Expression profiling of WD40 family genes including DDB1- and CUL4- associated factor (DCAF) genes in mice and human suggests important regulatory roles in testicular development and spermatogenesis
BMC Genomics volume 21, Article number: 602 (2020)
The WD40-repeat containing proteins, including DDB1–CUL4-associated factors (DCAFs), are abundant and conserved proteins that play important roles in different cellular processes including spermatogenesis. DCAFs are subset of WD40 family proteins that contain WDxR motif and have been proposed to function as substrate receptor for Cullin4-RING-based E3 ubiquitin ligase complexes to recruit diverse proteins for ubiquitination, a vital process in spermatogenesis. Large number of WD40 genes has been identified in different species including mouse and human. However, a systematic expression profiling of WD40 genes in different tissues of mouse and human has not been investigated. We hypothesize that large number of WD40 genes may express highly or specifically in the testis, where their expression is uniquely regulated during testis development and spermatogenesis. Therefore, the objective of this study is to mine and characterize expression patterns of WD40 genes in different tissues of mouse and human with particular emphasis on DCAF genes expressions during mouse testicular development.
Publically available RNA sequencing (RNA seq) data mining identified 347 and 349 WD40 genes in mouse and human, respectively. Hierarchical clustering and heat map analyses of RNA seq datasets revealed differential expression patterns of WD40 genes with around 60–73% of the genes were highly or specifically expressed in testis. Similarly, around 74–83% of DCAF genes were predominantly or specifically expressed in testis. Moreover, WD40 genes showed distinct expression patterns during embryonic and postnatal testis development in mice. Finally, different germ cell populations of testis showed specific patterns of WD40 genes expression. Predicted gene ontology analyses revealed more than 80% of these proteins are implicated in cellular, metabolic, biological regulation and cell localization processes.
We have identified large number of WD40 family genes that are highly or specifically expressed in the testes of mouse and human. Moreover, WD40 genes have distinct expression patterns during embryonic and postnatal development of the testis in mice. Further, different germ cell populations within the testis showed specific patterns of WD40 genes expression. These results provide foundation for further research towards understanding the functional genomics and molecular mechanisms of mammalian testis development and spermatogenesis.
The WD40-repeat (WDR) containing proteins are characterized by the presence of four or more repeats of 40–60 amino acids stretches that end in tryptophan (W)-aspartate (D) dipeptides [1, 2]. The WDR proteins are most abundant and conserved proteins with critical roles in diverse cellular processes including signal transduction, transcription regulation, DNA damage response, histone modification, cell cycle control, protein degradation and apoptosis [1,2,3,4,5,6,7]. The importance of WDR proteins, including DDB1–CUL4-associated factors (DCAFs), is not only demonstrated by their involvement in a diverse array of essential cellular processes, but is also revealed by their association with several human diseases [3, 5, 7,8,9,10,11,12]. The WD40 repeats fold into β-propeller structure, mostly comprising of seven WD40 repeats, which confer great potential of diverse protein-protein and protein-DNA interactions to form functional multisubunit complexes [5,6,7]. The genes encoding WDR proteins constitute one of the largest families of genes in the eukaryotic genomes [13,14,15,16,17]. Several systematic genome-wide investigations have been performed to identify and characterize WDR protein encoding genes in human, chimpanzee, mouse, silkworm, plant species and yeast [13, 14, 16,17,18,19,20,21]. Those investigations have identified 262 non-redundant WDR protein coding genes in human , 241 WDR protein coding genes in chimpanzee, 265 WDR protein coding genes in mouse, 172 WDR protein coding genes in silkworm , 743 WDR protein coding genes in wheat , 237 WDR protein coding genes in Arabidopsis , 200 WDR protein coding genes in rice  and 83 WDR protein coding genes in yeast .
A subgroup of WDR proteins that contain a conserved WDxR motif (also known as DWD or DxR box) within the WD40-repeat is collectively known as DCAFs or DDB1-binding/WD40 domain (DWD) containing proteins or CUL4–DDB1-associated WDR (CDW) proteins [23,24,25]. The WDxR motifs within the WDR proteins bind to Damaged DNA Binding 1 (DDB1) protein . Most of the DCAF proteins contain two WDXR motifs that are positioned between successive propeller blades and serve as an interaction site for DDB1 protein in the Cullin4-RING-based E3 ubiquitin ligase (CRL4) complexes [24, 25]. However, a few DCAF proteins such as DCAF15, DCAF16, DCAF17, DET1 and DDB1 associated 1 (DDA1) and de-etiolated homolog 1 (DET1) lack the conserved WD40 motif or other known protein interaction domains, but they can still interact with DDB1 [23,24,25,26]. The DCAF family proteins have been reported to serve as substrate receptors for the CRL4 complexes to recruit diverse proteins for ubiquitination and thus confer specificity to CRL4s [23, 25, 27, 28]. Protein ubiquitination is a vital reversible post-translational protein modification process that regulates broad range of cellular and developmental processes through proteolytic or non-proteolytic actions [29,30,31,32,33,34]. In this process, a small highly conserved ~ 8.5 kDa protein (76-amino acid) known as ubiquitin is covalently attached to target proteins by the sequential action of three enzymatic reactions involving ubiquitin-activating enzyme (E1), ubiquitin-conjugating enzyme (E2) and ubiquitin ligase enzyme (E3), in an ATP-dependent manner [32, 35].
Testis is the major male sex organ in which spermatozoa are produced from spermatogonia through a complex and highly regulated molecular and cellular processes, including ubiquitination [33, 34, 36, 37]. Several independent studies have shown the importance of different WDR proteins, including DCAFs, during spermatogenesis [38,39,40,41,42,43,44,45,46]. In addition, increasing number of studies have shown the significance of ubiquitination in the regulation of normal spermatogenesis [33, 34, 47, 48]. Microarray data mining and expression profiling of ubiquitin E3 ligases (E3s) in the mouse showed expression of 340 putative E3s in the testis including 73 of those E3s were highly or specifically expressed in the testis during different stages of spermatogenesis, suggesting their diverse roles in spermatogenesis . These important findings indicate that WD40 family genes, including DCAF subfamily genes, may have much more specific and complex expression patterns as well as physiological functions during the testicular development and spermatogenesis. Thus, it necessitates for a systematic investigation of WD40 family genes expression analyses across various tissues.
Considering the abundance of WDR proteins and their important roles in many vital cellular processes and disease pathology, we systematically conducted mining and expression profiling of the putative WDR protein encoding genes, including DCAFs, in different tissues of mouse and human with particular emphasis on testicular expression of DCAFs. Mining of mouse and human genome databases and literature search identified 347 and 349 WD40 genes in mouse and human genomes, respectively. Among these WD40 family genes, 60 and 65 belonged to DCAF subfamily genes in the genomes of mouse and human, respectively. RNA seq data analyses detected 289 to 313 WD40 genes with varying transcript levels across different tissues of mouse and human. Interestingly, large number of the WD40 genes was highly or specifically expressed in the testis, suggesting their important functions in the testis. Real time RT-PCR analyses of the mouse DCAF genes for different tissues showed differential expression of these genes with a large proportion of the genes was highly or specifically expressed in the testis. Further, these DCAF genes showed differential expression patterns during different stages of post-natal testis development in the mouse. Together, our data implicate intricate expression patterns for WD40 genes, particularly DCAF genes, reflecting complexity of spermatogenesis and also provide a valuable source to further investigate their functions and potential utilization as infertility biomarkers and/or to develop male contraceptive.
Mining of WD40 family genes from the mouse and human genomes
To mine putative WD40 protein encoding genes from the mouse and human genomes, we searched for WD40, DWD, CDW, DCAF, DDB1/2 and CUL4 terms in the publically available databases, genome browsers and scientific publications browser PubMed. Careful selection of WD40 genes resulted in identification of 347 and 349 non-redundant genes in the mouse and the human genomes, respectively (Fig. 1, Supplementary Table S1). Among them, 309 (~ 80%) putative WD40 genes were homologues between mouse and human (Fig. 1, Supplementary Table S1). Such a high proportion of WD40 gene homologues between the two species suggest their conserved roles in different cellular and developmental processes in mouse and human. Among the WD40 family genes, 60 genes (~ 17.3%) in mouse and 65 genes (~ 18.6%) in human genomes belong to DCAF subfamily genes (Table 1). Chromosomal localization analysis of DCAF subfamily genes in mouse genome showed that the genes are broadly distributed on all the chromosomes except chromosomes 3, 17, 18 and Y (Table 1). Similarly, the human genome also showed wide distribution of DCAF genes on all the chromosomes with exception of chromosomes 13, 18, 22 and Y (Table 1). Number of the DCAF genes present on each chromosome varied from 1 to 9 with maximum number of the DCAF genes is present on chromosome 1 in both the species (Table 1). Homology search for the DCAF genes corresponding to mouse and human genes in different species identified 61 DCAF genes in Bos taurus, 45 in Danio rerio, 60 in Rattus norvegicus, 55 in Xenopus tropicalis, 5 in Drosophila melanogaster and 3 in Saccharomyces cerevisiae (Supplementary Table S2).
RNA sequencing data analyses of WD40 family genes identified testis-enriched genes in mouse and human
Gene expression profile can provide important clues about the gene function. To investigate the mRNA abundance profiles of WD40 family genes, raw RNA seq data of mouse and human were collected from the FANTOM5 and GTEx data portals as described in materials and methods. The RNA seq data analyses of FANTOM5 datasets identified 292 transcripts of WD40 genes out of 347 WD40 genes in mouse and 289 transcripts of WD40 genes out of 349 WD40 genes in human. Whereas, analysis of the GTEx RNA seq dataset from human detected 313 WD40 gene transcripts out of total 349 WD40 genes. Hierarchical clustering and heat map analyses of mouse and human RNA seq datasets showed differential transcript abundance of WD40 genes in various tissues of mouse and human (Fig. 2a, b, c) with significantly large number of WD40 genes were highly or specifically expressed in the testis as compared to other tissues such as lung, heart, liver, brain, kidney, colon, pancreas, prostate, epididymis, ovary, oviduct and uterus (Fig. 2a, b, c). According to the FANTOM5 datasets, the percentages of highly expressed WD40 genes in the mouse and human testes were 59.6 and 64.4%, respectively (Fig. 2a, b). Similarly, the human GTEx dataset showed differential expression patterns of WD40 genes across different tissues with significantly large number of WD40 genes (73.5%) was highly or specifically expressed in the testis (Fig. 2c). Further analyses of mouse and human FANTOM5 RNA seq datasets detected 58 each transcripts of DCAF subfamily genes out of total 60 and 65 DCAFs in mouse and human, respectively. Hierarchical clustering and heat map analyses of the 58 DCAF genes from each of mouse and human RNA seq datasets displayed differential expression patterns across different tissues of both the species with considerably higher proportion of DCAF genes showed high abundance of transcripts in testis as compared to other tissues analysed in this study (Fig. 3a, b). Around 74 and 83% DCAF genes in mouse and human, respectively, showed specific or notably high expression in testis as compared to other tissues examined (Fig. 3a, b). In concordance, analysis of the GTEx dataset of human DCAF genes also displayed differential expression patterns with large fraction (~ 83%) of the genes were highly or specifically expressed in the testis (Fig. 3c). Based on DCAF gene transcripts abundance in testis, a clear grouping of highly or specifically expressed DCAFs and weakly expressed DCAFs was observed (Fig. 3a, b, c). Among the highly or specifically expressed DCAF genes in the testes of mouse and human, 41 genes were common, suggesting conserved roles in both species.
DCAF subfamily genes are differentially expressed across the major tissues of mouse and human
To validate the RNA seq data, semi-quantitative RT-PCR was performed using gene specific primers for 56 and 57 DCAF subfamily genes of mouse and human, respectively, as described in supplementary methods. We used 10 and 17 different major tissues from adult mouse and human, respectively, as described in materials and methods. As shown in the Fig. S1A & S1B, all the DCAF genes are differentially expressed across different tissues of mouse and human, respectively. In the mouse testis, the mRNA transcripts for majority the DCAF genes were detected from very low to very high levels, with very few genes showed undetectable levels (Fig. S1A). Some of the DCAF genes like Gnb2, Rbbp7, Wdr26, Sum1, Wsb1, Nil1 and Eed showed almost equal level of transcripts among all the tissues analysed, suggesting that they may have common functions that are required for all the tissues (Fig. S1A). The mRNA transcript levels of the genes Ddb2, Ercc8, Dcaf5, Dcaf10, Det1, Katnb1, Wdr51, Wdr51b, Wdr12, Tle3 and Nup43 were highest in testis with moderate to very low levels in other tissues, implying specific or major roles of these genes during spermatogenesis (Fig. S1A). Interestingly, the Cdt2 gene transcripts were only detected in testis and ovary, suggesting specific and unique role of this gene in gametogenesis (Fig. S1A). Similar expression patterns of human DCAF genes were observed in different human tissues used for this study (Fig. S1B). The β-actin gene and 18S rRNA were used as a house keeping genes as well as loading controls showing equal levels of transcripts among all the tissues analysed (Fig. S1A, B).
We further selected 16 of the highly expressed mouse DCAF genes to confirm their expression by qRT-PCR analysis in 10 different tissues from adult mice. The qRT-PCR results confirmed high mRNA levels of the selected DCAF genes in the mouse testis compare to other tissues analysed (Fig. 4). Genes Wdr12, Wdr51b, Wdr53, Katnb1, Lis1, Tle3, Cdt2, Ddb2, Ercc8, Dcaf5 and Dcaf10 showed very high levels of transcripts ranging from 28 to 450 folds high in the testis in comparison to other tissues (Fig. 4). Very high levels of transcript in testis suggest that those genes may have crucial and specific roles in spermatogenesis. Other genes Pwp1, FbxW8, Det1 and Nup43 showed transcripts abundance ranging from 6 to 14 folds high in the testis while other tissues like brain, ovary and oviduct showed moderate to high transcript levels suggesting that these genes may have shared functions in these tissues (Fig. 4). Expression profiling of the Wsb1 gene across different tissues showed higher expression in brain followed by lung and kidney than testes (Fig. 4).
Expression of DCAF subfamily genes during development of the mouse testis
To explore the mRNA levels of mouse WD40 family and DCAF subfamily genes during normal testicular development, RNA seq data for mouse testes at different developmental stages including embryonic (day 13, 15, 16, 17, and 18), neonate (day 0, 07, 10, 20, and 30), and adult were collected from FANTOM5 repository and analysed. Mining of FANTOM5 dataset from different developmental stages of the mouse testis detected 283 transcripts of WD40 genes. Hierarchical clustering and heat map analyses of the WD40 family and DCAF subfamily genes during different stages of testis development showed diverse expression patterns (Fig. 5a, b). As shown in Fig. 5, varying mRNA levels of WD40 family and DCAF subfamily genes are not only associated with different tissues, but also with the different developmental stages of the testis. According to the expression profiles during different stages of testicular development, the WD40 genes can be classified into three distinct groups. The largest group (159 genes) was highly expressed during post-natal testicular development from day 20 to adult (Fig. 5a). The second group containing 77 genes showed higher expression during embryonic day 13 through neonatal day 10 (Fig. 5a). The third group of 47 WD40 genes is highly enriched during neonatal day 0 through neonatal day 20 after birth (Fig. 5a). Similarly, the DCAF subfamily genes can be classified into two major groups depending upon their expression patterns as observed in the Fig. 5b. The first group of 36 genes showed high levels of transcripts during post-natal development of testis from neonatal day 20 through adult (Fig. 5b). Whereas, the second group of 22 genes showed high levels of transcripts from embryonic day 13 to post-natal day 20 of the testis development (Fig. 5b).
Stage-specific expression of WD40 family and DCAF subfamily genes during mouse spermatogenesis
To further investigate the expression profile of WD40 family and DCAF subfamily genes in different types of germ cell populations in the mouse testis, we used RNA seq datasets derived from Green et al. (Accession: GSE112393) and da Cruz et al. (Accession: PRJNA317251) [50, 51]. Independent mining of RNA seq datasets from Green et al. and da Cruz et al. identified 302 and 255 transcripts of total 347 WD40 genes, respectively. Hierarchical clustering and heat map analyses of the WD40 family and DCAF subfamily genes expressed in different germ cell populations of the mouse testis revealed diverse expression patterns among different spermatogenic cell populations (Fig. 6a, b & S2). Based on the heat map clustering analysis derived from Green et al. data, the WD40 family genes can be classified into three major groups according to their expression patterns in various germ cell populations (Fig. 6a). The first group of the WD40 genes that contained 164 genes were highly expressed in spermatogonia and preleptotene spermatocytes during mitotic stage (Fig. 6a). Second group included 105 genes that showed elevated expression during meiotic stage (Fig. 6a). Finally, the third group of 33 genes showed increased expression in post-meiotic round and elongated spermatids (Fig. 6a). Further analysis of Green et al. dataset for DCAF subfamily genes detected 57 DCAF transcripts with differential expression patterns across different spermatogenic cell populations (Fig. 6b). Depending upon the abundance of DCAF genes mRNA levels and spermatogenic cell populations, hierarchical clustering and heat map analyses of the 57 DCAF genes showed distinct clustering into three major groups that included 40 pre-meiotic, 12 meiotic and 5 post-meiotic genes (Fig. 6b). Similarly, hierarchical clustering and heat map profiling of WD40 gene transcripts from da Cruz et al. dataset displayed distinct expression patterns with four clear clusters based on mRNA abundance in different testicular cell populations (Fig. S2A). The WD40 genes with high abundance of mRNA in spermatogonia and somatic cells (2C) included 50 genes (Fig. S2A). Around 107 genes showed higher expression in meiotic prophase I early stages (leptotene and zygotene; LZ) cell populations (4C). The third cluster contained 44 genes showing increased levels of mRNA in pachytene spermatocytes (PS) (4C) (Fig. S2A). In the round spermatid (RS) population (C), 54 genes were highly expressed as compared to other spermatogenic cells (Fig. S2A). Hierarchical clustering and heat map analyses of DCAF subfamily genes from da Cruz et al. RNA seq dataset also exhibited differential expression patterns of various DCAF gene transcripts across different testicular cell populations (Fig. S2B). Around 18 (~ 30%) of DCAF subfamily genes were predominantly or specifically expressed in spermatogonia and somatic cell populations (2C) (Fig. S2B). More than a half number of DCAF genes (~ 53%) were highly or specifically expressed in leptotene and zygotene (LZ) spermatocyte cell populations (4C) (Fig. S2B). Pachytene spermatocyte (PS) population (4C) showed high or specific expression of around 11 DCAF genes (~ 18%) (Fig. S2B). The number of DCAF genes with high mRNA abundance in round spermatids (RS) population (C) included twelve (~ 20%) genes (Fig. S2B).
Further, hierarchical clustering and heat map analysis of human WD40 family genes and DCAF subfamily genes using Guo et al. RNA seq dataset also showed differential expression patterns in different spermatogenic cell populations (Fig. S3A, B) . According to the levels of WD40 and DCAF genes transcripts in different spermatogenic cells, the target genes can be grouped into three major clusters (Fig. S3A, B). First group of the genes was predominantly expressed in spermatogonia. Second group of the genes showed high transcript levels in spermatocytes and third group of the genes showed high transcript levels in spermatids (Fig. S3A, B).
qRT-PCR confirmed differential expression patterns of DCAF subfamily genes during different stages of post-natal testis development in mouse
To validate the observed differential expression patterns of DCAF subfamily genes in the RNA seq datasets, we randomly selected 12 of the highly expressed DCAF genes in the testis and checked their mRNA levels in mouse testes collected at different ages of 5, 14, 23, 32, 42 and 56 days postpartum (dpp) using qRT-PCR technique. As shown in the Fig. 8, all the selected DCAF genes showed diverse expression patterns during post-natal testis development. Depending upon the expression patterns, DCAF genes can be divided into three broad categories. In first category, low gene expression during early stage of testis development followed by gradual increase in the expression with the age till maturation and then the expression remains constant. The genes in this category include Dcaf5, Ercc8, Katnb1, Lis1, Tle3, Wdr12, Wdr51B and Wdr53 (Fig. 7). Second category of the genes show gradual increase in the transcript levels with the age till certain age, then it decreases until it reaches minimum level at the adult age. Examples of the genes in second category are Pwp1, FbxW8 and Nup43 (Fig. 7). The gene expression pattern in the third category, which includes Wsb1, shows higher expression during early developmental stages of testis and then the gene expression decreases gradually with the advancing age (Fig. 7).
Gene ontology (GO) annotation and network analysis of WD40 proteins
Gene ontology (GO) classification and enrichment analyses of human and mouse WD40 family and DCAF subfamily proteins were performed using PANTHER [53, 54], DAVID Bioinformatics Resources  and Ingenuity Pathways Analysis (IPA). According to PANTHER classification, broad molecular functions were assigned for WD40 and DCAF proteins. Based on the assigned GO terms for biological processes, the results showed putative participation of WD40 proteins in diverse biological processes that were classified into ten major categories (Fig. 8a & S4A, Table S3). Among different categories of biological processes, the WD40 proteins of mouse and human were predominantly participated in cellular processes (~ 130), followed by metabolic processes (~ 60), biological regulation (~ 45) and localization (~ 36) (Fig. 8a & S4A). Similarly, biological function analysis of DCAF proteins from mouse and human using PANTHER classification system classified the DCAF proteins into 10 and 9 biological processes, respectively (Fig. 8b & S4B). Majority of the proteins were involved in cellular process (~ 44%), metabolic process (~ 20%), biological regulation (~ 20%), localization (~ 5%) and developmental process (4%) (Fig. 8b & S4B).
GO enrichment analyses of WD40 family proteins using DAVID analysis revealed more than 290 significant biological process categories, around 100 cellular component categories and around 70 molecular function categories for mouse and human (Fig. S5, Table S4). Genes related to protein ubiquitination (p-value = 4.07 × 10− 15), cell cycle (p-value = 3 × 10− 8), protein modification process (p-value = 2 × 10− 7) and metabolic process (p-value = 1.4 × 10− 3), were among the most significantly enriched terms (Table S4). Likewise, the GO enrichment analysis of DCAF subfamily proteins recognized around 70 biological process categories, 25 cellular component categories and around 25 molecular function categories for both species (Fig. S6, Table S5). Genes related to protein ubiquitination (p-value = 7.83 × 10− 18), cellular protein modification process (p-value = 3.4 × 10− 11), histone modification (p-value = 6.58 × 10− 6) and covalent chromatin modification (p-value = 3.87 × 10− 5) were among the most significantly enriched terms (Table S5).
The DCAF proteins were further subjected to interaction network analysis by IPA. The top three scoring networks were shown in Fig. 9a-c. The first network included 41 proteins associated with post-translational modification, especially ubiquitination. The second network comprised of 36 proteins that are mainly involved in transcription, chromatin modification, sperm maturation, sperm motility and histone modifications. The third network included 34 proteins that are involved in ubiquitination, microtubule dynamics, transcription regulation, Wnt signalling pathway and spermatogonia differentiation. The first network was characterized by presence of genes involved in protein ubiquitination, DNA damage response and repair and global genomic repair (Fig. 9a, Table S6). The genes in network 1 were mainly linked to different types of cancers and loss of germ cells (Table S6). Network 2 was mainly associated with transcription, chromatin remodelling, apoptosis, cell cycle and protein ubiquitination (Fig. 9b, Table S6). The genes in network 2 were found to be linked with various types of cancers (Table S6). Network 3 was associated with organelle assembly, microtubule morphology, nuclear transport and protein ubiquitination (Fig. 9c, Table S6).
To gain comparative insights into the genome-wide transcriptional signatures of WD40 family genes in multiple tissues of mouse and human, we systematically mined and investigated their relative transcript levels using in silico and qRT-PCR techniques with specific focus on testicular expression profiling of DCAF subfamily genes. We identified more than 345 putative WD40 protein encoding genes including DCAFs from each mouse and human genomes and examined their expressions in different tissues as well as in different developmental stages of testis from several high-throughput gene expression datasets. In earlier studies using SMART database, it has also been predicted to have 349 proteins containing WD40 domain in the human [3, 4, 56]. Comprehensive in silico study of the human WD40 family by Zou et al. identified 262 non-redundant WD40 protein encoding genes . Similarly, sequence search-based domain analysis of protein database identified 265 WD40 protein coding genes in mouse genome . The discrepancy between the number of WD40 encoding genes identified in human genome by Zou et al. and in this study is because the study by Zou et al. have considered only WD40 proteins that contain six or more WD40 repeats . Whereas, in our study we have included all the proteins containing one or more WD40 repeats. Variations observed in the numbers of predicted WD40 genes among previous studies and this study may be due to the low level of sequence similarities among WD40 repeats, the variable number of repeats within a single WD40 domain, and functional diversity of WDR proteins .
Analyses of different mouse and human RNA seq datasets revealed substantial variation in the abundance of WD40 gene transcripts among different tissues of both the species, indicating their diverse and tissue specific roles in different cellular and developmental processes. Previous studies have reported many WD40 genes that are not only involved in different cellular and developmental processes but they are also linked to diseases [3,4,5, 9]. We found that significantly large number of WD40 genes (~ 60–73%) was predominantly or specifically expressed in the testis of mouse as well as human, suggesting that these genes may have important functions in testicular development and/or spermatogenesis. Our findings are supported by earlier study on RNA seq data analysis from the Human Protein Atlas by Zou et al. where it was shown that the testis expressed highest number of tissue-specific WD40 genes . Similarly, microarray data analysis of silkworm WD40 gene family identified a large number of these genes that were highly or specifically expressed in testis . Expression studies on some of the WD40 genes such as Lis1 (Pafah1B1), wuho, Wdr5 (Big-3), Wsb2, Wdc146, Wdr73, Wdr13, Crbn, Dcaf17 and Tle3 in different species by different research groups also showed significantly higher expression of those genes in the testis as compared to other tissues [39,40,41, 46, 58,59,60,61,62,63]. In addition, functional and genetic studies conducted by various groups on several WD40 family genes (β-TrCP, Katnb1, Ddb2, Brwd1, Dcaf17 and Lis1) also showed that these genes play critical roles in different stages of testis development, spermatogenesis and fertility [42,43,44,45,46, 64,65,66,67]. For example, human mutations and knockout mouse models for Cilia and flagella associated protein (CFAP) 43 and 44 (members of WD40 gene family) showed similar defective sperm morphology, sperm motility and male infertility . Moreover, male Dcaf17 knockout mouse model exhibited lower sperm count and motility, abnormal seminiferous tubules and disorganized sperm head structure . Mutations in DCAF17 gene caused hypogonadism among other symptoms including diabetes and mental retardation in human . The aforementioned genes are highly expressed in the testis of both species which underline the importance of elucidating contributions of WD40 genes in male fertility.
Similarly, the RNA seq dataset analyses for DCAF subfamily genes, a subgroup of WD40 family genes, of mouse and human also showed significant variation in the amount of each gene transcripts within various tissues with noticeably higher proportion (~ 74–83%) of DCAF genes were highly or specifically expressed in the testis as compared to other tissues in both, mouse and human. These were further confirmed by RT-PCR/qRT-PCR results in this study. Our findings suggest that the DCAF genes may play different and critical roles during the testicular development and spermatogenesis. In addition, analyses of RNA seq datasets of the mouse testes developmental stages revealed that all the WD40 and DCAF genes showed variable and specific expression patterns at different developmental stages. Based on the expression patterns of WD40 genes during testis development, the genes can be clearly divided into three major groups where a set of the genes was highly expressed during embryonic stage, second set of the genes was highly expressed during post-natal testis development stages from day 0 to day 20, and third set of the genes was highly expressed during post-natal testis developmental stages from day 20 to adult. Likewise, expression patterns of DCAF subfamily genes showed two major and distinct groups with one set of the genes was predominantly expressed during testis embryonic development and the second set of the genes was highly expressed during post-natal testicular development from neonatal day 20 to adult. These diverse expression characteristics of WD40 and DCAF genes, during testis development suggest that encoded proteins may regulate a complex network of pathways to perform different cellular and molecular functions during testicular development process. The Wsb2 gene expression study in mouse embryonic and adult gonads showed expression of the Wsb2 in the developing male mouse gonads at 11.5 dpc with gradual increase in the expression during gonadal development . Similarly, mouse Wdr13 gene exhibited expression during early stages of gonadal development through adult testis with a predominant expression in the germ cells of adult testis . Another study on Wdr73 expression in Larimichthys crocea demonstrated that the Wdr73 expression increased with the advancement of gonad development, starting from proliferative stage to mature stage .
Spermatogenesis is a highly regulated, dynamic and intricate biological process in which undifferentiated diploid spermatogonia undergo self-renewal and proliferation by number of mitotic divisions, two meiotic divisions and spermiogenesis to produce highly specialized mature spermatozoa [37, 69]. It is controlled by a synchronized expression of defined sets of genes in a stage-specific manner [50, 51]. Investigation of the expression patterns of all WD40 genes and separately of DCAF subfamily genes only showed differential expression patterns in different spermatogenic cell types, suggesting involvement of these genes in a cell- and stage-specific manner during spermatogenesis. Quantitative RT-PCR results examining testis highly expressed DCAF subfamily genes expression during post-natal testis development confirmed the differential and stage-specific expression patterns of these genes. This varying expression of DCAF genes during testicular development suggests that their expression is developmentally regulated to maintain normal spermatogenesis. In mammals, spermatogenesis begins from the day of birth. However, actively proliferating type A spermatogonia and Sertoli cells could be recognized from postnatal day 5 or 6 in mice [70,71,72]. The seminiferous epithelium of 5 to 6 days old mice testes contains only primitive type A spermatogonia and Sertoli cells. The type A spermatogonia undergo a series of mitotic division and give rise to type B spermatogonia by day 8. Around day 9 or 10, the type B spermatogonia enter meiotic division by generating primary spermatocytes. As the meiotic cell division progresses, primary spermatocytes produce early and late pachytene stage spermatocytes by days 14 and 18, respectively. Around day 18 of development, pachytene stage spermatocytes complete first meiotic division to form secondary spermatocytes, which subsequently undergo second meiotic division to produce haploid round spermatids at the onset of spermiogenesis on around day 20. By day 35 first cycle of spermatogenesis is completed [70,71,72]. The biochemical and morphological changes in germ cells during spermatogenesis require highly regulated, balanced, spatiotemporal expression of the genes, which presumably reflect differences in the mRNA populations of different stage-specific DCAF genes during germ cell development. DCAF proteins are proposed to function as substrate receptors for CRL4 complexes . Hou et al. have identified large number of highly or specifically expressed E3 ligases in mouse testis in a cell- and stage-specific manner . Proposed role of DCAF proteins in CRL4 mediated ubiquitination and similarity between the differential expression patterns of DCAF genes and E3 ligase genes suggest that proteins encoded by these genes may play critical roles in the regulation of spermatogenesis through ubiquitination of target proteins . However, future functional studies still need to be conducted to show testicular role for such genes with unknown male reproductive phenotypes. Dependence of spermatogenesis on proteolytic and non-proteolytic actions of protein ubiquitination is well documented and many E3 ligases have be shown to play vital roles in many of the cellular and molecular process required for the production of mature spermatozoa [33, 73, 74].
To know the significance of WD40 family genes, we performed comprehensive bioinformatics analyses using PANTHER, DAVID and IPA software. GO annotation and enrichment analyses of WD40 family and DCAF subfamily genes revealed that the top over-represented functions were related to protein ubiquitination, cellular processes, metabolic processes, biological regulations and localization, suggesting functional diversity of WD40 proteins. Molecular network modelling of DCAF subfamily genes using IPA, identified three top ranking molecular networks related to post-translational modification, chromatin modification, sperm maturation and motility, microtubule dynamics, transcription and spermatogonia differentiation, suggesting importance of the DCAF subfamily genes in the regulation of testicular development and spermatogenesis.
We performed comprehensive and systematic mining, and expression profiling of the putative WD40 protein encoding genes in different tissues of mouse and human. Our investigation identified 347 and 349 WDR protein encoding genes in the genomes of mouse and human, respectively. High throughput RNA seq datasets analyses of WD40 genes in mouse and human revealed differential expression patterns among different tissues with a significantly large number of these genes were highly or specifically expressed in testis, suggesting their distinct and tissue specific functions in testicular development and spermatogenesis. A subset of WD40 genes called DCAF subfamily genes that encode substrate receptor proteins for CRL4 complexes. We identified 60 and 65 DCAF genes in mouse and human genomes, respectively. RNA seq and RT-PCR/qRT-PCR analyses of DCAF genes revealed diverse expression patterns of these genes across different tissues with considerably large proportion of the genes were predominantly or specifically expressed in the testis of both the species. Further analyses of WD40 and DCAF genes expression during different stages of embryonic and post-natal testis development in mouse and also in different spermatogenic cell populations revealed developmental and spermatogenic stage-specific regulation of these genes. Together, our data implicated intricate expression patterns for WD40 genes, particularly DCAF genes, reflecting complexity of spermatogenesis and also provide a valuable source to further elucidate their functions during spermatogenesis. Information gained from this study will help to develop infertility interventions and/or male-specific contraception tools.
Data collection and mining
A comprehensive search for WD40 domain protein encoding genes including DCAF subfamily genes of mouse and human was conducted using the Mouse Genome Informatics (MGI) [http://www.informatics.jax.org/], Human Genome Organization (HUGO), HUGO Gene Nomenclature Committee (HGNC) [https://www.genenames.org/data/genegroup/#!/], Ensembl [https://www.ensembl.org/index.html] and Ingenuity® Pathway Analysis (IPA) (QIAGEN, www.qiagen.com/ingenuity) databases and literature [10, 13, 14, 23,24,25, 75,76,77,78,79]. The WD40, DCAF, DWD, CDW, DDB1/2 and CUL4 terms were used in our search to retrieve the list of WD40 family genes. The RNA sequencing (RNA seq) based high-throughput gene expression data of the genes encoding WD40 family proteins in different tissues of mouse and human were obtained from the publically available RNA seq datasets from data resources and projects: The Functional ANnoTation Of Mammalian genomes (FANTOM5) [http://fantom.gsc.riken.jp/5/] (with Accession #s E-MTAB-3579 and E-MTAB-3358 for mice and human tissues, respectively), and Genotype-Tissue Expression (GTEx) [https://gtexportal.org/home/] [80,81,82,83,84,85]. Normalized tags (counts) per million (TPM) were computed using the relative log expression (RLE) algorithm in the FANTOM5 dataset. In the GTEx dataset, the expression values were normalized between samples using the trimmed mean of M-values (TMM) normalization method. Gene expression data for mouse and human in FANTOM5 datasets were used to investigate the expression patterns of the genes encoding WD40 family proteins in 15 tissues of adult mice (testis, aorta, cerebellum, colon, epididymis, lung, olfactory apparatus, ovary, pancreas, prostate, thymus, urinary bladder, uterus, liver and oviduct) and 10 human tissues (testis, brain, colon, epididymis, lung, olfactory apparatus, ovary, pancreas, prostate gland and uterus). For mouse testicular tissue, gene expression data for several testicular developmental stages that cover embryonic (day 13, 15, 16, 17, and 18), neonate (day 0, 07, 10, 20, and 30), and adult were also investigated. The RNA seq data for different types of spermatogenic cells from mouse testis were obtained from the public functional genomics data repository “Gene Expression Omnibus (GEO)” [Accession: GSE112393]  and “NCBI Sequence Read Archive (SRA)” [Accession: PRJNA317251] .
Animal use and tissue collection
C57BL/6 J mice at different ages [5, 14, 23, 32, 42 and 56 dpp] were used for this study. All the mice were obtained from the King Faisal Specialist Hospital and Research Centre laboratory animal services, Riyadh, Saudi Arabia. The mice were housed under controlled conditions of temperature (21 ± 1 °C), humidity and a 12 h light/12 h dark cycles. Animals were provided free access to standard rodent chow and tap water. All the procedures for animal care and use were approved by the Institutional Animal Care and Use Committee (IACUC) at King Faisal Specialist Hospital and Research Centre, Riyadh (Project RAC# 2170 024). Procedures for animal euthanasia and tissue collection were carried out according to the IACUC and National Research Council’s Guide for the Care and Use of Laboratory Animals. All the animals above ten days old were sacrificed by cervical dislocation, while 10 days old and younger mice were euthanized by decapitation before tissue collection. Seven tissues (brain, heart, lung, liver, kidney, testis and epididymis) were dissected from 56 dpp old adult male C57BL/6 J mice and three tissues (ovary, oviduct and uterus) were dissected from 56 dpp old adult female C57BL/6 J mice. Testes were separately collected from the 5, 14, 23, 32 and 42 dpp old mice. Testes of 5 dpp and 14 dpp old mice were pooled from five animals each to yield sufficient total RNA samples. Triplicate tissue samples were obtained in a similar fashion from the same breeding pairs. Tissues were snap frozen in liquid nitrogen and placed at − 80 °C until the time of total RNA isolation.
Total RNA extraction and reverse transcription
Total RNAs from mouse tissues (brain, heart, lung, liver, kidney, testis, epididymis, ovary, oviduct, and uterus) were purified using TRIzol® reagent (Invitrogen, Life Technologies, Waltham, MA, USA), as per company’s provided protocol. Quality and quantity of the purified RNA samples were measured by absorbance at 260 and 280 nm using NanoDrop 2000c spectrophotometer (ThermoFisher Scientific, Waltham, MA, USA). Integrity of purified RNA samples was checked by electrophoresing the RNA samples on 2% denaturing Tris-acetate-EDTA (TAE) ethidium bromide stained agarose gel. Only those RNA samples showing an OD260/OD280 ratio between 1.8 to 2.1 and intact 28S and 18S RNA bands were used for cDNA synthesis. In case of human samples, the Total Human RNA Master Panel II and Human Ovary Total RNA (Clontech Laboratories, Incorporation, Mountain View, CA) of total RNA samples from selected tissues (Brain, heart, lung, liver, stomach, kidney, thymus, small intestine, skeletal muscles, bone marrow, spinal cord, colon, prostate, testis, ovary, uterus and placenta) were used for cDNA synthesis. Approximately 1 μg (for mouse) and 0.5 μg (for human) of purified total RNA samples were reverse transcribed into cDNA in a total of 20 μl cDNA synthesis reaction mixture using Superscript III First Strand Synthesis system (Invitrogen, Life Technologies, Waltham, MA, USA) and BIO-RAD C1000 Touch™ thermal cycler (BIO-RAD, CA, USA) as per manufacturer’s protocol. Oligo (dT) primer was used for cDNA synthesis with the following thermal cycle conditions: 65 °C for 5 min, 50 °C for 50 min, and 85 °C for 5 min, followed by incubation at 37 °C for 20 min after addition of RNaseH enzyme. The total RNA samples from different tissues were processed for cDNA synthesis simultaneously to avoid experimental variation.
Semi quantitative reverse transcription-polymerase chain reaction (RT-PCR)
The PCR amplifications were performed in 25 μl reaction volumes containing 2.5 μl of 10Χ Qiagen PCR buffer (Tris·Cl, KCl, (NH4)2SO4, 15 mM MgCl2; pH 8.7), 0.5 μl dNTP mix (10 mM each), 2 μl gene specific forward and reverse primers (Table S7) mixture (5 μM each), 0.5 μl MgCl2 (25 mM), 3 μl cDNA (1:10 diluted) as a template, 16.3 μl nuclease-free water and 0.2 μl Taq DNA polymerase (25 Units). The PCR reaction mixtures were subjected to amplification cycles on BIO-RAD C1000 Touch™ thermal cycler (BIO-RAD, CA, USA) using the thermal cycler conditions of initial denaturation at 94 °C for 15 min, 35 cycles of denaturation at 94 °C for 30 s, annealing at 59 °C for 30 s and extension at 72 °C for 45 s followed by final extension at 72 °C for 10 min. The PCR amplicons were loaded on 1% denaturing TAE agarose gel pre-stained with ethidium bromide using 5 μl of PCR product mixed with 1 μl 6X loading dye (Promega). To estimate the size of DNA samples 100 bp DNA ladder (Promega) was run on the agarose gel alongside the samples. To visualize PCR amplification product, the gel was exposed to UV light using an ImageQuant LAS 4000 (GE Life Sciences) imaging system and the gel images were captured using ImageQuant LAS 4000 software (GE Life Sciences).
Quantitative real-time polymerase chain reaction (qRT-PCR)
The qRT-PCR was performed on a 7500 Fast real-time PCR system (Applied Biosystems, CA, USA) using the PowerUp™ SYBR® Green Master Mix (Applied Biosystems, CA, USA). The qRT-PCR reaction mixture for each target gene contained 12.5 μl of 2Χ PowerUp™ SYBR® Green Master Mix, 1 μl of gene specific primer pairs (forward and reverse primers mixture) at final concentrations of 5 μM for each primer, 3 μl of diluted cDNA (dilution 1:10) as template and 3.5 μl of nuclease free distilled water in a total reaction volume of 20 μl. For negative control, cDNA template was omitted and equal volume of nuclease free dH2O was added to the reaction. Exon-exon junction spanning RT-PCR primers for target genes were designed using Primer-BLAST tool from NCBI [https://www.ncbi.nlm.nih.gov/tools/primer-blast/] . The sequences of the gene specific primers are shown in Table S7. Primers were designed to obtain an amplified product in a range of 100–300 bps, and their specificity was tested using BLASTn searches (http://www.ncbi.nlm.nih.gov/BLAST/). The ribosomal S2 protein (RpS2) or 18S rRNA gene was used as a housekeeping gene. The 7500 Software v2.3 (Applied Biosystems, CA, USA) was used to set up the qRT-PCR experiments. The qPCR cycle conditions were as follows: 1 cycle of activation at 95 °C for 15 min, and 40 cycles of denaturing at 95 °C for 15 s, annealing at 60 °C for 30 s and extension at 72 °C for 45 s, followed by default slow temperature-ramping dissociation steps (95 °C for 15 s, 60 °C for 15 s, and 95 °C for 15 s) for melting curve. The specificity of the PCR reactions was assessed by a melting curve analysis. All the RT-PCR reactions were performed on 3 technical replicates with three biological samples. Relative expression levels of target genes were analysed by the 2-∆∆CT method as previously described . Briefly, cycle threshold values (Ct) for the genes of interest and the RpS2 or 18S rRNA gene (housekeeping gene) were determined and collected using the 7500 Software v2.3 (Applied Biosystems, CA, USA). Ct values for the gene of interest were normalized to those of housekeeping gene values in each sample, and then the fold change for the gene of interest was calculated relative to the level in the reference sample. One-way ANOVA was performed, followed by pair wise comparisons of the means at a p value of ≤0.01, using Graphpad PRISM5 software (GraphPad Software, San Diego, CA, USA; https://www.graphpad.com/scientific-software/prism/).
Bioinformatics and data analysis
We performed unsupervised two-dimensional hierarchical clustering using Pearson’s correlation with average linkage clustering for mouse and human samples, separately based on their gene expression similarity using WD40 repeat encoding genes including DCAF family genes. In addition, functional and gene ontology analysis of genes were performed using QIAGEN’s Ingenuity Pathway Analysis (IPA®, QIAGEN Inc., Redwood City, CA, USA, https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis), DAVID [55, 88] and PANTHER™ classification systems [53, 54]. P-values were determined by applying right-tailed Fisher’s exact test to determine the probability that the biological function assigned to that data set is explained by chance alone.
For comparison of gene expression in testis versus other tissues and gene expression in testis at different ages, one-way ANOVA followed by a Fisher’s protected least significant difference test was performed using GraphPad PRISM version 5 (GraphPad Software, San Diego, CA, USA). A Student’s t test was conducted to compare the difference between two means. Comparison of multiple means was conducted by one-way ANOVA followed by a Bonferroni’s Multiple Comparison Test. The significance level was set at p < 0.05.
Availability of data and materials
All data generated or analysed during this study are included in this published article and its supplementary information files. The RNA sequencing datasets obtained from publicly available web-based resources and analysed during the current study are available in the Functional ANnoTation Of Mammalian genomes (FANTOM5) [http://fantom.gsc.riken.jp/5/] (Accession # E-MTAB-3579 and E-MTAB-3358), Genotype-Tissue Expression (GTEx) [https://gtexportal.org/home/], Gene Expression Omnibus (GEO) (Accession # GSE112393) [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE112393] and NCBI Sequence Read Archive (SRA) (Accession # PRJNA317251) [https://www.ncbi.nlm.nih.gov/bioproject/PRJNA317251/] repositories.
Analysis of variance
Basic Local Alignment Search Tool
Cilia and flagella associated protein
Cullin4-RING-based E3 ubiquitin ligase
Cycle threshold values
Database for annotation, visualization and integrated discovery
DET1 and DDB1 associated 1
Damaged DNA Binding 1
De-etiolated homolog 1
Ubiqitin E3 ligases
Functional ANnoTation Of Mammalian genomes 5
Gene Expression Omnibus
HUGO Gene Nomenclature Committee
Human Genome Organization
Institutional Animal Care and Use Committee
Ingenuity® Pathway Analysis
Mouse Genome Informatics
Leptotene and zygotene stage of spermatocytes
National Center for Biotechnology Information
Protein ANalysis THrough Evolutionary Relationships
Polymerase chain reaction
Quantitative real-time polymerase chain reaction
Relative log expression
- RNA seq:
Reverse transcription-polymerase chain reaction
Simple Modular Architecture Research Tool
Sequence Read Archive
Trimmed mean of M-values
Tags (counts) per million
- WDR or WD40:
Tryptophan (W)-aspartate (D) 40-repeats
Wingless-related integration site
Suganuma T, Pattenden SG, Workman JL. Diverse functions of WD40 repeat proteins in histone recognition. Genes Dev. 2008;22(10):1265–8.
Neer EJ, Schmidt CJ, Nambudripad R, Smith TF. The ancient regulatory-protein family of WD-repeat proteins. Nature. 1994;371(6495):297–300.
Jain BP, Pandey S. WD40 repeat proteins: Signalling scaffold with diverse functions. Protein J. 2018;37(5):391–406.
Zhang C, Zhang F. The multifunctions of WD40 proteins in genome integrity and cell cycle progression. J Genomics. 2015;3:40–50.
Li D, Roberts R. WD-repeat proteins: structure characteristics, biological function, and their involvement in human diseases. Cell Mol Life Sci. 2001;58(14):2085–97.
Smith TF, Gaitatzes C, Saxena K, Neer EJ. The WD repeat: a common architecture for diverse functions. Trends Biochem Sci. 1999;24(5):181–5.
Xu C, Min J. Structure and function of WD40 domain proteins. Protein Cell. 2011;2(3):202–14.
Song R, Wang ZD, Schapira M. Disease association and Druggability of WD40 repeat proteins. J Proteome Res. 2017;16(10):3766–73.
Schapira M, Tyers M, Torrent M, Arrowsmith CH. WD40 repeat domain proteins: a novel target class? Nat Rev Drug Discov. 2017;16(11):773–86.
Yan H, Bi L, Wang Y, Zhang X, Hou Z, Wang Q, Snijders AM, Mao JH. Integrative analysis of multi-omics data reveals distinct impacts of DDB1-CUL4 associated factors in human lung adenocarcinomas. Sci Rep. 2017;7(1):333.
Agopiantz M, Corbonnois P, Sorlin A, Bonnet C, Klein M, Hubert N, Pascal-Vigneron V, Jonveaux P, Cuny T, Leheup B, et al. Endocrine disorders in woodhouse-Sakati syndrome: a systematic review of the literature. J Endocrinol Investig. 2014;37(1):1–7.
Alazami AM, Al-Saif A, Al-Semari A, Bohlega S, Zlitni S, Alzahrani F, Bavi P, Kaya N, Colak D, Khalak H, et al. Mutations in C2orf37, encoding a nucleolar protein, cause hypogonadism, alopecia, diabetes mellitus, mental retardation, and extrapyramidal syndrome. Am J Hum Genet. 2008;83(6):684–91.
He S, Tong X, Han M, Hu H, Dai F. Genome-Wide Identification and Characterization of WD40 Protein Genes in the Silkworm, Bombyx mori. Int J Mol Sci. 2018;19(2).
Zou XD, Hu XJ, Ma J, Li T, Ye ZQ, Wu YD. Genome-wide analysis of WD40 protein family in human. Sci Rep. 2016;6:39262.
Lee JH, Terzaghi W, Gusmaroli G, Charron JB, Yoon HJ, Chen H, He YJ, Xiong Y, Deng XW. Characterization of Arabidopsis and rice DWD proteins and their roles as substrate receptors for CUL4-RING E3 ubiquitin ligases. Plant Cell. 2008;20(1):152–67.
Jain BP. Genome wide analysis of WD40 proteins in Saccharomyces cerevisiae and their Orthologs in Candida albicans. Protein J. 2019;38(1):58–75.
Feng R, Zhang C, Ma R, Cai Z, Lin Y, Yu M. Identification and characterization of WD40 superfamily genes in peach. Gene. 2019;710:291–306.
Hu R, Xiao J, Gu T, Yu X, Zhang Y, Chang J, Yang G, He G. Genome-wide identification and analysis of WD40 proteins in wheat (Triticum aestivum L.). BMC Genomics. 2018;19(1):803.
Bian S, Li X, Mainali H, Chen L, Dhaubhadel S. Genome-wide analysis of DWD proteins in soybean (Glycine max): significance of Gm08DWD and GmMYB176 interaction in isoflavonoid biosynthesis. PLoS One. 2017;12(6):e0178947.
Salih H, Gong W, Mkulama M, Du X. Genome-wide characterization, identification, and expression analysis of the WD40 protein family in cotton. Genome. 2018;61(7):539–47.
van Nocker S, Ludwig P. The WD-repeat protein superfamily in Arabidopsis: conservation and divergence in structure and function. BMC Genomics. 2003;4(1):50.
Ouyang Y, Huang X, Lu Z, Yao J. Genomic survey, expression profile and co-expression network analysis of OsWD40 family in rice. BMC Genomics. 2012;13:100.
Lee J, Zhou P. DCAFs, the missing link of the CUL4-DDB1 ubiquitin ligase. Mol Cell. 2007;26(6):775–80.
Jin J, Arias EE, Chen J, Harper JW, Walter JC. A family of diverse Cul4-Ddb1-interacting proteins includes Cdt2, which is required for S phase destruction of the replication factor Cdt1. Mol Cell. 2006;23(5):709–21.
He YJ, McCall CM, Hu J, Zeng Y, Xiong Y. DDB1 functions as a linker to recruit receptor WD40 proteins to CUL4-ROC1 ubiquitin ligases. Genes Dev. 2006;20(21):2949–54.
Higa LA, Wu M, Ye T, Kobayashi R, Sun H, Zhang H. CUL4-DDB1 ubiquitin ligase interacts with multiple WD40-repeat proteins and regulates histone methylation. Nat Cell Biol. 2006;8(11):1277–83.
Jackson S, Xiong Y. CRL4s: the CUL4-RING E3 ubiquitin ligases. Trends Biochem Sci. 2009;34(11):562–70.
Higa LA, Zhang H. Stealing the spotlight: CUL4-DDB1 ubiquitin ligase docks WD40-repeat proteins to destroy. Cell Div. 2007;2:5.
de Bie P, Ciechanover A. Ubiquitination of E3 ligases: self-regulation of the ubiquitin system via proteolytic and non-proteolytic mechanisms. Cell Death Differ. 2011;18(9):1393–402.
Bhat KP, Greer SF. Proteolytic and non-proteolytic roles of ubiquitin and the ubiquitin proteasome system in transcriptional regulation. Biochim Biophys Acta. 2011;1809(2):150–5.
Nandi D, Tahiliani P, Kumar A, Chandu D. The ubiquitin-proteasome system. J Biosci. 2006;31(1):137–55.
Hershko A, Ciechanover A. The ubiquitin system. Annu Rev Biochem. 1998;67:425–79.
Richburg JH, Myers JL, Bratton SB. The role of E3 ligases in the ubiquitin-dependent regulation of spermatogenesis. Semin Cell Dev Biol. 2014;30:27–35.
Nakamura N. Ubiquitination regulates the morphogenesis and function of sperm organelles. Cells. 2013;2(4):732–50.
Pickart CM. Mechanisms underlying ubiquitination. Annu Rev Biochem. 2001;70:503–33.
Cheng CY, Mruk DD. The biology of spermatogenesis: the past, present and future. Philos Trans R Soc Lond Ser B Biol Sci. 2010;365(1546):1459–63.
de Kretser DM, Loveland KL, Meinhardt A, Simorangkir D, Wreford N. Spermatogenesis. Hum Reprod. 1998;13(Suppl 1):1–8.
Volpi S, Bongiorni S, Fabbretti F, Wakimoto BT, Prantera G. Drosophila rae1 is required for male meiosis and spermatogenesis. J Cell Sci. 2013;126(Pt 16):3541–51.
Wu J, Hou JH, Hsieh TS. A new Drosophila gene wh (wuho) with WD40 repeats is essential for spermatogenesis and has maximal expression in hub cells. Dev Biol. 2006;296(1):219–30.
Ito S, Sakai A, Nomura T, Miki Y, Ouchida M, Sasaki J, Shimizu K. A novel WD40 repeat protein, WDC146, highly expressed during spermatogenesis in a stage-specific manner. Biochem Biophys Res Commun. 2001;280(3):656–63.
Sarraj MA, McClive PJ, Szczepny A, Daggag H, Loveland KL, Sinclair AH. Expression of Wsb2 in the developing and adult mouse testis. Reproduction. 2007;133(4):753–61.
Yao GD, Shi SL, Song WY, Jin HX, Peng ZF, Yang HY, Wang EY, Sun YP. Role of PAFAH1B1 in human spermatogenesis, fertilization and early embryonic development. Reprod BioMed Online. 2015;31(5):613–24.
Nayernia K, Vauti F, Meinhardt A, Cadenas C, Schweyer S, Meyer BI, Schwandt I, Chowdhury K, Engel W, Arnold HH. Inactivation of a testis-specific Lis1 transcript in mice prevents spermatid differentiation and causes male infertility. J Biol Chem. 2003;278(48):48377–85.
Morohoshi A, Nakagawa T, Nakano S, Nagasawa Y, Nakayama K. The ubiquitin ligase subunit beta-TrCP in Sertoli cells is essential for spermatogenesis in mice. Dev Biol. 2019;445(2):178–88.
Nakagawa T, Zhang T, Kushi R, Nakano S, Endo T, Nakagawa M, Yanagihara N, Zarkower D, Nakayama K. Regulation of mitosis-meiosis transition by the ubiquitin ligase beta-TrCP in male germ cells. Development. 2017;144(22):4137–47.
Ali A, Mistry BV, Ahmed HA, Abdulla R, Amer HA, Prince A, Alazami AM, Alkuraya FS, Assiri A. Deletion of DDB1- and CUL4- associated factor-17 (Dcaf17) gene causes spermatogenesis defects and male infertility in mice. Sci Rep. 2018;8(1):9202.
Hou CC, Yang WX. New insights to the ubiquitin-proteasome pathway (UPP) mechanism during spermatogenesis. Mol Biol Rep. 2013;40(4):3213–30.
Bebington C, Doherty FJ, Fleming SD. The possible biological and reproductive functions of ubiquitin. Hum Reprod Update. 2001;7(1):102–11.
Hou X, Zhang W, Xiao Z, Gan H, Lin X, Liao S, Han C. Mining and characterization of ubiquitin E3 ligases expressed in the mouse testis. BMC Genomics. 2012;13:495.
Green CD, Ma Q, Manske GL, Shami AN, Zheng X, Marini S, Moritz L, Sultan C, Gurczynski SJ, Moore BB, et al. A comprehensive roadmap of murine spermatogenesis defined by single-cell RNA-Seq. Dev Cell. 2018;46(5):651–67 e610.
da Cruz I, Rodriguez-Casuriaga R, Santinaque FF, Farias J, Curti G, Capoano CA, Folle GA, Benavente R, Sotelo-Silveira JR, Geisinger A. Transcriptome analysis of highly purified mouse spermatogenic cell populations: gene expression signatures switch from meiotic-to postmeiotic-related processes at pachytene stage. BMC Genomics. 2016;17:294.
Guo J, Grow EJ, Mlcochova H, Maher GJ, Lindskog C, Nie X, Guo Y, Takei Y, Yun J, Cai L, et al. The adult human testis transcriptional cell atlas. Cell Res. 2018;28(12):1141–57.
Mi H, Muruganujan A, Huang X, Ebert D, Mills C, Guo X, Thomas PD. Protocol update for large-scale genome and gene function analysis with the PANTHER classification system (v.14.0). Nat Protoc. 2019;14(3):703–21.
Mi H, Muruganujan A, Ebert D, Huang X, Thomas PD. PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res. 2019;47(D1):D419–26.
Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57.
Mishra AK, Puranik S, Prasad M. Structure and regulatory networks of WD40 protein in plants. J Plant Biochem Biotechnol. 2012;21(1):32–9.
Smith TF. Diversity of WD-repeat proteins. Subcell Biochem. 2008;48:20–30.
Lee S, Jang H, Moon S, Lee OH, Lee S, Lee J, Park C, Seol DW, Song H, Hong K, et al. Differential Regulation of TLE3 in Sertoli Cells of the Testes during Postnatal Development. Cells. 2019;8(10).
Xin W, Xiaohua N, Peilin C, Xin C, Yaqiong S, Qihan W. Primary function analysis of human mental retardation related gene CRBN. Mol Biol Rep. 2008;35(2):251–6.
Peterfy M, Gyuris T, Grosshans D, Cuaresma CC, Takacs L. Cloning and characterization of cDNAs and the gene encoding the mouse platelet-activating factor acetylhydrolase Ib alpha subunit/lissencephaly-1 protein. Genomics. 1998;47(2):200–6.
Gori F, Divieti P, Demay MB. Cloning and characterization of a novel WD-40 repeat protein that dramatically accelerates osteoblastic differentiation. J Biol Chem. 2001;276(49):46515–22.
Zhang DL, Yu DH, Luo HY, Wang ZY. WD repeat-containing protein 73, a novel gene correlated with gonad development in large yellow croaker, Larimichthys crocea. J World Aquacult Soc. 2016;47(2):268–76.
Suresh A, Shah V, Rani DS, Singh BN, Prasad GU, Subramanian S, Kumar S, Singh L. A mouse gene encoding a novel member of the WD family of proteins is highly conserved and predominantly expressed in the testis (Wdr13). Mol Reprod Dev. 2005;72(3):299–310.
Pattabiraman S, Baumann C, Guisado D, Eppig JJ, Schimenti JC, De La Fuente R. Mouse BRWD1 is critical for spermatid postmeiotic transcription and female meiotic chromosome stability. J Cell Biol. 2015;208(1):53–69.
O'Donnell L, McLachlan RI, Merriner DJ, O'Bryan MK, Jamsai D. KATNB1 in the human testis and its genetic variants in fertile and oligoasthenoteratozoospermic infertile men. Andrology. 2014;2(6):884–91.
Philipps DL, Wigglesworth K, Hartford SA, Sun F, Pattabiraman S, Schimenti K, Handel M, Eppig JJ, Schimenti JC. The dual bromodomain and WD repeat-containing mouse protein BRWD1 is required for normal spermiogenesis and the oocyte-embryo transition. Dev Biol. 2008;317(1):72–82.
Itoh T, Iwashita S, Cohen MB, Meyerholz DK, Linn S. Ddb2 is a haploinsufficient tumor suppressor and controls spontaneous germ cell apoptosis. Hum Mol Genet. 2007;16(13):1578–86.
Tang S, Wang X, Li W, Yang X, Li Z, Liu W, Li C, Zhu Z, Wang L, Wang J, et al. Biallelic mutations in CFAP43 and CFAP44 cause male infertility with multiple morphological abnormalities of the sperm flagella. Am J Hum Genet. 2017;100(6):854–64.
Jan SZ, Hamer G, Repping S, de Rooij DG, van Pelt AM, Vormer TL. Molecular control of rodent spermatogenesis. Biochim Biophys Acta. 2012;1822(12):1838–50.
Vergouwen RP, Huiskamp R, Bas RJ, Roepers-Gajadien HL, Davids JA, de Rooij DG. Postnatal development of testicular cell populations in mice. J Reprod Fertil. 1993;99(2):479–85.
Thomas KH, Wilkie TM, Tomashefsky P, Bellve AR, Simon MI. Differential gene expression during mouse spermatogenesis. Biol Reprod. 1989;41(4):729–39.
Bellve AR, Cavicchia JC, Millette CF, O'Brien DA, Bhatnagar YM, Dym M. Spermatogenic cells of the prepuberal mouse. Isolation and morphological characterization. J Cell Biol. 1977;74(1):68–85.
Yin Y, Lin C, Kim ST, Roig I, Chen H, Liu L, Veith GM, Jin RU, Keeney S, Jasin M, et al. The E3 ubiquitin ligase Cullin 4A regulates meiotic progression in mouse spermatogenesis. Dev Biol. 2011;356(1):51–62.
Kopanja D, Roy N, Stoyanova T, Hess RA, Bagchi S, Raychaudhuri P. Cul4A is essential for spermatogenesis and male fertility. Dev Biol. 2011;352(2):278–87.
Smith CL, Blake JA, Kadin JA, Richardson JE, Bult CJ. Mouse genome database G: mouse genome database (MGD)-2018: knowledgebase for the laboratory mouse. Nucleic Acids Res. 2018;46(D1):D836–42.
Finger JH, Smith CM, Hayamizu TF, McCright IJ, Xu J, Law M, Shaw DR, Baldarelli RM, Beal JS, Blodgett O, et al. The mouse gene expression database (GXD): 2017 update. Nucleic Acids Res. 2017;45(D1):D730–6.
Zerbino DR, Achuthan P, Akanni W, Amode MR, Barrell D, Bhai J, Billis K, Cummins C, Gall A, Giron CG, et al. Ensembl 2018. Nucleic Acids Res. 2018;46(D1):D754–61.
Wang Y, Hu XJ, Zou XD, Wu XH, Ye ZQ, Wu YD. WDSPdb: a database for WD40-repeat proteins. Nucleic Acids Res. 2015;43(Database issue):D339–44.
Braschi B, Denny P, Gray K, Jones T, Seal R, Tweedie S, Yates B, Bruford E: Genenames.org: The HGNC and VGNC resources in 2019 2019. Nucleic Acids Res 2019, 47(D1):D786-D792.
Lizio M, Harshbarger J, Abugessaisa I, Noguchi S, Kondo A, Severin J, Mungall C, Arenillas D, Mathelier A, Medvedeva YA, et al. Update of the FANTOM web resource: high resolution transcriptome of diverse cell types in mammals. Nucleic Acids Res. 2017;45(D1):D737–43.
Lizio M, Harshbarger J, Shimoji H, Severin J, Kasukawa T, Sahin S, Abugessaisa I, Fukuda S, Hori F, Ishikawa-Kato S, et al. Gateways to the FANTOM5 promoter level mammalian expression atlas. Genome Biol. 2015;16:22.
Consortium F, The RP, Clst, Forrest AR, Kawaji H, Rehli M, Baillie JK, de Hoon MJ, Haberle V, Lassmann T, et al. A promoter-level mammalian expression atlas. Nature. 2014;507(7493):462–70.
Carithers LJ, Moore HM. The genotype-tissue expression (GTEx) project. Biopreserv Biobank. 2015;13(5):307–8.
Consortium GT. The genotype-tissue expression (GTEx) project. Nat Genet. 2013;45(6):580–5.
Mele M, Ferreira PG, Reverter F, DeLuca DS, Monlong J, Sammeth M, Young TR, Goldmann JM, Pervouchine DD, Sullivan TJ, et al. Human genomics. The human transcriptome across tissues and individuals. Science. 2015;348(6235):660–5.
Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL. Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinform. 2012;13:134.
Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method. Methods. 2001;25(4):402–8.
Huang da W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37(1):1–13.
We gratefully acknowledge the support by King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia. Authors are thankful to all the staff of animal facility at King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia for providing mice. Some of the work described herein was performed by Hana M. Fitwi as part of her master degree research project.
This research work (RAC # 2170 024) was funded by King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
Ethics approval and consent to participate
All the experimental protocols were approved by the Institutional Animal Care and Use Committee (IACUC) at King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia (Project RAC# 2170 024).
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The authors declare that they have no competing interests.
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A: Agarose gel images of RT-PCR products of different DCAF genes from mouse (A). RT-PCR was performed on total RNA from different tissues of adult C57BL/6 mouse using gene specific primers for 56 different DCAF subfamily genes as well as housekeeping genes (β-actin and 18S rRNA). The PCR products were separated on 1.5% agarose gel and images were captured using gel imager. gDNA: Genomic DNA; -ve: No template control. Figure S1. B: Agarose gel images of RT-PCR products of different Dcaf genes from human (B). RT-PCR was performed on total RNA from different tissues of adult human using gene specific primers for 52 different DCAF subfamily genes as well as housekeeping genes (18S rRNA). The PCR products were separated on 1.5% agarose gel and images were captured using gel imager. gDNA: Genomic DNA; -ve control: No template control. Figure S2. Heat map of WD40 family genes (A) and DCAF subfamily genes (B) showing differential expression in different populations of purified spermatogenic cells from mouse testes. Heat map of WD40 and DCAF genes generated from Cruz et al’s RNA sequencing dataset (da Cruz et al., 2016). Samples are denoted in rows and genes are denoted in columns. Red and green denote highly and weakly expressed genes, respectively. LZ - leptotene and zygotene; 2C - spermatogonia, secondary spermatocytes and Sertoli cells; PS - pachytene spermatocytes; RS - round spermatids. Figure S3. Heat map of WD40 family genes (A) and DCAF subfamily genes (B) showing differential expression in different populations of purified spermatogenic cells from human testes. Heat map of WD40 and DCAF genes generated from Guo et al’s RNA sequencing dataset (Guo et al., 2018). Samples are denoted in columns and genes are denoted in rows. Red and green denote highly and weakly expressed genes, respectively. 1 – Spermatogonial stem cells (SSCs); 2 – Differentiating spermatogonia; 3 – Early primary spermatocytes; 4 – Late primary spermatocytes; 5 – Round spermatids; 6 – Elongated spermatids; 7 & 8 – Sperm. Figure S4. Pie charts showing the gene ontology (GO) categorization of the human WD40 family genes (A) and DCAF subfamily genes (B) according to biological processes. WD40 and DCAF genes of human were classified into 10 GO categories for biological processes using Panther. Size of the pie slice corresponds to the number of genes in a given GO category. Figure S5. Pie and bar charts representing the gene ontology (GO) categorization of the mouse(A, C, E) and human (B, D, F) WD40 family genes according to biological processes (A, B), cellular components (C, D) and molecular functions (E, F) using DAVID. Figure S6. Pie and bar charts representing the gene ontology (GO) categorization of the mouse (A, C, E) and human (B, D, F) DCAF family genes according to biological processes (A, B), cellular components (C, D) and molecular functions (E, F) using DAVID.
List of WD40-repeat encoding genes from mouse genome.
List of DCAF subfamily genes in different species.
GO categorization for biological processes of mouse WD40 genes using Panther.
GO categorization for cellular component of mouse WD40 genes using DAVID.
GO categorization for biological processes of human DCAF genes using DAVID.
IPA network analysis of DCAF subfamily genes.
DCAF family genes specific primer sequences and PCR product size for mouse and human.
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Mistry, B.V., Alanazi, M., Fitwi, H. et al. Expression profiling of WD40 family genes including DDB1- and CUL4- associated factor (DCAF) genes in mice and human suggests important regulatory roles in testicular development and spermatogenesis. BMC Genomics 21, 602 (2020). https://doi.org/10.1186/s12864-020-07016-9
- DDB1–CUL4-associated factors
- Gene expression
- RNA sequencing