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Content:
Supplementary Figure Legends S1-7
Supplementary Table Legends S1-6
Supplementary Text 1-3
References
Supplementary Figure Legends
Figure S1: Uromodulin is kidney specific as shown by expression pattern of the gene in several
reference expression data sets (a) mRNA expression profile from biogps.org (including Gene
Atlas) and (b) protein expression profile using Model Organism Protein Expression Database
[MOPED] dataset from genecards.org survey of diverse anatomic regions. (c)Heat map showing
the expression levels of all full length transcripts of UMOD gene across the 16 human tissues
using the Illumina generated RNA-seq data from the Human Body Map 2.0 Project.
Figure S2: Phylogenetic tree for UMOD and 15 selected orthologs using webPRANK
bioinformatics tool.
Figure S3: Comparison of conserved motifs in 2kb upstreams of UMOD gene of mouse and
human. (a) Location of ten motifs identified and their distribution with its coordinates in x-axis
in 2 kb upstream sequences in UMOD of human & mouse was shown in block diagram. The
position of each binding region with significant (p < 10-5) overlap with (b) 5 consensus motifs
obtained at 7 location in human and (c) 8 consensus motifs obtained at 10 location in mouse
were shown. Sequence strand specified as “+” (input sequence can be read from left to right) and
“-” (input sequence can be read on its complementary sequence from right to left) with respect to
occurence of motifs. (d) Ten significant consensus motifs and complementary sequences were
shown for reference.
Figure S4: Phylogenetically conserved and statistically significant (indicated by e-value < e-40)
novel motifs with the number of sites (across orthologous species) contributing its construction
was shown for UMOD 5kb upstream using MEME. These 20 motifs were displayed as sequence
LOGOs representing position weight matrices of each possible letter code occuring at particular
position of motif and its height representing the probability of the letter at that position
multiplied by the total information content of the stack in bits.
Figure S5: 5kb upstream region of mouse UMOD was investigated for DNase I hypersensitive
sites available in ENCODE project. An overlap of DHS signal was found and shown as blue
band over motif 1, 2, 3 and 9 near ~0.25 kb UMOD transcription start site (TSS) in the mouse
block diagram previously shown in Figure 2b.
Figure S6: Hierarchical Clustering of TFs using the protein interaction network shown in Figure
S5c.
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Figure S7. Transcripts expression data corresponds to TFs were collected from Human Body
Map databases across 16 tissues. Data were filtered with RPKM (Reads per Kilobase per Million
mapped reads) >50 for kidney followed by row wise normalization across 16 tissue with
maximum value. RPKM value of each TFs in kidney was shown at just left of heatmap.
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Supplementary Table Legends
Table S1: This table enlists human-UMOD in orthologous species (primates and rodents) with
its location (coordinates) and % query, target matching.
Table S2: Motifs identified in 2kb upstream region of UMOD in occuring species was shown.
For each motif, significance, location from start (0 in block diagram) and sequence at location
for each species was documented.
Table S3: Correlation indices of motifs identified in both analysis i.e. for 2kb upstream (10
motifs) and 5 kb upstream (20 motifs), separately were shown. Comparison matrix of 2kb motifs
(Orange) and 5kb motifs (Blue) using Pearson correlation was also documented (at bottom).
Table S4: This table enlists predicted TFs associated to 10 motifs identified in 2kb upstreams
region of UMOD using TOMTOM.
Table S5: Motifs identified in 5kb upstream region of UMOD in occuring species was shown.
For each motif, significance, location from start (0 in block diagram) and sequence at location
for each species was documented.
Table S6: This table enlists predicted TFs associated to 20 motifs identified in 5kb upstreams
region of UMOD using TOMTOM.
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Supplementary Text
TEXT 1: Materials and Methods.
UMOD transcripts and their expression profiles across tissues
UMOD gene is located on chromosome 16. We obtained human UMOD gene (Ensembl ID
ENSG00000169344)
and
its
sequence
from
the
ENSEMBL
database
(http://useast.ensembl.org/Homo_sapiens/Search/Details?db=core;end=1;idx=Gene;q=UMOD;sp
ecies=Homo_sapiens). There are 15 transcripts reported in Ensembl database for human UMOD
gene (Table 1). Full length transcripts of this gene which had expression data available were used
for expression profiling. RNA-seq data available for 16 different human tissues (viz. adipose,
adrenal, brain, breast, colon, heart, kidney, liver, lung, lymph, muscle, ovary, prostate, testes,
thyroid and white blood cells) from ArrayExpress1 (Accession no. E-MTAB-513) as part of the
Human Body Map (HBM) 2.0 project (http://www.ebi.ac.uk/arrayexpress/experiments/EMTAB-513/) 2, was obtained for expression profiling the transcripts of interest. Expression data
from the HBM project is quantified per transcript using the current annotations of the human
genome from the Ensembl and is available as Reads Per Kilobase per Millions of reads (RPKM)
for each sample and hence can be compared across tissues. Expression profiles of UMOD
transcripts were visualized using matrix2png 3.
Identification of human-UMOD orthologs and their upstream regulatory regions for
phylogenetic footprinting
Phylogenetic foot printing is one of the classical methods applied for DNA binding motif
discovery 4, 5. It involves using the upstream regulatory sequence of a gene of interest across
possible orthologs to search for highly conserved consensus DNA binding sites. We selected 15
orthologs of human UMOD gene including eight primates and seven rodents using Ensembl
Compara gene trees 6 which allowed the identification of orthologous sequences across species
with high sequence resemblance as shown in Table S1. Gene tree for UMOD and 15 selected
orthologs using webPRANK 7 showing the phylogenetic relationship is available as Figure S2.
Gene expression is controlled by various cis-acting transcriptional regulatory factors by binding
mostly in close proximity to the transcription start sites in the promoter regions of a gene 8.
Based on previous computational studies from other groups 9, 10 and our own analysis (data not
shown) we found that most functional TF binding sites occur with-in the 5kb upstream region of
the gene starts. So we initially focused our study on 2kb upstream regions of UMOD for motif
discovery and later extended to 5kb region. Upstream regulatory regions for human and its 15
listed (Table S1) UMOD orthologs were obtained from Ensembl database.
MEME analysis for discovering DNA binding motifs
DNA binding motif discovery using phylogenetic footprinting approach uses regulatory regions
in the promoters of orthologous genes from multiple species under the notion that regulatory
elements would be conserved in the background of non-functional sequences and hence can be
discriminated as footprints contributing to regulatory control. To facilitate the motif finding in
these regions we used the MEME-suite of tools 11. MEME is a tool for discovering motifs in a
group of related DNA or protein sequences, which detects the frequently occurring conserved
sequence across a group of related DNA sequences, using expectation maximization 12. These
motifs are typically represented as position-dependent letter-probability matrices in logos which
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describe the probability of each possible letter at each position in the pattern to incorporate the
variation in the detected motif instances across sequences. In this study, both 2kb and 5kb
upstream sequences of human UMOD and its 15 orthologs (12 orthologs for 5kb regions due to
limitations on the total length of the sequences) were compiled as a fasta file and used as an input
for MEME to identify significantly over-represented motifs (p <1E-28).
Prediction of TFs associated with discovered motifs
Transcription Factors (TFs) are proteins which bind specifically to their corresponding binding
motif and regulate the expression of a gene. DNA binding motifs were represented as PWM
(Position-Specific Weight Matrix) based logos. Nucleotide constituent of each consensus motif
has its own probability of occurrence within the site. Since PWMs for various TFs have already
been reported in JASPAR 13, Uni-PROBE 14 and Jolma et al 15 public databases, based on a
comparison of the similarity between the reported PWM of a TF to the footprinted PWM in the
orthologous upstream regions, it is possible to predict the TFs which are most likely to bind to
these predicted binding sites. Tomtom 16 is a tool in the MEME-suite which compares discovered
DNA motifs to known motifs of such databases. PWMs of various discovered motifs were used
as input file for Tomtom and compared with already reported PWMs of TFs from Jolma2013 15,
JASPAR_CORE_2009 13 and Uniprobe_Mouse 14 databases to identify the potential TFs
binding to the UMOD upstream regions. Only the TF associations which are identified at p ≤
0.02 are considered significant for both the 2kb and 5kb regions.
Analysis of DNase I hypersensitive site in UMOD upstream region.
DNase I hypersensitive sites are open chromatin region of DNA, sensitive to DNase I cleavage.
After enzymatic cleavage, this site is accessible to binding of protein such as transcription factor.
It is believed that, occurence of DHS in a region, especially in promoter region 17 is an indicator
of potential binding of transcription factor. We extracted the DHS data available for adult mouse
kidney from ENCODE project18 and visualized it for upstream region of UMOD gene in UCSC
genome browser (http://genome.ucsc.edu/cgi-bin/hgFileUi?db=mm9&g=wgEncodeUwDnase).
The image generated from the browser was positioned according to the coordinate of UMOD
upstream region of block diagram and studied for active BMo.
Calculating motif abundance similarity across genomes
To quantitatively compare the number of instances of a given motif across various genomes we
first constructed a matrix comprising the number of instances of a motif across the genomes and
then divided each value by the maximum number of times it was identified in a genome. Such a
motif centric normalized matrix was used as input to the cluster algorithm 19 to hierarchically
cluster the motifs using uncentered correlation as the distance metric and complete linkage as the
clustering method. Resulting data matrix was used to generate a heatmap using the javatree view
package 20. To have an identity for each motif, potential TF likely to bind the motif based on
Tomtom analysis was used as a reference name, along with the motif ID. Similar approach was
adopted to hierarchically cluster the protein-protein interaction network between TFs by
constructing a matrix of physical interactions between all pairs of TFs.
Mapping protein interactions between the potential TFs
Eukaryotic TFs often regulate the expression of genes by forming protein complexes and several
examples have been documented in the literature including that of SP1 interacting with SMAD3
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21
, KLF4 22 and GATA3 23 in kidney/kidney cell line to modulate the transcription of target
genes. So we employed the currently available manually curated set of protein-protein
interactions for the human genome available from the Biogrid database 24 to map the physical
associations between the predicted TFs from the Tomtom analysis for the 5kb region. This not
only allowed the construction of a protein interaction network between the predicted TFs but
allowed the dissection of the major TFs based on their number of protein interactions in the
network. TFs which had high degree were analyzed for their expression across cell types
available from Rat Transcriptomic database25 and Human Body Map 2.0 database.
TEXT 2. UMOD is kidney specific
Current information on UMOD mRNA and protein expression levels from databases such as
BioGps (www.biogps.org) and Gene cards (www.genecards.org) indicate that it is exclusively
expressed in kidney (Figure S1a, b). To further confirm the expression levels of UMOD gene in
the human kidney, we analyzed the currently available RNA-seq data for 16 different human
tissues
including
kidney
from
the
Human
Body
Map
2.0
Project
(http://rnaseq.crg.es/project/HBM/) (see Materials and Methods). Our analysis unambiguously
confirmed the specificity of UMOD’s transcripts to the kidney (Figure S1c). RNA-seq data
indicated the expression of only five full length transcripts across any of the 16 tissues studied,
with significant expression for the transcripts ENST00000396138 (464.44 RPKM),
ENST00000302509 (11706.4 RPKM) and ENST00000396142 (18775.3 RPKM) in kidney.
Indeed, all of these transcripts with significant expression (Measured as Reads Per Kilobase per
Millions of reads in the sample) were found to be exclusively expressed in the kidney. We also
found that that the transcript ENST00000396134 (3.3 RPKM in kidney) was very weakly
expressed across all tissues albeit with relatively higher level in the kidney suggesting that such
transcripts contribute little to the expression of UMOD. More generally, our results also suggest
that all the major transcript forms of UMOD are expressed exclusively in the kidney and hence
UMOD is likely to exhibit a specific cis-regulatory signature not prevalent in other non-kidney
specific genes.
TEXT 3: Description of some important transcription factors.
Transcription Factors:
HNF 1 α / β - Hepatocyte nuclear factor-1 beta is a homeo protein of HNF-1 family. This
transcription factor recognizes and binds to the consensus sequence 5-GTTAATNATTAAC-3 as
a homodimer or can form a heterodimer with a related protein, HNF-1 alpha and is involved in
controlling tissue-specific gene expression in kidney, liver, pancreas, and other epithelial organs
26
. In kidney, dysfunction of HNF beta is associated with renal cyst formation by modulating the
transcriptional activity of cystic genes like UMOD in mouse 27 however is not associated to
postnatal stage of human 28. Discovered binding motif 2 in our analysis was predicted to be
bound by this family of TFs. Comparison of the reported consensus sequence for HNF1 beta 26
clearly showed a 15 bp overlap with our discovered motif indicating that UMOD is under the
transcriptional control of this protein.
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ELF3 - E74-like factor 3 (ELF3) belongs to ETS family and is expressed exclusively in
epithelial cells under normal physiological conditions 29. It is a trans-acting phosphoprotein that
contains a DNA-binding winged helix-turn-helix domain (ETS domain) 30. ELF3 was predicted
to be able to bind with high specificity to our discovered motif 1 consensus 5'ACAGAGACCTTGTATTTCCGGGCACAGGTG-3' with an overlap of 12 bp (Figure 3). ELF3
is documented to be involved in various biological processes like differentiation of epithelial
cells, gut development, apoptosis and carcinogenesis. However its own expression level is
reported to be induced by stress or inflammatory responses 31 and hence can be a potential
regulatory factor governing the expression level of UMOD in stress or injury.
GATA3 - GATA3 is a C2C2-type zinc finger GATA family transcription factor which was
found
to
be
specific
to
our
discovered
consensus
sequence
5’ATCCCCATTTCATAGACAAGAAAATTGACC-3’ associated with Motif 10 (Figure 3b) with
an overlap of 22 bp in its binding region. The crystal structure of GATA3 DNA-Binding Domain
(DBD) bound to DNA, reported a palindromic sequence with two GATA-binding sites separated
by 3 bp further showing resemblance with our discovered consensus sequence 32. GATA3 is
expressed in the developing parathyroid glands, inner ear, and kidney, as well as in the thymus
and central nervous system. In kidney, it plays an important role in renal-specific immune
responses by generating T2 cells thus triggering higher T2 and T1 cell ratio during viral infection
or inflammation in AKI 33.
SP1 / SP3 - SP1 and SP3 belong to Specificity Protein (Sp) family, a zinc finger transcription
factor family which play an important role in transcription of viral and many cellular genes 34
including housekeeping genes 35. Sp1 and Sp3 were reported to be structural homologs in their
DNA binding domain region, however they differ in their functionality as revealed from in vitro
and in vivo studies 36. These TFs participate in chromatin remodeling by interacting or recruiting
pre-initiation complex, histone modifying enzymes and chromatin remodeling complexes to
facilitate regulation of gene expression 37. However certain posttranslational modifications in
these TFs, like phosphorylation, acetylation, sumoylation, ubiquitylation, and glycosylation have
been documented to contribute to the tissue specific role of SP family members 38. Various
studies have been reviewed with sufficient evidence 34, 39 for a cross talk between SP1 and STAT
3 in cancer progression and tumor development, indicating dysregulation of SP1 to be one of the
potent causes of aberrations in biological processes. These transcription factors can potentially
bind to GC rich motifs 38 and thus regulate the gene expression. Our results suggest the binding
specificity of these transcription factors to motif 5 consensus sequence (complementary) 3’TGTTTTTTGATATTGTTTTCTTGGGGGTGG-5’ with a high confidence.
SMAD3 - SMADs are downstream components of signaling cascades and act as transcriptional
mediators of multiple signaling pathways. SMAD3 is a member of the SMAD family which
plays a key role in modulating the transcriptional activity of target genes administered by
transforming growth factor-beta 140. SMAD3 has been shown to induce fibrosis and wound
healing under a variety of ailments like radiation-associated skin injury, bleomycin-induced lung
fibrosis, acute myocardial infarction induced cardiac fibrosis, obstructive kidney disease, and
liver and colon fibrosis 41. It is reported to bind to CAGA box 42, 43 and in some cases to the
reverse palindromic sequence ‘GTCTAGAC’ known as SBE (Smad Binding Element) 44 in the
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upstream regions of target genes by co-complexing with proteins like SP1 21. Motif 7 identified
in our analysis was predicted to be bound by SMAD3 further supporting the binding specificity
of this TF to UMOD regulatory regions. On a broader analysis for 5 kb upstream regions of
UMOD (see section below and Materials and Methods), consensus sequences of three detected
motifs 5, 6 and 13 all suggested SMAD3 to have high affinity to bind to them and was also found
to have high degree of physical interactions with other TFs like HNF 4, SP1, RUNX2 and
RUNX3 etc. in a protein-protein interaction network between TFs (Figure 4c).
RUNX2 - RUNX2 belongs to Runt domain family of transcription factors and is an essential TF
for osteoblast development and proper bone formation. It has 128 AA DNA binding domain
which interacts with the target binding site 5’-TGT/cGGTT- 3’ (or its complement) 45. It was
found to be specific for binding to Motif 7 (Tables S5 and S6). RUNX2 is documented to be
involved in a myriad of regulatory processes including in the activation or repression of target
genes with its associated co-activators (CBB beta, MOZ), co-repressors (STAT1, YAP1), cotranscription factors (SMADs, AP1, MSX2, oct1, ETS-1), extracellular signal mediators such as
integrins and steroid hormones as well as post translational modifiers like MAP kinases,
Ubiqutin E3 ligases and PKC acetyltransferases 45. Recently, a study reported RUNX2 as
prosurvival transcription factor in renal tubuloepithelial cell lines as well as in mouse kidney
tubules and was suggested to be responsible for promoting a protective role in these cells under
the command of parathyroid hormone-related protein 46.
Pou2f1 - Pou2 belongs to the archetypal group of transcription factors which includes the TFs,
Oct-1 (Pou2f1) and Oct-2 (Pou2f2). Pou2 binds specifically to 5’-ATGCCAAT-3’ known as the
octamer element 47. Pou2f1 is one of the primeval (POU) transcription factors and is the first
member reported from the Pou-family 48. It is known to be involved in several biological
processes 49 and stress/survival response signals 50, 51. It can coordinate the signal to target genes
by forming a complex with other transcription factors like SP1 52 and CREB1 53. It is believed
that its expression could mediate the stress response effect in kidney dysfunction/injury condition
by actively participating in regulation of UMOD gene and altering its expression.
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