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Títol: The effect of pervasive selection on the inference of demographic patterns of a population

Estudiant que ha llegit aquest projecte:

Tutor/a o Cotutor/a: CASALS MISSIO, JOAN

Departament: DEAB

Títol: The effect of pervasive selection on the inference of demographic patterns of a population

Data inici oferta: 12-09-2024      Data finalització oferta: 12-12-2024

Estudis d'assignació del projecte:
    GR ENG SIS BIOLÒG 23

Lloc de realització:
EEABB

Paraules clau:
Inferència demogràfica, espectre de freqüències al·lèliques (SFS), mida efectiva de població (Ne), simulacions forward-in-time, Stairway Plot, genòmica de poblacions, colls d'ampolla demogràfics

Descripció del contingut i pla d'activitats:
A key factor in the study of the evolution of the populations is determining their demographic history. Demographic trajectories of a population across the time (also called demographic landscape) can be inferred from genome sequence data using different methodologies (e.g., PSMC: Schiffels and Durbin 2014, Schweiger and Durbin 2023, MSMC: Li and Durbin 2011, Malaspinas et al. 2016, Stairway plot: Liu and Fu 2015, 2020). These methodologies assume that most positions in the genome are neutral (i.e., not affected by selection), that is, gene regions represent a tiny section of the genome and should not affect the demographic pattern. Nevertheless, it is known that deleterious mutations are spread across the functional regions of the genome, affecting neutral positions surrounding them in the whole genome (e.g., Fay 2011, Cao et al. 2011, Chao et al. 2013, Comeron 2017, Messer and Petrov 2013, Lye et al. 2017), and perhaps affect the inference of demographic patterns. Furthermore, in the case of plant species, self-pollination and low recombination increase linkage and can amplify the deviation from genome neutrality.

In this study, we consider deleterious (and beneficial) mutations distributed across the genome and vary recombination patterns, to contrast simulated demographic scenarios versus their inference. To achieve this analysis, we will (i) perform shell scripts to automatize the simulation study and (ii) obtain genome sequences from a population with SLiM (Haller and Messer 2023), a forward-in-time simulator where complex demographic and selective patterns can be easily included. (iii) Sequence data will be processed to obtain the frequency of the variants (e.g., using SLiM code) and (iv) the inference of the demographic trajectories will be obtained with Stairway Plot (Liu and Fu 2020). (v) Statistical comparisons will be performed in R. The results of this work will help to understand the contradictions between molecular and paleontological dating results.

Overview (resum en anglès): Understanding the demographic history of populations is essential to interpret patterns of
genetic diversity and evolutionary processes. Changes in population size, such as expansions or
bottlenecks, leave detectable signatures in genomic data, making it possible to reconstruct past
population dynamics.
In this study, we evaluate the ability to infer population demographic history from genomic data
using forward-in-time simulations. The focus is on assessing the reliability, temporal resolution,
and limitations of SFS-based demographic inference methods, using Stairway Plot as the primary
inference framework.
Genomic data were simulated under four theoretical demographic models of increasing
complexity: constant population size, a two-epoch model, a single bottleneck with recovery, and
multiple bottlenecks. Inferred Ne trajectories were directly compared with the corresponding
theoretical models, allowing a systematic evaluation of inference accuracy and identification of
methodological biases.
Results show that simple demographic scenarios, such as constant size and two-epoch models,
are accurately reconstructed, although with reduced resolution at very recent and ancient time
periods. In contrast, bottlenecked scenarios exhibit systematic smoothing of abrupt
demographic changes, overestimation of post-bottleneck Ne, and limited ability to resolve
closely spaced demographic events.
Overall, this work provides a reference framework for SFS-based demographic inference,
providing a necessary reference framework for interpreting inferred demographic histories. This
baseline will support future studies aimed at disentangling the effects of demographic
complexity and evolutionary processes such as positive and negative selection or recombination
rate heterogeneity.

Aquest projecte està relacionat amb l'adaptació al Canvi Climatic? No

Aquest projecte està relacionat amb la digitalització del seu àmbit de treball? Sí

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