Dataset Information

Genomic Targets of Positive Selection in Giant Mice from Gough Island.

ABSTRACT: A key challenge in understanding how organisms adapt to their environments is to identify the mutations and genes that make it possible. By comparing patterns of sequence variation to neutral predictions across genomes, the targets of positive selection can be located. We applied this logic to house mice that invaded Gough Island, an unusual population that shows phenotypic and ecological hallmarks of selection. We used massively parallel short-read sequencing to survey the genomes of 14 Gough Island mice. We computed a set of summary statistics to capture diverse aspects of variation across these genome sequences, used approximate Bayesian computation to reconstruct a null demographic model, and then applied machine learning to estimate the posterior probability of positive selection in each region of the genome. Using a conservative threshold, 1,463 5kb windows show strong evidence for positive selection in Gough Island mice but not in a mainland reference population of German mice. Disproportionate shares of these selection windows contain genes that harbor derived nonsynonymous mutations with large frequency differences. Over-represented gene ontologies in selection windows emphasize neurological themes. Inspection of genomic regions harboring many selection windows with high posterior probabilities pointed to genes with known effects on exploratory behavior and body size as potential targets. Some genes in these regions contain candidate adaptive variants, including missense mutations and/or putative regulatory mutations. Our results provide a genomic portrait of adaptation to island conditions and position Gough Island mice as a powerful system for understanding the genetic component of natural selection.

SUBMITTER: Payseur BA

PROVIDER: S-EPMC7947842 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic selection in autogamous crops, especially bringing long-term improvement.

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Genomic Targets of Positive Selection in Giant Mice from Gough Island.

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