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Record W2799440651 · doi:10.1371/journal.pgen.1007249

A less selfish view of genome size evolution in maize

2018· letter· en· W2799440651 on OpenAlexafffund
Julia M. Kreiner, Stephen Wright

Bibliographic record

VenuePLoS Genetics · 2018
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyGenomeEvolutionary biologyGeneticsGenome sizeComputational biologyGene

Abstract

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Genome size varies by many orders of magnitude across plants and animals, but resolving the most important evolutionary forces driving this variation remains challenging.Since eukaryotic genome size variation is not associated with complexity, genetic drift of the amount of noncoding DNA could dominate, implicating population and species history as key drivers of shifts in DNA content.Alternatively, directional selection could be acting on DNA content, but if so, it has not been resolved which level of selection is most important.Since the predominant component of many eukaryotic genomes is comprised of selfish genetic elements such as transposable elements (TEs) and regions subject to meiotic drive, factors that influence their differential success across populations and species could account for much of the variation in genome size.However, DNA content can also have important effects on organismal phenotype that could be under directional selection.Genome size may often be an important determinant of cell size and division rate and the subject of selection via its effects on developmental and metabolic phenotypes [1,2].Supporting this view, correlations of genome size with invasive potential and growth rate [3], regional abundance and seed size [4], and even metabolic intensity in flying birds [5], may suggest an adaptive role.In this issue, Bilinski et al. [6] present evidence for this organismal adaptation view of genome size evolution by providing an explicit test for natural selection on genome size and repeat abundance across multiple altitudinal clines in maize and its wild relatives and identifying the underlying physiological mechanism.Bilinski et al.[6] capitalize on the remarkable genome size variation in maize and its wild relatives, which differ by 40%-70% within and between subspecies.It is estimated that 85% of the maize genome is composed of TEs, B chromosomes, and heterochromatic knobs subject to meiotic drive [7,8], highlighting the success of selfish genetic elements in this lineage.Nevertheless, clines of genome size along with phenotypic and environmental variables in Zea mays spp.have been well described, with a number of studies showing evidence of genome reductions, including the loss of knobs and B chromosomes, in regions of high altitude and latitude [9][10][11][12][13].While these parallel clines are suggestive of an adaptive process, it has been difficult to definitively demonstrate this and fully reject a role for neutral population history.Bilinski et al. [6] add to this rich literature by using a quantitative genetics framework to conduct a test of local adaptation, recognizing that genome size is a trait governed by an immense number of small-effect loci.Moreover, it can be thought of as a quantitative trait under complete genetic control, since the variation in genome size is expected to be a simple function of the net number of insertion and deletion alleles individuals have across the genome.Under this framework, a neutral model predicts that genome size differences across a geographic region are a function of the relatedness and population structure [14] and thus determined by the extent of correlated allele frequencies between a given pair of individuals.It follows that if genome size is subject to selection, it should be more strongly correlated with

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.007
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.207
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2018
Admission routes2
Has abstractyes

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