Assessing Social – Ecological Trade-Offs to Advance Ecosystem-Based Fisheries Management

Modern resource management faces trade-offs in the provision of various ecosystem goods and services to humanity. For fisheries management to develop into an ecosystem-based approach, the goal is not only to maximize economic profits, but to consider equally important conservation and social equity goals. We introduce such a triple-bottom line approach to the management of multi-species fisheries using the Baltic Sea as a case study. We apply a coupled ecological-economic optimization model to address the actual fisheries management challenge of trading-off the recovery of collapsed cod stocks versus the health of ecologically important forage fish populations. Management strategies based on profit maximization would rebuild the cod stock to high levels but may cause the risk of stock collapse for forage species with low market value, such as Baltic sprat (Fig. 1A). Economically efficient conservation efforts to protect sprat would be borne almost exclusively by the forage fishery as sprat fishing effort and profits would strongly be reduced. Unless compensation is paid, this would challenge equity between fishing sectors (Fig. 1B). Optimizing equity while respecting sprat biomass precautionary levels would reduce potential profits of the overall Baltic fishery, but may offer an acceptable balance between overall profits, species conservation and social equity (Fig. 1C). Our case study shows a practical example of how an ecosystem-based fisheries management will be able to offer society options to solve common conflicts between different resource uses. Adding equity considerations to the traditional trade-off between economy and ecology will greatly enhance credibility and hence compliance to management decisions, a further footstep towards healthy fish stocks and sustainable fisheries in the world ocean.Open in a separate windowFigure 1Summary of multispecies management options in the Baltic.(A) Profit maximum. (B) Economic optimum while respecting sprat B_PA. (C) Equitable optimum while respecting sprat B_PA. Central numbers indicate total profits (million €/year) as well as an equity measure (in brackets). Area of each pie slice is relative to status quo values 2008-2010 (black circle), with error bars from sensitivity analysis.     

Triple X Egyptian woman and a Down's syndrome offspring

The 47, XXX karyotype (triple X) has a frequency of 1 in 1000 female newborns. However, this karyotype is not usually suspected at birth or childhood. Female patients with a sex chromosome abnormality may be fertile. In patients with a 47, XXX cell line there appears to be an increased risk of a cytogenetically abnormal child but the extent of this risk cannot yet be determined; it is probably lower in the non-mosaic 47, XXX patient than the mosaic 46, XX/47, XXX one. We describe a new rare case of triple X woman and a Down''s syndrome offspring. The patient is 26 years of age. She is a housewife, her height is 160 cm and weight is 68 kg and her physical features and mentality are normal. She has had one pregnancy at the age of 25 years resulted in a girl with Down''s syndrome. The child had 47 chromosomes with trisomy 21 (47, XX, +21) Figure 1. The patient also has 47 chromosomes with a triple X karyotype (47, XX, +X) Figure 2. The patient''s husband (27 years old) is physically and mentally normal. He has 46 chromosomes with a normal XY karyotype (46, XY). There are neither Consanguinity between her parent''s nor she and her husband.Open in a separate windowFigure 1Karyotype 47, XX + 21 of the daughter of Triple X syndromeOpen in a separate windowFigure 2Karyptype 47, XX + X of the Down syndrome''s mother     

Testicular Sclerosing Sertoli Cell Tumor: A Case Report and Review of the Literature

Sertoli cell tumors are very rare testicular tumors, representing 0.4% to 1.5% of all testicular malignancies. They are subclassified as classic, large-cell calcifying, and sclerosing Sertoli cell tumors (SSCT) based on distinct clinical features. Only 42 cases of SSCTs have been reported in the literature. We present a case of a 23-year-old man diagnosed with SSCT.Key words: Testicular neoplasm, Sertoli cell tumor, Sclerosing Sertoli cell tumorA 23-year-old man was referred to the Cleveland Clinic Department of Urology (Cleveland, OH) for an incidentally detected right testicular mass. The mass was identified during a work-up for transient left testicular discomfort. His only notable medical history was nephrolithiasis. There was no personal or family history of testicular cancer or cryptorchidism. On physical examination, he was a well-nourished, well-masculinized young man without gynecomastia. Testicular examination revealed normal volume and consistency bilaterally without other relevant findings. Testicular ultrasonography demonstrated an 8 mm × 6 mm × 6 mm hypoechoic, solid mass in the posterior right testicle with peripheral flow on color Doppler (Figure 1).Open in a separate windowFigure 1Testicular ultrasound demonstrating an 8 mm × 6 mm × 6 mm hypoechoic, solid mass in the posterior right testicle (blue arrows).The remainder of the ultrasound examination yielded normal results. Lactic dehydrogenase, B-human chorionic gonadotropin, and α-fetoprotein levels were all within the normal range. After a thorough review of the options, the patient was then taken to the operating room for inguinal exploration. Intraoperative ultrasound confirmed a superficial 8-mm hypoechoic testis lesion. A whiteyellow, well-demarcated nodule was widely excised and a frozen section was sent to pathology for examination. The frozen section examination revealed the lesion to be a neoplasm with differential diagnosis including sclerosing Sertoli cell tumor (SSCT), adenomatoid tumor, and a variant of Leydig cell tumor. Because the final diagnosis could not be determined from frozen section, the decision was made to perform a right radical orchiectomy. Pathologic examination revealed a grossly unifocal, well-circumscribed, white, firm mass of 0.8 cm. Microscopically the lesion was composed of solid and hollow tubules and occasional anastomosing cords distributed within the hypocellular, densely collagenous stroma. Although the lesion was somewhat well circumscribed, entrapped seminiferous tubules with Sertoli-only cells were present within the tumor (Figure 2). Tumor cells had pale or eosinophilic cytoplasm with small and dark nuclei with inconspicuous nucleoli. The tumor was confined to the testis and margins were negative. A diagnosis of SSCT was reached, supported by positive immunostain results for steroidogenic factor 1, focal inhibin, and calretinin expression, and negative stain results for cytokeratin AE1/AE3 and epithelial membrane antigen in the tumor (Figure 3). The postoperative course was unremarkable. Computed tomography scan of the abdomen and pelvis and chest radiograph were negative for metastatic disease.Open in a separate windowFigure 2Low-power examination revealing a well-circumscribed tumor composed of solid and hollow tubules and occasional anastomosing cords distributed within the hypocellular, densely collagenous stroma. Hematoxylin and eosin stain, original magnification ×40. (B) High-power examination. Note entrapped seminiferous tubules lacking spermatogenesis. Hematoxylin and eosin stain, original magnification ×100.Open in a separate windowFigure 3Nuclear expression of steroidogenic factor 1 in the tumor as well as benign Sertoli cells in entrapped seminiferous tubules (original magnification ×200). (B) Focal calretinin expression in the tumor (inhibin had a similar staining pattern; original magnification ×100).     

The Incubation Period of Buruli Ulcer (Mycobacterium ulcerans Infection)

Introduction

Buruli Ulcer (BU) is caused by the environmental microbe Mycobacterium ulcerans. Despite unclear transmission, contact with a BU endemic region is the key known risk factor. In Victoria, Australia, where endemic areas have been carefully mapped, we aimed to estimate the Incubation Period (IP) of BU by interviewing patients who reported defined periods of contact with an endemic area prior to BU diagnosis.

Method

A retrospective review was undertaken of 408 notifications of BU in Victoria from 2002 to 2012. Telephone interviews using a structured questionnaire and review of notification records were performed. Patients with a single visit exposure to a defined endemic area were included and the period from exposure to disease onset determined (IP).

Results

We identified 111 of 408 notified patients (27%) who had a residential address outside a known endemic area, of whom 23 (6%) reported a single visit exposure within the previous 24 months. The median age of included patients was 30 years (range: 6 to 73) and 65% were male. 61% had visited the Bellarine Peninsula, currently the most active endemic area. The median time from symptom onset to diagnosis was 71 days (range: 34–204 days). The midpoint of the reported IP range was utilized to calculate a point estimate of the IP for each case. Subsequently, the mean IP for the cohort was calculated at 135 days (IQR: 109–160; CI 95%: 113.9–156), corresponding to 4.5 months or 19.2 weeks. The shortest IP recorded was 32 days and longest 264 days (Figure 1 & 2). IP did not vary for variables investigated.Open in a separate windowFigure 1Geographic representation of Bellarine Peninsula, considered endemic for BU as of 2012.Bellarine Peninsula – east of line from Geelong to Torquay. Mornington and Westernport – southwest of line from Hampton to Tooradin (including Phillip Island).Open in a separate windowFigure 2Geographic representation of East Gippsland, considered endemic for BU as of 2012.East Gippsland: East of Sale and south of the great divide.

Conclusions

The estimated mean IP of BU in Victoria is 135 days (IQR: 109–160 days), 4.5 months. The shortest recorded was IP 34 days and longest 264 days. A greater understanding of BU IP will aid clinical risk assessment and future research.     

Arabinogalactan proteins (AGPs) related to pollen tube guidance into the embryo sac in Arabidopsis

Some AGP molecules or their sugar moieties are probably related to the guidance of the pollen tube into the embryo sac, in the final part of its pathway, when arriving at the ovules. The specific labelling of the synergid cells and its filiform apparatus, which are the cells responsible for pollen tube attraction, and also the specific labelling of the micropyle and micropylar nucellus, which constitutes the pollen tube entryway into the embryo sac, are quite indicative of this role. We also discuss the possibility that AGPs in the sperm cells are probably involved in the double fertilization process.Key words: Arabidopsis, arabinogalactan proteins, AGP 6, gametic cells, pollen tube guidanceThe selective labelling obtained by us with monoclonal antibodies directed to the glycosidic parts of AGPs, in Arabidopsis and in other plant species, namely Amaranthus hypochondriacus,¹ Actinidia deliciosa² and Catharanthus roseus, shows that some AGP molecules or their sugar moieties are probably related to the guidance of the pollen tube into the embryo sac, in the final part of its pathway, when arriving at the ovules. The evaluation of the selective labelling obtained with AGP-specific monoclonal antibodies (Mabs) JIM 8, JIM 13, MAC 207 and LM 2, during Arabidopsis pollen development, led us to postulate that some AGPs, in particular those with sugar epitopes identified by JIM 8 and JIM 13, can be classified as molecular markers for generative cell differentiation and development into male gametes.Likewise, we also postulated that the AGP epitopes recognized by Mabs JIM 8 and JIM 13 are also molecular markers for the development of the embryo sac in Arabidopsis thaliana. Moreover, these AGP epitopes are also present along the pollen tube pathway, predominantly in its last stage, the micropyle, which constitutes the region of the ovule in the immediate vicinity of the pollen tube target, the embryo sac.³We have recently shown the expression of AGP genes in Arabidopsis pollen grains and pollen tubes and also the presence of AGPs along Arabidopsis pollen tube cell surface and tip region, as opposed to what had been reported earlier. We have also shown that only a subset of AGP genes is expressed in pollen grain and pollen tubes, with prevalence for Agp6 and Agp11, suggesting a specific and defined role for some AGPs in Arabidopsis sexual reproduction (Pereira et al., 2006).⁴Therefore we continued by using an Arabidopsis line expressing GFP under the command of the Agp6 gene promoter sequence. These plants were studied under a low-power binocular fluorescence microscope. GFP labelling was only observed in haploid cells, pollen grains (Fig. 1) and pollen tubes (Fig. 2); all other tissues clearly showed no labelling. These observations confirmed the specific expression of Agp6 in pollen grains and pollen tubes. As shown in the Figures 1 and ​and2,2, the labelling with GFP is present in all pollen tube extension, so probably, AGP 6 is not one of the AGPs identified by JIM 8 and JIM 13, otherwise GFP light emission would localize more specifically in the sperm cells.⁵ So we think that MAC 207 which labels the entire pollen tube wall (Fig. 3) may indeed be recognizing AGP6, which seems to be expressed in the vegetative cell. In other words, the specific labelling obtained for the generative cell and for the two male gametes, is probably given by AGPs that are present in very low quantities, apparently not the case for AGP 6 or AGP 11.Open in a separate windowFigure 1Low-power binocular fluorescence microscope image of an Arabidopsis flower with the AGP 6 promoter:GFP construct. The labelling is evident in pollen grains that are being released and in others that are already in the stigma papillae.Open in a separate windowFigure 2Low-power binocular fluorescence microscope image of an Arabidopsis ovary with the AGP6 promoter:GFP construct. The ovary was partially opened to show the pollen tubes growing in the septum, and into the ovules. The pollen tubes are also labelled by GFP.Open in a separate windowFigure 3Imunofluorescence image of a pollen tube growing in vitro, and labeled by MAC 207 monoclonal antibody. The labelling is evident all over the pollen tube wall.After targeting an ovule, the pollen tube growth arrests inside a synergid cell and bursts, releasing the two sperm cells. It has recently been shown that sperm cells, for long considered to be passive cargo, are involved in directing the pollen tube to its target. In Arabidopsis, HAP2 is expressed only in the haploid sperm and is required for efficient pollen tube guidance to the ovules.⁶ The same could be happening with the AGPs identified in the sperm cells by JIM 8 and JIM 13. We are now working on tagging these AGPs and using transgenic plants aiming to answer to such questions.Pollen tube guidance in the ovary has been shown to be in the control of signals produced by the embryo sac. When pollen tubes enter ovules bearing feronia or sirene mutations (the embryo sac is mutated), they do not stop growing and do not burst. In Zea mays a pollen tube attractant was recently identified in the egg apparatus and synergids.⁷ Chimeric ZmEA1 fused to green fluorescent protein (ZmEA1:GFP) was first visible within the filiform apparatus and later was localized to nucellar cell walls below the micropylar opening of the ovule. This is the same type of labelling that we have shown in Arabidopsis ovules, using Mabs JIM 8 and JIM 13. We are now involved in the identification of the specific AGPs associated with the labellings that we have been showing.     

Splenogonadal Fusion: An Unusual Case of an Acute Scrotum

We highlight a case on a normal left testicle with a fibrovascular cord with three nodules consistent with splenic tissue. The torsed splenule demonstrated hemorrhage with neutrophilic infiltrate and thrombus consistent with chronic infarction and torsion. Splenogonadal fusion (SGF) is a rather rare entity, with approximately 184 cases reported in the literature. The most comprehensive review was that of 123 cases completed by Carragher in 1990. Since then, an additional 61 cases have been reported in the scientific literature. We have studied these 61 cases in detail and have included a summary of that information here.Key words: Splenogonadal fusion, Acute scrotumA 10-year-old boy presented with worsening left-sided scrotal pain of 12 hours’ duration. The patient reported similar previous episodes occurring intermittently over the past several months. His past medical history was significant for left hip dysplasia, requiring multiple hip surgeries. On examination, he was found to have an edematous left hemiscrotum with a left testicle that was rigid, tender, and noted to be in a transverse lie. The ultrasound revealed possible polyorchism, with two testicles on the left and one on the right (Figure 1), and left epididymitis. One of the left testicles demonstrated a loss of blood flow consistent with testicular torsion (Figure 2).Open in a separate windowFigure 1Ultrasound of the left hemiscrotum reveals two spherical structures; the one on the left is heterogeneous and hyperdense in comparison to the right.Open in a separate windowFigure 2Doppler ultrasound of left hemiscrotum. No evidence of blood flow to left spherical structure.The patient was taken to the operating room for immediate scrotal exploration. A normalappearing left testicle with a normal epididymis was noted. However, two accessory structures were noted, one of which was torsed 720°; (Figure 3). An inguinal incision was then made and a third accessory structure was noted. All three structures were connected with fibrous tissue, giving a “rosary bead” appearance. The left accessory structures were removed, a left testicular biopsy was taken, and bilateral scrotal orchipexies were performed.Open in a separate windowFigure 3Torsed accessory spleen with splenogonadal fusion.Pathology revealed a normal left testicle with a fibrovascular cord with three nodules consistent with splenic tissue. The torsed splenule demonstrated hemorrhage with neutrophillic infiltrate and thrombus consistent with chronic infarction and torsion (Figure 4).Open in a separate windowFigure 4Splenogonadal fusion, continuous type with three accessory structures.     

What Can Article-Level Metrics Do for You?

Article-level metrics (ALMs) provide a wide range of metrics about the uptake of an individual journal article by the scientific community after publication. They include citations, usage statistics, discussions in online comments and social media, social bookmarking, and recommendations. In this essay, we describe why article-level metrics are an important extension of traditional citation-based journal metrics and provide a number of example from ALM data collected for PLOS Biology.The scientific impact of a particular piece of research is reflected in how this work is taken up by the scientific community. The first systematic approach that was used to assess impact, based on the technology available at the time, was to track citations and aggregate them by journal. This strategy is not only no longer necessary—since now we can easily track citations for individual articles—but also, and more importantly, journal-based metrics are now considered a poor performance measure for individual articles [1],[2]. One major problem with journal-based metrics is the variation in citations per article, which means that a small percentage of articles can skew, and are responsible for, the majority of the journal-based citation impact factor, as shown by Campbell [1] for the 2004 Nature Journal Impact Factor. Figure 1 further illustrates this point, showing the wide distribution of citation counts between PLOS Biology research articles published in 2010. PLOS Biology research articles published in 2010 have been cited a median 19 times to date in Scopus, but 10% of them have been cited 50 or more times, and two articles [3],[4] more than 300 times. PLOS Biology metrics are used as examples throughout this essay, and the dataset is available in the supporting information (Data S1). Similar data are available for an increasing number of other publications and organizations.Open in a separate windowFigure 1Citation counts for PLOS Biology articles published in 2010.Scopus citation counts plotted as a probability distribution for all 197 PLOS Biology research articles published in 2010. Data collected May 20, 2013. Median 19 citations; 10% of papers have at least 50 citations.Scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator [2],[5],[6]. To this end, PLOS has collected and displayed a variety of metrics for all its articles since 2009. The array of different categorised article-level metrics (ALMs) used and provided by PLOS as of August 2013 are shown in Figure 2. In addition to citations and usage statistics, i.e., how often an article has been viewed and downloaded, PLOS also collects metrics about: how often an article has been saved in online reference managers, such as Mendeley; how often an article has been discussed in its comments section online, and also in science blogs or in social media; and how often an article has been recommended by other scientists. These additional metrics provide valuable information that we would miss if we only consider citations. Two important shortcomings of citation-based metrics are that (1) they take years to accumulate and (2) citation analysis is not always the best indicator of impact in more practical fields, such as clinical medicine [7]. Usage statistics often better reflect the impact of work in more practical fields, and they also sometimes better highlight articles of general interest (for example, the 2006 PLOS Biology article on the citation advantage of Open Access articles [8], one of the 10 most-viewed articles published in PLOS Biology).Open in a separate windowFigure 2Article-level metrics used by PLOS in August 2013 and their categories.Taken from [10] with permission by the authors.A bubble chart showing all 2010 PLOS Biology articles (Figure 3) gives a good overview of the year''s views and citations, plus it shows the influence that the article type (as indicated by dot color) has on an article''s performance as measured by these metrics. The weekly PLOS Biology publication schedule is reflected in this figure, with articles published on the same day present in a vertical line. Figure 3 also shows that the two most highly cited 2010 PLOS Biology research articles are also among the most viewed (indicated by the red arrows), but overall there isn''t a strong correlation between citations and views. The most-viewed article published in 2010 in PLOS Biology is an essay on Darwinian selection in robots [9]. Detailed usage statistics also allow speculatulation about the different ways that readers access and make use of published literature; some articles are browsed or read online due to general interest while others that are downloaded (and perhaps also printed) may reflect the reader''s intention to look at the data and results in detail and to return to the article more than once.Open in a separate windowFigure 3Views vs. citations for PLOS Biology articles published in 2010.All 304 PLOS Biology articles published in 2010. Bubble size correlates with number of Scopus citations. Research articles are labeled green; all other articles are grey. Red arrows indicate the two most highly cited papers. Data collected May 20, 2013.When readers first see an interesting article, their response is often to view or download it. By contrast, a citation may be one of the last outcomes of their interest, occuring only about 1 in 300 times a PLOS paper is viewed online. A lot of things happen in between these potential responses, ranging from discussions in comments, social media, and blogs, to bookmarking, to linking from websites. These activities are usually subsumed under the term “altmetrics,” and their variety can be overwhelming. Therefore, it helps to group them together into categories, and several organizations, including PLOS, are using the category labels of Viewed, Cited, Saved, Discussed, and Recommended (Figures 2 and ​and4,4, see also [10]).Open in a separate windowFigure 4Article-level metrics for PLOS Biology.Proportion of all 1,706 PLOS Biology research articles published up to May 20, 2013 mentioned by particular article-level metrics source. Colors indicate categories (Viewed, Cited, Saved, Discussed, Recommended), as used on the PLOS website.All PLOS Biology articles are viewed and downloaded, and almost all of them (all research articles and nearly all front matter) will be cited sooner or later. Almost all of them will also be bookmarked in online reference managers, such as Mendeley, but the percentage of articles that are discussed online is much smaller. Some of these percentages are time dependent; the use of social media discussion platforms, such as Twitter and Facebook for example, has increased in recent years (93% of PLOS Biology research articles published since June 2012 have been discussed on Twitter, and 63% mentioned on Facebook). These are the locations where most of the online discussion around published articles currently seems to take place; the percentage of papers with comments on the PLOS website or that have science blog posts written about them is much smaller. Not all of this online discussion is about research articles, and perhaps, not surprisingly, the most-tweeted PLOS article overall (with more than 1,100 tweets) is a PLOS Biology perspective on the use of social media for scientists [11].Some metrics are not so much indicators of a broad online discussion, but rather focus on highlighting articles of particular interest. For example, science blogs allow a more detailed discussion of an article as compared to comments or tweets, and journals themselves sometimes choose to highlight a paper on their own blogs, allowing for a more digestible explanation of the science for the non-expert reader [12]. Coverage by other bloggers also serves the same purpose; a good example of this is one recent post on the OpenHelix Blog [13] that contains video footage of the second author of a 2010 PLOS Biology article [14] discussing the turkey genome.F1000Prime, a commercial service of recommendations by expert scientists, was added to the PLOS Article-Level Metrics in August 2013. We now highlight on the PLOS website when any articles have received at least one recommendation within F1000Prime. We also monitor when an article has been cited within the widely used modern-day online encyclopedia, Wikipedia. A good example of the latter is the Tasmanian devil Wikipedia page [15] that links to a PLOS Biology research article published in 2010 [16]. While a F1000Prime recommendation is a strong endorsement from peer(s) in the scientific community, being included in a Wikipedia page is akin to making it into a textbook about the subject area and being read by a much wider audience that goes beyond the scientific community. PLOS Biology is the PLOS journal with the highest percentage of articles recommended in F1000Prime and mentioned in Wikipedia, but there is only partial overlap between the two groups of articles because they focus on different audiences (Figure 5). These recommendations and mentions in turn show correlations with other metrics, but not simple ones; you can''t assume, for example, that highly cited articles are more likely to be recommended by F1000Prime, so it will be interesting to monitor these trends now that we include this information.Open in a separate windowFigure 5 PLOS Biology articles: sites of recommendation and discussion.Number of PLOS Biology research articles published up to May 20, 2013 that have been recommended by F1000Prime (red) or mentioned in Wikipedia (blue).With the increasing availability of ALM data, there comes a growing need to provide tools that will allow the community to interrogate them. A good first step for researchers, research administrators, and others interested in looking at the metrics of a larger set of PLOS articles is the recently launched ALM Reports tool [17]. There are also a growing number of service providers, including Altmetric.com [18], ImpactStory [19], and Plum Analytics [20] that provide similar services for articles from other publishers.As article-level metrics become increasingly used by publishers, funders, universities, and researchers, one of the major challenges to overcome is ensuring that standards and best practices are widely adopted and understood. The National Information Standards Organization (NISO) was recently awarded a grant by the Alfred P. Sloan Foundation to work on this [21], and PLOS is actively involved in this project. We look forward to further developing our article-level metrics and to having them adopted by other publishers, which hopefully will pave the way to their wide incorporation into research and researcher assessments.     

Endemicity,Biogeography, Composition,and Community Structure On a Northeast Pacific Seamount

The deep ocean greater than 1 km covers the majority of the earth''s surface. Interspersed on the abyssal plains and continental slope are an estimated 14000 seamounts, topographic features extending 1000 m off the seafloor. A variety of hypotheses are posited that suggest the ecological, evolutionary, and oceanographic processes on seamounts differ from those governing the surrounding deep sea. The most prominent and oldest of these hypotheses, the seamount endemicity hypothesis (SMEH), states that seamounts possess a set of isolating mechanisms that produce highly endemic faunas. Here, we constructed a faunal inventory for Davidson Seamount, the first bathymetric feature to be characterized as a ‘seamount’, residing 120 km off the central California coast in approximately 3600 m of water (Fig 1). We find little support for the SMEH among megafauna of a Northeast Pacific seamount; instead, finding an assemblage of species that also occurs on adjacent continental margins. A large percentage of these species are also cosmopolitan with ranges extending over much of the Pacific Ocean Basin. Despite the similarity in composition between the seamount and non-seamount communities, we provide preliminary evidence that seamount communities may be structured differently and potentially serve as source of larvae for suboptimal, non-seamount habitats.Open in a separate windowFigure 1Bathymetric map of the Central California Coast with Monterey Canyon and Davidson Seamount.     

A Large Number of Reviews on Physician Rating Websites May Reflect Reputation Management

BackgroundPhysicians with a large number of reviews and a high rating may be employing reputation management strategies. Specialists may be more likely than non-specialists to employ such strategies. This should be apparent in a study of online physician reviews on physician rating websites (PRW).MethodsUsing one physician rating website, we gathered orthopedic surgeon and family physician reviews. We measured Spearman correlations between the number of reviews and average numerical rating and used chi-squared to test threshold relationships.ResultsThere were very small negative Spear-man correlations between the number of online reviews and the average numerical rating for orthopedic surgeons (p= -0.097, p-value=<0.001) family medicine physicians (p= -0.170, p-value=<0.001; Figure 2). Physicians with more than 100 reviews had a greater average numerical rating than physicians with fewer than 50 reviews. Orthopedic surgeons are more likely than family medicine physicians to have a large number of reviews and average numerical rating greater than 3.Open in a separate windowFigure 2.Family medicine physicians average rating plotted against number of reviews.ConclusionThe small fraction of physician with a high number of reviews may be utilizing reputation management strategies, and this seems relatively specific to specialists rather than non-specialists. Level of Evidence: III     

Gamete attachment process revealed in flowering plant fertilization

Sex-possessing organisms perform sexual reproduction, in which gametes from different sexes fuse to produce offspring. In most eukaryotes, one or both sex gametes are motile, and gametes actively approach each other to fuse. However, in flowering plants, the gametes of both sexes lack motility. Two sperm cells (male gametes) that are contained in a pollen grain are recessively delivered via pollen tube elongation. After the pollen tube bursts, sperm cells are released toward the egg and central cells (female gametes) within an ovule (Fig. 1). The precise mechanism of sperm cell movement after the pollen tube bursts remains unknown. Ultimately, one sperm cell fuses with the egg cell and the other one fuses with the central cell, producing an embryo and an endosperm, respectively. Fertilization in which 2 sets of gamete fusion events occur, called double fertilization, has been known for over 100 y. The fact that each morphologically identical sperm cell precisely recognizes its fusion partner strongly suggests that an accurate gamete interaction system(s) exists in flowering plants.Open in a separate windowFigure 1.Illustration of the fertilization process in flowering plants. First, each pollen tube accesses an ovule containing egg and central cells. Next, the 2 sperm cells face the female gametes in the ovule after the pollen tube bursts. Finally, each sperm cell simultaneously fuses with either egg or central cell.     

Streptomyces Development in Colonies and Soils

Streptomyces development was analyzed under conditions resembling those in soil. The mycelial growth rate was much lower than that in standard laboratory cultures, and the life span of the previously named first compartmentalized mycelium was remarkably increased.Streptomycetes are gram-positive, mycelium-forming, soil bacteria that play an important role in mineralization processes in nature and are abundant producers of secondary metabolites. Since the discovery of the ability of these microorganisms to produce clinically useful antibiotics (2, 15), they have received tremendous scientific attention (12). Furthermore, its remarkably complex developmental features make Streptomyces an interesting subject to study. Our research group has extended our knowledge about the developmental cycle of streptomycetes, describing new aspects, such as the existence of young, fully compartmentalized mycelia (5-7). Laboratory culture conditions (dense inocula, rich culture media, and relatively elevated temperatures [28 to 30°C]) result in high growth rates and an orderly-death process affecting these mycelia (first death round), which is observed at early time points (5, 7).In this work, we analyzed Streptomyces development under conditions resembling those found in nature. Single colonies and soil cultures of Streptomyces antibioticus ATCC 11891 and Streptomyces coelicolor M145 were used for this analysis. For single-colony studies, suitable dilutions of spores of these species were prepared before inoculation of plates containing GYM medium (glucose, yeast extract, malt extract) (11) or GAE medium (glucose, asparagine, yeast extract) (10). Approximately 20 colonies per plate were obtained. Soil cultures were grown in petri dishes with autoclaved oak forest soil (11.5 g per plate). Plates were inoculated directly with 5 ml of a spore suspension (1.5 × 10⁷ viable spores ml⁻¹; two independent cultures for each species). Coverslips were inserted into the soil at an angle, and the plates were incubated at 30°C. To maintain a humid environment and facilitate spore germination, the cultures were irrigated with 3 ml of sterile liquid GAE medium each week.The development of S. coelicolor M145 single colonies growing on GYM medium is shown in Fig. ​Fig.1.1. Samples were collected and examined by confocal microscopy after different incubation times, as previously described (5, 6). After spore germination, a viable mycelium develops, forming clumps which progressively extend along the horizontal (Fig. 1a and b) and vertical (Fig. 1c and d) axes of a plate. This mycelium is fully compartmentalized and corresponds to the first compartmentalized hyphae previously described for confluent surface cultures (Fig. 1e, f, and j) (see below) (5); 36 h later, death occurs, affecting the compartmentalized hyphae (Fig. 1e and f) in the center of the colony (Fig. ​(Fig.1g)1g) and in the mycelial layers below the mycelial surface (Fig. 1d and k). This death causes the characteristic appearance of the variegated first mycelium, in which alternating live and dead segments are observed (Fig. 1f and j) (5). The live segments show a decrease in fluorescence, like the decrease in fluorescence that occurs in solid confluent cultures (Fig. ​(Fig.11 h and i) (5, 9). As the cycle proceeds, the intensity of the fluorescence in these segments returns, and the segments begin to enlarge asynchronously to form a new, multinucleated mycelium, consisting of islands or sectors on the colony surfaces (Fig. 1m to o). Finally, death of the deeper layers of the colony (Fig. ​(Fig.1q)1q) and sporulation (Fig. ​(Fig.1r)1r) take place. Interestingly, some of the spores formed germinate (Fig. ​(Fig.1s),1s), giving rise to a new round of mycelial growth, cell death, and sporulation. This process is repeated several times, and typical, morphologically heterogeneous Streptomyces colonies grow (not shown). The same process was observed for S. antibioticus ATCC 11891, with minor differences mainly in the developmental time (not shown).Open in a separate windowFIG. 1.Confocal laser scanning fluorescence microscopy analysis of the development-related cell death of S. coelicolor M145 in surface cultures containing single colonies. Developmental culture times (in hours) are indicated. The images in panels l and n were obtained in differential interference contrast mode and correspond to the same fields as in panels k and m, respectively. The others are culture sections stained with SYTO 9 and propidium iodide. Panels c, d, k, l, p, and q are cross sections; the other images are longitudinal sections (see the methods). Panels h and i are images of the same field taken with different laser intensities, showing low-fluorescence viable hyphae in the center of the colonies that develop into a multinucleated mycelium. The arrows in panels e and s indicate septa (e) and germinated spores (s). See the text for details.Figure ​Figure22 shows the different types of mycelia present in S. coelicolor cultures under the conditions described above, depending on the compartmentalization status. Hyphae were treated with different fluorescent stains (SYTO 9 plus propidium iodide for nucleic acids, CellMask plus FM4-64 for cell membranes, and wheat germ agglutinin [WGA] for cell walls). Samples were processed as previously described (5). The young initial mycelia are fully compartmentalized and have membranous septa (Fig. 2b to c) with little associated cell wall material that is barely visible with WGA (Fig. ​(Fig.2d).2d). In contrast, the second mycelium is a multinucleated structure with fewer membrane-cell wall septa (Fig. 2e to h). At the end of the developmental cycle, multinucleated hyphae begin to undergo the segmentation which precedes the formation of spore chains (Fig. 2i to m). Similar results were obtained for S. antibioticus (not shown), but there were some differences in the numbers of spores formed. Samples of young and late mycelia were freeze-substituted using the methodology described by Porta and Lopez-Iglesias (13) and were examined with a transmission electron microscope (Fig. 2n and o). The septal structure of the first mycelium (Fig. ​(Fig.2n)2n) lacks the complexity of the septal structure in the second mycelium, in which a membrane with a thick cell wall is clearly visible (Fig. ​(Fig.2o).2o). These data coincide with those previously described for solid confluent cultures (4).Open in a separate windowFIG. 2.Analysis of S. coelicolor hyphal compartmentalization with several fluorescent indicators (single colonies). Developmental culture times (in hours) are indicated. (a, e, and i) Mycelium stained with SYTO 9 and propidium iodide (viability). (b, f, and j) Hyphae stained with Cell Mask (a membrane stain). (c, g, and l) Hyphae stained with FM 4-64 (a membrane stain). (d, h, and m) Hyphae stained with WGA (cell wall stain). Septa in all the images in panels a to j, l, and m are indicated by arrows. (k) Image of the same field as panel j obtained in differential interference contrast mode. (n and o) Transmission electron micrographs of S. coelicolor hyphae at different developmental phases. The first-mycelium septa (n) are comprised of two membranes separated by a thin cell wall; in contrast, second-mycelium septa have thick cell walls (o). See the text for details. IP, propidium iodide.The main features of S. coelicolor growing in soils are shown in Fig. ​Fig.3.3. Under these conditions, spore germination is a very slow, nonsynchronous process that commences at about 7 days (Fig. 3c and d) and lasts for at least 21 days (Fig. 3i to l), peaking at around 14 days (Fig. 3e to h). Mycelium does not clump to form dense pellets, as it does in colonies; instead, it remains in the first-compartmentalized-mycelium phase during the time analyzed. Like the membrane septa in single colonies, the membrane septa of the hyphae are stained with FM4-64 (Fig. 3j and k), although only some of them are associated with thick cell walls (WGA staining) (Fig. ​(Fig.3l).3l). Similar results were obtained for S. antibioticus cultures (not shown).Open in a separate windowFIG. 3.Confocal laser scanning fluorescence microscopy analysis of the development-related cell death and hyphal compartmentalization of S. coelicolor M145 growing in soil. Developmental culture times (in days) are indicated. The images in panels b, f, and h were obtained in differential interference contrast mode and correspond to the same fields as the images in panels a, e, and g, respectively. The dark zone in panel h corresponds to a particle of soil containing hyphae. (a, c, d, e, g, i, j, and k) Hyphae stained with SYTO 9, propidium iodide (viability stain), and FM4-64 (membrane stain) simultaneously. (i) SYTO 9 and propidium iodide staining. (j) FM4-64 staining. The image in panel k is an overlay of the images in panels i and j and illustrates that first-mycelium membranous septa are not always apparent when they are stained with nucleic acid stains (SYTO 9 and propidium iodide). (l) Hyphae stained with WGA (cell wall stain), showing the few septa with thick cell walls present in the cells. Septa are indicated by arrows. IP, propidium iodide.In previous work (8), we have shown that the mycelium currently called the substrate mycelium corresponds to the early second multinucleated mycelium, according to our nomenclature, which still lacks the hydrophobic layers characteristic of the aerial mycelium. The aerial mycelium therefore corresponds to the late second mycelium which has acquired hydrophobic covers. This multinucleated mycelium as a whole should be considered the reproductive structure, since it is destined to sporulate (Fig. ​(Fig.4)4) (8). The time course of lysine 6-aminotransferase activity during cephamycin C biosynthesis has been analyzed by other workers using isolated colonies of Streptomyces clavuligerus and confocal microscopy with green fluorescent protein as a reporter (4). A complex medium and a temperature of 29°C were used, conditions which can be considered similar to the conditions used in our work. Interestingly, expression did not occur during the development of the early mycelium and was observed in the mycelium only after 80 h of growth. This suggests that the second mycelium is the antibiotic-producing mycelium, a hypothesis previously confirmed using submerged-growth cultures of S. coelicolor (9).Open in a separate windowFIG. 4.Cell cycle features of Streptomyces growing under natural conditions. Mycelial structures (MI, first mycelium; MII, second mycelium) and cell death are indicated. The postulated vegetative and reproductive phases are also indicated (see text).The significance of the first compartmentalized mycelium has been obscured by its short life span under typical laboratory culture conditions (5, 6, 8). In previous work (3, 7), we postulated that this structure is the vegetative phase of the bacterium, an hypothesis that has been recently corroborated by proteomic analysis (data not shown). Death in confluent cultures begins shortly after germination (4 h) and continues asynchronously for 15 h. The second multinucleated mycelium emerges after this early programmed cell death and is the predominant structure under these conditions. In contrast, as our results here show, the first mycelium lives for a long time in isolated colonies and soil cultures. As suggested in our previous work (5, 6, 8), if we assume that the compartmentalized mycelium is the Streptomyces vegetative growth phase, then this phase is the predominant phase in individual colonies (where it remains for at least 36 h), soils (21 days), and submerged cultures (around 20 h) (9). The differences in the life span of the vegetative phase could be attributable to the extremely high cell densities attained under ordinary laboratory culture conditions, which provoke massive differentiation and sporulation (5-7, 8).But just exactly what are “natural conditions”? Some authors have developed soil cultures of Streptomyces to study survival (16, 17), genetic transfer (14, 17-19), phage-bacterium interactions (3), and antibiotic production (1). Most of these studies were carried out using amended soils (supplemented with chitin and starch), conditions under which growth and sporulation were observed during the first few days (1, 17). These conditions, in fact, might resemble environments that are particularly rich in organic matter where Streptomyces could conceivably develop. However, natural growth conditions imply discontinuous growth and limited colony development (20, 21). To mimic such conditions, we chose relatively poor but more balanced carbon-nitrogen soil cultures (GAE medium-amended soil) and less dense spore inocula, conditions that allow longer mycelium growth times. Other conditions assayed, such as those obtained by irrigating the soil with water alone, did not result in spore germination and mycelial growth (not shown). We were unable to detect death, the second multinucleated mycelium described above, or sporulation, even after 1 month of incubation at 30°C. It is clear that in nature, cell death and sporulation must take place at the end of the long vegetative phase (1, 17) when the imbalance of nutrients results in bacterial differentiation.In summary, the developmental kinetics of Streptomyces under conditions resembling conditions in nature differs substantially from the developmental kinetics observed in ordinary laboratory cultures, a fact that should be born in mind when the significance of development-associated phenomena is analyzed.     

Schwann Cells: Development and Role in Nerve Repair

Schwann cells develop from the neural crest in a well-defined sequence of events. This involves the formation of the Schwann cell precursor and immature Schwann cells, followed by the generation of the myelin and nonmyelin (Remak) cells of mature nerves. This review describes the signals that control the embryonic phase of this process and the organogenesis of peripheral nerves. We also discuss the phenotypic plasticity retained by mature Schwann cells, and explain why this unusual feature is central to the striking regenerative potential of the peripheral nervous system (PNS).The myelin and nonmyelin (Remak) Schwann cells of adult nerves originate from the neural crest in well-defined developmental steps (Fig. 1). This review focuses on embryonic development (for additional information on myelination, see Salzer 2015). We also discuss how the ability to change between differentiation states, a characteristic attribute of developing cells, is retained by mature Schwann cells, and explain how the ability of Schwann cells to change phenotype in response to injury allows the peripheral nervous system (PNS) to regenerate after damage.Open in a separate windowFigure 1.Main transitions in the Schwann cell precursor (SCP) lineage. The diagram shows both developmental and injury-induced transitions. Black uninterrupted arrows, normal development; red arrows, the Schwann cell injury response; stippled arrows, postrepair reformation of myelin and Remak cells. Embryonic dates (E) refer to mouse development. (Modified from Jessen and Mirsky 2012; reprinted, with permission and with contribution from Y. Poitelon and L. Feltri.)     

Bringing Rad52 foci into focus

In 2007, we published the results of a genome-wide screen for ORFs that affect the frequency of Rad52 foci in yeast. That paper was published within the constraints of conventional online publishing tools, and it provided only a glimpse into the actual screen data. New tools in the JCB DataViewer now show how these data can—and should—be shared.

Complete screen data

https://doi.org/10.1083/jcb.201108095.dv The Rad52 protein has pivotal functions in double strand break repair and homologous recombination. The activity of Rad52 is often monitored by the subnuclear foci that it forms spontaneously in S phase or after DNA damage (Lisby et al., 2001). In mammals, the functions of yeast Rad52 may be divided between human RAD52 and the tumor suppressor BRCA2 (Feng et al., 2011). The full host of molecular players that govern Rad52 focus formation and maintenance was not well known when we initiated our screen. Using a high-content, image-based assay, we assessed the proportion of cells containing spontaneous Rad52-YFP foci in 4,805 viable Saccharomyces cerevisiae deletion strains (Alvaro et al., 2007). Starting with 96-well arrays of a deletion strain library, we created hybrid diploid strains (homozygous for the deletions) using systematic hybrid loss of heterozygosity (SHyLOH; Alvaro et al., 2006). We then manually and sequentially examined each strain using epifluorescence microscopy for the presence of Rad52-YFP foci. All of our image analysis was performed manually.As is often the case, our screen was published showing only a couple of representative images and providing data tables to summarize the findings. Tomes of data that could not be included in the published paper were relegated to supplemental Excel tables, typical of genome-wide screens. Also, the raw image data were sequestered in the laboratory on DVDs. With considerable help from JCB and Glencoe Software, we are delighted that the raw data from our Rad52 screen are now freely available online through the JCB DataViewer. A new interface within the JCB DataViewer brings presentation and preservation of high-content, multidimensional image-based screening data to a whole new level. To facilitate the development of this new interface, JCB required a dataset that was not time sensitive, and we were happy to provide our previously published Rad52 data. In the future, this new interface will be used to present high-content screening (HCS) datasets linked to published JCB papers. Indeed, the first publication of this sort appears in this issue of JCB (Rohn et al., 2011).The presentation of our data in the JCB DataViewer clearly shows the many benefits of this new publishing resource for the scientific community. Users now can view the complete collection of 3D image data across the entire screen, not just the two images in our original publication (Alvaro et al., 2007). Additionally, detailed information on image acquisition parameters, locus identities, and more is easily accessible (Fig. 1). Phenotypic scoring results can be visualized in interactive chart formats (Fig. 1), and search (Fig. 2) and database-linking tools (Fig. 1) allow extensive mining of the data for genes and phenotypes of interest. These tools provide an unprecedented view into HCS data in their entirety, as well as a means for authors to share and archive their data. This kind of accessibility to the direct visualization of the entire set of original screening data, on a scale previously only available to the scientists performing the screen, allows users to understand the full context of the image data analyzed in a screen. Furthermore, it is only through full access to the raw images and associated metadata that this information can be of maximum use to the community for large-scale data mining.Open in a separate windowFigure 1.The HCS interface of the JCB DataViewer provides interactive tools for the analysis of complete datasets from image-based screens. The miniviewer (top left) provides information for each gene in the screen through a zoomable and scrollable display of original multidimensional image data. It contains detailed metadata and a gene ontology (GO) summary, a link to a relevant external database (e.g., the Saccharomyces Genome Database [SGD]; top right), and a link to phenotypic scoring data for the complete screen in the chart view (bottom right). Within the chart view, hits designated by the screen authors are shown in blue, and the strain currently on display in the miniviewer is shown in red. The plate view (bottom left) shows the position of the strain of interest (red box) relative to other strains screened.Open in a separate windowFigure 2.The HCS interface of the JCB DataViewer provides search tools for the mining of complete datasets from image-based screens. (A) Users can search screen data by gene name or keywords (e.g., DNA repair). (B) Users can pick candidates for further analysis from the phenotypic scoring information in the chart view.As in all large-scale screens, the real data are variable; e.g., some strains provide a clear Rad52 focus phenotype, whereas others are more ambiguous. For our particular screen, images were not collected using automated technology but were acquired manually, strain by strain, over a period of months, leading to different levels of fluorescence intensity of Rad52-YFP as a result of, for example, changes in the intensity of our mercury arc lamp. Differences also exist in the number of fields and z stacks captured for each strain. In the absence of automated image collection, images from the primary screen in a few cases were not archived with the others and thus for all intents and purposes have been lost. In addition, our Rad52 screen only assayed nonessential genes, and some mutants are refractory to the SHyLOH methodology. Knowing all of this information allows users to view the data in a realistic manner and further highlights the importance of providing a central repository to archive HCS data.When published through conventional publication media, many important imaging details are known only to the original screeners. The new HCS interface of the JCB DataViewer shines a light on screening data as metadata become freely accessible, allowing any user to ask novel questions of the dataset. For example, the plate view for images (Fig. 1) allows users to assess whether neighboring colonies played any role in determining the phenotype and to delve deeper into why that might be. For example, are any “hits” a result of contamination from adjacent strains, resulting in clusters of positives? In the context of an automated screen, how were control and experimental samples arrayed across a plate during data collection? Did the controls on a particular plate behave as expected? Because our screen used a novel chromosome-specific loss of the heterozygosity method, users can ask whether mutations on specific chromosomes share features of Rad52 foci levels. The global resolution of the dataset provided through this new interface puts users of the dataset as close to the seat of the original screening scientist as possible, allowing them to ask, “what did the authors really see?”Presenting HCS data in the JCB DataViewer holds immense potential value to the scientific community. Through this new interface, users can access powerful interactive tools for analyzing scored phenotypes across the entire dataset (Fig. 1). Each gene ID can be charted against the phenotypic parameters scored in the original screen (e.g., the percentage of cells with Rad52 foci) and compared with all other loci (Fig. 1). Users can take our data and create their own list of hits based on their criteria, create a gallery of thumbnails for their selections (Fig. 2), and seamlessly move between their list of hits and the original data in the plate display format (Fig. 1). Users can also compare their candidates with our list (Fig. 2). The ability to visualize these data for comparative analyses creates a whole new perspective. The HCS interface of the JCB DataViewer allows users to look for their favorite gene, compare related genes, and discover new genes they never anticipated were involved in a given process.In summary, these new features of the JCB DataViewer will allow users to access the primary data from large-scale screens and to look at the full dataset to see what all of the images really look like. The ability to mine these data opens up whole new dimensions in data sharing and transparency. In the future, we anticipate that it will be possible to search many genome-wide screens, such as our Rad52 dataset, to identify commonalities in protein localization, concentration, cell morphology, etc. However, this will only occur if image data are archived and made freely available to the scientific community. We wholeheartedly support the efforts of JCB and hope that groups that use image-based HCS will increasingly make their images available using tools such as the JCB DataViewer.     

Centre of the Cell: Science Comes to Life

Centre of the Cell is a unique biomedical science education centre, a widening participation and outreach project in London’s East End. This article describes Centre of the Cell’s first five years of operation, the evolution of the project in response to audience demand, and the impact of siting a major public engagement project within a research laboratory.Centre of the Cell is a unique cell-shaped science centre suspended above a real biomedical research laboratory in the heart of London’s East End. It is one of the few, perhaps the only, science education centres in the world to be situated inside a research lab—in the Blizard Institute at the Whitechapel medical and dental campus of Queen Mary University of London (QMUL). Since its opening in September 2009, over 100,000 people have participated in Centre of the Cell activities (Fig 1) with approximately one million visits to the interactive website www.centreofthecell.org. With visitor numbers and activities increasing year on year, we believe this is an example of an innovative and successful public engagement project that may serve as an example for similar initiatives in biomedical research institutes.Open in a separate windowFig 1Visitor statistics for Centre of the Cell years 3–6 (2011–2015).These monthly statistics include all visitors on site as well as visitors to our workshops and shows in schools and other locations. Year 1 and 2 figures (not shown here) were 15,387 and 19,585, respectively. These data show a consistent pattern from month to month. 2013–2014 numbers were lower, due to planned maintenance shutdown of the Pod and introduction of charging for Pod shows that led to a dip in visitor numbers that largely recovered during 2014.     

The evolution of genomic imprinting: theories,predictions and empirical tests

The epigenetic phenomenon of genomic imprinting has motivated the development of numerous theories for its evolutionary origins and genomic distribution. In this review, we examine the three theories that have best withstood theoretical and empirical scrutiny. These are: Haig and colleagues'' kinship theory; Day and Bonduriansky''s sexual antagonism theory; and Wolf and Hager''s maternal–offspring coadaptation theory. These theories have fundamentally different perspectives on the adaptive significance of imprinting. The kinship theory views imprinting as a mechanism to change gene dosage, with imprinting evolving because of the differential effect that gene dosage has on the fitness of matrilineal and patrilineal relatives. The sexual antagonism and maternal–offspring coadaptation theories view genomic imprinting as a mechanism to modify the resemblance of an individual to its two parents, with imprinting evolving to increase the probability of expressing the fitter of the two alleles at a locus. In an effort to stimulate further empirical work on the topic, we carefully detail the logic and assumptions of all three theories, clarify the specific predictions of each and suggest tests to discriminate between these alternative theories for why particular genes are imprinted.The discovery of genomic imprinting, where the expression of an allele depends on its parental origin, motivated a diversity of theories attempting to explain its existence (Spencer and Clark, 2014). Three main theories have withstood scrutiny and are the focus of this review: Haig and colleagues'' kinship theory (Haig and Westoby, 1989; Haig, 2000a, 2004); Day and Bonduriansky''s (2004) sexual antagonism theory (see also Bonduriansky, 2007); and Wolf and Hager''s (2006) maternal–offspring coadaptation theory (see also Wolf and Hager, 2009; Wolf, 2013). Although these theories rest on different logic and fundamental assumptions, they share a critical common feature: some process creates a selective asymmetry between the maternally and paternally inherited allelic copies at a locus that causes selection to favor differential expression of the alleles (typically silencing of one of the copies) (Figures 1, ​,2,2, ​,33).Open in a separate windowFigure 1The kinship theory of genomic imprinting has two prerequisites: first, epigenetic marks that differentiate matrigenes from patrigenes; second, a difference in the relatedness of matrigenes and patrigenes to the social group. (a) The social group in the example depicted is a single litter of offspring, and multiple mating produces a relatedness asymmetry between half-siblings. The relatedness for matrigenes is ½ and the relatedness for patrigenes is 0. (Other sources of relatedness asymmetry are possible—e.g., sex-biased dispersal or high fitness variance in one sex—and social interactions are not limited to the juvenile period only). (b) The kinship theory envisions kin selection acting independently on genes of maternal and paternal origin and solves for the evolutionarily stable gene expression strategy for matrigenes and patrigenes. (c) For genes where the matrigenic allele''s optimum expression level is higher than that of the patrigene''s (e.g., a fetal growth inhibitor), the kinship theory predicts silencing of the patrigenic allele; for genes with the opposite effect (e.g., a fetal growth enhancer), the prediction is for patrigenic expression.Open in a separate windowFigure 2(a, b) The sexual antagonism theory of genomic imprinting starts with sexually antagonistic selection, which produces different allele frequencies, shown as pie charts, for genes of maternal and paternal origin. (c, d) Natural selection favors individuals that are able to express the fitter of the two alleles at a locus, which for males will be the patrigenic allele and for females will be the matrigenic allele. (In addition, the sexual antagonism theory may predict matrigenic or patrigenic expression in both sexes, such that the expressed allele derives from the parental sex that experiences stronger selection pressure. This scenario is not depicted).Open in a separate windowFigure 3(a) The maternal–offspring coadaptation theory of genomic imprinting relies on the correlation of genes in the mother and genes of maternal origin in the offspring (shown in light blue). (b) Fitness of offspring is determined by the interaction (shown in dark purple) between the phenotypes of mothers and offspring. (c) Imprinted silencing of the patrigenic allele can be favored for either of two reasons, depending on the genetic architecture of the interacting phenotypes. First, when a single gene governs the interaction and phenotypic matching between mothers and their offspring produces high fitness, then silencing of the patrigenic allele is beneficial to offspring because it raises the probability of producing a match. Second, if different loci are involved in the phenotypic interaction, past correlational selection will have produced a covariance between them, generating haplotypes with combinations of alleles that interact well together. (N.B. This multi-locus interaction is not depicted in the figure.) The offspring is more likely to inherit from its mother an allele that interacts well with the alleles in the mother''s genotype. This also favors the imprinted silencing of the patrigenic allele because it raises the probability that the offspring expresses an allele that makes for a good interaction with the maternal phenotype.Here we provide an overview of the fundamental logic and critical assumptions of these models. We then derive predictions that can be used to distinguish between theories. In doing so, we also highlight ambiguities in and overlap between the predictions they make, with a goal of motivating further research. In addition, we suggest some areas for future work that will test some of these predictions.