Understanding the genetic basis of natural phenotypic variation is of great importance, particularly since selection can act on this variation to cause evolution. We examined expression and allelic variation in candidate flowering time loci in
Multiple Loci Control Eyespot Number Variation on the Hindwings of Bicyclus anynana Butterflies
The underlying genetic changes that regulate the appearance and disappearance of repeated traits, or serial homologs, remain poorly understood. One hypothesis is that variation in genomic regions flanking master regulatory genes, also known as input–output genes, controls variation in trait number, making the locus of evolution almost predictable. Another hypothesis implicates genetic variation in up- or downstream loci of master control genes. Here, we use the butterfly Bicyclus anynana , a species that exhibits natural variation in eyespot number on the dorsal hindwing, to test these two hypotheses. We first estimated the heritability of dorsal hindwing eyespot number by breeding multiple butterfly families differing in eyespot number and regressing eyespot numbers of offspring on midparent values. We then estimated the number and identity of independent genetic loci contributing to eyespot number variation by performing a genome-wide association study with restriction site-associated DNA sequencing from multiple individuals varying in number of eyespots sampled across a freely breeding laboratory population. We found that dorsal hindwing eyespot number has a moderately high heritability of ∼0.50 and is characterized by a polygenic architecture. Previously identified genomic regions involved in eyespot development, and novel ones, display high association with dorsal hindwing eyespot number, suggesting that homolog number variation is likely determined by regulatory changes at multiple loci that build the trait, and not by variation at single master regulators or input–output genes.
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- Award ID(s):
- 1656389
- NSF-PAR ID:
- 10171233
- Date Published:
- Journal Name:
- Genetics
- Volume:
- 214
- Issue:
- 4
- ISSN:
- 0016-6731
- Page Range / eLocation ID:
- 1059 to 1078
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Accelerating biomass improvement is a major goal of
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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.more » « less
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1534/genetics.120.303059
