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"Nichols, Richard"
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Estimating the Number of Subpopulations ( K ) in Structured Populations
A key quantity in the analysis of structured populations is the parameter K, which describes the number of subpopulations that make up the total population. Inference of K ideally proceeds via the model evidence, which is equivalent to the likelihood of the model. However, the evidence in favor of a particular value of K cannot usually be computed exactly, and instead programs such as Structure make use of heuristic estimators to approximate this quantity. We show—using simulated data sets small enough that the true evidence can be computed exactly—that these heuristics often fail to estimate the true evidence and that this can lead to incorrect conclusions about K. Our proposed solution is to use thermodynamic integration (TI) to estimate the model evidence. After outlining the TI methodology we demonstrate the effectiveness of this approach, using a range of simulated data sets. We find that TI can be used to obtain estimates of the model evidence that are more accurate and precise than those based on heuristics. Furthermore, estimates of K based on these values are found to be more reliable than those based on a suite of model comparison statistics. Finally, we test our solution in a reanalysis of a white-footed mouse data set. The TI methodology is implemented for models both with and without admixture in the software MavericK1.0.
Journal Article
The Punisher Invades the 'Nam
Years before he brought his personal war to the mean streets of the Marvel Universe, Marine Sgt. Frank Castle fought in Vietnam - and the man he would become took shape in those killing fields. Revisit the horrors of the 'Nam along with Frank as he battles side-by-side with comrade-in-arms Mike \"Ice\" Phillips and faces down a deadly jungle sniper, and fights alone in his final tour of duty to rescue a crew of downed airmen from a sadistic vivisectionists. Plus: Years later, Ice comes to the aid of his fellow veteran - but can the tow of them take down the paramilitary group the Sons of Liberty and a Central American drug kingpin?
Book
Genomic Prediction of Testcross Performance in Canola (Brassica napus)
Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable potential for pre-selection of promising hybrid combinations prior to resource-intensive field testing over multiple locations and years.
Journal Article
Genome size and ploidy influence angiosperm species' biomass under nitrogen and phosphorus limitation
Angiosperm genome sizes (GS) range c. 2400-fold, and as nucleic acids are amongst the most phosphorus- (P) and nitrogen (N)-demanding cellular biomolecules, we test the hypothesis that a key influence on plant biomass and species composition is the interaction between N and P availability and plant GS.
We analysed the impact of different nutrient regimes on above-ground biomass of angiosperm species with different GS, ploidy level and Grime's C-S-R (competitive, stresstolerant, ruderal) plant strategies growing at the Park Grass Experiment (Rothamsted, UK), established in 1856.
The biomass-weighted mean GS of species growing on plots with the addition of both N and P fertilizer were significantly higher than that of plants growing on control plots and plots with either N or P. The plants on these N + P plots are dominated by polyploids with large GS and a competitive plant strategy.
The results are consistent with our hypothesis that large genomes are costly to build and maintain under N and P limitation. Hence GS and ploidy are significant traits affecting biomass growth under different nutrient regimes, influencing plant community composition and ecosystem dynamics. We propose that GS is a critical factor needed in models that bridge the knowledge gap between biodiversity and ecosystem functioning.
Journal Article
Genomic assessment of local adaptation in dwarf birch to inform assisted gene flow
When populations of a rare species are small, isolated and declining under climate change, some populations may become locally maladapted. Detecting this maladaptation may allow effective rapid conservation interventions, even if based on incomplete knowledge. Population maladaptation may be estimated by finding genome–environment associations (GEA) between allele frequencies and environmental variables across a local species range, and identifying populations whose allele frequencies do not fit with these trends. We can then design assisted gene flow strategies for maladapted populations, to adjust their allele frequencies, entailing lower levels of intervention than with undirected conservation action. Here, we investigate this strategy in Scottish populations of the montane plant dwarf birch (Betula nana). In genome‐wide restriction site‐associated single nucleotide polymorphism (SNP) data, we found 267 significant associations between SNP loci and environmental variables. We ranked populations by maladaptation estimated using allele frequency deviation from the general trends at these loci; this gave a different prioritization for conservation action than the Shapely Index, which seeks to preserve rare neutral variation. Populations estimated to be maladapted in their allele frequencies at loci associated with annual mean temperature were found to have reduced catkin production. Using an environmental niche modelling (ENM) approach, we found annual mean temperature (35%), and mean diurnal range (15%), to be important predictors of the dwarf birch distribution. Intriguingly, there was a significant correlation between the number of loci associated with each environmental variable in the GEA and the importance of that variable in the ENM. Together, these results suggest that the same environmental variables determine both adaptive genetic variation and species range in Scottish dwarf birch. We suggest an assisted gene flow strategy that aims to maximize the local adaptation of dwarf birch populations under climate change by matching allele frequencies to current and future environments.
Journal Article
Transition-Transversion Bias Is Not Universal: A Counter Example from Grasshopper Pseudogenes
Comparisons of the DNA sequences of metazoa show an excess of transitional over transversional substitutions. Part of this bias is due to the relatively high rate of mutation of methylated cytosines to thymine. Postmutation processes also introduce a bias, particularly selection for codon-usage bias in coding regions. It is generally assumed, however, that there is a universal bias in favour of transitions over transversions, possibly as a result of the underlying chemistry of mutation. Surprisingly, this underlying trend has been evaluated only in two types of metazoan, namely Drosophila and the Mammalia. Here, we investigate a third group, and find no such bias. We characterize the point substitution spectrum in Podisma pedestris, a grasshopper species with a very large genome. The accumulation of mutations was surveyed in two pseudogene families, nuclear mitochondrial and ribosomal DNA sequences. The cytosine-guanine (CpG) dinucleotides exhibit the high transition frequencies expected of methylated sites. The transition rate at other cytosine residues is significantly lower. After accounting for this methylation effect, there is no significant difference between transition and transversion rates. These results contrast with reports from other taxa and lead us to reject the hypothesis of a universal transition/transversion bias. Instead we suggest fundamental interspecific differences in point substitution processes.
Journal Article
Non-uniform upregulation of the autogenic stretch reflex among hindlimb extensors following lateral spinal lesion in the cat
Successful propagation throughout the step cycle is contingent on adequate regulation of whole-limb stiffness by proprioceptive feedback. Following spinal cord injury (SCI), there are changes in the strength and organization of proprioceptive feedback that can result in altered joint stiffness. In this study, we measured changes in autogenic feedback of five hindlimb extensor muscles following chronic low thoracic lateral hemisection (LSH) in decerebrate cats. We present three features of the autogenic stretch reflex obtained using a mechanographic method. Stiffness was a measure of the resistance to stretch during the length change. The dynamic index documented the extent of adaptation or increase of the force response during the hold phase, and the impulse measured the integral of the response from initiation of a stretch to the return to the initial length. The changes took the form of variable and transient increases in the stiffness of vastus (VASTI) group, soleus (SOL), and flexor hallucis longus (FHL), and either increased (VASTI) or decreased adaptation (GAS and PLANT). The stiffness of the gastrocnemius group (GAS) was also variable over time but remained elevated at the final time point. An unexpected finding was that these effects were observed bilaterally. Potential reasons for this finding and possible sources of increased excitability to this muscle group are discussed.
Journal Article
Independent, Rapid and Targeted Loss of Highly Repetitive DNA in Natural and Synthetic Allopolyploids of Nicotiana tabacum
Allopolyploidy (interspecific hybridisation and polyploidy) has played a significant role in the evolutionary history of angiosperms and can result in genomic, epigenetic and transcriptomic perturbations. We examine the immediate effects of allopolyploidy on repetitive DNA by comparing the genomes of synthetic and natural Nicotiana tabacum with diploid progenitors N. tomentosiformis (paternal progenitor) and N. sylvestris (maternal progenitor). Using next generation sequencing, a recently developed graph-based repeat identification pipeline, Southern blot and fluorescence in situ hybridisation (FISH) we characterise two highly repetitive DNA sequences (NicCL3 and NicCL7/30). Analysis of two independent high-throughput DNA sequencing datasets indicates NicCL3 forms 1.6-1.9% of the genome in N. tomentosiformis, sequences that occur in multiple, discontinuous tandem arrays scattered over several chromosomes. Abundance estimates, based on sequencing depth, indicate NicCL3 is almost absent in N. sylvestris and has been dramatically reduced in copy number in the allopolyploid N. tabacum. Surprisingly elimination of NicCL3 is repeated in some synthetic lines of N. tabacum in their forth generation. The retroelement NicCL7/30, which occurs interspersed with NicCL3, is also under-represented but to a much lesser degree, revealing targeted elimination of the latter. Analysis of paired-end sequencing data indicates the tandem component of NicCL3 has been preferentially removed in natural N. tabacum, increasing the proportion of the dispersed component. This occurs across multiple blocks of discontinuous repeats and based on the distribution of nucleotide similarity among NicCL3 units, was concurrent with rounds of sequence homogenisation.
Journal Article
Quantitative measurement of phenotype dynamics during cancer drug resistance evolution using genetic barcoding
Cancer treatment frequently fails due to the evolution of drug-resistant cell phenotypes driven by genetic or non-genetic changes. The origin, timing, and rate of spread of these adaptations are critical for understanding drug resistance mechanisms but remain challenging to observe directly. We present a mathematical framework to infer drug resistance dynamics from genetic lineage tracing and population size data without direct measurement of resistance phenotypes. Simulation experiments demonstrate that the framework accurately recovers ground-truth evolutionary dynamics. Experimental evolution to 5-Fu chemotherapy in colorectal cancer cell lines SW620 and HCT116 validates the framework. In SW620 cells, a stable pre-existing resistant subpopulation was inferred, whereas in HCT116 cells, resistance emerged through phenotypic switching into a slow-growing resistant state with stochastic progression to full resistance. Functional assays, including scRNA-seq and scDNA-seq, validate these distinct evolutionary routes. This framework facilitates rapid characterisation of resistance mechanisms across diverse experimental settings.
Understanding the dynamics of how drug resistance originates in cancer remains crucial, but it is not possible to observe them directly. Here, the authors construct a mathematical framework to infer drug resistance dynamics in cancer using lineage tracing and population size data, which is confirmed with experimental evidence and single-cell sequencing.
Journal Article