NANOS2 gene in pig embryos to generate offspring with mono-allelic and bi-allelic mutations. We found that NANOS2 knockout pigs phenocopy knockout mice with male specific germline ablation but other aspects of testicular development are normal. Moreover, male pigs with one intact NANOS2 allele and female knockout pigs are fertile. From an agriculture perspective, NANOS2 knockout male pigs are expected to serve as an ideal surrogate for transplantation of donor spermatogonial stem cells to expand the availability of gametes from genetically desirable sires.Genome editing tools have revolutionized the generation of genetically modified animals including livestock. In particular, the domestic pig is a proven model of human physiology and an agriculturally important species. In this study, we utilized the CRISPR/Cas9 system to edit the  Spermatogenesis is a robust and dynamic developmental process that occurs in seminiferous tubules of testes and generates millions of sperm each day in males from puberty through advanced age. The undifferentiated spermatogonia provide the foundation for spermatogenesis1Aside from a role in sustaining steady-state spermatogenesis, SSCs are also capable of regenerating the spermatogenic lineage following cytotoxic damage that eliminates the progenitor population, or following transplantation into the seminiferous tubules of a germ cell ablated recipient male354The precursors of SSCs are prospermatogonia that are derived from primordial germ cells (PGCs) during fetal development10Beyond the generation of recipient models for SSC transplantation, understanding the mechanisms influencing prospermatogonial formation and survival, as well as SSC formation, could help inform cases of infertility in men. Non obstructive azoospermia (NOA) is a condition that describes the complete lack of sperm in the ejaculate. In many NOA cases, the cause is lack of germline, a condition referred to as “Sertoli-cell-only” syndromenanos (nos) gene encodes for a protein that is required for development of both male and female germlineNanos paralogs, each with a different role in germline development. Deficiency of Nanos1 has no known effect on growth and development of any systems including the germlineNanos3 deficiency leads to male and female sterility due to impaired survival of PGCs prior to sex determinationNanos2 knockout male mice are sterile due to apoptosis of prospermatogonia shortly after birth, however, homozygous knockout females, as well as heterozygous knockout males and females possess normal germline and are fertile10NANOS2 for targeting in livestock has two advantages: (1) homozygous NANOS2 knockout males will be deficient in SSCs and will serve as ideal recipients for transplantation; and (2) heterozygous knockout males when bred to homozygous knockout females (both fertile) will efficiently propagate the line and generate NANOS2 null animals at high frequency.The NANOS family of RNA binding proteins are known to play an essential role in the development of germline for all organisms studied to date. In Drosophila, the single NANOS2 gene of domestic pigs. Outcomes revealed that male pigs with bi-allelic frameshift mutations (i.e. knockouts) resulted in ablation of germline but with morphologically intact seminiferous tubules. Also, males with heterozygous frameshift mutations and females with homozygous and heterozygous frameshift mutations are fertile. These observations confirm that genetic modification of NANOS2 in pigs phenocopy mutations in mice.In this study, CRISPR/Cas9 technology was utilized to produce inactivating mutations in the NANOS2 is a single exonic gene with an open reading frame (ORF) of 417 bp. A candidate CRISPR/Cas9 single guide RNA (sgRNA) was designed to target 48 to 70 bp proximal to the translational start site (AUG)  . To prodonstruct , and 30  piglets . Genotyp piglets . Among tNANOS2 plays a role in the development and function of cell lineages other than the male germline in pigs, overall growth and development would be affected. To assess this, we measured the weight of male animals at periodic intervals from birth through adulthood  which was not different (P = 0.19) compared to the average weight of heterozygous knockout males, 1.9 ± 0.3 kg (n = 4). Likewise, there was no difference (P = 0.42) in body weight between the homozygous and heterozygous groups at weaning , or at 3, 6, 9, or 12 months of age , which is conserved from mouse to pig.To assess the testis phenotype of ll males , as wellll males . Howeverll males  and 146 ll males . In adulll males . Similarll males . In contll males . Note th2 allele . Thus, bNANOS2 locus. One of the clonal lines that was bi-allelic knockout for NANOS2 was used as a donor for somatic cell nuclear transfer (SCNT), which yielded true knockout female piglets  and evaluation of cross-sections from the ovaries of one piglet  revealed intact follicles and normal folliculogenesis (NANOS2 knockout littermate resulted in a successful pregnancy (confirmed by ultrasound at 4 weeks). Lastly, we utilized sperm from the mosaic heterozygous knockout boar #142 to breed NANOS2 mutant sows #145 and #149 (heterozygous knockouts), and boar #143 was bred to sow #140 (heterozygous knockout); all of which resulted in pregnancies and produced litters  or both alleles (17 piglets). The identification of edits in a mono- or bi-allelic fashion in all piglets (and no wildtype offspring) points to the high efficiency of the CRISPR/Cas9 editing approach. That said, one third of the bi-allelically edited piglets (6 piglets) were found to be mosaic with 3 different alleles in the animals. Notably, 4/5 mosaic males  were from injection of in vivo fertilized zygotes, compared to only one mosaic animal from injection of in vitro fertilized zygotes. The high incidence of mosaicism could be a result of injection into in vivo zygotes that are close to their first cell division resulting in independent editing events in two cells. In pigs, ovulations and consequently fertilization occurs over a broader window of time. This feature, coupled with harvest of embryos at different times could result in developmental asynchrony, with some embryos being more advanced than others in development. Conversely, harvest of oocytes that were in vitro fertilized are expected to be more synchronous. Another possibility is the persistence of CRISPR reagents and Cas9 protein past the first cell division, again resulting in differential modification and repair in the two cells. Relevant to this, the authors have noted that the use of in vivo matured oocytes that mount a better block to polyspermy, followed by in vitro fertilization, and injection of CRISPR ribonucleoproteins (instead of Cas9 mRNA) has no incidence of mosaicism in resulting offspring .In this study, we have shown that direct injection of CRISPR reagents into the cytoplasm of NANOS2 in the domestic pig phenocopies the mutations in the mouse. Prior to puberty, no difference in testis development, based on paired diameter measurements was observed between homozygous (#144 and #146) and heterozygous NANOS2 littermates. At puberty, the size of the testes had dramatically increased for pigs with NANOS2 sufficiency but limited growth occurred from the knockout male. Importantly, an abundance of sperm were visible in the ejaculates of pigs with functional NANOS2 alleles but not evident in the ejaculate of knockout pig #146 and evaluation of cross-sections of testicular tissue from knockout boars #144 and #146 confirmed germline ablation but intact seminiferous tubules. In addition, serum testosterone concentration was measured to be in the normal range for knockout pig #146 and the heterozygous edited and mosaic littermates, thus demonstrating functional testicular interstitial tissue and an intact HPG axis. Lastly, female NANOS2 knockout pigs are fertile and therefore possess an intact germline. Although comparison to wild-type littermates would have provided a more well-rounded perspective of the findings, the high efficiency of the CRISPR/Cas9 system to mutate at least one allele in each pig negated this possibility. Regardless, taken together, these findings demonstrate a male specific role for NANOS2 in germline maintenance.The role of NANOS proteins in germ cell development is well understood for model organism but undefined for higher order mammals. In the current study, we discovered that inactivation of NANOS2 in male germline maintenance for model organisms  is demonstrated, the mechanisms of its actions and mode of germ cell loss is still undefined. The NANOS2 knockout pig is expected to serve as a valuable bridge model for filling these gaps in knowledge. Polymorphisms in the NANOS genes are associated with NOA in men20NANOS2 could be the likely factor. Because germline and testis development in the pig is similar to humans, studying how germ cell loss occurs in NANOS2 knockout pigs may yield valuable information for devising therapeutic/diagnostic approaches to prevent loss in humans.Although the role of NANOS2 knockout male phenotype is that seminiferous tubules and testicular interstitial tissue function appear to be intact. Thus, these animals may serve as ideal recipients for transfer of male germline via SSC transplantation. When successful, donor-derived spermatogenesis would occur in the NANOS2 knockout recipient tubules without mixing the endogenous germ cells. Thus, 100% of offspring sired from breeding of the recipients via natural service or in vitro fertilization would possess the donor male’s haplotype. This paradigm would be extremely valuable for production animal agriculture as both a means to expand the availability of gametes and preserve the germline of genetically desirable sires. Importantly, the fact that male pigs with one inactive NANOS2 allele and female pigs with two inactive NANOS2 alleles are fertile allows for efficient expansion of the line and generation of sufficient knockout males for experimentation. As a necessary first step, we setup crosses of the heterozygous males and females and three litters have been generated  and Landrace (LR) breeds were crossbred to produce F1s that were utilized in this study.All animal procedures and experimentation were approved by the Institutional Animal Care and Use Committee (IACUC) of Washington State University and the USDA Animal Research Service (Beltsville) in accordance with the Guide for the Care and Use of Agricultural Animals in Research 3NANOS2 was designed based on the software developed by Dr. Feng Zhang at MIT (http://crispr.mit.edu/). The sequence of the Guide RNA used is: GATCAGTCCCAACACCACCTGG (20 nucleotide guide sequence and the PAM motif (underlined)). A second guide RNA: GAATCGTCGACAAGGGCCAGAGG, was used in the nuclear transfer experiment. The candidate CRISPR sgRNAs, in combination with Cas9:GFP mRNA, were in vitro transcribed using a T7 mMessage Machine kit (Ambion), cleaned with a Megaclear Kit (Ambion) and microinjected into the cytoplasm of in vivo or in vitro fertilized porcine one-cell embryos. To prepare embryo donors, nine pubertal gilts were subjected to estrus synchronization by treatment with the progesterone analog Regumate  for 14 days. Females in standing heat were then artificially inseminated (AI) with commercial boar semen provided by PIC. The in vivo derived embryos were recovered surgically 24 hours after AI by retrograde flushing with sterile PVA TL-Hepes medium from the oviduct. Fertilized embryos were then injected with Cas9:GFP mRNA and sgRNA targeting NANOS2, and cultured in PZM3 mediumin vitro. The oocytes were placed in 100 μl of a modified Tris-buffered medium (mTBM) and fertilized according to established protocol5 spermatozoa/ml, and co-incubated for 5 h at 38.5 °C and 5% CO2. Presumptive zygotes were microinjected five hours later and transferred to a surrogate female after 18 hours (n = 1 recipient receiving 54 embryos). Pregnancies were confirmed by lack of return to estrus (21 days) and ultrasound at 28 days post embryo transfer. For SCNT, the Cas9:GFP plasmid, in combination with a hU6 promoter driven sgRNA vector, were co-transfected into porcine somatic cells and sorted as single cells into a 96-well plate. Clonal lines were obtained by culture for two weeks, genotyped, and confirmed lines were used for cloning as a service by MOFA Global .A candidate chimeric sgRNA targeting Exon-1 of Ε. coli DH5-α maximum competent cells (Life Technologies). Five to ten colonies were picked, cultured, plasmid DNA extracted and sequenced (Macrogen). Sequences were aligned by Bio-Edit software for comparison with wild-type alleles. Primers for genotyping are provided in Tissue biopsies (ear notch) from fetuses and offspring were digested in a tissue lysis buffer  overnight at 65 °C. Next, genomic DNA was extracted using phenol-chloroform, and recovered by resuspension in 100 μl of 10 mM Tris- HCl, pH 7.4 buffer following ethanol precipitation. Purified genomic DNA was amplified using PCR, cloned into PCR2.1 vectors (Life Technologies) and transformed into Testes of boars at the immature and adult stages of development were imaged using a Sonoscape ultrasound machine and static images were captured to measure the diameter of testes.NANOS2 mutant male pigs, biopsies of parenchyma were collected for cross-sectioning. Briefly, boars were placed under general anesthesia, a small incision made in the scrotum and an 18 gauge biopsy punch was inserted into the testicular parenchyma and ~100 mg of tissue was removed. The tissue was then fixed 2–3 hours in Bouin’s solution followed by washing in 70% ethanol and processing for paraffin embedding. Cross-sections of 5 μm thickness were adhered to glass slides, deparrafanized, and then stained with hematoxylin and eosin.To assess whether seminiferous tubules were intact and the germline was present in NANOS2 mutant pigs, serum testosterone concentrations were measured using LC-MS. Briefly, blood samples were collected every 15 minutes for 1 hour because testosterone is secreted in a pulsatile manner. Samples were then centrifuged to separate serum and plasma and the serum stored at −20 °C before shipment to the Endocrine Technologies Support Core (ETSC) at the Oregon National Primate Research Center (ONPRC) for measurement of testosterone by LC-MS analysis  axis in NANOS2 mutant boars was conducted by collecting semen samples. Briefly, boars were trained at a young peri-pubertal age on a dummy apparatus (MOFA) for manual semen collection. Samples were diluted in commercial extender solution (MOFA) and analyzed by light microscopy.Assessment of sperm production by NANOS2 females were heat checked daily and estrus activity was first noted at five months of age with regular 21 day cycles. Estrus in the gilts was detected by noting visible signs of estrus behavior including increased physical activity, phonation, pointed ears, and lordosis  in the presence of teaser boar. The gilts were bred to heterozygous NANOS2 boars (10–16 months) or PIC semen at 10 months and confirmed pregnant by ultrasound 28 days later.The All quantitative data are presented as either the mean ± SEM or mean ± STDV for at least 3 different animals of each genotype or as values for each individual animal. Differences between means were examined statistically using a two-tailed t-test and a P-value of <0.05 was considered significant.How to cite this article: Park, K.-E. et al. Generation of germline ablated male pigs by CRISPR/Cas9 editing of the NANOS2 gene. Sci. Rep.7, 40176; doi: 10.1038/srep40176 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Additionally, RNase P copy number was measured and used to normalize nasal wash data. RSV gene copy numbers were found to significantly correlate with both cytokine/chemokine and biomarker levels; and RNase P-normalized viral gene copy numbers  were significantly higher in infants with less severe disease. Moreover, three of the normalized viral gene copy numbers  correlated significantly with arterial O2 saturation levels. The data support a model where a higher viral load early in infection can promote a robust innate immune response that protects against progression into hypoxic RSV-induced lower respiratory tract illness.Respiratory syncytial virus (RSV) causes significant infant morbidity and mortality. For decades severe RSV-induced disease was thought to result from an uncontrolled host response to viral replication, but recent work suggests that a strong innate immune response early in infection is protective. To shed light on host-virus interactions and the viral determinants of disease, copy numbers of five RSV genes  were measured by quantitative real-time polymerase chain reaction (qPCR) in nasal wash samples from children with RSV-associated bronchiolitis. Correlations were sought with host cytokines/chemokines and biomarkers. Associations with disposition from the emergency department  and pulse oximetry O RSV is the most common pathogen associated with lower respiratory tract disease worldwide –3. It cain utero and during infancy, and overcrowding—are well established for severe RSV illness. Less well established are the viral factors and their relationship to disease.For decades it was believed that an unrestrained and aberrant host innate immune response was the driver of RSV pathogenesis –12. HoweA number of groups, including our own, have investigated the role of viral load in disease with mixed results: some studies report a correlation between viral load and disease severity –23, whilin vitro (data not shown). The levels of other RSV proteins might depend less strictly on viral load, and could be of particular significance to determining disease severity. The nonstructural 1 and 2 (NS1 and NS2) proteins are not incorporated into virions and inhibit the innate immune response by suppressing induction of type I interferon (IFN) and IFN-inducible genes ; the independent variables included in the model were age (<6 & ≥6 months), DOI at enrollment (<3 days & ≥3 days), disposition , RSV subgroup (RSV/A & RSV/B) and normalized cytokines/biomarkers . IP-10 associated with RSV gene CN in 4 of the 5 models. Odds ratios (OR) for IP-10 were as follows: 1) NS1 model: OR = 1.27 ; 2) NS2 model: OR = 1.31 ; 3); N model: OR = 1.33 ; and 4) G model: OR = 1.11 . None of the independent variables used in the F model was found to be significant. Similar results were obtained when neither the RSV gene CNs nor the cytokines/biomarkers were normalized by RNase P, with IP-10 alone associating significantly with RSV gene CN in 4 of the 5 models.RSV gene CNs were analyzed for differences between infants who were hospitalized (ACU or PICU) and infants who were sent home after presenting in respiratory distress to the ED. Interestingly, NS1 CN  and all To better understand the determinants of disease severity in our patient cohort, multivariate logistic regression analyses were performed using disposition  as outcome. Five models were generated with backward elimination. Each model included a different normalized RSV gene CN , selected normalized cytokines and biomarkers , age (<6 & >6 months), DOI at enrollment (<3 days & ≥3 days), and RSV subgroup (RSV/A or RSV/B). In all 5 models IP-10 was identified as an independent factor influencing disposition, with higher levels predicting less severe disease  = 0.85 ). LDH was also significantly associated with disposition, with higher levels predicting more severe disease ). Similar results were obtained when neither the RSV gene CNs nor the cytokines/biomarkers were normalized by RNase P, with higher levels of IP-10 predicting less severe disease  and higher levels of LDH predicting more severe disease ) in all 5 models. Un-normalized IL-17 also associated with disposition in these analyses, with higher levels, like IP-10, predicting improved clinical outcome .2 saturation levels measured by pulse oximetry were used as an objective measure of airway injury and/or obstruction in children with bronchiolitis. Correlations were determined between O2 saturation levels and 1) RSV gene CNs, 2) cytokines/chemokines , and 3) biomarkers . Significant correlations were observed for normalized RSV gene CNs NS1, NS2 and N ; the cytokines IFN-gamma  and Il-15 ; and a significant inverse correlation was observed for LDH .Because disposition  is binary and potentially influenced by subjective criteria, OTo help unravel the contributions of viral cytopathic effect and host immune response to RSV pathogenesis, RSV gene copy numbers (CNs) were measured and analyzed for correlations with cytokine/chemokine levels, biomarker levels, and clinical outcome in samples collected from RSV-infected infants admitted to the ED.2 saturation levels. Although potentially counter-intuitive, we believe that we can rationalize the apparent disease-mitigating effect of higher viral loads observed in our study.RSV gene CNs correlated with a diversity of cytokines and all biomarkers measured. RSV gene CNs were higher in infants with less severe disease ; and significant correlations were found between normalized RSV gene CNs  and arterial OOur data come from samples collected shortly after patients were admitted to the ED and therefore represent earlier time-points with respect to the start of infection than data from most comparable studies –23; and et al. showed that defective viral genomes (DVGs) of RSV promote a strong innate antiviral response in mice and humans [Higher MOIs might also be directly protective. Sun d humans . DVGs ard humans . They ard humans . Higher d humans . Any DVGet al. performed a longitudinal study by infecting healthy adult volunteers with variable amounts of RSV and measuring their symptoms and viral load through time [Contrary to what we report here, a number of studies including our own have reported an association between higher viral load and greater disease severity –23. Receugh time . They cough time . What hoAll RSV gene CNs  correlated strongly and linearly with each other, and all were significantly different. CNs reflect the amount of 1) genomic and anti-genomic RNA , and2) mRNA present in our samples. The correlations and differences observed are perhaps not surprising as all RSV gene CNs will depend on viral load, leading to correlations; each RSV gene CN will also depend on a potentially different rate of transcription and transcript stability, leading to differences. Most correlations improved somewhat after correcting for sample quality by RNase P CN.RSV gene CNs correlated with levels of numerous cytokines from an array of functional groups and the activity levels of established bronchiolitis biomarkers (caspase and LDH). Although increases in both are an expected part of host resistance to viral replication, we did not expect to observe an apparent RSV gene CN-dependent response. Consistent with previous findings , these results suggest that the magnitude of the host response to infection with RSV depends on viral load.Both cytokine and biomarker levels were correlated with RSV gene CNs yet gave qualitatively different odds ratios in multivariate analyses with disposition as outcome . This is reasonable assuming increases in both are temporally distinct, as a simultaneous increase would suggest a contradictory host response. Additionally, it is misleading to call one protective and the other not, because both contribute to or reflect host resistance to viral replication—with the partial exception of LDH, whose levels reflect both apoptosis and/or necrosis of host tissue. Furthermore, we have reported associations in similar cohorts between bronchiolitis biomarker levels and both more and less severe disease , 42. SysThis study did not have an uninfected control group for measurements of and analyses including cytokine levels. Although the absence of an uninfected control group does not alter our RSV gene CN findings in relation to clinical outcomes. Samples were collected from infants early in the course of infection, but it would be ideal to have multi-time-point data spanning its full duration; dynamics measurements of 1) RSV gene CNs and 2) host cytokine/chemokine and biomarker levels coupled to a range of clinical outcomes might help reveal the determinants of severe disease. Additionally, no measurements were made to test for the presence of DVGs in our samples. Testing for DVGs is important for future studies; however, the major hypothesis to emerge from our data does not depend on their presence.Our results support the hypothesis that more virus early in illness can lead to less severe RSV-induced disease. This might result from higher viral loads—potentially through the increased generation of DVGs—inducing a swifter host immune response early in infection. We speculate that a delayed and/or weak host response early in infection is more likely to lead to prolonged viral replication with subsequent tissue injury reflecting clinically as severe disease.This was a cross-sectional, prospective, single-site study conducted at Texas Children’s Hospital from October 2010 through April 2011 during the bronchiolitis season in Houston, TX , 15. Finnd hypervariable region of the G gene.Viral RNA was extracted from NW samples as described  by usingSubgroup-specific primers and probes were generated for quantitative real-time polymerase chain reaction (qPCR) -based measurements of copy numbers of 5 different RSV genes: NS1, NS2, N, G, and F. Primers and probes were designed using sequences available from Genbank: U50362 (RSV A2) and NC_001781 (RSV B1). Reaction conditions were optimized to achieve amplification efficiencies greater than or equal to 90%.®, received lyophilized and resuspended in nuclease-free water. For each oligonucleotide standard a concentration was found at which the cycle threshold value (CT) measured by qPCR was at or close to 15 (around 1.0 pg/μl), with thresholding done according to the manufacturer’s instructions [CTs were then measured for: 1) each series of 10-fold standard dilutions; and 2) the appropriate cDNAs acquired from clinical samples. Samples were measured in duplicate, and copy numbers were determined by mapping unknown sample CTs to the linear relationship measured for standard CT vs. log10 of the standard concentration.To measure RSV gene copy numbers, the aforementioned sequences (U50362 and NC_001781) were used to generate subgroup-specific oligonucleotide standards. Standards were purchased from IDTructions . For eacRNase P primers and probes were acquired from the Centers for Disease Control and Prevention (CDC). RNase P was measured in a number of human cell lines . Briefly, HEp-2, A549, and Calu-3 cells were separately grown and harvested, counted with a hemocytometer, lysed by sonication and pelleted; RNAs in the supernatant were extracted and converted to cDNA. RNase P copy numbers were measured using standard dilutions of HEp-2 cells at known concentration. Thus, a sample’s RNase P copy number is equal to the number of HEp-2 cells needed to measure the same amount of RNase P. So long as the amplification efficiency remains constant, oligonucleotide standards or any other human cell line would suffice for generating RNase P copy numbers needed to adjust data for sample quality.et al. [Cytokine levels come from those reported in Nicholson et al.  and wereCaspase and LDH levels were measured as described  using thCopy numbers (CNs) measured by qPCR of 5 RSV genes  were either left alone (raw) or normalized by RNase P copy number for comparisons. To evaluate our data for relationships between RSV gene CNs and other molecular factors (cytokine/chemokine and biomarker levels) correlations were calculated using Spearman’s coefficient. For descriptive statistics, continuous variables were represented as mean and standard deviation (SD) or median (IQR (Q3-Q1)); categorical variables were represented as frequencies or corresponding percentages. Further analyses were conducted to test for association between RSV gene CNs and clinical outcome. Patients were separated into 2 groups for the primary outcome disposition: those who were hospitalized (children cared for in the acute care unit (ACU) or the pediatric intensive care unit (PICU)) and those who were not hospitalized (children discharged from the ED or observed for <24 hrs in the observation unit before being discharged home). Participants’ ages were divided into two groups: 0–5 months and ≥6 months. Duration of illness (DOI) at presentation was separated into three groups: 0–2 days, 3–5 days and >5 days or two groups: 0–2 and ≥3 days. Patients selected were exclusively infected with either RSV/A or /B. Wilcoxon-Mann-Whitney tests were used to test for differences of raw and normalized RSV gene CNs by disposition  and DOI (0–2 days and ≥3 days). For the identification of independent factors (including RSV gene CNs and cytokine levels) that may influence disposition , multivariable logistic regression analyses were performed to calculate odds ratios (OR) and corresponding 95% confidence intervals (95% CI). Final models were established based on multivariable logistic regression analyses with backward elimination. To determine the predictors that modified RSV gene CNs, using the categorized copy numbers (two groups: top quartile (Q4) vs. lower 3 quartiles combined ) as dependent variables, multivariate models were also developed while controlling for age, DOI, disposition of patients and virus infection type and cytokines. Similar multivariate analyses were performed using disposition  as dependent variable. All statistical analyses were performed using the SAS software package version 9.4 .S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.


Genome-wide association studies (GWAS) for type 2 diabetes (T2D) risk have identified a large number of genetic loci associated with disease susceptibility. However, progress moving from association signals through causal genes to functional understanding has so far been slow, hindering clinical translation. This review discusses the benefits and limitations of emerging, unbiased approaches for prioritising causal genes at T2D risk loci.Candidate causal genes can be identified by a number of different strategies that rely on genetic data, genomic annotations, and functional screening of selected genes. To overcome the limitations of each particular method, integration of multiple data sets is proving essential for establishing confidence in the prioritised genes. Previous studies have also highlighted the need to support these efforts through identification of causal variants and disease-relevant tissues.Prioritisation of causal genes at T2D risk loci by integrating complementary lines of evidence promises to accelerate our understanding of disease pathology and promote translation into new therapeutics. In the last decade, genome-wide association studies (GWAS) have evolved as a powerful tool for deciphering the genetic component of type 2 diabetes (T2D) risk. By associating regions of the genome with disease susceptibility, more than 100 loci influencing T2D risk have been identified so far , 7••. MoGWAS exploit the fact that single-nucleotide polymorphisms (SNP) tend to be located in linkage disequilibrium (LD) with other variants . By analThe challenge for functional follow-up studies in elucidating disease mechanisms lies therefore in finding both causal variants and the genes through which they impact on disease risk for the corresponding SNPs. Here, we first discuss the benefits of determining the causal variant(s) and affected tissue(s) as a prerequisite for identifying effector transcripts. We review several approaches for prioritising causal genes at T2D loci and provide recent and prominent examples of likely effector transcripts identified by these strategies. Finally, we highlight the importance of triangulating from multiple datasets and discuss the prospects for future integrative studies.Uncovering the underlying causal mechanisms of T2D risk loci is not exclusively a matter of finding causal genes, since these efforts are complicated by the need to identify both causal variant(s) and the affected tissue(s) in order to obtain a complete picture of disease pathology. Moreover, this additional information is often an inevitable requirement for performing functional follow-up studies in an appropriate model system.In GWAS, the variant most strongly associated with disease risk is reported for each locus, though such ‘lead SNPs’ may only serve as surrogate markers for other genetic perturbations that directly contribute to disease pathology. Identifying the true causal variants can provide a direct functional link between genotype and the observed disease phenotype, especially in cases where the variant is protein altering. To identify a causal variant, or a set of likely causal variants, several strategies have been developed, including fine-mapping of disease-associated regions, experimental prioritisation, and in silico prediction tools.Fine-mapping of a locus involves analysing SNPs in a defined region of the genome for disease association and is used to refine a GWAS association signal from the surrogate lead SNP to the actual causal variant(s). The SNPs are assayed by deep sequencing, or custom array-genotyping based on GWAS variants and imputation from extensive sequencing efforts such as the 1000 Genomes Project , 15. To MTNR1B) [MTNR1B locus has previously been implicated in T2D risk and the identification of the single causal variant revealed a likely, direct functional link to the causal gene [MTNR1B expression.Even so, most fine-mapping efforts uncover a large number of variants that, between them, are likely to be driving a particular association signal—a so-called credible set. In some exceptional cases, however, it is possible to narrow down the credible set to a single variant, as is the case for the melatonin receptor 1B gene (MTNR1B) •. The MTsal gene . The risJAZF1 and CDC123/CAMK1D loci [r2 > 0.8) with the lead GWAS SNP were selected for functional analysis based on maps of open chromatin. Effects on gene expression were tested in luciferase reporter assays, and DNA binding capability was analysed through electrophoretic mobility shift assays. The identified potential causal variants at the JAZF1 and CDC123/CAMK1D loci appear to act as part of cis-regulatory modules (CRMs). These specific regions harbour combinatorial transcription factor binding sites (TFBS), and the variants affect binding of PDX1 and FOXA1/FOXA2, respectively. However, due to practical limitations, this type of experimental studies mostly analyses a subset of regional variants, opening up the possibility of missing potential true causal variants. Further, the evidence generated is only circumstantial, since establishing functionality is necessary but not sufficient to prove causation. The emergence of new experimental lines of evidence may affect the prioritisation of the true causal variants and should ideally involve integration of different types of analyses  and developmental stage(s), which allow any functional follow-up studies to be performed in a disease-relevant model. As the majority of T2D association signals are located in non-coding regions and exert regulatory effects, their influence on gene expression may be subject to context-specific activity . Thus, sagenesis •. The idThe aim of translating genetic variants into molecular mechanisms will ultimately centre on the identification of causal genes. It is enhanced understanding at this level that holds the key to discovering novel treatments, prevention targets, and diagnostic markers. Several strategies to address this issue are being pursued, including the interrogation of coding variants, establishing variant-gene links for non-coding variants, and using high-throughput screens to prioritise candidate genes.Recent GWAS endeavours have shifted attention towards exome-arrays and exome-sequencing to enable identification of rare and low-frequency variants with potentially larger effect sizes—and a more direct biological interpretation—than common variants ••, 28–30SLC30A8, which encodes a zinc transporter (ZnT8) that is active in the secretory vesicles of beta cells. SLC30A8 was initially identified as a T2D susceptibility gene harbouring a common missense variant [SLC30A8 [SLC30A8 has been validated with high confidence as the causal gene. Furthermore, this study highlights the importance of discovering an extended allelic series to understand functional mechanisms. More broadly, it has established reduced activity of ZnT8 as a protective disease mechanism in T2D and a potential treatment strategy based on antagonism [The importance of coding variants for ascertaining causal mechanisms is illustrated by [SLC30A8 •. Strikitagonism .TBC1D4 was discovered in the Greenlandic population with the largest effect size for a common T2D risk allele (odds ratio = 10.3) [The power to detect causal genes through coding variants can be further harnessed by performing genetic association studies in isolated populations. These populations, founded by a bottleneck event, show a higher degree of LD, less genetic complexity, and higher allelic frequencies due to genetic drift, which leads to fixation or extinction of specific alleles over time . Further = 10.3) •. The vaAKT2 in the Finnish population [AKT2 that cause monogenic heterogeneous glycaemic diseases [Another recent study leveraging the advantages of isolated populations detected a low-frequency coding variant in pulation . The alldiseases , 38. Coldiseases . By desicis-eQTL) or over a long distance (trans-eQTL), and provide an approach for directly linking a GWAS variant to its causal gene through effects on expression levels [In contrast to missense coding variants, associating GWAS signals in non-coding regions with their downstream causal gene is often a more complex challenge. To identify regulatory effects, non-coding variants can be correlated with genomic annotations to establish a functional link with their target gene Fig. . Expressn levels . Crucialn levels .cis-eQTLs and overlapping these with variants driving T2D association signals [ZMIZ1, harbouring a gene that had been sparsely characterised for its role in T2D risk [ZMIZ1 as the likely causal gene at this T2D risk locus, and functional follow-up work has established a role in beta cell function for insulin secretion and exocytosis, thus giving first insights into a potential mechanism [For T2D, a large number of disease risk loci have been found through physiological studies to affect insulin processing or secretion in the beta cell, highlighting pancreatic islets as a relevant starting point for annotation studies at these loci . Up to n signals , 44•. Onechanism .trans-eQTLs. Trans-eQTLs act over distance and the entire genome is interrogated for any variant-gene associations, thus further limiting power due to more stringent multiple-testing correction [KFL14, a gene linked with both T2D and other metabolic traits [trans-genes that are influenced by varied KLF14 levels through cis-eQTL variants. Several genes with genome-wide significance were discovered and the study not only connected GWAS, cis- and trans-associations for the same set of variants, but also defined important disease-related pathways.Tissue availability has so far prevented any progress in finding islet rrection . Still, c traits . As KLF1cis-eQTL studies, predicted expression association studies are unable to detect context-dependent effects that are not captured by the tissues and developmental stages included in the reference panel used for modelling [The search for causal genes has been pushed ahead by eQTL studies, but the ability to perform large-scale studies containing correlated sets of genotype, phenotype and expression data are still limited by cost obstacles and sample availability. GWAS only measure genetic variation related to a disease phenotype, and expression studies suffer from reduced statistical power due to smaller sample sizes. Predicted expression association studies attempt to circumvent these limitations by integrating existing GWAS and eQTL data –50. Thisodelling , 49. It odelling . DespiteA third way to identify genes involved in disease risk is prioritisation based on known or observed functions that are perceived to be relevant for disease pathogenesis. T2D risk variants, for instance, would be expected to affect genes involved in cellular processes relevant to disease susceptibility, such as beta cell function and insulin resistance. A gene found to regulate insulin secretion would thus have high prior odds of being the downstream mediator for a nearby T2D association signal known to impact on islet function. Though this is an indirect approach for prioritisation, the strategy benefits from focusing on the relevant processes that ultimately causes effects on disease pathology Fig. . For unbARL15, THADA, and ZMIZ1. Independently of the previously described cis-eQTL study, this work thus attributed a role to ZMIZ1 in beta cell function, converging multiple lines of evidence to enhance confidence in the candidacy of this gene as causal. Importantly, the study also demonstrated a strong enrichment for known regulators of insulin secretion among significant hits, providing an internal validation that is an essential aspect of any screening strategy.High-throughput functional genomic screening is an emerging and increasingly powerful approach that allows for highly parallel phenotypic screening to address this gap. Several screening strategies have been established that differ in their direction of modulated gene expression (gain of function (GOF) vs LOF), format (pooled vs arrayed), and gene modulation techniques (RNA interference (RNAi) vs CRISPR/Cas9 modulation) –56, 57•.Spry2, the gene in the closest proximity to a nearby T2D GWAS association signal [Spry2 as the likely causal gene at this locus, and follow-up work in cellular and in vivo systems including beta cell specific knockout mice discovered a potential functional mechanism. However, a link between the non-coding association signal and Spry2 remains to be investigated, ideally through integration with variant-to-gene approaches in human beta cells. This screen also provided robust internal validation by confirming the strongest hits to be known transcription factors targeting the insulin promoter.Taking a more inclusive approach, Pappalardo and colleagues recently pursued the first whole-genome siRNA screen to identify genes involved in glucose homeostasis and T2D . While an signal . The worPLUTO was established as a regulator of its neighbouring gene PDX1, a transcription factor involved in pancreatic development and beta cell function [Medium-throughput screens and systematic analysis of selected classes of genes represents a related strategy for analysing candidate genes in more depth across a larger spectrum of possible disease phenotypes. This approach was pursued by a recent study that investigated the function of 12 long non-coding RNAs (lncRNAs) in beta cell gene regulation and their potential role in T2D . These lfunction . Based oFuture genetic screens hold the potential to play an important role in identifying causal genes for T2D. Pooled approaches are able to extend the scale of arrayed screens in a cost-effective manner and allow for simultaneous perturbation of thousands of genes to promote unbiased interrogation of candidate causal genes. The continuous development and improvement of the differentiation process of induced pluripotent stem cells into beta cells will also allow for investigations of disease-relevant phenotypes at various developmental stages , 63. HigAll of the above outlined strategies provide complementary approaches for prioritising causal genes for association signals, each with individual advantages and drawbacks. Coding variants are reliant upon large-scale association studies and naturally occurring variation, while variant-gene links are limited by the availability of primary tissue and possible pleiotropy, and gene-centric functional studies establish indirect evidence in a manner that is strongly dependent on context-dependent effects. As a result, one specific line of evidence can only give limited insights into causal mechanisms and is rarely sufficient to provide definitive evidence for a particular mechanism. The true causal gene(s) can only be identified with confidence through integration and convergence of several complementing datasets .ARAP1(CENTD2) and STARD10 [ARAP1 as an effector transcript at the locus, but recent findings contradict this assumption and instead propose STARD10 as the causal gene [cis-eQTL in islet samples, and global and selective mice knockout models were all used to generate complementary data that attribute a role to STARD10 at this locus. The comprehensive set of data makes it possible to infer causality by triangulation from different results. This point is emphasised by examining the chromatin confirmation capture data in isolation. Physical interactions between both the STARD10 and ARAP1 promoters and variants in the credible causal set highlight the possibility of regulatory effects on either gene. Thus, additional information was required to clarify the roles of these genes in disease pathology.The importance of taking an integrative approach is illustrated by the T2D susceptibility locus on chromosome 11q13, which is located near the protein-coding genes  STARD10 . Initialsal gene , 67••. FSLC16A11 and SLC16A13 [SLC16A11. Liver expression data and chromatin modification analysis showed reduced SLC16A11 expression and less-activating histone modifications in samples from T2D risk allele carriers, thus proposing SLC16A11 as the candidate causal gene. Further studies into the function of SLC16A11, an H+-coupled monocarboxylate transporter revealed that the coding risk variants exert their effect through decreased chaperone interaction and SLC16A11 plasma membrane localization. Rusu et al. were also able to show how decreased SLC16A11 function might lead to increased T2D risk by having an effect on cellular fatty acid and lipid metabolism, providing a possible therapeutic strategy.Another recent study outlines how the integration of genomic, expression and functional data can prioritise a potential causal gene and disease mechanism, and furthermore directly propose a therapeutic hypothesis. The investigated T2D risk allele is common in Mexicans and Latin Americans  and located near SLC16A13 . Fine-maDespite comprehensive integration of datasets, the evidence in these studies still cannot exclude additional pleiotropy . Exhaustively addressing these gaps will require access to data that enable interrogation of variant function in any context , and is far from being a feasible aim for current post-GWAS studies. The emergence of ever-greater, publically available datasets of this nature will increasingly facilitate integration with results of individual studies and thereby guide interpretation. Large-scale projects such as ENCODE, Genotype-Tissue Expression (GTEx) and the NIH Epigenomics Roadmap have already generated enormous functional annotation datasets that allow for intersection with potentially causal variants across hundreds of cell types , 69, 70.Connecting GWAS association signals to their corresponding causal genes has proven a major experimental challenge and bottleneck for therapeutic translation. As a consequence of GWAS design and the genetic architecture of T2D, causal variants and genes cannot be easily inferred from genetic association studies, hindering functional interpretation. Thus, prioritising causal genes at T2D loci to aid functional understanding is a central aspect of current studies. These studies must be guided by parallel efforts to identify causal variants and appropriate disease-relevant model systems. A number of strategies have emerged for causal gene prioritisation based on genetic data, genomic annotations, and functional screening, each with limitations that render them insufficient in isolation. Several lines of evidence and different experimental strategies should thus be triangulated to validate the results and increase confidence in a specific causal mechanism. Looking forward, this era of gene prioritisation based on T2D GWAS loci and functional understanding holds the promise to unlock the full potential of genomic medicine and clinical translation.


Human induced pluripotent stem cells (hiPSCs) have been attempted for clinical application with diverse iPSCs sources derived from various cell types. This proposes that there would be a shared reprogramming route regardless of different starting cell types. However, the insights of reprogramming process are mostly restricted to only fibroblasts of both human and mouse. To understand molecular mechanisms of cellular reprogramming, the investigation of the conserved reprogramming routes from various cell types is needed. Particularly, the maturation, belonging to the mid phase of reprogramming, was reported as the main roadblock of reprogramming from human dermal fibroblasts to hiPSCs. Therefore, we investigated first whether the shared reprogramming routes exists across various human cell types and second whether the maturation is also a major blockage of reprogramming in various cell types.We selected 3615 genes with dynamic expressions during reprogramming from five human starting cell types by using time-course microarray dataset. Then, we analyzed transcriptomic variances, which were clustered into 3 distinct transcriptomic phases ; and greatest difference lied in the late phase. Moreover, functional annotation of gene clusters classified by gene expression patterns showed the mesenchymal-epithelial transition from day 0 to 3, transient upregulation of epidermis related genes from day 7 to 15, and upregulation of pluripotent genes from day 20, which were partially similar to the reprogramming process of mouse embryonic fibroblasts. We lastly illustrated variations of transcription factor activity at each time point of the reprogramming process and a major differential transition of transcriptome in between day 15 to 20 regardless of cell types. Therefore, the results implied that the maturation would be a major roadblock across multiple cell types in the human reprogramming process.Human cellular reprogramming process could be traced into three different phases across various cell types. As the late phase exhibited the greatest dissimilarity, the maturation step could be suggested as the common major roadblock during human cellular reprogramming. To understand further molecular mechanisms of the maturation would enhance reprogramming efficiency by overcoming the roadblock during hiPSCs generation.The online version of this article (10.1186/s12864-017-4389-8) contains supplementary material, which is available to authorized users. Human induced pluripotent stem cells (hiPSCs) have revolutionized not only stem cell research but also clinical medicine by advancing cell therapy, disease modeling, and drug discovery. However, the reprogramming process is still inefficient and establishment of high-quality hiPSCs is unreliable regardless of many developed reprogramming methods to increase efficiency and safety , 2. TherPrevious studies conducted time-course gene expression analyses during reprogramming using mouse embryonic fibroblasts (MEFs) , 4. ThesHowever, the characteristics and the timing of hiPSCs reprogramming events have been reported to be different from mouse, although iPSCs can be generated by the induction of the same transcription factors . For exaAlthough the current insights of cellular reprogramming of hiPSCs were confined to fibroblasts, hiPSCs have been established from multiple somatic cell types including dermal fibroblasts , 13, adiFor the purpose, we extracted dynamically expressed genes in five different human somatic reprogramming cell types from time-course microarray dataset . Next, wTo find conserved genes with dynamic expression from various human cell types in cellular reprogramming, we used a dataset from Gene Expression Omnibus under the accession number GSE50206 . It cont2 transformation and quantile normalization. We used the limma package for quantile normalization in R using Bioconductor [P-value <0.01, FDR < 0.05, R2 > 0.6). The filtration yielded 3615 extracted genes  and were found many times in the net (more than one hundredth of the maximum number of gene regulatory network). These are default parameters in CoRegNet package.In Fig. http://metascape.org) to find top 10 clusters with the representative enriched terms of Reactome and GO Biological Processes [For functional annotation of gene sets, we used Metascape  and HDFs . SimilarIn addition, DNMT3L, a catalytically inactive regulatory factor of DNA methyltransferases, was reported that it was highly expressed on day 20 of reprogrammed HDF in iPSCs generation . MoreoveThe previous studies illustrated the mouse cell line reprogramming from MEFs; firstly mesenchymal gene expression was lost, followed by transiently upregulation of epidermal genes, and lastly pluripotency genes are stably expressed , 7. InteAlthough, transcriptome dynamics during reprogramming were justifiably represented by using microarray dataset, because the microarray is bulk measurements on cell populations so it can mask the transcriptomic changes of small cell population . NeverthIn comparison to microarray, RNA-seq would be more suitable to detect dynamically expressed genes because it is more sensitive in detecting genes with very low expression and has a wider dynamic range . HoweverIt is also possible that the different copies of OSKM retroviral vectors were integrated into genome and influence different gene expression profiles. Indeed, previous study showed each iPS clone derived from MEF has different numbers of retroviral integration . In addiAs far as we know, our report is the first study to describe that human reprogramming process was partially shared across multiple different human somatic cells and that maturation could be the common barrier in reprogramming in various human cell types. The strategy can be applied not only transcriptome but also epigenetic or proteomic studies and it would provide further insights of the fundamental mechanisms of cellular reprogramming.In summary, we illustrate that the reprogramming process was shared in five human somatic cell types by applying the genome-wide analyses of time-course microarray data. From the results of functional annotations of the gene expression patterns and reconstruction of transcription factor activity, we suggest the maturation could be the common roadblock of reprogramming into hiPSCs in various cell types. Identification of a reprogramming route shared in cell types would provide the keys to further investigate and understand the mechanisms of cellular reprogramming.Additional file 1: Table S1.List of microarray sample data which used in this study. (TSV 5 kb)Additional file 2: Figure S3.(a) Gene expression patterns during reprogramming in five cells and H3K79me2 and H3K27me3 ChIP-seq tracks  for SNAI2, TUBB3, and PRDM14 in fibroblasts (D0), at day 6 of OSKM induced fibroblasts (D6) and ESCs (ES). Bars below each ChIP-seq track were genomic features which contain top 0.1% signal intensity. (b) Gene expression patterns in each cluster PCA and HCA of each cell type by using logAdditional file 4: Table S2List of gene symbols clustered with five groups in Fig. Additional file 5: Figure S2.2 expression value. (a) all 22,062 genes in GPL14550 platform. (b) extracted 3615 genes. Tissue-derived cells and ESC-derived cells were labeled as black and dark red, respectively. (PDF 66 kb)PCA of 75 cell types by using logAdditional file 6: Figure S4.FOSL2 gene expression pattern. (PDF 39 kb)Additional file 7: Figure S5.DNMT3L and AIRE gene expression patterns. (PDF 76 kb)


Gossypium hirsutum) is only around 20%. In this study, we modified the accumulation of oils by the down-regulation of phosphoenolpyruvate carboxylase 1 (GhPEPC1) via RNA interference in transgenic cotton plants. The qRT-PCR and enzyme activity assay revealed that the transcription and expression of GhPEPC1 was dramatically down-regulated in transgenic lines. Consequently, the cottonseed oil content in several transgenic lines showed a significant (P < 0.01) increase (up to 16.7%) without obvious phenotypic changes under filed condition when compared to the control plants. In order to elucidate the molecular mechanism of GhPEPC1 in the regulation of seed oil content, we quantified the expression of the carbon metabolism related genes of transgenic GhPEPC1 RNAi lines by transcriptome analysis. This analysis revealed the decrease of GhPEPC1 expression led to the increase expression of triacylglycerol biosynthesis-related genes, which eventually contributed to the lipid biosynthesis in cotton. This result provides a valuable information for cottonseed oil biosynthesis pathway and shows the potential of creating high cottonseed oil germplasm by RNAi strategy for cotton breeding.Cottonseed oil is recognized as an important oil in food industry for its unique characters: low flavor reversion and the high level of antioxidants (VitaminE) as well as unsaturated fatty acid. However, the cottonseed oil content of cultivated cotton ( Gossypium hirsutum L.) is one of the widespread cultivation domesticated genera of Gossypium in the family of Malvaceae. Its cultivation can be dated from as long ago as 3,500G. hirsutum2G. babardenceG. raimondii G. arboreum Allotetraploid upland cotton  biosynthetic enzymes as well as modification of the upstream carbon flow, and transcription factors (TFs) that regulate the expression of multiple genes, and provide a good reference for us to enhance the contents of cottonseed oilArabidopsis was generated by the enhancer tagging system as well as a protein synthesis-related gene At1g0150 was identified by Meyer and his colleaguesAt1g01050 gene by seed-preferred RNA interference, increase in seed oil content was observed from 1% to 4%, mostly at the expense of seed storage protein. This study demonstrates the important role of pyrophosphate in regulation of carbon flow in oil and protein synthesis and also provide a novel route to modify seed composition by biotechnology.The plant oil is largely stored in seed in the form of oil droplets, which interacts with oleosin to maintain its stability in the cotyledons cells, and is consumed during the initial stage of seed germinationet al. proved the role of PEPCase in the accumulation of protein and oil through RNAi/over-expression of CrCIS and CrPEPC1 genes in C. reinhardtii. In addition, they investigated the carbon source used for biosynthesis of the fatty acids only accounted for 45.9% of the total amount of photosynthetic carbon fixation17Phosphoenolpyruvate carboxylase  and Acetyl-CoA carboxylase  are generally considered to play critical role in the regulation of assimilate carbon flow into oil and protein biosynthesis pathway . ACC is Caenorhabditis elegans202122RNAi (RNA interference), a post transcriptional gene silencing (PTGS) mechanism occurs in the cell’s cytoplasm, which is controlled by the RNA-induced silencing complex (RISC) and initiated by short double-stranded RNA (dsRNA)C. reinhardtii was observed during the down-regulation of pepc2 gene by RNAi suggesting a negative correlation between pepc2 mRNA abundance and oil contentCrPEPC1 gene in C. reinhardtii by RNAi decreased PEPC activities by 39–50% and subsequently increased TAG level by 20%. Moreover, the decrease in CrPEPC1 expression was observed to increase the expression of TAG biosynthesis-related genes. Conversely, CrPEPC1 over-expression decreased TAG level by 37% and increased PEPC activities by 157–184%. These observations suggest that the oil content of algal cells can be controlled by regulation of the CrPEPC1 gene expressionChlamydomonas citrate synthase (CrCIS) was also investigated by the same team. The results showed that the down-regulation of CrCIS gene by RNAi could also increase the lipid content of algal cells. In the algal cells, the TAG level was increased by 169.5% after decreasing of CrCIS activity by 16.7% to 37.7% in the transgenic algae. Moreover, the decrease in CrCIS expression led to the increase in expression of TAG biosynthesis-related genesPEPC gene was found to be a crucial gene having role in modulating the balance of carbon and nitrogen metabolism. The transgenic plants accumulated more starch and sucrose but significantly lower nitrate levels were observed during the performance of double knockout of ppc1/ppc2Although the current research of PEPC is mainly concentrated in photosynthesis, still there are several reports which focus on the PEPC’s function on carbon flux distribution. A 14–28% increase in oil content of PEPC cDNAs was cloned by RACE with the length of 3405 bp, but the detailed analysis about its function was not reportedGhPEPC2 was isolated from cotton (G. hirsutum cv. zhongmian 35) by RACE-PCR as well as its genetic information, expression patterns and catalytic were also describedet al. examined the molecular basis of GhPEPC1 and 2 by malate synthesis in cotton fiber rapid elongation phaseThe first cotton GhPEPC1 (GenBank: AF008939.1) and GhPEPC2 (GenBank: EU032328.1) is available in National Center for Biotechnology Information (NCBI). GhPEPC2 is encoding 971 amino acids having molecular mass of 110.6 kD and pI of 5.56. The amino acids multiple sequence alignment revealed that this enzyme contain all the conserved functional domains. It has been shown by tissue expression analysis and function analysis that GhPEPC2 might be a house-keeping gene, which might play important physiological roles in rootsGhPEPC1 in cotton. In order to investigate the correlation between GhPEPC expression and oil accumulation in cotton, the GhPEPC1 gene was down-regulated GhPEPC1 in transgenic cotton plants by RNAi strategy. Our results revealed that cottonseed oil content is significantly increased in transgenic lines parallel with lower GhPEPC1 transcription levels. Moreover, we quantified the expression of the carbon metabolism related genes of transgenic GhPEPC1 RNAi lines and the control plants by transcriptome and biochemistry analysis, which revealed that the decrease in GhPEPC1 expression led to the increase in expression of TAG biosynthesis related genes. Taken together, this report demonstrates the feasibility of improving cottonseed oil yield by the regulation of carbon flux through GhPEPC gene.However, the information of two PEPC isoforms, GhPEPC1 encodes 965 amino acids having molecular weight of 110 kD and an isoelectric point of 5.95. Multiple sequence alignment of the PEPC amino acid sequence from G. raimondii genomeG. hirsutum in NCBI revealed that GhPEPC1 contains a Ser residue in N terminus, which acts as a phosphorylation site and exclusively belongs to plant PEPCs29303132GhPEPC1 has all conserved motifs and function domains that had been identified in plant PEPCs gene family 28GhPEPC1 contains total 47 phosphorylation sites, including 26 serine, 15 threonine and 6 tyrosine predicted by NetPhos2.0. Transmembrane helices, signal peptide and subcellular localization analysis showed that GhPEPC1 might be a cytoplasmic solubility protein without transmembrane domains  and signal peptide . Furthermore, rooted phylogenetic analysis using the PEPCs coding sequence and zea mays (GI: 162461755) acting as outgroup showed two distinct branches, suggesting that GhPEPC1 and GhPEPC2 were belonged to two different branches  in this gene as the RNAi target fragments  fragments silencing vectors , which were cultivated in greenhouses (T0 generation) and field . The results of southern blot showed that T-DNA region of RNAi vector has been inserted into the upland cotton genome with single-copy (PPC8) or double-copies (PPC1) .To determine the influences of  vectors  of the GThe total cottonseed oil content of transgenic lines and null cotton plants were assayed by using the Nuclear Magnetic Resonance (NMR). Furthermore, Gas Chromatography was used to select some representative lines  for fatty acid composition assay. Determination of total cottonseed oil content in these transgenic lines and null plants showed that cottonseed oil content was significantly increased by 16.7% (p < 0.01) in GhPPC transgenic line-PPC1  as compaFor fatty acid composition analysis, 0.2 mg/ml fatty acid standard solution  was used to determine the peak time of each fatty acid in the standard solution . Then, the cottonseed fatty acid composition in different lines at different developmental stages were detected and the results show a relatively abundant linolenic acid content in leaves than cottonseed, but the linoleic acid is opposite. Another obvious trend is that the cottonseed begins a sharp oil accumulation during 10DPA to 30DPA. Hexadecanoic acid and linoleic acid, no doubt, are the major contributors in this process. Particularly, at maturation stage (40DPA), the cottonseed oil content was significantly increased  in PPC1 transgenic line when compared to null plants ,b, with GhPEPC1.With the increase of total cottonseed oil content, the total protein content in this cottonseed was found to be displayed downtrend . A negatG. hirsutum genome2 = 0.95 similarity between transgenic line and null plants due to the almost identical genetic background except a transgenic event of the GhPEPC1 gene silenced by RNAi . FPKM analysis showed a total of 82 DEGs between PPC8 transgenic line and null plants, of which 55 were up-regulated and 27 down-regulated. Subsequently, by comparison with the annotation result from Zhang’s report2 indicated that some of the genes identified here were novel and had not been annotated so far. The DEGs between the null plants and RNAi line was showed by using volcanic figure. The red dots are up-regulated genes and blue dots indicated down regulated genes . Since we were concerned about the expression of all GhPEPC genes in transcriptional level, the line graph were performed to compare all GhPEPCs genes expression level (FPKM) between null and PPC8. Results revealed that only Gh_A09G0010 (GhPEPC1) gene expression level was significantly lower  than in the null. Moreover, we also observed other PEPC homologous genes showing a slightly declined expression level .To investigate the changes of transcript accumulation in RNAi transgenic lines, one of the transgenic lines PPC8 was used to construct the RNA-Seq library. A summary of read pairs and mapping information of this study were listed in 2 integrate into ribulose-1,5-bisphosphate and then produces 3-phosphoglycerate after hydrolysisGhPEPC1 gene in carbon fixation and photosynthesis  gene was analyzed by qRT-PCR. Increase in ACC transcription levels was observed in transgenic plant compared with null plant. Most importantly, the ACC expression levels and the content of cottonseed oil in different lines were positively related (R2 = 0.66) and the expression level of ACC gene was significantly  increased in PPC1 lines compared with null plant .It is well known that phosphoenolpyruvate carboxylase is a key enzyme involved in photosynthesis. So we evaluated the phenotype and major agronomic traits of transgenic descendants under field conditions at three research station located in Hubei province-Ezhou, Wuhan and Campus station from May 1st to October 1st in several major parameters of photosynthesis , chlorophyll and other agronomic traits of transgenic lines were investigated to evaluate the effects of RNAi silencing As shown in Table S3, chlorophyll content were all slightly declined for RNAi lines in different research stations and statistics analysis revealed that this difference was significant in some lines . Decrease in photosynthesis was observed in transgenic plants as comparsion with null plants . To investigate the circadian rhythm changes of photosynthesis, we measured photosynthetic rate at three time points within the same day. The results revealed that photosynthetic rate intensity of transgenic lines and null plants showed similar trends: followed by morning >noon >afternoon. The proper order of stomatal conductance and transpiration rate was shown as follows: noon >morning >afternoon .At the flowering stage of cotton plants, all the transgenic plants did not show obvious phenotype changes under field conditions . Interestingly, the size of cotton seeds was even enlarged when compared to the null cotton seeds . Boll number per plant is an important indicator to estimate the yield eventually. In this experiment, we found that the mean boll number per plant in most transgenic cotton lines were significantly higher than the control lines . Seed inTropaeolum majus diacylglycerol acyltransferase 1 (TmDGAT1), an enzyme that catalyzes the change of diacylglycerol combined with Acyl-CoA to triglycerides, resulted in an increase of 3.5–10% oil content in dry weight in wild-type Arabidopsis and confirmed the importance of serine/threonine site in this kinaseet al. proposed that more carbon flow into acetyl-CoA could improve the chloroplastic CoA pool level and higher acetyl-CoA biosynthesis could enhance TAG biosynthesisC. reinhardtii, the comprehensive study of PEPCGhPEPC1 gene via RNAi strategy.With the sharp increase of people’s living standards as well as frequent health threat related complications, such as obesity, cancer and cardiovascular disease, more and more people are concerned about healthy eating. Under this circumstance, more peoples fascinated cottonseed oil due to its high content of unsaturated fatty acid (linoleic acid), low content of trans-fatty acid, high level antioxidants (Vitamin E) and low flavor reversion. To meet this demand of increased consumption of cottonseeds oil, the metabolic engineering is recognized as a feasible and efficient strategy by changing the expression of key enzymes in metabolic process. Fortunately, many key genes involved in the metabolite biosynthesis especially for oil biosynthesis have been identified from diverse species. For example, an overexpression of the et al. expressed AtWRI1 gene in the Camelina sativa and which increased the total seed oil by14% through the up-regulation of several genes related to the genes of lipid biosynthesis including pyruvate dehydrogenase E1α subunit, biotin carboxyl carrier protein and expansin 1GhPEPC1 resulted in the expression level of several genes coinciding with existing reports, as well as expansin gene, which may involve in cell expansionGhPEPC1 is not a transcription factor, this is a hub gene plays role in the basic metabolism net having close relationship with carbon flows. Consequently multiple related gene would be affected due to disturbance of expression of this gene.Compared to a single function gene, more researchers are paying attention to the transcription factor due to its ability to regulate multiple genes at the same time. An GhPEPC1 with regard to the carbon and lipid metabolic in cotton. GhPEPC1 works as a core enzyme not only involved in photosynthesis but also regulated the inflowing of carbon turnover to fatty acid biosynthesis and finally contributed to the increase of cottonseed oil content . These citrates have participated into biosynthesis of fatty acids and finally stored in cottonseed in the form of TAG . The pyntration . The excm of TAG .GhPEPC1 was selected as RNAi target gene and a number of transgenic lines were obtained through Agrobacterium-mediated genetic transformation by using 35S promoter. The results of genetic transformation presents two dilemma. On the one hand, Why does a few deleterious effects throughout the plant of down-regulating a very important gene by 35S promoter- mediated RNAi? For this question, as it is known that the upland cotton is allotetraploid and we found up to 31 copies of GhPEPC genes based on the Gossypium hirsutum genome2. So, the deleterious effects–resulted from 35s promoter-were maybe offset by some paralogs genes of RNAi target gene. On the other hand, we found only half of the transgenic lines showed significantly improve in oil content ranging from 5.0–16.7%. It has been speculated that one of the main reasons is that RNAi cannot thoroughly suppress the express of target genes. Luckily, we created a transgenic RNAi population with more than 40 independent lines and several lines such as PPC1 line showed obvious decrease in both transcription and activity of GhPEPC1. It is known that RNAi requires active repression effect on the target gene, but this effect could be weaken through increased target genes mRNA turnover and/or decrease RNA-induced silencing complex (RISC) turnover4243In this metabolism engineering of cotton oil content, the In this report, it has also been found that most of DEGs identified by RNA-seq are less than 1kb in length . Under systematic study of human and mouse genomes Grishkevich and Itai proposed that gene length and expression levels are closely related with gene duplication and alternative splicing. Generally, short genes more tend to have low expression levels and few splice variants but many gene duplicates, it indicates that large gene families are less important for the development of plantsGhPEPC1 via RNAi in transgenic cotton plants. The results indicated that cottonseed oil content in transgenic plants showed a significantly increase up to 16.7% in comparison with control plants. The transcriptome analysis applied in transgenic and control plants revealed that most of DEGs were involved in the metabolism of carbon and lipid. This result provides valuable information for cotton oil biosynthesis pathway and shows the potential of creating high cottonseed oil content germplasm by RNAi strategy in cotton breeding.In this study, we successfully modified the accumulation of oils by down-regulation of the The total RNA of transgenic and null (negative offspring derived from genetic segregation of positive transgenic plant) cotton plants were prepared by using the modified guanidine thiocyanate method as previously described in our reporthttp://web.expasy.org/protparam/). Protein phosphorylation sites were performed by using NetPhos 2.0 (http://www.cbs.dtu.dk/services/NetPhos/). TMHMM (http://www.cbs.dtu.dk/services/TMHMM/) and SignalP  were used to predict transmembrane helices and signal peptide. Protein subcellular localization was analyzed with PSORT II Prediction (http://psort.hgc.jp/form2.html), and the sequence alignments were completed using the DNAMAN and MEGA6 software with the neighbour-joining method for phylogenetic analysis.The primary structure of protein was predicted by using ExPASy-ProtParam tool . The conserved domain and 3′-UTR-specific region fragments of the GhPEPC1 gene were amplified respectively by PCR using primers GhPPC-F: 5′-TTGAATACTTCCGCCTAGCA -3′ and Gh PPC -R: 5′-AGCGATTCCAGGGTCTCC -3′. After purification of the DNA using Purification Kit , the target gene fragments were inserted into RNAi vector pHellsgate 4 of the gateway system. The resulting plasmids was designated as 35s-GhPPC. All above DNA sequences analyzed were performed by Beijing Genomics Institute . The expression constructs were introduced into the Agrobacterium tumefaciens strains EHA105 (kanamycin as selectable marker) after electroporation, and then used for genetic transformation via Agrobacterium-meditated in cotton cultivar YZ1 according to our previous publications2347Total RNA was isolated as mentioned above and the first strand of cDNA was synthesized by using the SuperScript III reverse transcriptase . Complete coding sequence DNA was isolated from the young leaves of putative transgenic and null plants using a Plant Genomic DNA Kit . The 35S promoter forward primer from RNAi vector and target gene fragment reverse primer were used for PCR amplification of positive detection with transgenic lines.NPTII gene was used as a probe for Southern blotting to detect the copy number of transgene insertion. A DIG High Prime DNA Labeling and Detection Starter Kit II  were used for Southern hybridization. First, the cotton genomic DNA was digested with Hind III -HF, electrophoresed on 0.8% agarose gel (DNA Molecular Weight Marker II labeled with DIG) and blotted onto a Hybond N+ membrane through salt bridge for hybridization. After hybridization and stringent washing, the Digoxigenin-11-dUTP was incorporated into the newly synthesized DNA probes via PCR amplification and then hybridized with the target DNA. Finally, a digoxin antibody that connected with alkaline phosphatase was used as detection probe labeled with digoxin. After completion of these protocols, CSDP  was used to visualize the position of probe hybridization in x-rays.Through the PCR amplification, the fragment of For determination of cottonseed oil content, cotton flowers were self on the first day postanthesis (DPA) and collected at four developmental stages, 10, 30, and 40 DPA, representing different stages of cottonseed oil accumulation in embryo or immature seeds according to previous reportThe method of Nuclear Magnetic Resonance (NMR) Spectroscopy  was used to determine the mature oil content of cotton seed. The oil content of developing seeds was determined by using Gas Chromatography (GC) analyses as the Fatty Acid Mass Spectrometry ProtocolThe content of total methyl esters fatty acid composition was measured on a gas chromatograph-mass spectrometer . The oven temperature was maintained at 170 °C for 1 min and then increased in steps by 3 °C every min to 230 °C. Methyl ester derivatives were detected by using MS.In consideration of the completed with protein and oil content in cottonseed, we were also determined the total protein content in mature cottonseed. Approximately 0.1 g cottonseed kernel was collected and mixed in 500 μL of protein extracting solution , then completely ground by using mortar and pestle. The mixture was transferred into 1.5 ml centrifuge tube and placed on ice for 5–10 min. After centrifugation at 13000 rpm at 4 °C for 15 min, the supernatant was pipetted and then again mixture was centrifuged to get final supernatant. Final total protein content was determined by using RC DC Protein Assay Kit  following the standard assay protocol and calculated at the 750 nm absorbance within the standard curve, which BAS was used as standard protein.http://www.usadellab.org/cms/). FastQC and SolexaQA quality visualization were applied and clean reads would be used for further analysis. RNA-seq analysis protocol contains sequence alignment, assembly, calculation of expression and mining of differentially expression genes (DEGs) referred Trapnell’s proposalG. hirsutum L. acc. TM-1Total RNA was extracted as previously described protocol. RNA samples, with qualified quality, were sequenced on the Illumina Hi-Seq 2500 sequencer  at the Biomarker Technologies . All reads are available for download on NCBI bioproject (PRJNA339421). Clean reads were filtered from raw reads to remove low quality reads and adapter under this command parameters: LEADING:5 TRAILING:5 SLIDINGWINDOW:4:20 MINLEN:50 using Trimmomatic . Hierarchical clustering of differentially expression genes were performed on FPKM with ward.D2 clustering method and visualized on Heat map in R using the pheatmap package.G. hirsutum coding sequenceCT. Error bars represent the standard deviation.Isolated total RNA of transgenic and null plants was reverse-transcribed to cDNA as previously described. Quantitative real-time PCR (qRT-PCR) was performed with the ABI Prism 7000 system  using SYBR Green as the fluorescent dye. In this qRT-PCR analysis, 3 plants of each transgenic line and null plants were randomly selected and sampled for each independent biological replicate. Gene sequences were obtained from the RNA-seq resulted and The PEPCase enzyme activity of transgenic lines and null plants were determined by using a phosphoenolpyruvate carboxylase kit  following the manufacturer’s instruction. Finally, one unit (U) of PEPCase activity was defined as the amount of PEPCase required to consume 1 nmol NADH of per gram tissue in per minute.g for 10 min. Determination process was completed with the following steps: 300 μL supernatant and 100 μL 2,4-Dinitrophenylhydrazine assay buffer 1 were added into the 1.5 ml centrifuge tube. After well mixed and transitory quieted for 2 min, 500 μL alkaline assay buffer 2 was added and the absorbance were measured at 520 nm with L6 UV-visible spectrophotometer . Final pyruvate content was calculated through the standard curve.Pyruvate content was detected by using pyruvic acid assay kit . For the sample preparation, approximately 0.1 g leaf tissues were collected and mixed with 1 ml extracting solution, then rapidly homogenized on the ice. In order to fully extract pyruvate, the homogenate was quieted for 30 min and then centrifuged with 8000 × An oxaloacetate colorimetric assay kit  was used to determine total oxaloacetate content in cotton following the recommended manufacturer’s instruction. Final OAA concentrations were also calculated based on the standard curve.® Biosciences, Nebraska, USA) and chlorophyll contents were detected by SPAD 502 Plus Chlorophyll Meter . The measurement time of photosynthesis was around 10:00 am, but for chlorophyll was inadvertent. In particular, we measured the photosynthesis at different time points in one of the research stations (Campus station) at 8 am, 2 pm and 5 pm, respectively.We designed filed test for T2 generation of transgenic population and null plants at three research stations, namely, Ezhou, Wuhan and Campus station. At the flowering stage, the photosynthesis rate of cotton plants was measured by using the LI-6400XT Portable Photosynthesis System , the agronomic traits of all transgenic lines and null plants were determined including phenotypic traits and yield traits. For yield traits, seed index (100-grain cottonseed weight), cottonseed oil content and boll number per plant were determined.GhPEPC1 expression in transgenic cotton led to the increased expression of TAG biosynthesis related genes and elevated cottonseed oil content, which demonstrated the feasibility of improving cottonseed oil yield by regulating the carbon flux.This is the first report of artificially improved oil content via RNAi strategy and the analysis of its metabolic mechanism in Upland cotton. Decreased How to cite this article: Xu, Z. et al. Metabolic engineering of cottonseed oil biosynthesis pathway via RNA interference. Sci. Rep.6, 33342; doi: 10.1038/srep33342 (2016).