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Cell Death & Disease logoLink to Cell Death & Disease
. 2018 May 22;9(6):586. doi: 10.1038/s41419-018-0671-1

Transcriptome analysis of the adult human Klinefelter testis and cellularity-matched controls reveals disturbed differentiation of Sertoli- and Leydig cells

Sofia Boeg Winge 1, Marlene Danner Dalgaard 1,2, Kirstine G Belling 3, Jacob Malte Jensen 4, John Erik Nielsen 1, Lise Aksglaede 1, Mikkel Heide Schierup 4, Søren Brunak 3, Niels Erik Skakkebæk 1, Anders Juul 1, Ewa Rajpert-De Meyts 1, Kristian Almstrup 1,
PMCID: PMC5964117  PMID: 29789566

Abstract

The most common human sex chromosomal disorder is Klinefelter syndrome (KS; 47,XXY). Adult patients with KS display a diverse phenotype but are nearly always infertile, due to testicular degeneration at puberty. To identify mechanisms causing the selective destruction of the seminiferous epithelium, we performed RNA-sequencing of 24 fixed paraffin-embedded testicular tissue samples. Analysis of informative transcriptomes revealed 235 differentially expressed transcripts (DETs) in the adult KS testis showing enrichment of long non-coding RNAs, but surprisingly not of X-chromosomal transcripts. Comparison to 46,XY samples with complete spermatogenesis and Sertoli cell-only-syndrome allowed prediction of the cellular origin of 71 of the DETs. DACH2 and FAM9A were validated by immunohistochemistry and found to mark apparently undifferentiated somatic cell populations in the KS testes. Moreover, transcriptomes from fetal, pre-pubertal, and adult KS testes showed a limited overlap, indicating that different mechanisms are likely to operate at each developmental stage. Based on our data, we propose that testicular degeneration in men with KS is a consequence of germ cells loss initiated during early development in combination with disturbed maturation of Sertoli- and Leydig cells.

Introduction

Klinefelter syndrome (KS) is caused by the presence of at least one additional X-chromosome in men. KS is the most common sex chromosomal disorder with an estimated prevalence of 1 in 660 newborn boys, but only one fourth of the expected cases are diagnosed throughout life1. There is a huge variation in the phenotype of men with KS. In adulthood, the classical symptoms are tall stature, gynecomastia, reduced virilization, hypergonadotropic hypogonadism, and small testes25. Many men with KS, however, first discover their condition when they want to have a child as the most pervasive symptom is azoospermia or, rarely, severe oligozoospermia.

The histology of a typical testis from an adult KS man shows absence of germ cells, high amounts of degenerated, hyalinized tubules, and Leydig cell hyperplasia2,6. In some men with KS, focal spermatogenesis is nevertheless observed and is considered the result of elimination of the supernumerary X-chromosome in a subset of spermatogonia710. Presence of focal spermatogenesis opens the possibility to recover sperm in the ejaculate or to perform surgical microdissection of the seminiferous tubules and isolate areas with focal spermatogenesis (micro-TESE procedures) that subsequently can be used for intracytoplasmic sperm injection. This allows such patients to become fathers of children with apparently normal karyotype (reviewed in refs. 11).

The molecular mechanisms responsible for the KS phenotype are poorly understood. Best described is the increased dosage of the X-chromosomal SHOX gene, which accounts at least in part for the tall stature observed in men with KS12. Recently, several studies have reported transcriptome analysis of peripheral blood samples1315 and of cultured lymphocytes isolated from blood16 from KS patients compared to controls. The only overlap between the transcriptome profiles was upregulation of the long non-coding RNA (lncRNA) XIST1316. Upregulation of XIST is expected and can be used as a quality control, as XIST is involved in X-chromosome inactivation (XCI)17,18. Only 12 transcripts were differentially expressed in more than one study13,15,16, highlighting the diverse phenotype.

Pre-pubertal testicular development in KS has been described as similar to boys with normal karyotypes, albeit with smaller testis volume and reduced germ cell numbers6,19. However, our recent study indicated that despite the supposedly normal pre-pubertal testicular development, the fetal KS testis displays impairment of fetal gonocyte differentiation resulting in loss of pre-spermatogonia20. This effect is most likely caused by the extra X-chromosome because the fetal KS testis transcriptome revealed enrichment of X-chromosomal transcripts as well as lncRNAs20. Later on, initiation of spermatogenesis at pubertal onset fails in the KS testis and results in testicular degeneration6,19.

Gene expression analysis of human KS testes is challenging, as available material is scarce because testicular biopsies are not performed in the routine clinical work-up. But three recent studies used leftover testis tissue from TESE and micro-TESE. In one study, expression of metabolic components was examined in six KS and six controls with azoospermia but conserved spermatogenesis21. In another study, D’Aurora et al. performed microarray analysis of bilateral testicular biopsies from six non-mosaic KS patients with absence of germ cells compared to a pool of three biopsies from patients with obstructive azoospermia but complete spermatogenesis22. While the material used in the two studies is unique and very precious, the huge cellularity differences are expected to drive most of the changes in the transcriptome and mask transcripts involved in the actual testicular phenotype of KS. In another study by D’Aurora et al., testicular biopsies from three atypical adult KS patients with focal spermatogenesis were compared to the controls used in their former study23. The cellularity differences were thereby less pronounced but the transcriptome now reflected the atypical situation of KS testis with focal spermatogenesis.

To describe the adult KS testicular transcriptome and to account for cellularity differences, we performed RNA-sequencing of fixed, paraffin-embedded testicular biopsies from adult KS patients and cellularity-matched controls (CMC), which had Sertoli-cell-only (SCO) pattern and Leydig cell hyperplasia. The cellular origin of the differentially expressed transcripts (DETs) was determined by including samples with complete spermatogenesis. Moreover, to describe developmental changes in the testicular KS transcriptome, we included testis samples from pre-pubertal KS boys along with our published data on the fetal KS testis.

Results

The adult KS testicular transcriptome

We performed RNA-sequencing of 15 fixed, paraffin-embedded testis samples, and the average reads per sample was 2.8 million (Table 1). The RNA quality was compromised and we, therefore, performed a thorough quality control based on MDS plots, heatmaps and expression of XIST in the KS samples (Fig. 1a and Supplementary Fig. S1). Based on this, three KS samples and three CMC were used in the subsequent analyses (Fig. 1a).

Table 1.

Samples used for RNA-sequencing

ID Group Age Karyotype (blood) Fixative Block age Library size Included in final analysis/ reason for exclusion
aKS1 Adult KS 21y, 7m 47,XXY GR-fix 1 y 7,413,356 Yes
aKS2 Adult KS 27y, 7m 47,XXY Bouin 14 y 1,693,175 Yes
aKS3 Adult KS 28 y, 7 m 47,XXY GR-fix 4 y 2,199,570 Yes
aKS4a Adult KS 30 y, 7 m Stieve 42 y 812,877 No XIST expression
aKS5 Adult KS 40y, 2m 47,XXY Stieve 16 y 177,280 Low library size and MDS plot
aKS6 Adult KS 21y, 3m 48,XXYY, 47,XXY Stieve 40 y 132,405 Low library size and MDS plot
aKS7a Adult KS 27 y, 11 m Stieve 48 y 541,108 MDS plot
aKS8a Adult KS 28 y, 6 m Stieve 48 y 123,653 No XIST expression
aKS9 Adult KS, GCs 21y, 7m 47,XXY GR-fix 1 y 8,233,082 Same patient as aKS1
aKS10 Adult KS, GCs 30y, 0m 47,XXY Stieve 14 y 188,313 Low library size and MDS plot
aCMC1 Adult CMC 32 y, 0 m 46,XY GR-fix 6 y 4,480,564 Yes
aCMC2 Adult CMC 32y, 7m Two SHOX copies GR-fix 4 y 7,868,360 Yes
aCMC3 Adult CMC 33 y, 8 m 46,XY GR-fix 7 y 2,044,132 Yes
aCMC4 Adult CMC 39 y, 8 m 46,XY GR-fix 5 y 3,113,958 Balance with number of KS samples
aCMC5 Adult CMC 42 y, 2 m 46,XY GR-fix 7 y 2,443,579 Balance with number of KS samples
aSCO1 Adult SCO 29 y, 6 m 46,XY GR-fix 3 y 3,064,063
aSCO2 Adult SCO 31 y, 7 m 46,XY GR-fix 7 y 2,317,076
aSCO3 Adult SCO 33 y, 3 m 46,XY GR-fix 6 y 7,157,424
aSCO4 Adult SCO 35 y, 4 m 46,XY GR-fix 6 y 3,897,228
aSCO5 Adult SCO 43 y, 5 m 46,XY GR-fix 5 y 634,570 Low library size and MDS plot
aNorm1b Adult NT 30 y, 2 m 46,XYd GR-fix 4 y 4,635,540 Yes
aNorm2c Adult NT 31 y, 3 m 46,XYe GR-fix 6 y 3,100,541 Yes
aNorm3c Adult NT 35 y, 9 m 46,XYe GR-fix 6 y 1,213,352 Yes
aNorm4b Adult NT 39 y, 9 m No karyotyped GR-fix 5 y 373,341 Yes
pKS1a,d Pre-pubertal KS 9 y, 6 m Stieve 39 y 442,161 Yes
pKS2a,d Pre-pubertal KS 9 y, 6 m Stieve 35 y 481,952 Yes
pKS3a,d Pre-pubertal KS 11 y, 0 m Cleland 32 y 404,698 Yes
pKS4a,d Pre-pubertal KS 14 y, 1 m Stieve 37 y 231,918 Yes
pKS5a,d Pre-pubertal KS 14 y, 9 m Stieve 39 y 1,120,193 No XIST expression
pNorm1e Pre-pubertal NT 7 y, 5 m Stieve 21 y 671,897 Yes
pNorm2f Pre-pubertal NT 7 y, 9 m Cleland 30 y 1,026,282 Yes
pNorm3f Pre-pubertal NT 10 y, 2 m Cleland 30 y 392,993 Yes
pNorm4f Pre-pubertal NT 10 y, 10 m Stieve 35 y 268,552 Yes

KS Klinefelter syndrome, GCs germ cells, SCO Sertoli cell-only, NT normal testis (biopsy with complete spermatogenesis), GR-fix modified Stieve’s fixative, y years, m months

aKnown KS patient, no karyotype available

bTestis cancer patient

cMan from infertile couple

dBiopsy taken due to suspicion of urological problems

eAcute lymphocytic leukemia patient

fAutopsy

Fig. 1. Differentially expressed transcripts (DETs) in testis from adult Klinefelter syndrome (KS) patients compared to cellularity-matched control (CMC) testes.

Fig. 1

a Flowchart depicting the exclusion of samples. b Top: Volcano plot with all expressed transcripts. The red dots are the DETs using an un-adjusted p-value < 0.01. The most significant DETs are indicated. Bottom: The same plot as on the top, but with all X-chromosomal transcripts plotted according to their X-chromosome inactivation status25. The significant X-chromosomal DETs are indicated. c Heatmap of the DETs

Using an un-adjusted p-value < 0.01, 235 DETs were identified, with 153 being upregulated and 82 being downregulated in KS compared to CMC (Fig. 1b, c, and Supplementary Tables S1 and S2). The most significant DET was XIST, as expected. Apart from XIST, eight X-chromosomal DETs were upregulated (Fig. 1b and Supplementary Table S1); three of these, POU3F4, PNMA5, and ALPN, have previously been reported to undergo XCI24. The remaining upregulated transcripts have no or discordant data regarding XCI status. Four X-chromosomal transcripts were downregulated, one expressed from PAR1: ASMTL-AS1, one previously reported to undergo XCI: LONRF3, and two with no or discordant data regarding XCI (Fig. 1b and Supplementary Table S2).

Protein expression of DACH2 and FAM9A

To validate our findings, we selected two upregulated X-chromosomal candidates, DACH2 and FAM9A based on availability of antibodies and supportive literature.

Immunohistochemical staining showed that DACH2 was expressed in the nuclei. In testes with complete spermatogenesis, DACH2 showed strongest intensity in the wall of blood vessels, medium-strong intensity in primary spermatocytes, and faint-negative staining in Sertoli cells (Supplementary Fig. S2). In testes from adult men with KS (n = 2), DACH2 was expressed in a subset of Sertoli cell nuclei of type A (mature) and type B (immature) SCO tubules (identified according to ref. 25) (Fig. 2a, b). Sertoli cell nuclei showed only faint DACH2 staining in CMC biopsies (n = 3) (Fig. 2c, d), which confirmed upregulation of DACH2. To test whether DACH2 expression depended on the Sertoli cell maturation stage, an adjacent section was stained with AMH, a marker of immature Sertoli cells. In Sertoli cells, AMH was expressed in the cytoplasm with varying intensity, with the majority of DACH2-positive Sertoli cells also positive for AMH (Supplementary Fig. S3). However, a subset of AMH-positive Sertoli cells were negative for DACH2, and a small proportion of the DACH2-positive Sertoli cells were negative for AMH (Supplementary Fig. S3).

Fig. 2. Localization of DACH2 and FAM9A in a testis from an adult man with Klinefelter syndrome (KS).

Fig. 2

IHC staining with antibodies against DACH2 and FAM9A of a testis from an adult man with KS (which is the same sample as aKS3 used for RNA-sequencing). DACH2 was expressed in a fraction of nuclei both in type A (mature) Sertoli cell-only (SCO) tubules (a) and type B (immature) SCO tubules (b). The same pattern was seen in another KS testis, aKS1, also used for the transcriptome profiles (data not shown). In the CMC testis (n = 3) (exemplified here aCMC1 used for RNA-sequencing), DACH2 was only expressed weakly (c, d) In adult KS, FAM9A was expressed in Leydig cells with varying intensity (e) and in all Sertoli cell nuclei (f). Immunofluorescence staining showed that FAM9A and INSL3 were expressed by two populations of Leydig cells with limited overlap. Scale bars correspond to 50 µm

In a fetal testis aged gestational week (Gw)10, a large fraction of the Sertoli cells indeed showed expression of DACH2 (Supplementary Fig. S2).

In testes with complete spermatogenesis, FAM9A showed strongest intensity in the cell membrane of spermatocytes and spermatids, moderate-strong intensity in Sertoli cell nuclei and faint-strong staining in Leydig cell cytoplasm (Supplementary Fig. S2). In the testis from an adult KS patient, FAM9A was expressed in the cytoplasm of Leydig cells with varying intensity and in the nuclei of all Sertoli cells (Fig. 2e, f), and the same pattern was seen in CMC testes (n = 3) (data not shown). A double fluorescent staining with FAM9A and insulin-like 3 (INSL3, a marker of mature Leydig cells26) showed that FAM9A and INSL3 were only partially overlapping with distinct FAM9A-positive/INSL3-negative and FAM9A-negative/INSL3-positive populations visible (Fig. 2), indicating that FAM9A is expressed predominantly in immature Leydig cells and during the transition phase into mature Leydig cells. In a fetal testis aged Gw10, a fraction of interstitial cells (most probably fetal Leydig cells) were positive for FAM9A (Supplementary Fig. S2).

Enrichment analyses of the KS DETs

Next, we compared DETs from previous studies of KS patients1316,22,23, and found an overlap of three DETs with the transcriptome profiles from blood and nine DETs from the studies on testes (Fig. 3a, b). Overlapping DETs included FOSB and DLK1 (Supplementary Table S3).

Fig. 3. Overlap of the differentially expressed transcripts (DETs) with previous studies.

Fig. 3

Overlap with previous studies performed on blood1417 (a) and on testis tissue23,24 (b). The overlapping transcripts can be seen in Supplementary Table S3

We noticed that many of the DETs were ncRNAs (Supplementary Tables S1 and S2), and we, therefore, analyzed for enrichment of transcript biotypes classified by the GENCODE annotation27. We found significant (p-value = 0.0018) enrichment of long, intergenic ncRNAs (lincRNAs) among the upregulated transcripts. Also, protein-coding transcripts among the upregulated (p-value = 0.0058) and antisense transcripts among the downregulated transcripts were significantly enriched (p-value = 3.3E-5) (Fig. 4a and Supplementary Table S4).

Fig. 4. Enrichment analyses of the differentially expressed transcripts (DETs).

Fig. 4

a Distribution in RNA biotype among the upregulated (left) and downregulated (right) transcripts. The significant biotypes are indicated with p-values. For RNA biotypes of each individual DET, see Supplementary Tables S1 and S2, and for description of RNA biotypes, see Supplementary Table S4. b Significantly overrepresented gene ontology (GO) “Biological Process” terms of the DETs

To gain insight into the potential function of the DETs, we searched for enrichment of particular gene ontologies (GO). Among the most interesting results were those involved in reproduction (“reproductive process”, “reproduction”, and “multi-organism reproductive process”), development (“multi-cellular organism development”, “single-organism developmental process”, “animal organ development”, “system development”, and “developmental process”), as well as “response to hormone” (Fig. 4b).

Cellular origin of the KS DETs

In order to identify the potential cellular origin of the 235 DETs, we used a comparative approach, and profiled the transcriptome of five adult testis biopsies with SCO and normal amounts of Leydig cells, and four adult testis biopsies with full spermatogenesis and normal amounts of Leydig cells (these samples are termed Norm) (Table 1 and Supplementary Fig. S4). We excluded one SCO sample due to poor quality (data not shown).

First, we compared the expression of known cell type-specific transcripts in the four groups (Fig. 5a). As expected, KS and CMC specimens displayed relative upregulation of Leydig cell transcripts compared to SCO samples, which had a higher level than the Norm samples. The same tendency was seen for peritubular/blood vessel transcripts. The levels of Sertoli cell transcripts were similar among KS, CMC, and SCO, but lower in the Norm samples. And as expected, the levels of germ cell transcripts were highest in Norm samples (Fig. 5a).

Fig. 5. Depicted cellular origin of the differentially expressed transcripts (DETs).

Fig. 5

a Known Sertoli, Leydig, peritubular/blood vessel and germ cell markers expressed in the testis of Klinefelter syndrome (KS), cellularity-matched controls (CMC), Sertoli cell-only (SCO), and normal testes with complete spermatogenesis (Norm). The lines indicate the mean expression values in each group. b Pie charts of average cellularity in each group and resultant predicted cellular origin of the overlapping DETs taking into account the amounts of cellularity transcripts in (a)

We also evaluated the cellularity of each sample by measuring the area of the cellular compartments (Supplementary Fig. S4) and when calculating the average cellularity, we could predict the cellular origin of the DETs for each comparison (Figs. 5b and 6a).

Fig. 6. Expression of transcripts with depicted cellular origin in each sample.

Fig. 6

a Venn plots of the transcripts from the comparisons in Fig. 4b. The upregulated transcripts in KS vs. SCO and the downregulated transcripts in CMC vs. SCO are not included as they are predicted to be unique for KS and SCO. b Heatmap of the transcripts from (a). The clustering is made so that the different cellularity transcripts are grouped together

We compared the DETs with those of all of the group comparisons, and thereby could get an idea about the cellular origin of the individual transcripts. There was some overlap between the comparisons, allowing prediction of cellular origin of 71 out of the 235 DETs (Fig. 6a, b). Twenty-six were upregulated in KS and the remaining 45 were downregulated. We were not able to predict the cellular origin of 127 of the upregulated transcripts and 37 of the downregulated transcripts, which could be because the transcripts are expressed in many different cell types or that they are only expressed in the KS testis.

Overlap between DETs in the KS testis throughout development

In our previous study20, we identified 211 DETs in the fetal KS testis compared to controls. To investigate changes of the KS testis transcriptome throughout development, we performed transcriptome analysis of testis samples from pre-pubertal KS boys and age-matched controls (Supplementary Fig. S5). The data quality was severely compromised with on average 490,000 reads per sample (Table 1). We did sanity checks, and one of the pre-pubertal KS samples did not have expression of XIST and was excluded (Supplementary Fig. S6). We identified 181 DETs, with 139 being downregulated (Supplementary Fig. S7 and Supplementary Tables S5 and S6).

When we compared the testicular transcriptome profiles at the three different developmental time points in an MDS plot, each age group clustered separately, rather than clustering according to the karyotype (Fig. 7a). Only seven transcripts overlapped between the three developmental time points (Fig. 7b, c, and Supplementary Table S7). Of these, only XIST was shared at all time points. Apart from XIST, none of overlapping DETs were expressed from the X-chromosome. Two transcripts were upregulated in fetal and adult KS (RP11-15H7.2 and RP11-44K6.3). One transcript was downregulated in pre-pubertal and adult KS (GLI1), and the remaining transcripts showed different directions of regulation between two time points (Fig. 7c).

Fig. 7. Overlap in adult Klinefelter syndrome (KS) differentially expressed transcripts (DETs) with fetal and pre-pubertal DETs.

Fig. 7

a MDS plot showing that the different age groups are separated from each other, rather than KS and controls. b Venn plot showing the overlap with the DETs of fetal21, pre-pubertal and adult KS. c Heatmap showing the expression level of the overlapping transcripts in each developmental group. More details can be found in Supplementary Table S7

Discussion

It is intriguing that an extra X-chromosome in KS patients is associated with loss of germ cells, although the adult testicular phenotype with degeneration and hyalinization of seminiferous tubules does not develop until puberty. It is to be expected that chromosome pairing and segregation during meiosis is impaired with the presence of an extra chromosome. However, since the loss of spermatogonia begins before puberty, even as early as during fetal development, other mechanisms must be involved. To bring new insights into the functional mechanisms that result in germ cell loss and testicular degeneration we analyzed the testicular transcriptome. It was admittedly challenging to obtain informative transcriptome profiles from the archived material. Furthermore, tubular and interstitial compartments of the testis contain many different types of cells. In order to tackle this, we collected all the testicular biopsies from KS men that were available in our archives. However, of the 12 samples available, only 10 could be used for RNA-sequencing and only 3 KS samples were found suitable in the analysis. Moreover, we did not have statistical power to correct for multiple testing, which is normal practice in transcriptome analysis. Instead, we used an un-adjusted p-value and identified 235 DETs potentially involved in the pathogenesis of the KS testicular phenotype.

One of the interesting DETs was DACH2, with a potential function in “reproduction” and “development” according to the GO analysis. The potential involvement of DACH2 in the testicular phenotype of KS men is supported by two studies. One study showed that Dach2 was expressed in the fetal mouse testis, but not in the ovary, with pronounced expression in interstitial cells. Interestingly, the fetal gonadal expression of Dach2 was lost in the Wnt-4 knock-out testis28. Another study identified an association between several rare mutations in the DACH2 gene and premature ovarian failure, which is characterized by an early loss of germ cells29. We validated the protein expression of DACH2 in the adult KS testis, and observed an interesting staining pattern. DACH2 was specifically expressed in a subset of Sertoli cell nuclei in the KS testis, which was not observed in the CMC. This indicates that DACH2 is a marker of immature Sertoli cells in the adult KS testis, which was supported by identification of DACH2 in fetal Sertoli cells and by the majority of DACH2-positive Sertoli cells in the adult KS testis being positive for AMH. Further studies are needed to corroborate this finding.

Interestingly, FAM9A, also appeared to be linked to the somatic cell maturation stage. FAM9A was expressed in a subset of Leydig cells, which appeared to be less mature than normal adult Leydig cells, which express INSL326, and FAM9A was also identified in fetal Leydig cells. FAM9A was, in addition, expressed in all nuclei of Sertoli cells, but not at the fetal stage. The difference in the subcellular localization between Leydig- and Sertoli cells indicates that FAM9A has different functions in the two cell types. Nevertheless, both DACH2 and FAM9A seem to mark less mature somatic cell types in the KS confirming previous observations of immature Sertoli- and Leydig cells in the adult KS testis25,26. This hypothesis is further supported by the enrichment of GO terms, which revealed overrepresentation of terms related to “reproduction”, “development”, and “response to hormone”. Dysregulation of these pathways in general fits very well with the KS phenotype.

Another interesting upregulated KS transcript was PNMA5, which recently was shown to induce apoptosis30. According to the GTex portal (http://www.gtexportal.org/home/gene/PNMA5, accessed 7 Sept 2017). and the Human Protein Atlas (http://www.proteinatlas.org/ENSG00000198883-PNMA5/tissue, accessed 7 Sept 2017), PNMA is expressed exclusively in the testis and brain. Yet another pro-apoptotic protein upregulated in the KS samples was AIFM331. Increased apoptosis could be a very relevant mechanism responsible for degeneration of the KS testis but when KS samples were stained with cleaved PARP (cPARP), a known marker of apoptotic cells, we only observed very few positively stained cells (data not shown).

When we compared our 235 KS DETs with previous transcriptome studies of KS samples, the overlap consisted of only 12 transcripts. Three DETs, were identified in studies performed on peripheral blood1316 and the remaining nine were identified in studies performed on adult testis biopsies22,23. Since the control used in the testicular studies22,23 included complete spermatogenesis, the overlap with our study, using CMC, was expected to be limited. Moreover, the microarray approach used in these studies would not detect all types of transcripts (e.g., lncRNAs) contrary to the RNA-sequencing approach we used. In line with our previous study of fetal KS samples20, we indeed observed an enrichment of lincRNAs among the upregulated transcripts in the adult KS testis. This indicates that dysregulation of lincRNAs may play a central role in the KS testis.

Among the protein-coding DETs, three overlapped with previous studies; DLK1, FAM9A and FBOXO43, which all have been described previously in relation to testicular function. In the mouse, Fbxo43 is expressed solely in the testis and ovary32, and was shown to be involved in meiosis I progression in rodent spermatocytes33,34. DLK1 is a marker of immature Leydig cells26 and its upregulation detected in the previous study23 and in our present study is consistent with the presence of more immature Leydig cells in the KS testis. In line with this, expression of FAM9A, which has been shown to be testis-specific35, was also found in less mature Leydig cells in our present study. Taken together, these results indicate that the somatic compartment in the adult KS testis is less mature than that in CMC.

When comparing the KS DETs in fetal, pre-pubertal and adult testes, the identified overlap was limited, indicating that different mechanisms are responsible for the testicular architecture and cellular composition at the different developmental stages. We did see an overlap in dysregulation of JAK3 and GLI1. JAK3 was upregulated in the pre-pubertal samples but downregulated in the adult samples, and GLI1 was downregulated both in pre-pubertal and adult samples. A relationship between GLI1 and JAK3 was identified in acute T-cell lymphoblastic leukemia, where their expression levels showed a positive correlation36. As GLI1 is a component of Hedgehog signaling, which regulates development and cancer progression37, downregulation of this transcript in both pre-pubertal and adult samples, as well as downregulation of JAK3 in the adult samples, may indicate a disturbance in the development of the KS testis. Indeed, Hedgehog signaling within the primary cilia of Sertoli cells from adult KS samples has previously been described to be different to that of Sertoli cells in tubules with ongoing spermatogenesis38. In our previous study of the fetal KS testis transcriptome20, we found enrichment of X-chromosomal DETs, which we could not recapitulate in the adult (or pre-pubertal) KS testis. This indicates that the effect of the extra X-chromosome is more direct in fetal life than in the adult. The adult KS testis consequently seems a consequence of the disturbed fetal gonadal development caused directly by the extra X-chromosome.

Based on our results we hypothesize that the overexpressed genes from the extra X-chromosome in patients with KS are directly causing changes in the testicular transcriptome primarily in fetal life, leading to the initiation of the germ cell loss, gonadal dysgenesis, and subsequent failure of the differentiation of the somatic cells, which consequently appears immature in the adult KS testis. Clearly our study was limited by lack of power due to compromised quality of the isolated RNA. Hopefully, technical advancements in the field will allow future studies to isolate RNA of better quality. Future studies should also focus on including more samples, as the individual variation in testicular development besides variations in cellularity is quite substantial. The present study nevertheless provided reference data for further mechanistic studies, and could also have some clinical implications concerning management of patients with KS. Our results indicate that intervention by supporting or stimulating development of the testicular somatic niche already during childhood could increase chances of fertility in adulthood. Before puberty, many boys with KS still have germ cells in the testis that with proper support by somatic cells might enter spermatogenesis. Such interventions, however, need to be investigated before they can be considered.

In conclusion, we were able to analyze the transcriptome of a total of 24 adult KS testis and controls. Enrichment analysis and protein expression patterns showed disturbed maturation of Sertoli-  and Leydig cells. We identified enrichment of lincRNAs, but not of X-chromosomal transcripts, indicating an indirect effect of the supernumerary X-chromosome. Furthermore, the adult testicular KS transcriptome showed a very limited overlap with that of pre-pubertal and fetal KS testis, indicating that distinct processes occur at these stages of development. Our study indicates that Sertoli-  and Leydig cells in the testis of adult men with KS are immature and that impairment of testicular function has its origin early in development.

Materials and methods

Tissue samples

The use of testicular tissue for this project was approved by a regional medical and research ethics committee (permit no. H-2-2014-103) and the Danish Data Protection Agency (no. 2012-58-0004, local no. 30-1482, I-Suite 03696). The testis samples were collected between 1976 and 2014. Following surgical excision, the samples were immediately fixed in different fixatives, dehydrated, and embedded in paraffin (Table 1). The blocks were stored either at +4 °C or −20 °C until sectioning.

Immunohistochemistry (IHC)

Details on antibodies and detection reagents are shown in Supplementary Table S8.

IHC staining with anti-MAGE-A4 and anti-cPARP antibodies was performed essentially as described before39. For MAGE-A4, staining was performed on testes from ten adult men with KS, five with CMC testicular histology, five with Sertoli-cell-only (SCO), and four with full spermatogenesis (Table 1). In brief, paraffin-embedded sections were deparaffinized and rehydrated. Antigen retrieval was accomplished by microwaving the sections for 15 min in unmasking buffer. Then sections were incubated with 2% non-immune goat serum (Zymed Histostain Kit, Life Technologies, CA, USA) to minimize cross-reactivity. The primary antibody was added and incubated overnight at +4 °C, and then the sections were incubated with biotinylated goat anti-mouse IgG (MAGE-A4) or biotinylated goat-anti-rabbit (cPARP), before a peroxidase-conjugated streptavidin complex was used as a tertiary layer (Zymed Histostain Kit). Visualization was performed with amino ethyl carbasole (Zymed Histostain Kit).

Staining with anti-DACH2 and anti-FAM9A were performed on testes from two adult men with KS, three with full spermatogenesis and three with CMC testicular histology, and staining with anti-AMH was performed on testes from two adult men with KS (Supplementary Table S9), essentially as described before40. In brief, sections were subjected to pressure cooking-induced antigen retrieval in unmasking buffer at 110 °C for 30 min. Unspecific binding was blocked with 0.5% skimmed milk in TBS. Sections were incubated overnight with primary antibody diluted in skimmed milk at +4 °C. Horse anti-rabbit IgG HRP (ImmPRESS detection kit, Vector laboratories, CA, USA) was applied for 30 min followed by development with diaminobenzidin DAB (ImmPress detection kit) and nuclear counterstaining with Mayer’s Hematoxylin. Control sections with omission of primary antibody were all negative (data not shown).

Double immunofluorescence

Details of antibodies and detection reagents are shown in Supplementary Table S8. Staining was performed on a testis sample from an adult man with KS (Supplementary Table S9) essentially as described before40. In brief, following pressure cooking treatment as described for IHC, the section was incubated with horse serum diluted in PBS containing 5% (w/v) BSA. The anti-FAM9A antibody was applied and the slides were left overnight at +4 °C and 1 h at room temperature. The section was incubated with peroxidase-conjugated chicken anti-rabbit secondary antibody (Sigma-Aldrich, MO, USA) for 30 min followed by incubation with Tyramide Cy3 (Perkin Elmer, MA, USA) for 10 min. Antigen retrieval with pressure cooker, blockade with horse serum, and incubation with primary antibody was repeated for the anti-INSL3 antibody. The section was then incubated with peroxidase-conjugated chicken anti-rabbit secondary antibody followed by incubation with Tyramide Fluorescien (Perkin Elmer) for 10 min. Finally, the section was counterstained with DAPI (Sigma-Aldrich). The section was imaged with an Olympus BX61 microscope, captured using the Cell Sense Dimensions V1.6 software (Olympus Ltd., Ballerup, Denmark) and processed in Adobe Photoshop 6.0.

Quantification of cellularity

Adobe Photoshop CC 2014 (Adobe Systems Inc, CA, USA) was used to assess the cellularity of each sample. The area of tubules with germ cells was evaluated on the basis of the MAGE-A4-staining and was quantified with the “lasso” tool. SCO tubules, areas of Leydig cells, blood vessels, hyalinized tubules and connective tissue were identified by visual inspection also measured with the “lasso” tool.

Tissue sectioning

Fixed, paraffin-embedded tissue was sectioned on a microtome at a thickness of 10 μm and placed in Eppendorf tubes at +4 °C until RNA extraction. A total of 20–50 μm of tissue was used. Serial sections of each tissue were collected before and after the collection on membranes and stored at −20 °C for subsequent histological assessment of cellularity.

RNA extraction

Total RNA was extracted using the Recover All Total Nucleic Acid Isolation Kit for FFPE (Thermo Fisher Scientific, MS, USA) according to the manufacturer’s recommendations. RNA was eluted in LoBind tubes using nuclease-free water. To assess the quantity and quality of the samples, the Qubit RNA HS Assay Kit (Thermo Fisher Scientific) and the Agilent RNA 6000 Pico Kit (Agilent Technologies, CA, USA), respectively, were used.

Library preparation

The Ovation Human FFPE RNA-Seq Multiplex Systems (NuGEN, Leek, Netherlands) were used for library preparation from 150–200 ng of total RNA according to the manufacturer’s recommendations with the following modifications: The cDNA samples were fragmented to yield sizes of approximately 150 bp using the Covaris E210 sonicator (Covaris Ltd., Brighton, UK). For the final library amplification, 20 cycles of amplification were used. An extra DNA purification was performed with a 1.4 times overload of Agencourt AMPure XP beads (Beckman Coulter, IN, USA) to get rid of adapters and primers. Samples were pooled in groups of five with equal amount of each. We performed 150 nt paired-end read sequencing on the Illumina HiSeq 2000 sequencing platform (Illumina, CA, USA).

Analysis of RNA-sequencing data

Reads were demultiplexed using a custom perl script and adapter sequences trimmed using AdapterRemoval v1.541. Reads were mapped to the human reference genome (GRCh38) in which the pseudoautosomal region (PAR) on the Y-chromosome (PARY; chrY:10001-2781479, chrY:56887903-57217415) were masked using STAR v. 2.5.2b42. Read counts were summarized using HTseq v. 0.6.043.

Data were analyzed in the R software v. 3.3.2 (http://www.r-project.org). Briefly, the count data was loaded into the limma/edgeR package44,45 and heatmaps were generated with the package gplots46 using the heatmap.2 function with the “complete” hierarchical clustering method. Based on this analysis, seven KS samples and two CMC were excluded (Fig. 1a and Supplementary Fig. S1). To avoid accidental findings, we decided to include only transcripts with at least 1 count per million (CPM) in at least two samples in the overexpressing group. This left a total of 22,020 transcripts in the analysis. In Table 1, the library sizes are shown for all samples.

The R package limma47 was used to identify DETs and fold changes were calculated as the mean expression values for the two groups of interest and then further log2-transformed. A p-value < 0.01 and a log2 fold change (logFC) ≥ 1.5 or ≤ 1.5 was used as cutoff. Enrichment analyses were performed using mroast and camera functions. XCI status was acquired from ref. 24 and GENCODE transcript biotypes were obtained from Ensembl using the biomaRt package in R48,49. A hypergeometric test using the phyper function in R was used to test for enrichment of transcript biotypes. Expression of known Sertoli, Leydig, germ cell, and peritubular/blood cell markers in KS, CMC, SCO, and Norm were plotted with GraphPad Prism version 4 (GraphPad Software Inc, CA, USA).

DETs were identified between KS, CMC, SCO, and Norm as performed with the KS vs. CMC, and the overlap was identified in R. The relative expression level of transcripts that overlapped was visualized with the heatmap.2 function using the “manhattan” distance matrix and the “ward.D2” hierarchical clustering method. The overlap was visualized using the interactive venn website (http://www.interactivenn.net/, accessed 2 Sept 2017). Overrepresentation of GO terms50 (the “Biological Process” terms) was tested using the DAVID Bioinformatics Resources51,52.

Data has been deposited in the GEO public database with the accession number GSE103905.

Electronic supplementary material

Supplementary Tables (131.2KB, docx)
Supplementary Figures (35.2MB, docx)

Acknowledgements

We thank Ana Ricci Nielsen for technical assistance with tissue sectioning and Camilla Tang Thomsen for technical assistance with RNA extraction. This work was supported by the Danish Council for Independent Research | Medical Sciences [grant number DFF-4004-00412 to ERDM] and the Innovation Fund Denmark [grant number 14-2013-4 to K.A.].

Conflict of interest

The authors declare that they have no conflict of interest.

Footnotes

Edited by D. Aberdam

Electronic supplementary material

Supplementary Information accompanies this paper at 10.1038/s41419-018-0671-1.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Bojesen A, Juul S, Gravholt CH. Prenatal and postnatal prevalence of Klinefelter syndrome: a national registry study. J. Clin. Endocrinol. Metab. 2003;88:622–626. doi: 10.1210/jc.2002-021491. [DOI] [PubMed] [Google Scholar]
  • 2.Aksglaede L, Skakkebaek NE, Almstrup K, Juul A. Clinical and biological parameters in 166 boys, adolescents and adults with nonmosaic Klinefelter syndrome: a Copenhagen experience. Acta Paediatr. 2011;100:793–806. doi: 10.1111/j.1651-2227.2011.02246.x. [DOI] [PubMed] [Google Scholar]
  • 3.Bonomi M, et al. Klinefelter syndrome (KS): genetics, clinical phenotype and hypogonadism. J. Endocrinol. Invest. 2017;40:123–134. doi: 10.1007/s40618-016-0541-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Chang S, Skakkebaek A, Gravholt CH. Klinefelter syndrome and medical treatment: hypogonadism and beyond. Horm. (Athens). 2015;14:531–548. doi: 10.14310/horm.2002.1622. [DOI] [PubMed] [Google Scholar]
  • 5.Nieschlag E, et al. The Klinefelter syndrome: current management and research challenges. Andrology. 2016;4:545–549. doi: 10.1111/andr.12208. [DOI] [PubMed] [Google Scholar]
  • 6.Aksglaede L, et al. Natural history of seminiferous tubule degeneration in Klinefelter syndrome. Hum. Reprod. Update. 2006;12:39–48. doi: 10.1093/humupd/dmi039. [DOI] [PubMed] [Google Scholar]
  • 7.Blanco J, Egozcue J, Vidal F. Meiotic behaviour of the sex chromosomes in three patients with sex chromosome anomalies (47,XXY, mosaic 46,XY/47,XXY and 47,XYY) assessed by fluorescence in-situ hybridization. Hum. Reprod. 2001;16:887–892. doi: 10.1093/humrep/16.5.887. [DOI] [PubMed] [Google Scholar]
  • 8.Garcia-Quevedo L, et al. Hidden mosaicism in patients with Klinefelter’s syndrome: implications for genetic reproductive counselling. Hum. Reprod. 2011;26:3486–3493. doi: 10.1093/humrep/der351. [DOI] [PubMed] [Google Scholar]
  • 9.Sciurano RB, et al. Focal spermatogenesis originates in euploid germ cells in classical Klinefelter patients. Hum. Reprod. 2009;24:2353–2360. doi: 10.1093/humrep/dep180. [DOI] [PubMed] [Google Scholar]
  • 10.Yamamoto Y, et al. Morphometric and cytogenetic characteristics of testicular germ cells and Sertoli cell secretory function in men with non-mosaic Klinefelter’s syndrome. Hum. Reprod. 2002;17:886–896. doi: 10.1093/humrep/17.4.886. [DOI] [PubMed] [Google Scholar]
  • 11.Corona G, et al. Sperm recovery and ICSI outcomes in Klinefelter syndrome: a systematic review and meta-analysis. Hum. Reprod. Update. 2017;23:265–275. doi: 10.1093/humupd/dmx008. [DOI] [PubMed] [Google Scholar]
  • 12.Ottesen AM, et al. Increased number of sex chromosomes affects height in a nonlinear fashion: a study of 305 patients with sex chromosome aneuploidy. Am. J. Med Genet Part A. 2010;152A:1206–1212. doi: 10.1002/ajmg.a.33334. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Belling K, et al. Klinefelter syndrome comorbidities linked to increased X chromosome gene dosage and altered protein interactome activity. Hum. Mol. Genet. 2017;26:1219–1229. doi: 10.1093/hmg/ddx014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Huang J, et al. Global transcriptome analysis of peripheral blood identifies the most significantly down-regulated genes associated with metabolism regulation in Klinefelter syndrome. Mol. Reprod. Dev. 2015;82:17–25. doi: 10.1002/mrd.22438. [DOI] [PubMed] [Google Scholar]
  • 15.Zitzmann M, et al. Gene expression patterns in relation to the clinical phenotype in Klinefelter syndrome. J. Clin. Endocrinol. Metab. 2015;100:E518–E523. doi: 10.1210/jc.2014-2780. [DOI] [PubMed] [Google Scholar]
  • 16.Vawter MP, Harvey PD, Delisi LE. Dysregulation of X-linked gene expression in Klinefelter’s syndrome and association with verbal cognition. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 2007;144B:728–734. doi: 10.1002/ajmg.b.30454. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Lee JT. Gracefully ageing at 50, X-chromosome inactivation becomes a paradigm for RNA and chromatin control. Nat. Rev. Mol. Cell Biol. 2011;12:815–826. doi: 10.1038/nrm3231. [DOI] [PubMed] [Google Scholar]
  • 18.Kleinheinz A, Schulze W. Klinefelter’s syndrome: new and rapid diagnosis by PCR analysis of XIST gene expression. Andrologia. 1994;26:127–129. doi: 10.1111/j.1439-0272.1994.tb00773.x. [DOI] [PubMed] [Google Scholar]
  • 19.Wikström AM, et al. Klinefelter syndrome in adolescence: onset of puberty is associated with accelerated germ cell depletion. J. Clin. Endocrinol. Metab. 2004;89:2263–2270. doi: 10.1210/jc.2003-031725. [DOI] [PubMed] [Google Scholar]
  • 20.Winge SB, et al. Transcriptome profiling of fetal Klinefelter testis tissue reveals a possible involvement of long non-coding RNAs in gonocyte maturation. Hum. Mol. Genet. 2018;27:430–439. doi: 10.1093/hmg/ddx411. [DOI] [PubMed] [Google Scholar]
  • 21.Alves MG, et al. Testicular lactate content is compromised in men with Klinefelter Syndrome. Mol. Reprod. Dev. 2016;83:208–216. doi: 10.1002/mrd.22608. [DOI] [PubMed] [Google Scholar]
  • 22.D’Aurora M, et al. Deregulation of sertoli and leydig cells function in patients with Klinefelter syndrome as evidenced by testis transcriptome analysis. BMC Genom. 2015;16:156. doi: 10.1186/s12864-015-1356-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.D’Aurora M, et al. Testis transcriptome modulation in Klinefelter patients with hypospermatogenesis. Sci. Rep. 2017;7:45729. doi: 10.1038/srep45729. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Balaton BP, Cotton AM, Brown CJ. Derivation of consensus inactivation status for X-linked genes from genome-wide studies. Biol. Sex. Differ. 2015;6:35. doi: 10.1186/s13293-015-0053-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Skakkebaek NE. Two types of tubules containing only Sertoli cells in adults with Klinefelter’s syndrome. Nature. 1969;223:643–645. doi: 10.1038/223643a0. [DOI] [PubMed] [Google Scholar]
  • 26.Lottrup G, et al. Expression patterns of DLK1 and INSL3 identify stages of Leydig cell differentiation during normal development and in testicular pathologies, including testicular cancer and Klinefelter syndrome. Hum. Reprod. 2014;29:1637–1650. doi: 10.1093/humrep/deu124. [DOI] [PubMed] [Google Scholar]
  • 27.Harrow J, et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 2012;22:1760–1774. doi: 10.1101/gr.135350.111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Naillat F, et al. Identification of the genes regulated by Wnt-4, a critical signal for commitment of the ovary. Exp. Cell Res. 2015;332:163–178. doi: 10.1016/j.yexcr.2015.01.010. [DOI] [PubMed] [Google Scholar]
  • 29.Bione S, et al. Mutation analysis of two candidate genes for premature ovarian failure, DACH2 and POF1B. Hum. Reprod. 2004;19:2759–2766. doi: 10.1093/humrep/deh502. [DOI] [PubMed] [Google Scholar]
  • 30.Lee YH, Pang SW, Poh CL, Tan KO. Distinct functional domains of PNMA5 mediate protein-protein interaction, nuclear localization, and apoptosis signaling in human cancer cells. J. Cancer Res. Clin. Oncol. 2016;142:1967–1977. doi: 10.1007/s00432-016-2205-5. [DOI] [PubMed] [Google Scholar]
  • 31.Xie Q, Lin T, Zhang Y, Zheng J, Bonanno JA. Molecular cloning and characterization of a human AIF-like gene with ability to induce apoptosis. J. Biol. Chem. 2005;280:19673–19681. doi: 10.1074/jbc.M409517200. [DOI] [PubMed] [Google Scholar]
  • 32.Shoji S, et al. Mammalian Emi2 mediates cytostatic arrest and transduces the signal for meiotic exit via Cdc20. EMBO J. 2006;25:834–845. doi: 10.1038/sj.emboj.7600953. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Perrard MH, Chassaing E, Montillet G, Sabido O, Durand P. Cytostatic factor proteins are present in male meiotic cells and beta-nerve growth factor increases mos levels in rat late spermatocytes. PLoS ONE. 2009;4:e7237. doi: 10.1371/journal.pone.0007237. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Gopinathan L, et al. Emi2 is essential for mouse spermatogenesis. Cell Rep. 2017;20:397–708. doi: 10.1016/j.celrep.2017.06.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Martinez-Garay I, et al. A new gene family (FAM9) of low-copy repeats in Xp22.3 expressed exclusively in testis: implications for recombinations in this region. Genomics. 2002;80:259–267. doi: 10.1006/geno.2002.6834. [DOI] [PubMed] [Google Scholar]
  • 36.Dagklis A, et al. Hedgehog pathway activation in T-cell acute lymphoblastic leukemia predicts response to SMO and GLI1 inhibitors. Blood. 2016;128:2642–2654. doi: 10.1182/blood-2016-03-703454. [DOI] [PubMed] [Google Scholar]
  • 37.Altaba A, Mas C, Stecca B. The Gli code: an information nexus regulating cell fate, stemness and cancer. Trends Cell Biol. 2007;17:438–447. doi: 10.1016/j.tcb.2007.06.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Nygaard MB, Almstrup K, Lindbaek L, Christensen ST, Svingen T. Cell context-specific expression of primary cilia in the human testis and ciliary coordination of Hedgehog signalling in mouse Leydig cells. Sci. Rep. 2015;5:10364. doi: 10.1038/srep10364. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Blomberg Jensen M, et al. Vitamin D receptor and vitamin D metabolizing enzymes are expressed in the human male reproductive tract. Hum. Reprod. 2010;25:1303–1311. doi: 10.1093/humrep/deq024. [DOI] [PubMed] [Google Scholar]
  • 40.Mitchell RT, et al. Xenografting of human fetal testis tissue: a new approach to study fetal testis development and germ cell differentiation. Hum. Reprod. 2010;25:2405–2414. doi: 10.1093/humrep/deq183. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Lindgreen S. AdapterRemoval: easy cleaning of next-generation sequencing reads. BMC Res. Notes. 2012;5:337. doi: 10.1186/1756-0500-5-337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Dobin A, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21. doi: 10.1093/bioinformatics/bts635. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Anders S, Pyl PT, Huber W. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–169. doi: 10.1093/bioinformatics/btu638. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.McCarthy DJ, Chen Y, Smyth GK. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res. 2012;40:4288–4297. doi: 10.1093/nar/gks042. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–140. doi: 10.1093/bioinformatics/btp616. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.gplots: Various R Programming Tools for Plotting Data. R package version 3.0.1. http://CRAN.R-project.org/package=gplots
  • 47.Ritchie ME, et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucl. Acids Res. 2015;43:e47. doi: 10.1093/nar/gkv007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Durinck S, et al. BioMart and bioconductor: a powerful link between biological databases and microarray data analysis. Bioinformatics. 2005;21:3439–3440. doi: 10.1093/bioinformatics/bti525. [DOI] [PubMed] [Google Scholar]
  • 49.Durinck S, Spellman PT, Birney E, Huber W. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat. Protoc. 2009;4:1184–1191. doi: 10.1038/nprot.2009.97. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Ashburner M, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 2000;25:25–29. doi: 10.1038/75556. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Huang DW, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucl. Acids Res. 2009;37:1–13. doi: 10.1093/nar/gkn923. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 2009;4:44–57. doi: 10.1038/nprot.2008.211. [DOI] [PubMed] [Google Scholar]

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