Job Summary: The Spence laboratory is part of the Department of Internal Medicine, the Department of Cell and Developmental Biology and the Department of Biomedical Engineering at the University of Michigan Medical School. We are recruiting a highly motivated postdoctoral fellow to join our research team, and to conduct research focused on understanding human lung development. Our research seeks to understand species differences during development, cellular heterogeneity, cell-cell communication and progenitor/stem cell regulation in the lung. The position will include use of primary human tissue specimens and human pluripotent stem cells to address these topic areas.

The Spence lab is a highly energetic and collaborative group made up of undergraduate and graduate students, postdoctoral fellows and staff scientists. We conduct team-based science, while fostering and encouraging intellectual independence and creative approaches to addressing biological questions. As a laboratory, our whole team is committed to fostering a safe, peaceful and respectful environment for everyone to work towards common scientific goals. We actively support a diverse workforce.

We are interested in receiving applications from qualified applicants with training in a range of disciplines, including (but not limited to) developmental biology, cell biology, molecular biology, engineering, gemonics/epigenomics, systems biology and computational biology. The following skills are helpful, but not essential: pluripotent stem cell culture, organoid culture, gene editing (i.e. Cas9/Crispr), histology and immunofluorescence, confocal microscopy, FACS, analysis of large data sets (i.e. RNA-sequencing).

Required Qualifications: Qualified applicants will hold a Ph.D. in one of the aforementioned (or related) disciplines, will be self-motivated, and will have a demonstrated history of productivity in the form of peer-reviewed publications. Strong interpersonal communication skills are essential.

Background Screening: Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings.  Background screenings are performed in compliance with the Fair Credit Report Act.

Mission Statement: Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally.  Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.

Interested applicants should email Jason Spence: spencejr@umich.edu

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Sarah E. Hall

Department of Biology, Syracuse University, Syracuse, NY 13244

For over a century, the nature versus nurture debate has questioned the relative contributions of genetic sequences and the environment to the phenotype of an individual (Galton 1869). Genome-wide association studies in humans have shown that environmental stress experienced in utero or during critical periods of development can affect the physiology of adults, even in the absence of the original stress in future generations (e.g. Kaati et al. 2007). The mechanism of this phenomenon, known as environmental programming, is through stress-specific modulation of the hippocampal-pituitary-adrenal (HPA) axis by epigenetic regulation of genes important for the mammalian stress response (Spencer 2013). Although some progress has been made in the mechanistic understanding of environmental programming over the last decade, some unanswered questions still remain. How does environmental stress globally influence the epigenome to affect development and behavior in animals? Do these environmentally programed changes in gene expression have evolutionary consequences?

To address these questions, we developed Caenorhabditis elegans as a model system of environmental programming as their developmental trajectory is dependent upon their environmental conditions in early life. If conditions are favorable for growth after hatching (available food, low population density), worms will develop continuously through four larval stages to become a reproductive adult (controls). However, if food is scarce or population density is high (detected by high levels of pheromone), worms can enter the dauer diapause stage (Cassada and Russell 1975). When dauers detect more favorable environmental conditions during migration, they can re-enter continuous development to become reproductive postdauer adults. Since C. elegans populations are primarily self-fertilizing hermaphrodites producing isogenic progeny, they offer the opportunity to directly examine the environmental regulation of gene expression.

Our initial experiments examining differences between wildtype control and postdauer adults that experienced crowding showed significant effects on gene expression profiles, genome-wide chromatin states, and life history traits such as longevity and reproduction (Hall et al. 2010). In addition, we found that endogenous small interfering RNA (endo-siRNA) sequences differed between the two populations, and that the argonaute CSR-1 was a major contributor to the environmental programming of postdauer phenotypes (Hall et al. 2013). After starting my own laboratory in 2012, we began follow-up experiments of my initial results, particularly brood size assays, to dissect the mechanism of environmental programming in C. elegans. To my surprise, we were getting the opposite results from what was expected—a feeling that a starting assistant professor does not want to experience! At the same time, a graduate student in my lab was examining the role of endogenous RNAi pathways in dauer formation, and was finding that mutations in RNAi components exhibited stress-specific effects on dauer formation and were required in different tissue types (Bharadwaj and Hall 2017). Together, these results led us to the realization that perhaps not all dauers are created equally, and that different early-life stresses may lead to distinct adult phenotypes. Our most recent study, “Early experiences mediate distinct adult gene expression and reproductive programs in Caenorhabditis elegans” published in PLoS Genetics, was born out of this new hypothesis.

To examine if different dauer-inducing stresses result in distinct adult phenotypes, analogous to what is observed in humans, we performed transcriptional profiling of control and postdauer adults that experienced either starvation or crowding (pheromone)-induced dauer in wild type and csr-1 hypomorph strains (Ow et al. 2018). In both wildtype datasets, we found over 1000 genes that exhibited significant changes in gene expression between postdauer and control adults. To our surprise, we found few genes whose expression were affected by dauer formation generally. Instead, we identified a set of 512 genes whose gene expression was opposite in postdauers compared to controls depending on the dauer-inducing stress (Figure 1). After careful validation using multiple biologically independent samples to verify that we did not just mix up the tubes, we were thoroughly convinced and named this set of genes the “seesaw” genes based on their up-or-down, stress-sensitive changes in gene expression. Curation of these genes showed that their expression patterns correlated with their stress-specific changes in mRNA levels between controls and postdauers. For example, in the starvation condition, genes expressed in somatic tissue were upregulated while genes expressed in the germ line were downregulated, and vice versa for crowding. The magnitude and pattern of these gene expression changes are so striking that it would be possible to determine the life history of worm just by measuring the mRNA levels of a few genes!

Figure 1 Early life history experience mediates gene expression in adults. Volcano plots representing mRNA changes between wild-type control and postdauer adults that experienced early-life (A) starvation or (B) crowding (pheromone) conditions. The dotted line indicates FDR cutoff of p = 0.05. Red and blue dots represent the WT_Phe down::WT_Stv up and WT_Phe up::WT_Stv down seesaw genes, respectively. This figure was originally published as Figure 1 A and B in Ow et al. (2018).

To examine how endogenous RNAi pathways may be playing a role in environmental programming, we also examined the transcriptional profiles of csr-1 hypomorph control and postdauer adults that experienced different stresses. Interestingly, we found that seesaw changes in gene expression were almost entirely eliminated in the csr-1 hypomorph, including for somatic genes that have not yet been identified as CSR-1 targets (Figure 2). The argonaute CSR-1 has been implicated in numerous mechanisms regulating gene expression, including promoting transcription and formation of euchromatic domains, post-transcriptional gene silencing, and inhibition of translation (Wedeles et al. 2013). Most of our knowledge of CSR-1 function is from studies within the germ line, including CSR-1’s germline expressed targets (Claycomb et al. 2009). However, these results suggest that CSR-1 may have more far-reaching effects on gene expression in tissues other than the germ line.

Figure 2 Environmentally programmed gene expression changes are dependent on CSR-1. Volcano plots depicting the mRNA changes between csr-1 hypomorph control and postdauer adults that experienced early-life (A) crowding or (B) starvation conditions. Dotted line indicates FDR cutoff p = 0.05. Red dots represent the csr-1_Phe down::csr-1_Stv up seesaw genes. This figure was originally published at Figure 2 in Ow et al. (2018).

Given the significant genome-wide effect we observed in the csr-1 hypomorph compared to wild type, we were curious whether CSR-1 was regulating the observed changes in mRNA at the transcriptional level. Since CSR-1 targets in the germ line have been shown to be physically clustered in the genome (Tu et al. 2015), we examined if there was a relationship between seesaw gene expression change and their chromosomal location. When we plotted the gene expression changes between control and postdauer adults for all genes in starvation or crowding conditions, we observed a striking trend indicating that a majority of genes exhibit seesaw expression, although not in the strict statistical sense of our transcriptional profiling analysis. When we mapped the seesaw genes to a chromosomal location, we were surprised to find that genes with similar changes in gene expression in the starvation conditions were found on the same chromosomes. For instance, genes that are upregulated in starvation-induced postdauers were enriched on chromosomes V and X, whereas genes that were downregulated in the same conditions were primarily enriched on chromosomes I and III (Figure 3). Since most isolated wild populations of C. elegans have been found in dauer (Frezal and Felix 2015), this observation suggests that gene expression changes in starvation-induced dauers are ecologically relevant, and perhaps beneficial, to the fitness of postdauers and may have contributed to the evolution of the C. elegans genome. This observation also is consistent with the model that CSR-1 could be regulating genes at the transcriptional level based on environmental cues. Since CSR-1 is thought to organize chromatin domains, selection may have favored clustering of genes with similar regulation in response to starvation so that chromatin remodeling of that “domain” could be more efficient. We are currently testing this hypothesis.

Figure 3 Chromosomal bias of CSR-1 targets and expression changes for all genes. Genes are categorized by quadrant analysis as shown in Figure 5A in Ow et al. (2018). * p < 0.05; ** p < 0.001; *** p < 0.001; **** p < 0.0001; χ²comparison to uniform distribution based on gene number per chromosome. This figure was originally published as Figure 5C in Ow et al. (2018).

To examine if the seesaw gene expression changes had consequences on fitness, we examined the evolutionarily selectable trait of brood size. We had previously shown that crowding-induced postdauers had a significantly larger brood size compared to control adults (Hall et al. 2010). Interestingly, the brood size seesaws similarly to gene expression, as starvation-induced postdauers have a significantly lower brood size compared to controls (Figure 4). Since C. elegans development is famously invariant (Kipreos 2005), we wondered about the developmental mechanism regulating the stress-specific changes in reproductive plasticity. Worm germ line development begins with mitotic cell proliferation maintained by the distal tip cell in early larval stages. As the gonad grows and expands, the cells pushed beyond the distal tip cell undergo meiosis, first becoming sperm during the L4 larval stage and then oocytes during adulthood (Kimble and White 1981; Austin and Kimble 1987). Given that self-fertilization in hermaphrodites is limited by the number of sperm produced, we hypothesized that changes in sperm number could result in altered brood size in adults.

Figure 4 Reproductive plasticity is dependent on early life history. Whisker-box plots (minimum and maximum of all data) of the average brood size for controls (CON) and postdauers (PD) that experienced (A) high pheromone or (B) starvation for WT, csr-1 hypomorph, glp-4(bn2), and sid-1(qt9) strains. Assays for WT, the csr-1 hypomorph, and sid-1(qt9) were performed at 20ºC; brood assays for glp-4(bn2) were performed at 15ºC. Total sample number is indicated by n over at least 3 biologically independent trials. This figure was originally published as Figure 6A and B in Ow et al. (2018).

A major difficulty in developing this manuscript was how to test our brood size hypothesis. Our initial attempts to count mature sperm in young adult animals were unsuccessful due to high variability in sperm counts relative to the brood size differences between control and postdauer adults. Eventually, we decided to examine for differences in the onset of germline proliferation in early larval stages, with the expected result being that starvation-induced postdauers would initiate germline proliferation later, and crowding-induced postdauers earlier, compared to controls. Germline proliferation begins in the L3 larval stage. However, dauer animals bypass the L3 stage; thus, our challenge was to determine a method to synchronize the somatic development of control and postdauer larvae to compare the onset of proliferation. Since the vulva has distinct morphology characteristic of each developmental stage (Seydoux et al. 1993; Mok et al. 2015), we used vulva development as our method of synchronizing populations. Using DAPI-staining of whole-mount larvae, we were able to determine that control and postdauer worms at the identical stage of somatic development exhibited different numbers of germ cell rows. Our results indicated that crowding-induced and starvation-induced postdauer larvae exhibited significantly greater or fewer germ line cell rows, respectively, compared to controls. This observation was consistent with our hypothesis and the brood size differences in adult populations. From a developmental perspective, these results are logical given that larvae induced into dauer by starvation would have less fat stored compared to crowding-induced dauers. Dauer formation and exit is likely to be metabolically expensive, especially since dauers are non-feeding; thus, it may require more time for starvation-induced postdauers to acquire enough fat to begin reproduction. In addition, environmental stresses such crowding and starvation have been shown to negatively regulate germline proliferation in L4 control animals through modulation of Notch genes via TGF-ß signaling (Pekar et al. 2017; Dalfó et al. 2012). TGF-ß signaling also regulates dauer formation based on environmental cues (Fielenbach and Antebi 2008), and a connection between this pathway and the regulation of seesaw genes and the brood size phenotype remains to be determined. Why crowding-induced dauer formation results in an earlier onset of germline proliferation, and not a delay similar to starvation, is not clear. However, we can speculate that postdauer worms that were crowded, but not starved, may begin germline proliferation earlier to produce a few offspring before the food is depleted.

Although many questions still remain regarding the mechanisms regulating seesaw gene expression, we were able to determine some mechanistic points of our model by performing qRT-PCR and brood size analysis in control and postdauer adults of different mutant strains. First, our csr-1 hypomorph transcriptional profiling results evoked two non-mutually exclusive hypotheses to explain CSR-1 function in environmental programming: 1) CSR-1 dependent signals are exported from the germ line to regulate somatic gene expression, or 2) CSR-1 targets a unique set of genes in somatic tissues compared to the germ line. Using a glp-4(bn2) strain, which lacks a germ line at restrictive temperature, we determined that a functional germ line was only required for starvation-induced phenotypes, not crowding phenotypes, regardless of where the genes are expressed. This conclusion was also consistent with the brood sizes assays of glp-4 animals at the permissive temperature (Figure 4). Given that the seesaw changes appear to involve crosstalk between tissue types, and CSR-1 is in the endogenous RNAi pathway, we also examined whether systemic RNAi might play a role. Systemic RNAi involves the spread of double stranded RNAs between cell and tissue types, which ultimately results in the downregulation of the homologous mRNA (Winston et al. 2002; Feinberg and Hunter 2003). To our surprise, only the crowding-induced phenotypes required the effector of systemic RNAi, SID-1, suggesting the possibility that endogenous dsRNA may transmit signals across tissue types about environmental conditions (Figure 4). Thus, we derived a model whereby the starvation-induced phenotypes require signals from the germ line that are not dsRNA, and the crowding-induced phenotypes require systemic RNAi but not the germ line (Figure 5). This model indicates that CSR-1 can function in somatic tissue independently from the germ line for the crowding phenotypes. However, in the starvation condition, whether the germ line signal requires CSR-1 function remains unclear. Moreover, where the systemic RNAi and germline-dependent signals are being produced, where they are being received, and what genes they might be regulating to elicit the stress-specific phenotypes are yet to be determined.

Figure 5 Postdauer animals retain a cellular memory of early environmental history that governs gene expression and reproductive plasticity. The germ line, SID-1, and CSR-1 mediate the crowding- and starvation-induced programs. This figure was originally published as Figure 7 in Ow et al. (2018).

An interesting aspect of this model is that the separate mechanisms for starvation and crowding induced phenotypes are in opposition, such that if you mutate one pathway (i.e. glp-4 for starvation phenotypes), the postdauer animals exhibit the phenotypes of the opposite stress (Figure 4). This observation suggests that starvation and crowding-induced mechanisms regulating the seesaw genes may share common components, but whether that pathway is in “starvation mode” or “crowding mode” is determined by stress-specific cues. Identification and dissection of these pathways will be critical in understanding how different stresses in early development can result in distinct adult phenotypes. Different early-life stresses in humans also result in different gene expression and phenotypic outcomes in adults; thus, we are more like worms than ever before.

Austin, Judithe, and Judith Kimble. “glp-1 is required in the germ line for regulation of the decision between mitosis and meiosis in C. elegans.” Cell 51.4 (1987): 589-599.

Bharadwaj, Pallavi S., and Sarah E. Hall. “Endogenous RNAi pathways are required in neurons for dauer formation in Caenorhabditis elegans.” Genetics 205.4 (2017): 1503-1516.

Cassada, Randall C., and Richard L. Russell. “The dauerlarva, a post-embryonic developmental variant of the nematode Caenorhabditis elegans.” Developmental biology 46.2 (1975): 326-342.

Claycomb, Julie M., et al. “The Argonaute CSR-1 and its 22G-RNA cofactors are required for holocentric chromosome segregation.” Cell 139.1 (2009): 123-134.

Dalfó, Diana, David Michaelson, and E. Jane Albert Hubbard. “Sensory regulation of the C. elegans germline through TGF-β-dependent signaling in the niche.” Current Biology 22.8 (2012): 712-719.

Fielenbach, Nicole, and Adam Antebi. “C. elegans dauer formation and the molecular basis of plasticity.” Genes & development 22.16 (2008): 2149-2165.

Feinberg, Evan H., and Craig P. Hunter. “Transport of dsRNA into cells by the transmembrane protein SID-1.” Science301.5639 (2003): 1545-1547.

Frézal, Lise, and Marie-Anne Félix. “The natural history of model organisms: C. elegans outside the Petri dish.” Elife 4 (2015): e05849.

Galton, Francis. Hereditary genius: An inquiry into its laws and consequences. Vol. 27. Macmillan, 1869.

Hall, Sarah E., et al. “A cellular memory of developmental history generates phenotypic diversity in C. elegans.” Current Biology 20.2 (2010): 149-155.

Hall, Sarah E., et al. “RNAi pathways contribute to developmental history-dependent phenotypic plasticity in C. elegans.” Rna 19.3 (2013): 306-319.

Kaati, Gunnar, et al. “Transgenerational response to nutrition, early life circumstances and longevity.” European Journal of Human Genetics 15.7 (2007): 784.

Kimble, J. E., and J. G. White. “On the control of germ cell development in Caenorhabditis elegans.” Developmental biology 81.2 (1981): 208-219.

Kipreos, Edward T. “Developmental cell biology: C. elegans cell cycles: invariance and stem cell divisions.” Nature Reviews Molecular Cell Biology 6.10 (2005): 766.

Mok, Darren ZL, Paul W. Sternberg, and Takao Inoue. “Morphologically defined sub-stages of C. elegans vulval development in the fourth larval stage.” BMC developmental biology 15.1 (2015): 26.

Ow, Maria C., et al. “Early experiences mediate distinct adult gene expression and reproductive programs in Caenorhabditis elegans.” PLoS genetics 14.2 (2018): e1007219.

Pekar, Olga, et al. “Linking the environment, DAF-7/TGFβ signaling and LAG-2/DSL ligand expression in the germline stem cell niche.” Development 144.16 (2017): 2896-2906.

Seydoux, Geraldine, Cathy Salvage, and Iva Greenwald. “Isolation and characterization of mutations causing abnormal eversion of the vulva in Caenorhabditis elegans.” Developmental biology 157.2 (1993): 423-436.

Spencer, Sarah J. “Perinatal programming of neuroendocrine mechanisms connecting feeding behavior and stress.” Frontiers in neuroscience 7 (2013): 109.

Tu, Shikui, et al. “Comparative functional characterization of the CSR-1 22G-RNA pathway in Caenorhabditis nematodes.” Nucleic acids research 43.1 (2014): 208-224.

Wedeles, Christopher J., Monica Z. Wu, and Julie M. Claycomb. “A multitasking Argonaute: exploring the many facets of C. elegans CSR-1.” Chromosome research 21.6-7 (2013): 573-586.

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We have open postdoctoral positions in our lab. We are looking for researchers interested in understanding the mechanisms through which non-coding RNAs and RNA metabolic pathways regulate gene expression in mammals and how these mechanisms impact animal development and disease. Our lab uses a combination of mouse models and genetic tools together with biochemical and computational approaches to stringently define the roles of these pathways in vivo.

To learn more about our research go to our website at vidigallab.com

Who you are:

• You share our enthusiasm for RNA biology, gene regulation, mouse development, and tumor biology
• You have PhD-experience in one or more of the following: RNA biology, mouse genetics, developmental biology, tumorigenesis, massively-parallel sequencing techniques, or computational biology.

What we offer:

• Fully-funded postdoc positions.
• A stimulating and collaborative environment.
• Opportunity to start your own research program or lead ongoing projects.

Apply: Send the following to vidigal.lab@gmail.com

• 2 paragraph cover letter explaining your scientific trajectory and why you would like to join us.
• CV and email contacts for 3 references.

NIH is dedicated to building a diverse community in its training and employment programs. This position is subject to a background investigation.

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The transition to multicellularity in eukaryotes appears to be intimately linked to the transition from isogamy (gametes of the same size) to anisogamy (gametes of distinct sizes), and indeed to oogamy, a form of anisogamy with a large, immotile egg and a motile sperm. Volvocine algae provide a useful and fascinating model to study how this transition occurred, and a new paper in Development explores the genetics of the process in Volvox and some of its relatives. We caught up with first author Sa Geng and his PI James Umen, Joseph Varner Distinguished Investigator at the Donald Danforth Plant Science Center in St. Louis Missouri, to hear the story behind the work.

James, can you give us your scientific biography and the questions your lab is trying to answer?

JU I was a PhD student at University of California, San Francisco where I studied yeast pre-mRNA splicing in Dr. Christine Guthrie’s laboratory. I moved to Dr. Ursula Goodenough’s laboratory at Washington University as a postdoc to work on the mechanism of chloroplast DNA inheritance and its control by mating type in the green alga Chlamydomonas. During that time we made a somewhat fortuitous discovery of a mutation in the Chlamydomonas retinoblastoma tumor suppressor gene that initiated an interest in cell size control, a problem which we have continued to work on in my own laboratory. During my stay in the Goodenough laboratory we had joint meetings with Dr. David Kirk’s group who were doing research at the forefront of Volvox developmental biology. My exposure to Volvox and my attendance of a class on the emerging field of evolution and development catalyzed a long-term interest in pursuing an integrative program of cell, developmental and evolutionary biology in volvocine algae (i.e. Chlamydomonas, Volvox and other multicellular relatives) in order to gain a better understanding of how ancestral genetic and cell biological mechanisms are co-opted and how new ones evolve during the transition to multicellularity.

A major question associated with the transition to multicellularity is the evolution and origin of male and female sexes; but tackling this problem seemed like a distant goal when I began my first independent position at Salk Institute in San Diego in 2002. By the time I moved my laboratory to Danforth Plant Science Center in 2011 volvocine algae had entered the era of modern genomics which gave us new tools and information for investigating the transition to multicellularity and evolution of sexes. Besides our work on cell size control and evolution of multicellularity, we also became interested in the control of intracellular carbon partitioning in algae which has some important practical implications for sustainable production of lipid-based biofuels and other bioproducts.

And Sa, how did you come to be involved with this project?

SG When I joined the Umen lab, the function of Volvox MID had not been tested and some of the important methods we needed such as transformation of Volvox and sexual crosses were not yet firmly established. After optimizing those methods we figured out the spermatogenesis function of MID in Volvox and I became curious how MID evolved in algae and when it acquired the function to drive spermatogenesis. To answer these questions, I did cross-species MID transformation, putting GpMID and PsMID into female Volvox.

What makes volvocine algae useful models for evolutionary developmental biology?Are they easy models to work with on a day-to-day basis?

SG&JU From an evolutionary and taxonomic perspective volvocine algae are unique in being closely related, yet encompassing a graded series of multicellular innovations. They range from the well-studied model unicellular alga Chlamydomonas reinhardtii, to simple genera with small groups of coherently-organized undifferentiated cells, all the way to species like Volvox carteri that evolved a relatively complex pattern of morphogenesis, complete germ-soma division of labor, and oogamy. The haploid genomes of Chlamydomonas, Volvox, and other sequenced volvocine species have low genetic redundancy (no whole genome duplications) and are quite similar to each other in terms of gene content and gene number, prompting the question of how evolutionary innovations arose among organisms with such similar genetic toolkits. Both Chlamydomonas and Volvox (and other volvocine species) are relatively easy to culture and have short generation times. Besides classical genetics they have an expanding set of molecular genetic tools such as transformation, RNAi and CRISPR-based gene editing. Using these tools, it is now possible to test hypotheses about how gene/protein functions change (or not) in association with developmental innovations.

Can you give us the key results of the paper in a paragraph?

SG&JU Prior to our study we knew that a transcription factor called Mid (minus dominance) was a key mating type or sex determinant in volvocine algae. The Mid ortholog in unicellular Chlamydomonas (an isogamous species) specifies minus mating-type differentiation, while the Volvox Mid ortholog specifies spermatogenesis; but the Chlamydomonas MID gene was non-functional when expressed in Volvox. These results suggested to us that the spermatogenic function of Mid might have coevolved with sexual dimorphism. In our newly published study we expanded our cross-species complementation experiments and found that MID genes from two relatives of Volvox which are more closely related to it than Chlamydomonas—isogamous Gonium pectorale and anisogamous Pleodorina starrii—could both induce spermatogenesis in Volvox. The discovery that Mid from an isogamous species could function in Volvox spermatogenesis was unexpected and has forced us to rethink our model for the role of Mid and the Mid pathway in sex determination.

Since Mid proteins did not drive the transition to oogamy in volvocine algae, do you have any idea about which factors/genetic changes did?

SG&JU We are pretty sure that the number of Mid-controlled genes in Volvox has expanded substantially compared with Chlamydomonas and other isogamous genera, which makes sense because spermatogenesis involves the deployment of developmental programs that have no direct analogs in isogamous species. If Mid itself did not change substantially in the transition from isogamy to anisogamy/oogamy, then perhaps its hypothetical partner protein(s) changed to enable more target genes to be controlled. Alternatively, if a few key developmental TFs from Volvox gained Mid binding sites in their promoters, then perhaps those cis-regulatory changes were sufficient to indirectly expand the Mid network without requiring any major changes in Mid DNA binding specificity or changes its partner protein(s). We are now actively pursuing the identity of Mid target genes and Mid interacting proteins to get at this question.

What does your work suggest about evolutionary divergence of transcription factors following species divergence?

SG & JU This is an interesting topic that prompts some thought about the concept of homology and origins of phenotypic novelties. For Pax6/Eyeless the proteins from flies and vertebrates retained a high degree of sequence similarity and functional interactions, perhaps because they evolved as parts of a regulatory module for specifying eyes that was already highly constrained in their common ancestor and/or predisposed to evolve via downstream interactions, just as we think the Mid network did in volvocine algae. On the other hand, a small number of changes in the conserved plant TF Leafy was sufficient for neofunctionalization by altering its DNA binding site. In the case of Mid proteins in volvocine algae they are much faster evolving than Pax6/Eyeless or Leafy, so we were expecting that there might have been a major change in Mid function associated with the transition from isogamy to anisogamy/oogamy, but clearly Mid was not the major locus of change for the emergence and elaboration of this novel trait. Determining whether there are any patterns and rules for TF network evolution is still a major challenge.

When doing the research, did you have any particular result or eureka moment that has stuck with you?

SG Yes. I was intrigued to see that the induced female Volvox with a Gonium MID transgene produced sperm packets under microscope. Then I asked Dr. Umen to come over to check the culture on the slide. I noticed Dr. Umen was excited, but he was obviously not so sure with the result. Then we decided to do more experiments to confirm the finding. The lesson I learned here is to do more scientific analysis and experiments to make the data more convincing when unexpected results come up.

And what about the flipside: any moments of frustration or despair?

SG Frustration is always around when we are doing science, sometimes big, sometimes small. Transforming Volvox requires a lot of time and planning, and I felt frustrated when the transformation efficiency for Volvox was not ideal. When this occurred, I had to spend some time to figure out what’s the problem from the setting of the gene gun to the materials and reagents I used in the lab. I’m happy everything went well finally.

What next for you Sa?

SG My interest is still on the regulation mechanism of sex determination in volvocine algae. I will focus on the sex determination function of the Mid protein in Volvox and on the Mid network.

Where will this work take the Umen lab?

JU Some important new directions have emerged from our study. We think the Mid network expanded during the transition to oogamy in Volvox, but we don’t know how. We want to determine whether Mid binds DNA on its own or with other proteins, what are its target genes in different volvocine species, and how did its new targets get recruited during the transition to anisogamy and oogamy. On a more general level we are asking the question of how TF networks expand and integrate new inputs and developmental processes as they evolve more complex functions.

Finally, let’s move outside the lab – what do you like to do in your spare time?

JU My favorite hobbies outside of the lab are food (cooking and eating), tennis and fly fishing, plus anything else that gets me into the outdoors/nature.

SG I usually take care of my vegetable garden when I don’t need to go to lab to see my algae. I play table tennis with my wife almost every day, and I also go to fitness centre quite often recently.

Evolutionary divergence of the sex-determining gene MID uncoupled from the transition to anisogamy in volvocine algae. Sa Geng, Ayano Miyagi, James G. Umen
Development 2018 145: dev162537 doi: 10.1242/dev.162537

This is #40 in our interview series. Browse the archive here. 

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We seek candidates interested in completing a PhD thesis within the framework of a research project (46 months) funded by the Swiss National Science Foundation (SNF).

Chromosome reorganization during spermatogenesis is dramatic. Beyond meiosis, it includes chromosome compaction into an elongated sperm nucleus which is accompanied by an almost complete exchange of histones with sperm nuclear basic proteins (SNBPs). Exploiting advantages of the model organism Drosophila melanogaster, our project addresses: (1.) Homolog pairing and chromosome territory formation in spermatocytes and its molecular basis. (2.) Molecular mechanisms maintaining homolog conjunction until metaphase I, as well as Separase-dependent resolution of this conjunction just before anaphase I. (3.) Transformation of the spherical postmeiotic spermatid nucleus into the compact needle shape present in mature sperm. A wide range of methods will be applied (genetics: classic, RNAi, CRISPR/cas, proteomics, time lapse imaging, FISH, immunofluorescence).

Prerequisite for the PhD position is a MSc degree (or equivalent) in biology, biochemistry or related fields. We are looking for a highly motivated individual with a strong background in cell biology, developmental biology, molecular biology, genetics, biochemistry. Experience with Drosophila is beneficial. Successful candidates will join the PhD program in Molecular Life Sciences (MLS) of the Life Science Zurich Graduate School (LSZGS) jointly organized by ETH and University of Zurich (UZH). UZH is an equal opportunity employer.

Application deadline is 31 May 2018. Application documents should include a motivation letter, curriculum vitae and a grade transcript. Applications should be sent electronically as one single file in PDF format to the address below. Additionally, candidates should organize that two to three letters of recommendation are sent to the same address.

Prof. Dr. Christian Lehner, Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland. christian.lehner[at]imls.uzh.ch

Additional information: www.imls.uzh.ch/en/research/Lehner.html

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We invite applications for a postdoctoral position to join a multidisciplinary project in the Alenius group at Umeå university. The project is based on our recent discovery that Hedgehog control neuronal activity in both Drosophila and mouse^{1. 2}  The approach is to combine Drosophila genetics, biochemistry with imaging in order to investigate the fundamental mechanisms that control neuronal activity and communication.

We are now looking for a highly motivated candidate, with a strong background in either Drosophila molecular biology or cell signalling. Additional skills in Drosophila neuroscience, imaging, and cryo-EM are considered a plus. The position involves using Drosophila genomic tools, biochemistry and live cell imaging, which in combination with cryo-EM and super-resolution microscopy and cutting-edge neuroscience approaches to identify the mechanisms by which hedgehog regulate neuronal activity.

Candidates are encouraged to send applications (cover letter, CV, and contact information of 3 references) to mattias.alenius@umu.se. Recommended application deadline is May 15th, 2018. Application review will start immediately until the position is filled. Openings are available immediately and the position is funded until the end of 2020.

Umeå and the Department of molecular biology: Umeå is a very metropolitan city with an international, welcoming and open attitude. The university and the department of molecular biology has a long standing tradition of big discoveries and is the birth place of the CRISPR/Cas9 technology. The university has several highly advanced technical platforms, including imaging and correlative electron microscopy platforms. The Department is creative, interdisciplinary and cutting edge and you will be part of one of the strongest Drosophila research environments in Sweden.

1. 1. Hedgehog signaling regulates ciliary localization of mouse odorant receptors. PNAS, Kumar Maruya D., Bohm S. and Alenius M. 2017
2. Hedgehog signaling regulates the ciliary transport of odorant receptors in Drosophila. Cell Reports, Sanchez G. M., Alkhori L., Hatano E., Schultz S. W., Kuzhandaivel A., Jafari S., Granseth B., and Alenius M. 2016

Group page: (http://www.molbiol.umu.se/english/research/researchers/mattias-alenius/)

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After leaving the bar, what are we to do? I propose to move on to a better bar (and I hope that you will not be disappointed when you find out that I’m actually referring to an interval).

In a previous blog I advocated the transparent presentation and reporting of data in graphs. It was highlighted that 95% confidence intervals (95%CI) are the preferred indicator of uncertainty (Gardner and Altman, 1986; Cumming 2013).The 95%CI of the median can be indicated by notches in boxplots (Krzywinski and Altman, 2014). The calculation of this 95%CI is based on the interquartile range (McGill et al., 1978). However, this definition does not allow for asymmetric confidence intervals and may therefore not be ideal when samples sizes are moderate and distributions are non-normal or skewed. Here, I will discuss another method for calculating and visualising the 95%CI for the median, which is based on bootstrapping. The analysis and visualization is done using the open source software environment R & ggplot2 and the scripts are available here.

Asymmetry & the median

In our work, the distribution of measured values rarely adheres to a normal distribution. Skewed, or asymmetric distributions are commonly encountered. It has been put forward that the normal (or Gaussian) distribution is the exception rather than the norm (Wilcox, 2017). Moreover, when sample sizes are small, it is virtually impossible to determine whether it adheres to normality. In case of asymmetric distributions, the median is better measure of centrality (i.e. the typical or representative value of a sample) than the mean (Wilcox and Rousselet, 2017). As a consequence, it makes more sense to display medians instead of means when experimental data is visualised (footnote 1).

Bootstrap & the median

The bootstrap is a computational method that generates a large number of samples based on the existing experimental sample, instead of performing additional measurements (footnote 2). The bootstrap approach is a robust and versatile method that was introduced and popularized by Efron and colleagues (Efron, 1979; Efron and Tibshirani, 1986). It has been demonstrated to work (surprisingly) well. Its main powerful feature is that it can be used to derive statistics that are impossible to calculate directly. More details on bootstrapping can be found here and here). A brief description of the procedure follows. Suppose you have done a measurement and obtained a sample of 20 values. A random value is drawn from this experimental sample, and this is done 19 more times, to obtain a bootstrap sample (footnote 3). This procedure of resampling can be performed multiple times (usually somewhere between 1,000 and 10,000 times). The statistic of interest can be determined from each of the bootstrap samples. Figure 1 illustrates the bootstrap process for resampling the median 1000x (an animated version is available here).

Figure 1: The principle of bootstrapping. The original data (left panel) is resampled to generate a bootstrap sample and the median is determined. This process is repeated many times (1000x in this example) to generate a collection of new median values. The median of the sample is indicated by the horizontal line and this new value is added to the collection of medians (indicated with the large dot). An animated version of this figure as well as R scripts to generate these figures are available.

Confidence & the median

The 95%CI is supposed to capture the statistic of interest 95% of the time, if the sampling was repeated multiple times. Repeated sampling is exactly what the bootstrap procedure is all about. Therefore, we can use the bootstrapped samples of the median to derive the 95%CI of the median (Wood, 2004). To this end, we rank the 1000 median values that were obtained by resampling from low to high. The 95%CI is now defined by the middle 95% of these values (footnote 4). In case of 1000 bootstrapped samples we use the 25th value and the 975th value of the ranked medians as the limits of the confidence interval. Figure 2 shows the histogram of the sampling distributions and the limits of the 95%CI as vertical lines.

Figure 2: The distribution of 1000 median values obtained by bootstrapping (same data as used in figure 1). The vertical lines indicate the limits of the 95% confidence interval [0.74, 0.81].

Let’s get back to where it all started, i.e. better bars intervals. As an example I compare the data shown in a previous blog with the 95%CI determined as for boxplot notches and the 95%CI calculated by the percentile bootstrap (figure 3). The medians and the confidence intervals are shown below as grey bars (the raw data is left out of the plot to draw attention to the 95%CIs). The main difference between the two methods is the asymmetry of the confidence interval that was determined by bootstrapping which better reflects the underlying data.

Figure 3: Comparison of the 95% confidence interval (indicated with a grey bar) as defined for boxplot notches (left) and determined by boostrapping (right). An R script to produce this figure is available here.

Final Words

The percentile bootstrap method for calculating confidence intervals for the median is “not bad”, but improved bootstrap methods are described (Hesterberg, 2015). There is also another way to determine a 95%CI of the median based on work by Hettmansperger and Sheather which is implemented in R (Wilcox and Rousselet, 2017).

Which of the methods for calculating the 95%CI works best for your data needs to be judged on a case-by-case basis. Only if the distribution of the population values is known, the best 95%CI can be identified by performing simulations. However, since the properties of the population distribution are usually unknown, a firm conclusion on the most accurate 95%CI is not possible. To conclude, I like the percentile bootstrap method for calculation of the 95%CI for the median since it is relatively accurate, intuitive and it allows for asymmetric intervals.

Shout-outs to:

–Peter Kamerman for the code on his blog that was used to calculate the 95%CI by bootstrap: https://www.painblogr.org/2017-10-18-purrring-through-bootstraps.

–Guillaume Rousselet for explaining the basics of robust methods and for sharing his insights on robust statistics in numerous blogs.

–Marten Postma for introducing me to bootstrap methods.

Footnotes

Footnote 1: The median is not a cure-all and has some issues of its own. Another robust measure of centrality for non-gaussian distributions is the trimmed mean. The accompanying R scripts can be modified to determine the 95%CI of a trimmed mean via the percentile bootstrap.

Footnote 2: To experimentalists, the bootstrap approach may seem like cheating. It is important to realize that the bootstrap method does not increase the number of datapoints. Instead, it is based on the concept that the existing sample represents the population and therefore can be resampled to obtain new samples that also represent the population that was originally sampled.

Footnote 3: In bootstrapping the resampling is performed with replacement, which means that the same value can be drawn multiple times.

Footnote 4: Since the confidence interval is based on the middle 95% of the distribution and the limits of the interval are based on ‘percentiles’ this procedure is also known as the percentile bootstrap.

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Laboratory: Laboratory of developmental biology, dr. Alena Krejci, Biology Centre, Czech Academy of Sciences, Ceske Budejovice, Czech republic

http://www.prf.jcu.cz/en/kmb/research/research-groups/laboratory-of-developmental-biology.html

We aim to dissect the interplay between metabolism and major signalling pathways, with the emphasis on Notch signalling pathway.

Project: Metabolic stress as regulator of Notch signalling

The Notch pathway has been described in several contexts to regulate glycolytic as well as mitochondrial metabolism (including paper from our lab Slaninova V, Open Biology, 2016). At the same time, recent evidence suggest that Notch pathway activity is sensitive to the cell metabolic parameters, such as the NAD:NADH ratio, amino acid availability or activity of metabolism related signalling pathway such as mTOR (Horvath M, Biochem J, 2016 and our current paper in preparation). We investigate this interplay using Drosophila wing disc, eye disc and immune system as models. The theme of the postdoc/PhD project will be directed to identification of binding sites for a previsouly unknown Notch targeted transcription factor that mediates crosstalk between Notch signalling, metabolism and immunity.

Applicant: Applicant should have a degree in molecular or cellular biology. Previous experience with Drosophila, molecular biology techniques and/or confocal microscopy is welcome.

Position: Postdoc offer includes a fixed contract till end of 2019 with the possibility of extension. PhD position is a part of the 4-year PhD program at the Department of molecular biology and genetics, University of South Bohemia. More details of the Department at http://www.prf.jcu.cz/en/kmb

Send your CV including address of two referees to akrejci@prf.jcu.cz

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