The results identify that in old males decreased expression of CRABP2 leads to cell proliferation, whereas in old females it leads to cellular senescence. In conjunction with existing literature the results explain gender disparity in the development and types of degenerative diseases as well as highlighting a wide range of considerations for the analysis of transcriptomic data. Wider implications are that degenerative diseases may need to be treated differently in males and females because alternative mechanisms may be involved.The development of tendinopathy is influenced by a variety of factors including age, gender, sex hormones and diabetes status. Cross platform comparative analysis of transcriptomic data elucidated the connections between these entities in the context of ageing. Tissue-engineered tendons differentiated from bone marrow derived mesenchymal stem cells from young (20–24 years) and old (54–70 years) donors were assayed using ribonucleic acid sequencing (RNA-seq). Extension of the experiment to microarray and RNA-seq data from tendon identified gender specific gene expression changes highlighting disparity with existing literature and published pathways. Separation of RNA-seq data by sex revealed underlying negative binomial distributions which increased statistical power. Sex specific  Tendons provide physical and mechanical connections between muscle and bone allowing movement of the skeletal system2. The cellular and molecular mechanisms that result in increased age-related tendon injury are not well established but are thought to result in altered matrix turnover4. Interest in mesenchymal stem cells (MSCs) as a therapy for musculoskeletal disorders such as tendinopathy and arthritis has increased recently due to their ability to differentiate into osteoblasts for bone regeneration, chondrocytes for cartilage regeneration, and tissue-engineered tendons (TET) for tendon production5. Aged MSCs are thought to be less able to proliferate and regenerate tissues giving rise to musculoskeletal diseases affecting 1.7 billion people across the globe6. One theory is that as we age genes become hypermethylated blocking transcriptional start sites, which results in reduced transcription and a subsequent reduction in cell proliferation, however contradictory results have been obtained9. Studies show high concentrations of external glucose reduce the potential for cells to respond to oxidative stress damaging the biomechanics of tendon, and that thyroid disorders and diabetes increase calcification of tendon10. Females, diabetics and those treated with quinolones are most susceptible; the development of tendinopathy has been specifically linked to gender and hormones11. Testosterone, oestrogen, insulin and growth hormones have all been found to influence the development of tendinopathies. In mixed male (n = 3) and female (n = 5) samples from donors with tibial tendon dysfunction oestrogen receptors are not significantly differentially expressed12. In male rat achilles tendon systematic application of glucocorticoids decreases tensile strength, collagen type I and lysyl oxidase expression13. Diabetic male rats with injured tendon have identified reductions in the expression of collagen I and III as well as MMP-314. Gene focused RT-PCR studies completed on tendon like tissues derived from male mesenchymal stromal cells did not identify significant age-related differences in osteocalcin TGF-β2 or decorin15. Some gender differences have been highlighted; achilles tendinopathy serum has lower concentrations of both Tumour Necrosis Factor alpha (TNF-α), Interleukin 1 beta (IL-1-β) and Platelet Derived Growth Factor (PDGF-BB) in females16.Tendinopathy is especially common among athletes and manual workers, and development of tendinopathy is known to increase in frequency with age17. Thus transcriptomic data from TET could prove an invaluable in vitro model to assess factors contributing to the development of tendinopathy. RNA-seq has a plethora of advantages over microarrays such as the ability to identify isoforms, alternate splicing, differences in transcriptional start sites, and differential promoter use. Additionally RNA-seq is not dependent on the design of microarray probes, fluorescence of dyes, efficiency of microarray scanners, poly-A selection or RT-PCR steps. RNA sequencing can identify microRNAs, long non-coding RNAs and small nuclear RNAs as well as mRNA resulting in a detailed and comprehensive view of the transcriptome. Transcriptional start sites have been found to be different in males and females producing different isoforms under different oestrogen concentrations and in different tissues18. In females hypermethylation of one X chromosome leads to inactivation of transcriptional start sites in some tissues; females are mosaics with patches of tissue expressing either the paternally or maternally derived X chromosome20.Experimental animal models are frequently male which does not represent the demographic affected by tendinitis, additionally they may not capture the structure and function of human tendons, both of which are limitations. There are clear benefits in replacing animal models with alternatives wherever possible; reducing the number of animals used to a minimum21. The validity of this was tested using parallel analysis of microarray data from young and old tendon derived from various tendons22 (E-GEOD-26051), contrasting and comparing results. To the authors knowledge this is the first study of its kind, implementing a cross platform parallel analysis of samples with separation of male and female subsets to identify gender specific gene expression changes with age. Separate analysis of male and female data sets simplified analysis and reduced the dependency of results on mathematical algorithms and their underlying assumptions. The results highlight the importance of gender differences which are frequently neglected in gene expression studies.This study extends the analysis of RNA-seq data from tissue derived Achilles tendon from young and old donors (E-MTAB-2449) to include RNA-seq data from TET (E-MTAB-4879). Both of the aforementioned studies were gender imbalanced. Analysis of these combined datasets was undertaken in order to identify male and female specific gene expression changes with age. Previous work has identified that age affects gene expression in tendon and TET similarly2 of young males and females was similar, however CV2 is reduced in old females, but increased in old males. Old females have similar gene expression profiles to young males, and old males are similar to young females  only young (y) tendon (T) and old (o) TET was available. For males (Y) young and old cells from T, TET were assessed when both were combined (T/TET). Old versus young, and male versus female comparisons were possible due to CuffDiff analysis on male and female data sets combined. When age and gender factors are used to separate samples into groups all DE transcripts from females have different transcriptional start sites (TSS). More transcripts, isoforms, and transcriptional start sites were identified as significantly different in the male versus female comparison than the old versus young comparison. Additionally old female tendon (oX T) versus young female TET (yX TET) identified the most transcripts as DE. In females all transcripts had different promoters, and transcriptional start sites giving rise to different isoforms. No alternate splicing was identified in any comparison and a large number of small RNAs  were identified. The total number of transcripts identified was over 2.5 million, and the percentage of transcripts identified as DE was below 0.01% in all comparisons. Descriptive statistics were obtained for the data generated using Method Two; separate male and female analysis with sex specific transcript files ) and E-MTAB-4879 TET old male versus young male (oY v yY (TET). Additionally an old versus young analysis was completed on mixed tendon and TET from males (oY V yY (T/TET)). Direct old versus young, and male versus female comparisons were not possible due to separate CuffDiff analysis for male and female data sets and sex specific merged transcript files. However significantly q < 0.05) DE transcripts identified in males and females were compared Figs , 4 and 5 DE transNo genes were identified as significantly DE using both technologies for aged males or females Tables M1 and M2S3Table Using Method One with RNA-seq data genes in the p38MAPK cascade were over-represented in old males Figure M1. Using MGene Ontology analysis of RNA-seq genes decreased in old males using Method One identified they were involved in regulation of the immune system with reductions in collagen fibril organisation, keratin catabolism and mineral regulation Figure M1. Using Mγ R-mediated phagocytosis, pathways in cancer, PPAR signalling and regulation of the actin cytoskeleton consistent with increased cell cycle. Significant pathways identified by genes significantly decreased in expression included transcriptional misregulation in cancer, N-glycan biosynthesis, proteoglycans in cancer, and PI3K-AKT signalling (Table M2Only the nitrogen metabolism pathway (glutamate synthesis) was identified as increased in old males using microarrays. RNA-seq identified more pathways; when mixed tendon and TET were assessed using Method One genes increased were involved in inflammation (cytokines), calcium signalling, response to hormones, Janus kinase (JAK) Signal Transducer and Activator of Transcription (JAK-STAT) signalling, increased cell cycle and cancers. Genes decreased were involved in immune signalling; major histocompatibility complex II, killer cell inhibitory receptor, natural killer cells and regulation of cell proliferation Table M1. When Me Table M2.RNA-seq identified increased gene expression in old females that represented a variety of biological processes involved in cell development, response to oxygen, lipid transport, protein modification, T-cell anergy as well as alterations in metabolic pathways  DE in tendon in the original study by Peffers et al.55 compared to the log2 fold change in expression of significantly (q < 0.05) DE transcripts identified in tendon and TET in this study. When no significant (q < 0.05) DE was identified for a gene in the analysis it is shown as NA. For most of the genes shown in Table et al.55 were not significant when old male tendon was analysed separately from old female tendon. To visualise differences in the expression levels heatmaps were generated from RNA-seq data to compare and contrast the expression levels of genes affected by age in males and females for separate and mixed tendon and TET tissues .TET from young males (yY TET) had different gene expression to TET from young females (yX TET) Fig. . HierarcThe heatmap in Fig. No genes identified as DE using microarrays were also identified as DE using RNA-seq Tables M1 and M2S3Transcripts in females started and ended at different loci, contained miRNAs, lincRNAs and these were transcribed from the reverse strand. The GC content of genes is different because the transcripts are different. Out of 696 transcripts that were DE in old males and females Fig.  148 21.. To inveFor males no significant reactome categories were identified for upregulated genes, whilst genes decreased identified the xenobiotic reactome (q = 0.00217) alone. Significant reactome categories for upregulated genes in old females were mRNA splicing, processing and transport (Table β Protein Precursors (APP) were identified as significant nodes in the networks for genes increased and decreased in expression  was a significant node connected to all genes increased in expression. UBC was increased in expression 6.7 fold in old females (q = 0.0003). In old females genes increased in expression were involved in immune response (TNF Receptor Associated Factor 6 (TRAF6)), growth and transcriptional regulation; Specificity Protein 1 (SP1) and and Early Growth Response 1 (EGR1). Interestingly Cullin Associated and Neddylation Dissociated 1 (CAND1) and Amyloid Figure M2. More siMost of the genes decreased are involved in cell cycle regulation Table . InteresFor males analysis was completed on mixed tendon tissues as well as TET and Achilles tendon separately. Network analysis was completed on genes increased in expression in each analysis, the results are summarised in Table The processes identified in each of the tissues were different, the mixed analysis and TET both identified increased expression of cell cycle regulating genes. Whilst the genes identified in each analysis were different some processes were similar. Chromatin remodelling was identified in mixed tendon analysis and tendon. Response to cellular stress were evidenced by ubiquitination and autophagy in tendon, and response to stress in old male TET. When old male TET was assessed separately genes increased respond to hormones; Serum/Glucocorticoid Regulated Kinase 1 (SGK1), RAN, Member RAS Oncogene Family, Androgen Receptor-Associated Protein 24 (RAN). The functions of genes identified by network analysis of genes decreased in expression are summarised in Table Most of the genes decreased in expression in male tendon tissues were involved in regulating transcription. More processes were identified in tendon than when tendon and TET are mixed. In mixed tendon/TET NR1I3 a transcription factor that regulates cytochromes was decreased. This coincided with increased metabolism, ion binding and catalytic activity Figures M22.Comparative analysis of RNA-seq data identified that 696 genes were significantly (q < 0.05) DE in males and females, but their expression levels changed in opposite directions Fig. . RNA-seqβ3 to initiate differentiation, whereas RNA was directly extracted from Achilles tendon after donation. TGF-β proteins are involved in regulating cell proliferation, differentiation and maturation; high concentrations of TGF-β3 have been observed in mature oocytes of large folicles23. Young female and most old male samples came from TET  library created from a single male donor (RPCI-11). Ten subsequent BAC libraries were created from a mixture male (n = 1) and female (n = 1) DNA which were pooled and Sanger sequenced. Each sequence library was mapped to the genome using the male (RPCI-11) map21. The use of male only DNA to map sequences meant that potential differences in the DNA of males and females could not be identified. In addition the map produced did not contain the second X chromosome from females; the sequences could not be mapped to male DNA, so they were discarded. The methods assumed that the two X chromosomes from females were identical, and that the X chromosome in males was the same as those in females so there was enough X chromosome coverage. Evidence against this assumption is that the Y chromosome in males is clearly not the same as the X chromosome. The human genome project was the benchmark study and all subsequent mammalian genome projects used the same methods. Transcriptomic studies have identified the genes on only one X chromosome are expressed, subsequently theories have arisen that female mammals are mosaics with patches of tissue expressing either the paternally or maternally derived X chromosome19. However one considers that females may express the genes on both X chromosomes in all tissues; but we can only measure the expression of genes we know about and can map back to reference genomes. Inability to align transcripts from the second female X chromosome is a current limitation of all mammalian transcriptomic analyses, and all technologies based on reference genomes. Additionally a high degree of variation in X chromosomes observed in experimental data sets could be attributed to the assumption the male X chromosome was the same as both female X chromosomes. Whereas experimentally observed increased variance in the Y chromosome could be due to reduction in the number of samples used, n = 10 versus n = 20 for the rest of the genome. This study shows that females are transcriptionally different, in terms of the genes DE as well as the sequences and sizes of the transcripts. An increase in average transcript size alongside a significant reduction in the total number of transcripts identified using Method Two  together with gene transcripts in RNA-seq analyses would improve our understanding of transcription and translation? These results also raise questions about whether genome alignments of RNA-seq data reliably identify isoforms given the assumptions and subsequent limitations of reference genomes, annotated transcript files, short read sequencers and aligners? This study identified transcripts transcribed from the reverse strand, however the direction of transcription cannot be determined from the data or existing technologies. What impact does our assumption of direction have on measured expression levels? And if transcripts are being transcribed from alternate loci backwards from the reverse strand to include small RNAs, does this fit with the triplet code theory of translation?Analysis of RNA-seq data generated from TET was extended to include RNA-seq and microarray data from young and old tendon providing more samples for each biologically defined group , to compensate for a gender imbalance in each of the separate experiments. The work is subject to limitations namely; combining experimental data sets is problematic due to batch effects. A batch effect cannot be reliably determined due to the differences in the biological compositions of each experiment Table  which coET Table  that hadr Tables  and M2S4es Table , and Tabes Table  and 2, aes Table  would exes Table . These des Table , and thees Table  and 2. Nnor RPCI-1. Ten sur Tables . Method r Tables , leading24. Separating samples by known biological differences (age and gender) aimed to decrease overall variance and further increase statistical power. Separating samples by sex changed the data distribution from Poisson to Negative Binomial , reduced overall variance, potentially improving the accuracy and reproducibility of results. On these basis should males and females be analysed separately in all analyses?The utility of transcriptomic results and ease at which they can be interpreted depend on the experimental design, confounding factors, data analysis decisions, assumptions, the accuracy of technologies and tools, as well as statistical methods. The calculation of significance relies on underlying assumptions made about the probability distributions of transcript measurements as well as accurate measurement of mean counts and variance per geneial Fig. , an obse32; therefore RNA extracted from rapidly dividing cells represents a pooled sample of RNA with high variability. Higher variance observed in old male cells  have been implicated in activation of the p38MAPK pathway, regulation of energy metabolism, and thermoregulation37. Ageing leads to increased circulating leptin in males which has been associated with decreased testosterone concentrations and increased BMI. Leptins such as LEP are involved in lipid metabolism38, and are also regulators of immune and inflammatory responses, nutrient uptake, insulin secretion, and MMP expression  and NFκB were decreased, whilst genes involved in the production of cytokines, the cytokine receptor , and JAK-STAT pathway were increased  gene expression48. HSP90 was increased in old females using RNA-seq, and was identified as a significant node in network topology  higher methylation than males53. Contrary to this Horvath et al54. reported that males have significantly higher methylation than females, and that ethnicity also impacts on methylation. Age related changes in DNA methylation could alter transcriptional start sites as observed in this study. Decreased expression of histone de-acetylases in old female TET  and females (n = 3)  as well as two and a half fold in old male mixed tendon tissues. Assessing TET and Achilles tendon separately CRABP2 was not significantly (q < 0.05) DE; however it was decreased four fold and five fold respectively. In old female tendon CRABP2 was also identified as significantly (q < 0.05) and three fold decreased in expression using Method One and four fold using Method Two. Similar results were observed for MMP3. It was increased in old age in the study by Peffers et al.55, and also increased in old male tendon and in old female tendon in this study. Few other results from this study were in agreement with the study by Peffers et al.55. Dramatic differences and sometimes a change in direction of expression are seen when samples are separated by gender prior to analysis  the generation of male and female specific reference genomes would facilitate more accurate assessment of gene expression so sequences could be more accurately aligned and transcriptome assemblies improved.RNA-seq data from Achilles tendon E-MTAB-2449) has previously been analysed3) Table . CRABP2 49 has pr59. It may be the case that females who have higher body fat percentages oxidise lipids to deal with oxidative stress, whereas males who have lower body fat produce proteins to deal with oxidative stress. Oxidative stress in males and females may not differ but rather the methods used to measure them (oxidative stress proteins) have led to this conclusion. However high metabolic and lipid synthesis rates are known to generate high ROS that may underpin higher oxidative stress in males.The results of this study show that ageing affects cell cycle, oxidative stress, immune signalling and gene expression differently in males and females. Documented differences between males and females including the presence of different isoforms are supported by cross species studies. Males and females differ in body compositions, fat mass, FFM, genetics, metabolic rates, oxidative stress levels, hormone profiles, longevity and the propensity to develop degenerative conditions. Females have greater longevity which has been correlated with reduced oxidative stress, different oxidative stress bio-markers and hormone profiles62, however increased lipid synthesis is both a precursor and requirement for cell division.A reduction in the steroid bio-synthesis pathway in old females, alongside differences in retinol and lipid metabolism are coupled with a reduction in the cell cycle. Lipids determine whether cells have the ability to proliferate  or synthesise hormones, MHCs and vitamin D because lipids are precursors for these molecules. Elevated lipid synthesis is thought to be a hallmark of cancers63. In old female TET genes are transcribed from different start sites and many are identified as isoforms, genes from TET could have different transcriptional start sites to tendon, ageing could alter transcriptional start sites, or genes in females could have different transcriptional start sites. Consistency in RNA-seq and microarray studies is limited; differing GC content of transcripts, high numbers of isoforms, alternate splicing, different transcriptional start sites and promoters all act to reduce the sensitivity of microarrays, an effect that is compounded by data processing techniques. This study goes some way to meeting the aims of the three Rs; identifying these compounding factors means in future we can better design studies to avoid confusion and experimental repeats to address anomalies. Taking gender into account is hampered by the lack of reporting in public repositories such as Array Express where gender and age are often not reported. A large number of tendon based gene expression studies were excluded from this study because essential information such as age and gender were not recorded. We would like to see age and gender included in Minimum Information standards such as MIAME which would help overcome current limitations. Refining and grouping samples by biological attributes can improve data distribution calculations greatly increasing statistical power and thus obtain significant results when the number of replicates is low. Our study highlights just some of the factors that need to be considered in the design and analysis of omics studies. Our study identifies a clear requirement for the biology community to conduct well planned gender balanced studies and analyse data generated from males and females separately.This study highlights the fundamental importance of gender in large scale studies such as this. Indeed gender may be an overlooked factor that could help account for controversial data, regarding the levels and impacts of genes and proteins in the pathways identified64, sense strand RNA libraries were prepared and sequenced as described in65 and66. Studies for incorporation in the analysis were identified by filtering by organism (Homo sapiens), experiment type (RNA assay) and constructing search queries in array express (Table The research aimed to investigate the effects of ageing on the transcription of genes in tendon tissues. TET samples were differentiated as described inss Table . For comss Table .55. Technologies used and available replicates for each age and gender group for each technology are shown in Table Summary data for RNA-seq samples from TET (E-MTAB-4879), tendon (E-MTAB-2449), and their associated attributes are shown in Tables M1More young males were assayed in the microarray experiment (Affymetrix) than the RNA-seq experiments (Illumina). Only young TET and old tendon samples were available for females.Two methods were applied to RNA-seq data, the first (Method One) assessed age and gender related differences in gene expression in the same analysis using a merged transcript file generated by merging male and female transcripts. The second (Method Two) aimed to identify sex specific differences in transcripts by analysing males and females in separate pipelines with sex specific merged transcript files Fig. .Figure 767 with the very sensitive setting unpaired reads were excluded (bowtie2 –very-sensitive –no-mixed -x hg19*). SAM files were converted to sorted BAM files using SAMtools68 and insert sizes, mean inner distance, and standard deviation per sample was estimated using Picard tools (BroadInstitute 2014). Fastq files were aligned with the hg19 genome build using -b2-sensitive settings in Tophat69 parameterised using descriptive statistics to produce tophat aligned BAM files. Mapped reads were assembled into transcript files per sample using Cufflinks70. Male and female transcript files were merged using CuffMerge to create a merged transcripts file. Phenotypic data; age group and gender , old male, old female (>54) was used to assign samples to groups. FPKM normalised data was significance tested using the cross replicate pooled condition dispersion method in CuffDiff. CuffDiff was completed on male and female data sets combined  plots and PCA plots  and 1.5 fold increase or decrease in expression  male, including adapter regions, and assessing differential expression in males and females simultaneously was controlled for by re-analysing male and female data sets in completely separate pipelines Fig. , 10 nuclFigure M2. To asce Table M2. A matri275 Fig. . Old fem year old275 Fig. .76 ensembl hg19 libraries from chromosome, transcriptional start sites and transcript end sites. Potential differences in sequence properties were probed by determining the percentage GC content of transcripts from males and females using the GC function of the seqinr package77. The percentage differences in GC content was determined by subtracting female GC content from male GC content , Robust Multi-array Analysis (RMA), Variance Stabilising Normalisation with Robust Multi-array Analysis (VSN-RMA), Guanine-Cytosine affinity correction with Robust Multi-array Analysis (GC-RMA), and MicroArray Suite 5 (MAS5) Table . RMA nor2 transformed. Limma79 was used to assign samples to groups based on phenotypic data , old = 60 and over), gender, and disease state. Phenotypic data was used to exclude diseased tendon: Only samples from healthy tendon in young and old participants were compared. Contrasts were created in Limma, fit to a linear model and standard error smoothed using empirical Bayes for males and females to identify genes that were significantly (q < 0.05) and 1.5 fold increased and decreased in expression in old age  from E-GEOD-26051, the data was log Table M1. To testFor both Methods One and Two gene symbols for each of the conditions were written out from the R console and intersecting genes for possible comparisons identified using grep –Fx in command line Tables M1 and M2S380. Significantly (q < 0.05) affected Gene Ontology categories were reduced for visualisation using REVIGO81. Scatterplots and TreeMaps were selected to visualise GO categories  categories are summarised in Tables M1Gene lists were written out from the R console for each tissue type, condition, technology (microarray and RNA-seq) and method Fig. . UnrankeSupplementary File


Cellular signaling controls an organism's molecular milieu in two ways—by facilitating internal growth and development, as well as responding to external stimuli, which includes response to environmental stress and drug effects. Signaling networks control the information flow at molecular level in a robust manner despite some inherent noise, tightly controlling the molecular determinants of homeostatic balance. Several drug candidates are under trial for neurodegenerative disorders for which molecular mechanism is not known in detail. Most drugs act on more targets (including off-targets) than previously thought. Studying the mechanisms of drug action is thus important not only for understanding biology, but also for design of more potent therapeutic molecules. If the molecular underpinnings are adequately understood, those can be easily tinkered with without causing toxicity or adverse effects. Exploration of mechanisms of drug action by studying drug-induced signaling perturbations using quantitative proteomics is gaining momentum  and heavy (Aβ25−35 + GFKP-19) on Q-Exactive (QE) and Q-Exactive HF (HF) mass spectrometers. Specific phosphorylation changes were captured with ~25,000 phosphorylation sites of which ~18,000 have high localization probability. The important regulatory perturbations in phosphoproteome studies at 4 and 24-h in each condition were captured and as expected, the authors found that the 4-h time period shows more regulation of the phosphoproteome than 24-h, since the signaling changes in phosphoproteins will be driving the information flow in early time period. Regulated phosphosites between control vs. Aβ-treatment and drug vs. Aβ were observed to control cytoskeletal protein functions. Authors also found Tau phosphorylations, which are known causative agent of aggregation in AD. Proline directed kinase (PDK) motifs were found in motif analysis along with basophilic motifs in both Aβ treatment and the drug rescue conditions. Oxidative damage due to aggregation is caused by superoxide radicals binding to NO which can be formed by nitric oxide synthases . Aβ induces phosphorylation of NOS1 at S847 which is reversed by GFKP-19 bringing down oxidative damage. Another site S479 of ASPP2 increased with Aβ treatment was rescued by the drug but the functional aspect of this site is unknown. Six sites in Tau protein were upregulated out of 20, which had known counterparts in humans and the drug reversed the effect in all 6 sites. From the interaction network, authors postulated that phosphorylation of MARK2 and MAPK14 may be involved in AD based on several phosphosites although many previously known sites were not observed. For more depth in understanding, profiling of these molecular changes in phosphoproteome at a finely-resolved temporal level will be interesting, as literature has shown phosphoproteome level regulation starts much earlier than studied here. This may require a multiplexed quantitative proteomics technique like hyperplexing combining SILAC and iTRAQ , Ministry of Science and Technology, India.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Macaca fuscata (Japanese macaque). In prior studies we have demonstrated that a high fat, caloric dense maternal diet structures the offspring’s epigenome, metabolome, and intestinal microbiome. During the course of this work we have consistently observed that a 36% fat diet leads to obesity in the majority, but not all, of exposed dams. In the current study, we sought to identify the genomic loci rendering resistance to obesity despite chronic consumption of a high fat diet in macaque dams. Through extensive phenotyping together with exon capture array and targeted resequencing, we identified three novel single nucleotide polymorphisms (SNPs), two in apolipoprotein B (APOB) and one in phospholipase A2 (PLA2G4A) that significantly associated with persistent weight stability and insulin sensitivity in lean macaques. By application of explicit orthogonal modeling (NOIA), we estimated the polygenic and interactive nature of these loci against multiple metabolic traits and their measures  which collectively render an obesity resistant phenotype in our adult female dams.Maternal obesity contributes to an increased risk of lifelong morbidity and mortality for both the mother and her offspring. In order to better understand the molecular mechanisms underlying these risks, we previously established and extensively characterized a primate model in  In the last several decades, a global epidemic of increasing rates of obesity in humans has been well described but relatively poorly understood at a genomic leveli.e., diet, exercise, early life exposures, reproductive life-stage, sex, and co-morbid metabolic conditions), identifying clearly defined obese susceptible and resistant genomic variants in humans is exceedingly challenging since it necessitates enormous subject cohorts in ancestrally diverse populations with reliable linked exposure data for fine-mapping of loci.Given such relative rarity  of obese susceptibility variants in the general population, but persistent evidence for heritability16Macaca fuscata (Japanese macaque)1819201819222324252618232627293032de novo SNPs of interest for subsequent validation in an inclusive larger cohort.An alternative to human meta-analyses of GWAS data are strong phenotype-genotype studies in relevant non-human primate models. To this end, we have spent nearly a decade establishing and characterizing the effect of obesity and chronic high fat dietary exposure on adult female dams and their offspring in Macaca fuscata) model20212223242526272829303132Macaca fuscata gene assembly, and subsequent concern for misclassification of whole genome sequencing data which would be inherent to mapping onto a moderate (6–12X) resolution Macaca mulatta rhesus assembly. Genes were selected for inclusion on the array based on a role in obesity, hyperlipidemia, insulin resistance, or lipid metabolism (such as those for cholesterol and triglyceride metabolism). Since the Macaca fuscata genome has not been sequenced, we used the currently available primate genome assemblies, with an emphasis on the rhesus macaque (M. mulatta) genome which diverged from M. fuscata 0.31 to 0.88 million years agoM. fuscata breeding group is a grand mean of 0.01802 .To identify functional and potentially novel SNPs associated with sensitivity or resistance to the development of obesity with high fat diet consumption present in our well characterized Japanese macaque  or sensitive (n = 4) based on mean % bodyweight gain , leptin/body weight ratio , and insulin AUC . Genomic DNA was extracted, hybridized to the array, and sequenced using the 454 FLX Titanium platform. SNPs of potential further interest for validation were first called based on an odds ratio approximating infinity . These criteria were sequentially relaxed to allow for 3 of 4 and 2 of 4 in one cohort, but still absent in the comparison cohort  which only identifies homozygous alternative allele SNPs. Genes were identified for further analysis on Atlas-SNP2 and SNPTools if ssahaSNP made homozygous alternative allele calls in all the samples in one group, but none of the samples in the other group (odds ratio approximating infinity). Among the 1534 SNPs called by all three SNP calling tools, Variant Effect Predictor (VEP)p value < 0.063 in our small discovery cohort) were chosen for further analysis. A SNP in phospholipase A2, group IVA  (PLA2G4A) (p = 0.012) (APOB) (p = 0.061 and p = 0.062)   and two = 0.062)  met thesPLA2G4A and APOB SNPs were further interrogated by two means: functional annotation and validation in an expansive cohort. Functional annotation used a Combined Annotation Dependent Depletion (CADD)PLA2G4A SNP had the highest PHRED scaled C-score (23.6). A PHRED score of ≥20 indicates the SNP is among the 1% of SNPs in the human genome most likely to have a functional effect. The PHRED scores for the APOB chr13:20932165 (9.018) and chr13:20940049 (15.07) approach or surpass a PHRED score ≥10 which indicates they are predicted to be among the 10% most likely SNPS to have a functional effect. Examination of individual constituents of the CADD scores showed that the PLA2G4A and APOB chr2:21235409 loci are highly conserved across primates, including humans.The i.e., exploration of potential mechanisms rendering an association with obesity resistance in our cohort of strictly experimentally defined animals , we took a dual approach. First, we completed expanded phenotyping among a total of 71 animals, inclusive of 43 adult female dams who had been placed on the HFD for at least 3 years and subjected to expansive phenotypic testing and measured analysis . Second, the PLA2G4A and APOB SNPs were assayed by PCR based genotyping in an extended panel among all 43 adult female dams on the HFD for at least 3 years with extensive trait-correlated and trait-independent phenotypic data , age starting diet  nor age at first pregnancy after starting diet , nor initial baseline metabolic phenotyping (p = 0.02).At the time of initial allocation onto the HFD, adult animals subsequently classified as obese resistant and sensitive did not significantly differ by virtue of number of prior pregnancies  association between the classification and the PLA2G4A SNP. PLINK quantitative trait association analysis showed significant (p < 0.05) associations of both APOB SNPs with insulin and glucose AUC after year 3 on the HFD  models across 15 phenotypes enotypes . Of the n = 43 animals). The Genotype  shows the genotypes for each of the loci . Significance of association is annotated by boxing, with the genotypes and allelic variation predicted to associate with the phenotype in a significant manner being outlined with colored boxes. The Genotypic Effects (y-axis) shows the NOIA predicted effect of the genotype on a phenotype, with the value being specific to the phenotype. For example, in panel APOB.1 is demonstrated to be significant in an additive model with a p = 0.035. In contrast, neither APOB.2 nor PLA2G4A demonstrated a significant effect on weight change (one phenotypic characteristic which renders of fails to render obesity). In fact, when examining all six other phenotypic characteristics projected in APOB.1 locus demonstrated an additive effect on weight change percent , we estimated the polygenic and interactive nature of these loci against multiple traits which collectively render an obesity resistant phenotype in our adult female dams.We applied comparative principles and designed an exon capture array of conserved metabolism genes for use in Japanese macaque, and demonstrated the capacity of this technology to identify functional SNPs related to insulin sensitivity and resistance to obesity in a relevant primate model of chronic high fat diet exposure. We discovered that although body weight and body composition traits are quantitative, two loci in Our approach towards identifying obesity resistant loci in adult primates has significant advantages and provides clarity over previous human GWAS analysis seeking to identify susceptibility loci. Recent meta-analyses2212We have overcome these inherent limitations to human GWAS analysis in our well-characterized primate model in three manners. First, we challenged all animals in our analysis to a high fat diet and normalized our trait measures to reproductive life-stage, time of exposure to the diet, and baseline characteristics at the time of initial diet allocation. Second, we estimated association with 37 different trait loci which have both independent and dependent predictive capacity and estimated their interaction. This second manner enabled us to further identify significant associations with multiple additional traits that accompany or lend to the obesity resistant phenotype in an extended panel of all 43 adult female dams on the HFD for at least 3 years with extensive phenotype data. Third, we were thus able to apply multiple previously validated means for fine-mapping of polygenic and interactive loci.APOB C/T SNP at chr13:20932165 coding for glycine or aspartic acid is of particular interest because it is also present in humans as SNP rs142828185. Although little information is presently available regarding the SNP with no minor allele frequency or phenotypic association reported in dbSNP, much is known about the role of APOB as a primary apolipoprotein of LDLs45APOBFrom a translational perspective, the APOB C/T SNP at chr13:20932165 coding for glycine or aspartic acid was associated with multiple traits in addition to levels of serum LDL, the likelihood that these and potentially other variants in humans would culminate in up to one third of adult females being resistant to high fat diet induced obesity is both novel and of particular interest. Such pleiotropy would support a model of gene-by-food environment interactions, whereby the majority of a population cohort are susceptible to HFD with resultant insulin resistance and obesity. To this end, and of particular interest to our study, common coding variants in APOB have recently been suggested to play a role in maternally-derived obesity in young adults. Specifically, Hochner et al. recently demonstrated that a common coding variant in the 4th exon of APOB (rs1367117) demonstrated a significant maternally-derived effect on BMI  and waste circumference p > 0.6). Moreover, these investigators working with 1250 young adults and their parents were able to demonstrate a dominant maternal parent-of-origins effect, suggestive of maternally-derived associations of rs1367117 with elevated fasting glucose  and insulin APOB rs1469513 on obesity-rendering traits, alongside the interaction of APOB rs1469513 and dietary intake on these same traitsp 0.001) and low-density lipoprotein cholesterol (p 0.010), body weight (p 0.048), and body mass index (p 0.029) were significantly different in carriers of the A allele and minor G allele of APOB rs1469513. Among individuals whose fat intake was above the median of the study cohort, the difference for the body mass index across genotypes was 1.14%  and carriers of the minor G allele had increased odds of being obese  compared with homozygotes for the A alleleAPOB gene demonstrating an alternate risk of modifying risk of obesity resistance. What is notable is the concomitant impact of both presumptive maternal parent of origin effect, as well as modifier of dietary impact, in our primate cohort. Taken together, our findings alongside the current collective literature suggests that APOB is a primary determinant of high fat diet induced obesity, and may render multigenerational impact through a maternal parent of origin effect.Because we found that the PLA2G4A is of additional translational interest, although less is known regarding variants in the human population. The PLA2G4A gene encodes a key calcium activated enzyme which catalyzes the hydrolysis of membrane phospholipids to release arachidonic acid, rendering eicosanoids (prostaglandins and leukotrienes) and lysophospholipidsPLA2G4A on plasma triglyceride levels in 208 human subjects, genotype by supplementation interaction effects were observed for 4 SNPs. Specifically, the rs10752979, rs10737277, rs7540602, and rs3820185 in PLA2G4A withstood MIXED procedure testing adjusting for age, sex, BMI and energy intake. NOIA generated four models showing an association between PLA2G4A genotype and triglyceride levels including two models in which PLA2G4A was dominant (APOB) and central enzymes for mediating eicosanoid-driven inflammation (PLA2G4A) modulate obesity-resistant traits in response to dietary challenge or supplementationdominant . Our finAPOB in humans may render susceptibility to obesity in first generation young adult offspringEqually intriguing are these current findings in context with our prior demonstrations that generally regardless of maternal insulin resistance and obesity status, there is a notable impact of high fat diet feeding during gestation and lactation among offspring. The impact of early in life high fat diet exposure are noteworthy and include non-alcoholic fatty liver disease (NAFLD) with lipid accumulation, pancreatic and immune modulatory dysfunction, thyroid hormone dysregulation, hypertension, and alterations in sirtuins and their regulated pathways1827505130192425The loci identified here as significant represent an experimentally robust, in-depth, fine-mapped genotype-phenotype association analysis in a highly relevant and well-characterized primate model. Future application of our findings into human cohorts are likely to yield important insights into the molecular and physiologic mechanisms leading to obesity and insulin resistance in not only the current generation, but in the generations to come.A total of 783 lipid metabolism, obesity, and fatty acid related genes were selected as targets . Human, Experimental design: The use of M. fuscata by our consortium of investigators has been previously described242526272829303132rd trimester of pregnancy or post lactation/pre-gestation. The area under the curve (AUC) for glucose and insulin were calculated from zero values. Body composition analysis (DXA) was performed in year 3 of diet exposure in the non-pregnant state, and lean and fat mass were calculated with standard measures has been previously described242526272829303132242526272829303132All animal protocol work is approved by and in accordance with the relevant guidelines and regulations as stated by the institutional animal care and use committees (IACUC) at both Baylor College of Medicine (protocol number AN-4752) and the Oregon National Primate Research Center (ONPRC). The full extended trait panel is shown in 20212223242526272829303132i.e., present in all 4 dams of one group, and absent in all of the other) as estimated by ssahaSNP, which only identifies homozygous alternative allele SNPs. In order to further assure high quality and statistically robust SNP identification in an initial small discovery cohort of 8 animals, three tools were used to call SNPs APOB and one PLA2G4A SNPs in association with each of the 37 phenotype measurements with significance defined by probability (p < 0.05) models across 15 phenotypes.Our initial SNP calls were based on infinite odds ratios .Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


C) genotype is a major determinant for the susceptibility to prion diseases. The Q/K222-PrPC polymorphic variant provides goats and mice with high resistance against classical scrapie and bovine spongiform encephalopathy (BSE); yet its effect against atypical scrapie is unknown. Here, transgenic mice expressing the goat wild-type (wt) or the K222-PrPC variant were intracerebrally inoculated with several natural cases of atypical scrapie from sheep and goat and their susceptibility to the prion disease was determined. Goat wt and K222-PrPC transgenic mice were 100% susceptible to all the atypical scrapie isolates, showing similar survival times and almost identical disease phenotypes. The capacity of the K222-PrPC variant to replicate specifically the atypical scrapie strain as efficiently as the goat wt PrPC, but not the classical scrapie or cattle-BSE as previously reported, further suggests the involvement of concrete areas of the host PrPC in the strain-dependent replication of prions.Host prion (PrP C) into a pathological misfolded form (PrPSc). Scrapie occurs in a variety of phenotypes within two forms—classical and atypical scrapie forms—which differ in their incubation periods, clinical signs, neuropathological lesion profiles and/or PrPSc biochemical properties. The zoonotic potential of classical scrapie has been recently proposed from transmission studies of a panel of classical scrapie isolates in non-human primates [Scrapie is a fatal neurodegenerative disease of sheep and goats caused by the conversion of the host cellular prion protein  and the prion strain. Strategies to promote breeding for the Prnp allele linked to classical scrapie resistance, A136R154R171, in sheep herds were implemented in some European countries and in the USA, resulting in rapid decline of classical scrapie outbreaks [136R154R171 genotype does not provide resistance towards atypical scrapie [Susceptibility of sheep and goats to scrapie is strongly determined by the PrP222-PrPC variant to a wide variety of classical scrapie isolates using transgenic (Tg) mice [222-PrPC variant as a good candidate for developing selective breeding programs in goat herds. These studies are very valuable to control the spread of prion diseases in animals, but also provide crucial information about the role of the host genotype in the prion pathobiology. In the present study, we analyze the role of K222-PrPC variant on the resistance/susceptibility of goats to atypical scrapie using goat-PrP Tg mice.We have previously demonstrated the high resistance of the goat KTg) mice . These rTg) mice  and we tAnimal experiments were carried out in strict accordance with the recommendations of the Code for Methods and Welfare Considerations in Behavioral Research with Animals (Directive 86/609EC) and approved by the Committee on the Ethics of Animal Experiments (CEEA) of the Spanish Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA); Permit Number: CEEA2011/050.C (Q222-Tg501) or the K222-PrPC variant (K222-Tg516) at two fold the PrPC levels in the goat brain [res) by Western blot. Survival time was calculated as the mean number of survival dpi for all the mice positive for PrPres in the brain, with the standard error included, while attack rate was expressed as the proportion of PrPres-positive mice among the mice inoculated.Groups of 5–6 Tg mice (6–7 weeks old) expressing either the goat wild type (wt) PrPQ222-Tg50 or the Kres in transgenic mouse brains, 100 µL of 10% brain homogenate were analyzed by Western blotting as previously described [93WGQGG97 of the sheep PrP sequence) at a final concentration of 1 μg/mL. Immunocomplexes were detected with horseradish peroxidase-conjugated anti-mouse IgG (Amersham Pharmacia Biotech) after incubating the membranes for 1 h, and blots were developed with chemiluminescent substrate ECL Select . Images were captured using ChemiDoc XRS + System and then processed using Image Lab 5.2.1 Software.Brain tissue was homogenized in 5% glucose in distilled water in grinding tubes (Bio-Rad) and adjusted to 10% (w/v) by using a TeSeETM Precess 48TM homogenizer (Bio-Rad) following the manufacturer’s instructions. To determine the presence of PrPescribed  with somSc accumulation, tissue sections were subjected to antigen retrieval and quenching of hydrogen peroxide, as described previously [240SPPVILLISFLIFLI254 epitope of the sheep PrP sequence); the subsequent steps of the IHC procedure were performed by a commercial immunoperoxidase technique  as per manufacturer’s instructions and sections were finally counterstained with Mayer’s haematoxylin. The PrPSc types considered included the intraneuronal (ITNR), intraglial , stellate (STEL), fine particulate (PART), coalescing (COAL), linear (LINR) and plaques  as described elsewhere [Sc were termed “coalescing”, without prejudice to them actually corresponding to primitive plaques.Formalin-fixed brains were trimmed, dehydrated, embedded in paraffin-wax, cut to 4 µm thickness, de-waxed and rehydrated by standard procedures. For IHC demonstration of PrPeviously  and inculsewhere . PlaquesC (Q222-Tg501) and the K222-PrPC variant (K222-Tg516) were intracerebrally challenged with 3 natural cases of atypical scrapie  and poor pathology in brain. These long survival times are consistent with the old age at which sheep and goats normally develop atypical scrapie either naturally (over 5 years of age) [C species context. In line with this view, mice overexpressing 8- to 10-fold the sheep PrPC in their brains succumbed to the intracerebral inoculation of multiple French atypical scrapie isolates only after more than 400 dpi [222-Tg501 mice (unpublished data).Intracerebral transmission of atypical scrapie in both Q of age)  or after of age)  and sugg 400 dpi . However222-Tg501 and K222-Tg516 mice consistently revealed a mild accumulation of PrPSc restricted to the cerebellum with little or no vacuolation also limited to this brain area. These outcomes clearly contrast with the widespread PrPSc and intense vacuolation observed in classical scrapie infected Q222-Tg501 mice or in BSE infected K222-Tg516 mice [Sc deposition in the cerebellum of sheep and goats with natural atypical scrapie [res glycoprofiles of all the atypical scrapie isolates were also maintained in both Q222-Tg501 and K222-Tg516 mouse lines which, together with the survival times and the histological outcomes, further demonstrates the validity of our animal models to characterize prion strains of sheep and goats.The histological and immunohistochemical examinations of the brains from all the atypical scrapie infected Q scrapie . The PrPC and PrPSc amino acid sequence [C amino acid sequences may have greater “plasticity” or ability to misfold—as proposed for the unique susceptibility of bank voles to a wide variety of prion diseases [C and preventing its conversion by different prion strains. Nonetheless, the plasticity of the host PrPC would not explain why certain amino acid substitutions inhibit the replication of some prion strains but not others. A clear example is the goat K222 variant which provides high resistance against classical scrapie and bovine spongiform encephalopathy (BSE) from cattle—being protective even in heterozygous mice and goats [C in replicating sheep and goat-BSE [222 variant to classical scrapie was associated to the additional positive charge at codon 222 provided by the lysine amino acid, which could interfere with the PrPC:PrPSc interaction, abolishing or lowering the conversion rates of PrPC [C surface charge distribution and structural rearrangements mainly localized at the β2–α2 loop region (residues 169–179 in goat PrPC numbering) are likely to underlie the resistance of the human E/K219 variant against CJD [Susceptibility to prions and disease phenotypes are likely modulated by conformational properties of prion strains and the PrPsequence . Some hodiseases  and to “diseases —while otnd goats , 6, 9—bugoat-BSE  and atyp of PrPC . SimilarC–PrPSc interaction sites during the templating of PrPC by different prions was proposed [C areas in the strain-dependent replication of prions could account for the variable role of the K222-PrPC variant in the susceptibility to scrapie. While for classical scrapie polymorphic variants along the PrPC have been associated to modulate the susceptibility to the disease, for atypical scrapie only few have been reported—A/V136, F/L141, R/H154 and Q/R171 [C and therefore any amino acid exchange outside this segment would not affect the capacity of replication of the atypical scrapie, as observed in our transmission study in goat wt and K222-PrPC mice. In fact this area seems to be accessible in the abnormally folded aggregate of the atypical scrapie agent as suggested by the observation that the C-terminal part of atypical scrapie PrPSc can be specifically trimmed by PK [C areas in the strain-dependent replication of prions. Thus, strategies to fight prion diseases based on genotype breeding programs should be prion strain targeted.More recently, the existence of critical initial PrPproposed . The invd Q/R171 — that, ied by PK . In conc


Reliable exon recognition is key to the splicing of pre-mRNAs into mature mRNAs. TDP-43 is an RNA-binding protein whose nuclear loss and cytoplasmic aggregation are a hallmark pathology in amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD). TDP-43 depletion causes the aberrant inclusion of cryptic exons into a range of transcripts, but their extent, relevance to disease pathogenesis and whether they are caused by other RNA-binding proteins implicated in ALS/FTD are unknown.We developed an analysis pipeline to discover and quantify cryptic exon inclusion and applied it to publicly available human and murine RNA-sequencing data.We detected widespread cryptic splicing in TDP-43 depletion datasets but almost none in another ALS/FTD-linked protein FUS. Sequence motif and iCLIP analysis of cryptic exons demonstrated that they are bound by TDP-43. Unlike the cryptic exons seen in hnRNP C depletion, those repressed by TDP-43 cannot be linked to transposable elements. Cryptic exons are poorly conserved and inclusion overwhelmingly leads to nonsense-mediated decay of the host transcript, with reduced transcript levels observed in differential expression analysis. RNA-protein interaction data on 73 different RNA-binding proteins showed that, in addition to TDP-43, 7 specifically bind TDP-43 linked cryptic exons. This suggests that TDP-43 competes with other splicing factors for binding to cryptic exons and can repress cryptic exon inclusion.Our quantitative analysis pipeline confirms the presence of cryptic exons during the depletion of TDP-43 but not FUS providing new insight into to RNA-processing dysfunction as a cause or consequence in ALS/FTD.The online version of this article (doi:10.1186/s12920-017-0274-1) contains supplementary material, which is available to authorized users. Splicing depends on the reliable recognition and subsequent removal of non-coding intronic sequence by the multi-protein spliceosome complex. Boundaries that demarcate exons from introns are first recognised by the binding of the U1 small nuclear RNA (snRNA) to the 5′ splice site at the beginning of the intron and the U2 snRNA binding to the polypyrimidine tract and 3′ splice site at the end of the intron. The two snRNAs then interact with each other and the intronic sequence is removed via a series of transesterification reactions [Due to the long length and reduced evolutionary conservation of intronic sequences, pairs of 3′ and 5′ splice sites can emerge randomly to create potentially new exons. These cryptic exons  arise due to mutations that create new splice sites or remove the existing binding sites for splicing repressors. These type of mutations have also been implicated in a number of genetic diseases –5. IncluCryptic exons can also emerge from transposable elements. One such example are Alu elements, the predominant transposable element in primates which are often found within introns in the antisense direction . The conTARDBP gene. Loss of TDP-43 from the nucleus accompanied by TDP-43 positive inclusions in the cytoplasm of cortical and spinal cord neurons is the hallmark pathology of amyotrophic lateral sclerosis (ALS) as well as the majority of cases of frontotemporal dementia (FTD) [TARDBP can cause familial ALS [TDP-43 is an RNA-binding protein encoded by the ia (FTD) . In addilial ALS . These fCFTR gene by binding to long UG-rich sequences [Rare ALS-causing mutations have been found in another RNA-binding protein, FUS  further equences  and subsequences –19. TDP-equences . Transcrequences –24. Of pequences , 23.Recently, Ling and colleagues observed the inclusion of cryptic exons when TDP-43 was depleted in HeLa or mouse embryonic stem cells . These chttp://icount.biolab.si/). Both the human and mouse TDP-43 iCLIP data have been previously published [Table ublished , 28.TablProcessed eCLIP data (previously described by ) was dowSplicing aware alignment software such as STAR cut short reads that originate from a spliced transcript and align the pieces separately, marking the distance between them as a splice junction. Splice junctions can be used to reaffirm known splicing patterns or infer novel splicing. We define cryptic splicing as the emergence or relative increase in splice junctions that splice from known splice sites to unannotated positions within introns. This increase correlates with the depletion of a particular RNA binding protein. Different repositories have different levels of proof for annotating exons but we define an annotated exon as one listed in the Ensembl list of transcripts (release 82).Due to the diversity in the quality of published RNA-seq data, the cryptic splicing discovery pipeline was designed to be used on any RNA-seq library, whether single or paired end, stranded or unstranded, total RNA or polyA-selected RNA. However, when high quality RNA-seq data is available (paired end reads >100bp sequenced with >30M reads per sample), we instead suggest using one of the several recently released tools that can identify and classify unannotated splice junctions such as JunctionSeq , MAJIQ  or SGSeqThe inherent flexibility of our pipeline results in a large number of false positive hits which have to be aggressively filtered downstream. The initial cryptic exon discovery pipeline was written in Bash, using SAMTools (version 1.2)  and BEDTIn order to discover all possible splice junctions that travel into the intron we first extracted all spliced reads from each aligned bam file using SAMTools, filtering out any secondary alignments. To extract only the spliced reads that overlap an annotated exon we then performed an intersection in BEDTools with a flattened list of exons, created using the dexseq prepare annotation.py Python script included with the DEXSeq package . An inveP-value  < 5% and a | log2(fold change)| > 0.6 were extracted from the DEXSeq results table  were previously generated by the RepeatMasker tool  and werePhyloP compares the sequence alignments of multiple species to produce per base conservation scores . AverageFor each sample the number of reads overlapping each gene were counted using HTSeq using the same Ensembl gene models as before. Differentially expressed genes were identified using DESeq2  at a falAny cryptic exon which did not fall within the coding sequence of a transcript was omitted. Splice junctions generated by STAR were used to determine the upstream and downstream exons adjacent to each cryptic exon. Only cryptic exons that had both upstream and downstream splice junctions (cassette exons) were kept. The upstream and downstream exons were matched to their corresponding annotated exon in the Ensembl transcript file for each species to assign the correct reading frame for translation. Nucleotide sequences for transcripts either including or excluding the central cryptic exon were created and translated in silico using the R Biostrings package. Premature termination codons (PTCs) were identified from the translated sequence and defined as escaping nonsense mediated decay (NMD) if they occurred within 50 nucleotides of the downstream exon-exon junction. Frameshifts were identified by comparing the sequence of the downstream exon with and without the central cryptic exon. A null distribution of PTC-containing or frame shifted transcripts was created by generating central exons from random nucleotide sequence, keeping the length distribution the same. For each species this was repeated 100 times.The strength of 5′ and 3′ splice sites was calculated for the human cryptic exons using maxEnt . Higher We compared the involvement of two ALS-linked RNA-binding proteins in cryptic splicing: TDP-43 and FUS. We analyzed publicly available TDP-43 depletion RNA-Seq datasets  cassette-like, where novel 3′ and 5′ splice sites are recognised, which forms a completely new exon; (ii) 5′ extension, where a novel 3′ splice site is recognised and an existing exon is extended upstream of its annotated start and (iii) 3′ extension, where a novel 5′ splice site is recognised and an exon is extended downstream of its annotated end Fig. . Note thFigure Both mouse datasets differ in both cell type (adult striatum in dataset 5 vs embryonic stem (ES) cell in dataset 6) and read depth (35-60M in dataset 5 vs 2-10M in dataset 6). 52 cryptic exons were identified in total, with 46 detected in the adult striatum and 15 in ES cells, with 6 exons observed in both. Of the 46 cryptic splicing events identified in murine samples by Ling et al, 13 were detected in at least one of datasets 5 and 6. Side by side visual inspection  searching for enriched motifs in the RNA sequence including and surrounding the cryptic exons and (ii) correlating the positions of cryptic exons with TDP-43 protein-RNA interaction data.P < 10−50; proportion test) and mouse .TDP-43 can repress or enhance the inclusion of a given exon by either binding within or adjacent to the exonic sequence . Hence fhttp://icount.biolab.si/). We then intersected each set of iCLIP peaks with our cryptic exons, surrounded by 100 base pairs of flanking sequence either side. The proportion of overlapping cryptic exons was compared to the proportion of overlap between iCLIP peaks and two classes of null exon; the first created from the surrounding intronic sequence outside of each flanked cryptic and the second from an adjacent intron .Individual nucleotide resolution UV crosslinking followed by immunoprecipitation (iCLIP) allows for precise nucleotide-resolution observation of which RNA species interact with a particular RNA-binding protein , 54. We ron Fig. . If TDP-Motivated by previous findings of cryptic exons associated with hnRNP C depletion and caused by exonisation of antisense Alu elements , 55, we P < 10−16; proportion test), a result consistent with previous analyses of dataset 9 [The mouse cryptic exons show a modest enrichment in antisense SINE elements in and around the cryptic exons when compared to the rest of the surrounding intron. However the elements are also common in adjacent introns and so are not enriched for this comparison Fig. . The antataset 9 . AltogetWe then quantified the extent of evolutionary conservation of cryptic exons using the multiple species alignment conservation scores generated by PhyloP. We calculated mean conservation scores per exon for the cryptic exons and compared them to scores from both the annotated exons and randomly sampled intronic sequences from the same genes. We found no difference between cryptic exons and matched intronic sequences Fig. , and a min silico. In this analysis we only considered the”cassette-like” cryptic exons that had both upstream and downstream splice junctions. Of the 31 human cryptic exons tested, 21 (67%) are predicted to destabilise their host transcript through the NMD pathway  into a transcript could lead to either mRNA degradation by the nonsense-mediated decay (NMD) pathway. Alternatively, if the PTC falls within 50 nucleotides upstream of an exon-exon junction then NMD can be evaded, leading to the production of a truncated protein . These tway Fig. . Five crway Fig. . The ranP < 0.001; hypergeometric test).We then investigated, in datasets 3-6, whether genes containing cryptic exons showed a specific pattern of altered expression. We calculated the proportion of the cryptic exon containing genes in each dataset that were differentially expressed at a FDR of 10%. We compared this with the proportion of differential expression of all genes with an expression level at or greater than the lowest expressed cryptic exon found in that dataset. Figure P < 0.001; hypergeometric test). Visual inspection of these 10 introns in the mouse ES cell data , the majority had scores far greater than those from random sequence, suggesting that they are able function as real, albeit weaker, splice sites when TDP-43 is depleted.Whereas cassette-like cryptic exons appear as separate exons distinct from their surrounding exons, extension events must rely on a switch from a canonical splice site to a newly accessible splice site. We hypothesised that these extension events result from competition between two splice sites upon TDP-43 depletion. This would require the sequence of and around the cryptic splice site to be similarly recognisable to the spliceosome. Using the MaxEnt statistical model  to scoreP-value from the four tests was reported and corrected for multiple testing using a strict Bonferroni approach. Only proteins with a resulting P < 0.05 are reported. Unsurprisingly TDP-43 had the highest number of overlapping exons , followed by U2AF65, TIA1, SRSF7, U2AF35, PPIG, SRSF1 and IGF2BP1. Figure Proteomic studies have demonstrated that TDP-43 interacts with a number of RNA-binding proteins (RBPs), including multiple members of the heterologously expressed ribonucleoprotein (hnRNP) family and other splicing factors –58. The We have designed an analytical strategy to identify cryptic splicing that takes advantage of biological replicates in RNA sequencing data. We have applied this tool to a set of human and murine TDP-43 depletion datasets, as well as datasets that deplete hnRNP C or FUS. Our results are consistent with the previous findings that depletion of TDP-43 or hnRNP C leads to the inclusion of novel cryptic exons in both human and mouse, albeit with hnRNP C depletion leading to a far greater number of events than TDP-43. Although FUS undoubtedly plays an important role in splicing and mRNA stability and shares a number of targets with TDP-43 , the lowin silico to any annotated coding exons, suggesting a role for cryptic exon inclusion in to upstream open reading frames and 3′ untranslated regions, both of which have been observed to provide a site for modulation of gene expression by introducing premature termination codons [Further examination of TDP-43 linked exons suggests they tend to possess the necessary UG-rich sequence elements to be bound by TDP-43 and using iCLIP data we observed that a subset of the cryptic exons are bound by TDP-43 in vivo. We went on to investigate the origins of these TDP-43 bound cryptic exons, as has been done for the targets of hnRNP C. We observed that unlike hnRNP C linked cryptic exons, which invariably originate from antisense Alu elements, TDP-43 linked cryptic exons do not originate from any single family of transposable element. Furthermore their sequences show very low species conservation, akin to random intronic sequence, but remarkably they contain splice sites very close in strength to those of their adjacent annotated exons. Our differential expression analysis suggests that the bulk of cryptic exon containing genes are significantly downregulated upon TDP-43 depletion. We hypothesize that while some cassette-like cryptic exons will create functional or truncated proteins, most will lead to premature stop codons and nonsense-mediated decay of the inclusion transcript. The large number of exon extensions discovered by CryptEx may similarly lead to frameshifting and nonsense-mediated decay upon inclusion but may alternatively be sequestered in the nucleus and degraded by the mRNA surveillance pathway, as has been observed for retained introns . A numben codons , 62.HUWE1 and GOLGB1 had protein levels that were 8 and 31% of the control cells respectively whereas the third, HNRNPH3 was found to be 7-fold increased under TDP-43 depletion. Interestingly, the cryptic exon discovered in HNRNPH3 falls upstream of the start codon whereas those found in HUWE1 and GOLGB1 are predicted to trigger NMD by inclusion into the coding sequence  between depletion and control samples. The cryptic exon classifier throws out any splicing event where the canonical intron in which the cryptic splicing event appears is represented by less than five spliced reads (purple) or where the |log2(fold change)| < 0.6 (light blue). Splicing events are classified as cryptic exons if the spliced reads agree with the rest of the reads and have at least 1 spliced read per sample (red). Those that fail this step are coloured orange. (ZIP 1386 kb)Pre-classification output of CryptEx pipeline demonstrates a variety of novel splicing events in TDP-43, FUS and hnRNP C depletion data. Every novel splicing event plotted by mean depth of reads covering the novel event against logAdditional file 2: Figure S2.Each cryptic exon discovered in either of the two mouse datasets. For each dataset, the biological replicates were combined to create merged BAM files for each condition. The BAM files were loaded into IGV for visualisation. Read coverage and splice junctions are shown. The Ensembl transcripts for the mm10 build are provided, as are the coordinates of the cryptic exons discovered by CryptEx. (PDF 2436 kb)Additional file 3: Figure S3.Each cryptic exon discovered in either of the two human K562 datasets. As above, with the hg38 human genome build. (PDF 5917 kb)Additional file 4: Tables S1 and S2.Quantification of all results for each cryptic exon discovered by CryptEx in mouse (ST1) and human (ST2). Change in percent spliced in (∆PSI) scores were calculated by taking the difference of ratios of novel splice junctions over the sum of novel and annotated (intron-spanning) splice junctions in control and depletion samples for the 5′ and 3′ splice junctions. (ZIP 8 kb)Additional file 5: Tables S5 and S6.Reep3 E001i1 and Adipor2 E010i2 are included in a few tissues at very low levels. Elmod1 E003i2 is seen in brain tissue at an inclusion rate above 10%, whereas Thoc7 E007i1 was included in every tissue bar heart. However, the inclusion rates were highly variable. Among the 95 human cryptic exons, only three were detected in 49 different human tissues from the GTEx project. MPDZ E015i1, UHRF2 E017i2 and DEAF1 E005i2 were all detected in at least 1 tissue. Only UHRF2 E017i2 was regularly seen above 10% inclusion, albeit with very high variance between samples. (PDF 66 kb)Inclusion of cryptic exons in normal mouse (ST5) and human (ST6) tissues. RNA-seq data from multiple mouse tissues from  and multAdditional file 6: Figure S4.Motif finding with HOMER The top ten motifs reported by the algorithm when comparing flanked cryptic exons with adjacent intronic sequence. The red asterisk indicates that the motif is potentially a false positive result. (TIF 1799 kb)Additional file 7: Tables S3 and S4.Figure S5. The RNA sequence of the B2 SINE in the antisense orientation. The DNA sequence of the B2 SINE was downloaded from lncrnadb [All repeat elements enriched in mouse (ST3) and human (ST4) cryptic exons. For each class of repeat element that was enriched in a set of cryptic exons, the exact overlapping repeat element was compiled into a table. The strand column refers to the orientation of the gene, not the repeat element. For the simple repeats, all annotations are made in the positive direction. Therefore (AC)n containing repeats in the antisense direction are in fact (GT)n repeats for genes on the negative strand. lncrnadb  and conv


Arabidopsis thaliana have contributed to better understand the role of the cell cycle components and their implication in the establishment of functional galls. Mitotic activity mainly occurs during the initial stages of gall development and is followed by an intense endoreduplication phase imperative to produce giant-feeding cells, essential to form vigorous galls. Transgenic lines overexpressing particular cell cycle genes can provoke severe nuclei phenotype changes mainly at later stages of feeding site development. This can result in chaotic nuclear phenotypes affecting their volume. These aberrant nuclear organizations are hampering gall development and nematode maturation. Herein we report on two nuclear volume assessment methods which provide information on the complex changes occurring in nuclei during giant cell development. Although we observed that the data obtained with AMIRA tend to be more detailed than Volumest (Image J), both approaches proved to be highly versatile, allowing to access 3D morphological changes in nuclei of complex tissues and organs. The protocol presented here is based on standard confocal optical sectioning and 3-D image analysis and can be applied to study any volume and shape of cellular organelles in various complex biological specimens. Our results suggest that an increase in giant cell nuclear volume is not solely linked to increasing ploidy levels, but might result from the accumulation of mitotic defects.Root-knot nematodes induce galls that contain giant-feeding cells harboring multiple enlarged nuclei within the roots of host plants. It is recognized that the cell cycle plays an essential role in the set-up of a peculiar nuclear organization that seemingly steers nematode feeding site induction and development. Functional studies of a large set of cell cycle genes in transgenic lines of the model host  Heterodera and Globodera.Plant-parasitic nematodes are a major threat to many plant cultures worldwide, and root-knot nematodes (RKN) are responsible for extensive economic losses caused by phytonematodes . Cyst neFigure 1A). Nematode-induced GCs undergo multiple and often synchronous acytokinetic mitotic events  (Feeding sites induced by RKN are composed of outsized feeding cells named “giant cells” (GCs) which hold a dense cytoplasm filled with organelles and enlarged nuclei, representative of high metabolic activity. These giant-feeding cells are surrounded by mitotically active vascular tissue cells characterized by asymmetric cell wall positioning. This peculiar division pattern gives rise to a multi-layered shell consisting of small cells neighboring the GCs. This finally outlines the typical knot shape in susceptible roots called a “gall.” On the other hand, CN initiate a syncytium through elongation of a single initial feeding cell, accompanied by division of neighboring cells which will fuse as syncytia expands . Unlike gure 1B) .Figures 1C,D). Cytogenetic studies revealed that giant cell nuclei are polyploid or aneuploid  while giant cell nuclei present profuse chromocenters differently sized suggestive of nuclei polyploidization . Chromocenters are densely stained heterochromatic regions matching to centromeres and nuclear organizing regions (3H-thymidine incorporation studies (AtCCS52B gene family) also support the implication of the endocycle in giant cell development  and their regulatory subunits (CYCs) [see Vieira and de Almeida Engler in same issue and  nuclei present in wild-type (Col-0) and OEKRP3 and OEKRP5 Arabidopsis transgenic lines  and transgenic lines 35S::KRP3-GFP and 35S::GFP-KRP5 (designated OEKRP3 and OEKRP5 hereafter) were sown on cups containing a sterile mix of sand and soil (2:1). After cold treatment (2 days at 4°C) in the dark, seeds were kept in a growth chamber with a 12-h light:12-h dark photoperiod at 21°C. Fourteen-day-old seedlings were then individually placed in a sand/soil mixture and 1 week later, roots were inoculated with 200 freshly hatched, second-stage juveniles (J2s) of M. incognita. Infections were performed in two independent experiments for both transgenic and wild-type lines. Galls were subsequently collected at 14 and 21 days after inoculation (DAI).Seeds from wild-type Figure 2. Nematode-infected roots from 14 to 21 DAI were fixed in phosphate-buffered saline (PBS), pH 7.2, containing 1% formaldehyde (PBSF) for 16 h at 4°C. Samples were embedded in liquid 3% agarose  in small plastic stubs. When solidified, agarose blocks were removed and mounted on the sample holder of the Vibratome, slices of 150–200 μm were generated floating on distilled water. Vibroslices containing gall tissue were fished and subsequently fixed in PBSF for 1 h at RT. Then samples were dehydrated twice with absolute methanol and four times with absolute ethanol (both stored at 4°C) 10 min each step. Vibroslices were stored at -20°C for 2–4 days to allow tissue clearing. Subsequently, they were washed twice for 15 min with PBS. Vibrosliced galls were then incubated in a solution containing PBS, 0.05% Triton-X 100 , and 1 μg/ml DAPI  for 20 min. Finally, the samples were washed in PBS for 5 min and mounted with care to avoid compression in 90% glycerol between two coverslips to allow double side confocal imaging.Nuclear analyses of cleared thick gall slices (named vibroslices thereafter) made with a Vibratome  were basically treated as described in OEKRP3 and OEKRP5 transgenic lines . Volumest allows volume estimation using confocal data sets. Before estimating the volume of GCs nuclei, 3D projections of each image stack were made with ImageJ, to facilitate nuclei mapping. Then, original z-stacks were prepared as required for Volumest analysis. Volume measurements were performed on a selection of nuclei with bright DAPI staining as identified from maximum projection images. This selection was necessary to avoid measuring background noise. Well defined nuclei were subsequently measured using the cumulative nuclei volume tool and recorded as shown in the Supplementary File Image stacks of DAPI-stained galls were analyzed with the plugin VolumestTo simplify the measuring procedure we assessed the nuclei volume from a single Col-0 image stack at different manners. First, the nuclear volumes were computed by summing the volumes of each individual image in the stack. Then volumes were measured by skipping one, two, three or four images in the same sequence taking into account the slice thickness. All measurements were carried out on at least 400 GC nuclei with a minimum of 22 GCs for each time point for each line. Also, the volume of NGC was measured with more than 100 per time point for each line.P < 0.05.All data generated were analyzed statistically by Sigma Plot version 12  using one-way analysis of variance (ANOVA). The Shapiro–Wilk test was used for normality, the Levene test for homogeneity of variance and Tukey’s test to compare the means. Different letters between groups indicate a significant difference at In order to confirm the reliability of the data obtained using the ImageJ Volumest software, the same dataset was also analyzed with the AMIRA software package . For the latter, nuclei were segmented according to standard procedures and correspondingly volume rendered. Briefly, to enhance the signal to noise ratio while preserving edges, images were first filtered with a 2D-median rolling ball, then nuclei were segmented by applying a white Top-Hat filter. Sorted out nuclei from gall sections were then filled to avoid holes within the selection. GC and NGC nuclei were individually labeled via the AMIRA segmentation tool and analyzed for morphologic traits.Figure 2) is essentially based on a method developed for the microscopic analysis of whole mounts of RKN infected roots . Therefore, this procedure allows a detailed analysis of GC nuclei shape, structure, volume, and spatial distribution. Other modifications include shorter sample preparation time, the use of DAPI instead of propidium iodide (PI); the former having a higher specificity for DNA. Samples were finally mounted between two coverslips  to allow imaging both sides of the gall sections.The protocol here described . Nematode nuclei are also clearly visible in DAPI stained samples being round shaped and smaller than GC nuclei. In galls (14 DAI) we could observe enlarged and often grouped nuclei in expanding GCs as well as individual nuclei in neighboring cells . Dark areas correspond to vacuoles while the very small DAPI stained fluorescent dots within the GCs are plastids and/or mitochondria. Cell walls are weakly stained due to background DAPI staining delimiting the living cells from dead xylem tissue.Cleared vibroslices of DAPI stained galls 7 DAI, were used to image the initial stages of giant cell development allowing to observe enlarged nuclei close to the nematode head . This plugin allows estimating volumes from confocal acquired z-stack. In this way, we were able to estimate the GC nuclear volume by measuring the nuclear area from different gall confocal optical sections within a z-stack . No differences were observed in the final nuclear volume when measuring only  of the optical sections taking into account four times bigger optical slice thickness. Therefore, all volumetric measurements of GC nuclei were performed by measuring one and skipping the next three confocal slices.Herein, we describe a methodology to measure nuclear volumes from plant root cells, especially from GCs induced by Figures 1, 5) . However, the nuclear volume from OEKRP3 (14 and 21 DAI) and OEKRP5 (21 DAI) was statistically larger than those of the wild-type . No differences were observed between the nuclear volumes of NGCs at any time point .To acquire information other than nuclear size and morphology , we esties 1, 5) . In ordeOEKRP3, OEKRP5, and wild-type lines 14 and 21 days after infection with the RKN M. incognita) using a 3D analysis dedicated software named AMIRA . GC and NGC nuclei were segmented  and investigated for their volume  via AMIRA imaging software according to the “Materials and Methods” session. Throughout the RKN infection process in the wild-type, we measured a slight but significant (p < 0.01) 1.8-fold increase of the GC nuclear volume between 14 and 21 DAI. This volume rise may be explained by the onset of the endoreduplication process. Furthermore, the overexpression of KRP3 at 14 DAI, promotes a 3.8-fold increase of GC nuclear volume compared to wild-type (p < 0.001). At 21 DAI, KRP3 and KRP5 overexpression also induced a significant increase in the nuclear volume of approximately threefold compared to wild-type 21 DAI.To consolidate the data obtained with the Volumest software, we also analyzed the confocal datasets obtained from the different KRP lines (OEKRP3 and OEKRP5 lines underwent a slight but significant rise of volume 1.45- to 2-fold (p < 0.001).No nuclear volume changes of NGC were detected from 14 up to 21 DAI within wild-type galls suggesting the absence of endoreduplication in normally mitotically active NGC. Interestingly, our measurements illustrate that NGC nuclei of galls 14 and 21 DAI for both In plant cells, polyploidization is linked with cessation of cell division and initiation of terminal differentiation. Previous data indicate that nematodes maneuver the plant host cell cycle pushing feeding cells to undergo multiple mitotic and endoreduplication cycles resulting in polyploidy. Therefore, deciphering the plant cell cycle machinery in nematode feeding sites will contribute to better understand how nematodes manage to steer the plant cell cycle in their favor.in vivo specimens allowed us to determine the nuclear 3D shape and to measure nuclear sizes and volumes in nematode-induced GC , we compared their volumes with wild-type GC nuclei. Despite the observed variation in nuclear volume amongst GCs in different lines evaluated, nuclei in OEKRP3 and OEKRP5 lines are consistently larger in volume than in wild-type. These data suggest that defective mitotic events occurring in GC may prevent complete nuclear division and thereby lead to the abnormal increase in nuclear volume. This result is in agreement with the fact that even though there is only a slight increase in ploidy level for the OEKRP3 line, a considerable increase in nuclear volume is observed. Moreover, despite the vast increase in GC nuclear volume in the OEKRP5 line, previous flow cytometry data showed no increase in ploidy levels for this line supporting the idea that the nuclear volume increase observed for these mutants is not caused by an increase in DNA content but rather a consequence of mitotic defects  in a single cross section and, the plug-in generated a three-dimensional volume calculation  based on defects . Using tAs a second measuring approach we used AMIRA, a commercial software package which is based on morphological segmentation of the image data set. This segmentation relies on a white top-hat transformation to extract objects (here nuclei) from the data set. The size of the extracted object is conditioned by a self-chosen kernel size for a mathematical operation called “opening.” In digital image processing, an opening is the dilation of the erosion of the image by a structuring element named a kernel matrix. While opening removes small objects from the foreground, it can also be used to extract specific features from the image that fits the kernel matrix. Segmented objects are finally properly labeled and analyzed for volumetrics. Since the latter method involves image processing before measuring, it is expected to be less depending on manual errors.OEKRP3 and OKRP5E lines increased up to three times in volume compared to wild-type GC nuclei. A slight increase of NGC nuclear volume was also observed for both KRP lines within a range of 1.5–2 times for OEKRP3 and OEKRP5 21 DAI as compared to wild-type NGC nuclei. These results suggest that ectopic KRP3 and KRP5 expression in galls promotes an increase in the nuclear volume of GC and to a lesser extent but also true for NGC nuclei.Interestingly, measurements by AMIRA revealed that GCs nuclei in galls 21 DAI in the OEKRP3 and OEKRP5 lines than in the wild-type. These data together with volume rendering of giant cell nuclei suggest that OEKRP3 and OEKRP5 lines accumulate mitotic defects which can lead to disturbed mitotic events and erroneous nuclear division. These defects may explain the elongated and undulated nuclear phenotype observed in GC of both KRP overexpressing lines . Despite that both analysis point in the same direction, nuclear volume differences are more pronounced when using the AMIRA approach. The latter also enabled to detect minor but significant volumetric variation when comparing nuclei from different plant lines. Several criteria may explain such differences: a lack of reproducibility when using Volumest which relies on the manual delineation of each nucleus determined by the user, and its limited ability to discriminate all shades of gray preventing the accurate delineation of nuclear boundaries. This error may affect the volume output and the observed differences between the two methods. Besides, the highly irregular nuclear shapes observed in the KRP lines may hamper the selection of a single nucleus which actually might consist of two entangled entities in very close proximity. A manual measuring procedure will be more prone to introducing this type of error. Since Volumest seems less accurate, it may also have prevented to observe the increase of NGC nuclear volume in KRP3OE and KRP5OE lines during the nematode infection process.The results obtained from both volumetric measurement methods show that giant cell nuclei are significantly bigger in both Although our analysis revealed that the Volumest approach seems to provide somewhat less accurate results than AMIRA, the former still features some advantages: -it is a free public domain software, -there is no need for additional mathematical operation and, -it is easy in use relying on hand-made object delineation. Since “Volumest” is supported by ImageJ, it is up to the user to implement additional data processing tools such as the “top-hat” approach prior to “Volumest” analysis.Astragalus sinicus roots infected with Heterodera glycines. The strategy we propose here and which is based on root vibroslicing combined with nuclear volume measurement (ImageJ and AMIRA) can also be applied for much thicker roots infected with cyst or RKN. Currently, thick vibrosliced samples are being optimized using different clearing approaches for deep tissue imaging.It is important to mention that recently KRP3 and KRP5 compared to wild-type. Both lines presented exceptionally elongated and apparently connected nuclear morphology. These phenotypes are characteristically occurring in some KRP overexpressing lines and were enhanced in mature GC (21 DAI) compared to young feeding cells (5–10 DAI), most likely due to cumulative defective mitotic events .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.