Population Genetics of the Aquatic Fungus Tetracladium marchalianum over Space and Time

Abstract The geographic distribution of genetic variation is an important theoretical and experimental component of population genetics. Previous characterizations of genetic structure of populations have used measures of spatial variance and spatial correlations. Yet a full understanding of the causes and consequences of spatial structure requires complete characterization of the underlying space-time system. This paper examines important interactions between processes and spatial structure in systems of subpopulations with migration and drift, by analyzing correlations of gene frequencies over space and time. We develop methods for studying important features of the complete set of space-time correlations of gene frequencies for the first time in population genetics. These methods also provide a new alternative for studying the purely spatial correlations and the variance, for models with general spatial dimensionalities and migration patterns. These results are obtained by employing theorems, previously unused in population genetics, for space-time autoregressive (STAR) stochastic spatial time series. We include results on systems with subpopulation interactions that have time delay lags (temporal orders) greater than one. We use the space-time correlation structure to develop novel estimators for migration rates that are based on space-time data (samples collected over space and time) rather than on purely spatial data, for real systems. We examine the space-time and spatial correlations for some specific stepping stone migration models. One focus is on the effects of anisotropic migration rates. Partial space-time correlation coefficients can be used for identifying migration patterns. Using STAR models, the spatial, space-time, and partial space-time correlations together provide a framework with an unprecedented level of detail for characterizing, predicting and contrasting space-time theoretical distributions of gene frequencies, and for identifying features such as the pattern of migration and estimating migration rates in experimental studies of genetic variation over space and time.

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Ancient DNA and the Population Genetics of Cave Bears (Ursus spelaeus) Through Space and Time

Molecular Biology and Evolution ◽

10.1093/oxfordjournals.molbev.a004016 ◽

2002 ◽

Vol 19 (11) ◽

pp. 1920-1933 ◽

Cited By ~ 71

Author(s):

Ludovic Orlando ◽

Dominique Bonjean ◽

Herve Bocherens ◽

Aurelie Thenot ◽

Alain Argant ◽

...

Keyword(s):

Population Genetics ◽

Ancient Dna ◽

Space And Time

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Coalescent models for developmental biology and the spatio-temporal dynamics of growing tissues.

10.1101/022251 ◽

2015 ◽

Author(s):

Patrick Smadbeck ◽

Michael P.H. Stumpf

Keyword(s):

Developmental Biology ◽

Population Genetics ◽

Large Scale ◽

Cell Tracking ◽

Temporal Dynamics ◽

Growth Models ◽

Tissue Growth ◽

Lineage Tracing ◽

Space And Time ◽

Spatio Temporal

Development is a process that needs to tightly coordinated in both space and time. Cell tracking and lineage tracing have become important experimental techniques in developmental biology and allow us to map the fate of cells and their progeny in both space and time. A generic feature of developing (as well as homeostatic) tissues that these analyses have revealed is that relatively few cells give rise to the bulk of the cells in a tissue; the lineages of most cells come to an end fairly quickly. This has spurned the interest also of computational and theoretical biologists/physicists who have developed a range of modelling -- perhaps most notably are the agent-based modelling (ABM) --- approaches. These can become computationally prohibitively expensive but seem to capture some of the features observed in experiments. Here we develop a complementary perspective that allows us to understand the dynamics leading to the formation of a tissue (or colony of cells). Borrowing from the rich population genetics literature we develop genealogical models of tissue development that trace the ancestry of cells in a tissue back to their most recent common ancestors. We apply this approach to tissues that grow under confined conditions --- as would, for example, be appropriate for the neural crest --- and unbounded growth --- illustrative of the behaviour of 2D tumours or bacterial colonies. The classical coalescent model from population genetics is readily adapted to capture tissue genealogies for different models of tissue growth and development. We show that simple but universal scaling relationships allow us to establish relationships between the coalescent and different fractal growth models that have been extensively studied in many different contexts, including developmental biology. Using our genealogical perspective we are able to study the statistical properties of the processes that give rise to tissues of cells, without the need for large-scale simulations.

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New root endophytic water borne conidial fungi from Kumaun Himalaya

Current Botany ◽

10.19071/cb.2017.v8.3122 ◽

2017 ◽

Vol 8 ◽

pp. 12 ◽

Cited By ~ 1

Author(s):

S. C. Sati ◽

Richa Pathak

Keyword(s):

Plant Species ◽

Host Plants ◽

Healthy Plant ◽

Aquatic Fungus ◽

Root Endophytes ◽

Kumaun Himalaya ◽

Conidial Fungi ◽

New Hosts ◽

Water Borne ◽

Tetracladium Marchalianum

Water borne conidial fungi occurring in living roots of healthy plant growing in the wet and ravine areas of Dogaon and Ramgarh, Nainital, Kumaun Himalaya (India) were isolated as root endophytes. A total of 15 species (Alatospora acuminata, Anguillospora longissima, Beltrania rhombica, Campylospora chaetocladia, Claviriopsis aquatica, Cylindrocarpon aquaticum, Flagellospora penicilloides, Helicomyces roseus, Helicosporium lumbricoides, Pleurophragmium sonum, Pestalotiopsis submersus, Seridium sp, Setosynnema isthomosporum, Tetrachaetum elegans and Tetracladium marchalianum) of endophytic aquatic fungus were recovered as root endophytes of various host plants. Three species viz. Helicosporium lumbricoides, Pleurophragmium sonum and Setosynnema isthomosporum isolated from the roots of pteridophytes and grasses were found as new root endophytes. Among the studied host plants five plant species were also found as new hosts.

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Spatial Population Genetics: It's About Time

Annual Review of Ecology Evolution and Systematics ◽

10.1146/annurev-ecolsys-110316-022659 ◽

2019 ◽

Vol 50 (1) ◽

pp. 427-449 ◽

Cited By ~ 20

Author(s):

Gideon S. Bradburd ◽

Peter L. Ralph

Keyword(s):

Population Genetics ◽

Genetic Variation ◽

Evolutionary Process ◽

Genetic Data ◽

Space And Time ◽

Spatial Population ◽

Alive Today

Many important questions about the history and dynamics of organisms have a geographical component: How many are there, and where do they live? How do they move and interbreed across the landscape? How were they moving a thousand years ago, and where were the ancestors of a particular individual alive today? Answers to these questions can have profound consequences for our understanding of history, ecology, and the evolutionary process. In this review, we discuss how geographic aspects of the distribution, movement, and reproduction of organisms are reflected in their pedigree across space and time. Because the structure of the pedigree is what determines patterns of relatedness in modern genetic variation, our aim is to thus provide intuition for how these processes leave an imprint in genetic data. We also highlight some current methods and gaps in the statistical toolbox of spatial population genetics.

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