A genome-wide comparison between selected and unselected Valle del Belice sheep reveals differences in population structure and footprints of recent selection

About three decades of breeding and selection in the Valle del Belìce sheep are expected to have left several genomic footprints related to milk production traits. In this study, we have assembled a dataset with 451 individuals of the Valle del Belìce sheep breed: 184 animals that underwent directional selection for milk production and 267 unselected animals, genotyped for 40,660 single-nucleotide polymorphisms (SNPs). Three different statistical approaches, both within (iHS and ROH) and between (Rsb) groups, were used to identify genomic regions potentially under selection. Population structure analyses separated all individuals according to their belonging to the two groups. A total of four genomic regions on two chromosomes were jointly identified by at least two statistical approaches. Several candidate genes for milk production were identified, corroborating the polygenic nature of this trait and which may provide clues to potential new selection targets. We also found candidate genes for growth and reproductive traits. Overall, the identified genes may explain the effect of selection to improve the performances related to milk production traits in the breed. Further studies using high-density array data, would be particularly relevant to refine and validate these results

Genomic data as the “hitchhiker's guide” to cattle adaptation: tracking the milestones of past selection in the bovine genome

The bovine species have witnessed and played a major role in the drastic socio-economical changes that shaped our culture over the last 10,000 years. During this journey, cattle hitchhiked on human development and colonized the world, facing strong selective pressures such as dramatic environmental changes and disease challenge. Consequently, hundreds of specialized cattle breeds emerged and spread around the globe, making up a rich spectrum of genomic resources. Their DNA still carry the scars left from adapting to this wide range of conditions, and we are now empowered with data and analytical tools to track the milestones of past selection in their genomes. In this review paper, we provide a summary of the reconstructed demographic events that shaped cattle diversity, offer a critical synthesis of popular methodologies applied to the search for signatures of selection (SS) in genomic data, and give examples of recent SS studies in cattle. Then, we outline the potential and challenges of the application of SS analysis in cattle, and discuss the future directions in this field

Predicting Thermal Adaptation by Looking Into Populations’ Genomic Past

Molecular evolution offers an insightful theory to interpret the genomic consequences of thermal adaptation to previous events of climate change beyond range shifts. However, disentangling often mixed footprints of selective and demographic processes from those due to lineage sorting, recombination rate variation, and genomic constrains is not trivial. Therefore, here we condense current and historical population genomic tools to study thermal adaptation and outline key developments (genomic prediction, machine learning) that might assist their utilization for improving forecasts of populations’ responses to thermal variation. We start by summarizing how recent thermal-driven selective and demographic responses can be inferred by coalescent methods and in turn how quantitative genetic theory offers suitable multi-trait predictions over a few generations via the breeder’s equation. We later assume that enough generations have passed as to display genomic signatures of divergent selection to thermal variation and describe how these footprints can be reconstructed using genome-wide association and selection scans or, alternatively, may be used for forward prediction over multiple generations under an infinitesimal genomic prediction model. Finally, we move deeper in time to comprehend the genomic consequences of thermal shifts at an evolutionary time scale by relying on phylogeographic approaches that allow for reticulate evolution and ecological parapatric speciation, and end by envisioning the potential of modern machine learning techniques to better inform long-term predictions. We conclude that foreseeing future thermal adaptive responses requires bridging the multiple spatial scales of historical and predictive environmental change research under modern cohesive approaches such as genomic prediction and machine learning frameworks

Genomic analysis of Ugandan and Rwandan chicken ecotypes using a 600 k genotyping array

Background Indigenous populations of animals have developed unique adaptations to their local environments, which may include factors such as response to thermal stress, drought, pathogens and suboptimal nutrition. The survival and subsequent evolution within these local environments can be the result of both natural and artificial selection driving the acquisition of favorable traits, which over time leave genomic signatures in a population. This study’s goals are to characterize genomic diversity and identify selection signatures in chickens from equatorial Africa to identify genomic regions that may confer adaptive advantages of these ecotypes to their environments. Results Indigenous chickens from Uganda (n = 72) and Rwanda (n = 100), plus Kuroilers (n = 24, an Indian breed imported to Africa), were genotyped using the Axiom® 600 k Chicken Genotyping Array. Indigenous ecotypes were defined based upon location of sampling within Africa. The results revealed the presence of admixture among the Ugandan, Rwandan, and Kuroiler populations. Genes within runs of homozygosity consensus regions are linked to gene ontology (GO) terms related to lipid metabolism, immune functions and stress-mediated responses (FDR \u3c 0.15). The genes within regions of signatures of selection are enriched for GO terms related to health and oxidative stress processes. Key genes in these regions had anti-oxidant, apoptosis, and inflammation functions. Conclusions The study suggests that these populations have alleles under selective pressure from their environment, which may aid in adaptation to harsh environments. The correspondence in gene ontology terms connected to stress-mediated processes across the populations could be related to the similarity of environments or an artifact of the detected admixture

Demography, Selection and Evolution in Conifers

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Biología. Fecha de lectura: 12-09-2017La presente tesis doctoral la componen un total de 3 capítulos dedicados a inferir diferentes aspectos de la adaptación molecular en las coníferas. En el primer capítulo introducimos el trabajo y lo contextualizamos en el actual entendimiento de la genética molecular de las coníferas. En el segundo capítulo nos centramos en el estudio de la demografía y los procesos de selección natural del pino Carrasco (Pinus halepensis Mill) a lo largo de su distribución natural. Ahondamos en el efecto de la historia demográfica y del “gene surfing” (fenómeno estocástico por el que genes de baja frecuencia pueden alcanzar altas frecuencias a causa de colonizaciones a larga distancia) y de cómo esto dificulta la detección de las señales de selección. En el tercer capítulo estudiamos los procesos de selección a escala local, para lo cual utilizamos pares de poblaciones procedentes de zonas cuyas características ambientales contrastan entre sí, dentro del hábitat del pino Carrasco. Para desarrollar este capítulo comparamos diferentes metodologías estadísticas para inferir SNPs con frecuencias atípicas potencialmente bajo selección. Usamos lo aprendido hasta ahora para inferir selección en otras especies de coníferas, haciendo uso de datos genómicos. En el cuarto capítulo investigamos los MicroRNAs (un tipo de Pequeño ARN no codificante) en coníferas como una potencial y clave dirección para entender la adaptación molecular. Exploramos cómo establecer una ontología de genes para estas moléculas y así facilitar la transferencia de conocimientos de especies modelo, como es Arabidopsis thaliana (L.) Heynh, a otras especies a día de hoy menos estudiadas como son el grupo de coníferas. Keywords: Molecular Ecology, Selection, Adaptation, Genomics, Conifers

Genomic signature of adaptive divergence despite strong nonadaptive forces on Edaphic Islands: A case study of primulina juliae

Both genetic drift and divergent selection are expected to be strong evolutionary forces driving population differentiation on edaphic habitat islands. However, the relative contribution of genetic drift and divergent selection to population divergence has rarely been tested simultaneously. In this study, restriction-site associated DNA-based population genomic analyses were applied to assess the relative importance of drift and divergent selection on population divergence of Primulina juliae, an edaphic specialist fromsouthern China. All populations were found with low standing genetic variation, small effective population size (NE), and signatures of bottlenecks. Populations with the lowest genetic variation were most genetically differentiated from other populations and the extent of genetic drift increased with geographic distance fromother populations. Together with evidence of isolation by distance, these results support neutral drift as a critical evolutionary driver.Nonetheless, redundancy analysis revealed that genomic variation is significantly associated with both edaphic habitats and climatic factors independently of spatial effects. Moreover, more genomic variationwas explained by environmental factors than by geographic variables, suggesting that local adaptationmight have played an important role in driving population divergence. Finally, outlier tests and environment association analyses identified 31 singlenucleotide polymorphisms as candidates for adaptive divergence. Among these candidates, 26 single-nucleotide polymorphisms occur in/near genes that potentially play a role in adaptation to edaphic specialization. This study has important implications that improve our understanding of the joint roles of genetic drift and adaptation in generating population divergence and diversity of edaphic specialists

Genomic Comparison of Indigenous African and Northern European Chickens Reveals Putative Mechanisms of Stress Tolerance Related to Environmental Selection Pressure

Global climate change is increasing the magnitude of environmental stressors, such as temperature, pathogens, and drought, that limit the survivability and sustainability of livestock production. Poultry production and its expansion is dependent upon robust animals that are able to cope with stressors in multiple environments. Understanding the genetic strategies that indigenous, noncommercial breeds have evolved to survive in their environment could help to elucidate molecular mechanisms underlying biological traits of environmental adaptation. We examined poultry from diverse breeds and climates of Africa and Northern Europe for selection signatures that have allowed them to adapt to their indigenous environments. Selection signatures were studied using a combination of population genomic methods that employed FST, integrated haplotype score (iHS), and runs of homozygosity (ROH) procedures. All the analyses indicated differences in environment as a driver of selective pressure in both groups of populations. The analyses revealed unique differences in the genomic regions under selection pressure from the environment for each population. The African chickens showed stronger selection toward stress signaling and angiogenesis, while the Northern European chickens showed more selection pressure toward processes related to energy homeostasis. The results suggest that chromosomes 2 and 27 are the most diverged between populations and the most selected upon within the African (chromosome 27) and Northern European (chromosome 2) birds. Examination of the divergent populations has provided new insight into genes under possible selection related to tolerance of a population’s indigenous environment that may be baselines for examining the genomic contribution to tolerance adaptions

Inferring Signatures of Positive Selection in Whole-Genome Sequencing Data: An Overview of Haplotype-Based Methods

Signatures of positive selection in the genome are a characteristic mark of adaptation that can reveal an ongoing, recent, or ancient response to environmental change throughout the evolution of a population. New sources of food, climate conditions, and exposure to pathogens are only some of the possible sources of selective pressure, and the rise of advantageous genetic variants is a crucial determinant of survival and reproduction. In this context, the ability to detect these signatures of selection may pinpoint genetic variants that are responsible for a significant change in gene regulation, gene expression, or protein synthesis, structure, and function. This review focuses on statistical methods that take advantage of linkage disequilibrium and haplotype determination to reveal signatures of positive selection in whole-genome sequencing data, showing that they emerge from different descriptions of the same underlying event. Moreover, considerations are provided around the application of these statistics to different species, their suitability for ancient DNA, and the usefulness of discovering variants under selection for biomedicine and public health in an evolutionary medicine framework

PLoS One

VKORC1 (vitamin K epoxide reductase complex subunit 1, 16p11.2) is the main genetic determinant of human response to oral anticoagulants of antivitamin K type (AVK). This gene was recently suggested to be a putative target of positive selection in East Asian populations. In this study, we genotyped the HGDP-CEPH Panel for six VKORC1 SNPs and downloaded chromosome 16 genotypes from the HGDP-CEPH database in order to characterize the geographic distribution of footprints of positive selection within and around this locus. A unique VKORC1 haplotype carrying the promoter mutation associated with AVK sensitivity showed especially high frequencies in all the 17 HGDP-CEPH East Asian population samples. VKORC1 and 24 neighboring genes were found to lie in a 505 kb region of strong linkage disequilibrium in these populations. Patterns of allele frequency differentiation and haplotype structure suggest that this genomic region has been submitted to a near complete selective sweep in all East Asian populations and only in this geographic area. The most extreme scores of the different selection tests are found within a smaller 45 kb region that contains VKORC1 and three other genes (BCKDK, MYST1 (KAT8), and PRSS8) with different functions. Because of the strong linkage disequilibrium, it is not possible to determine if VKORC1 or one of the three other genes is the target of this strong positive selection that could explain present-day differences among human populations in AVK dose requirement. Our results show that the extended region surrounding a presumable single target of positive selection should be analyzed for genetic variation in a wide range of genetically diverse populations in order to account for other neighboring and confounding selective events and the hitchhiking effect