Behavioral mechanisms of reproductive isolation in avian hybrid zones

Sexual signals and mating behaviors influence whether sympatric species interbreed, and can therefore promote or impede behavioral reproductive isolation between species in secondary contact. Traditionally, research on sexual selection and hybridization has focused on the importance of interspecific mate choice and species discrimination from the perspective of choosy females, and competition from the lens of aggressive and indiscriminate males. I examined two different avian systems to compare the role of male and female competition on hybridization: white-crowned sparrows on the west coast of the US, and sex-role reversed jacanas in Panama. Using genomics and experimental field techniques, I tested morphological, behavioral, and historical factors that influence patterns of gene flow between lineages. I found that contrary to traditional expectations, divergence in male competitive signals can promote reproductive isolation, and female competition can facilitate hybridization

Extra-Pair Copulation-Seeking Behavior in Purple Martins, Progne subis subis: The Relatedness Hypothesis

Although socially monogamous, both male and female Purple Martins, Progne subis subis, seek extra-pair copulations (EPCs) resulting in multiple-sired broods (Morton 1990; Wagner et al. 1996). Although numerous studies have attempted to explain this behavior, evolutionary mechanisms are not yet known. For this reason I assessed the genetic relatedness hypothesis using microsatellite genotypes derived from a colony of Purple Martins in Severna Park, Maryland from 1993. Although I predicted that all extra-pair offspring would be sired by adult males after their second year of age, extra-pair paternity was not confined to older males. I further predicted that older males sing to attract related subadult males. However there was no evidence that adult males were recruiting related subadults to achieve indirect genetic benefits. I also predicted that females with multiple-sired brood paired to related males seek EPCs leading to extra-pair fertilizations in an attempt to genetically diversify their broods. I found no evidence that avoiding related males was the motive behind EPC-seeking behavior in females. I also predicted that exclusively monogamous females would be less related to their social mate in comparison to polyandrous females. However, there was no significant difference in relatedness between the two

Genomics and spatial surveillance of Chagas disease and American visceral leishmaniasis

The Trypanosomatidae are a family of parasitic protozoa that infect various animals and plants. Several species within the Trypanosoma and Leishmania genera also pose a major threat to human health. Among these are Trypanosoma cruzi and Leishmania infantum, aetiological agents of the highly debilitating and often deadly vector-borne zoonoses Chagas disease and American visceral leishmaniasis. Current treatment options are far from safe, only partially effective and rarely available in the impoverished regions of Latin America where these ‘neglected tropical diseases’ prevail. Wider-reaching, sustainable protection against T. cruzi and L. infantum might best be achieved by intercepting key routes of zoonotic transmission, but this prophylactic approach requires a better understanding of how these parasites disperse and evolve at various spatiotemporal scales. This dissertation addresses key questions around trypanosomatid parasite biology and spatial epidemiology based on high-resolution, geo-referenced DNA sequence datasets constructed from disease foci throughout Latin America: Which forms of genetic exchange occur in T. cruzi, and are exchange events frequent enough to significantly alter the distribution of important epidemiological traits? How do demographic histories, for example, the recent invasive expansion of L. infantum into the Americas, impact parasite population structure, and do structural changes pose a threat to public health? Can environmental variables predict parasite dispersal patterns at the landscape scale? Following the first chapter’s review of population genetic and genomic approaches in the study of trypanosomatid diseases in Latin America, Chapter 2 describes how reproductive polymorphism segregates T. cruzi populations in southern Ecuador. The study is the first to clearly demonstrate meiotic sex in this species, for decades thought to exchange genetic material only very rarely, and only by non-Mendelian means. T. cruzi subpopulations from the Ecuadorian study site exhibit all major hallmarks of sexual reproduction, including genome-wide Hardy-Weinberg allele frequencies, rapid decay of linkage disequilibrium with map distance and genealogies that fluctuate among chromosomes. The presence of sex promotes the transfer and transformation of genotypes underlying important epidemiological traits, posing great challenges to disease surveillance and the development of diagnostics and drugs. Chapter 3 demonstrates that mating events are also pivotal to L. infantum population structure in Brazil, where introduction bottlenecks have led to striking genetic discontinuities between sympatric strains. Genetic hybridization occurs genome-wide, including at a recently identified ‘miltefosine sensitivity locus’ that appears to be deleted from the majority of Brazilian L. infantum genomes. The study combines an array of genomic and phenotypic analyses to determine whether rapid population expansion or strong purifying selection has driven this prominent > 12 kb deletion to high abundance across Brazil. Results expose deletion size differences that covary with phylogenetic structure and suggest that deletion-carrying strains do not form a private monophyletic clade. These observations are inconsistent with the hypothesis that the deletion genotype rose to high prevalence simply as the result of a founder effect. Enzymatic assays show that loss of ecto-3’-nucleotidase gene function within the deleted locus is coupled to increased ecto-ATPase activity, raising the possibility that alternative metabolic strategies enhance L. infantum fitness in its introduced range. The study also uses demographic simulation modelling to determine whether L. infantum populations in the Americas have expanded from just one or multiple introduction events. Comparison of observed vs. simulated summary statistics using random forests suggests a single introduction from the Old World, but better spatial sampling coverage is required to rule out other demographic scenarios in a pattern-process modelling approach. Further sampling is also necessary to substantiate signs of convergent selection introduced above. Chapter 4 therefore develops a ‘genome-wide locus sequence typing’ (GLST) tool to summarize parasite genetic polymorphism at a fraction of genomic sequencing cost. Applied directly to the infection source (e.g., vector or host tissue), the method also avoids bias from cell purification and culturing steps typically involved prior to sequencing of trypanosomatid and other obligate parasite genomes. GLST scans genomic pilot data for hundreds of polymorphic sequence fragments whose thermodynamic properties permit simultaneous PCR amplification in a single reaction tube. For proof of principle, GLST is applied to metagenomic DNA extracts from various Chagas disease vector species collected in Colombia, Venezuela, and Ecuador. Epimastigote DNA from several T. cruzi reference clones is also analyzed. The method distinguishes 387 single-nucleotide polymorphisms (SNPs) in T. cruzi sub-lineage TcI and an additional 393 SNPs in non-TcI clones. Genetic distances calculated from these SNPs correlate with geographic distances among samples but also distinguish parasites from triatomines collected at common collection sites. The method thereby appears suitable for agent-based spatio-genetic (simulation) analyses left wanted by Chapter 3 – and further formulated in Chapter 5. The potential to survey parasite genetic diversity abundantly across landscapes compels deeper, more systematic exploration of how environmental variables influence the spread of disease. As environmental context is only marginally considered in the population genetic analyses of Chapters 2 – 4, Chapter 5 proposes a new, spatially explicit modelling framework to predict vector-borne parasite gene flow through heterogeneous environment. In this framework, remotely sensed environmental raster values are re-coded and merged into a composite ‘resistance surface’ that summarizes hypothesized effects of landscape features on parasite transmission among vectors and hosts. Parasite population genetic differentiation is then simulated on this surface and fitted to observed diversity patterns in order to evaluate original hypotheses on how environmental variables modulate parasite gene flow. The chapter thereby makes a maiden step from standard population genetic to ‘landscape genomic’ approaches in understanding the ecology and evolution of vector-borne disease. In summary, this dissertation first demonstrates the power of population genetics and genomics to understand fundamental biological properties of important protist parasites, then identifies areas where analytical tools are missing and creates new technical and conceptual frameworks to help fill these gaps. The general discussion (Chapter 6) also outlines several follow-up projects on the key finding of meiotic genetic signatures in T. cruzi. Exploiting recently developed T. cruzi genome-editing systems for the detection of meiotic gene expression and heterozygosis will help understand why and in which life cycle stage some parasite populations use sex and others do not. Long-read sequencing of parental and recombinant genomes will help understand the extent to which sex is diversifying T. cruzi phenotypes, especially virulence and drug resistance properties conferred by surface molecules with repetitive genetic bases intractable to short-read analysis. Chapter 6 also provides follow-up plans for all other research chapters. Emphasis is placed on advancing the complementarity, transferability and public health benefit of the many different methods and concepts employed in this work

Culture-free genome-wide locus sequence typing (GLST) provides new perspectives on Trypanosoma cruzi dispersal and infection complexity

El análisis del polimorfismo genético es una poderosa herramienta para la vigilancia epidemiológica y investigar. Sin embargo, la inferencia poderosa de la variación genética del patógeno es a menudo restringido por el acceso limitado al ADN objetivo representativo, especialmente en el estudio de especies parásitas obligadas para las cuales el cultivo ex vivo requiere muchos recursos o es propenso a sesgos. Los métodos modernos de captura de secuencias permiten analizar directamente la variación genética de los patógenos del material del huésped/vector, pero a menudo son demasiado complejos y costosos para entornos de escasos recursos donde prevalecen las enfermedades infecciosas. Este estudio propone un método sencillo y rentable Herramienta de tipificación de secuencias de locus de todo el genoma (GLST) basada en la amplificación paralela masiva de puntos críticos de información en todo el genoma del patógeno objetivo. el multiplexado La reacción en cadena de la polimerasa amplifica cientos de objetivos genéticos diferentes definidos por el usuario en un único tubo de reacción y la posterior limpieza basada en gel de agarosa y código de barras completan la preparación de la biblioteca por menos de 4 USD por muestra. Nuestro estudio genera un modelo flexible Flujo de trabajo de diseño de panel de imprimación GLST para Trypanosoma cruzi, el agente parásito de Chagas enfermedad. Aplicamos con éxito nuestro panel GLST de 203 objetivos a extractos nómicos metagénicos directos y sin cultivo de vectores triatominos que contienen un mínimo de 3,69 pg/μl de ADN de T. cruzi y elaborar más sobre el rendimiento del método mediante la secuenciación de bibliotecas GLST de T. cruzi clones de referencia que representan unidades de tipificación discretas (DTU) TcI, TcIII, TcIV, TcV y TcVI. Los 780 sitios SNP que identificamos en el conjunto de muestras distinguen parásitos de forma repetitiva infectar vectores simpátricos y detectar correlaciones entre distancias genéticas y geográficas a escala regional (< 150 km), así como continental. Los marcadores también separan claramente TcI, TcIII, TcIV y TcV + TcVI y parecen distinguir infecciones multiclonales dentro de TcI. Discutimos las ventajas, limitaciones y perspectivas de nuestro método a través de un espectro de la investigación epidemiológica.Analysis of genetic polymorphism is a powerful tool for epidemiological surveillance and research. Powerful inference from pathogen genetic variation, however, is often restrained by limited access to representative target DNA, especially in the study of obli gate parasitic species for which ex vivo culture is resource-intensive or bias-prone. Mod ern sequence capture methods enable pathogen genetic variation to be analyzed directly from host/vector material but are often too complex and expensive for resource-poor set tings where infectious diseases prevail. This study proposes a simple, cost-effective ‘genome-wide locus sequence typing’ (GLST) tool based on massive parallel amplifica tion of information hotspots throughout the target pathogen genome. The multiplexed polymerase chain reaction amplifies hundreds of different, user-defined genetic targets in a single reaction tube, and subsequent agarose gel-based clean-up and barcoding com pletes library preparation at under 4 USD per sample. Our study generates a flexible GLST primer panel design workflow for Trypanosoma cruzi, the parasitic agent of Chagas disease. We successfully apply our 203-target GLST panel to direct, culture-free metage nomic extracts from triatomine vectors containing a minimum of 3.69 pg/μl T. cruzi DNA and further elaborate on method performance by sequencing GLST libraries from T. cruzi reference clones representing discrete typing units (DTUs) TcI, TcIII, TcIV, TcV and TcVI. The 780 SNP sites we identify in the sample set repeatably distinguish parasites infecting sympatric vectors and detect correlations between genetic and geographic dis tances at regional (< 150 km) as well as continental scales. The markers also clearly sep arate TcI, TcIII, TcIV and TcV + TcVI and appear to distinguish multiclonal infections within TcI. We discuss the advantages, limitations and prospects of our method across a spectrum of epidemiological research

Bulk pollen sequencing reveals rapid evolution of segregation distortion in the male germline of Arabidopsis hybrids

International audienceGenes that do not segregate in heterozygotes at Mendelian ratios are a potentially important evolutionary force in natural populations. Although the impacts of segregation distortion are widely appreciated, we have little quantitative understanding about how often these loci arise and fix within lineages. Here, we develop a statistical approach for detecting segregation distorting genes from the comprehensive comparison of whole genome sequence data obtained from bulk gamete versus somatic tissues. Our approach enables estimation of map positions and confidence intervals, and quantification of effect sizes of segregation distorters. We apply our method to the pollen of two interspecific F1 hybrids of Arabidopsis lyrata and A. halleri and we identify three loci across eight chromosomes showing significant evidence of segregation distortion in both pollen samples. Based on this, we estimate that novel segregation distortion elements evolve and achieve high frequencies within lineages at a rate of approximately one per 244,000 years. Furthermore, we estimate that haploid-acting segregation distortion may contribute between 10% and 30% of reduced pollen viability in F1 individuals. Our results indicate haploid acting factors evolve rapidly and dramatically influence segregation in F1 hybrid individuals

MHC polymorphism in a songbird : Fitness, mate choice, and sexual conflict

Sex differences in immune responses have been observed across a wide range of animal species, with the generaltendency that males have weaker immune responses than females. These differences are at least partly caused by immune-regulating effects of sex hormones, and have been associated with an increased prevalence of autoimmune disorders in females and with a general tendency for males to be parasitized more often than females. Because of these differences, male and female phenotypes may be regarded as different immunological environments, however it has not previously been investigated whether sex differences in immune responses may lead to sexually antagonistic selection on immune system genes.The first chapter of this thesis presents a literature study of the effects of sex hormones on the strength of immune responses in vertebrates, based on which we propose the hypothesis that sexual selection may drive sexually antagonistic selection on genes associated with the immune system. In the following chapters, we investigated this hypothesis using major histocompatibility complex class I (MHC-I) genes in a species subject to strong sexual selection, a socially polygynous songbird, the great reed warbler Acrocephalus arundinaceus.MHC genes play an important role in vertebrate adaptive immunity where they enable recognition and elimination of pathogens. Due to an ongoing co-evolution between hosts and their pathogens, the MHC genes are among the most variable genes known in vertebrates. It has been hypothesized that hosts benefit from having high MHC diversity, because this confers protection against a wider range of pathogens. Interestingly, we found evidence for a sexual conflict and for sexually differential selection on MHC-I diversity in our great reed warbler study population.It has been predicted that genes associated with disease resistance should be advantageous in terms of sexual selection, and this prediction is central to our hypothesis that sexual selection may drive sexually antagonistic selection on genes associated with the immune system. We therefore investigated whether MHC-I genes were associated with sexual selection in great reed warblers. Our results indicated that MHC-I diversity (i) conveys a ‘good genes’ benefit to females that select older males and males with large song repertoires, and (ii) affects the ability of males to acquire attractive territories. These results confirmed that MHC-I genes are associated with sexual selection, and thereby corroborated our hypothesis that sexual selection may be driving the observed sexual conflict over MHC-I diversity via immune regulating effects of sex hormones.Finally, we investigated the source of MHC-I genotypic variation in great reed warblers by analyzing segregation of MHC-I haplotypes and performing phylogenetic reconstruction on MHC-I alleles. We identified five distinct clades in a phylogenetic tree that indicate the presence of several divergent MHC-I loci in the great reed warbler genome. Analyses of positive selection implied that each putative MHC-I locus may have evolved slightly different functions. Importantly, variation in MHC-I diversity between haplotypes was largely explained by variation within two specific clades, suggesting that the sexual conflict over MHC-I diversity may be caused by sexually antagonistic effects associated with alleles from these clades in particular.Our results suggest that sexually antagonistic selection is an important force in the evolution of vertebrate adaptive immunity, which may be important for a comprehensive, evolutionary understanding of autoimmune diseases and other costs associated with immune responses in vertebrates. The results presented in this thesis invite further studies that investigate the generality of sexually antagonistic selection over immune system genes in other species, as well as more detailed studies of the mechanisms underlying such sexual conflicts

Mechanisms Driving Karyotype Evolution and Genomic Architecture

Understanding of the origin of species and their adaptability to new environments is one of the main questions in biology. This is fueled by the ongoing debate on species concepts and facilitated by the availability of an unprecedented large number of genomic resources. Genomes are organized into chromosomes, where significant variations in number and morphology are observed among species due to large-scale structural variants such as inversions, translocations, fusions, and fissions. This genomic reshuffling provides, in the long term, new chromosomal forms on which natural selection can act upon, contributing to the origin of biodiversity. This book contains mainly articles, reviews, and an opinion piece that explore numerous aspects of genome plasticity among taxa that will help in understanding the dynamics of genome composition, the evolutionary relationships between species and, in the long run, speciation

Investigate Genomic 3D Structure Using Deep Neural Network

The 3D structures of the chromosomes play fundamental roles in essential cellular functions, e.g., gene regulation, gene expression, evolution and Hi-C technique provides the interaction density between loci on chromosomes. In this dissertation, we developed multiple algorithms, focusing the deep learning approach, to study the Hi-C datasets and the genomic 3D structures. Building 3D structure of the genome one of the most critical purpose of the Hi-C technique. Recently, several approaches have been developed to reconstruct the 3D model of the chromosomes from HiC data. However, all of the methods are based on a particular mathematical model and lack of flexibility for new development.We introduce a novel approach using the genetic algorithm. Our approach is flexible to accept any mathematical models to build a 3D chromosomal structure. Also, our approach outperforms current techniques in accuracy. Although an increasing number of Hi-C datasets have been generated in a variety of tissue/cell types, Due to high sequencing cost, the resolution of most Hi-C datasets are coarse and cannot be used to infer important biological functions (e.g., enhancerpromoter interactions, and link disease-related non-coding variants to their target genes). To address this challenge, we develop HiCPlus, a computational approach based on deep convolutional neural network, to infer high-resolution Hi-C interaction matrices from low-resolution Hi-C data. Through extensive testing, we demonstrate that HiCPlus can impute interaction matrices highly similar to original ones while using only as few as 1/16 of the total sequencing reads. We observe that Hi-C interaction matrix contains unique local features that are consistent across di!erent cell types, and such features can be e!ectively captured by the deep learning framework. We further apply HiCPlus to enhance and expand the usability of Hi-C datasets in a variety of tissue and cell types. In summary, our work not only provides a framework to generate high-resolution Hi-C matrix with a fraction of the sequencing cost but also reveals features underlying the formation of 3D chromatin interactions. The noise level in the Hi-C is high, and the structure of the noise is complicated. Also, even under most strict experimental conditions, the absolute noise-free Hi-C data still cannot be obtained. We proposed a novel approach to learn a denoising network without clean data. Our approach employs Siamese structure, utilizing two replicates of the same experimental settings to train the model; the resulting model can then be applied to datasets where only one replicate is available. We applied our new approach to enhance Hi-C data, an important type of data in exploring threedimensional genomic structures. The results prove that the model trained by our method significantly reduce the noise level in Hi-C data. In the past few years, we have seen an explosion of Hi-C data in a variety of cell/tissue types. While these publicly available data presents an unprecedented opportunity to interrogate chromosomal architecture, how to quantitatively compare Hi-C data from di!erent tissues and identify tissue-specific chromatin interactions remains challenging. We developed HiCComp, a comprehensive framework for comparing Hi-C data. HiCComp utilizes convolutional neural networks to extract key features in Hi-C interaction matrices in a fully automatic way. The core component of HiCComp is a triplet network, which contains three identical convolutional neural networks with shared parameters. The inputs to our network are three Hi-C matrices: two of them are biological replicates from the same cell type, and the third one is from another cell type. The HiCComp network takes advantages of the two biological replicates to estimate the natural variation in the experiments and further use it to identify significant variations between Hi-C matrices from di!erent cell types. Furthermore, we incorporate systematic occluding method into our framework so that we can identify the dynamic interaction regions from Hi-C maps. Finally, we show that the dynamic regions between two cell types are enriched for transcription factor binding sites and histone modifications that are associated with cis-regulatory functions, suggesting these variations in 3D genome structure are potentially gene regulatory events

Morphological, genotypic and metabolomic signatures confirm interfamilial hybridization between the ubiquitous kelps Macrocystis (Arthrothamnaceae) and Lessonia (Lessoniaceae)

We thank the support from G. Millne (UoA), M. Rateb (UoA) and D. Zagal (UACh) in the histological preparations, mass spectrometry set-up and the cultivation of the hybrid progeny, respectively. PM and LM developed part of this work with BecasChile (Fondecyt) funding, specifically grants No. 72130422 (PM) and No. 73140389 (LM). We would like to acknowledge the British Council Newton Fund Institutional Links, project No. 261781172 for funding SS a postdoctoral research fellow. We are also grateful to the UK Natural Environment Research Council for their support to FCK (program Oceans 2025–WP 4.5 and grants NE/D521522/1 and NE/ J023094/1). This work also received support from the Marine Alliance for Science and Technology for Scotland pooling initiative. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. RW thanks financial support from Gobierno Regional de Los Lagos (grants FIC 2012 E7259-2 and FIC 2013 BIP30234872-0) and Fondef, Conicyt (HUAM AQ12I0010), which allows the sampling expeditions at Chiloe Island by PM, LM, DJP.Peer reviewedPublisher PD