Biology subjects

Reid, K.

Publications and source records attributed to Reid, K..

23 records · Page 2Linked to original sources

bioRxiv2023

Heterogeneous genomic architecture of skeletal armour traits in sticklebacks

Whether populations adapt to similar selection pressures using the same underlying genetic variants depends on population history and the distribution of standing genetic variation at the metapopulation level. Studies of sticklebacks provide a case in point: when colonising and adapting to freshwater habitats, three-spined sticklebacks (Gasterosteus aculeatus; TSSs) with high gene flow tend to fix the same adaptive alleles in the same major loci, whereas nine-spined sticklebacks (Pungitius pungitius; NPSs) with limited gene flow tend to utilize a more heterogeneous set of loci. In accordance with this, we report results of quantitative trait locus (QTL) analyses using a F2 back-cross design showing that lateral plate number variation in the western European lineage of NPSs mapped to three moderate-effect QTL, contrary to one major QTL in TSSs and these QTL were different from the four previously identified QTL in the eastern European lineage of NPSs. Furthermore, several QTL were identified associated with variation in lateral plate size, and three moderate-effect QTL with body size. Together, these findings indicate that genetic underpinnings of skeletal armour variation in Pungitius sticklebacks are more polygenic and heterogenous than those in three-spined sticklebacks, indicating limited genetic parallelism underlying armour trait evolution in the family Gasterostidae.

evolutionary biology↗

bioRxiv2023

De novo mutation rates in sticklebacks

Mutation rate is a fundamental parameter in population genetics. Apart from being an important scaling parameter for demographic and phylogenetic inference, it allows one to understand at what rate new genetic diversity is generated and what is the expected level of genetic diversity in a population at equilibrium. However, except for well-established model organisms, accurate estimates of de novo mutation rates are available for a very limited number of organisms from the wild. We estimated mutation rates ({micro}) in two marine populations of the nine-spined stickleback (Pungitius pungitius) with the aid of several 2- and 3-generational family pedigrees, deep (>50x) whole genome re-sequencing and a high-quality reference genome. After stringent filtering, we discovered 295 germline mutations from 106 offspring translating to {micro} = 4.64 x 10-9 and {micro} = 4.08 x 10-9 per base, per generation, in the two populations, respectively. Twenty percent of the mutations were shared by full-sibs showing that the level of parental mosaicism was relatively high. Since the estimated {micro} was 3.2 times smaller than the commonly used substitution rate, recalibration with {micro} led to substantial increase in estimated divergence times between different stickleback species. Our estimates of de novo mutation rate should provide a useful resource for research focused on fish population genetics and that of sticklebacks in particular.

genomics↗

bioRxiv2022

Reducing mitochondrial ribosomal gene expression does not alter metabolic health or lifespan in mice

Maintaining mitochondrial function is critical to an improved health span and lifespan. Introducing mild stress by inhibiting mitochondrial translation invokes the mitochondrial unfolded protein response (UPRmt) and increases lifespan in several animal models. Notably, lower mitochondrial ribosomal protein (MRP) expression also correlates with increased lifespan in a reference population of mice. In this study, we tested whether partially reducing the expression of a critical MRP, Mrpl54, reduced mitochondrial DNA-encoded protein content, induced the UPRmt, and affected lifespan or metabolic health using germline heterozygous Mrpl54 mice. Despite reduced Mrpl54 expression in multiple organs and a reduction in mitochondrial-encoded protein expression in myoblasts, we identified few significant differences between male or female Mrpl54+/- and wild type mice in initial body composition, respiratory parameters, energy intake and expenditure, or ambulatory motion. We also observed no differences in glucose or insulin tolerance, treadmill endurance, cold tolerance, heart rate, or blood pressure. There were no differences in median life expectancy or maximum lifespan. Overall, we demonstrate that genetic manipulation of Mrpl54 expression reduces mitochondrial-encoded protein content but is not sufficient to improve healthspan in otherwise healthy and unstressed mice.

cell biology↗

bioRxiv2020

Heuristic hyperparameter optimization of deep learning models for genomic prediction

There is a growing interest among quantitative geneticists and animal breeders in the use of deep learning (DL) for genomic prediction. However, the performance of DL is affected by hyperparameters that are typically manually set by users. These hyperparameters do not simply specify the architecture of the model, they are also critical for the efficacy of the optimization and model fitting process. To date, most DL approaches used for genomic prediction have concentrated on identifying suitable hyperparameters by exploring discrete options from a subset of the hyperparameter space. Enlarging the hyperparameter optimization search space with continuous hyperparameters is a daunting combinatorial problem. To deal with this problem, we propose using differential evolution (DE) to perform an efficient search of arbitrarily complex hyperparameter spaces in DL models and we apply this to the specific case of genomic prediction of livestock phenotypes. This approach was evaluated on two pig and cattle datasets with real genotypes and simulated phenotypes (N=7,539 animals and M=48,541 markers) and one real dataset (N=910 individuals and M=28,916 markers). Hyperparameters were evaluated using cross validation. We compared the predictive performance of DL models using hyperparameters optimized by DE against DL models with "best practice" hyperparameters selected from published studies and baseline DL models with randomly specified hyperparameters. Optimized models using DE showed clear improvement in predictive performance across all three datasets.DE optimized hyperparameters also resulted in DL models with less overfitting and less variation in predictive performance over repeated retraining compared to non-optimized DL models.

genetics↗

bioRxiv2020

Predicting future from past: The genomic basis of recurrent and rapid stickleback evolution

Similar forms often evolve repeatedly in nature, raising longstanding questions about the underlying mechanisms. Here we use repeated evolution in sticklebacks to identify a large set of genomic loci that change recurrently during colonization of new freshwater habitats by marine fish. The same loci used repeatedly in extant populations also show rapid allele frequency changes when new freshwater populations are experimentally established from marine ancestors. Dramatic genotypic and phenotypic changes arise within 5-7 years, facilitated by standing genetic variation and linkage between adaptive regions. Both the speed and location of changes can be predicted using empirical observations of recurrence in natural populations or fundamental genomic features like allelic age, recombination rates, density of divergent loci, and overlap with mapped traits. A composite model trained on these stickleback features can also predict the location of key evolutionary loci in Darwins finches, suggesting similar features are important for evolution across diverse taxa.

evolutionary biology↗