JARB Journal of Animal Reproduction and Biotehnology

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Journal of Animal Reproduction and Biotechnology 2021; 36(1): 35-44

Published online March 31, 2021

https://doi.org/10.12750/JARB.36.1.35

Copyright © The Korean Society of Animal Reproduction and Biotechnology.

Identification of plasma miRNA biomarkers for pregnancy detection in dairy cattle

Hyun-Joo Lim *, Hyun Jong Kim , Ji Hwan Lee , Dong Hyun Lim , Jun Kyu Son , Eun-Tae Kim , Gulwon Jang and Dong-Hyeon Kim

Dairy Science Division, Department of Animal Resources Development, National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Korea

Correspondence to: Hyun-Joo Lim
E-mail: limhj0511@korea.kr
ORCID https://orcid.org/0000-0001-7059-1553

Received: October 19, 2020; Revised: March 12, 2021; Accepted: March 13, 2021

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

A pregnancy diagnosis is an important standard for control of livestock’s reproduction in paricular dairy cattle. High reproductive performance in dairy animals is a essential condition to realize of high life-time production. Pregnancy diagnosis is crucial to shortening the calving interval by enabling the farmer to identify open animals so as to treat or re-breed them at the earliest opportunity. MicroRNAs are short RNA molecules which are critically involved in regulating gene expression during both health and disease. This study is sought to establish the feasible of circulating miRNAs as biomarkers of early pregnancy in cattle. We applied Illumina small-RNA sequencing to profile miRNAs in plasma samples collected from 12 non-pregnant cows (“open” cows: samples were collected before insemination (non-pregnant state) and after pregnancy check at the indicated time points) on weeks 0, 4, 8, 12 and 16. Using small RNA sequencing we identified a total of 115 miRNAs that were differentially expressed weeks 16 relative to non-pregnancy (“open” cows). Weeks 8, 12 and 16 of pregnancy commonly showed a distinct increase in circulating levels of miR-221 and miR-320a. Through genome-wide analyses we have successfully profiled plasma miRNA populations associated with pregnancy in cattle. Their application in the field of reproductive biology has opened up opportunities for research communities to look for pregnancy biomarker molecules in dairy cattle.

Keywords: dairy cattle, miRNA, pregnancy diagnosis

Mammals should reproduce to be able to lactate. Estrus detection, artificial insemination (AI) and pregnancy diagonosis are routinely performed. Good reproductive management in dairy farms is reliant on early and precise diagnosis of pregnancy. Currently, several pregnancy diagnosis tools including the rectal palpation, ultrasonography, milk progesterone test, and preganncy-associated glycoproteins have been widely utilized. Any direct or indirect method for pregnancy diagnosis must accurately distinguish between pregnant and non-pregnant animals. Pregnancy diagnosis can identify open cows, help expect calving dates, and help producers make culling decisions. Early identification of non-pregnant dairy cattle post AI can improve reproductive performance and pregnancy rate by decreasing the interval between AI services and increasing AI service rate. Identification of animals in a herd that fails to conceive within 3 weeks after insemination would reduce economic losses. Finally it extends the calving interval and have contributed to the decline in profitability. Thus, new technologies to identify pregnant dairy cattle early after artificial insemination (AI) may play a key role in economically viable reproductive management decision to improve reproductive performance and profitability to commercial dairy farms.

Currently, several pregnancy diagnosis tools use molecules including pregnancy-associated glycoproteins (PAGs), protein B, DG29 and preliplantation factor (PIF). Research to develop commercial indirect mehods for pregnancy diagnosis continues because these methods are non-invasive and the tests can be marketed to and performed by dairy farmers or herd employees. We aimed at finding micro RNA (miRNAs) biomarkers by hypothesis-free, small RNA next generation sequencing (NGS). miRNAs are small non-coding RNAs molecule (16-27 nt long) that act as post-transcriptional gene regulators and play important roles in regulation of gene expression. The research for easily accessible biomarkers of several diseases and physiological condition has recently focused on circulating microRNAs (miRNA). The differentially expressed miRNAs could serve as feasible biomarkers for not only early diagnosis of pregnancy but also for various livestock health and disease (Hale et al., 2014). As miRNAs are mainly secreted into small extracellular vesicles and miRNAs have been found in numerous biofluids ranging from serum and amniotic fluid to urine and milk (Reid et al., 2011; Pohler et al., 2015). They can therefore be taken as a liquid biopsy and represent ideal molecules for the use of non-invasive biomarker of disease. (Reid et al., 2011; Buschmann et al., 2016).

MicroRNAs are expeled from cells of most tissue types in plasma membrane bound extracellular vesicles (EV), in particular exosomes. The packaging of miRNA in EVs or exosomes is important in terms of a detection standpoint as ribonuclease (RNA-ases) are unable to penetrate and breakdown the miRNA allowing them to be extracted from blood and serum (Reid et al., 2011). Exosomes and EVs play a crucial role in intercellular communication, including promotion of sperm maturation, regulation of immune function, release of miRNA for a wide array of regulatory functions, as well as other roles currently under reserach (Raposo and Stoorvogel, 2013). Plasma and whole blood have found an appropriate resource of EV-derived miRNA profiles, thus offering a feasible blood-borne biomarker candidate for several disease and physiological condition (Häusler et al., 2010; Reid et al., 2011).

Human based disease resaerch has found significant differences in profusion of miRNAs for many cancers (Lawrie et al., 2008; Häusler et al., 2010), heart disease (Tijsen et al., 2010) and sepsis (Wang et al., 2010). Furthermore, earlier studies in humans have shown that circulating miRNA profiles related to pregnancy become more pronounced as pregnancy progresses. Circulating miRNAs in maternal serum have been regarded as feasible biomarkers of pregnancy condition due to their significant impact on gene expression and regulation (Chim et al., 2008). A study by Gilad et al. (2008) identified miRNAs that are increased in profusion in pregnant humans but not in non-pregnant females. This finding led to the sharp progress of identifying miRNAs that were unique to pregnancy and across various species, although none have been thoroughly explained.

This thesis is aimed to focus on physiological role of miRNAs during pregnancy, alsso emphasizing their feasible for being biomarkers for pregnancy detection. The object of the present study was to determine the expression pattern of circulatory miRNAs in plasma of pregnant and non-pregnant dairy cows.

Animals selection and sampling

The selected animals and the experimental protocol were approved by institutional animal ethical committee of the National Institute of Animal Science (NIAS). A total of 30 dairy cow were used according to their health condition, parity (≥ 2) and with a BCS of approximately 3.5. After pregnancy diagnosis, non-pregnant cows were excluded from the analysis. For the present investigation, the blood samples were collected from individual animal (n = 12) on different weeks of pregnancy (0, 4, 8, 12 and 16 weeks). Day 0 represents the control (collection of blood before artificial insemination: AI). Following AI, blood was collected from the cows till the 16 weeks of pregnancy. Briefly, about 10 mL whole blood was collected in EDTA tubes, and then the samples were incubated at room temperature for 1 h. The collected blood sample was centrifuged at 3,000 rpm for 15 min at 4℃ to obtain plasma. After this step, the circulating cell-free nucleic acid was in the supernatant (plasma) and then the obtained plasma was transferred into a fresh 2.0 mL tube and the plasma samples were stored at -80℃ until further processing.

Confirmation of pregnancy

Pregnancy was diagnosed by palpation per rectum of the uterine contents between days 50 and 60 after AI or ultrasonic examination to determine pregnancy status. Ultrasonography was carried out using a B-Mode ultrasound scanner (MyLabTMOneVET, esaote) equipped with a 5.0-MHz linear array probe. Pregnancy diagnosis was confirmed by observation of embryocoele and allantoic fluid (Abdullah et al., 2014). The ovaries were also scanned for the presence of corpus luteum.

Total RNA isolation

Before RNA isolation, the exosomes in plasma were firstly isolated by using Total Exosomes Isolation kit (Invitrogen, Carlsbad, CA). Exosomal total RNA, including mRNA and miRNA, was isolated by using miRNeasy Mini Kit (Qiagen) following manufacturer’s protocos. The concentration of RNA was measured by using the Qubit microRNA assay kit (Invitrogen, Carlsbad, CA). RNA integrity of all RNA eluates was assessed. And high quality (RNA integrity number ≥ 7) samples from isolated total RNA were selected. The total RNA with lowest quality was not used for further study. The RNA samples were stored at -80℃ until further processing.

Illumina sequencing and data analysis

Total RNA (5 mL) from each sample was used to construct miRNA library by using the NEXTflex Small RNA Sequencing Kit (Illumina, San Diego, CA) according to the manufacturer’s instruction. Small RNA libraries were then pooled together in equal volumes for gel purification. The pooled library was sequenced by using the HiSeq 2500 system (Illumina) as 50 bp single reads. Read quality (adaptor removal, and size selection) was assessed using FastQC v0.11.5 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and cutadapt (Martin, 2011). The sequences with read length larger than 18 nucleotides (nt) were aligned against bovine miRNA database (miR-Base, release version 21) with the default parameters to identify known miRNAs using Bowtie2 (Langmead and Salzberg, 2012). Each library was processed separately. The expression level of miRNAs in each library was estimated by sRNAbench, which normalized reads count number of each miRNA reads per million (RPM) by the following foumula: RPM = (miRNA reads number/total mapped reads per library) × 1,000,000. The differentially expressed (DE) miRNAs were investigated by using bioinformatics tool edgeR v3.10.2 (Robinson et al., 2010). The DE miRNAs were determined by Log2 fold change (FC) > 1 OR < -1 and false discovery rate (FDR) < 0.05 based on counting reads by using HTSeq (Anders et al., 2015).

Identification of novel miRNA prediction

Prediction of novel miRNAs was performed by using the miRDeep2 software. Briefly, quality-trimmed reads from all samples were combined into a single reads file followed by the preprocessing, mapping, and novel miRNA prediction steps through mapper.pl and miRDeep2.pl scripts. Next, the FASTA files of predicted novel miRNA and quantifier.pl script were used to determine the read-counts/expression values for each novel miRNA from each sample. Combined count matrix for novel miRNAs was generated by using the custom scripts. Differential expression between control and pregnant groups was calculated by using the DESeq2 package (version 1.12.4).

We sequenced a total of 60 blood samples from non-pregnancy and 16 weeks of pregnancy. On average, the high throughput Illumina sequencing resulted in 22.4 million raw reads per sample from the exosomes of all stages (Table 1). 71.5% reads were uniquely mapped to annotate miRNAs in bovine genome.

Table 1 . Sequencing and miRNA profiling statistics of normal and days of pregnancy samples

SampleTotal readsMapped reads (%)Precursor miRNA readsMature miRNA readsKnown precursor with ≥ 5× coverageNo. known miRNANo. novel miRNA
Normal24773796.0 ± 3962727.173.2 ± 5.6305494.7 ± 81383.07713350.2 ± 2613944.7361.7 ± 45.0334.8 ± 27.4 491.8 ± 138.4
4 weeks19421596.7 ± 3587596.674.3 ± 4.7179172.5 ± 146647.28038306.5 ± 3180088.2385.5 ± 57.1307.3 ± 37.2 367.3 ± 178.1
8 weeks24122975.9 ± 4669481.770.7 ± 12.5239792.4 ± 154469.7 6806040.9 ± 3069368.0383.9 ± 53.6314.4 ± 43.0410.0 ± 179.6
12 weeks22139499.4 ± 3132885.268.8 ± 5.8155846.3 ± 56288.97785174.4 ± 1930464.7374.7 ± 28.2306.1 ± 19.7320.7 ± 72.9
16 weeks21845616.1 ± 2814855.670.5 ± 6.8140514.6 ± 54922.57386644.1 ± 1905019.6343.1 ± 39.2307.0 ± 35.0316.7 ± 83.6

The average data of all five analyzed samples for each animal is displayed.



Venn diagrams were used to demonstrate the overlap between pregnant groups (Fig. 1). Pregnant 8, 12 and 16 weeks groups had 2 common miRNAs (bta-miR-221 and bta-miR-320a).

Figure 1. Venn diagrma showing the overlap of the number and percentage of miRNAs detected in plasma samples.

To determine the miRNA expression patterns in blood samples, miRNA microarray analysis was conducted. By using small RNA sequencing we identified a total of 115 miRNAs that were differentially expressed on pregnancy compared to non-pregnancy. A total of 115 miRNAs were identified to be significantly differentially expressed between the groups; 91 miRNAs were upregulated and 26 miRNAs were downregulated (Table 2). And 91 upregulated and 26 downregulated miRNAs are listed (Table 3).

Table 2 . Differential miRNA profile expression between normal and weeks of prengnancy groups (p-value < 0.05)

Differentially expressed miRNAsUpDown
4 weeks98
8 weeks168
12 weeks32
16 weeks638


Table 3 . List of significantly differentially expressed plasma circulatory miRNAs in pregnant cows

WeekGene_ida.valuep.valueq.value
Up-regulation
4 weeksbta-miR-455-5p1.071864930.042596140.98472459
bta-miR-193b9.600837490.003096880.50066183
bta-miR-133a9.909826350.033997510.98472459
bta-miR-296-5p11.1354140.019740890.98472459
bta-miR-130711.62372960.028104070.98472459
bta-miR-34215.44006310.037377140.98472459
bta-miR-15016.07780230.000424260.20576638
bta-miR-339a16.22707170.005684940.6892985
bta-miR-339b16.51137710.009924020.80219133
8 weeksbta-miR-23495.529787130.036430070.80182568
bta-miR-2299-3p10.98424920.037826670.80182568
bta-miR-87711.58085170.026690410.80182568
bta-miR-428612.16092160.04915370.80182568
bta-miR-37812.39583760.017199060.78481392
bta-miR-14313.09279180.02015740.78481392
bta-miR-2284z13.621520.044366740.80182568
bta-miR-2284aa14.00333620.039166450.80182568
bta-miR-45114.5886540.040876860.80182568
bta-miR-32814.5996980.022078440.78481392
bta-miR-37515.14852130.006976310.6188333
bta-miR-339a16.28407690.002897510.57394257
bta-miR-15016.34534270.012003760.78481392
bta-miR-15016.52516870.001687360.57394257
bta-miR-22117.07219930.007671490.6188333
bta-miR-320a18.47417940.00355750.57394257
12 weeksbta-miR-22116.79798490.004103781
bta-miR-26a14.91687730.030690571
bta-miR-320a18.29246350.035970421
16 weeksbta-miR-24811.149638510.030411010.28213644
bta-miR-133b2.868699020.00302510.06646495
bta-miR-23465.762419160.04236370.32562789
bta-miR-1275.978362780.043107560.32562789
bta-miR-1584-3p7.202873770.048276210.34076361
bta-miR-6119-5p7.206863330.041941460.32562789
bta-miR-146a7.342240670.020605630.24081834
bta-miR-23b-5p7.504147780.0106680.16368713
bta-miR-200b7.550218040.009224510.15405228
bta-miR-12968.481942520.021294130.24081834
bta-miR-133a8.682072220.001086190.04102443
bta-miR-2118.938802250.049275390.34076361
bta-miR-2284w9.147773050.020517130.24081834
bta-miR-7449.223867860.006698010.12180462
bta-miR-7699.790080830.006271570.12144622
bta-miR-193b9.79922750.009412560.15405228
bta-miR-2284ab10.70004890.035869820.29850986
bta-miR-3210.72063890.031603880.28213644
bta-miR-2299-3p10.78751790.002376510.0648259
bta-miR-296-5p10.82195270.000126210.00834593
bta-miR-29b11.1148110.001848550.06050908
16 weeksbta-miR-57411.13832290.031484690.28213644
bta-miR-87711.22420150.002297090.0648259
bta-miR-130711.30366640.000152980.00834593
bta-miR-345-3p11.39750950.039645580.3191144
bta-miR-2285f11.48133840.003107420.06646495
bta-miR-9811.77132340.034858270.29850986
bta-miR-428611.78126850.000840860.03440499
bta-miR-16a12.03244170.000285750.01403053
bta-miR-126-3p12.0347860.007397630.12972271
bta-miR-425-3p12.15198120.017001180.22677729
bta-miR-88512.19306320.026277890.27452004
bta-miR-32612.33060690.04880330.34076361
bta-miR-18512.34410550.037924510.31034894
bta-miR-37812.42273550.043017510.32562789
bta-miR-2285k12.77707550.031264960.28213644
bta-miR-16b13.03785580.001461220.05124697
bta-miR-65213.15756260.029673020.28213644
bta-miR-26b13.20769220.013286240.18851546
bta-miR-2284y13.36548160.020494320.24081834
bta-miR-14313.39761770.001163750.00399116
bta-miR-2284z13.42318160.018640530.24081834
bta-miR-2284aa13.84863830.028800730.28213644
bta-miR-87413.94592770.001976430.00399116
bta-miR-27a-3p13.98671050.003889760.07957799
bta-miR-10b14.26900920.009776440.15484621
bta-miR-21514.35116910.021580460.24081834
bta-miR-32814.40052580.013437970.18851546
bta-miR-19714.46554930.024839390.27102538
bta-miR-130614.53820780.021373290.24081834
bta-miR-29a14.96442050.003113430.06646495
bta-miR-37515.03060740.00270770.06646495
bta-miR-26a15.12684210.002023950.06210982
bta-miR-45115.19977360.000379210.01692671
bta-miR-142-5p15.35040920.000152290.00834593
bta-let-7g15.65078680.013422060.18851546
bta-miR-339a15.93907830.000905170.00142078
bta-miR-30e-5p15.95344420.03425030.29850986
bta-miR-15016.19510350.002545830.06578964
bta-let-7b16.22475720.046347030.33964761
bta-miR-339b16.2308310.001972380.00399116
bta-miR-22116.74515050.001362490.00142078
bta-miR-320a18.18786670.001350290.00399116
Down-regulation
4 weeksbta-miR-2454-5p-4.289396940.001502320.36431335
bta-miR-2415-5p-4.289396940.00771440.74829656
bta-miR-7861-4.289396940.024194680.98472459
bta-miR-196a-4.289396940.025150210.98472459
bta-miR-4449-4.289396940.034338010.98472459
bta-miR-338-4.289396940.036129270.98472459
bta-miR-1277-4.289396940.036275680.98472459
bta-miR-17-3p-4.289396940.047100530.98472459
8 weeksbta-miR-2313-5p-4.484120730.006789680.6188333
bta-miR-4449-4.484120730.014302480.78481392
bta-miR-2284h-3p-4.484120730.017396990.78481392
bta-miR-2378-4.484120730.018016760.78481392
bta-miR-154b-4.484120730.022701230.78481392
bta-miR-381-4.484120730.030923790.80182568
bta-miR-187-4.484120730.032581870.80182568
bta-miR-99a-3p-4.484120730.046756560.80182568
12 weeksbta-miR-346-4.173037050.038265481
bta-miR-187-4.173037050.04686531
16 weeksbta-miR-196a-4.244906610.006430960.12144622
bta-miR-2377-4.244906610.017089120.22677729
bta-miR-2378-4.244906610.026052440.27452004
bta-miR-2446-4.244906610.027462470.2809182
bta-miR-346-4.244906610.03044510.28213644
bta-miR-4449-4.244906610.035668520.29850986
bta-miR-188-4.244906610.044805450.33332536


Gene ontology (GO) and pathway enrichment analysis were used to explore the functions of differentially expressed genes in bta-miR-221 (Fig. 2A). The target genes were enriched in a total of 167 GO terms, which included 12 molecular function (GO:MF), 132 biological process (GO:BP), and 23 cellular component (GO:CC) terms, in addition to reactomes (REAC), and WiKiPathways (WP). The target genes of differentially expressed bta-miR-320a were significantly enriched in a total of 144 GO terms, which included 23 molecular function (GO:MF), 98 biological process (GO:BP), and 23 cellular component (GO:CC) terms, in addition to reactomes (REAC), and WiKiPathways (WP).

Figure 2. Manhattan plot illustrating the differentially expressed gene-enriched GO terms (MF, molecular function; BP, biological process; and CC, cellular component) and KEGG pathways across reactome pathways (REAC), WiKi-Pathways (WP), transcription factor (TF), microRNA target base (MIRNA), and human phenotype ontology (HP) term categories. (A) bta-miR-221 enriched in GO terms and pathways. (B) bta-miR-320a enriched in GO terms and pathways.

This study aimed to characterize the earliest changes in miRNA expression for the purpose of define a marker for early pregnancy detection. We determined the expression pattern of circulatory miRNAs in plasma of pregnant and non-pregnant dairy cattle. Varing expression patterns of circulating miRNAs in the regulation of pregnancy has been determined in bovines (Cai et al., 2017). Many researchers are now investigating miRNAs as biomarkers for pregnancy diagnosis in the cow. There is increasing evidence that pregnancy specific miRNAs exist and may be feasible markers for pregnancy diagnosis. In 2015, exosomal miRNAs were reported to be differentially expressed in pregnant versus non-pregnant dairy cattle and dairy cattle undergoing early embryonic mortality (Pohler et al., 2015). A recent study by Fiandanese et al. (2016) identified a feasible miRNA, bta-miR 140, as an early biomarker for pregnancy diagnosis in high producing dairy cows. At day 19, bta-miR 140 was up regulated in all pregnant dairy cattle, and at day 13 onwards, it was upregulated in pregnant, non-lactating dairy cattle (Fiandanese et al., 2016). Similarly, Ioannidis and Donadeu (2016) proved different stages of the estrous cycle (day 16: bta-miR-26a, bta-miR-29c, bta-miR-138, bta-miR-204. Day 24: bta-miR-1249, day 16 & 24: hsa-miR-4532) that were differentially expressed in pregnant heifers and miR-26a was differentially upregulated on Day 16 pregnant relative to non-pregnant heifers. The expression pattern of miR-496 and miR-125a has significantly varied during formation of bovine conceptus. This clearly suggests the role of these miRNAs in maternal-to-zygotic transcription translation (Tesfaye et al., 2009). Likewise, various miRNAs including miR-27a and miR-92b are differentially expressed during the formation of the placenta (Su et al., 2010). In the present study, we report the results of circulating bta-miR-221 and bta-miR-320a were notably expressed at over 8 weeks of pregnancy. The expression of miR-221 during pregnancy indicates the interface between maternal and fetal. Also miR-320 may promote uterine migration of endometrial stromal cells during gestation (Bidarimath et al., 2014).

Increading proofes indicated the presence of human placenta-specific miRNAs in maternal circulation. The expression of placenta-specific human chromosome 19 miRNA cluster (C19MC); hsa-miR-515-3p, hsa-miR-517a, hsa-miR-517c, hsa-miR-518b, and hsa-miR-526b increased in maternal circulation during the third trimester of pregnancy and decreased after parturition (Kotlabova et al., 2011). The villous of trophoblast cells shed the C19MC miRNA cluster encapsulated in exosomes and could be the main source of placenta-specific miRNAs in maternal circulation (Luo et al., 2009; Donker et al., 2012). Furthermore, according to Morales-Prieto et al. (2013) the human chromosome 14 miRNA cluster (C14MC) is also announced to be related to pregnancy. Other miRNAs involving miR-141, miR-149, miR-299-5p, and miR-135, which are offered to be aplenty expressed in placenta were also augmented in plasma of pregnant women and their concentration declines after parturition (Chim et al., 2008). Eariler study expressed that 25 miRNAs were differentially expressed between exosomes of maternal serum derived from non-pregnant and day 30 and 90 pregnant ewes (Cleys et al., 2014).

Even though purification is essential to accuarate optimal miRNA for pregnancy detection, results mean that miRNAs have feasible as an early pregnancy diagnosis tool. In addition, miRNA may offer information to represent embryonic viability. A study indicate dairy cattle that go through embryo mortality compared to dairy cattle that have a successful pregnancy have a significantly rose abundance of unique miRNAs at days 17 and 24 of conception (Reese et al., 2016). Future studies are needed to evaluate the repeatability of these result and to decide unique miRNA most appropriate for embryo viability survey.

Two new and generally available technologies for reproductive management include hormonal protocols such as Ovsynch (Pursley et al., 1995, 1997) and Presynch/Ovsynch (Moreira et al., 2001; Navanukraw et al., 2004) that synchronize ovulation and allow for TAI, and use of transrectal ultrasonography for early detection of non-pregnant cows. Dairy farms must schedule and administer artificial inseminations, hormone injections, and pregnancy tests for a multitude of animals on a daily or weekly basis. Detection of non-pregnant dariy cattle early after breeding can only improve reproductive performance when together with a operating schedule to quickly present non-pregnant dairy cattle for a subsequent AI service. Accurate detection of non-pregnancy is administered to synchronize estrus or ovulation to reduce the interval to the subsequent AI service.

In conclusion, comprehensive profiling of miRNAs in plasma of pregnant and non-pregnant dairy cattle found specific miRNA expression pattern. Much studies and development efforts are being made toward advancement of a pregnancy diagnosis for dairy cattle. Our study provides an experimental basis to reveal the feasible role of miRNAs as biomarkers in pregnancy diagnosis. This specific pregnancy differentially expressed miRNAs marker can be used as the retrospective detection of early pregnancy biomarkers. Pregnancy-associated microRNA profiling at 8 weeks in bovine was described for the first time and can be used for comparative studies. These miRNAs may have similar function in mammalian species and can be feasible molecular markers for evolution. Coupling a non-pregnancy diagnosis with a management strategies to quickly reinitiate. AI service may improve reproductive performance by decreasing the interval between AI services and the effectiveness of hormonal ovulation and estrus control protocols initiated at certain physiologic stages post AI breeding. Future experiments are needed in this area to truly understand early identification of pregnancy diagnosis through miRNA biomarkers.

This work was carried out with the support of the “Cooperative Research Program for Agriculture Science & Technology Development (Project title: Development of early pregnancy diagnostic technology using fetal DNA isolated from maternal plasma, Project No. PJ01199401)” Rural Development Administration, Republic of Korea.

No potential conflict of interest relevant to this article was reported.

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Article

Original Article

Journal of Animal Reproduction and Biotechnology 2021; 36(1): 35-44

Published online March 31, 2021 https://doi.org/10.12750/JARB.36.1.35

Copyright © The Korean Society of Animal Reproduction and Biotechnology.

Identification of plasma miRNA biomarkers for pregnancy detection in dairy cattle

Hyun-Joo Lim *, Hyun Jong Kim , Ji Hwan Lee , Dong Hyun Lim , Jun Kyu Son , Eun-Tae Kim , Gulwon Jang and Dong-Hyeon Kim

Dairy Science Division, Department of Animal Resources Development, National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Korea

Correspondence to:Hyun-Joo Lim
E-mail: limhj0511@korea.kr
ORCID https://orcid.org/0000-0001-7059-1553

Received: October 19, 2020; Revised: March 12, 2021; Accepted: March 13, 2021

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A pregnancy diagnosis is an important standard for control of livestock’s reproduction in paricular dairy cattle. High reproductive performance in dairy animals is a essential condition to realize of high life-time production. Pregnancy diagnosis is crucial to shortening the calving interval by enabling the farmer to identify open animals so as to treat or re-breed them at the earliest opportunity. MicroRNAs are short RNA molecules which are critically involved in regulating gene expression during both health and disease. This study is sought to establish the feasible of circulating miRNAs as biomarkers of early pregnancy in cattle. We applied Illumina small-RNA sequencing to profile miRNAs in plasma samples collected from 12 non-pregnant cows (“open” cows: samples were collected before insemination (non-pregnant state) and after pregnancy check at the indicated time points) on weeks 0, 4, 8, 12 and 16. Using small RNA sequencing we identified a total of 115 miRNAs that were differentially expressed weeks 16 relative to non-pregnancy (“open” cows). Weeks 8, 12 and 16 of pregnancy commonly showed a distinct increase in circulating levels of miR-221 and miR-320a. Through genome-wide analyses we have successfully profiled plasma miRNA populations associated with pregnancy in cattle. Their application in the field of reproductive biology has opened up opportunities for research communities to look for pregnancy biomarker molecules in dairy cattle.

Keywords: dairy cattle, miRNA, pregnancy diagnosis

INTRODUCTION

Mammals should reproduce to be able to lactate. Estrus detection, artificial insemination (AI) and pregnancy diagonosis are routinely performed. Good reproductive management in dairy farms is reliant on early and precise diagnosis of pregnancy. Currently, several pregnancy diagnosis tools including the rectal palpation, ultrasonography, milk progesterone test, and preganncy-associated glycoproteins have been widely utilized. Any direct or indirect method for pregnancy diagnosis must accurately distinguish between pregnant and non-pregnant animals. Pregnancy diagnosis can identify open cows, help expect calving dates, and help producers make culling decisions. Early identification of non-pregnant dairy cattle post AI can improve reproductive performance and pregnancy rate by decreasing the interval between AI services and increasing AI service rate. Identification of animals in a herd that fails to conceive within 3 weeks after insemination would reduce economic losses. Finally it extends the calving interval and have contributed to the decline in profitability. Thus, new technologies to identify pregnant dairy cattle early after artificial insemination (AI) may play a key role in economically viable reproductive management decision to improve reproductive performance and profitability to commercial dairy farms.

Currently, several pregnancy diagnosis tools use molecules including pregnancy-associated glycoproteins (PAGs), protein B, DG29 and preliplantation factor (PIF). Research to develop commercial indirect mehods for pregnancy diagnosis continues because these methods are non-invasive and the tests can be marketed to and performed by dairy farmers or herd employees. We aimed at finding micro RNA (miRNAs) biomarkers by hypothesis-free, small RNA next generation sequencing (NGS). miRNAs are small non-coding RNAs molecule (16-27 nt long) that act as post-transcriptional gene regulators and play important roles in regulation of gene expression. The research for easily accessible biomarkers of several diseases and physiological condition has recently focused on circulating microRNAs (miRNA). The differentially expressed miRNAs could serve as feasible biomarkers for not only early diagnosis of pregnancy but also for various livestock health and disease (Hale et al., 2014). As miRNAs are mainly secreted into small extracellular vesicles and miRNAs have been found in numerous biofluids ranging from serum and amniotic fluid to urine and milk (Reid et al., 2011; Pohler et al., 2015). They can therefore be taken as a liquid biopsy and represent ideal molecules for the use of non-invasive biomarker of disease. (Reid et al., 2011; Buschmann et al., 2016).

MicroRNAs are expeled from cells of most tissue types in plasma membrane bound extracellular vesicles (EV), in particular exosomes. The packaging of miRNA in EVs or exosomes is important in terms of a detection standpoint as ribonuclease (RNA-ases) are unable to penetrate and breakdown the miRNA allowing them to be extracted from blood and serum (Reid et al., 2011). Exosomes and EVs play a crucial role in intercellular communication, including promotion of sperm maturation, regulation of immune function, release of miRNA for a wide array of regulatory functions, as well as other roles currently under reserach (Raposo and Stoorvogel, 2013). Plasma and whole blood have found an appropriate resource of EV-derived miRNA profiles, thus offering a feasible blood-borne biomarker candidate for several disease and physiological condition (Häusler et al., 2010; Reid et al., 2011).

Human based disease resaerch has found significant differences in profusion of miRNAs for many cancers (Lawrie et al., 2008; Häusler et al., 2010), heart disease (Tijsen et al., 2010) and sepsis (Wang et al., 2010). Furthermore, earlier studies in humans have shown that circulating miRNA profiles related to pregnancy become more pronounced as pregnancy progresses. Circulating miRNAs in maternal serum have been regarded as feasible biomarkers of pregnancy condition due to their significant impact on gene expression and regulation (Chim et al., 2008). A study by Gilad et al. (2008) identified miRNAs that are increased in profusion in pregnant humans but not in non-pregnant females. This finding led to the sharp progress of identifying miRNAs that were unique to pregnancy and across various species, although none have been thoroughly explained.

This thesis is aimed to focus on physiological role of miRNAs during pregnancy, alsso emphasizing their feasible for being biomarkers for pregnancy detection. The object of the present study was to determine the expression pattern of circulatory miRNAs in plasma of pregnant and non-pregnant dairy cows.

MATERIALS AND METHODS

Animals selection and sampling

The selected animals and the experimental protocol were approved by institutional animal ethical committee of the National Institute of Animal Science (NIAS). A total of 30 dairy cow were used according to their health condition, parity (≥ 2) and with a BCS of approximately 3.5. After pregnancy diagnosis, non-pregnant cows were excluded from the analysis. For the present investigation, the blood samples were collected from individual animal (n = 12) on different weeks of pregnancy (0, 4, 8, 12 and 16 weeks). Day 0 represents the control (collection of blood before artificial insemination: AI). Following AI, blood was collected from the cows till the 16 weeks of pregnancy. Briefly, about 10 mL whole blood was collected in EDTA tubes, and then the samples were incubated at room temperature for 1 h. The collected blood sample was centrifuged at 3,000 rpm for 15 min at 4℃ to obtain plasma. After this step, the circulating cell-free nucleic acid was in the supernatant (plasma) and then the obtained plasma was transferred into a fresh 2.0 mL tube and the plasma samples were stored at -80℃ until further processing.

Confirmation of pregnancy

Pregnancy was diagnosed by palpation per rectum of the uterine contents between days 50 and 60 after AI or ultrasonic examination to determine pregnancy status. Ultrasonography was carried out using a B-Mode ultrasound scanner (MyLabTMOneVET, esaote) equipped with a 5.0-MHz linear array probe. Pregnancy diagnosis was confirmed by observation of embryocoele and allantoic fluid (Abdullah et al., 2014). The ovaries were also scanned for the presence of corpus luteum.

Total RNA isolation

Before RNA isolation, the exosomes in plasma were firstly isolated by using Total Exosomes Isolation kit (Invitrogen, Carlsbad, CA). Exosomal total RNA, including mRNA and miRNA, was isolated by using miRNeasy Mini Kit (Qiagen) following manufacturer’s protocos. The concentration of RNA was measured by using the Qubit microRNA assay kit (Invitrogen, Carlsbad, CA). RNA integrity of all RNA eluates was assessed. And high quality (RNA integrity number ≥ 7) samples from isolated total RNA were selected. The total RNA with lowest quality was not used for further study. The RNA samples were stored at -80℃ until further processing.

Illumina sequencing and data analysis

Total RNA (5 mL) from each sample was used to construct miRNA library by using the NEXTflex Small RNA Sequencing Kit (Illumina, San Diego, CA) according to the manufacturer’s instruction. Small RNA libraries were then pooled together in equal volumes for gel purification. The pooled library was sequenced by using the HiSeq 2500 system (Illumina) as 50 bp single reads. Read quality (adaptor removal, and size selection) was assessed using FastQC v0.11.5 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and cutadapt (Martin, 2011). The sequences with read length larger than 18 nucleotides (nt) were aligned against bovine miRNA database (miR-Base, release version 21) with the default parameters to identify known miRNAs using Bowtie2 (Langmead and Salzberg, 2012). Each library was processed separately. The expression level of miRNAs in each library was estimated by sRNAbench, which normalized reads count number of each miRNA reads per million (RPM) by the following foumula: RPM = (miRNA reads number/total mapped reads per library) × 1,000,000. The differentially expressed (DE) miRNAs were investigated by using bioinformatics tool edgeR v3.10.2 (Robinson et al., 2010). The DE miRNAs were determined by Log2 fold change (FC) > 1 OR < -1 and false discovery rate (FDR) < 0.05 based on counting reads by using HTSeq (Anders et al., 2015).

Identification of novel miRNA prediction

Prediction of novel miRNAs was performed by using the miRDeep2 software. Briefly, quality-trimmed reads from all samples were combined into a single reads file followed by the preprocessing, mapping, and novel miRNA prediction steps through mapper.pl and miRDeep2.pl scripts. Next, the FASTA files of predicted novel miRNA and quantifier.pl script were used to determine the read-counts/expression values for each novel miRNA from each sample. Combined count matrix for novel miRNAs was generated by using the custom scripts. Differential expression between control and pregnant groups was calculated by using the DESeq2 package (version 1.12.4).

RESULTS

We sequenced a total of 60 blood samples from non-pregnancy and 16 weeks of pregnancy. On average, the high throughput Illumina sequencing resulted in 22.4 million raw reads per sample from the exosomes of all stages (Table 1). 71.5% reads were uniquely mapped to annotate miRNAs in bovine genome.

Table 1. Sequencing and miRNA profiling statistics of normal and days of pregnancy samples.

SampleTotal readsMapped reads (%)Precursor miRNA readsMature miRNA readsKnown precursor with ≥ 5× coverageNo. known miRNANo. novel miRNA
Normal24773796.0 ± 3962727.173.2 ± 5.6305494.7 ± 81383.07713350.2 ± 2613944.7361.7 ± 45.0334.8 ± 27.4 491.8 ± 138.4
4 weeks19421596.7 ± 3587596.674.3 ± 4.7179172.5 ± 146647.28038306.5 ± 3180088.2385.5 ± 57.1307.3 ± 37.2 367.3 ± 178.1
8 weeks24122975.9 ± 4669481.770.7 ± 12.5239792.4 ± 154469.7 6806040.9 ± 3069368.0383.9 ± 53.6314.4 ± 43.0410.0 ± 179.6
12 weeks22139499.4 ± 3132885.268.8 ± 5.8155846.3 ± 56288.97785174.4 ± 1930464.7374.7 ± 28.2306.1 ± 19.7320.7 ± 72.9
16 weeks21845616.1 ± 2814855.670.5 ± 6.8140514.6 ± 54922.57386644.1 ± 1905019.6343.1 ± 39.2307.0 ± 35.0316.7 ± 83.6

The average data of all five analyzed samples for each animal is displayed..



Venn diagrams were used to demonstrate the overlap between pregnant groups (Fig. 1). Pregnant 8, 12 and 16 weeks groups had 2 common miRNAs (bta-miR-221 and bta-miR-320a).

Figure 1.Venn diagrma showing the overlap of the number and percentage of miRNAs detected in plasma samples.

To determine the miRNA expression patterns in blood samples, miRNA microarray analysis was conducted. By using small RNA sequencing we identified a total of 115 miRNAs that were differentially expressed on pregnancy compared to non-pregnancy. A total of 115 miRNAs were identified to be significantly differentially expressed between the groups; 91 miRNAs were upregulated and 26 miRNAs were downregulated (Table 2). And 91 upregulated and 26 downregulated miRNAs are listed (Table 3).

Table 2. Differential miRNA profile expression between normal and weeks of prengnancy groups (p-value < 0.05).

Differentially expressed miRNAsUpDown
4 weeks98
8 weeks168
12 weeks32
16 weeks638


Table 3. List of significantly differentially expressed plasma circulatory miRNAs in pregnant cows.

WeekGene_ida.valuep.valueq.value
Up-regulation
4 weeksbta-miR-455-5p1.071864930.042596140.98472459
bta-miR-193b9.600837490.003096880.50066183
bta-miR-133a9.909826350.033997510.98472459
bta-miR-296-5p11.1354140.019740890.98472459
bta-miR-130711.62372960.028104070.98472459
bta-miR-34215.44006310.037377140.98472459
bta-miR-15016.07780230.000424260.20576638
bta-miR-339a16.22707170.005684940.6892985
bta-miR-339b16.51137710.009924020.80219133
8 weeksbta-miR-23495.529787130.036430070.80182568
bta-miR-2299-3p10.98424920.037826670.80182568
bta-miR-87711.58085170.026690410.80182568
bta-miR-428612.16092160.04915370.80182568
bta-miR-37812.39583760.017199060.78481392
bta-miR-14313.09279180.02015740.78481392
bta-miR-2284z13.621520.044366740.80182568
bta-miR-2284aa14.00333620.039166450.80182568
bta-miR-45114.5886540.040876860.80182568
bta-miR-32814.5996980.022078440.78481392
bta-miR-37515.14852130.006976310.6188333
bta-miR-339a16.28407690.002897510.57394257
bta-miR-15016.34534270.012003760.78481392
bta-miR-15016.52516870.001687360.57394257
bta-miR-22117.07219930.007671490.6188333
bta-miR-320a18.47417940.00355750.57394257
12 weeksbta-miR-22116.79798490.004103781
bta-miR-26a14.91687730.030690571
bta-miR-320a18.29246350.035970421
16 weeksbta-miR-24811.149638510.030411010.28213644
bta-miR-133b2.868699020.00302510.06646495
bta-miR-23465.762419160.04236370.32562789
bta-miR-1275.978362780.043107560.32562789
bta-miR-1584-3p7.202873770.048276210.34076361
bta-miR-6119-5p7.206863330.041941460.32562789
bta-miR-146a7.342240670.020605630.24081834
bta-miR-23b-5p7.504147780.0106680.16368713
bta-miR-200b7.550218040.009224510.15405228
bta-miR-12968.481942520.021294130.24081834
bta-miR-133a8.682072220.001086190.04102443
bta-miR-2118.938802250.049275390.34076361
bta-miR-2284w9.147773050.020517130.24081834
bta-miR-7449.223867860.006698010.12180462
bta-miR-7699.790080830.006271570.12144622
bta-miR-193b9.79922750.009412560.15405228
bta-miR-2284ab10.70004890.035869820.29850986
bta-miR-3210.72063890.031603880.28213644
bta-miR-2299-3p10.78751790.002376510.0648259
bta-miR-296-5p10.82195270.000126210.00834593
bta-miR-29b11.1148110.001848550.06050908
16 weeksbta-miR-57411.13832290.031484690.28213644
bta-miR-87711.22420150.002297090.0648259
bta-miR-130711.30366640.000152980.00834593
bta-miR-345-3p11.39750950.039645580.3191144
bta-miR-2285f11.48133840.003107420.06646495
bta-miR-9811.77132340.034858270.29850986
bta-miR-428611.78126850.000840860.03440499
bta-miR-16a12.03244170.000285750.01403053
bta-miR-126-3p12.0347860.007397630.12972271
bta-miR-425-3p12.15198120.017001180.22677729
bta-miR-88512.19306320.026277890.27452004
bta-miR-32612.33060690.04880330.34076361
bta-miR-18512.34410550.037924510.31034894
bta-miR-37812.42273550.043017510.32562789
bta-miR-2285k12.77707550.031264960.28213644
bta-miR-16b13.03785580.001461220.05124697
bta-miR-65213.15756260.029673020.28213644
bta-miR-26b13.20769220.013286240.18851546
bta-miR-2284y13.36548160.020494320.24081834
bta-miR-14313.39761770.001163750.00399116
bta-miR-2284z13.42318160.018640530.24081834
bta-miR-2284aa13.84863830.028800730.28213644
bta-miR-87413.94592770.001976430.00399116
bta-miR-27a-3p13.98671050.003889760.07957799
bta-miR-10b14.26900920.009776440.15484621
bta-miR-21514.35116910.021580460.24081834
bta-miR-32814.40052580.013437970.18851546
bta-miR-19714.46554930.024839390.27102538
bta-miR-130614.53820780.021373290.24081834
bta-miR-29a14.96442050.003113430.06646495
bta-miR-37515.03060740.00270770.06646495
bta-miR-26a15.12684210.002023950.06210982
bta-miR-45115.19977360.000379210.01692671
bta-miR-142-5p15.35040920.000152290.00834593
bta-let-7g15.65078680.013422060.18851546
bta-miR-339a15.93907830.000905170.00142078
bta-miR-30e-5p15.95344420.03425030.29850986
bta-miR-15016.19510350.002545830.06578964
bta-let-7b16.22475720.046347030.33964761
bta-miR-339b16.2308310.001972380.00399116
bta-miR-22116.74515050.001362490.00142078
bta-miR-320a18.18786670.001350290.00399116
Down-regulation
4 weeksbta-miR-2454-5p-4.289396940.001502320.36431335
bta-miR-2415-5p-4.289396940.00771440.74829656
bta-miR-7861-4.289396940.024194680.98472459
bta-miR-196a-4.289396940.025150210.98472459
bta-miR-4449-4.289396940.034338010.98472459
bta-miR-338-4.289396940.036129270.98472459
bta-miR-1277-4.289396940.036275680.98472459
bta-miR-17-3p-4.289396940.047100530.98472459
8 weeksbta-miR-2313-5p-4.484120730.006789680.6188333
bta-miR-4449-4.484120730.014302480.78481392
bta-miR-2284h-3p-4.484120730.017396990.78481392
bta-miR-2378-4.484120730.018016760.78481392
bta-miR-154b-4.484120730.022701230.78481392
bta-miR-381-4.484120730.030923790.80182568
bta-miR-187-4.484120730.032581870.80182568
bta-miR-99a-3p-4.484120730.046756560.80182568
12 weeksbta-miR-346-4.173037050.038265481
bta-miR-187-4.173037050.04686531
16 weeksbta-miR-196a-4.244906610.006430960.12144622
bta-miR-2377-4.244906610.017089120.22677729
bta-miR-2378-4.244906610.026052440.27452004
bta-miR-2446-4.244906610.027462470.2809182
bta-miR-346-4.244906610.03044510.28213644
bta-miR-4449-4.244906610.035668520.29850986
bta-miR-188-4.244906610.044805450.33332536


Gene ontology (GO) and pathway enrichment analysis were used to explore the functions of differentially expressed genes in bta-miR-221 (Fig. 2A). The target genes were enriched in a total of 167 GO terms, which included 12 molecular function (GO:MF), 132 biological process (GO:BP), and 23 cellular component (GO:CC) terms, in addition to reactomes (REAC), and WiKiPathways (WP). The target genes of differentially expressed bta-miR-320a were significantly enriched in a total of 144 GO terms, which included 23 molecular function (GO:MF), 98 biological process (GO:BP), and 23 cellular component (GO:CC) terms, in addition to reactomes (REAC), and WiKiPathways (WP).

Figure 2.Manhattan plot illustrating the differentially expressed gene-enriched GO terms (MF, molecular function; BP, biological process; and CC, cellular component) and KEGG pathways across reactome pathways (REAC), WiKi-Pathways (WP), transcription factor (TF), microRNA target base (MIRNA), and human phenotype ontology (HP) term categories. (A) bta-miR-221 enriched in GO terms and pathways. (B) bta-miR-320a enriched in GO terms and pathways.

DISCUSSION

This study aimed to characterize the earliest changes in miRNA expression for the purpose of define a marker for early pregnancy detection. We determined the expression pattern of circulatory miRNAs in plasma of pregnant and non-pregnant dairy cattle. Varing expression patterns of circulating miRNAs in the regulation of pregnancy has been determined in bovines (Cai et al., 2017). Many researchers are now investigating miRNAs as biomarkers for pregnancy diagnosis in the cow. There is increasing evidence that pregnancy specific miRNAs exist and may be feasible markers for pregnancy diagnosis. In 2015, exosomal miRNAs were reported to be differentially expressed in pregnant versus non-pregnant dairy cattle and dairy cattle undergoing early embryonic mortality (Pohler et al., 2015). A recent study by Fiandanese et al. (2016) identified a feasible miRNA, bta-miR 140, as an early biomarker for pregnancy diagnosis in high producing dairy cows. At day 19, bta-miR 140 was up regulated in all pregnant dairy cattle, and at day 13 onwards, it was upregulated in pregnant, non-lactating dairy cattle (Fiandanese et al., 2016). Similarly, Ioannidis and Donadeu (2016) proved different stages of the estrous cycle (day 16: bta-miR-26a, bta-miR-29c, bta-miR-138, bta-miR-204. Day 24: bta-miR-1249, day 16 & 24: hsa-miR-4532) that were differentially expressed in pregnant heifers and miR-26a was differentially upregulated on Day 16 pregnant relative to non-pregnant heifers. The expression pattern of miR-496 and miR-125a has significantly varied during formation of bovine conceptus. This clearly suggests the role of these miRNAs in maternal-to-zygotic transcription translation (Tesfaye et al., 2009). Likewise, various miRNAs including miR-27a and miR-92b are differentially expressed during the formation of the placenta (Su et al., 2010). In the present study, we report the results of circulating bta-miR-221 and bta-miR-320a were notably expressed at over 8 weeks of pregnancy. The expression of miR-221 during pregnancy indicates the interface between maternal and fetal. Also miR-320 may promote uterine migration of endometrial stromal cells during gestation (Bidarimath et al., 2014).

Increading proofes indicated the presence of human placenta-specific miRNAs in maternal circulation. The expression of placenta-specific human chromosome 19 miRNA cluster (C19MC); hsa-miR-515-3p, hsa-miR-517a, hsa-miR-517c, hsa-miR-518b, and hsa-miR-526b increased in maternal circulation during the third trimester of pregnancy and decreased after parturition (Kotlabova et al., 2011). The villous of trophoblast cells shed the C19MC miRNA cluster encapsulated in exosomes and could be the main source of placenta-specific miRNAs in maternal circulation (Luo et al., 2009; Donker et al., 2012). Furthermore, according to Morales-Prieto et al. (2013) the human chromosome 14 miRNA cluster (C14MC) is also announced to be related to pregnancy. Other miRNAs involving miR-141, miR-149, miR-299-5p, and miR-135, which are offered to be aplenty expressed in placenta were also augmented in plasma of pregnant women and their concentration declines after parturition (Chim et al., 2008). Eariler study expressed that 25 miRNAs were differentially expressed between exosomes of maternal serum derived from non-pregnant and day 30 and 90 pregnant ewes (Cleys et al., 2014).

Even though purification is essential to accuarate optimal miRNA for pregnancy detection, results mean that miRNAs have feasible as an early pregnancy diagnosis tool. In addition, miRNA may offer information to represent embryonic viability. A study indicate dairy cattle that go through embryo mortality compared to dairy cattle that have a successful pregnancy have a significantly rose abundance of unique miRNAs at days 17 and 24 of conception (Reese et al., 2016). Future studies are needed to evaluate the repeatability of these result and to decide unique miRNA most appropriate for embryo viability survey.

Two new and generally available technologies for reproductive management include hormonal protocols such as Ovsynch (Pursley et al., 1995, 1997) and Presynch/Ovsynch (Moreira et al., 2001; Navanukraw et al., 2004) that synchronize ovulation and allow for TAI, and use of transrectal ultrasonography for early detection of non-pregnant cows. Dairy farms must schedule and administer artificial inseminations, hormone injections, and pregnancy tests for a multitude of animals on a daily or weekly basis. Detection of non-pregnant dariy cattle early after breeding can only improve reproductive performance when together with a operating schedule to quickly present non-pregnant dairy cattle for a subsequent AI service. Accurate detection of non-pregnancy is administered to synchronize estrus or ovulation to reduce the interval to the subsequent AI service.

CONCLUSION

In conclusion, comprehensive profiling of miRNAs in plasma of pregnant and non-pregnant dairy cattle found specific miRNA expression pattern. Much studies and development efforts are being made toward advancement of a pregnancy diagnosis for dairy cattle. Our study provides an experimental basis to reveal the feasible role of miRNAs as biomarkers in pregnancy diagnosis. This specific pregnancy differentially expressed miRNAs marker can be used as the retrospective detection of early pregnancy biomarkers. Pregnancy-associated microRNA profiling at 8 weeks in bovine was described for the first time and can be used for comparative studies. These miRNAs may have similar function in mammalian species and can be feasible molecular markers for evolution. Coupling a non-pregnancy diagnosis with a management strategies to quickly reinitiate. AI service may improve reproductive performance by decreasing the interval between AI services and the effectiveness of hormonal ovulation and estrus control protocols initiated at certain physiologic stages post AI breeding. Future experiments are needed in this area to truly understand early identification of pregnancy diagnosis through miRNA biomarkers.

ACKNOWLEDGEMENTS

This work was carried out with the support of the “Cooperative Research Program for Agriculture Science & Technology Development (Project title: Development of early pregnancy diagnostic technology using fetal DNA isolated from maternal plasma, Project No. PJ01199401)” Rural Development Administration, Republic of Korea.

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

Fig 1.

Figure 1.Venn diagrma showing the overlap of the number and percentage of miRNAs detected in plasma samples.
Journal of Animal Reproduction and Biotechnology 2021; 36: 35-44https://doi.org/10.12750/JARB.36.1.35

Fig 2.

Figure 2.Manhattan plot illustrating the differentially expressed gene-enriched GO terms (MF, molecular function; BP, biological process; and CC, cellular component) and KEGG pathways across reactome pathways (REAC), WiKi-Pathways (WP), transcription factor (TF), microRNA target base (MIRNA), and human phenotype ontology (HP) term categories. (A) bta-miR-221 enriched in GO terms and pathways. (B) bta-miR-320a enriched in GO terms and pathways.
Journal of Animal Reproduction and Biotechnology 2021; 36: 35-44https://doi.org/10.12750/JARB.36.1.35

Table 1 . Sequencing and miRNA profiling statistics of normal and days of pregnancy samples.

SampleTotal readsMapped reads (%)Precursor miRNA readsMature miRNA readsKnown precursor with ≥ 5× coverageNo. known miRNANo. novel miRNA
Normal24773796.0 ± 3962727.173.2 ± 5.6305494.7 ± 81383.07713350.2 ± 2613944.7361.7 ± 45.0334.8 ± 27.4 491.8 ± 138.4
4 weeks19421596.7 ± 3587596.674.3 ± 4.7179172.5 ± 146647.28038306.5 ± 3180088.2385.5 ± 57.1307.3 ± 37.2 367.3 ± 178.1
8 weeks24122975.9 ± 4669481.770.7 ± 12.5239792.4 ± 154469.7 6806040.9 ± 3069368.0383.9 ± 53.6314.4 ± 43.0410.0 ± 179.6
12 weeks22139499.4 ± 3132885.268.8 ± 5.8155846.3 ± 56288.97785174.4 ± 1930464.7374.7 ± 28.2306.1 ± 19.7320.7 ± 72.9
16 weeks21845616.1 ± 2814855.670.5 ± 6.8140514.6 ± 54922.57386644.1 ± 1905019.6343.1 ± 39.2307.0 ± 35.0316.7 ± 83.6

The average data of all five analyzed samples for each animal is displayed..


Table 2 . Differential miRNA profile expression between normal and weeks of prengnancy groups (p-value < 0.05).

Differentially expressed miRNAsUpDown
4 weeks98
8 weeks168
12 weeks32
16 weeks638

Table 3 . List of significantly differentially expressed plasma circulatory miRNAs in pregnant cows.

WeekGene_ida.valuep.valueq.value
Up-regulation
4 weeksbta-miR-455-5p1.071864930.042596140.98472459
bta-miR-193b9.600837490.003096880.50066183
bta-miR-133a9.909826350.033997510.98472459
bta-miR-296-5p11.1354140.019740890.98472459
bta-miR-130711.62372960.028104070.98472459
bta-miR-34215.44006310.037377140.98472459
bta-miR-15016.07780230.000424260.20576638
bta-miR-339a16.22707170.005684940.6892985
bta-miR-339b16.51137710.009924020.80219133
8 weeksbta-miR-23495.529787130.036430070.80182568
bta-miR-2299-3p10.98424920.037826670.80182568
bta-miR-87711.58085170.026690410.80182568
bta-miR-428612.16092160.04915370.80182568
bta-miR-37812.39583760.017199060.78481392
bta-miR-14313.09279180.02015740.78481392
bta-miR-2284z13.621520.044366740.80182568
bta-miR-2284aa14.00333620.039166450.80182568
bta-miR-45114.5886540.040876860.80182568
bta-miR-32814.5996980.022078440.78481392
bta-miR-37515.14852130.006976310.6188333
bta-miR-339a16.28407690.002897510.57394257
bta-miR-15016.34534270.012003760.78481392
bta-miR-15016.52516870.001687360.57394257
bta-miR-22117.07219930.007671490.6188333
bta-miR-320a18.47417940.00355750.57394257
12 weeksbta-miR-22116.79798490.004103781
bta-miR-26a14.91687730.030690571
bta-miR-320a18.29246350.035970421
16 weeksbta-miR-24811.149638510.030411010.28213644
bta-miR-133b2.868699020.00302510.06646495
bta-miR-23465.762419160.04236370.32562789
bta-miR-1275.978362780.043107560.32562789
bta-miR-1584-3p7.202873770.048276210.34076361
bta-miR-6119-5p7.206863330.041941460.32562789
bta-miR-146a7.342240670.020605630.24081834
bta-miR-23b-5p7.504147780.0106680.16368713
bta-miR-200b7.550218040.009224510.15405228
bta-miR-12968.481942520.021294130.24081834
bta-miR-133a8.682072220.001086190.04102443
bta-miR-2118.938802250.049275390.34076361
bta-miR-2284w9.147773050.020517130.24081834
bta-miR-7449.223867860.006698010.12180462
bta-miR-7699.790080830.006271570.12144622
bta-miR-193b9.79922750.009412560.15405228
bta-miR-2284ab10.70004890.035869820.29850986
bta-miR-3210.72063890.031603880.28213644
bta-miR-2299-3p10.78751790.002376510.0648259
bta-miR-296-5p10.82195270.000126210.00834593
bta-miR-29b11.1148110.001848550.06050908
16 weeksbta-miR-57411.13832290.031484690.28213644
bta-miR-87711.22420150.002297090.0648259
bta-miR-130711.30366640.000152980.00834593
bta-miR-345-3p11.39750950.039645580.3191144
bta-miR-2285f11.48133840.003107420.06646495
bta-miR-9811.77132340.034858270.29850986
bta-miR-428611.78126850.000840860.03440499
bta-miR-16a12.03244170.000285750.01403053
bta-miR-126-3p12.0347860.007397630.12972271
bta-miR-425-3p12.15198120.017001180.22677729
bta-miR-88512.19306320.026277890.27452004
bta-miR-32612.33060690.04880330.34076361
bta-miR-18512.34410550.037924510.31034894
bta-miR-37812.42273550.043017510.32562789
bta-miR-2285k12.77707550.031264960.28213644
bta-miR-16b13.03785580.001461220.05124697
bta-miR-65213.15756260.029673020.28213644
bta-miR-26b13.20769220.013286240.18851546
bta-miR-2284y13.36548160.020494320.24081834
bta-miR-14313.39761770.001163750.00399116
bta-miR-2284z13.42318160.018640530.24081834
bta-miR-2284aa13.84863830.028800730.28213644
bta-miR-87413.94592770.001976430.00399116
bta-miR-27a-3p13.98671050.003889760.07957799
bta-miR-10b14.26900920.009776440.15484621
bta-miR-21514.35116910.021580460.24081834
bta-miR-32814.40052580.013437970.18851546
bta-miR-19714.46554930.024839390.27102538
bta-miR-130614.53820780.021373290.24081834
bta-miR-29a14.96442050.003113430.06646495
bta-miR-37515.03060740.00270770.06646495
bta-miR-26a15.12684210.002023950.06210982
bta-miR-45115.19977360.000379210.01692671
bta-miR-142-5p15.35040920.000152290.00834593
bta-let-7g15.65078680.013422060.18851546
bta-miR-339a15.93907830.000905170.00142078
bta-miR-30e-5p15.95344420.03425030.29850986
bta-miR-15016.19510350.002545830.06578964
bta-let-7b16.22475720.046347030.33964761
bta-miR-339b16.2308310.001972380.00399116
bta-miR-22116.74515050.001362490.00142078
bta-miR-320a18.18786670.001350290.00399116
Down-regulation
4 weeksbta-miR-2454-5p-4.289396940.001502320.36431335
bta-miR-2415-5p-4.289396940.00771440.74829656
bta-miR-7861-4.289396940.024194680.98472459
bta-miR-196a-4.289396940.025150210.98472459
bta-miR-4449-4.289396940.034338010.98472459
bta-miR-338-4.289396940.036129270.98472459
bta-miR-1277-4.289396940.036275680.98472459
bta-miR-17-3p-4.289396940.047100530.98472459
8 weeksbta-miR-2313-5p-4.484120730.006789680.6188333
bta-miR-4449-4.484120730.014302480.78481392
bta-miR-2284h-3p-4.484120730.017396990.78481392
bta-miR-2378-4.484120730.018016760.78481392
bta-miR-154b-4.484120730.022701230.78481392
bta-miR-381-4.484120730.030923790.80182568
bta-miR-187-4.484120730.032581870.80182568
bta-miR-99a-3p-4.484120730.046756560.80182568
12 weeksbta-miR-346-4.173037050.038265481
bta-miR-187-4.173037050.04686531
16 weeksbta-miR-196a-4.244906610.006430960.12144622
bta-miR-2377-4.244906610.017089120.22677729
bta-miR-2378-4.244906610.026052440.27452004
bta-miR-2446-4.244906610.027462470.2809182
bta-miR-346-4.244906610.03044510.28213644
bta-miR-4449-4.244906610.035668520.29850986
bta-miR-188-4.244906610.044805450.33332536

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