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Live imaging RNAi screen reveals genes essential for meiosis in mammalian oocytes

Nature volume 524, pages 239–242 (2015)Cite this article

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Abstract

During fertilization, an egg and a sperm fuse to form a new embryo. Eggs develop from oocytes in a process called meiosis. Meiosis in human oocytes is highly error-prone1,2, and defective eggs are the leading cause of pregnancy loss and several genetic disorders such as Down’s syndrome3,4,5. Which genes safeguard accurate progression through meiosis is largely unclear. Here we develop high-content phenotypic screening methods for the systematic identification of mammalian meiotic genes. We targeted 774 genes by RNA interference within follicle-enclosed mouse oocytes to block protein expression from an early stage of oocyte development onwards. We then analysed the function of several genes simultaneously by high-resolution imaging of chromosomes and microtubules in live oocytes and scored each oocyte quantitatively for 50 phenotypes, generating a comprehensive resource of meiotic gene function. The screen generated an unprecedented annotated data set of meiotic progression in 2,241 mammalian oocytes, which allowed us to analyse systematically which defects are linked to abnormal chromosome segregation during meiosis, identifying progression into anaphase with misaligned chromosomes as well as defects in spindle organization as risk factors. This study demonstrates how high-content screens can be performed in oocytes, and allows systematic studies of meiosis in mammals.

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Figure 1: RNAi screen in live oocytes.
Figure 2: Defects during meiosis I in siRNA-treated oocytes.
Figure 3: Dusp7 and Mastl depletion phenotypes.
Figure 4: Factors implicated in chromosome segregation errors.

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Gene Expression Omnibus

Data deposits

RNA sequencing data have been deposited in Gene Expression Omnibus under accession number GSE68150.

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Acknowledgements

We thank the staff of the MRC Laboratory of Molecular Biology’s Animal and Microscopy Facilities for technical assistance; J. Ellenberg, L. Jaffe and M. Freudzon for technical advice on culturing siRNA-injected follicles in vitro; J. Ellenberg and M. Madan Babu for discussions; G. Chalancon for help with data analyses; E. Voets for the Mastl construct; and members of the Schuh laboratory and S. Munro for comments on the manuscript. S.P. and M.P. received PhD fellowships from Boehringer-Ingelheim Fonds. T.T. is supported by an EMBO Long Term Fellowship (ALTF700-2014). The research leading to these results has received financial support from the European Research Council under grant agreement no. 337415 and the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 241548.

Author information

Author notes

  1. Sybille Pfender, Vitaliy Kuznetsov and Michał Pasternak: These authors contributed equally to this work.

Authors and Affiliations

  1. Medical Research Council, Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge, CB2 0QH, UK

    Sybille Pfender, Vitaliy Kuznetsov, Michał Pasternak, Thomas Tischer, Balaji Santhanam & Melina Schuh

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  1. Sybille Pfender
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Contributions

All authors analysed data. S.P. microinjected the majority of siRNA mixes, and identified, validated and characterized most genes; M.P. microinjected siRNA mixes, compared the developmental capacity and expression profile of oocytes grown in vitro and in vivo, and identified, validated and characterized several genes; V.K. microinjected siRNA mixes and wrote software in OriginPro to quantify phenotypes; T.T. validated and characterized Dusp7; B.S. did all bioinformatics analyses; V.K. and M.S. developed and established the strategy of the screen; M.S. wrote the manuscript; S.P., M.P., T.T. and B.S. commented on and edited the manuscript; M.P. and M.S. prepared the revised manuscript; M.S. supervised the study.

Corresponding author

Correspondence to Melina Schuh.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Efficiency of follicle growth and comparison of oocytes grown in vitro and in vivo.

a, Follicles before (top panel) and after (bottom panel) in vitro culture. The perimeters of oocyte and granulosa cells are highlighted on the right. The follicle diameter increases from 103.4 ± 11.3 µm to 314.1 ± 104.0 µm during in vitro culture. This lies between the diameter of in vivo grown early antral (∼248 µm) and Graafian (∼424 µm) mouse follicles26. The diameter of n follicles was measured before and after in vitro culture and is displayed as mean ± s.d. Measurements from three or two independent experiments for before and after culture, respectively. b, Diameter of oocytes grown in vivo or in vitro. Data from two and seven experiments, respectively. The box plot shows median (line), mean (small square), 5th, 95th (whiskers) and 25th and 75th percentile (boxes). c, Efficiency of follicle growth on different culture substrates. The numbers of independent experiments are 343, 56, 11 and 3 from left to right. The total number of follicles is specified above the bars. Error bars, s.d. d, Live oocyte expressing eGFP–MAP4 (green, microtubules) and H2B–mRFP (magenta, chromosomes). The characteristic time points of oocyte maturation that were determined for each oocyte in the screen (2,241 oocytes in total from 70 experiments) are listed above the representative images. Quantification of timing in e. Scale bar, 10 µm. e, The timing of bipolar spindle assembly, chromosome alignment during meiosis I, anaphase, polar body extrusion and chromosome alignment during meiosis II were quantified in oocytes obtained from 5-week-old (C57BL × CBA) F1 females or in oocytes from the same strain grown in vitro within follicles. Data from four independent experiments. Error bars, s.d. f, Transmitted light images of blastocysts derived from fertilized (C57BL × CBA) F1 oocytes grown in vitro within follicles (left) or in vivo (right). Scale bar, 20 µm. Quantifications in g. g, (C57BL × CBA) F1 oocytes grown in vitro within follicles or in vivo were denuded, matured in vitro and fertilized. The percentages of all oocytes (fertilized and unfertilized) that developed into two-cell embryos (two-cell from total) and two-cell embryos that developed into blastocysts (blastocyst from total) were quantified. Developmental rates are consistent with previous studies, in which in vitro matured denuded oocytes were fertilized27,28; 179 oocytes grown in vivo and 180 oocytes grown in vitro were analysed in total. Data from three independent experiments for each group. Error bars, s.d. h, Transmitted light images of control oocytes and oocytes microinjected with an siRNA mix targeting Zp3 together with 11 other genes (RNAi Mix against Zp3) or an siRNA mix microinjected at the same time that targeted 12 other genes (RNAi mix against other genes). Highlighted region is magnified below. Scale bar, 10 µm. Quantification of phenotype in i. i, The presence of the zona pellucida was scored in oocytes microinjected with control siRNA (control), an siRNA mix targeting one of the three Zp genes (Zp1, Zp2 or Zp3) together with 11 other genes and an siRNA mix microinjected at the same time that targeted 12 different genes (RNAi mix against other genes). The number of analysed oocytes is given next to bars.

Extended Data Figure 2 Transcriptome analysis of oocytes grown in vivo and in vitro.

a–c, Transcriptome analysis of oocytes grown in vitro and in vivo. a, Differentially expressed genes in oocytes grown in vitro based on evaluation using NOISeq algorithm. Transcript abundances are reported in transcript FPKM. Only about 2% (213 out of 11,470) of genes were differentially expressed. b, Differentially expressed genes in oocytes cultured in vitro based on evaluation using DESeq2 algorithm. Only about 4% (445 genes out of 10,597) of genes were differentially expressed after applying filters in both b and c. The blue lines indicate genes with at least twofold change in expression. Red colour indicates differentially expressed genes with the denoted probability. For details, see Methods. c, The overlap between NOISeq and DESeq2 results, presented as Venn diagrams. There is at least over 80% overlap in genes in either upregulated or downregulated groups for both NOISeq and DESeq2. d, Qualitative network of phenotypes in oocytes microinjected with siRNA mixes. Blue nodes represent siRNA mixes, purple nodes represent phenotypes. Grey lines between mixes and phenotypes denote if at least one oocyte microinjected with a given mix displayed the phenotype. The clusters indicate a close relationship between a set of phenotypes and mixes. The clusters were obtained using ClusterViz (https://code.google.com/p/clusterviz-cytoscape/) of Cytoscape, which encodes the MCODE method to identify clusters of closed related nodes based on the topology of the network. The network contains six clusters identified by ClusterViz.

Extended Data Figure 3 Description of defects scored in screen.

a, Scheme illustrating the main categories of defects that were quantified in the screen. b, Table listing the main categories of defects and their subcategories as well as a description of each defect. c, Table listing the numerical values that were measured in the screen and a description of each numerical value.

Extended Data Figure 4 Defects during meiosis II in siRNA-treated oocytes.

a, d, g, The frequency of cytokinetic defects (a), spindle defects in metaphase II (d) and chromosome defects in metaphase II (g) were scored in siRNA-treated oocytes. The absolute number of oocytes with each defect is given next to bars. Data from 70 independent experiments. Corresponding control data are shown in Extended Data Fig. 5. b, e, h, Examples of defects in live oocytes. Chromosomes (magenta) were labelled with H2B–mRFP, microtubules (green) with eGFP–α-tubulin. Quantifications in a, d, g. Scale bars, 10 µm. c, f, i, The z-scores were calculated as the deviation of the mean of a single siRNA mix to the mean of all controls of the RNAi screen, normalized to the s.d. of all controls. siRNA mixes were sorted according to their z-score. The dashed line delineates mixes with a z-score higher than two s.d. above the average value of all controls. j, List of genes that were tracked down to the individual gene level in the RNAi screen. Note that defects caused by depletion of some proteins such as Zfp420 or Uhrf1 may reflect the function of more proximal genes under the control of these proteins. We were able to allocate 16 out of 20 tested defects to individual genes. Defects that could not be tracked down to individual gene level are shown as grey bars ending after the second or third round.

Extended Data Figure 5 Frequency of meiosis I and meiosis II defects in oocytes treated with control siRNAs.

a–g, The frequency of scored general morphological defects (a), spindle defects in meiosis I (b), chromosome defects in meiosis I (c), defects in anaphase I (d), defects during cytokinesis (e), spindle defects in meiosis II (f) and chromosome defects in meiosis II (g) were scored in oocytes microinjected with control siRNAs. The absolute number of oocytes with each defect is given next to bars.

Extended Data Figure 6 Eif4enif1 is required for release from prophase arrest and Birc5 for spindle integrity.

a, Live oocytes microinjected with control siRNA (control) or siRNAs targeting Eif4enif1 (Eif4enif1 RNAi) expressing eGFP–α-tubulin (green, microtubules) and H2B–mRFP (magenta, chromosomes) merged with differential interference contrast (DIC) image. Region of spindle and chromosomes is magnified without DIC below. Quantification of phenotype in b. Scale bar, 10 µm. b, Live oocytes microinjected with control siRNA or Eif4enif1 siRNAs were monitored by long-term time-lapse microscopy as shown in a and the efficiency of NEBD was scored. The number of analysed oocytes is specified next to bars. The P value was calculated with Fisher’s exact test. Data from a total of three experiments. c, Live oocytes microinjected with control siRNA (control) or siRNAs targeting Birc5 (Birc5 RNAi) expressing eGFP–α-tubulin (green, microtubules) and H2B–mRFP (magenta, chromosomes) merged with DIC. Region of spindle and chromosomes is magnified without DIC below. Quantification of phenotypes in d–g. Scale bar, 10 µm. d, Live oocytes microinjected with control siRNA (control), a mix of three different Birc5 siRNAs (siRNA 1–3) or two Birc5 siRNAs individually (siRNA 1, 2) were scored for temporary or permanent disintegration of the meiotic spindle. The number of analysed oocytes is specified next to bars. The P value was calculated with Fisher’s exact test comparing control and all Birc5 siRNA microinjected oocytes from five experiments. e–g, Live oocytes microinjected with control siRNA or Birc5 siRNAs were monitored by long-term time-lapse microscopy as shown in c and the efficiency of NEBD (e), the presence or absence of misaligned chromosomes (f) as well as the efficiency of chromosome segregation (g) were scored. The number of analysed oocytes is specified next to bars. P values were calculated with Fisher’s exact test. Data (d–g) from five independent experiments.

Extended Data Figure 7 Aspm function in mouse oocytes.

a, Oocytes microinjected with siRNAs targeting Aspm or injected with control siRNA. Microtubules in green, chromosomes in magenta. Arrows highlight lagging chromosomes. Quantification of phenotypes in b–g. Scale bar, 10 µm. b, c, Lagging (b) or misaligned chromosomes (c) in oocytes microinjected with different Aspm siRNAs. d–g, Live oocytes microinjected with control siRNA (control) or Aspm siRNAs (Aspm RNAi) were monitored by long-term time-lapse microscopy as shown in a and scored for progression through anaphase (d), time of anaphase onset (e), polar body extrusion (f) and spindle length (g). The number of analysed oocytes is specified next to bars. The P value was calculated with Fisher’s exact test (b, c, d, f) or Student’s t-test (e, g) comparing control and all Aspm siRNA microinjected oocytes. The box plots in e and g show median (line), mean (small square), 5th, 95th (whiskers) and 25th and 75th percentile (boxes). Data from four independent experiments.

Extended Data Figure 8 Mastl is required for metaphase II arrest and accurate chromosome segregation, but is dispensable for cytokinesis and chromosome condensation in mouse oocytes.

a, Live oocytes microinjected with control siRNA (control) or siRNAs targeting Mastl (Mastl RNAi) expressing eGFP–Lamin B1 (green, nuclear lamina) and H2B–mRFP (magenta, chromosomes) merged with DIC. Representative of 30 control and 16 Mastl RNAi oocytes. Scale bar, 10 µm. b, c, Live oocytes microinjected with a mix of three different Mastl siRNAs expressing human Greatwall fused with eGFP (green) and H2B–mRFP (magenta, chromosomes) merged with DIC. eGFP–Greatwall localized to the nucleus and was released into the cytoplasm shortly before NEBD, consistent with previous studies in mitotic cells29,30. Representative of 23 oocytes. Quantification in Fig. 3f. Scale bar, 10 µm. d–g, Live oocytes microinjected with control siRNA or Mastl siRNAs were monitored by long-term time-lapse microscopy and scored for anaphase progression (d), time of anaphase onset (e), successful formation or retraction of a polar body upon anaphase (f) and the prolonged presence of a midbody upon cytokinesis (g). The number of analysed oocytes is specified next to bars. Data from five independent experiments. h, Maximum z-projection (left) and three-dimensional reconstruction (right) of chromosomes (Hoechst) in fixed mouse oocytes microinjected with control siRNAs or siRNAs targeting Mastl were generated in Imaris. Quantification in i. i, The chromosome volume was quantified in mouse oocytes microinjected with control siRNAs or siRNAs targeting Mastl as shown in h in Imaris. The number of analysed oocytes is specified next to bars. Data from two independent experiments. j, Mastl mRNA levels in control oocytes and oocytes microinjected with Mastl siRNAs were quantified by real-time PCR. Mean values from two independent experiments. P values were calculated with Fisher’s exact test (d, f, g) or Student’s t-test (e, i). The box plots in e and j show median (line), mean (small square), 5th, 95th (whiskers) and 25th and 75th percentile (boxes).

Extended Data Figure 9 Systematic analysis of phenotype correlations in mouse oocytes.

a, b, Heatmap representation of clusters of phenotypes generated based on Jaccard indices between them. Jaccard indices, range between 0 and 1, were calculated as described in Methods and Extended Data Fig. 10. Jaccard indices calculated from control oocytes (a) and RNAi-treated oocytes (b) are shown. The ‘red’ and ‘blue’ respectively correspond to high and low Jaccard indices as indicated by the legend. Clusters of phenotypes were generated using Pheatmap with ‘Pearson correlation’ values and ‘average’ clustering input parameters.

Extended Data Figure 10 Network of phenotypes and calculation of Jaccard indices.

a, Network of phenotype to oocytes was converted into a phenotype–phenotype network based on number of oocytes that display two phenotypes in question. The network consists of 53 phenotypes and 867 connections between them. The nodes in the network denote phenotypes and edges denote shared oocytes. This is a qualitative network and does not consider the strength of connection, edge weight or number of oocytes in which a given pair of phenotypes co-occurs. Nodes of identical colours denote a cluster (a group of related phenotypes based on topological properties of the network). Phenotypes that are not part of any cluster are in the centre and indicated by squares (white). Related clusters (if they share phenotypes) are marked by dashed circles considered as ‘superclusters’. Clusters were identified by the NeMo method in Cytoscape. Network clusters are purely based on topological properties and are in agreement with the clusters in the heatmap constructed using quantitative measures of Jaccard indices (Extended Data Fig. 9a): for example, two superclusters, top left and top right respectively, correspond to heatmap clusters at the top left and middle of Extended Data Fig. 9a. b–d, Overview of computational approach with schematics to decipher phenotype clusters. Oi, Mi and Ni correspond to oocyte i, mix i and numerical value of phenotype i, respectively. b, Conversion of yes, no and numerical data depicts the way we converted a combination of ‘yes’, ‘no’ and numerical data (denoted by N1, N2, N3 and N4) of phenotypes across oocytes into purely ‘yes’ and ‘no’ groups with the ‘yes’ group further classified as ‘yes+’ and ‘yes−’. c, Reconstruction of the phenotype–oocyte network: we reconstructed a phenotype–oocyte network from the above data of ‘yes’ and ‘no’ values by considering only the ‘yes’ group. A nonlinear decay relationship between the number of phenotypes and number of oocytes in the network is displayed as represented by two plots. Details of the plots suggest a median value of 2 for phenotypes. d, Network transformation and calculation of Jaccard index matrix illustrate our network transformation strategy from a phenotype–oocyte network to a phenotype–phenotype network and the simultaneous estimation of Jaccard indices between phenotypes. The matrix of Jaccard indices between phenotypes was clustered using the pheatmap software in the R package with the ‘Pearson correlation’ parameter and the ‘average’ clustering method.

Supplementary information

Supplementary Table 1

This table contains transcriptome analysis of in vitro and in vivo grown oocytes. The table lists expression levels in in vitro and in vivo grown oocytes, it also indicates which genes were up- or down-regulated in oocytes grown in vitro based on NOISeq or DESeq analysis. (XLS 17296 kb)

Supplementary Table 2

This table contains annotated defects caused by targeting 798 genes in mouse oocytes. Every video of oocyte meiosis was scored for 41 potential defects, 5 meiotic times and the length and width of the spindle in meiosis I and II. All data are summarized in Supplementary Table 2. The targeting of genes that caused strong phenotypes in each category can be identified by sorting columns based on their Z-score. The table also includes hyperlinks to the individual video files. Some fields are empty because some parameters could not be determined. For instance, if oocytes failed to extrude a polar body the time of polar body extrusion could not be determined. Extended Data Fig. 2d shows a related network representation of phenotypes in oocytes microinjected with siRNA mixes. This file was updated online on 20 July 2015 to correct a hyperlink (XLSX 171 kb)

Supplementary Table 3

This table contains annotated defects for 2241 individual oocytes. Every video of oocyte meiosis was scored for 41 potential defects, 5 meiotic times and the length and width of the spindle in meiosis I and II. The parameters determined for every individual oocyte are listed. Some fields are empty or contain ‘not determined’. These reflect defects or parameters that could not be assessed in the particular oocyte. For instance, if the spindle was oriented vertical to the imaging plane at the time of anaphase, the presence of lagging chromosomes could not be assessed. Parameters for siRNA injected oocytes in different mixes are listed at the top of the table. Parameters for control oocytes are listed at the bottom of the table. (XLSX 950 kb)

Supplementary Table 4

This table contains siRNA sequences used in the screen. (XLS 341 kb)

DUSP7 is required to release oocytes from prophase arrest

Live oocytes microinjected with control siRNA (Control) or siRNAs targeting Dusp7 alone (Dusp7 RNAi) or with mRNA encoding EGFP-DUSP7, H2B-mRFP (magenta, chromosomes) merged with DIC. (MOV 5466 kb)

ASPM is required to prevent lagging chromosomes in oocytes

Live oocytes microinjected with control siRNA (Control) or siRNAs targeting Aspm (Aspm RNAi) expressing mEGFP-α-tubulin (green, microtubules) and H2B-mRFP (magenta, chromosomes). (MOV 3110 kb)

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Pfender, S., Kuznetsov, V., Pasternak, M. et al. Live imaging RNAi screen reveals genes essential for meiosis in mammalian oocytes. Nature 524, 239–242 (2015). https://doi.org/10.1038/nature14568

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