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Fig. 2 in Functional integrity of Colossoma macropomum (Cuvier, 1816) sperm cryopreserved with enriched extender solutions
Fig. 2. Mean and standard deviation of the Fertilization Rate (Fert) and Hatching Rate (Hat) of Colossoma macropomum semen frozen with two extenders (T1 - Solution 1 and T2 - Solution 2). Evaluated using the Kruskal-Wallis nonparametric test.
Fig. 1 in Functional integrity of Colossoma macropomum (Cuvier, 1816) sperm cryopreserved with enriched extender solutions
Fig. 1. (a) Mean and standard deviation of Progressive Motility (Mot) and Normal Sperm (N Sperm) and (b) Motility Time (TMot) of Colossoma macropomum, fresh and frozen, with two extenders (T1 - Solution 1 and T2 - Solution 2). Evaluated using the Kruskal-Wallis non-parametric test.
Fig. 3 in Functional integrity of Colossoma macropomum (Cuvier, 1816) sperm cryopreserved with enriched extender solutions
Fig. 3. The average percentage of damage found in frozen semen of Colossoma macropomum in different treatments. (a) Primary damage: Macrocephaly (Macro); Microcephaly (Micro); Head Degeneration (HD); Degenerated Midpiece (DMP); Curly Tail (CT); Broken Tail (BT); Folded Tail (FT). (b) Secondary damage: Degenerated Tail (DeT); Free Normal Head (FNH); Distal Droplet (DD); Proximal Droplet (PD).
The sperm dataset for IsoVEM method
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Figure 8 from: Jiang Z, Liu J, Qin D (2019) Sperm ultrastructure of Pochazia shantungensis (Chou & Lu) and Ricania speculum (Walker) (Hemiptera, Ricaniidae) with phylogenetic implications. ZooKeys 880: 43-59. https://doi.org/10.3897/zookeys.880.32810
Figure 8 Cross-sections of the sperm flagellum of R. speculum. A, B Flagella, showing the axoneme (ax), accessory bodies (ab) and mitochondrial derivatives (md) including oval electron-lucid portion (1), an electron-dense region (2), and one mitochondrial cristae region (3) C axoneme, showing the typical 9 + 9 + 2 pattern, nine outermost accessory microtubules (am), a pair of central microtubules (cm), and doublet microtubules (dm) in between D flagellum, showing the axoneme (ax), accessory bodies (ab) and mitochondrial derivatives (md) E–F flagellum without mitochondrial derivatives (md). Scale bars: 0.5 µm (A, B, D, F); 0.1 µm (C, E).
Figure 6 from: Jiang Z, Liu J, Qin D (2019) Sperm ultrastructure of Pochazia shantungensis (Chou & Lu) and Ricania speculum (Walker) (Hemiptera, Ricaniidae) with phylogenetic implications. ZooKeys 880: 43-59. https://doi.org/10.3897/zookeys.880.32810
Figure 6 Longitudinal sections of spermatozoa of R. speculum. A, B Acrosome (a), nucleus (N), axoneme (ax), accessory bodies (ab) and mitochondrial derivatives (md), arrow indicates acrosome and nucleus connection area C nucleus-flagellum transition, showing nucleus (N), mitochondrial derivatives (md), accessory bodies (ab), axoneme (ax), arrow indicates centriole, triangular arrowhead indicates centriolar adjunct D sperm flagellum, showing cristae (arrow) arranged in mitochondrial derivatives (md). Scale bars: 0.5 µm (A, B); 0.1 µm (C, D).
Figure 5 from: Jiang Z, Liu J, Qin D (2019) Sperm ultrastructure of Pochazia shantungensis (Chou & Lu) and Ricania speculum (Walker) (Hemiptera, Ricaniidae) with phylogenetic implications. ZooKeys 880: 43-59. https://doi.org/10.3897/zookeys.880.32810
Figure 5 TEM and light micrographs of spermatozoon and spermatodesms of R. speculum. A Light micrograph of spermatodesm B light micrograph of spermatozoon with the head (H, arrow) and flagellum (F) C, D cross-sections of the oval nucleus (N), showing the acrosome (a) and homogenous matrix (ma). Scale bars: 50 µm (A); 20 µm (B); 0.5 µm (C); 2 µm (D).
Figure 4 from: Jiang Z, Liu J, Qin D (2019) Sperm ultrastructure of Pochazia shantungensis (Chou & Lu) and Ricania speculum (Walker) (Hemiptera, Ricaniidae) with phylogenetic implications. ZooKeys 880: 43-59. https://doi.org/10.3897/zookeys.880.32810
Figure 4 Cross-sections of the sperm flagellum of P. shantungensis. A–D Flagella, showing axoneme (ax), fishhook-shaped accessory bodies (ab), D-shaped mitochondrial derivatives (md), containing oval lucent region (1), serrated electron-dense region (2) and mitochondrial cristae region (3) E–F flagellum, mitochondrial derivatives slowly disappear, axonemes (ax) become disordered, accessory bodies (ab) become smaller G axoneme, showing the typical 9 + 9 + 2 pattern, nine outermost accessory microtubules (am), nine doublet microtubules (dm) and two innermost central microtubules (cm) H Showing doublet microtubules finally disappearing. Scale bars: 2 µm (A); 0.5 µm (B); 0.1 µm (C–H).
Figure 3 from: Jiang Z, Liu J, Qin D (2019) Sperm ultrastructure of Pochazia shantungensis (Chou & Lu) and Ricania speculum (Walker) (Hemiptera, Ricaniidae) with phylogenetic implications. ZooKeys 880: 43-59. https://doi.org/10.3897/zookeys.880.32810
Figure 3 Cross-sections of spermatozoa of P. shantungensis. A Acrosome, showing the dothideoid acrosome B–E serial cross-sections of head showing the dothideoid acrosome (a), the nucleus (N), and the plasma membrane (pm) F oval nucleus (N) G–N nucleus-flagellum transition region, showing the nucleus (N), mitochondrial derivatives (md), accessory bodies (ab), axoneme (ax). The asterisk indicates the centriolar adjunct (ca). Scale bars: 0.5 µm (B–D); 0.2 µm (A, K, L, N); 0.1 µm (E–J, M).
Figure 1 from: Jiang Z, Liu J, Qin D (2019) Sperm ultrastructure of Pochazia shantungensis (Chou & Lu) and Ricania speculum (Walker) (Hemiptera, Ricaniidae) with phylogenetic implications. ZooKeys 880: 43-59. https://doi.org/10.3897/zookeys.880.32810
Figure 1 TEM and light micrographs of spermatozoa and spermatodesms of P. shantungensis. A, B Light micrographs of spermatodesm and spermatozoa C light micrograph of a single spermatozoon with the head (H, arrow) and wavy flagellum (F) D, ETEM micrographs of cross-sections of spermatozoa, showing the acrosome (a) and nucleus (N). Arrow shows head cluster, asterisk indicates the acrosome. Scale bars: 20 µm (A–C); 2 µm (D); 0.5µm (E).
Figure 2 from: Jiang Z, Liu J, Qin D (2019) Sperm ultrastructure of Pochazia shantungensis (Chou & Lu) and Ricania speculum (Walker) (Hemiptera, Ricaniidae) with phylogenetic implications. ZooKeys 880: 43-59. https://doi.org/10.3897/zookeys.880.32810
Figure 2 Longitudinal sections of spermatozoa of P. shantungensis. A, B Spermatozoa, showing acrosome (a), nucleus (N), arrow indicates connection area between acrosome and nucleus C nucleus-flagellum transition, showing nucleus (N), mitochondrial derivatives (md), accessory body (ab), axoneme (ax), arrow indicates centriole, triangular arrowhead indicates centriolar adjunct D, E flagella of sperm, showing axoneme (ax), mitochondrial derivatives (md) and cristae (arrow). Scale bars: 2 µm (A); 0.5 µm (B, D); 0.1 µm (C, E).
A novel role for Eip74EF in male reproduction in promoting sperm elongation at the cost of fecundity
<p>Spermatozoa are the most morphologically variable cell type, yet little is known about genes controlling natural variation in sperm shape. <i>Drosophila</i> fruit flies have evolved the longest sperm known, which are evolving under postcopulatory sexual selection, driven by sperm competition and cryptic female choice. Long sperm outcompete short sperm but primarily when females have long seminal receptacles (SRs), the primary sperm storage organ. Thus, selection on sperm length is mediated by SR length, and the two traits are coevolving across the <i>Drosophila</i> lineage, driven by a genetic correlation and fitness advantage of long sperm and long SR genotypes in both males and females. <i>Ecdysone induced protein 74EF </i>(<i>Eip74EF</i>)<i> </i>is rapidly evolving under positive selection in <i>Drosophila</i>, and it is expressed during post-meiotic stages of spermatogenesis, when spermatid elongation occurs. Partial knockdown of <i>Eip74EF</i> leads to shorter sperm but does not affect SR length, suggesting that <i>Eip74EF</i> is involved in promoting spermatid elongation but is not a genetic driver of male-female coevolution. We also found that <i>Eip74EF </i>knockdown has opposing effects on fecundity in males and females, with an increase in fecundity for males but a decrease in females, consistent with its documented role in oocyte maturation. It is possible that knockdown males produce more sperm that are also shorter, which would explain the increase in fecundity, but this hypothesis remains to be tested. Our results document a novel function of <i>Eip74EF</i> in spermatogenesis and demonstrates that this gene influences both male and female reproductive success.</p>
Data from: Female MHC type affects male testosterone levels and sperm number in the horse (Equus caballus)
Odours of vertebrates often contain information about the major histocompatibility complex (MHC), and are used in kin recognition, mate choice or female investment in pregnancy. It is, however, still unclear whether MHC-linked signals can also affect male reproductive strategies. We used horses (Equus caballus) to study this question under experimental conditions. Twelve stallions were individually exposed either to an unfamiliar MHC-similar mare and then to an unfamiliar MHC-dissimilar mare, or vice versa. Each exposure lasted over a period of four weeks. Peripheral blood testosterone levels were determined weekly. Three ejaculates each were collected in the week after exposure to both mares (i.e. in the ninth week) to determine mean sperm number and sperm velocity. We found high testosterone levels when stallions were kept close to MHC-dissimilar mares and significantly lower ones when kept close to MHC-similar mares. Mean sperm number per ejaculate (but not sperm velocity) was positively correlated to mean testosterone levels and also affected by the order of presentation of mares: sperm numbers were higher if MHC-dissimilar mares were presented last than if MHC-similar mares were presented last. We conclude that MHC-linked signals influence testosterone secretion and semen characteristics, two indicators of male reproductive strategies.
Data from: Sperm head morphology is associated with sperm swimming speed: a comparative study of songbirds using electron microscopy
Sperm exhibit extraordinary levels of morphological diversification across the animal kingdom. In songbirds, sperm have a helically shaped head incorporating a distinct acrosomal membrane or 'helical keel', the form and extent of which varies across species. The functional significance of this helical shape, however, remains unknown. Using scanning electron microscopy, we quantified inter- and intra-specific variation in sperm head morphology across 36 songbird species (Passeriformes: Passerida). Using phylogenetic comparative methods, we investigated the relationship between sperm head morphology and both sperm swimming speed and the frequency of extra-pair young (EPY). We found that species whose sperm had a relatively more pronounced helical form (i.e. long acrosome, short nucleus, wide helical membrane, and a more pronounced waveform along the sperm head 'core') had faster-swimming sperm. We found no evidence of a relationship between inter-specific variation in sperm head morphology and EPY, although we did find that among- and within-male variation in sperm head traits were negatively correlated with EPY. Applying principles of fluid mechanics, we discuss how the helical form of the sperm head may influence swimming speed, and suggest that further studies considering aspects of sperm morphology beyond sperm length are needed to improve our understanding of sperm structure-function relationships.
Data from: Additive genetic variance in polyandry enables its evolution, but polyandry is unlikely to evolve through sexy or good sperm processes
Polyandry is widespread despite its costs. The sexually selected sperm hypotheses ('sexy' and 'good' sperm) posit that sperm competition plays a role in the evolution of polyandry. Two poorly studied assumptions of these hypotheses are the presence of additive genetic variance in polyandry and sperm competitiveness. Using a quantitative genetic breeding design in a natural population of Drosophila melanogaster, we first established the potential for polyandry to respond to selection. We then investigated whether polyandry can evolve through sexually selected sperm processes. We measured lifetime polyandry and offensive sperm competitiveness (P2) while controlling for sampling variance due to male x male x female interactions. We also measured additive genetic variance in egg-to-adult viability and controlled for its effect on P2 estimates. Female lifetime polyandry showed significant and substantial additive genetic variance and evolvability. In contrast, we found little genetic variance or evolvability in P2 or egg-to-adult viability. Additive genetic variance in polyandry highlights its potential to respond to selection. However, the low levels of genetic variance in sperm competitiveness suggest the evolution of polyandry may not be driven by sexy sperm or good sperm processes.
Data from: Male seminal fluid substances affect sperm competition success and female reproductive behavior in a seed beetle
Male seminal fluid proteins are known to affect female reproductive behavior and physiology by reducing mating receptivity and by increasing egg production rates. Such substances are also though to increase the competitive fertilization success of males, but the empirical foundation for this tenet is restricted. Here, we examined the effects of injections of size-fractioned protein extracts from male reproductive organs on both male competitive fertilization success (i.e., P2 in double mating experiments) and female reproduction in the seed beetle Callosobruchus maculatus. We found that extracts of male seminal vesicles and ejaculatory ducts increased competitive fertilization success when males mated with females 1 day after the females' initial mating, while extracts from accessory glands and testes increased competitive fertilization success when males mated with females 2 days after the females' initial mating. Moreover, different size fractions of seminal fluid proteins had distinct and partly antagonistic effects on male competitive fertilization success. Collectively, our experiments show that several different seminal fluid proteins, deriving from different parts in the male reproductive tract and of different molecular weight, affect male competitive fertilization success in C. maculatus. Our results highlight the diverse effects of seminal fluid proteins and show that the function of such proteins can be contingent upon female mating status. We also document effects of different size fractions on female mating receptivity and egg laying rates, which can serve as a basis for future efforts to identify the molecular identity of seminal fluid proteins and their function in this model species.
Figure 4 in Cephalopods in the potential prey field of sperm whales (Physeter macrocephalus) (Cetacea: Physeteridae) in the northern Gulf of Mexico
Figure 4. Number of stations where potential cephalopod prey of sperm whales was collected.
Figure 7. Sperm whale sightings 2010 in Cephalopods in the potential prey field of sperm whales (Physeter macrocephalus) (Cetacea: Physeteridae) in the northern Gulf of Mexico
Figure 7. Sperm whale sightings 2010; grey lines represent the transect lines.
Figure 1. Summer 2009 in Cephalopods in the potential prey field of sperm whales (Physeter macrocephalus) (Cetacea: Physeteridae) in the northern Gulf of Mexico
Figure 1. Summer 2009 Pilot Study survey effort and sperm whale sightings.
Figure 3 in Cephalopods in the potential prey field of sperm whales (Physeter macrocephalus) (Cetacea: Physeteridae) in the northern Gulf of Mexico
Figure 3. Cephalopod species richness by station, 2010.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.