A study on the minimum number of loci required for genetic evaluation using a finite locus model

For a finite locus model, Markov chain Monte Carlo (MCMC) methods can be used to estimate the conditional mean of genotypic values given phenotypes, which is also known as the best predictor (BP). When computationally feasible, this type of genetic prediction provides an elegant solution to the problem of genetic evaluation under non-additive inheritance, especially for crossbred data. Successful application of MCMC methods for genetic evaluation using finite locus models depends, among other factors, on the number of loci assumed in the model. The effect of the assumed number of loci on evaluations obtained by BP was investigated using data simulated with about 100 loci. For several small pedigrees, genetic evaluations obtained by best linear prediction (BLP) were compared to genetic evaluations obtained by BP. For BLP evaluation, used here as the standard of comparison, only the first and second moments of the joint distribution of the genotypic and phenotypic values must be known. These moments were calculated from the gene frequencies and genotypic effects used in the simulation model. BP evaluation requires the complete distribution to be known. For each model used for BP evaluation, the gene frequencies and genotypic effects, which completely specify the required distribution, were derived such that the genotypic mean, the additive variance, and the dominance variance were the same as in the simulation model. For lowly heritable traits, evaluations obtained by BP under models with up to three loci closely matched the evaluations obtained by BLP for both purebred and crossbred data. For highly heritable traits, models with up to six loci were needed to match the evaluations obtained by BLP.     

Phytoplankton Growth and Microzooplankton Grazing in the Subtropical Northeast Atlantic

Dilution experiments were performed to estimate phytoplankton growth and microzooplankton grazing rates during two Lagrangian surveys in inner and eastern locations of the Eastern North Atlantic Subtropical Gyre province (NAST-E). Our design included two phytoplankton size fractions (0.2–5 µm and >5 µm) and five depths, allowing us to characterize differences in growth and grazing rates between size fractions and depths, as well as to estimate vertically integrated measurements. Phytoplankton growth rates were high (0.11–1.60 d⁻¹), especially in the case of the large fraction. Grazing rates were also high (0.15–1.29 d⁻¹), suggesting high turnover rates within the phytoplankton community. The integrated balances between phytoplankton growth and grazing losses were close to zero, although deviations were detected at several depths. Also, O₂ supersaturation was observed up to 110 m depth during both Lagrangian surveys. These results add up to increased evidence indicating an autotrophic metabolic balance in oceanic subtropical gyres.     

First record of anomalous otoliths of Menticirrhus americanus in the South Atlantic

Sagitta otoliths are usually formed of calcium carbonate polymorphs as aragonite. The objective of this study was to verify which carbonate polymorph is predominant in the sagitta otolith of Menticirrhus americanus and check whether this pattern remains in otoliths with morphological alterations. Otoliths of M. americanus were obtained from five sites on the southeast‐south coast of Brazil (São Sebastião (SS) 23°45′S–45°24′O, n = 29; Cananéia‐Iguape Estuarine Complex (CI) 25°02′S–47°54′O, n = 30; Paranaguá Estuarine Complex (PEC) 25°28′S–48°20′O, n = 35; Itapoá (IT) 26°07′S–48°36′O, n = 31; Laguna (LA) 28°28′S–48°46′O, n = 13). The characterization of carbonate polymorphs of otoliths was performed through Raman spectroscopy, a photonic and non‐destructive technique that analyzes molecular vibrations induced by laser. We analyzed 138 pairs of M. americanus otoliths, of which eight otoliths from different pairs presented morphological alterations (SS n = 1, CEP n = 5, IT n = 1, LA n = 1). The Raman spectra show that normal otoliths, that is, without morphological alterations, presented only aragonite in their structure. Among the otoliths that presented morphological alterations, the Raman spectra allowed to identify in six otoliths the deposition of aragonite and in only two otoliths the deposition of vaterite (one specimen of the PEC and one of SS).     

Coalescence-based species delimitation using genome-wide data reveals hidden diversity in a cosmopolitan group of lichens

Although there is an abundance of species delimitation methods on the market, most approaches depend on predefined assignment of specimens to species or populations. Assignment-free methods, which can simultaneously infer boundaries and relationships among species, are of high importance in cases, when correct pre-assignment is difficult or not at all possible. In this study, we use assignment-free multispecies coalescent-based species delimitation (STACEY, tr2-delimitation, and BP&P), phylogenetic methods, and clustering algorithms to investigate the inter- and infraspecific relationships within a common and widespread group of lichens with contentious species boundaries. The Cetraria aculeata group presents a good example of extreme morphological variability and unclear species delimitation in lichens. Based on DNA-sequence data from 26 fungal loci and 10 microsatellite loci, as well as morphological and chemical data, our results provide evidence for the occurrence of five different taxa within the group and highlight the difficulties of morphologically distinguishing these species. We discovered a separate lineage (clade C) within C. aculeata s. str., which does not fully coincide with any of the a priori identified species C. aculeata, C. crespoae, or C. steppae and conclude that this clade constitutes a semi-cryptic, genetically isolated lineage within C. aculeata. We recognize this lineage at subspecific rank as C. aculeata subsp. steppae and synonymize Cetraria crespoae with C. aculeata subsp. aculeata. Epitypes are designated for all involved names to stabilize their usage. The PKS8 gene locus is recommended as a barcode for the separation of C. aculeata subsp. aculeata and subsp. steppae. We demonstrate the potential use of microsatellite data for species delimitation in lichens that might offer an alternative insight or be used to test species delimitation hypotheses, when dealing with closely related or potentially cryptic species. Our results also confirm the presence of an undescribed sister lineage to C. odontella previously misidentified as C. muricata and extend the known range of this lineage to Central Asia (Altay Mts.) and the Central European Alps (France, Switzerland), which calls for a critical reappraisal of records of C. aculeata and C. muricata from these mountain ranges.

     

Prospects for incorporation of epigenetic biomarkers in human health and environmental risk assessment of chemicals

Epigenetic mechanisms have gained relevance in human health and environmental studies, due to their pivotal role in disease, gene × environment interactions and adaptation to environmental change and/or contamination. Epigenetic mechanisms are highly responsive to external stimuli and a wide range of chemicals has been shown to determine specific epigenetic patterns in several organisms. Furthermore, the mitotic/meiotic inheritance of such epigenetic marks as well as the resulting changes in gene expression and cell/organismal phenotypes has now been demonstrated. Therefore, epigenetic signatures are interesting candidates for linking environmental exposures to disease as well as informing on past exposures to stressors. Accordingly, epigenetic biomarkers could be useful tools in both prospective and retrospective risk assessment but epigenetic endpoints are currently not yet incorporated into risk assessments. Achieving a better understanding on this apparent impasse, as well as identifying routes to promote the application of epigenetic biomarkers within environmental risk assessment frameworks are the objectives of this review. We first compile evidence from human health studies supporting the use of epigenetic exposure‐associated changes as reliable biomarkers of exposure. Then, specifically focusing on environmental science, we examine the potential and challenges of developing epigenetic biomarkers for environmental fields, and discuss useful organisms and appropriate sequencing techniques to foster their development in this context. Finally, we discuss the practical incorporation of epigenetic biomarkers in the environmental risk assessment of chemicals, highlighting critical data gaps and making key recommendations for future research within a regulatory context.     

Dormancy and germination: making every seed count in restoration

From 50 to 90% of wild plant species worldwide produce seeds that are dormant upon maturity, with specific dormancy traits driven by species' occurrence geography, growth form, and genetic factors. While dormancy is a beneficial adaptation for intact natural systems, it can limit plant recruitment in restoration scenarios because seeds may take several seasons to lose dormancy and consequently show low or erratic germination. During this time, seed predation, weed competition, soil erosion, and seed viability loss can lead to plant re‐establishment failure. Understanding and considering seed dormancy and germination traits in restoration planning are thus critical to ensuring effective seed management and seed use efficiency. There are five known dormancy classes (physiological, physical, combinational, morphological, and morphophysiological), each requiring specific cues to alleviate dormancy and enable germination. The dormancy status of a seed can be determined through a series of simple steps that account for initial seed quality and assess germination across a range of environmental conditions. In this article, we outline the steps of the dormancy classification process and the various corresponding methodologies for ex situ dormancy alleviation. We also highlight the importance of record‐keeping and reporting of seed accession information (e.g. geographic coordinates of the seed collection location, cleaning and quality information, storage conditions, and dormancy testing data) to ensure that these factors are adequately considered in restoration planning.