RAD sequencing resolves fine-scale population structure in a benthic invertebrate: implications for understanding phenotypic plasticity.

The field of molecular ecology is transitioning from the use of small panels of classical genetic markers such as microsatellites to much larger panels of single nucleotide polymorphisms (SNPs) generated by approaches like RAD sequencing. However, few empirical studies have directly compared the ability of these methods to resolve population structure. This could have implications for understanding phenotypic plasticity, as many previous studies of natural populations may have lacked the power to detect genetic differences, especially over micro-geographic scales. We therefore compared the ability of microsatellites and RAD sequencing to resolve fine-scale population structure in a commercially important benthic invertebrate by genotyping great scallops (Pecten maximus) from nine populations around Northern Ireland at 13 microsatellites and 10 539 SNPs. The shells were then subjected to morphometric and colour analysis in order to compare patterns of phenotypic and genetic variation. We found that RAD sequencing was superior at resolving population structure, yielding higher Fst values and support for two distinct genetic clusters, whereas only one cluster could be detected in a Bayesian analysis of the microsatellite dataset. Furthermore, appreciable phenotypic variation was observed in size-independent shell shape and coloration, including among localities that could not be distinguished from one another genetically, providing support for the notion that these traits are phenotypically plastic. Taken together, our results suggest that RAD sequencing is a powerful approach for studying population structure and phenotypic plasticity in natural populations

RAD sequencing resolves fine-scale population structure in a benthic invertebrate: implications for understanding phenotypic plasticity

The field of molecular ecology is transitioning from the use of small panels of classical genetic markers such as microsatellites to much larger panels of single nucleotide polymorphisms (SNPs) generated by approaches like RAD sequencing. However, few empirical studies have directly compared the ability of these methods to resolve population structure. This could have implications for understanding phenotypic plasticity, as many previous studies of natural populations may have lacked the power to detect genetic differences, especially over micro-geographic scales. We therefore compared the ability of microsatellites and RAD sequencing to resolve fine-scale population structure in a commercially important benthic invertebrate by genotyping great scallops (Pecten maximus) from nine populations around Northern Ireland at 13 microsatellites and 10 539 SNPs. The shells were then subjected to morphometric and colour analysis in order to compare patterns of phenotypic and genetic variation. We found that RAD sequencing was superior at resolving population structure, yielding higher Fst values and support for two distinct genetic clusters, whereas only one cluster could be detected in a Bayesian analysis of the microsatellite dataset. Furthermore, appreciable phenotypic variation was observed in size-independent shell shape and coloration, including among localities that could not be distinguished from one another genetically, providing support for the notion that these traits are phenotypically plastic. Taken together, our results suggest that RAD sequencing is a powerful approach for studying population structure and phenotypic plasticity in natural populations

A comprehensive analysis of autocorrelation and bias in home range estimation

Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function [AKDE], Silverman´s rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ((Formula presented.)) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing (Formula presented.). To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal´s movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small (Formula presented.). While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an (Formula presented.) >1,000, where 30% had an (Formula presented.) <30. In this frequently encountered scenario of small (Formula presented.), AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.Fil: Noonan, Michael J.. National Zoological Park; Estados Unidos. University of Maryland; Estados UnidosFil: Tucker, Marlee A.. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Fleming, Christen H.. University of Maryland; Estados Unidos. National Zoological Park; Estados UnidosFil: Akre, Thomas S.. National Zoological Park; Estados UnidosFil: Alberts, Susan C.. University of Duke; Estados UnidosFil: Ali, Abdullahi H.. Hirola Conservation Programme. Garissa; KeniaFil: Altmann, Jeanne. University of Princeton; Estados UnidosFil: Antunes, Pamela Castro. Universidade Federal do Mato Grosso do Sul; BrasilFil: Belant, Jerrold L.. State University of New York; Estados UnidosFil: Beyer, Dean. Universitat Phillips; AlemaniaFil: Blaum, Niels. Universitat Potsdam; AlemaniaFil: Böhning Gaese, Katrin. Senckenberg Gesellschaft Für Naturforschung; Alemania. Goethe Universitat Frankfurt; AlemaniaFil: Cullen Jr., Laury. Instituto de Pesquisas Ecológicas; BrasilFil: de Paula, Rogerio Cunha. National Research Center For Carnivores Conservation; BrasilFil: Dekker, Jasja. Jasja Dekker Dierecologie; Países BajosFil: Drescher Lehman, Jonathan. George Mason University; Estados Unidos. National Zoological Park; Estados UnidosFil: Farwig, Nina. Michigan State University; Estados UnidosFil: Fichtel, Claudia. German Primate Center; AlemaniaFil: Fischer, Christina. Universitat Technical Zu Munich; AlemaniaFil: Ford, Adam T.. University of British Columbia; CanadáFil: Goheen, Jacob R.. University of Wyoming; Estados UnidosFil: Janssen, René. Bionet Natuuronderzoek; Países BajosFil: Jeltsch, Florian. Universitat Potsdam; AlemaniaFil: Kauffman, Matthew. University Of Wyoming; Estados UnidosFil: Kappeler, Peter M.. German Primate Center; AlemaniaFil: Koch, Flávia. German Primate Center; AlemaniaFil: LaPoint, Scott. Max Planck Institute für Ornithologie; Alemania. Columbia University; Estados UnidosFil: Markham, A. Catherine. Stony Brook University; Estados UnidosFil: Medici, Emilia Patricia. Instituto de Pesquisas Ecológicas (IPE) ; BrasilFil: Morato, Ronaldo G.. Institute For Conservation of The Neotropical Carnivores; Brasil. National Research Center For Carnivores Conservation; BrasilFil: Nathan, Ran. The Hebrew University of Jerusalem; IsraelFil: Oliveira Santos, Luiz Gustavo R.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Olson, Kirk A.. Wildlife Conservation Society; Estados Unidos. National Zoological Park; Estados UnidosFil: Patterson, Bruce. Field Museum of National History; Estados UnidosFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; ArgentinaFil: Ramalho, Emiliano Esterci. Institute For Conservation of The Neotropical Carnivores; Brasil. Instituto de Desenvolvimento Sustentavel Mamirauá; BrasilFil: Rösner, Sascha. Michigan State University; Estados UnidosFil: Schabo, Dana G.. Michigan State University; Estados UnidosFil: Selva, Nuria. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Sergiel, Agnieszka. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Xavier da Silva, Marina. Parque Nacional do Iguaçu; BrasilFil: Spiegel, Orr. Universitat Tel Aviv; IsraelFil: Thompson, Peter. University of Maryland; Estados UnidosFil: Ullmann, Wiebke. Universitat Potsdam; AlemaniaFil: Ziḝba, Filip. Tatra National Park; PoloniaFil: Zwijacz Kozica, Tomasz. Tatra National Park; PoloniaFil: Fagan, William F.. University of Maryland; Estados UnidosFil: Mueller, Thomas. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Calabrese, Justin M.. National Zoological Park; Estados Unidos. University of Maryland; Estados Unido

De novo TBR1 variants cause a neurocognitive phenotype with ID and autistic traits:report of 25 new individuals and review of the literature

TBR1, a T-box transcription factor expressed in the cerebral cortex, regulates the expression of several candidate genes for autism spectrum disorders (ASD). Although TBR1 has been reported as a high-confidence risk gene for ASD and intellectual disability (ID) in functional and clinical reports since 2011, TBR1 has only recently been recorded as a human disease gene in the OMIM database. Currently, the neurodevelopmental disorders and structural brain anomalies associated with TBR1 variants are not well characterized. Through international data sharing, we collected data from 25 unreported individuals and compared them with data from the literature. We evaluated structural brain anomalies in seven individuals by analysis of MRI images, and compared these with anomalies observed in TBR1 mutant mice. The phenotype included ID in all individuals, associated to autistic traits in 76% of them. No recognizable facial phenotype could be identified. MRI analysis revealed a reduction of the anterior commissure and suggested new features including dysplastic hippocampus and subtle neocortical dysgenesis. This report supports the role of TBR1 in ID associated with autistic traits and suggests new structural brain malformations in humans. We hope this work will help geneticists to interpret TBR1 variants and diagnose ASD probands

Histone H3.3 beyond cancer: Germline mutations in Histone 3 Family 3A and 3B cause a previously unidentified neurodegenerative disorder in 46 patients

Although somatic mutations in Histone 3.3 (H3.3) are well-studied drivers of oncogenesis, the role of germline mutations remains unreported. We analyze 46 patients bearing de novo germline mutations in histone 3 family 3A (H3F3A) or H3F3B with progressive neurologic dysfunction and congenital anomalies without malignancies. Molecular modeling of all 37 variants demonstrated clear disruptions in interactions with DNA, other histones, and histone chaperone proteins. Patient histone posttranslational modifications (PTMs) analysis revealed notably aberrant local PTM patterns distinct from the somatic lysine mutations that cause global PTM dysregulation. RNA sequencing on patient cells demonstrated up-regulated gene expression related to mitosis and cell division, and cellular assays confirmed an increased proliferative capacity. A zebrafish model showed craniofacial anomalies and a defect in Foxd3-derived glia. These data suggest that the mechanism of germline mutations are distinct from cancer-associated somatic histone mutations but may converge on control of cell proliferation

Data from: RAD sequencing resolves fine-scale population structure in a benthic invertebrate: implications for understanding phenotypic plasticity

The field of molecular ecology is transitioning from the use of small panels of classical genetic markers such as microsatellites to much larger panels of single nucleotide polymorphisms (SNPs) generated by approaches like RAD sequencing. However, few empirical studies have directly compared the ability of these methods to resolve population structure. This could have implications for understanding phenotypic plasticity, as many previous studies of natural populations may have lacked the power to detect genetic differences, especially over micro-geographic scales. We therefore compared the ability of microsatellites and RAD sequencing to resolve fine-scale population structure in a commercially important benthic invertebrate by genotyping great scallops (Pecten maximus) from nine populations around Northern Ireland at 13 microsatellites and 10 539 SNPs. The shells were then subjected to morphometric and colour analysis in order to compare patterns of phenotypic and genetic variation. We found that RAD sequencing was superior at resolving population structure, yielding higher Fst values and support for two distinct genetic clusters, whereas only one cluster could be detected in a Bayesian analysis of the microsatellite dataset. Furthermore, appreciable phenotypic variation was observed in size-independent shell shape and coloration, including among localities that could not be distinguished from one another genetically, providing support for the notion that these traits are phenotypically plastic. Taken together, our results suggest that RAD sequencing is a powerful approach for studying population structure and phenotypic plasticity in natural populations

Pmaximus_Microsatellite_genotypes

The file contains data for 180 samples of great scallop (Pecten maximus) genotyped at 13 microsatellite loci. These samples where collected from nine locations along the coast of Northern Ireland

Supplementary information 2: Detailed ddRAD library preparation protocol from RAD sequencing resolves fine-scale population structure in a benthic invertebrate: implications for understanding phenotypic plasticity

The field of molecular ecology is transitioning from the use of small panels of classical genetic markers such as microsatellites to much larger panels of single nucleotide polymorphisms (SNPs) generated by approaches like RAD sequencing. However, few empirical studies have directly compared the ability of these methods to resolve population structure. This could have implications for understanding phenotypic plasticity, as many previous studies of natural populations may have lacked the power to detect genetic differences, especially over micro-geographic scales. We therefore compared the ability of microsatellites and RAD sequencing to resolve fine-scale population structure in a commercially important benthic invertebrate by genotyping great scallops (<i>Pecten maximus</i>) from nine populations around Northern Ireland at 13 microsatellites and 10 539 SNPs. The shells were then subjected to morphometric and colour analysis in order to compare patterns of phenotypic and genetic variation. We found that RAD sequencing was superior at resolving population structure, yielding higher <i>F</i>_st values and support for two distinct genetic clusters, whereas only one cluster could be detected in a Bayesian analysis of the microsatellite dataset. Furthermore, appreciable phenotypic variation was observed in size-independent shell shape and coloration, including among localities that could not be distinguished from one another genetically, providing support for the notion that these traits are phenotypically plastic. Taken together, our results suggest that RAD sequencing is a powerful approach for studying both population structure and phenotypic plasticity in natural populations

Supplementary figure 1: Illustration of the process of generating scallop shell outline coordinates for the geometric morphometrics analysis. From left to right: scaled digital photograph, isolated shell outline, and 1000 pseudo-landmarks placed along the shell perimeter from RAD sequencing resolves fine-scale population structure in a benthic invertebrate: implications for understanding phenotypic plasticity

The field of molecular ecology is transitioning from the use of small panels of classical genetic markers such as microsatellites to much larger panels of single nucleotide polymorphisms (SNPs) generated by approaches like RAD sequencing. However, few empirical studies have directly compared the ability of these methods to resolve population structure. This could have implications for understanding phenotypic plasticity, as many previous studies of natural populations may have lacked the power to detect genetic differences, especially over micro-geographic scales. We therefore compared the ability of microsatellites and RAD sequencing to resolve fine-scale population structure in a commercially important benthic invertebrate by genotyping great scallops (<i>Pecten maximus</i>) from nine populations around Northern Ireland at 13 microsatellites and 10 539 SNPs. The shells were then subjected to morphometric and colour analysis in order to compare patterns of phenotypic and genetic variation. We found that RAD sequencing was superior at resolving population structure, yielding higher <i>F</i>_st values and support for two distinct genetic clusters, whereas only one cluster could be detected in a Bayesian analysis of the microsatellite dataset. Furthermore, appreciable phenotypic variation was observed in size-independent shell shape and coloration, including among localities that could not be distinguished from one another genetically, providing support for the notion that these traits are phenotypically plastic. Taken together, our results suggest that RAD sequencing is a powerful approach for studying both population structure and phenotypic plasticity in natural populations

Supplementary table 2: Pairwise Fst values (below diagonal) and corresponding p-values (above diagonal) calculated using (a) 13 microsatellites genotyped in 180 individuals and (b) 10,539 SNPs genotyped in 45 individuals from RAD sequencing resolves fine-scale population structure in a benthic invertebrate: implications for understanding phenotypic plasticity

The field of molecular ecology is transitioning from the use of small panels of classical genetic markers such as microsatellites to much larger panels of single nucleotide polymorphisms (SNPs) generated by approaches like RAD sequencing. However, few empirical studies have directly compared the ability of these methods to resolve population structure. This could have implications for understanding phenotypic plasticity, as many previous studies of natural populations may have lacked the power to detect genetic differences, especially over micro-geographic scales. We therefore compared the ability of microsatellites and RAD sequencing to resolve fine-scale population structure in a commercially important benthic invertebrate by genotyping great scallops (<i>Pecten maximus</i>) from nine populations around Northern Ireland at 13 microsatellites and 10 539 SNPs. The shells were then subjected to morphometric and colour analysis in order to compare patterns of phenotypic and genetic variation. We found that RAD sequencing was superior at resolving population structure, yielding higher <i>F</i>_st values and support for two distinct genetic clusters, whereas only one cluster could be detected in a Bayesian analysis of the microsatellite dataset. Furthermore, appreciable phenotypic variation was observed in size-independent shell shape and coloration, including among localities that could not be distinguished from one another genetically, providing support for the notion that these traits are phenotypically plastic. Taken together, our results suggest that RAD sequencing is a powerful approach for studying both population structure and phenotypic plasticity in natural populations