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1. Few Fixed Variants between Trophic Specialist Pupfish Species Reveal Candidate Cis -Regulatory Alleles Underlying Rapid Craniofacial Divergence

   https://doi.org/10.1093/molbev/msaa218  

   McGirr, Joseph A; Martin, Christopher H (September 2020, Molecular Biology and Evolution)

   Wittkopp, Patricia (Ed.)

   Abstract Investigating closely related species that rapidly evolved divergent feeding morphology is a powerful approach to identify genetic variation underlying variation in complex traits. This can also lead to the discovery of novel candidate genes influencing natural and clinical variation in human craniofacial phenotypes. We combined whole-genome resequencing of 258 individuals with 50 transcriptomes to identify candidate cis-acting genetic variation underlying rapidly evolving craniofacial phenotypes within an adaptive radiation of Cyprinodon pupfishes. This radiation consists of a dietary generalist species and two derived trophic niche specialists—a molluscivore and a scale-eating species. Despite extensive morphological divergence, these species only diverged 10 kya and produce fertile hybrids in the laboratory. Out of 9.3 million genome-wide SNPs and 80,012 structural variants, we found very few alleles fixed between species—only 157 SNPs and 87 deletions. Comparing gene expression across 38 purebred F1 offspring sampled at three early developmental stages, we identified 17 fixed variants within 10 kb of 12 genes that were highly differentially expressed between species. By measuring allele-specific expression in F1 hybrids from multiple crosses, we found that the majority of expression divergence between species was explained by trans-regulatory mechanisms. We also found strong evidence for two cis-regulatory alleles affecting expression divergence of two genes with putative effects on skeletal development (dync2li1 and pycr3). These results suggest that SNPs and structural variants contribute to the evolution of novel traits and highlight the utility of the San Salvador Island pupfish system as an evolutionary model for craniofacial development. 

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2. Trans-Acting Genotypes Associated with mRNA Expression Affect Metabolic and Thermal Tolerance Traits

   https://doi.org/10.1093/gbe/evad123  

   Drown, Melissa K; Oleksiak, Marjorie F; Crawford, Douglas L (July 2023, Genome Biology and Evolution)

   Betancourt, Andrea (Ed.)

   Abstract Evolutionary processes driving physiological trait variation depend on the underlying genomic mechanisms. Evolution of these mechanisms depends on the genetic complexity (involving many genes) and how gene expression impacting the traits is converted to phenotype. Yet, genomic mechanisms that impact physiological traits are diverse and context dependent (e.g., vary by environment and tissues), making them difficult to discern. We examine the relationships between genotype, mRNA expression, and physiological traits to discern the genetic complexity and whether the gene expression affecting the physiological traits is primarily cis- or trans-acting. We use low-coverage whole genome sequencing and heart- or brain-specific mRNA expression to identify polymorphisms directly associated with physiological traits and expressed quantitative trait loci (eQTL) indirectly associated with variation in six temperature specific physiological traits (standard metabolic rate, thermal tolerance, and four substrate specific cardiac metabolic rates). Focusing on a select set of mRNAs belonging to co-expression modules that explain up to 82% of temperature specific traits, we identified hundreds of significant eQTL for mRNA whose expression affects physiological traits. Surprisingly, most eQTL (97.4% for heart and 96.7% for brain) were trans-acting. This could be due to higher effect size of trans- versus cis-acting eQTL for mRNAs that are central to co-expression modules. That is, we may have enhanced the identification of trans-acting factors by looking for single nucleotide polymorphisms associated with mRNAs in co-expression modules that broadly influence gene expression patterns. Overall, these data indicate that the genomic mechanism driving physiological variation across environments is driven by trans-acting heart- or brain-specific mRNA expression. 

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3. Learning gene networks under SNP perturbation using SNP and allele-specific expression data

   https://doi.org/10.1101/2023.10.23.563661  

   Yoon, Jun Ho; Kim, Seyoung (October 2023, bioRxiv)

   Abstract Allele-specific expression quantification from RNA-seq reads provides opportunities to study the control of gene regulatory networks bycis-acting andtrans-acting genetic variants. Many existing methods performed a single-gene and single-SNP association analysis to identify expression quantitative trait loci (eQTLs), and placed the eQTLs against known gene networks for functional interpretation. Instead, we view eQTL data as a capture of the effects of perturbation of gene regulatory system by a large number of genetic variants and reconstruct a gene network perturbed by eQTLs. We introduce a statistical framework called CiTruss for simultaneously learning a gene network andcis-acting andtrans-acting eQTLs that perturb this network, given population allele-specific expression and SNP data. CiTruss uses a multi-level conditional Gaussian graphical model to modeltrans-acting eQTLs perturbing the expression of both alleles in gene network at the top level andcis-acting eQTLs perturbing the expression of each allele at the bottom level. We derive a transformation of this model that allows efficient learning for large-scale human data. Our analysis of the GTEx and LG×SM advanced intercross line mouse data for multiple tissue types with CiTruss provides new insights into genetics of gene regulation. CiTruss revealed that gene networks consist of local subnetworks over proximally located genes and global subnetworks over genes scattered across genome, and that several aspects of gene regulation by eQTLs such as the impact of genetic diversity, pleiotropy, tissue-specific gene regulation, and local and long-range linkage disequilibrium among eQTLs can be explained through these local and global subnetworks. 

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4. Quantifying the Evolution of SNPs That Affect RNA Secondary Structure in Arabidopsis thaliana Genes

   https://doi.org/10.1093/molbev/msaf126  

   Martin, Galen_T; Fiscus, Christopher_J; Gaut, Brandon_S; Josephs, ed., Emily (June 2025, Molecular Biology and Evolution)

   Abstract Single-stranded RNA molecules can form intramolecular bonds between nucleotides to create secondary structures. These structures can have phenotypic effects, meaning mutations that alter secondary structure may be subject to natural selection. Here, we examined the population genetics of these mutations within Arabidopsis thaliana genes. We began by identifying derived SNPs with the potential to alter secondary structures within coding regions, using a combination of computational prediction and empirical data analysis. We identified 8,469 such polymorphisms, representing a small portion (∼0.024%) of sites within transcribed genes. We examined nucleotide diversity and allele frequencies of these “pair-changing mutations” (pcM) in 1,001 A. thaliana genomes. The pcM SNPs at synonymous sites had a 13.4% reduction in nucleotide diversity relative to non-pcM SNPs at synonymous sites and were found at lower allele frequencies. We used demographic modeling to estimate selection coefficients, finding selection against pcMs in 5′ and 3′ untranslated regions. Previous work has shown that some pcMs affect gene expression in a temperature-dependent matter. We explored associations on a genome-wide scale, finding that pcMs existed at higher population frequencies in colder environments, but so did non-PCM alleles. Derived pcM mutations had a small but significant relationship with gene expression; transcript abundance for pcM-containing alleles had an average reduction in expression of ∼4% relative to alleles with conserved ancestral secondary structure. Overall, we document selection against derived pcMs in untranslated regions but find limited evidence for selection against derived pcMs at synonymous sites. 

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5. The quantitative genetics of gene expression in Mimulus guttatus

   https://doi.org/10.1371/journal.pgen.1011072  

   Veltsos, Paris; Kelly, John K. (April 2024, PLOS Genetics)

   Lasky, Jesse R. (Ed.)

   Gene expression can be influenced by genetic variants that are closely linked to the expressed gene (cis eQTLs) and variants in other parts of the genome (trans eQTLs). We created a multiparental mapping population by sampling genotypes from a single natural population ofMimulus guttatusand scored gene expression in the leaves of 1,588 plants. We find that nearly every measured gene exhibits cis regulatory variation (91% have FDR < 0.05). cis eQTLs are usually allelic series with three or more functionally distinct alleles. The cis locus explains about two thirds of the standing genetic variance (on average) but varies among genes and tends to be greatest when there is high indel variation in the upstream regulatory region and high nucleotide diversity in the coding sequence. Despite mapping over 10,000 trans eQTL / affected gene pairs, most of the genetic variance generated by trans acting loci remains unexplained. This implies a large reservoir of trans acting genes with subtle or diffuse effects. Mapped trans eQTLs show lower allelic diversity but much higher genetic dominance than cis eQTLs. Several analyses also indicate that trans eQTLs make a substantial contribution to the genetic correlations in expression among different genes. They may thus be essential determinants of “gene expression modules,” which has important implications for the evolution of gene expression and how it is studied by geneticists. 

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