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1. Evaluating the power and limitations of genome-wide association studies in Caenorhabditis elegans

   https://doi.org/10.1093/g3journal/jkac114  

   Widmayer, Samuel J; Evans, Kathryn S; Zdraljevic, Stefan; Andersen, Erik C (May 2022, G3 Genes|Genomes|Genetics)

   Macdonald, S (Ed.)

   Abstract Quantitative genetics in Caenorhabditis elegans seeks to identify naturally segregating genetic variants that underlie complex traits. Genome-wide association studies scan the genome for individual genetic variants that are significantly correlated with phenotypic variation in a population, or quantitative trait loci. Genome-wide association studies are a popular choice for quantitative genetic analyses because the quantitative trait loci that are discovered segregate in natural populations. Despite numerous successful mapping experiments, the empirical performance of genome-wide association study has not, to date, been formally evaluated in C. elegans. We developed an open-source genome-wide association study pipeline called NemaScan and used a simulation-based approach to provide benchmarks of mapping performance in collections of wild C. elegans strains. Simulated trait heritability and complexity determined the spectrum of quantitative trait loci detected by genome-wide association studies. Power to detect smaller-effect quantitative trait loci increased with the number of strains sampled from the C. elegans Natural Diversity Resource. Population structure was a major driver of variation in mapping performance, with populations shaped by recent selection exhibiting significantly lower false discovery rates than populations composed of more divergent strains. We also recapitulated previous genome-wide association studies of experimentally validated quantitative trait variants. Our simulation-based evaluation of performance provides the community with critical context to pursue quantitative genetic studies using the C. elegans Natural Diversity Resource to elucidate the genetic basis of complex traits in C. elegans natural populations. 

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2. Graph pangenome captures missing heritability and empowers tomato breeding

   https://doi.org/10.1038/s41586-022-04808-9  

   Zhou, Yao; Zhang, Zhiyang; Bao, Zhigui; Li, Hongbo; Lyu, Yaqing; Zan, Yanjun; Wu, Yaoyao; Cheng, Lin; Fang, Yuhan; Wu, Kun; et al (June 2022, Nature)

   Abstract Missing heritability in genome-wide association studies defines a major problem in genetic analyses of complex biological traits 1,2 . The solution to this problem is to identify all causal genetic variants and to measure their individual contributions 3,4 . Here we report a graph pangenome of tomato constructed by precisely cataloguing more than 19 million variants from 838 genomes, including 32 new reference-level genome assemblies. This graph pangenome was used for genome-wide association study analyses and heritability estimation of 20,323 gene-expression and metabolite traits. The average estimated trait heritability is 0.41 compared with 0.33 when using the single linear reference genome. This 24% increase in estimated heritability is largely due to resolving incomplete linkage disequilibrium through the inclusion of additional causal structural variants identified using the graph pangenome. Moreover, by resolving allelic and locus heterogeneity, structural variants improve the power to identify genetic factors underlying agronomically important traits leading to, for example, the identification of two new genes potentially contributing to soluble solid content. The newly identified structural variants will facilitate genetic improvement of tomato through both marker-assisted selection and genomic selection. Our study advances the understanding of the heritability of complex traits and demonstrates the power of the graph pangenome in crop breeding. 

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3. Many functionally connected loci foster adaptive diversification along a neotropical hybrid zone

   https://doi.org/10.1126/sciadv.abb8617  

   Lewis, James J.; Van Belleghem, Steven M.; Papa, Riccardo; Danko, Charles G.; Reed, Robert D. (September 2020, Science Advances)

   null (Ed.)

   Characterizing the genetic complexity of adaptation and trait evolution is a major emphasis of evolutionary biology and genetics. Incongruent findings from genetic studies have resulted in conceptual models ranging from a few large-effect loci to massively polygenic architectures. Here, we combine chromatin immunoprecipitation sequencing, Hi-C, RNA sequencing, and 40 whole-genome sequences from Heliconius butterflies to show that red color pattern diversification occurred via many genomic loci. We find that the red wing pattern master regulatory transcription factor Optix binds dozens of loci also under selection, which frequently form three-dimensional adaptive hubs with selection acting on multiple physically interacting genes. Many Optix-bound genes under selection are tied to pigmentation and wing development, and these loci collectively maintain separation between adaptive red color pattern phenotypes in natural populations. We propose a model of trait evolution where functional connections between loci may resolve much of the disparity between large-effect and polygenic evolutionary models. 

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4. Ultrabithorax Is a Micromanager of Hindwing Identity in Butterflies and Moths

   https://doi.org/10.3389/fevo.2021.643661  

   Tendolkar, Amruta; Pomerantz, Aaron F.; Heryanto, Christa; Shirk, Paul D.; Patel, Nipam H.; Martin, Arnaud (March 2021, Frontiers in Ecology and Evolution)

   null (Ed.)

   The forewings and hindwings of butterflies and moths (Lepidoptera) are differentiated from each other, with segment-specific morphologies and color patterns that mediate a wide range of functions in flight, signaling, and protection. The Hox gene Ultrabithorax ( Ubx ) is a master selector gene that differentiates metathoracic from mesothoracic identities across winged insects, and previous work has shown this role extends to at least some of the color patterns from the butterfly hindwing. Here we used CRISPR targeted mutagenesis to generate Ubx loss-of-function somatic mutations in two nymphalid butterflies ( Junonia coenia , Vanessa cardui ) and a pyralid moth ( Plodia interpunctella ). The resulting mosaic clones yielded hindwing-to-forewing transformations, showing Ubx is necessary for specifying many aspects of hindwing-specific identities, including scale morphologies, color patterns, and wing venation and structure. These homeotic phenotypes showed cell-autonomous, sharp transitions between mutant and non-mutant scales, except for clones that encroached into the border ocelli (eyespots) and resulted in composite and non-autonomous effects on eyespot ring determination. In the pyralid moth, homeotic clones converted the folding and depigmented hindwing into rigid and pigmented composites, affected the wing-coupling frenulum, and induced ectopic scent-scales in male androconia. These data confirm Ubx is a master selector of lepidopteran hindwing identity and suggest it acts on many gene regulatory networks involved in wing development and patterning. 

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5. Association mapping across a multitude of traits collected in diverse environments in maize

   https://doi.org/10.1093/gigascience/giac080  

   Mural, Ravi_V; Sun, Guangchao; Grzybowski, Marcin; Tross, Michael_C; Jin, Hongyu; Smith, Christine; Newton, Linsey; Andorf, Carson_M; Woodhouse, Margaret_R; Thompson, Addie_M; et al (August 2022, GigaScience)

   Abstract Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction. 

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