (Guo et al. 2005; Ru et al. 2006; Wu et al. 2006; Yang et al. 2006). To investigate the genome-wide expression patterns of miRNAs in osaxr, we performed a microarray study. Among 243 miRNAs (miRBase Release 10.1) (Gri Y ths-Jones et al. 2006), 118 members with detectable expression data for 12 experimental combinations (two samples￡two treatments￡three biological replicates) were clustered (Fig.2). Based on their expression patterns, all of the miRNAs could be classi W ed into eight major clusters (Fig.2). We selected the miRNAs (osa-miR164abf, osa-miR167d-j, osa-miR171g and osa-miR390) with signi W cantly changed expression patterns in osaxr for Northern con W rmation (Fig.3).
[Since not all 12 expression data of osa-miR171g were present according to the microarray data (Table S1 in Elec-tronic Supplementary Material), osa-miR171g was not included in the clustering analysis (Fig.2).] The results were consistent with our microarray data.
Auxin sensitivity of rice miRNAs
In WT, 33.1% of the clustered miRNAs were sensitive (over 1.5-fold change compared with mock treatment) to exogenous IAA treatment (Table S1). At the twofold change threshold, only 5.1% were identi W ed as auxin sensi-tive. Consistent with previous results in Arabidopsis (Mallory et al. 2005), IAA treatment did not signi W cantly in X uence the auxin-related rice homologous miRNAs, such as osa-miR160, osa-miR164, and osa-miR167. Interest-ingly, many auxin-sensitive rice miRNAs revealed by our analysis are not implicated in the auxin-signalling pathway; instead, they or their homologues, such as osa-miR395 and osa-miR169, are reported to be implicated in nutrition metabolism or stress response (Jones-Rhoades and Bartel 2004; Chiou 2007; Sunkar et al. 2007; Zhao et al. 2007). In osaxr, the number of auxin-sensitive miRNAs was greatly reduced (3.4% with 1.5-fold change compared with mock treatment; 0.8% with twofold change and only osa-miR528 was observed) (Table S1).
Duplication and expression pattern analysis
of rice miRNAs
All of the miRNAs in the clustering analysis were included for the duplication and expression pattern assay. Protein-coding gene duplication segments containing these miRNA genes were retrieved from TIGR (https://www.doczj.com/doc/ea2798329.html,/tdb/ e2k1/osa1/segmental_dup/index.shtml). Our results showed that certain members of the miR156, miR159, miR160, miR166, miR167, miR168, miR169, miR171, miR319, miR394, miR397, and miR806 families with simi-lar expression patterns were located in the duplication seg-ment pairs (Fig.4). Potential polycistrons formed by two or more miRNAs were scattered on the rice chromosomes (Fig.4), and most consisted of the same family members.
osa-miR159c and osa-miR159d with a similar expression pattern cluster within a region of <10Kb. osa-miR159ab and osa-miR159f also had a similar expression pattern, but they were far from each other on the same chromosome (Fig.S1 in Electronic Supplementary Material and Fig.4). The expression patterns of osa-miR156k and osa-miR156l on di V erent chromosomes were also quite uniform (Fig.2). With respect to the miRNAs from di V erent families, osa-miR160a–d and osa-miR171b–f had a similar expression pattern, as did osa-miR171h and osa-miR390 (Fig.2).
MicroRNA promoter characterisation
First, the promoters of abnormally expressed miRNAs in osaxr (Table1) were recruited (Data S1) following the rule proposed by Zhou et al.(2007). The W rst residue of pre-miRNA was de W ned as the boundary for promoter collec-tion. We used TSSP (Shahmuradov et al. 2003) to search for the TSS and the TATA-box, and used PlantCARE (Lescot et al. 2002) to search for the CAAT-box. The results indicated that the relative distributions of the three cis-acting elements in these miRNA promoters (data avail-able in Table S3) were quite similar to those of the RNA polymerase II-dependent protein-coding genes in eukary-otic organisms (Breathnach and Chambon 1981) (Fig.5).
Cis-acting elements in miRNA promoters were searched by PlantCARE (Lescot et al. 2002). Certain cis-acting ele-ments are family speci W cally distributed (Table1). The MSA-like element involved in cell cycle regulation was present in the miR160, miR169, and miR528 families, while the Motif I, implicated in root-speci W c expression, was present in the miR167 and miR169 families. The NON-box element involved in meristem speci W c activation was found only in osa-miR159e.
For auxin-speci W c cis-acting element analysis, typical AuxREs were recruited, and their distribution patterns were characterised (Table1). We identi W ed DR5-related sequences (Ulmasov et al. 1995) in the promoters of osa-miR160f and osa-miR164a (Table1). Previous experiments showed that the proper combination of GAGACA and the TATA-box could be bound by OsARF1 speci W cally, whereas TGTCTC alone could not (Inukai et al. 2005). This information opens up the possibility that in addition to typi-cal AuxREs, co-elements are also required for ARF binding in some cases. Therefore, W ve short AuxRE variants were combined with the TATA-box to generate W ve combina-tions with relatively high ARF-binding speci W city and probability. osa-miR171b and osa-miR171c had at least one of the W ve combinations of AuxREs and the TATA-box located in similar upstream regions, as did osa-miR164a
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and osa-miR164f (Table1). osa-miR171h and osa-miR390 exhibited similar expression patterns (Fig.2), and they also had combinations of AuxREs and the TATA-box with sim-ilar distribution patterns. These results led to the possibility that auxin-speci W c cis-acting elements play a regulatory role in miRNA transcription under certain conditions.
To demonstrate that AuxREs have a speci W cally high occurrence in the auxin-related miRNA families (Table1),
Fig.
2Clustering analysis of microRNA expression data. The miRNA
microarray data (Table S1) were sorted by hierarchical clustering method (Eisen et al. 1998). The intensity of blue and yellow colour indicates the relative expression levels. The clustering result was sort-ed into eight major clusters with colour bars marked on vertical axis. The histograms simulating the expression patterns of the correspond-ing clusters are presented on the right. CK normal culture conditions, IAA 30 M IAA treatment for 3h, WT wild type, MT osaxr mutant
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all rice miRNA promoters (data S1) were recruited for the AuxRE distribution frequency calculation (Table
S4). The results indicated that AuxREs occurred more frequently in
auxin-related miRNA families than in other miRNA fami-lies (5.69 AuxREs per each auxin-related miRNA promoter vs. 4.42 AuxREs per each additional miRNA promoter)(Fig.6a, b). This di V erence was signi W cant (t test,P =0.0163). When only DR5, DR5R, ER9 and the W ve com-binations of AuxREs and the TATA-box were analysed, the di V erence was even more signi W cant (0.56 AuxREs per each auxin-related miRNA promoter vs. 0.21 AuxREs per each additional miRNA promoter; t test, P =0.0091) (Fig.6c, d).MicroRNA–target pairs and potential feedback circuit between microRNA(s) and ARF(s)
All rice miRNA targets were predicted by miRU (Zhang 2005) and CSRDB (Johnson et al. 2007). We classi W ed the targets into three categories based on TIGR GO annotations (https://www.doczj.com/doc/ea2798329.html,/data_download.shtml ):molecular function, biological process and cellular compo-nent (Fig.S2). Considering molecular function, 4.13% of the targets were identi W ed as having RNA polymerase II TF activity, and 0.98% of the targets were identi W ed as being involved in auxin response in biological process. Both of the target groups contained ARFs.
To investigate the expression patterns of miRNA targets,we performed microarray analysis for protein-coding genes (Table S5). Considering the major cleavage e V ect of plant miRNAs on their target mRNAs, our comparative analysis of miRNA and protein-coding gene expression datasets revealed a number of reciprocally expressed miRNA–target pairs. Fifteen pairs were found under normal culture condi-tions (Table 2a), and 33 pairs were found under IAA treat-ment (Table 2b).
Yang et al. (2006) reported that OsARF6(LOC_Os02g06910) and OsARF12 (LOC_Os04g57610)were genuine targets in cultured rice cells. Thus, OsARF6 is an in vivo target of the miR167 family in rice. It is also strongly supported by the fact that OsARF6 is upregulated in osaxr with repressed expression of the miR167 family (Fig.S3). The promoters of some miR167 family members have speci W c AuxREs with high ARF-binding potential (Table 1), suggesting that OsARF6 probably regulates the transcription of certain miR167 family member under spe-ci W c conditions. Thus, we propose a feedback circuit between the miR167 family and OsARF6 (Fig.S4).
Discussion
A number of microRNAs are expressed abnormally in osaxr
Our clustering analysis showed that many miRNAs were abnormally expressed in osaxr , including those with
Fig.3Veri W cation of microRNA microarray data by Northern blot.a osa-miR164abf . b osa-miR167d–j . c osa-miR171g . d osa-miR390.Ethidium bromide-stained 5S rRNAs/tRNAs were used as loading controls. CK normal culture conditions, IAA 30 M IAA treatment for 3h, WT wild type, MT osaxr mutant
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signi W cantly changed expression levels or reduced auxin sensitivity compared with WT (Fig.2). Many targets of these miRNAs are TFs involved in auxin signalling or root development (Table1). Consistent with the microarray data, the Northern results showed that osa-miR167d-j, osa-miR171g and osa-miR390 were intensively repressed in osaxr (Fig.3b–d) and that their putative targets were ARFs, Scarecrow-like TFs and TAS3, respectively. Two bands appeared on the blot of osa-miR164abf (Fig.3a), and the upper band was consistent with the microarray data. In Ara-bidopsis, the two-band expression pattern of the miR164 family was also observed and was organ-speci W c (Dunoyer et al. 2004). Guo et al. (2005) reported that ath-miR164 directed NAC1 mRNA cleavage to downregulate the auxin signal for lateral root development. Considering the lateral root defect of osaxr, we suggest that the upper band repre-sents the functional osa-miR164abf, whereas the lower band represents low-weight molecules with unknown func-tion or only the non-speci W c hybridisation signal. Thus, the higher expression level of osa-miR164abf in osaxr is a rea-sonable explanation for its lateral root defect. However, this hypothesis requires experimental validation.
MicroRNA auxin sensitivity is greatly reduced in osaxr The number of auxin-sensitive miRNAs in osaxr was greatly reduced compared with WT. This W nding indicates that miRNAs in the roots of osaxr are much less sensitive to exogenous auxin, consistent with the auxin-resistant pheno-type of the mutant (Fig.1c, e). In addition, a number of auxin-sensitive miRNAs in WT are not involved in the auxin-signalling pathway. Instead, they or their homo-logues in Arabidopsis, such as osa-miR395 and osa-miR169, are involved in nutrition metabolism or stress response (Jones-Rhoades and Bartel 2004; Chiou 2007; Sunkar et al. 2007; Zhao et al. 2007). Considering the widespread signal interactions between hormones and nutrition or stress in plants, the results suggest that miR-NAs may also mediate these signal interactions.
Some rice miRNAs share an overlapping duplication history with protein-coding genes
Duplication and expression pattern analysis show that cer-tain members of the miR156, miR159, miR160, miR166, miR167, miR168, miR169, miR171, miR319, miR394, miR397 and miR806 families with similar expression pat-terns are located in the duplication segment pairs of rice protein-coding genes (Fig.4). Base on the data provided by TIGR (https://www.doczj.com/doc/ea2798329.html,/tdb/e2k1/osa1/segmental_dup/ index.shtml), the putative duplicated protein-coding genes within the duplication segment pairs usually have analo-gous functions or even are the same family members. Thus, rice miRNAs and protein-coding genes may share an
Fig.4
Duplication and expression pattern analysis of rice microR-
NAs. All of the miRNAs in clustering analysis (Fig.2) were marked on the rice chromosomes according to their locus information (miR-Base Release 10.1). All duplication segments containing these miR-NAs were retrieved from TIGR (https://www.doczj.com/doc/ea2798329.html,/tdb/e2k1/osa1/ segmental_dup/index.shtml). The duplication segment pairs are shown with the same colours. In the duplication segment pairs, the miRNAs with similar expression patterns were linked. Both light and dark grey duplication segments are odd ones, whose counterparts (not shown) possess no analysed miRNAs. Dark grey segments overlap-ping with other segments were marked with asterisks. The scale bar on the left indicates the physical distance approximately. The number on the top of each chromosome represents the corresponding chromo-some number
Planta Table1Expression data, putative targets and cis-acting element search results of miRNAs abnormally expressed in osaxr
MiRNA MiRNA expression data (average)Putative target
families a Promoter cis-acting element analysis b
CK WT IAA WT CK MT IAA MT
osa-miR159a20,10320,50010,69810,846MYB transcription
factor AuxRR-core c(?245);
TGA-element j(?16, ?1780); TGTCTC m(?1568)
osa-miR159b–
osa-miR159c12,00810,3356,0425,400MBS f(?612, ?842, ?918);
TGTCTC(?713)
osa-miR159d12,95111,6266,6126,099–
osa-miR159e12,17410,5886,1265,549MBS(?846, ?1342, ?1977);
NON-box i(?403); TGTCTC(?666)
osa-miR159f18,48618,3719,7449,733CCGTCC-box e(?1203); MBS(?811, ?1770)
osa-miR160a580771356392Auxin response factors MBS(?247); TGTCTC(?1713)
osa-miR160b MBS(?32, ?52, ?1233); MSA-like h(?341)
osa-miR160c CAT-box d(?1081, ?1127, ?1749, ?1766);
CCGTCC-box(?1248);
TGTCTC(?811, ?1689);
TGTCTC*TATA-box q(?1689)
osa-miR160d CCGTCC-box(?509, ?1541);
MBS(?580, ?1234); TGTCTC(?291, ?1631) osa-miR160e587774343396CAT-box(?347); TGTCTC(?133)
osa-miR160f213299160196MBS(?258, ?368, ?861);
TGTCTC(?158, ?152); DR5n(?158)
osa-miR164a2,2321,74410,9548,374NAC domain proteins CAT-box(?386); CCGTCC-box(?1592, ?1666);
MBS(?552, ?612, ?1083, ?1217, ?1653);
TGTCTC(?262, ?175); DR5(?262);
TGTCTC*TATA-box(?175)
osa-miR164b AuxRR-core(?1373); CAT-box(?322, ?797);
MBS(?270); AATAAG*TATA-box t(?1518) osa-miR164f MBS(?430, ?1616, ?1641); TGTCTC(?245);
GAGACA*TATA-box p(?250)
osa-miR164c2,6242,03212,5599,596MBS(?534)
osa-miR164d2,3561,83711,3018,593CCGTCC-box(?556);
MBS(?343, ?379, ?616, ?1267, ?1588, ?1852) osa-miR164e3,7973,43116,25513,249CAT-box(?216); CCGTCC-box(?289, ?527);
MBS(?1141, ?1191); dOCT k(?1891);
TGTCTC(?382)
osa-miR167a6,8965,8901,4711,475Auxin response factors CAT-box(?1070); MBS(?449);
TGA-element(?1662); TGTCTC(?1676)
osa-miR167b MBS(?390); TGTCTC(?402);
AATAAG*TATA-box(?790)
osa-miR167c TGTCTC(?1680)
osa-miR167d8,3137,3491,7431,834CAT-box(?276); MBS(?294, ?480, ?1348);
TGTCTC(?1428); TGTCAC*TATA-box s(?441) osa-miR167e CAT-box(?83, ?162); MBS(?1690);
MRE g(?1146, ?1960);
TGTCTC(?1563, ?151, ?35)
osa-miR167f MBS(?1030); motif I l(?376);
TGTCTC(?930, ?1087)
osa-miR167g AuxRR-core(?496); MBS(?1548);
MRE(?1431); TGA-element(?407, ?647);
TGTCTC(?1026); TGTCTC*TATA-box(?1026) osa-miR167h CAT-box(?249);
CCGTCC-box(?1040); MBS(?855)
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overlapping duplication history to some extent. Recently,Axtell and Bowman (2008) reported that many miRNA family members arose through genome-wide duplication events. Maher et al. (2006) demonstrated that both miRNAs and genes had high birth and death rates during duplication;thus, they might not di V er from each other. In addition,recent results have shown that the evolutionary history of miRNA families seems to be similar to that of the protein-coding gene families in plants (Li and Mao 2007). Our results are consistent with these reports to some extent. In Arabidopsis, several miRNA genes originated by inverted duplication of their target genes (Allen et al. 2004).
Table 1continued – no information available, CK normal culture conditions, IAA 30 M IAA treatment for 3h, WT wild type, MT osaxr mutant a
The results are based on references (Llave et al. 2002; Allen et al. 2005; Guo et al. 2005; Wang et al. 2005; Williams et al. 2005; Ru et al. 2006;Wu et al. 2006; Yang et al. 2006; Liu et al. 2007; Reyes and Chua 2007) and miRU prediction b
Double-stranded miRNA promoters were collected for cis -acting element analysis c
AuxRR-core: cis -acting element involved in auxin responsiveness d
CAT-box: cis -acting element related to meristem expression e
CCGTCC-box: cis -acting element related to meristem speci W c activation f
MBS: MYB binding site involved in drought-inducibility g
MRE: MYB binding site involved in light responsiveness h
MSA-like: cis -acting element involved in cell cycle regulation
i NON-box: cis -acting element related to meristem speci W c activation j
TGA-element: auxin-responsive element k
dOCT: cis -acting element related to meristem speci W c activation l
motif I: cis -acting element root speci W c m–t
AuxREs. TATA-box: TATA(A|T)A(T|A)(A|G). Asterisk represent any nucleic acid compositions <100 nt. ‘|’ means ‘or’. The annotations of 3–12 were adopted from PlantCARE
MiRNA
MiRNA expression data (average)Putative target families a
Promoter cis -acting element analysis b
CK WT
IAA WT CK MT IAA MT
osa-miR167i AuxRR-core(?1342); CAT-box(?101, ?1300); MBS(?1322); TGTCTC(?124)osa-miR167j
AuxRR-core(?653, ?1561); CCGTCC-box(?676); MBS(?478, ?555, ?750, ?822, ?1242);
TGA-element(?592, ?1823); TGTCTC(?1387)
osa-miR171a
172
304
130
181
GRAS domain transcription factors (SCARECROW-like)CAT-box(?442); MBS(?164, ?227, ?311, ?394, ?1036, ?1097); TGA-element(?1271); TGTCTC(?691, ?1771)osa-miR171b 7721,066498516
AuxRR-core(?18); CAT-box(?153, ?1430);
CCGTCC-box(?1794); MBS(?68, ?223, ?847);
MRE(?1707); TGA-element(?83); TGTCTC(?1407); TGTCTC*TATA-box(?1407); AATAAG*TATA-box(?1285)
osa-miR171c CAT-box(?708, ?1521); TGA-element(?677, ?1059); TGTCTC(?1440); GAGACA*TATA-box(?1445)osa-miR171d CCGTCC-box(?776); MRE(?938); TGTCTC(?601)osa-miR171e
AuxRR-core(?231); CCGTCC-box(?1360); MRE(?660); TGA-element(?472); TGTCTC(?109, ?474, ?599, ?1451)osa-miR171f MBS(?503, ?831, ?1075); TGA-element(?155); TGTCTC(?1420)
osa-miR171g 4024591533MBS(?748, ?1507); TGTCTC(?647, ?832, ?1754); AATAAG*TATA-box(?273)osa-miR171h 3694468397CAT-box(?469); MBS(?507, ?645); TGTCTC(?855); TGTCAC*TATA-box(?567)osa-miR3904725083645Leu-rich repeat proteins; TAS3CAT-box(?588); MBS(?335, ?738, ?882, ?924); TGTCTC(?331, ?694); TGTCTC*TATA-box(?331)osa-miR528
1,758
911
4,608
1,329
–
CCGTCC-box(?901); MSA-like(?278)
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Whether the same mechanism exists in rice needs to be fur-ther elucidated.
The chromosome distribution shows that most potential miRNA polycistrons are made up of the same family mem-bers, which is consistent with recent observations (Cui et al. 2009). They probably arise from tandem duplication events. In addition, the miRNA clusters with similar expression patterns, such as osa-miR159c and osa-miR159d , may share common promoters. In contrast to a previous W nding (Jiang et al. 2006), in the current work, we found that miRNAs within the same families, such as the miR159 family, share quite uniform expression patterns.AuxREs have a highly speci W c occurrence in auxin-related miRNAs
Our TSS, TATA-box and CAAT-box distribution analysis showed that the rice miRNA promoters share similar char-acteristics with the RNA polymerase II-dependent protein-coding gene promoters (Fig.5) (Breathnach and Chambon 1981). Although Breathnach and Chambon (1981) charac-terised non-plant eukaryotic promoters, our result is consis-tent with a previous report that RNA polymerase II transcribes most miRNAs (Lee et al. 2004). We observed that the distributions of the three cis -acting elements were consistently upstream-shifted. The explanation is that pri-mary miRNA is transcribed upstream of the boundary that we de W ned for promoter collection. In addition, our results also support the hypothesis proposed by Zhou et al. (2007)that miRNA core promoters are close to precursor miR-NAs.
Auxin-speci W c cis -acting element analysis showed that TGTCTC, a typical AuxRE, existed in most miRNA fami-lies because of its poor sequence speci W city (Table S4).
DR5 can confer auxin responsiveness to the minimal ?46CaMV 35S promoter (Ulmasov et al. 1995, 1997). DR5-related sequences are present in the promoters of osa-miR160f and osa-miR164a (Table 1), which have homologs in Arabidopsis that play key roles in auxin signalling (Guo et al. 2005; Wang et al. 2005; Liu et al. 2007).
To demonstrate that the AuxREs have a highly speci W c occurrence in the auxin-related miRNA families (Table 1),all rice miRNA promoters (data S1) were recruited for the AuxRE distribution frequency calculation (Table S4). Our results demonstrated that AuxREs were more frequently present in the promoters of auxin-related miRNAs.Potential miRNA–target pairs in rice roots
Comparative analysis of miRNA and protein-coding gene expression datasets revealed a number of reciprocally expressed miRNA–target pairs. Fifteen pairs were found under normal culture conditions (Table 2a), and 33 pairs were found under IAA treatment (Table 2b). Similar to Arabidopsis (Gustafson et al. 2005; Wang et al. 2005; Wu et al. 2006; Liu et al. 2007), the miR160 and miR167 fami-lies in rice have corresponding ARF targets. ath-miR390positively regulates AtTAS3 to produce trans -acting small interfering RNA (ta-siRNA), which has AtARF2, AtARF3and AtARF4 as targets (Allen et al. 2005; Gustafson et al.2005; Williams et al. 2005). We retrieved the sequence information for ta-siRNA encoded by OsTAS3 (Williams et al. 2005) for target prediction and identi W ed OsARF2,OsARF3 and OsARF4 as the putative targets of OsTAS3.ath-miR164 regulates several NAC domain-encoding genes involved in auxin signal transduction for lateral root devel-opment (Xie et al. 2000; Guo et al. 2005; Gustafson et al.2005). Four osa-miR164–NAC pairs were predicted under
Fig.
5The basic characteristics of microRNA promoters are similar to those of the RNA polymerase II-dependent pro-tein-coding genes. The promot-ers of abnormally expressed miRNAs in osaxr (Table 1) were recruited for the analysis. The distribution patterns of the TSS, the TATA-box and the CAAT-box in the miRNA promoters (Table S3) were depicted by scatter plot and simulated by trend lines using loess method (Cleveland and Devlin 1988). The Y -axis represents the
distance from the 5? end of the pre-miRNAs
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both normal culture conditions and IAA treatment (Table2). Our prediction results additionally showed that osa-miR396abde targeted LOC_Os03g51970 (Table2), consistent with a previous report (Sunkar et al. 2005). ath-miR408 is involved in copper utilisation (Abdel-Ghany and Pilon 2008). Interestingly, four osa-miR408–target pairs were predicted under IAA treatment, and all of the targets were copper related (Table2b). Homologous targets of the
Fig.6
AuxREs have speci W cally high occurrence in the promoters of
the auxin-related microRNAs. a The numbers of the 16 AuxREs pos-sessed by each miRNA family. b The average numbers of the 16 Aux-REs possessed by one miRNA in each family were calculated and depicted with blue squares. Red dash line represents the average num-bers of the 16 AuxREs possessed by one miRNA. c The numbers of the eight AuxREs with relatively high ARF-binding speci W city and poten-tial possessed by each miRNA family. d The average numbers of the eight AuxREs possessed by one miRNA in each family were calcu-lated and depicted with blue squares. Red dash line represents the aver-age numbers of the eight AuxREs possessed by one miRNA
Planta Table2Potential miRNA–target pairs with reciprocal expression patterns in rice roots
miRNA miRNA CK
log2(MT/WT)a Target CK
log2(MT/WT)b
TIGR locus name TIGR annotation c miRU d CSRDB
a. Normal culture conditions
osa-miR164c 2.259?2.184LOC_Os02g36880.1–3NAC domain protein NAC5Yes Yes osa-miR164c 2.259?6.644LOC_Os09g36490.1Collagen, type IV, alpha 5Yes osa-miR164a/b/f 2.295?2.184LOC_Os02g36880.1–3NAC domain protein NAC5Yes Yes osa-miR164d 2.262?2.184LOC_Os02g36880.1–3NAC domain protein NAC5Yes Yes osa-miR164d 2.262?2.000LOC_Os01g59120.1Cyclin IaZm Yes
osa-miR164d 2.262?1.737LOC_Os09g30486.1Fasciclin-like arabinogalactan
protein 7 precursor
Yes osa-miR164e 2.098?2.184LOC_Os02g36880.1–3NAC domain protein NAC5Yes Yes osa-miR528 1.390?1.737LOC_Os01g21070.1Endoglucanase 1 precursor Yes
osa-miR528 1.390?4.322LOC_Os01g03620.1Copper ion binding protein Yes
osa-miR169a 1.569?2.474LOC_Os03g11900.1Sugar transport protein 8Yes osa-miR396d/e0.850?2.556LOC_Os03g51970.1Growth-regulating factor 1Yes
osa-miR166i/j0.819?1.599LOC_Os03g10440.11,4-Beta-xylanase Yes
osa-miR397b0.862?2.644LOC_Os03g16610.1L-Ascorbate oxidase precursor Yes
osa-miR397b0.862?3.184LOC_Os12g15680.1L-Ascorbate oxidase precursor Yes
osa-miR806a-h?0.588 1.700LOC_Os04g48200.1Cytochrome P450 87A3Yes
miRNA miRNA IAA
log2 (MT/WT)a Target IAA
log2 (MT/WT)b
TIGR locus name TIGR annotation c miRU d CSRDB
b. IAA treatment
osa-miR164c 2.240?2.556LOC_Os06g49660.1Taxadien-5-alpha-ol O-acetyltransferase Yes Yes osa-miR164c 2.240?3.474LOC_Os02g36880.1–3NAC domain protein NAC5Yes Yes osa-miR164c 2.240?1.786LOC_Os11g05190.1Phytosulfokines 2 precursor Yes
osa-miR164c 2.240?5.059LOC_Os09g36490.1Collagen, type IV, alpha 5Yes osa-miR164a/b/f 2.264?2.556LOC_Os06g49660.1Taxadien-5-alpha-ol O-acetyltransferase Yes Yes osa-miR164a/b/f 2.264?3.474LOC_Os02g36880.1–3NAC domain protein NAC5Yes Yes osa-miR164a/b/f 2.264?1.786LOC_Os11g05190.1Phytosulfokines 2 precursor Yes
osa-miR164a/b/f 2.264?1.599LOC_Os11g05820.1Transposon protein, Mutator sub-class Yes
osa-miR164d 2.226?2.556LOC_Os06g49660.1Taxadien-5-alpha-ol O-acetyltransferase Yes
osa-miR164d 2.226?3.474LOC_Os02g36880.1–3NAC domain protein NAC5Yes
osa-miR164d 2.226?1.599LOC_Os11g05820.1Transposon protein, Mutator sub-class Yes
osa-miR164d 2.226?1.889LOC_Os02g43170.1Salt tolerance-like protein Yes
osa-miR164d 2.226?1.786LOC_Os08g01480.1Cytochrome P450 71C4Yes osa-miR164e 1.949?2.556LOC_Os06g49660.1Taxadien-5-alpha-ol O-acetyltransferase Yes
osa-miR164e 1.949?3.474LOC_Os02g36880.1–3NAC domain protein NAC5Yes
osa-miR164e 1.949?1.786LOC_Os08g01480.1Cytochrome P450 71C4Yes
osa-miR396a/b 1.798?4.059LOC_Os03g51970.1Growth-regulating factor 1Yes
osa-miR397b 1.606?2.943LOC_Os03g16610.1L-Ascorbate oxidase precursor Yes
osa-miR397b 1.606?2.837LOC_Os12g15680.1L-Ascorbate oxidase precursor Yes
osa-miR397b 1.606?2.000LOC_Os01g63180.1L-Ascorbate oxidase precursor Yes
osa-miR166i/j 1.254?2.556LOC_Os03g10440.11,4-Beta-xylanase Yes
osa-miR397a0.948?2.943LOC_Os03g16610.1L-Ascorbate oxidase precursor Yes Yes osa-miR397a0.948?2.837LOC_Os12g15680.1L-Ascorbate oxidase precursor Yes Yes osa-miR397a0.948?3.322LOC_Os01g15810.1Peroxidase 9 precursor Yes
osa-miR397a0.948?2.000LOC_Os01g63180.1L-Ascorbate oxidase precursor Yes Yes osa-miR408 1.185?2.644LOC_Os06g15600.1Chemocyanin precursor Yes
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miR396 and miR408 families have been demonstrated in Arabidopsis (Gustafson et al. 2005; miRNA target informa-tion in Arabidopsis can be viewed at https://www.doczj.com/doc/ea2798329.html,/db/download.html ); thus, these miRNA–target pairs can serve as a repository for further experimental analysis of speci W c miRNA–target regulatory relationships.Feedback regulatory models between miRNAs and TFs have been established in animals and humans (Tsang et al.2007). In this study, we investigated the feedback regulation involved in auxin signalling in rice, and based on our results,we proposed a feedback circuit between the miR167 family and OsARF6 (Fig.S4). Although this feedback model requires further validation, it re X ects the widespread feed-back regulatory loops between miRNAs and TFs in plants.
Acknowledgments This study is supported by 973 Program (2005CB120901), NSFC (30771326), 863 Program (2008AA10Z125), and Program for NCET.
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Mean expression levels averaged from two biological replicates were used for the calculation; protein-coding genes with more than threefold changed expression levels in osaxr compared with the wild type were selected c
Gene annotations from TIGR (Version 5)d
miRU prediction was performed with the lowest stringency
miRNA miRNA IAA log 2 (MT/WT)a Target IAA log 2 (MT/WT)b TIGR locus name TIGR annotation c
miRU d CSRDB osa-miR408 1.185?1.599LOC_Os06g11490.1Blue copper protein precursor Yes Yes
osa-miR408 1.185?3.059LOC_Os01g03530.1copper ion binding protein Yes osa-miR408 1.185?2.059LOC_Os02g43660.1Blue copper protein precursor Yes osa-miR166k/l 0.800?3.322LOC_Os10g31690.1Glycine-rich cell wall structural protein 2 precursor Yes osa-miR160a-d ?0.976 2.498LOC_Os04g37990.1Sugar transport protein 5Yes osa-miR160e ?0.966 2.498LOC_Os04g37990.1Sugar transport protein 5Yes osa-miR171h
?2.207
1.664
LOC_Os03g19070.1
Long cell-linked locus protein
Yes
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糖尿病肾病的诊治 北京大学人民医院李月红 糖尿病肾病是糖尿病最常见的一个并发症，是导致终末期肾脏病最主要的原因，也是患者死亡的主要原因。随着糖尿病患者的越来越多，在5-7年以后，因为糖尿病肾病引起终末期肾脏病甚至透析的患者数量会越来越多。因此，糖尿病肾病一定要早期诊断、早期治疗。 一、糖尿病肾病的诊断 （一）糖尿病肾病的概念 糖尿病肾病是一个非常广泛的一个概念，有广义和狭义之分。广义的糖尿病肾病是指糖尿病导致的肾脏微血管病变的出现，包括病理的异常和临床检验的异常，甚至病理形态学的异常。狭义的糖尿病肾病是指糖尿病导致肾脏临床检验的异常。 （二）糖尿病肾病的分期及临床表现 Mogensen将1型的糖尿病肾病分为5期，目前2型的糖尿病肾脏的损害，尝试参照了1型糖尿病肾损害的分期。ppt7图表显示的是1型糖尿病肾脏损害的分期及临床和病理表现。 Ⅰ期：肾小球高滤过期。肾小球滤过率增加；血压正常；主要病理表现为肾小球肥大。 Ⅱ期：间断白蛋白尿期。肾小球滤过率增加或正常；间断的蛋白尿；病人的血压多数在正常范围之内；肾脏的病理表现为系膜基质的增宽和基底膜的增厚。 Ⅲ期：早期糖尿病肾病期。肾小球滤过率大致正常；病人可以出现持续的尿的白蛋白的增加；血压正常或升高；肾脏的病理表现加重。 Ⅳ期：临床糖尿病肾病期。肾小球滤过率下降；尿蛋白阳性；血压升高；病理表现进一步加重，部分肾小球硬化。 Ⅴ期：肾功能衰竭期。肾小球滤过率的下降，尿中可以发现大量的蛋白尿，病人出现血压的升高；肾穿病理，可以看到肾小球的硬化荒废，甚至肾小球间质纤维化和肾小管萎缩。 （三）糖尿病肾病的发病机理
如ppt6图片所示，首先是高血糖，血糖的升高可以引起氧化应激的异常，引起细胞因子的改变，引起终末期，糖激化终末期产物的增加。这两种因素最后导致了血管内皮和系膜的损伤和胶原的沉积，最后引起肾小球的硬化和肾小管间质的纤维化。所以高血糖在整个疾病的发生过程中是一个始动因素。 肾小球滤过率的下降，尿中可以发现大量的蛋白尿，病人出现血压的升高，水钠的潴留。在肾穿病理上，可以看到肾小球的硬化荒废，甚至肾小球间质的纤维化和肾小管的萎缩。 （四）糖尿病肾病的诊断 1.尿液的筛查 糖尿病的患者在5-7年以后，要注意尿液的检查。最早期最简单的检查方法就是筛查患者的尿白蛋白排泄率，或者24小时尿微量白蛋白的水平。鼓励患者每年进行一次尿微量白蛋白的筛查，尤其是糖尿病病史5年以上的患者，当尿白蛋白的水平大于30mg/g的时候就要当心。一般来说，1型糖尿病的患者在确诊5年以后，要每年筛查尿液的检查，2型糖尿病的患者因为合并多种危险因素，在确诊时，就鼓励患者进行尿液的检查，检测的频率一般是3-6个月。 2.排除其他的肾脏病变 如果患者无糖尿病视网膜病变，表现为GFR下降过快，同时出现急剧增加的蛋白尿或肾病综合征，和难以控制的高血压，出现活动性尿沉渣，甚至在应用了RASS系统抑制剂ACEI或ARB以后，出现短期的2-3个月之内的肾小球滤过率的下降大于30%的情况下，要引起高度的重视，患者可能合并了非糖尿病的肾病。 3.确诊糖尿病的的诊断 （1）诊断糖尿病肾病具备的条件：大量的白蛋白尿；微量白蛋白尿伴糖尿病视网膜病变；1型DM确诊5-7年。 （2）诊断糖尿病肾病的同时，我们一定要注意除外有没有其他的肾病的可能。 （五）重视糖尿病肾病的早期诊断 如ppt13图片所示，糖尿病肾病进展早期比较缓慢，早期的治疗效果好，费用也低。因此，一定要重视早期糖尿病肾病。如果从3期左右尽早的发现、尽早的治疗，可以逆转到2期，甚至1期；当出现大量尿蛋白甚至肾病综合征的时候，治疗就非常棘手，治疗手段也非常匮乏。另外，早期的糖尿病肾病是多种心血管系统疾病的高危的风险因素，如果早期治疗了糖尿病肾病，也可以预防心脑血管事件的发生。所以如何早期逆转糖尿病肾病至关重要。
Primer 5.0搜索引物： 1.Primer Length我常设置在18－30bp,短了特异性不好，长了没有必要。当然有特殊要求的除外，如加个酶切位点什么的。 2.PCR Product size最好是100－500bp之间，小于100bp的PCR产物琼脂糖凝胶电泳出来，条带很模糊，不好看。至于上限倒也不必要求苛刻。 3.Search parameters还是选Manual吧，Search stringency应选High，GC含量一般是40－60％。其它参数默认就可以了。 4.搜索出来的引物，按Rating排序，逐个送Oligo软件里评估。当然，搜索出的引物，其扩增产物很短，你可以不选择它，或是引物3端≥2个A或T,或引物内部连续的G或C太多,或引物3端≥2个G或C，这样的引物应作为次选，没得选了就选它。对于这样的引物，如果其它各项指标还可以，我喜欢在引物末端去掉一个不满意的或加上一个碱基，看看引物的评估参数有没有变好点。 Oligo 6.0评估引物： 1.在analyze里,Duplex Formation不管是上游引物、下游引物还是上下游引物之间，The most stable 3’-Dimer绝对值应小于4.5kcal/mol, The most stable Dimer overall绝对值一般应小于多少kcal/mol跟PCR退火温度有关，我几次实验感觉在PCR退火温度在65°的时候，The most stable Dimer ove rall 6.7kcal/mol没有问题。 2.Hairpin Formation根据黄金法则 3.False priming sites: Primer的priming efficiency应该是错配地方的4倍左右，更多当然更好。 4.在PCR栏，个人感觉其所显示的optimal annealing temperature数值值得参考。在PCR摸索条件的时候，退火温度为其数值加减2的范围就可以了。 5.Internal stability很重要：我们希望引物的内部稳定性是中间高、两边低的弧形，最起码保证3端不要过于稳定。下图1引物3端过于稳定，很容易导致不适当扩增。△G参照黄金法则，这其实很好理解：把一滴水放到大海里，这滴水就会不停的扩散分布，扩散的越厉害越稳定，所以△G绝对值越大结构越稳定。 最后说一句，敢于尝试就会成功。 第二贴 －－科室工作很多，小医生了，没有办法，所以肯怕不能满足很多战友的要求（qq聊或帮助设计），在此表示抱歉。就楼上的问题我试着回答一下，不一定正确，供参考吧。 －－1、两个评价系统不一样，个人感觉oligo评价引物好点，primer出来的引物，我一般按效率排序，再结合退火温度和引物长度，选择引物到oligo测试。这是初步的选择，其实引物到了oligo里，退火温度也不一样。 －－2、3端的二聚体应该避免，这个要看你的退火温度决定，一个50°的退火温度肯定和65°对二聚体的影响不一样了，一般来讲尽量控制在－4.5kcal/mol以下（个人观点，很多东西真得还是需要自己摸索）。 －－3、个人感觉3端有A无A影响不大，3端有T的没有经验。有T是不是一定不行，个人感觉不见得。软件是评估，法则也不是没有例外，不是1＋1＝2那么确定。 －－4、错配和二聚体谁轻谁重，个人觉得“到致命的程度”谁都重要，我也说不好。我设计的时候，尽量两个都不得罪。 －－5、GC含量并非不重要，它直接影响引物各端稳定性，3端来两个G或C,稳定性就上去了，粘在模板上很牢。所以我设计的时候，尽量避免这样的情况出现。 谈一下我学这个引物设计的过程吧：
熊去氧胆酸片说明书 熊去氧胆酸片(人福)用于胆固醇型胆结石，形成及胆汁缺乏性脂肪泻，也可用于预防药物性结石形成及治疗脂肪痢(回肠切除术后)。下面是小编整理的熊去氧胆酸片说明书，欢迎阅读。 熊去氧胆酸片商品介绍 通用名：熊去氧胆酸片 生产厂家: 宜昌人福药业有限责任公司 批准文号：国药准字H42022097 药品规格：50mg*30片 药品价格：￥8.8元 熊去氧胆酸片说明书 【通用名称】熊去氧胆酸片 【商品名称】熊去氧胆酸片 【拼音全码】XiongQuYangDanSuanPian 【主要成份】熊去氧胆酸片主要成份为熊去氧胆酸。化学名：3a,7b-二羟基-5b-胆甾烷-24-酸分子式：C24H40O4分子量：392.58 【性状】熊去氧胆酸片为白色片。 【适应症/功能主治】熊去氧胆酸片用于胆固醇型胆结石，形成及胆汁缺乏性脂肪泻，也可用于预防药物性结石形成及治疗脂肪痢(回肠切除术后)。 【规格型号】50mg*30s
【用法用量】成人口服：每日8～10mg/kg，早、晚进餐时分次给予。疗程短为6个月，6个月后超声波检查及胆囊造影无改善者可停药;如结石已有部分溶解则继续服药直至结石完全溶解。 【不良反应】熊去氧胆酸片的毒性和副作用比鹅去氧胆酸小，一般不引起腹泻，其他偶见的不良反应有便秘、过敏、头痛、头晕、胰腺炎和心动过速等。 【禁忌】胆道完全梗阻和严重肝功能减退者禁用。 【注意事项】1.长期使用熊去氧胆酸片可增加外周血小板的数量。 2.如治疗胆固醇结石中出现反复胆绞痛发作，症状无改善甚至加重，或出现明显结石钙化时，则宜中止治疗，并进行外科手术。 3.熊去氧胆酸片不能溶解胆色素结石、混合结石及不透X线的结石。 【儿童用药】遵医嘱。 【老年患者用药】老年患者慎用。 【孕妇及哺乳期妇女用药】熊去氧胆酸片FDA分类属B类药物，孕妇及哺乳期妇女慎用。 【药物相互作用】1.避孕药可增加胆汁饱和度，用熊去氧胆酸片治疗时应尽量采取其他节育措施以免影响疗效。2.考来烯胺(Cholestyramine，消胆胺)、考来替泊(Colestipol，降胆宁)和含铝制酸剂都能与CDCA结合，减少其吸收，不宜同用。 【药物过量】若服用过量，立即以不少于1L的考来烯胺或活性炭(每100ml水中2g)洗胃，再口服氢氧化铝悬液50ml。 【药理毒理】熊去氧胆酸片可增加胆汁酸的分泌，同时导致胆汁
早期糖尿病肾病相关因素研究与中药疗效评价 发表时间：2018-06-11T10:11:53.343Z 来源：《文化研究》2018年第5月作者：范春蕾 [导读] 糖尿病相关性慢性肾脏病（ diabetic kidney disease,DKD）发病率也在不断升高，DKD 已成为引起终末期肾病的主要原因。 齐齐哈尔工程学院护理学专业 161005 摘要：随着生活水平的提高及经济的快速发展，糖尿病患病率在不断增长，一项研究表明，2013 年，我国患糖尿病人数达到 1.139亿，其中 DKD 患者有 2430 万，DKD 已成为引 起终末期肾病的主要原因。本研究收集 2015-2016 年间于我院内分泌病房住院的 T2DM患者 85 人的资料，其中并发早期糖尿病肾病者 45人，对其资料进行回顾性分析，梳理其中医证候特点，并探讨影响早期糖尿病肾病的相关危险因素，旨在为糖尿病肾病预防及临床治疗提供有效依据。 关键词：早期糖尿病肾病；中医证型；中医治疗 一、前言 糖尿病（diabetes mellitus,DM）作为一种慢性非传染性疾病，其患病率在发展中国家增长迅速。糖尿病相关性慢性肾脏病（diabetic kidney disease,DKD）发病率也在不断升高，DKD 已成为引起终末期肾病的主要原因。北京大学张路霞所做的相关研究指出，2010 至 2015 年，来自我国三甲医院的 3530 万 2 型糖尿病患者中，约有 21.3%合并 DKD，DKD 是 1 型糖尿病的主要死因，在 2 型糖尿病患者中，其危险程度仅次于心脑血管疾病。糖尿病肾脏疾在，直接或间接影响肾脏功能。故高血压对糖尿病肾病的影响不容忽视。苗青原等研病严重影响着人民群众的健康和生活质量，寻找有效的方法进行预防并延缓其发展具有重要意义。中医药利用特有的辨证理论体系，并采用个体化治疗，对于糖尿病肾病的预防和治疗有着独到优势及巨大前景。本研究收集了 85 例糖尿病患者资料，其中并发早期糖尿病肾病者 45 例，比较早期糖尿病肾病组与对照组（ACR<30mg/g）差异，分析早期糖尿病肾病组证候特点及合并心脑血管疾病情况。本研究结合循证医学，查阅现代用益气养阴活血药物治疗早期糖尿病肾病文献，对相关文献进行 Meta 分析，并寻找其规律。 二、高血压与 DKD 早期糖尿病肾病患者中，多数合并有心脑血管疾病，早期糖尿病肾病组收缩压、舒张压均高于对照组。因全身高血压可致肾脏高灌注以及肾内毛细血管压力增高，而后者被认为是加速肾损害重要因素。高血压又常与高血糖及胰岛素抵抗同时存在，直接或间接影响肾脏功能。故高血压对糖尿病肾病的影响不容忽视。苗青原等研究表明，积极控制血压被认为是控制和延缓 DKD 患者肾脏进一步损害的重要措施。糖尿病肾病伴发高血压机制可能是：长期高血压会导致肾脏结构和功能的改变，肾脏动脉硬化及玻璃样变，继而引起肾脏缺血、缺氧，进一步影响肾功能，最终致终末期肾病。 三、高尿酸与 DKD 由早期糖尿病肾病组和对照组临床指标比较结果可知，高尿酸具有统计学意义（P<0.05）。肾脏是尿酸盐排泄主要器官，其功能状态直接影响 UA 水平，同时高 UA 也可进一步加重肾脏损害。高尿酸与高胰岛素血症及肥胖显著相关，高尿酸还参与胰岛素抵抗( IR)等相关疾病发生。研究表明高尿酸促进 DKD 的发生发展，可能是通过氧化酶、肿瘤坏死因子、血管平滑肌细胞作用来实现。其中肿瘤坏死因子可导致胰岛素抵抗( IR)，反之，IR 又能促进尿酸盐重吸收，久之，尿酸盐排泄减少，可最终导致高尿酸发生，同时，高胰岛素血证还可通过高血压、高血脂、高血糖等间接作用促使肾脏功能恶化。总之高尿酸是肾脏疾病发生发展的独立危险因素，尿酸与糖尿病肾病密切相关。 四、高血糖与 DKD 结果可知早期糖尿病肾病组和对照组的比较，还是二组同一证型即气阴两虚兼血瘀型相关理化指标比较，糖化血红蛋白都具有统计学意义（P<0.05）,由此可知，高血糖是导致 DKD 生发展的最关键因素，故临床上应严格控制血糖以降低 DKD的发生率。苗青原研究表明，高血糖、晚期糖基化终末产物、山梨醇、蛋白激酶 C 等可激活多种细胞因子或炎症因子，此类物质在血流动力学异常、肾小球的基底膜增厚、系膜基质积聚等过程中起重要作用，最终致肾脏组织缺血缺氧。钮丽萍的研究结果也表明 Hb A1C 水平与尿微量白蛋白排出量成正相关，血糖蛋白增多首先会导致高血糖和高血脂，高糖和高脂会进一步加重对肾脏的损害作用。临床要根据个体化原则，控制糖尿病及糖尿病肾病患者的血糖，减少患者血糖波动。糖尿病肾病早期患者往往没有特殊症状，很多糖尿病肾病患者在确诊时已达 3 期，所以已确诊为糖尿病的患者，应尽早检查肾功，及早预防和治疗肾脏损害。 五、视网膜病变与 DKD 早期糖尿病肾病患者 49%合并有视网膜病变，对照组 15%的患者合并有视网膜病变。糖尿病视网膜病变与 DKD 均是微血管病变，二者具有相同的致病因素，高血糖是二者致病的中心环节，临床上糖尿病肾病患者多合并有糖尿病视网膜病变。多项研究表明，微量白蛋白尿不仅是糖尿病肾病诊断标准及危险因素，而且与增殖性视网膜病变密切相关。佟爱华所做的临床研究表明糖尿病肾病患者白蛋白尿与糖尿病视网膜病变存在显著相关性，糖尿病视网膜病变与糖尿病肾病密切相关。闫济民研究表明糖尿病视网膜病变可以作为糖尿病肾损伤的一个预测指标。 六、中医症状分布情况 早期糖尿病肾病组症状频率较高的是乏力，口渴，尿频，四肢麻木、发凉、疼痛，视物模糊，脉象以沉细为主，舌苔薄白少津或少苔最为常见，乏力，口渴、四肢麻凉疼是典型的气阴两虚兼血瘀表现，脉沉细、苔薄白少津或少苔也为气阴亏虚之象。因而可知，气阴两虚兼血瘀证型是早期糖尿病肾病最常见的证型。早期糖尿病肾病组和对照组相比较，乏力、口渴，四肢麻木、疼痛也是二者共有的常见症状，气阴两虚兼血瘀也是对照组最常见的证型。早期糖尿病肾病患者没有特殊的临床表现，其症状往往与一般糖尿病患者相似，不同的是，糖尿病肾病患者病程更长，通常已患糖尿病 10年以上，根据中医“久病必瘀”，“久病入络”的理论，糖尿病肾病患者血瘀征象可能较糖尿病患者明显。 总结：糖尿病病程越长，累及于肾可能性越大,血压对早期糖尿病肾病有影响。糖尿病肾病最常见症状为乏力、口渴、四肢麻木、疼痛，常见舌象有暗红、暗淡等，舌苔多以苔白少津为主，脉象多以沉细为主。
一、病例分析: 王XX,女,56岁, 主诉:反复泡沫尿两年余,加重一周。 病史:患者2年前体检时发现蛋白尿、血尿,当时查尿常规示:pro(2+),RBC(3+),后于肾炎康复片、中草药治疗,病情时好时坏,自诉尿pro波动于+~2+,RBC(-),近一周自觉尿中泡沫增多,故来院就诊。刻下:患者小便混浊,小便乳白如脂膏,精神萎靡,消瘦无力,腰膝酸软,头晕耳鸣,面色咣白,形寒肢冷。胃纳一般,便溏,夜寐尚安。 查体:T 37℃Ｐ72次/分R 18次/分BP 150/100mmHg。 神清,精神一般,皮肤粘膜未见黄染,颈静脉无怒张,心率72次/分,律齐;两肺呼吸音粗,未闻及干湿罗音,腹软,无压痛,移动性浊音(-),肝脾肋下未及。双下肢轻度浮肿。舌质淡红,脉沉细。 辅检:尿常规:pro(2+)。24h尿蛋白定量1、2g。血钾5、2mmol/L。肾功能:尿素5、4mmol/L;血肌酐162umol/L;尿酸333umol/L。血脂:TG 1、5mmol/L,TC 4、8mmol/L。空腹血糖9、5mmol/L。糖化血红蛋白7、5%。血浆白蛋白38g/L。 进一步问诊: 诱发因素:两年前及此次发病(如劳累、剧烈运动、发热、食物、药物等)。若有发热,多久后发病。 主症特点:泡沫尿就是一过性还就是持续性;就是否有肉眼血尿 伴随症状:有无口干、多饮、多尿等;有无关节红肿热痛、畸形;有无皮疹;有无体重减轻;有无发热、有无尿频尿急尿痛、有无腰酸腰痛等;就是否有口苦,尿道有灼热感;有无小腹坠胀,劳累或进食油腻则发作加重等。(结合十问歌)。 诊疗经过(略) 既往史:就是否有泌尿道感染、一过性蛋白尿、血尿病史等,有无糖尿病、高血压、肝炎、肿瘤疾病等病史。 过敏史:有无食物及药物过敏史(过敏性紫癜性肾炎)。 家族史:就是否有糖尿病、高血压、肝炎、肿瘤疾病等病史。 进一步查体:颜面部及眼睑就是否有水肿？肾区叩击痛？肾脏就是否可以触及？输尿管点压痛？腹部体检？ 进一步辅助检查:ANA 、ENA、ds-DNA、C3、C4、ANCA;肿瘤指标;肝功能、三对半;血常规、凝血功能;β2-MG、尿MA、尿RBP、尿NAG酶;尿沉渣、尿相差、中段尿培养;B超、CT、造影、甚至膀胱镜;肾穿刺、肝肾功能、眼底检查等。 二、完善病史: 王XX,女,56岁, 主诉:反复泡沫尿两年余,加重一周。 病史:患者2年前体检时发现蛋白尿、血尿,当时查尿常规示:pro(2+),RBC(3+),后于肾炎康复片、中草药治疗,病情时好时坏,自诉尿pro波动于+~2+,RBC波动于+,近一周自觉尿中泡沫增多,故来院就诊。追问病史患者有糖尿病病史10余年,平素予以诺与灵30R(早16u 晚8u)控制血糖,血糖控制欠佳。有无高血压、肝炎、肿瘤疾病等病史。此次发病以来,有无关节红肿热痛、畸形;无皮疹;无体重减轻;无发热、无尿频尿急尿痛。刻下:小便混浊,小便乳白如脂膏,口干多饮,消瘦无力,腰膝酸软,头晕耳鸣,面色咣白,形寒肢冷。胃纳一般,便溏,夜寐尚安。 过敏史:无食物及药物过敏史。 查体:T 37℃Ｐ72次/分R 18次/分BP 150/100mmHg。 神清,精神一般,正常面容。皮肤黏膜未见紫癜及黄染。双侧甲状腺未及肿大。两肺呼吸音清,
1. 引物的长度一般为15-30 bp，常用的是18-27 bp，但不应大于38，因为过长会导致其延伸温度大于74℃，不适于Taq DNA聚合酶进行反应。 2. 引物序列在模板内应当没有相似性较高，尤其是3’端相似性较高的序列，否则容易导致错配。引物3’端出现3个以上的连续碱基，如GGG或CCC，也会使错误引发机率增加。 3. 引物3’端的末位碱基对Taq酶的DNA合成效率有较大的影响。不同的末位碱基在错配位置导致不同的扩增效率，末位碱基为A的错配效率明显高于其他3个碱基，因此应当避免在引物的3’端使用碱基A。另外，引物二聚体或发夹结构也可能导致PCR反应失败。5’端序列对PCR影响不太大，因此常用来引进修饰位点或标记物。 4. 引物序列的GC含量一般为40-60%，过高或过低都不利于引发反应。上下游引物的GC含量不能相差太大。 5. 引物所对应模板位置序列的Tm值在72℃左右可使复性条件最佳。Tm值的计算有多种方法，如按公式Tm＝4(G+C)＋2(A+T)，在Oligo软件中使用的是最邻近法(the nearest neighbor method)。 6. ΔG值是指DNA双链形成所需的自由能，该值反映了双链结构内部碱基对的相对稳定性。应当选用3’端ΔG值较低（绝对值不超过9），而5’端和中间ΔG值相对较高的引物。引物的3’端的ΔG值过高，容易在错配位点形成双链结构并引发DNA聚合反应。 7. 引物二聚体及发夹结构的能值过高（超过mol）易导致产生引物二聚体带，并且降低引物有效浓度而使PCR反应不能正常进行。 8. 对引物的修饰一般是在5’端增加酶切位点，应根据下一步实验中要插入PCR 产物的载体的相应序列而确定。 引物序列应该都是写成5-3方向的， Tm之间的差异最好控制在1度之内， 另外我觉得扩增长度大一些比较好，500bp左右。 要设计引物首先要找到DNA序列的保守区。同时应预测将要扩增的片段单链是否形成二级结构。如这个区域单链能形成二级结构，就要避开它。如这一段不能形成二级结构，那就可以在这一区域设计引物。
胆汁淤积的治疗方法及药物的概述 来源：《肝脏》作者：张大志浏览:2567 发布时间：2008-10-13 9:39:00 胆汁淤积不是单一的疾病, 而是一组临床综合征, 且其病因及发病机制十分复杂。因此胆汁淤积的治疗应 包括病因及相关并发症的治疗。 一、病因治疗 1/3的致病原因不明，对基本病因明确的胆汁淤积，如有可能均应力争根治或控制基础疾病。 1. 肝外胆汁淤积的手术治疗：手术治疗主要用于肝外胆汁淤积。肝外胆汁淤积是肝外或近肝门处大胆管的机械梗阻所致, 主要为胆管结石、寄生虫、肿瘤以及感染、发育异常、手术后并发症等引起的肝外胆管阻塞。因此采用手术治疗解除梗阻, 一般能取得较好疗效。目前能采用的手术方式有经内镜介入胆道引流术、经皮肝胆道引流术（PTCD）和开腹手术。（1）经内镜介入胆道引流术: 以其创伤小、病死率低、住院周期短等优点而成为解除肝外梗阻的首选方式。自1973年经内镜十二指肠乳头括约肌切开治疗胆总管结石以来, 经内镜鼻胆管引流术及经内镜胆管支架引流术已广泛用于治疗良、恶性胆道梗阻, 取得较好的效果。但ERCP 术可能因幽门或十二指肠狭窄、先前的胃肠手术、导管无法插入等因素的影响而不能获得成功。近年有报 道ERCP和PTCD失败的患者可在EUS引导下经食管、胃、小肠胆道引流术取得成功, 拓宽了内镜的治疗范围。（2）PTCD：自1974年Molnar和Stocknm首先报道采用PTCD缓解恶性梗阻性黄疸以来, PTCD技术上有很大的改善和发展。但PTCD有一定的并发症, 如胆汁外漏、腹膜炎、大量胆汁流失引起电解质的紊乱、胆道出血、疼痛和患者生活不便，以致许多患者不愿接受。现已成为胆道梗阻经逆行性胆管造影术治疗失 败后的一种选择。（3）开腹手术：因创伤大、并发症多、住院时间长、费用高等弊端而成为胆汁淤积手术治疗的次要选择。但肝移植术仍不失为治愈复发性、顽固性胆汁淤积瘙痒及某些潜在肝脏疾病的最终方法。 2. 胆小管的免疫性损伤：免疫抑制剂可抑制免疫反应和炎症反应、促进胆汁分泌等作用, 能有效改善患者临床症状和肝功能, 可用于治疗多种病因的肝内胆汁淤积。但免疫抑制剂由于选择性和特异性的限制, 在 治疗的同时不可避免地会损害造血系统、免疫系统及肝、肾功能, 可能引发更为严重的损害，如硫唑嘌呤 的使用可能导致胆汁淤积和肝细胞损害。
引物设计step by step 1、在NCBI上搜索到目的基因，找到该基因的mRNA，在CDS选项中，找到编码区所在位置，在下面的origin中，Copy该编码序列作为软件查询序列的候选对象。 2、用Primer Premier5搜索引物 ①打开Primer Premier5，点击File-New-DNA sequence, 出现输入序列窗口，Copy目的序列在输入框内（选择As），此窗口内，序列也可以直接翻译成蛋白。点击Primer，进入引物窗口。 ②此窗口可以链接到“引物搜索”、“引物编辑”以及“搜索结果”选项，点击Search按钮，进入引物搜索框，选择“PCR primers”，“Pairs”，设定搜索区域和引物长度和产物长度。在Search Parameters里面，可以设定相应参数。一般若无特殊需要，参数选择默认即可，但产物长度可以适当变化，因为100～200bp的产物电泳跑得较散，所以可以选择300～500bp. ③点击OK，软件即开始自动搜索引物，搜索完成后，会自动跳出结果窗口，搜索结果默认按照评分（Rating）排序，点击其中任一个搜索结果，可以在“引物窗口”中，显示出该引物的综合情况，包括上游引物和下游引物的序列和位置，引物的各种信息等。 ④对于引物的序列，可以简单查看一下，避免出现下列情况：3’不要出现连续的3个碱基相连的情况，比如GGG或CCC，否则容易引起错配。此窗口中需要着重查看的包括：Tm 应该在55～70度之间，GC％应该在45％～55％间，上游引物和下游引物的Tm值最好不要相差太多，大概在2度以下较好。该窗口的最下面列出了两条引物的二级结构信息，包括，发卡，二聚体，引物间交叉二聚体和错误引发位置。若按钮显示为红色，表示存在该二级结构，点击该红色按钮，即可看到相应二级结构位置图示。最理想的引物，应该都不存在这些二级结构，即这几个按钮都显示为“None”为好。但有时很难找到各个条件都满足的引物，所以要求可以适当放宽，比如引物存在错配的话，可以就具体情况考察该错配的效率如何，是否会明显影响产物。对于引物具体详细的评价需要借助于Oligo来完成，Oligo自身虽然带有引物搜索功能，但其搜索出的引物质量感觉不如Primer5. ⑤在Primer5窗口中，若觉得某一对引物合适，可以在搜索结果窗口中，点击该引物，然后在菜单栏，选择File-Print-Current pair，使用PDF虚拟打印机，即可转换为Pdf文档，里面有该引物的详细信息。 3、用Oligo验证评估引物 ①在Oligo软件界面，File菜单下，选择Open，定位到目的cDNA序列（在primer中，该序列已经被保存为Seq文件），会跳出来两个窗口，分别为Internal Stability（Delta G）窗口和Tm窗口。在Tm窗口中，点击最左下角的按钮，会出来引物定位对话框，输入候选的上游引物序列位置（Primer5已经给出）即可，而引物长度可以通过点击Change－Current oligo length来改变。定位后，点击Tm窗口的Upper按钮，确定上游引物，同样方法定位下游引物位置，点击Lower按钮，确定下游引物。引物确定后，即可以充分利用Analyze 菜单中各种强大的引物分析功能了。
引物设计的原理与方法 This model paper was revised by the Standardization Office on December 10, 2020
PCR引物设计的原理及方法 阎振鑫S111666(四川大学生命科学学院细胞生物学成都 610014) 摘要：自20世纪后期发展了PCR技术以来，PCR已经改变了整个生物学研究的进程。而PCR反应的第一步就是设计引物，引物设计的好坏直接关系到PCR的成败。PCR引物设计有许多的原则必须要遵循：引物与引物之间避免形成稳定的二聚体或发夹结构，引物与模板的序列要紧密互补。引物不能在模板的非目的位点引发DNA聚合反应等。另外，引物的设计方法也越来越多，出现了许多专门的设计软件和网站，如：PrimerPremier5.0等。 关键词：PCR 引物原理方法 NCBI PrimerPremier5.0 PCR primer design principle and method YanZhenxin (sichuan Univercity, Life science college cell biology chengdu 610014 ) Abstract: When PCR technology was find, PCR has changed all of the program in research of biology. The design of primer is the frist step of PCR. It is relation to the fate of PCR. There are some principals must be obey: dipolymer and hairpin structure must be avoid between different primers. The DNA polymerization reaction should not be triggered at the wrong site. Therefore, there are more and more methods of design primer, include the professional softwares and professional web site. Key word: PCR primer principle NCBI PrimerPremier5.0 聚合酶链式反应(Polymerase chain reaction。PCR)是20世纪后期发展起来的 一种体外扩增特异DNA片断的技术。具有快速、简便及高度敏感等优点，能极大地缩短目的基因扩增时间[1]。因此，其一直是生物学者们致力于构建cDNA文库、基因克隆以及表达调控研究的必要前提和基础[2]。PCR的第一步就是引物设计。引物设计的好坏，直接影响了PCR的结果，因此这一步很关键。成功的PCR反应既要高效，又要特异性扩增产物，因此对引物设计提出了较高的要求。引物设计需要注意的地方很多，在大多数情况下，我们都是在知道已知模板序列时进行PCR扩增的。在某些情况比如构建文库的时候也会在不知道模板序列的情况下进行设计。这个时候随机核苷酸序列
熊去氧胆酸片 【药品名称】 通用名称：熊去氧胆酸片 英文名称：Ursodeoxycholic Acid 【成份】 本品主要成份为：熊去氧胆酸。其化学名称为：3a,7b-二羟基-5b-胆甾烷-24-酸。 【适应症】 本品用于胆固醇型胆结石，形成及胆汁缺乏性脂肪泻，也可用于预防药物性结石形成及治疗脂肪痢（回肠切除术后）。 【用法用量】 口服，利胆：一次50mg(1片)，一日150mg(3片)； 溶胆石：一日450-600mg(9-12片)，分2次服用； 或每日按体重8-10mg/kg，肥胖者需每日15mg/kg，进食时分2次给予。 【不良反应】 本品的毒性和副作用比鹅去氧胆酸小，一般不引起腹泻，其他偶见的不良反应有便秘、过敏、头痛、头晕、胰腺炎和心动过速等。治疗期可引起胆结石钙化，软便。 【禁忌】 急性胆系感染、胆道梗阻、孕妇及哺乳期妇女。 【注意事项】 （1）长期使用本品可增加外周血小板的数量。（2）如治疗胆固醇结石中出现反复胆绞痛发作，症状无改善甚至加重，或出现明显结石钙化时，则宜中止治疗，并进行外科手术。（3）本品不能溶解胆色素结石、混合结石及不透X线的结石。【孕妇及哺乳期妇女用药】
本品FDA分类属B类药物，孕妇及哺乳期妇女慎用。【老年患者用药】老年患者慎用。 【特殊人群用药】 儿童注意事项： 妊娠与哺乳期注意事项： 孕妇及哺乳期妇女禁用。 老人注意事项： 老年患者慎用。 【药物相互作用】 熊去氧胆酸胶囊不应与考来烯胺（消胆胺）、考来替泊（降胆宁）、氢氧化铝和/或氢氧化铝-三硅酸镁等药同时服用，因为这些药可以在肠中和熊去氧胆酸结合，从而阻碍吸收，影响疗效。如果必须服用上述药品，应在服用该药前两小时或在服药后两小时服用熊去氧胆酸胶囊。熊去氧胆酸胶囊可以增加环孢素在肠道的吸收，服用环孢素的患者应做环孢素血清浓度的监测，必要时要调整服用环孢素的剂量。个别病例服用熊去氧胆酸胶囊会降低环丙沙星的吸收。 【药理作用】 本品可增加胆汁酸的分泌，同时导致胆汁酸成分的变化，使本品在胆汁中的含量增加。 本品还能显著降低人胆汁中胆固醇及胆固醇酯的摩尔浓度和胆固醇的饱和指数，从而有利于结石中胆固醇逐渐溶解 【贮藏】 遮光，密封保存。 【批准文号】
最新糖尿病肾病防治专家共识（2014 版） 糖尿病肾病是糖尿病最主要的微血管并发症之一，是目前引起终末期肾病（end-stage renal disease，ESRD）的首要原因。早期诊断、预防与延缓糖尿病肾病的发生发展对提高糖尿病患者存活率，改善其生活质量具有重要意义。为规范糖尿病肾病的诊断和治疗，中华医学会糖尿病学分会微血管并发症学组组织国内的内分泌和肾内科领域专家共同制定了共识。该共识近日发表在中华糖尿病杂志上，主要内容如下。 一、糖尿病肾病的定义与诊断 糖尿病肾病是由糖尿病引起的肾脏损伤，以往用DN（diabetic nephropathy）表示，2007 年美国肾脏病基金会（NKF）制定了肾脏病生存质量指导指南，简称NKF/KDOQI。该指南建议用DKD（diabetic kidney disease）取代DN。2014 年美国糖尿病协会（ADA）与NKF 达成共识，认为DKD（diabetic kidney disease）是指由糖尿病引起的慢性肾病，主要包括肾小球滤过率（GFR）低于60 ml·min-1·1.73 m2 或尿白蛋白/ 肌酐比值（ACR）高于30 mg/g 持续超过3 个月。糖尿病性肾小球肾病（diabetic glomerulopathy）专指经肾脏活检证实的由糖尿病引起的肾小球病变。 糖尿病肾病的诊断分为病理诊断和临床诊断。肾脏病理被认为是诊断金标准。糖尿病主要引起肾小球病变，表现为肾小球系膜增生、基底膜增厚和K-W （Kimmelstiel-Wilson）结节等，是病理诊断的主要依据。糖尿病还可引起肾小管间质、肾微血管病变，如肾间质纤维化、肾小管萎缩、出球动脉透明变性或肾微血管硬化等，这些改变亦可由其他病因引起，在诊断时仅作为辅助指标。 目前糖尿病肾病临床诊断的依据有尿白蛋白和糖尿病视网膜病变。糖尿病肾病早期可表现为尿白蛋白阴性，症状不明显，易被忽略，但目前仍缺乏比尿微量白蛋白更可靠敏感的糖尿病肾病早期检测指标。 （一）糖尿病肾病临床诊断依据 1. 尿白蛋白：微量白蛋白尿是糖尿病肾病早期的临床表现，也是诊断糖尿病肾病的主要依据。 其评价指标为尿白蛋白排泄率（UAE/AER）或ACR。个体间UAE 的差异系数接近40%，与之相比ACR 更加稳定且检测方法方便，只需要检测单次随机晨尿即可，故推荐使用ACR。 尿白蛋白排泄异常的定义见表1，因尿白蛋白排泄受影响因素较多，需在3-6 个月内复查，3 次结果中至少 2 次超过临界值，并且排除影响因素如24h 内剧
PCR引物设计的原理及方法 阎振鑫S111666(四川大学生命科学学院细胞生物学成都610014) 摘要：自20世纪后期发展了PCR技术以来，PCR已经改变了整个生物学研究的进程。而PCR反应的第一步就是设计引物，引物设计的好坏直接关系到PCR的成败。PCR引物设计有许多的原则必须要遵循：引物与引物之间避免形成稳定的二聚体或发夹结构，引物与模板的序列要紧密互补。引物不能在模板的非目的位点引发DNA聚合反应等。另外，引物的设计方法也越来越多，出现了许多专门的设计软件和网站，如：PrimerPremier5.0等。 关键词：PCR 引物原理方法NCBI PrimerPremier5.0 PCR primer design principle and method YanZhenxin (sichuan Univercity, Life science college cell biology chengdu 610014 ) Abstract: When PCR technology was find, PCR has changed all of the program in research of biology. The design of primer is the frist step of PCR. It is relation to the fate of PCR. There are some principals must be obey: dipolymer and hairpin structure must be avoid between different primers. The DNA polymerization reaction should not be triggered at the wrong site. Therefore, there are more and more methods of design primer, include the professional softwares and professional web site. Key word: PCR primer principle NCBI PrimerPremier5.0 聚合酶链式反应(Polymerase chain reaction。PCR)是20世纪后期发展起来的一种体外扩增特异DNA片断的技术。具有快速、简便及高度敏感等优点，能极大地缩短目的基因扩增时间[1]。因此，其一直是生物学者们致力于构建cDNA文库、基因克隆以及表达调控研究的必要前提和基础[2]。PCR的第一步就是引物设计。引物设计的好坏，直接影响了PCR的结果，因此这一步很关键。成功的PCR反应既要高效，又要特异性扩增产物，因此对引物设计提出了较高的要求。引物设计需要注意的地方很多，在大多数情况下，我们都是在知道已知模板序列时进行PCR扩增的。在某些情况比如构建文库的时候也会在不知道模板序列的情况下进行设计。这个时候随机核苷酸序列就与模板不是完全匹配。我们通常指的设计引物都是在已知模板序列的情况下进行。设计的目的是在两个目标间取得平衡：扩增特异性和扩增效率。
核准日期： 修改日期： 熊去氧胆酸胶囊说明书 请仔细阅读说明书并在医师指导下使用。 【药品名称】 通用名称：熊去氧胆酸胶囊 商品名称：优思弗 英文名称：Ursodeoxycholic Acid Capsules 汉语拼音：Xiongquyangdansuan Jiaonang 【成份】 化学名称：3α,7β-二羟基-5β-胆甾烷-24-酸。 化学结构式： 分子式：C24H40O4 分子量：392.58 【性状】 本品为白色不透明硬质胶囊，内容物为白色的粉末或颗粒。 【适应症】 1. 胆囊胆固醇结石—必须是X射线能穿透的结石，同时胆囊收缩功能须正常； 2. 胆汁淤积性肝病（如：原发性胆汁性肝硬化）； 3. 胆汁反流性胃炎。 【规格】250mg 【用法用量】 1.胆囊胆固醇结石和胆汁淤积性肝病 按时用少量水送服。按体重每日剂量为10mg/kg，即： 体重每日剂量服药时间
胆结 胆汁淤积性肝病 石 晚早中晚 60kg2粒2 1 - 1 80kg3粒3 1 1 1 100kg4粒4 1 1 2溶石治疗：一般需6~24个月，服用12个月后结石未见变小者，停止服用。治疗结果根据每6个月进行超声波或X射线检查判断。 2. 胆汁反流性胃炎 晚上睡前用水吞服，必须定期服用，一次一粒（250mg），一日一次。一般服用10~14天，遵从医嘱决定是否继续服药。 【不良反应】 不良反应的评估基于下列频率数据： 十分常见：≥ 10%常见：≥ 1%~ < 10% 偶见：≥ 0.1%~ < 1%罕见：≥0.01%~ < 0.1% 十分罕见：<0.01%或现有数据无法评估 胃肠道紊乱： 临床试验中，用熊去氧胆酸进行治疗时稀便或腹泻的报告常见。 在治疗原发性胆汁性肝硬化时，发生严重的右上腹疼痛十分罕见。 肝胆功能紊乱： 用熊去氧胆酸进行治疗时，发生胆结石钙化的病例十分罕见。 治疗晚期原发性胆汁性肝硬化时，发生肝硬化失代偿的情形十分罕见，停止治疗后部分恢复。 过敏反应： 发生荨麻疹十分罕见。 【禁忌】 下列情况下禁用熊去氧胆酸胶囊： -急性胆囊炎和胆管炎； -胆道阻塞（胆总管和胆囊管）； -经常性的胆绞痛发作； -射线穿不透的胆结石钙化；
附件8 《中药新药用于糖尿病肾脏疾病临床研究技术指导原则》（征求意见稿）起草说明 一、起草背景、目的和意义 糖尿病肾脏疾病是由糖尿病引起的肾脏损伤，临床主要表现为持续性白蛋白尿和（或）肾小球滤过率下降。糖尿病肾脏疾病既是糖尿病最常见的并发症，也是导致慢性和终末期肾病的主要原因，目前临床治疗主要是降糖、降压和控制蛋白摄入等措施，其中ACEI/ARB类药物的治疗受到重视，但仍存在较大未被满足的临床需求。 糖尿病肾脏疾病属于中医学“消渴病肾病”范畴，中药在改善临床症状、减少尿白蛋白排泄率，甚至延缓糖尿病肾脏疾病病程方面，都具有一定的作用，但目前尚无有关糖尿病肾脏疾病的中药新药临床研究技术指导原则，直接影响到糖尿病肾脏疾病相关中药新药的研发。在此背景下，开展了《中药新药用于糖尿病肾脏疾病临床研究技术指导原则》（以下简称“指导原则”）制订工作，以指导科学评价中药新药用于糖尿病肾脏疾病的临床有效性及安全性。 二、起草过程
本指导原则制订工作自2018年4月25日正式启动，起草组成员由内分泌及肾脏病中西医临床专家和药审中心人员共同组成。2018年7月19日于北京江西大酒店召开了初稿讨论会；2018年8月30日起草组借助世界中医药学会联合会糖尿病专业委员会学术年会期间在新疆进行了专家研讨；2018年11月22日在北京江西大酒店召开了扩大专家讨论会，起草组专家与扩大的业内专家对本指导原则进行讨论并达成了共识。 三、指导原则主要内容和特点 （一）指导原则的主要内容 目前已发布的中药新药临床研究指导原则尚未涵盖糖尿病肾脏疾病，本指导原则旨在为糖尿病肾脏疾病的中药新药临床试验设计提供指导性建议，促进用于糖尿病肾脏疾病的中药新药研发的规范性和科学性，体现中药新药用于糖尿病肾脏疾病的优势与特色。本指导原则内容包括用于糖尿病肾脏疾病的中药新药临床定位、诊断标准、受试者选择、给药方案、有效性评价、安全性评价及质量控制等试验设计方面的内容。 （二）本指导原则的特点 本指导原则的制定结合了近年来国内外专家共识及临床指南，广泛征求了内分泌及肾脏病中西医临床专家意见，有以下几个方面的特点：
引物设计的原理与方法 The latest revision on November 22, 2020
PCR引物设计的原理及方法 阎振鑫S111666(四川大学生命科学学院细胞生物学成都 610014) 摘要：自20世纪后期发展了PCR技术以来，PCR已经改变了整个生物学研究的进程。而PCR反应的第一步就是设计引物，引物设计的好坏直接关系到PCR的成败。PCR引物设计有许多的原则必须要遵循：引物与引物之间避免形成稳定的二聚体或发夹结构，引物与模板的序列要紧密互补。引物不能在模板的非目的位点引发DNA聚合反应等。另外，引物的设计方法也越来越多，出现了许多专门的设计软件和网站，如：PrimerPremier5.0等。 关键词：PCR 引物原理方法 NCBI PrimerPremier5.0 PCR primer design principle and method YanZhenxin (sichuan Univercity, Life science college cell biology chengdu 610014 ) Abstract: When PCR technology was find, PCR has changed all of the program in research of biology. The design of primer is the frist step of PCR. It is relation to the fate of PCR. There are some principals must be obey: dipolymer and hairpin structure must be avoid between different primers. The DNA polymerization reaction should not be triggered at the wrong site. Therefore, there are more and more methods of design primer, include the professional softwares and professional web site. Key word: PCR primer principle NCBI PrimerPremier5.0 聚合酶链式反应(Polymerase chain reaction。PCR)是20世纪后期发展起来的 一种体外扩增特异DNA片断的技术。具有快速、简便及高度敏感等优点，能极大地缩短目的基因扩增时间[1]。因此，其一直是生物学者们致力于构建cDNA文库、基因克隆以及表达调控研究的必要前提和基础[2]。PCR的第一步就是引物设计。引物设计的好坏，直接影响了PCR的结果，因此这一步很关键。成功的PCR反应既要高效，又要特异性扩增产物，因此对引物设计提出了较高的要求。引物设计需要注意的地方很多，在大多数情况下，我们都是在知道已知模板序列时进行PCR扩增的。在某些情况比如构建文库的时候也会在不知道模板序列的情况下进行设计。这个时候随机核苷酸序列