Haploid transcriptome analysis reveals allelelic gene expression variants, co-expressed gene groups, and linkages between expression and copy number variation
Bibliographic record
Abstract
Genetic variation can cause changes in gene expression (mRNA abundance) among individuals. This so-called heritable variation in gene expression is affected by genetic variants that are co-segregating with the gene locus (local/ cis effects) and/or segregating independently from it (distant/ trans effects). Genetic variation in gene expression can be measured to estimate the extant of variation in gene expression within a population, and to determine to what degree expression alleles of different genes are connected within regulatory networks. Furthermore, determining whether variation in the expression of a gene is linked to local or distant effects allows us to make inferences about how heritable variation may change depending on gene function, the number of interacting partners, genetic architecture and evolutionary history [ 1 , 2 ]. Detecting heritable variation in gene expression can be a challenging task in diploid organisms, mainly because of tissue-specificity and dominance effects of allelic expression. For example, up to 70% of gene expression alleles in Drosophila may be masked by dominance [ 3 ]. We developed an experimental system to overcome these obstacles by utilizing the conifer seed’s maternally derived haploid tissue, the megagametophyte. Analyzing a set of sibling megagametophytes allows us to first, measure separately the expression each of the two alleles in the maternal genome in the absence of dominance and second, identify genes whose expression levels are co-segregating. In addition, the megagametophyte allows us to categorize the underlying genetic variants into local or distant with a simple co-segregation assay. We set out to characterize segregating variation in gene expression in white spruce ( Picea glauca [Moench] Voss). We analyzed the transcriptomes of germinating sibling megagametophytes from two controlled-crossed families (C9412516: male 2388 x female 77111 & C9612856: male 80109 x female 80112) with a custom microarray comprised of 32,000 spotted oligonucleotides, which represent over 25,000 unique white spruce genes. Each megagametophyte was split into two halves to provide technical replicates that were analyzed separately. A separate comparison of microarray results and RNA-Seq data has been carried out to validate the quality of the microarray. The single-color microarray data was background-corrected and quantile-normalized with the R package Limma [ 4 ]. We used the R package Mclust [ 5 ] to test for unimodal vs. bimodal expression distributions of each gene across sibling megagametophytes. Genes that exhibited at least two expression alleles, which segregated within the 95% IC of their expected proportions, were selected. The segregation had to be repeatable with a replicate sample set to be considered valid.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".