An integrated transcriptomics-guided genome-wide promoter analysis and next-generation proteomics approach to mine factor(s) regulating cellular differentiation

Abstract

Differential next-generation-omics approaches aid in the visualization of biological processes and pave the way for divulging important events and/or interactions leading to a functional output at cellular or systems level. To this end, we undertook an integrated Nextgen transcriptomics and proteomics approach to divulge differential gene expression of infant and pubertal rat Sertoli cells (Sc).Unlike, pubertal Sc, infant Sc are immature and fail to support spermatogenesis. We found exclusive association of 14 and 19 transcription factor binding sites to infantile and pubertal states of Sc, respectively, using differential transcriptomics-guided genome-wide computational analysis of relevant promoters employing 220 Positional Weight Matrices from the TRANSFAC database. Proteomic SWATH-MS analysis provided extensive quantification of nuclear and cytoplasmic protein fractions revealing 1,670 proteins differentially located between the nucleus and cytoplasm of infant Sc and 890 proteins differentially located within those of pubertal Sc. Based on our multi-omics approach, the transcription factor YY1 was identified as one of the lead candidates regulating differentiation of Sc.YY1 was found to have abundant binding sites on promoters of genes upregulated during puberty. To determine its significance, we generated transgenic rats with Sc specific knockdown of YY1 that led to compromised spermatogenesis.

Keywords: SWATH-MS; TRANSFAC; cellular differentiation; multi-omics; sertoli cell.

Figure 1

Workflow used for (A) TFBS analysis using TRANSFAC database. (B) Comprehensive proteome quantification using SWATH analysis.

Figure 2

Transcriptomic analysis and TFBS analysis using TRANSFAC database. (A) Volcanic map representing the genes differentially expressed in infant and pubertal Sc of rat as obtained from microarray analysis. Positive y-axis represents the genes up regulated in pubertal Sc as compared to infant Sc. Similarly, negative y-axis represents the genes down regulated in pubertal Sc as compared to infant Sc. P < 0.05 as represented by the x-axis. (B) Pie chart showing the TFBS found to be in high abundance over the promoters of up regulated and down regulated genes of pubertal Sc with respect to infant Sc (comparison was performed with the promoters of control genes displaying no change in expression pattern using χ² test, P < 0.05). (C) List of TFBS found exclusively in high abundance in each case (up and down with reference to pie chart in B). See Supplementary Tables S1 and S2.

Figure 3

TRANSFAC analysis (A) Heat map showing abundance of each TFBS on the promoters of each gene. (B) Heat map showing positional abundance of each TFBS with reference to TSS cumulatively along whole promoter set. (C) Bar graph showing promoter count and binding against their corresponding promoter set (Binding count represents total number of a particular TFBS located within up and down-regulated gene-set promoter. Promoter count is the number of promoters found in a gene-set promoter (up or down), in which a particular TFBS is present at least once). See Supplementary Tables S3–S5.

Figure 4

Depiction of interacting partners (build using STRING database) associated with the TFBS obtained from TRANSFAC analysis. (A) Up network and (B) down network. See Supplementary Table S6.

Figure 5

Heat maps depicting comprehensive proteome quantification profile comparison of nuclear and cytoplasmic extracts of infant (5 days old) and pubertal (12 days old) Sc. (FDR < 5%, peptide confidence > 95%, P < 0.05). (A) Five-day nucleus vs 5-day cytoplasm. (B) Five-day nucleus vs 12-day nucleus. (C) Twelve-day nucleus vs 12-day cytoplasm. (D) Five-day cytoplasm vs 12-days cytoplasm. See Supplementary Table S7.

Figure 6

Depiction of comprehensive PTM analysis. Each modification on a single protein has been recognized as a unique modification for representation (red colour represents presence and blue colour represents absence of each modification). (A) Heat map depicting comprehensive PTM analysis of each proteome. (B) Pie chart showing number of PTMs identified in each sample set. (C) Categorical representation of different PTMs. See Supplementary Tables S9 and S10.

Figure 7

In vivo validation of the role of YY1 in Sc differentiation (A) Nuclear localization of YY1 in cultured pubertal Sc. (B) Western blot showing knockdown of YY1 in knockdown (YY1-KD) animals compared to age matched wild type (control) animals. (C) Real-time PCR analysis showing mRNA levels of Amh and Gdnf. (D) Histology of YY1-KD and control animals (Luc-KD) showing reduced seminiferous tubule diameter. (E) Quantitative analysis of seminiferous tubule diameter and sperm count of YY1-KD animals compared to Luc-KD animals. The animals used for real-time PCR, western blot, sperm count and histological analysis were >8 weeks old. Error bars were represented as ±SEM, n = 3. Statistical significance was determined using Student’s t-test. *P < 0.05, ***P < 0.001.

Figure 8

Transcriptome analysis of YY1 knockdown animals. (A) Heat map showing fold change of each differentially expressed gene in testis of YY1 knockdown animal as compared to the age matched Luc-KD control animals. (B) Representation of the YY1 binding sites over the promoters (±2 kb across TSS) of the differentially expressed genes (those having at least one YY1 binding site) along with their fold change in YY1-KD animals. (C) GO analysis of the differentially expressed genes in YY1-KD animals. See Supplementary Table S11.