Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

32

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

32 results for “intergenerational effects”

Learn how ShareScore rates datasets ↗
dryad36/100

Data from: Environmental enrichment induces intergenerational behavioural and epigenetic effects on fish

Parental effects influence offspring phenotypes through pre- and post-natal routes but little is known about their molecular basis, and therefore their adaptive significance. Epigenetic modifications, which control gene expression without changes in the DNA sequence and are influenced by the environment, may contribute to parental effects. We investigated the effects of environmental enrichment on the behaviour, metabolic rate and brain DNA methylation patterns of parents and offspring of the highly inbreed mangrove killifish (Kryptolebias marmoratus). Parental fish reared in enriched environments had lower cortisol levels, lower metabolic rates and were more active and neophobic than those reared in barren environments. They also differed in 1,854 methylated cytosines (DMCs). Offspring activity and neophobia were determined by the parental environment. Among the DMCs of the parents, 98 followed the same methylation patterns in the offspring, three of which were significantly influenced by parental environments irrespective of their own rearing environment. Our results suggest that parental environment influences the behaviour and, to some extent, the brain DNA methylation patterns of the offspring.

opencc-zeroMay 2020View details →
dryad36/100

Sex-specific intergenerational plasticity I: maternal and paternal effects on sons and daughters

<p>1. Intergenerational plasticity or parental effects – when parental environments alter the phenotype of future generations – can influence how organisms cope with environmental change. An intriguing, underexplored possibility is that sex –of both the parent and the offspring – plays an important role in driving the evolution of intergenerational plasticity in both adaptive and nonadaptive ways.</p> <p>2. Here, we evaluate the potential for sex-specific parental effects in a freshwater population of threespined sticklebacks (Gasterosteus aculeatus) by independently and jointly manipulating maternal and paternal experiences and separately evaluating their phenotypic effects in sons versus daughters. We tested the adaptive hypothesis that daughters are more responsive to cues from their mother, while sons are more responsive to cues from their father.</p> <p>3. We exposed mothers, fathers, or both parents to visual cues of predation risk and measured offspring antipredator traits and brain gene expression.</p> <p>4. Predator-exposed fathers produced sons that were more risk-prone, while predator-exposed mothers produced more anxious sons and daughters. Further, maternal and paternal effects on offspring survival were nonadditive: offspring with a predator-exposed father, but not two predator-exposed parents, had lower survival against live predators. There were also strong sex-specific effects on brain gene expression: exposing mothers versus fathers to predation risk activated different transcriptional profiles in their offspring, and sons and daughters strongly differed in the ways in which their brain gene expression profiles were influenced by parental experience.</p> <p>5. We found little evidence to support the hypothesis that offspring prioritize their same-sex parent's experience. Parental effects varied with both the sex of the parent and the offspring in complicated and nonadditive ways. Failing to account for these sex-specific patterns (e.g., by pooling sons and daughters) would have underestimated the magnitude of parental effects. Altogether, these results draw attention to the potential for sex to influence patterns of intergenerational plasticity and raise new questions about the interface between intergenerational plasticity and sex-specific selective pressures, sexual conflict, and sexual selection. </p>

opencc-zeroOct 2020View details →
dryad36/100

Intergenerations effects of starvation on Athalia

<p>Intergenerational effects, also known as parental effects in which the offspring phenotype is influenced by the parental phenotype, can occur in response to factors that occur not only in early but also in late parental life. However, little is known about how these parental life stage-specific environments interact with each other and with the offspring environment to influence offspring phenotypes, particularly in organisms that realize distinct niches across ontogeny. We examined the effects of parental larval starvation and adult reproductive environment on offspring traits under matching or mismatching offspring larval starvation conditions using the holometabolous, haplodiploid insect <i>Athalia rosae</i> (turnip sawfly). We show that parental larval starvation had trait-dependent intergenerational effects on both life-history and consumption traits of offspring larvae, partly in interaction with offspring conditions, while there was no significant effect of parental adult reproductive environment. In addition, while offspring larval starvation led to numerous gene- and pathway-level expression differences, parental larval starvation impacted far fewer genes and only the ribosomal pathway. Our findings reveal that parental starvation evokes complex intergenerational effects on offspring life-history traits, consumption patterns as well as gene expression, although the effects are less pronounced than those of offspring starvation.</p>

opencc-zeroDec 2021View details →
dryad36/100

Condition dependent seminal fluid gene expression and intergenerational paternal effects on ejaculate quality

<p>1. There is increasing evidence to show that the environment experienced by fathers can have intergenerational paternal effects on the phenotype of offspring. Paternal effects can be mediated by ejaculate traits beyond the genes carried by sperm, for example through methylation of DNA during spermatogenesis, or non-sperm components of the ejaculate such as small RNAs or seminal fluid proteins (sfp).<br> 2. Theory suggests that ejaculate-mediated paternal effects can have important evolutionary consequences, especially if they exhibit condition dependent expression. Here we use the nutritional geometry approach to explore condition dependence in ejaculate traits and intergenerational paternal effects in the cricket Teleogryllus oceanicus.<br> 3. We fed males one of 24 chemically defined diets that varied in macronutrient concentration and the ratio of protein (P) to carbohydrate (C). We measured paternal expenditure on testes and accessory gland growth, and the expression of three seminal fluid protein genes that are known to impact sperm viability and the survival of embryos to hatching. We also measured the hatching success and reproductive phenotypes of adult offspring.<br> 4. We found linear effects of P and C on testes and accessory gland mass, and linear and correlated effects of P and C on the expression of two sfp genes. Paternal diet had no effect on the survival of embryos to hatching.<br> 5. There were significant intergenerational effects of paternal diet on the viability of sperm produced by sons, but no paternal effects on the expression of sfp genes in sons or fecundity in daughters.<br> 6. Our data suggest that ejaculate quality can have a significant non-genetic component determined by the paternal environment, which holds important implications for the evolutionary maintenance of variation in heritable male fitness.</p>

opencc-zeroDec 2021View details →
dryad36/100

Data from: Environmental enrichment induces intergenerational behavioural and epigenetic effects on fish

Open the record for dataset details and reuse information.

publicJul 2020View details →
dryad36/100

Intergenerations effects of starvation on Athalia

Open the record for dataset details and reuse information.

publicDec 2021View details →
dryad36/100

Data from: Intergenerational effects of dietary changes on trait means and variance

Open the record for dataset details and reuse information.

publicSep 2025View details →
dryad36/100

Sex-specific intergenerational plasticity I: maternal and paternal effects on sons and daughters

Open the record for dataset details and reuse information.

publicOct 2020View details →
dryad36/100

Condition dependent seminal fluid gene expression and intergenerational paternal effects on ejaculate quality

Open the record for dataset details and reuse information.

publicDec 2021View details →
dryad32/100

Data from: Intergenerational effects of early adversity on survival in wild baboons

Early life adversity can affect an individual's health, survival, and fertility for many years after the adverse experience. Whether early life adversity also imposes intergenerational effects on the exposed individual's offspring is not well understood. We fill this gap by leveraging prospective, longitudinal data on a wild, long-lived primate. We find that juveniles whose mothers experienced early life adversity exhibit high mortality before age 4, independent of the juvenile's own experience of early adversity. These juveniles often preceded their mothers in death by 1 to 2 years, indicating that high adversity females decline in their ability to raise offspring near the end of life. While we cannot exclude direct effects of a parent's environment on offspring quality (e.g., inherited epigenetic changes), our results are completely consistent with a classic parental effect, in which the environment experienced by a parent affects its future phenotype and therefor e its offspring's phenotype.

opencc-zeroOct 2019View details →
zenodo32/100

Figure 2 in The fate of the TARDIS offspring: no intergenerational effects of space exposure

Figure 2. Schematic description of the different generations of Milnesium tardigradum referred to in this study.

opennotspecifiedNov 2016View details →
zenodo32/100

Figure 5 in The fate of the TARDIS offspring: no intergenerational effects of space exposure

Figure 5. Mean percentage (SE) of viable animals in Echiniscus testudo and Ramazzottius oberhaeuseri exposed to space vacuum and cosmic radiation within the TARDIS experiment in 2007. Figure data are based on four replicate samples in each species.

opennotspecifiedNov 2016View details →
zenodo32/100

Figure 4 in The fate of the TARDIS offspring: no intergenerational effects of space exposure

Figure 4. Mean percentage (with SE) hatching success and survival until day 7 post-hatching in controls, space vacuum and UVAB treatment groups of the F1 (A) and F3 (B) generations of Milnesium tardigradum, representing descendants of the parental (P) generation that was exposed to space conditions in the TARDIS experiment (Jonsson et al., 2008). Treatment categories: Control, Earth laboratory control; SV, space vacuum and cosmic radiation; SV+UVAB, space vacuum, cosmic radiation and UVAB. Mean (SD) values: Hatching success F1: Control, 86.8% (5.3); SV, 92.5% (3.8); SV+UVAB, 91.7% (—). Hatching success F3: Control, 98.1% (0.82); SV, 95.9% (2.8); SV+UVAB, 98.0% (—). Survival 7-days post-hatch F1: Control, 92.9% (4.2); SV, 88.2% (3.8); SV+UVAB, 93.5% (—). Survival 7-days post-hatch F3: Control, 91.2% (3.3); SV, 88.3% (4.0); SV+UVAB, 91.3% (—).

opennotspecifiedNov 2016View details →
zenodo32/100

Figure 3 in The fate of the TARDIS offspring: no intergenerational effects of space exposure

Figure 3. Mean fecundity (with SE) in the F1 generation (eggs produced by the P generation exposed in space) and the F3 generation (eggs produced by the F2 generation) in Milnesium tardigradum, based on the number of eggs in individual exuvia. Treatment categories: Control, Earth laboratory control; SV, space vacuum and cosmic radiation; SV+UVAB, space vacuum, cosmic radiation and UVAB. Number of replicate samples: F1, n = 4 for both controls and SV; F3: n = 4 for controls and 3 for SV. The analysis included only one sample of UV-exposed animals. Mean (SD) values F1: Control, 8.0 (1.15); SV, 7.1 (1.35); SV+UVAB, 7.0 (—). Mean (SD) values F3: Control, 9.6 (0.54); SV, 9.9 (0.058); SV+UVAB, 9.8 (—).

opennotspecifiedNov 2016View details →
zenodo32/100

Replication Package for "Long-term and Intergenerational Effects of Education: Evidence from School Construction in Indonesia"

<p>Replication package for:</p> <p>Akresh, Richard, Daniel Halim, and Marieke Kleemans. 2023.&nbsp;&quot;Long-term and Intergenerational Effects of Education: Evidence from School Construction in Indonesia&quot;&nbsp;<em>Economic Journal</em>, forthcoming.</p>

opencc-by-4.0Aug 2022View details →
dryad32/100

Data from: Intergenerational effects of early adversity on survival in wild baboons

Open the record for dataset details and reuse information.

publicOct 2019View details →
dryad32/100

Data from: Intergenerational environmental effects: functional signals in offspring transcriptomes and metabolomes after parental jasmonic acid treatment in apomictic dandelion

Open the record for dataset details and reuse information.

publicSep 2018View details →
dryad32/100

Data from: Intergenerational effects of inbreeding in Nicrophorus vespilloides: offspring suffer fitness costs when either they or their parents are inbred

Open the record for dataset details and reuse information.

publicDec 2012View details →
dryad28/100

DNA methylation profiles suggest intergenerational transfer of maternal effects

<p>The view of maternal effects (non-genetic maternal environmental influence on offspring phenotype) has changed from one of distracting complications in evolutionary genetics to an important evolutionary mechanism for improving offspring fitness. Recent studies have shown that maternal effects act as an adaptive mechanism to prepare offspring for stressful environments. Although research into the magnitude of maternal effects is abundant, the molecular mechanisms of maternal influences on offspring phenotypic variation are not fully understood. Despite recent work identifying DNA methylation as a potential mechanism of non-genetic inheritance, currently proposed links between DNA methylation and parental effects are indirect and primarily involve genomic imprinting. We combined a factorial breeding design and gene-targeted sequencing methods to assess inheritance of methylation during early life stages at 14 genes involved in growth, development, metabolism, stress response and immune function of Chinook salmon (<i>Oncorhynchus tshawytscha</i>). We found little evidence for additive or non-additive genetic effects acting on methylation levels during early development; however, we detected significant maternal effects. Consistent with conventional maternal effect data, maternal effects on methylation declined through development and were replaced with non-additive effects when offspring began exogenous feeding. We mapped methylation at individual CpG sites across the selected candidate genes to test for variation in site-specific methylation profiles and found significant maternal effects at selected CpG sites that also declined with development stage. While intergenerational inheritance of methylated DNA is controversial, we show that CpG-specific methylation may function as an underlying molecular mechanism for maternal effects, with important implications for offspring fitness.</p>

opencc-zeroDec 2019View details →
dryad28/100

Data from: Intergenerational paternal effect of adult density in Drosophila melanogaster

1. Notwithstanding recent evidences, paternal environment is thought to be a potential but unlikely source of fitness variation that can affect trait evolution. Here we studied intergenerational effects of males' exposure to varying adult density in Drosophila melanogaster laboratory populations. 2. We held sires at normal (N), medium (M) and high (H) adult densities for two days before allowing them to mate with virgin females. This treatment did not introduce selection through differential mortality. Further, we randomly paired males and females and allowed a single round of mating between the sires and the dams. We then collected eggs from the dams and measured the egg size. Finally, we investigated the effect of the paternal treatment on juvenile and adult (male) fitness components. 3. We found a significant treatment effect on juvenile competitive ability where the progeny sired by the H-males had higher competitive ability. Since we did not find the treatment to affect egg size, this effect is unlikely to be mediated through variation in female provisioning. 4. Male fitness components were also found to have a significant treatment effect: M-sons had lower dry weight at eclosion, higher mating latency and lower competitive mating success. 5. While being the first study to show both adaptive and non-adaptive effect of the paternal density in Drosophila, our results highlight the importance of considering paternal environment as important source of fitness variation.

opencc-zeroDec 2018View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

ScienceDex for faculty

Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.