Prepared in cooperation with the U.S. Fish and Wildlife Service

Differential Expression Profiles of microRNA in 

the Little Brown Bat (Myotis lucifugus) Associated with 

White Nose Syndrome Affected and Unaffected Individuals

Open-File Report 2013–1099

U.S. Department of the Interior

U.S. Geological Survey

Differential Expression Profiles of 

microRNA in the Little Brown Bat (Myotis 

lucifugus) Associated with White Nose 

Syndrome Affected and Unaffected 

Individuals

By D. D. Iwanowicz, L. R. Iwanowicz, N. P. Hitt, and T. L. King

Prepared in cooperation with the U.S. Fish and Wildlife Service 

Open-File Report 2013–1099

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013

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Suggested citation:

Iwanowicz, D.D., Iwanowicz, L.R., Hitt, N.P., and King, T.L., 2013, Differential expression profiles of microRNA in the 

little brown bat (Myotis lucifugus) associated with white nose syndrome affected and unaffected individuals: U.S. 

Geological Survey Open-File Report 2013–1099, 11 p.
iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Methods...........................................................................................................................................................2

Sequencing data analysis and miRNA identification .....................................................................3

Next Generation Sequencing and Databases .................................................................................4

Results .............................................................................................................................................................4

Histology.................................................................................................................................................5

Genetic Screening................................................................................................................................5

Next Generation Sequencing and Databases .................................................................................5

Summary..........................................................................................................................................................8

References Cited............................................................................................................................................9

Glossary.........................................................................................................................................................11

Figures

1. Representation of small non-coding RNA molecules that are found in the current 

ENSEMBL microbat non-coding RNA database .....................................................................4

2. Internal transcribed spacer polymerase chain reaction analysis of DNA extracted 

from bat wing biopsy tissue ........................................................................................................4

3. Proportional Venn diagram depicting the distribution of unique and common 

mature miRNA in both the White Nose Syndrome positive treatment group and 

the WNS-negative treatment group ..........................................................................................7

4. Statistically significant differences in differentially regulated non-coding RNA 

between White Nose Syndrome-(WNS) positive and WNS-negative groups...................7

Tables

1. General sequencing results and analytical handling of sequence reads for 

expression analysis with the number of fragments included in RNA-Seq analysis..........5

2. Most abundant mature miRNA detected in the White Nose Syndrome 

positive group................................................................................................................................6

3. Most abundant mature miRNA detected in the White Nose Syndrome 

negative group ..............................................................................................................................6

4. Unique miRNA detected in the White Nose Syndrome positive group...............................6

5. Unique miRNA detected in the White Nose Syndrome negative group .............................7
iv

Conversion Factors and Datum

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in)

millimeter (mm) 0.03937 inch (in)

Volume

liter (L) 33.82 ounce, fluid (fl. oz)

liter (L) 2.113 pint (pt)

liter (L) 1.057 quart (qt)

liter (L) 0.2642 gallon (gal)

liter (L) 61.02 cubic inch (in3) 

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83)
Differential Expression Profiles of microRNA in the Little 

Brown Bat (Myotis lucifugus) Associated with White 

Nose Syndrome Affected and Unaffected Individuals

By D. D. Iwanowicz, L. R. Iwanowicz, N. P. Hitt, and T. L. King

Abstract

First documented in New York State in 2006, white 

nose syndrome (WNS) quickly became the leading cause of 

mortality in hibernating bat species in the United States. WNS 

is caused by a psychrophilic fungus, Geomyces destructans. 

Clinical signs of this pathogen are expressed as a dusty white 

fungus predominately around the nose and on the wings of 

affected bats. Relatively new biomarkers, such as microRNAs 

(miRNAs) are being targeted as markers to predict the syndrome prior to the clinical manifestation. The primary objective of this study was to identify miRNAs that could serve as 

biomarkers and proxies of little brown bat health. Bats were 

collected from hibernacula that had tested positive and negative for WNS. Genetic sequencing was completed using the 

Ion Torrent platform. A number of miRNAs were identified 

from the liver as putative biomarkers of WNS. However, given 

the small sample size for each treatment, this data set has only 

coarsely identified miRNAs indicative of WNS, and further 

validation is required.

Introduction

White-nose syndrome (WNS) was first documented in 

New York State during 2006. This syndrome is associated 

with mortality and morbidity in multi-species of bats in the 

United States. Since the first description and observation of 

WNS, increased mortality rates have been reported, and the 

geographical range of WNS has expanded to include most of 

the continental United States. This syndrome affects hibernating bat species, including the little brown bat (Myotis lucifugus) and the federally listed Indiana bat (Myotis sodalis). 

Given the considerable effects that WNS seems to have on 

such populations, further structured research is imperative to 

identify at risk populations and develop reliable predictive 

diagnostic tools.

The disease condition of WNS syndrome is caused by the 

psychrophilic fungus Geomyces destructans (G. destructans)

(Blehert and others, 2009; Gargas and others, 2009; and Lorch 

and others, 2011), which grows optimally at the low temperatures characteristic of hibernacula. The presence of this pathogen on the wings and nose of affected bats is the hallmark 

clinical sign of this emerging disease. Originally believed 

to only occur in eastern North America, G. destructans has 

recently been identified across Europe (Hayes, 2012; Pikula 

and others, 2012; Šimonovičov and others, 2011; Puechmaille 

and others, 2011; Wibbelt and others, 2010; and Martínková, 

2010). Although G. destructans clinically manifests on bats in 

Europe, infections have not been linked to the mortality seen 

in the United States (Verant and others, 2012). Reasons for the 

discrepancy have not been determined, but the reasons could 

be found in the physiological differences in either the bats or 

the fungus (Hayes, 2012).

A salient aspect of this syndrome is the current geographical range. Although it is suspected that warmer temperatures at southern latitudes may impede the growth of the 

fungus, the disease is clearly expanding to these areas. To date, 

WNS has been observed in bat hibernacula in 16 states and 4 

Canadian provinces. It is expected that observations of WNS 

affected bats in other states is likely. In the WNS-affected bat 

hibernacula, at least seven species of bats have succumbed to 

mortality from WNS, including the federally endangered Indiana bat (Myotis sodalis). The number of bats killed by WNS is 

estimated to be more than 5.7 million, with some hibernacula 

experiencing 100 percent mortality (Froschauer and Coleman, 2012). Bats exhibit unique life-history characteristics 

that make them very susceptible to this type of population 

decline (social community structure, longevity, low fecundity). 

Given the geographic scale of WNS, it is clear that a better 

understanding of WNS requires a concerted multidisciplinary 

research approach that considers the community structure 

of the host, the host environment (hibernacula), microbial 

community structure (pathogen and other microbes), and 

putative biomarkers. 
2 Differential Expression Profiles of microRNA in the Little Brown Bat Associated with White Nose Syndrome

Colonies of little brown bats, either affected or unaffected 

by WNS, have been identified by the U.S. Fish and Wildlife 

Service (USFWS) and state wildlife management agencies. 

Regardless of the cause of WNS, bats affected or unaffected 

by this syndrome (clinical or preclinical) are physiologically different from each other by virtue of this disease or 

other predisposing factors. Non-invasive comparative physiological examination of these bats is likely to reveal differences indicative of the problem, presumably leading to the 

development of predictive markers of the syndrome prior to 

clinical manifestation.

Biomarkers are commonly exploited in human and animal health as indicators of normal physiological or pathological conditions. Recent discoveries and advances in molecular 

biology have identified a unique class of regulatory molecules 

that have the potential to revolutionize diagnostic research 

(Gilad and others, 2008). These molecules termed small 

RNAs are a class of small single-stranded noncoding RNAs 

(about 18–30 nucleotides in length) that essentially function 

by silencing genes at the transcriptional or post-transcriptional 

level and, therefore, ultimately regulate the synthesis of gene 

products (Hamilton and Baulcombe, 1999; Birchler and Kavi, 

2008). Small RNAs have been identified in animals, plants, 

and viruses. The wealth of multispecies microRNAs (miRNAs) has led to the development of a functional database, 

miRBase, which contains data on more than 17,000 distinct 

mature miRNAs from over 140 species (Kozomara and 

Griffiths-Jones, 2011). Bioinformatics and cloning studies estimate that miRNAs may regulate 30 percent of all human genes 

(Wang and others, 2007). Many studies have determined that 

individual miRNA’s may play pleiotropic physiological roles 

(Jenkins and others, 2012). Profiles of miRNA expression have 

been used successfully as biomarkers of physiological conditions, such as pregnancy (Gilad and others, 2008) and abnormal conditions, including cancer (Waldman and Terzic, 2007; 

Mitchell and others, 2008; and Tanaka and others, 2009).

The primary objective of the investigation, conducted 

by the U.S. Geological Survey in cooperation with the U.S. 

Fish and Wildlife Service (proposal title “Expanding our 

understanding of White Nose Syndrome in Little Brown Bats 

Myopsis lucifugus”), was to identify miRNAs that could serve 

as biomarkers or proxies of little brown bat physiological condition and health. More specifically, the intent was to identify 

miRNA biomarkers indicative of little brown bat populations 

at risk for WNS. A number of hepatic miRNAs and other small 

noncoding RNAs (ncRNAs) associated with hibernating bats 

with or without clinical WNS have been identified. A few 

candidate biomarkers have been identified, but require further 

validation for field application.

This report presents a discussion of the methods used 

to investigate the presence or absence of WNS and a fungus 

in little brown bats in three types of hibernacula. Discussion 

of the results includes descriptions of histology and genetic 

screening. Next generation sequencing and databases also 

are discussed. 

Methods

The proposed experimental design for this project 

included the collection of samples across a similar longitude 

(1) in caves that exhibited no signs of WNS (Ohio), (2) with 

WNS in the area but not in the cave sampled (Pennsylvania), 

and (3) in WNS infected hibernacula (New Jersey). The goal 

was to sample 10 to 15 bats collected at each hibernaculum. 

Sampling times were to include (1) during hibernation, (2) 

during early arousal (early winter), and (3) during early spring 

at the end of hibernation. Additionally, all sampling methods 

were proposed to be non-lethal and minimally invasive (for 

example, samples of blood and guano). This sampling regime 

would provide 45 bats per cave and the subsequent knowledge of the best time to collect bats for miRNA detection. 

Because of conflicts with cave closings and the inability of 

the USFWS, state agencies, and non-governmental organizations to assist in these collections as initially proposed, the 

experimental design was modified to include only two caves 

with only five bats collected from each cave, as required by 

the cooperators. 

WNS-positive bats were collected from Snow Top Mountain Mine near Wampum, Pa., (40°53’01”N 80°20’44”W) 

in late December 2010. WNS-negative bats were collected 

at Bowden Cave, Randolph County, W.Va., (38°54’31”N 

70°42’35”W) in January 2011. Bowden Cave became positive 

for WNS in March 2011, and five more samples were collected 

in April 2011 to evaluate subsequent changes in expression. 

Regardless of the site, bats were collected in the morning, and 

bagged and processed outside of the hibernacula. Five bats 

were removed at each sampling (total of 15 bats for the study, 

n=5 per collection). Bats were euthanized with a lethal dose of 

isoflurane (a cotton ball soaked in isoflurane was placed in a 

50-milliliter (mL) conical tube; bats were individually placed 

in each tube) (AVMA, 2007). Bats remained in their respective 

tubes until no sign of life was evident. After bats were euthanized, the sex was recorded and three punch biopsies from 

the wings were collected and preserved in 95-percent ethanol. 

Blood collection was attempted by cardiac puncture; however, 

sufficient blood could not be collected from these hibernating 

animals for later use. Consequently, blood samples were successfully obtained only from the April collection. The collection of urine and feces samples were attempted from a number 

of bats, but again, such samples were not reliably obtained 

from hibernating bats. Pieces of liver, spleen, and lung were 

removed and placed in RNA Later® for molecular analyses. 

Carcasses were fixed in Z-fix and archived for histological 

evaluation. Tissues were processed for histology, embedded 

in paraffin, cut into 6-micrometer sections, and stained with 

hemotoxylin and eosin. Periodic acid-Schiff stain (PAS) was 

used to identify the presence of G. destructans. 

Genetic screening for G. destructans (5 isolates from 

each site) was based on the ribosomal RNA gene internal 

transcribed spacer (ITS) region. Briefly, DNA was extracted 

from the 2 milligrams (mg) of an ethanol fixed wing biopsy 
Methods 3

using the Qiagen DNeasy Tissue Kit (Valencia, California) 

and stored at 4 degrees Celsius (°C) prior to amplification. 

Forward and reverse primers and methods used for polymerase 

chain reaction (PCR) amplifications targeted G. destructans

sequences and followed those of Lorch and others (2010). 

In this study, the forward primer nu-SSI (1506)-184-5’Gd 

(5’-GGGGACGTCCTAAAGCCT-3’) and the reverse primer 

nu-5.8S-144-3’-Gd (5’-TTGTAATGACGCTCGGAC-3’) were 

used. All primers were purchased from Integrated DNA Technologies (www.idtdna.com). The PCR amplifications were 

conducted in a master mix containing 1 microMolar (mM) of 

each primer, 1 microliter (μL) of DNA, GoTaq® Green Master 

Mix (Promega, Madison, Wisc.), and nuclease free water. 

After amplification, 5 mL of the DNA sample was identified 

visually after electrophoresis at 90 volts for 45 minutes (min) 

in a 1.2-percent agarose gel (I.D.NA®, FMC Bioproducts, 

Rockland, Maine). 

Confirmation of the amplicons (pieces of DNA or RNA) 

as G. destructans was achieved using Sanger sequencing in 

which PCR products were cleaned with a Qiagen PCR Purification kit (Valencia, Calif.). Cycle sequencing conditions were 

25 cycles at 96°C for 30 seconds (sec), and 50°C for 15 sec, 

followed by a 4-min extension at 60°C. Cycle sequencing 

reactions were performed using Applied Biosystems (Foster 

City, Cali.) Big Dye Cycle Sequencing Kit, and the reaction 

samples were cleaned with Agencourt CleanSeq Beads (Beckman Coulter Genomics, Danvers, Mass.). The cleaned samples 

were sequenced in both directions using an Applied Biosystems 3100 Genetic Analyzer. Consensus sequences were 

generated using the forward and reverse sequences.

The isolation of miRNA was conducted using the 

Ambion® mirVanaTM miRNA isolation kit (Life Technologies, Grand Island, N.Y.) as per manufacturer recommendations. A starting mass of 10 milligrams (mg) of liver tissue 

was used for all samples. Purified miRNA was stored at 

-80°C prior to preparation for the sample library. All library 

construction was performed using specific kits and protocols 

for Ion Torrent (Life Technologies) sequencing. The miRNA 

was converted to complementary DNA (cDNA) prior to the 

development of Ion Total RNA-Seq Small RNA Libraries. 

Briefly, the concentration and quality of miRNA was assessed 

using the Agilent 2100 Bioanalyzer small RNA kit. For each 

sample, 100 nanograms (ng) of miRNA was used as the starting template. All samples were hybridized at 65°C for 10 min 

and 16°C for 5 min and then ligated at 16°C for 16 hours. 

Following ligation, a reverse transcription master mix was 

added to each sample, incubated at 70°C for 5 min, and then 

1 μL of ArrayScriptTM. Reverse Transcriptase was added and 

incubated at 42°C for 30 min. cDNA was purified with the 

MinElute® PCR Purification Kit (Qiagen, Valencia, Calif.) 

and eluted with 10 μL of elution buffer. Samples were run on 

a Novex® 10-percent TBE-Urea Gel in an XCell SureLockTM 

Mini-Cell at 180 volts for 45 minutes. Two samples of gel of 

60 to 80 nucleotide (nt) were excised and placed individually 

into 0.2 mL PCR tubes. To amplify the cDNA, a PCR cocktail 

containing 76.8 μL of nuclease free water (NF H2

0), 10 μL 

of 10X PCR Buffer, 8.0 μL of 2.5 mM deoxyribonucleotide 

triphosphates (dNTP) Mix, 2.0 μL of Ion 5’PCR Primer, 

2.0 μL of Ion 3’PCR primer, and 1.2 μL of AmpliTaq® DNA 

Polymerase for a total volume of 100.0 μL was added to each 

tube. The amplification was then run on the following PCR 

cycling profile: 95°C for 5 min, 21 cycles of 95°C for 30 sec, 

62°C for 30 sec, 72°C for 30 sec, and an extension of 72°C for 

7 min. Amplified cDNA was purified with the PureLink® PCR 

Micro Kit (Life Technologies, Grand Island, N.Y.) with a final 

elution in 12 μL of elution buffer. For a final assessment of the 

yield and size distribution of the amplified DNA, the samples 

were run on the Agilent® 2100 BioanalyzerTM Instrument with 

the Agilent® DNA 1000 Kit (Agilent Technologies, Santa 

Clara, Calif.). All library concentrations were serially diluted 

following the equation below before proceeding to template 

preparation: 

[Library concentration in nanoMolar (nM)] × [(5 × 109

molecules)/*8.3 nM)] × [18 μL/(280 × 106 molecules)]. 

Once the optimal library concentration was determined, 

the Ion SphereTM Particles were prepared and cleaned following the manufacturer’s protocol (Ion Torrent, Publication part 

number 4465884 Rev.B, May 2011). An emulsion PCR was 

then generated with the following protocol: A denaturing step 

at 94°C for 6 min, followed by 40 cycles of 94°C for 30 sec, 

58°C for 30 sec, and 72°C for 90 sec, and then 5 cycles at 

94°C for 30 sec and 68°C for 6 min, with a final hold time at 

10°C forever. The ion sphere particles were then recovered 

washed and enriched with Dynabeads® MyOneTM Strepavidin 

C1 beads. Finally the beads were captured, eluted, and transferred to a 0.2 mL PCR tube and loaded onto the Ion Torrent.

Sequencing data analysis and miRNA 

identification

Adapters were trimmed from the resulting sequences and 

Ion Torrent sequence reads for individual bats were imported 

into the CLC Workbench analysis software package. Primary 

analyses included RNA-Seq analyses for each individual 

using the microbat non-coding RNA (ncRNA) library as a 

reference scaffold to determine expression levels of miRNA 

and other ncRNA. At the time of this analysis little brown bat 

genome (Ensembl, 2012) was sequenced to 7 times coverage. Although the ncRNA library (database) contains data on 

3,826 ncRNA molecules, the data are coarsely annotated to the 

level of small RNA class [for example, miRNA, small nuclear 

RNA (snRNA), small nucleolar RNA (snoRNA), ribosomal 

RNA (rRNA, and miscellaneous RNA (miscRNA); fig. 1]. Of 

these ncRNA, 795 are putative miRNA. This database was 

selected for the current analysis because it is the only source 

of authentic little brown bat ncRNA sequences available. By 

using this database, the consideration of mismatches could be 

circumvented for the initial analyses. RNA-Seq expression 

data were reported as reads per kilobase per million mapped 
4 Differential Expression Profiles of microRNA in the Little Brown Bat Associated with White Nose Syndrome

miRNA

snRNA

snoRNA

rRNA

miscRNA

795

1,308

1,175

173

375

EXPLANATION

Figure 1. Representation of small non-coding RNA molecules 

that are found in the current ENSEMBL microbat non-coding RNA 

database (http://useast.ensembl.org/Myotis_lucifugus/Info/Index).

reads. Values were normalized to the total number of sequence 

reads from the sample with the least number of reads. 

All secondary quantitative analyses were executed using 

the small RNA workflow in CLC Workbench. Trimmed 

sequences from individual bats were analyzed using the 

extract and count procedure. Sequences were excluded from 

analyses if values were less than 15 nt or greater than 55 nt. 

Additionally, sequences were discarded if they appeared less 

than three times in a given sequence read. Annotation of the 

sequences was executed using the “Annotate and Merge” command in CLC Workbench. This procedure used the microbat 

ncRNA database as the primary database and the miRBase as 

the secondary database for annotation. 

The abundance of miRNAs was compared between bats 

collected from confirmed WNS-negative, WNS-transitional 

(prior to WNS-positive determination), and WNS-positive 

hibernacula. Data were refined to identify the miRNA biomarker candidates. Thresholds for data refinement included 

analysis of those miRNA that were present only in one 

treatment group and not the other, or if relative differences in 

expression were greater than two fold. Differences in expression were expressed as the ratio of median miRNA abundance 

in WNS-positive bats to that of WNS-negative bats. 

Next Generation Sequencing and Databases

Databases used for quantification and analysis, and annotation, of Myotis lucifugus miRNAs included the ENSEMBL 

microbat ncRNA database and miRBase (release 18). Approximately 21 percent of the microbat ncRNA database is miRNA 

(795 unique sequences, fig. 2). The sequences in miRBase 

used for this analysis included four species, Mus musculus, 

Bos taurus, Homo sapiens, and Mus domesticus, and the numbers of corresponding miRNA in the database from each were 

741, 662, 1,526 and 156, respectively. 

WNS- WNS+ WNS+/-

L 7643 521 9 12118 13 14 15 L 10

Figure 2. Internal transcribed spacer polymerase chain reaction 

analysis of DNA extracted from bat wing biopsy tissue. The 

example is agarose gel images from the three collections of 

the White Nose Syndrome (WNS) negative group from January 

2011(Bowden Cave, Randolph County, West Virginia; 38°54’31”N 

70°42’35”W), the WNS positive group from December 2010 (Snow 

Top Mountain Mine near Wampum, Pennsylvania; 40°53’01”N 

80°20’44”W), and the Bowden Cave samples collected in March 

2011 (Bowden Cave, Randolph County, West Virginia; 38°54’31”N 

70°42’35”W). Products are the amplicons of the Geomyces 

destructans internal transcribed spacer region of the 18S gene; 

1.2-percent agarose gel. 

MicroRNA from 13 bats was sequenced using the Ion 

Torrent PGM platform. These analyses were conducted on 

four bats from a WNS-negative hibernaculum, four bats 

from a WNS-positive hibernaculum, and five from a tWNStransitional hibernaculum. The status of these hibernacula was 

based on official status reports by state wildlife managers and 

was confirmed by PCR analyses (fig. 2). Sequence data for 

the WNS-transitional hibernaculum are not included in the 

results here because relevant temporal control treatment was 

not available. 

Results

Multiple end-points were used to determine the presence 

of G. destructans within the sampled bats, including both 

histology and PCR amplification and sequencing the rRNAITS region. Histological analysis is considered the standard for 

diagnosis of G. destructans in WNS and was used in tandem 

with PCR of the G. destructans ITS region for a multi-tiered 

confirmation (Lorch and others, 2010). 

Histology 

Histological analysis confirmed that bats from Bowden 

Cave, presumed negative at sampling by local officials, 

were all negative for G. destructans fugal hyphae. Bats from 
Results 5

Snow Top Mountain Mine that exhibited clinical signs of 

WNS (white noses and bodies) in the field, however, were 

also negative by histological analysis (exhibited no fungal hyphae). Interestingly, the bats tested from Bowden 

Cave in April all exhibited signs of fungal hyphae with a 

light infection. 

Genetic Screening

PCR of the ITS region of G. destructans consistently 

amplified G. destructans specific product in 5 of the 15 bats 

tested. These bats were from the Snow Top Mountain Cave 

December 2010 sampling (fig. 2). PCR was repeated six 

times per individual, and extractions were repeated twice. 

The five bats that were consistently positive for G. destructans were not found to be positive for WNS by histopathological analysis. This result is atypical to what Lorch and 

others (2010) found in their research but likely reflect the 

stage of infection. The five bats collected from Bowden Cave 

during March 2011were all positive for WNS by histopathological analysis. However, with PCR positive detection 

was not routinely acquired for all bats. All bats were PCR 

positive for G. destructans for at least one PCR reaction. 

This very likely reflects a sampling bias for the punch biopsy 

method and a low grade infection of G. destructans, and 

therefore, a low yield of extracted fungal DNA. 

Next Generation Sequencing and Databases

Approximately 2.7 million reads were obtained from 

the eight bat samples (four bats from a WNS-negative 

hibernaculum, Bowden Cave January 2011, and four bats 

from a WNS-positive hibernaculum, Snow Top Mountain 

December 2010) with an average of 337,000 reads per sample 

(table 1). Sequence reads averaged 66 bases. An average 

of 123,000 sequences from each sample was utilized in the 

expression analysis. An Extract & Count analysis was performed that included each individual sequence read within a 

treatment group. The resulting data file was subjected to an 

automated annotation procedure within CLC bio Genomics 

Workbench using the Mus musculus mature miRNA database 

within the MirBase v18 database. This analysis yielded 220 

mature miRNA. The most abundant miRNA identified in each 

treatment group are identified in tables 2 and 3, in descending order of abundance. The miRNA unique to each treatment 

group are listed in tables 4 and 5. The expression of these 

mature miRNAs appeared to differ between groups (fig. 3). 

Several miRNAs were identified as being potentially different (fig. 4) on the basis of the Wilcoxin based ranked sum 

test; however, the sample size was small. The difference in 

mature miRNAs is very likely an artifact of the small sample 

size (number of individuals). Given that the samples were not 

normalized prior to this analysis, inclusion as a unique miRNA 

does not reflect abundance, and a miRNA was counted if it 

was identified in as few as one individual in a group. A number of miRNAs and other ncRNAs were identified that were 

either unique in each treatment group or were present at a 

significantly different abundance. 

A few ncRNAs were identified that were differentially expressed in the liver samples between 

WNS-positive and WNS-negative groups. These 

included ENSMLUT00000020579 (putative miR574), ENSMLUT00000021974 (putative miR-2531), 

ENSMLUT00000021023 (putative miscRNA), ENSMLUT00000018522 (putative snoRD62), and ENSMLUT00000020118 (putative snoRD28; fig. 4). The biological significance of these ncRNAs is largely unknown.

Table 1. General sequencing results and analytical handling of sequence reads for expression 

analysis with the number of fragments included in RNA-Seq analysis. Much of the sequence data did 

not correspond to any data in either database.

[%, percent]

Sample 

number 

of bat

Total sequence 

reads

(Thousands)

Count 

(Annotated)

(Thousands)

Perfect matches 

in miRBase 

database

Perfect matches 

in ENSEMBL 

database

Unannotated*

6 183 18 (10.1%) 7.7% 92.2% 89.9%

8 362 99 (27.4%) 17.8% 82.2% 72.6%

9 239 19 (7.8%) 10.4% 89.6% 92.2%

10 475 260 (54.8%) 37.9% 62.1% 45.2%

1 382 253 (66.3%) 35.2% 64.8% 33.7%

2 436 112 (25.6%) 9.2% 90.8% 74.4%

4 374 180 (48.4%) 25.8% 74.2% 51.6%

5 244 39 (16.1%) 14.3% 85.7% 83.9%

*

Indicates the proportion of total sequences not included in the expression analysis and likely indicates novel small 

RNAs.
6 Differential Expression Profiles of microRNA in the Little Brown Bat Associated with White Nose Syndrome

Table 2. Most abundant mature miRNA detected in the White 

Nose Syndrome-positive group (Snow Top Mountain Mine near 

Wampum, Pennsylvania; 40°53’01”N 80°20’44”W). Identification 

is based solely on miRBase homology to the house mouse (Mus 

musculus).

Mature miRNA sequence Putative identifier

AAACCGTTACCATTACTGAGTT mir-451

CTGACCTATGAATTGACAGCC mir-192

TGGAGTGTGACAATGGTGTTTG mir-122

TGTAAACATCCTACACTCAGCT mir-30b

TAGCTTATCAGACTGATGTTGA mir-21

TGTAAACATCCTACACTCTCAGC mir-30c-1//mir-30c-2

CAACGGAATCCCAAAAGCAGCTG mir-191

AACCCGTAGATCCGATCTTGTG mir-99a

TGTAACAGCAACTCCATGTGGA mir-194-1//mir-194-2

GTCCAGTTTTCCCAGGAATCCCT mir-145

TCCCTGAGACCCTAACTTGTGA mir-125b-2//mir-125b-1

TGAGGTAGTAGGTTGTATAGTT let-7a-1//let-7a-2

CCCAGTGTTCAGACTACCTGTTC mir-199a-1//mir-199a-2

TGAGGTAGTAGTTTGTACAGTT let-7g

TAGCAGCACGTAAATATTGGCG mir-16-1//mir-16-2

TTCAAGTAATCCAGGATAGGCT mir-26a-1//mir-26a-2

CATTATTACTTTTGGTACGCG mir-126

TCCCTGAGACCCTTTAACCTGTGA mir-125a

TGTAAACATCCTCGACTGGAAG mir-30a

TGTAAACATCCCCGACTGGAAG mir-30d

Table 3. Most abundant mature miRNA detected in the White 

Nose Syndrome-negative group (Bowden Cave, Randolph 

County, West Virginia; 38°54’31”N 70°42’35”W). Identification is 

based solely on miRBase homology to the house mouse (Mus 

musculus).

Mature miRNA sequence Putative identifier

CTGACCTATGAATTGACAGCC mir-192

AAACCGTTACCATTACTGAGTT mir-451

TGTAAACATCCTACACTCAGCT mir-30b

TGGAGTGTGACAATGGTGTTTG mir-122

TGTAAACATCCTACACTCTCAGC mir-30c-1//mir-30c-2

TAGCTTATCAGACTGATGTTGA mir-21

CAACGGAATCCCAAAAGCAGCTG mir-191

AACCCGTAGATCCGATCTTGTG mir-99a

TTCAAGTAATCCAGGATAGGCT mir-26a-1//mir-26a-2

TGTAACAGCAACTCCATGTGGA mir-194-1//mir-194-2

GTCCAGTTTTCCCAGGAATCCCT mir-145

TAGCAGCACGTAAATATTGGCG mir-16-1//mir-16-2

TGAGGTAGTAGTTTGTACAGTT let-7g

TCCCTGAGACCCTAACTTGTGA mir-125b-2//mir-125b-1

CATTATTACTTTTGGTACGCG mir-126

CCCAGTGTTCAGACTACCTGTTC mir-199a-1//mir-199a-2

TGTAAACATCCTCGACTGGAAG mir-30a

TGTAAACATCCCCGACTGGAAG mir-30d

TGAGGTAGTAGGTTGTATAGTT let-7a-1//let-7a-2

TCCCTGAGACCCTTTAACCTGTGA mir-125a

Table 4. Unique miRNA detected in the White Nose Syndromepositive group (Snow Top Mountain Mine near Wampum, 

Pennsylvania; 40°53’01”N 80°20’44”W). These sequences were 

not seen in any bats from the White Nose Syndrome-negative 

cave (Bowden Cave, Randolph County, West Virginia; 38°54’31”N 

70°42’35”W).

Feature sequence Putative identifier

ACAGTACTGTGATAACTGA mir-101c

TACCCTGTAGAACCGAATTTGTG mir-10b

AGGGCTTAGCTGCTTGTGAGCA mir-27a

AGGAGCTCACAATCTATTTAG mir-28b

AGGGACGGGACGTGGTGCAGTGTT mir-92b

CGGGGCCGTAGCACTGTCTGA mir-128-1

AACCGTGGCTTTCGATTGTTAC mir-132

GCTGGTAAAATGGAACCAAAT mir-133a-1//mir-133a-2

TATGGCTTTTTATTCCTATGTGA mir-135a-1//mir-135a-2

TATGGCTTTTCATTCCTATGTGA mir-135b

TAGGTTATCCGTGTTGCCTTCG mir-154

AACATTCATTGTTGTCGGTGGGT mir-181d

ATGGAGGTCTCTGTCTGACTT mir-1843b

TTCCTATGCATATACTTCTTT mir-202

AGTGGTTCTTGACAGTTCAACA mir-203

TACTGCATCAGGAACTGACTGGA mir-217

TGATTGTCCAAACGCAATTCT mir-219-1

ACTTAAACGTGGTTGTACTTGC mir-302a

TGGCCAAGGATGAGAACT mir-3096

GGGGGGCAGGAGGGGCTCAGGG mir-328

TTATAAAGCAATGAGACTGATT mir-340

AGGGGTGCTATCTGTGATTGAG mir-342

AAAGTGCATGCGCTTTGGG mir-350

AGATCGACCGTGTTATATTCGC mir-369

GCGACGAGCCCCTCGCACAAAC mir-375

AGAGGTTGCCCTTGGTGAATTC mir-377

TGGTCGACCAGCTGGAAAGTAAT mir-412

AATGACACGATCACTCCCGTTGA mir-425

TTTTGCGATGTGTTCCTAATAT mir-450a-1//mir-450a-2

AAGACGGGAGAAGAGAAGGGAG mir-483

GAAGTTGCCCATGTTATTTTTCG mir-495

AATCCTTTGTCCCTGGGTGAAA mir-501

GGAGAAATTATCCTTGGTGTGT mir-539

AAGTTGCCCGCGTGTTTTTCG mir-543

TCTTGTTAAAAAGCAGAGTCT mir-544

TGGTGCGGAAAGGGCCCACAGT mir-675

TGGTTGACCAGAGAGCACACG mir-758

CACCACCTCCCCTGCAAACGTCC mir-1306

CCCCCGAGGAGGACGAGGAGGA mir-1895

CAGTGGTAGAGCATATGAC mir-1957

AGCTGCCAGCTGTAGAACTGT mir-3966

AGCTTGTCTGACTGATGTTG mir-3967

TAGCTCAGCGGGAGAGCAC mir-5112
Results 7

Table 5. Unique miRNA detected in the White Nose Syndromenegative group (Bowden Cave, Randolph County, West Virginia; 

38°54’31”N 70°42’35”W). These sequences were not seen in 

any bats from the White Nose Syndrome-positive cave (Snow 

Top Mountain Mine near Wampum, Pennsylvania; 40°53’01”N 

80°20’44”W).

Feature identifier Name

ACATACTTCTTTATATGCCCATA mir-1a-1

TACATACTTCTTTACATTCCA mir-1b

AGGCAGTGTAGTTAGCTGATTGC mir-34c

GGTTTACCGTCCCACATACAT mir-299b

AGGTGGTCCGTGGCGCGTTCGC mir-323

AACAATATCCTGGTGCTGAGTG mir-338

AGCGAGGTTGCCCTTTGTATATT mir-381

AGGTTGTCCGTGTTGTCTTCTC mir-494

GCCGGCGGGAGCCCCAGGGAG mir-2137

GGCGCCGCTCGTGGGGGGCC mir-5105

WNS- WNS+

10 167 43

Figure 3. Proportional Venn diagram depicting the distribution 

of unique and common mature miRNA in both the White Nose 

Syndrome-(WNS) positive treatment group (Snow Top Mountain 

Mine near Wampum, Pennsylvania; 40°53’01”N 80°20’44”W) and 

the WNS-negative treatment group (Bowden Cave, Randolph 

County, West Virginia; 38°54’31”N 70°42’35”W). Numbers of the 

outer areas are the numbers of unique mature miRNA found 

in individual groups; the number in the center is the number of 

common mature miRNA found in both the positive and negative 

WNS groups.

10,000

8,000

6,000

4,000

2,000

0

RPKM

miRNA miscRNA snoRNA

Noncoding RNA

A

WNSWNS+

EXPLANATION

B C

D

E

Figure 4. Statistically significant differences in differentially 

regulated non-coding RNA between White Nose Syndrome- 

(WNS) positive (Snow Top Mountain Mine near Wampum, 

Pennsylvania; 40°53’01”N 80°20’44”W) and WNS-negative groups 

(Bowden Cave, Randolph County, West Virginia; 38°54’31”N 

70°42’35”W). Putative identification of the non-coding RNAs are 

A=miR-574, B=miR-2531, C=miscRNA, D=snoRD62, E=snoRD28. 

Wilcoxon signed-rank test; p is equal to or less than 0.05. (RPKM, 

reads per kilobase per million)
8 Differential Expression Profiles of microRNA in the Little Brown Bat Associated with White Nose Syndrome

Summary

The original intent of this research was to identify 

microRNA (miRNA) profiles indicative of White Nose Syndrome- (WNS) susceptible bat colonies. At the onset of this 

research, WNS was still an idiopathic disease associated with 

G. destructans. Given that fungi are rarely primary pathogens, 

it was hypothesized that bat colonies were susceptible as a 

result of an altered physiological status and that the physiological regulatory environment could be used as a proxy to 

identify such individuals or populations. The original proposed 

sample design included the collection of bats from similar 

latitudes extending westward to locations where WNS had not 

been documented. Those proposed hibernacula were defined 

as (1) confirmed WNS-infected hibernacula (New Jersey), (2) 

WNS present in the area but not in the sampled cave (Pennsylvania), and (3) WNS-negative hibernacula (Ohio). The goal 

was to collect 10 to 15 bats at each hibernaculum at multiple 

time points, including (1) during hibernation, (2) during early 

arousal (early winter), and (3) during early spring at the end 

of hibernation. Additionally, all sampling was proposed to be 

non-lethal and minimally invasive. Target biological samples 

included body fluids, such as blood and urine. However, 

because of unforeseen difficulties in the coordination with 

field biologists to collect samples across the proposed sample 

range and times, the sample design was modified considerably 

to coordinate with available field support of field biologists 

from cooperating governmental agencies and non-governmental organizations. These necessary modifications included 

limiting the number of sample locations, sample size, and 

target tissues for analysis, which radically affected the overall 

expected outcome of the proposed research. However, in 

spite of these restrictions, the study was still able to identify 

miRNAs associated with WNS-affected or -unaffected bats. At 

the present time (2013), it is unknown whether these miRNAs 

are associated with the diseased condition of affected bats 

or indicate an underlying physiological status that indicates 

susceptibility to the fungus.

A few non-coding RNAs (ncRNAs) were identified 

in this study as putative biomarkers of WNS. Two of these 

were miRNAs, putative miR-574 and miR-2531. Little is 

known about the specific functions of these miRs; however, 

miR-574-5p has been utilized as a serum-based marker of 

non-small cell lung cancer in humans (Foss and others, 2011). 

Most miRNAs are pleiotropic and affect numerous target 

messenger RNAs, thus it is possible that this miRNA may 

be a legitimate biomarker associated with WNS. Because of 

the limitations associated with the collection of body fluids 

from hibernating bats (that are generally poorly hydrated), the 

miRNA expression here reflects that exclusively in the liver. It 

is possible that these miRNAs are also present in the plasma, 

but confirmation would require further analysis with appropriate biological samples. Additionally, validation of expression 

levels of these miRNAs still requires validation using real time 

PCR(qPCR). Given the small sample size (n=4) for each treatment, the statistical power of the analyses were considerably 

affected. As a result, this data set has only coarsely identified 

biomarker miRNA as indicative of WNS, and further validation of this result using a larger sample size is necessary. This 

work does, however, establish baseline research regarding the 

identification of little brown bat miRNAs that can be used in 

future investigations. 

Of note, when the sequence data were compared to those 

within both miRBase and ENSEMBL databases, there were 

discrepancies regarding the miRNAs identified as potential 

biomarkers. This likely reflects the novelty of miRNA and 

ncRNA research and the less than comprehensive comparative databases. Greater than 70 percent of the sequences were 

not included in these analyses because there were no homologous small RNA data in available databases. Annotation and 

validation of these novel sequences will take considerable 

time and effort (years) and was beyond the scope of the current research. It is possible that some of these sequences may 

serve as biomarkers, but further validation and analysis with 

adequate sample sizes is necessary.

Since the first identification of WNS in the United States 

and confirmation of G. destructans as the associated primary 

pathogen, this fungal pathogen has been identified in Europe. 

More specifically it has been isolated from external samples of 

bats inhabiting locations in Germany, Hungary, and Switzerland. Of particular note, Europeans bats do not appear to be 

mortally affected by G. destructans. It has been postulated 

that this suspected resistance is the result of adaptive pressures associated with coevolution and that such bats may be 

more immunologically or behaviorally resistant compared to 

the bats in the United States. The miRNAs identified in this 

study may be useful markers for further comparative analyses 

designed to rigorously investigate such differences. 
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Glossary 11

Glossary

Bioinformatics The retrieval and analysis of 

biochemical and biological data using mathematics and computer science, as in the study 

of genomes.

Clone A cell, cell product, or organism that 

is genetically identical to the unit or 

Individual from which it was derived.

Complementary DNA Single-stranded DNA 

synthesized in the laboratory using messenger 

RNA as a template and the enzyme reverse 

transcriptase.

Fecundity Capacity of producing young.

Gene Expression Process by which information from a gene is used in the synthesis of a 

functional gene product.

Genetic Screening Assessment of an individual’s genetic makeup in an attempt to predict genetic predisposition to certain illnesses.

Hibernacula Winter quarters of a hibernating animal. 

Histology The structure, especially the 

microscopic structure, of organic tissues.

Longevity The length or duration of life.

PCR Abbreviation for polymerase chain 

reaction: a technique for rapidly producing 

many copies of a fragment of DNA for diagnostic or research purposes.

Putative Commonly regarded as being; supposed.

Ribosomal RNA A type of RNA, distinguished by its length and abundance, functioning in Protein synthesis as a component of 

ribosomes (abbrev: rRNA).

Salient Prominent or conspicuous.

Sequence To determine the order of (chemical units in a polymer chain), especially 

nucleotides in DNA or RNA or amino acids in 

a protein.

Small RNA Term used for short noncoding RNA. There are different classes of 

small RNAs such as small nucleolar RNAs 

(snoRNAs), small nuclear RNAs (snRNAs), 

miscellaneous RNAs (miscRNA). Each class 

primarily guide chemical modifications of 

other RNAs.

microRNA Single-stranded RNA molecules 

of about 21-23 nucleotides in length, which 

regulate gene expression.

Prepared by the West Trenton Publishing Service Center.

For more information concerning this report, contact:

Director

U.S. Geological Survey

Leetown Science Center

11649 Leetown Road

Kearneysville, WV 25430

or visit our Web site at:

http://www.lsc.usgs.gov/
Iwanowicz and others—Differential Expression Profiles of microRNA in the Little Brown Bat Associated with White Nose Syndrome—Open-File Report 2013–1099