Genomic architecture of a genetically assimilated seasonal color pattern.
06 Nov 2020-Science (American Association for the Advancement of Science)-Vol. 370, Iss: 6517, pp 721-725
TL;DR: Endocrine assays and chromatin accessibility and conformation analyses showed that the transition of wing coloration from an environmentally determined trait to a predominantly genetic trait occurred through selection for regulatory alleles of downstream wing-patterning genes.
Abstract: Developmental plasticity allows genomes to encode multiple distinct phenotypes that can be differentially manifested in response to environmental cues. Alternative plastic phenotypes can be selected through a process called genetic assimilation, although the mechanisms are still poorly understood. We assimilated a seasonal wing color phenotype in a naturally plastic population of butterflies (Junonia coenia) and characterized three responsible genes. Endocrine assays and chromatin accessibility and conformation analyses showed that the transition of wing coloration from an environmentally determined trait to a predominantly genetic trait occurred through selection for regulatory alleles of downstream wing-patterning genes. This mode of genetic evolution is likely favored by selection because it allows tissue- and trait-specific tuning of reaction norms without affecting core cue detection or transduction mechanisms.
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TL;DR: Livraghi et al. as discussed by the authors used a DNA editing technique called CRISPR to find out whether the cortex gene affects scale type, and they confirmed that deleting cortex turned black and red scales yellow.
Abstract: Heliconius butterflies have bright patterns on their wings that tell potential predators that they are toxic. As a result, predators learn to avoid eating them. Over time, unrelated species of butterflies have evolved similar patterns to avoid predation through a process known as Mullerian mimicry. Worldwide, there are over 180,000 species of butterflies and moths, most of which have different wing patterns. How do genes create this pattern diversity? And do butterflies use similar genes to create similar wing patterns? One of the genes involved in creating wing patterns is called cortex. This gene has a large region of DNA around it that does not code for proteins, but instead, controls whether cortex is on or off in different parts of the wing. Changes in this non-coding region can act like switches, turning regions of the wing into different colours and creating complex patterns, but it is unclear how these switches have evolved. Butterfly wings get their colour from tiny structures called scales, which each have their own unique set of pigments. In Heliconius butterflies, there are three types of scales: yellow/white scales, black scales, and red/orange/brown scales. Livraghi et al. used a DNA editing technique called CRISPR to find out whether the cortex gene affects scale type. First, Livraghi et al. confirmed that deleting cortex turned black and red scales yellow. Next, they used the same technique to manipulate the non-coding DNA around the cortex gene to see the effect on the wing pattern. This manipulation turned a black-winged butterfly into a butterfly with a yellow wing band, a pattern that occurs naturally in Heliconius butterflies. The next step was to find the mutation responsible for the appearance of yellow wing bands in nature. It turns out that a bit of extra genetic code, derived from so-called ‘jumping genes’, had inserted itself into the non-coding DNA around the cortex gene, ‘flipping’ the switch and leading to the appearance of the yellow scales. Genetic information contains the instructions to generate shape and form in most organisms. These instructions evolve over millions of years, creating everything from bacteria to blue whales. Butterfly wings are visual evidence of evolution, but the way their genes create new patterns isn't specific to butterflies. Understanding wing patterns can help researchers to learn how genetic switches control diversity across other species too.
30 citations
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TL;DR: The relationship between the pigments and insect color pattern is introduced, the genes involved in the pigment synthesis, transport, and patterning are summarized, and the future progress is expected in this field.
Abstract: Insects have an amazing variety of colors and patterns. It should be noted that pigments and/or genes involved in body color formation are markedly different between insects and vertebrates. Insect pigments have been traditionally classified into the following eight classes: melanins, ommochromes, pteridines, tetrapyrroles, carotenoids, flavonoids, papiliochromes, and quinones. Among them, melanins, ommochromes, and pteridines are three major pigments that are distributed in most insects. Insect melanins are secreted into cuticles, and dark-colored melanins are predominantly derived from dopamine, whereas light-colored melanins are mostly derived from N-β-alanyldopamine (NBAD) and/or N-acetyldopamine (NADA). Ommochromes are tryptophan-derived pigments restricted to invertebrates and are ubiquitous in the compound eyes of insects. Ommochromes and pteridines are accumulated within pigment granules ommochromasomes and pterinosomes, respectively. In recent years, much has been revealed at the molecular level about pigment synthesis and pattern formation in insects. In this review, we introduce the relationship between the pigments and insect color pattern, and summarize the genes involved in the pigment synthesis, transport, and patterning. Meanwhile, there are still many insects whose pigments have not been identified, and the future progress is expected in this field.
12 citations
TL;DR: In this article, the authors present a model of ecdysone response evolution that integrates both gene regulatory architecture and organismal development, and propose a set of testable mechanistic hypotheses for how plastic response profiles of specific genes can evolve.
7 citations
TL;DR: It is concluded that cortex played key roles in the diversification of lepidopteran wing patterns in part due to its switch-like effects in scale identity across the entire wing surface.
Abstract: The wing patterns of butterflies are an excellent system with which to study phenotypic evolution. The incredibly diverse patterns are generated from an array of pigmented scales on a largely two-dimensional surface, resulting in a visibly tractable system for studying the evolution of pigmentation. In Heliconius butterflies, much of this diversity is controlled by a few genes of large effect that regulate pattern switches between races and species across a large mimetic radiation. One of these genes – cortex - has been repeatedly mapped in association with colour pattern evolution in both Heliconius and other Lepidoptera, but we lack functional data supporting its role in modulating wing patterns. Here we carried out CRISPR knock-outs in multiple Heliconius species and show that cortex is a major determinant of scale cell identity. Mutant wing clones lacking cortex showed shifts in colour identity, with melanic and red scales acquiring a yellow or white state. These homeotic transformations include changes in both pigmentation and scale ultrastructure, suggesting that cortex acts during early stages of scale cell fate specification rather than during the deployment of effector genes. In addition, mutant clones were observed across the entire wing surface, contrasting with other known Heliconius mimicry loci that act in specific patterns. Cortex is known as a cell-cycle regulator that modulates mitotic entry in Drosophila, and we found the Cortex protein to accumulate in the nuclei of the polyploid scale building cells of the butterfly wing epithelium, speculatively suggesting a connection between scale cell endocycling and colour identity. In summary, and while its molecular mode of action remains mysterious, we conclude that cortex played key roles in the diversification of lepidopteran wing patterns in part due to its switch-like effects in scale identity across the entire wing surface.
7 citations
Stockholm University1, Sacred Heart University2, George Washington University3, University of Helsinki4, Russian Academy of Sciences5, Florida Museum of Natural History6, University of Wisconsin-Madison7, University of Massachusetts Amherst8, University of South Carolina9, Rocky Mountain Biological Laboratory10
TL;DR: The findings suggest Alba has a singular origin and has been maintained in Colias through a combination of balancing selection and introgression for nearly one million years and at least as many generations.
Abstract: Alternative life-history strategies (ALHS) are genetic polymorphisms generating phenotypes differing in life histories that generally arise due to metabolic resource allocation tradeoffs. Althouigh ALHS are often be limited to a single sex or populations of a species, they can, in rare cases, be found among several species across a genus. In the butterfly genus Colias, at least a third of the species have a female limited ALHS called Alba. While many females develop brightly pigmented wings, Alba females reallocate nitrogen resources used in pigment synthesis to reproductive development, producing white-winged, more fecund females. Whether this ALHS evolved once or many times, and whether it has moved among species via introgression or been maintained via long-term balancing selection, has not been established. Answering these questions presents an opportunity to investigate the genetic basis and evolutionary forces acting upon ALHS, which have rarely been studied at a genus level. Here we identify the genetic locus of Alba in a second Colias species, allowing us to compare this with previous results in a larger phylogenetic context. Our findings suggest Alba has a singular origin and has been maintained in Colias through a combination of balancing selection and introgression for nearly one million years and at least as many generations. Finally, using CRISPR/Cas9 deletions in the cis-regulatory region of the Alba allele, we demonstrate that the Alba allele is a modular enhancer for the BarH1 gene and is necessary for the induction of the ALHS, which potentially facilitates its long-term persistence in the genus.
6 citations
Cites background from "Genomic architecture of a genetical..."
...While such mosaic phenotypes have greatly advanced the study of morphological traits (Burg et al., 2020; Perry et al., 2016; Westerman et al., 2018b), such mosaics of physiological phenotypes are nearly impossible to interpret, leaving the study of non-morphological phenotypes unable to use these…...
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TL;DR: This work introduces PLINK, an open-source C/C++ WGAS tool set, and describes the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation, which focuses on the estimation and use of identity- by-state and identity/descent information in the context of population-based whole-genome studies.
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TL;DR: The GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
Abstract: Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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TL;DR: The command-line tool cutadapt is developed, which supports 454, Illumina and SOLiD (color space) data, offers two adapter trimming algorithms, and has other useful features.
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