Agricultural environments have long presented an opportunity to study evolution in action, and genomic approaches are opening doors for testing hypotheses about adaptation to crops, pesticides, and fertilizers. Here, we begin to develop the cabbage white butterfly (Pieris rapae) as a system to test questions about adaptation to novel, agricultural environments. We focus on a population in the north central United States as a unique case study: here, canola, a host plant, has been grown during the entire flight period of the butterfly over the last three decades.
First, we show that the agricultural population has diverged phenotypically relative to a nonagricultural population: when reared on a host plant distantly related to canola, the agricultural population is smaller and more likely to go into diapause than the nonagricultural population. Second, drawing from deep sequencing runs from six individuals from the agricultural population, we assembled the gut transcriptome of this population. Then, we sequenced RNA transcripts from the midguts of 96 individuals from this canola agricultural population and the nonagricultural population in order to describe patterns of genomic divergence between the two. While population divergence is low, 235 genes show evidence of significant differentiation between populations. These genes are significantly enriched for cofactor and small molecule metabolic processes, and many genes also have transporter or catalytic activity. Analyses of population structure suggest the agricultural population contains a subset of the genetic variation in the nonagricultural population.
Taken together, our results suggest that adaptation of cabbage whites to an agricultural environment occurred at least in part through selection on standing genetic variation. Both the phenotypic and genetic data are consistent with the idea that this pest has adapted to an abundant and predictable agricultural resource through a narrowing of niche breadth and loss of genetic variants rather than de novo gain of adaptive alleles. The present research develops genomic resources to pave the way for future studies using cabbage whites as a model contributing to our understanding of adaptation to agricultural environments.
Agricultural environments have long provided an opportunity to study evolution in action [1,2,3], whether through adaptation to pesticides [4,5,6] or adaptation of pests to specific crops [7,8,9]. In some cases, agricultural environments may even result in diversification [10] or unique evolutionary dynamics in pests, because crop resources are incredibly abundant and homogenous relative to wild populations of resources [11,12,13]. Genomic tools are facilitating novel approaches to testing hypotheses about evolutionary responses of populations to agriculture [14,15,16,17]. For instance, genomic studies in aphids have shown changes in copy number, symbionts, and gene expression associated with specific crops and insecticides [18,19,20,21]. However, there have been calls to study more diverse systems in order to test a range of hypotheses about pest evolution [14].
Here, we begin to develop the cabbage white butterfly (Pieridae: Pieris rapae) as a new system to test questions about adaptation to agricultural environments. The cabbage white butterfly uses plants in the family Brassicaceae as hosts, which includes many cultivated species such as cabbage, canola, and radish. Thus, they are often important pests, especially for organic farmers [22,23,24]. Cabbage whites and their close relatives are well studied with respect to behavioral, physiological, and morphological plasticity [25,26,27,28,29,30,31,32], making them a great system to explore the relatively untested role of plasticity in the colonization of agricultural environments [14]. In the present study, we focus on the hypothesis that adaptation to a novel agricultural environment occurs at least in part through selection on standing genetic variation, resulting in a subsampling of the ancestral population. Similar to other genetic studies of adaptations of pests to agricultural environments [20, 33,34,35], we predict that the more recent agricultural population will show lower genetic diversity, as well as some population structure and divergence despite continued gene flow.
To test these predictions, we are studying a unique population of cabbage white butterflies that is associated with intensive canola agriculture. Northern North Dakota, southern Manitoba and Saskatchewan have been extensively farmed for canola since the late 1970s and early 1980s. In the last decade, the northeastern region of North Dakota often plants over half a million acres of canola annually [36]. Cabbage whites in this area feed on canola crops as both a larval host and adult nectar plant, especially since pesticide application is minimal and, when it does occur, is limited to early in the season when butterfly numbers are low [37]. From the perspective of pest adaptation to agriculture, this region is truly unique because in other regions of North America, Brassicaceae agriculture tends to be limited to cool seasons, whereas in North Dakota, canola is available throughout most of the flight period of cabbage white butterflies. This represents an abundant, predictable and high nutrient resource. Indeed, in some areas in the late summer, we have estimated adult butterfly density at over 150,000 individuals per hectare. Relative to other pest systems, this represents a case where an agricultural population may be adapting to a high nutrient and abundant resource without going through major pesticide-induced bottlenecks.
In contrast to this agricultural population, most populations of cabbage whites make use of many wild native and non-native mustards, in addition to using hosts in gardens, roadsides, ditches and other disturbed areas. This represents a unique opportunity to study adaptations to agricultural environments, as one can study both the agriculture-associated population and a nonagricultural population that is probably representative of the ancestral condition (found in St. Paul, Minnesota, approximately 430 miles away). Thus, at the landscape level, there is a clear mosaic of resource predictability that is likely shaping pest adaptation despite ongoing gene flow [33]. In particular, the relative homogeneity and predictability of the agricultural area should, over time, favor increased specialization and associated loss of plasticity related to the use of a range of host plants. In this research, we first describe phenotypic differences between the populations, comparing development time and adult body size of each population when reared in the lab on hosts varying in relatedness to canola. Then, we begin to develop genomic tools for comparing this unique agricultural population to nonagricultural populations. After assembling the gut transcriptome of this population, we compare patterns of differentiation in coding sequences between the two populations. We expected to find genetic differentiation between populations at both the phenotypic and genomic levels.
White butterflies hold a special place in the insect world with their delicate beauty and graceful flight. These winged creations come in a dazzling array of shapes and sizes each adapted to different environments across the globe. By taking a closer look at some of the most common types of white butterflies we can better appreciate nature’s artistry.
A Diverse Family
There are over 160 species of white butterflies found in the United States alone. They can be broadly categorized into 3 main families – the Whites and Sulphurs (Pieridae) the Metalmarks (Riodinidae) and the Gossamer-Winged Butterflies (Lycaenidae).
The Pieridae family includes the Cabbage White, Checkered White, Falcate Orangetip and Pine White With their predominantly white wings offset by black speckles and orange, yellow or grey patterns, these butterflies are a familiar sight in backyards and gardens across North America
The Riodinidae family contains the smaller but no less mesmerizing species like the Avalon Scrub-Hairstreak and the Bernardino Blue. Their wings flash iridescent blues and oranges, making them living jewels.
Finally, the Lycaenidae family includes the luminous Azures, Blues and Hairstreaks. From the stark brilliance of the Chiricahua White to the electric blue of the Greenish Blue, these butterflies dazzle the eye.
Feeding and Behavior
Though visually diverse, white butterflies share some common traits. As adults, they live on liquid nectar from flowers like thistles, clovers and lilacs. Their caterpillars, however, prefer dining on cruciferous plants like cabbages and mustards. This can make some of them crop pests, like the notorious Cabbage White.
These insects are generally active during the day, flying low among vegetation as they search for food and mates. Species like the Sara Orangetip and Pine White inhabit woodlands and forests, while the Falcate Orangetip and Western White prefer open prairies and fields. Some whites are migratory, travelling large territories seasonally in search of ideal conditions.
Life Stages
The life cycle of white butterflies contains four main stages – egg, larva or caterpillar, pupa and adult. The eggs are laid singly on suitable host plants. Upon hatching, the caterpillars immediately begin feeding on the leaves. As they grow, they molt or shed their exoskeletons several times.
When fully developed, the caterpillar forms the pupa or chrysalis phase. This is a protective shell within which the larva transforms into the winged adult. Upon emerging from the chrysalis, the adult butterfly is ready to continue the breeding cycle.
Conservation Concerns
Though most white butterfly species are still common, some face conservation issues. The Mustard White is threatened by invasive toxic plants that are dangerous to its caterpillars. Urbanization and pesticides also endanger populations of the Karner Blue and the Bernardino Blue. Public education and responsible gardening practices can give these lovely creatures a fighting chance.
By taking time to observe and learn about white butterflies, we foster a respect for the natural world. Something as fleeting as a fluttering white wing can connect us to nature’s fragile beauty. If you’re lucky enough to have whites in your garden, put down that bug spray bottle and take a moment to appreciate life’s small wonders.
Population performance on different hosts
We raised caterpillars from both the agricultural (herein referred to as ND) and nonagricultural (MN) populations under controlled conditions to contrast the performance of the two populations on hosts varying in relatedness to canola. “Canola” represents several different cultivars of three Brassica species—Brassica napus, B. rapa, and B. juncea. Most varieties in North Dakota are B. napus, but B. rapa is also grown [37]. We used Brassica rapa (var. chinensis) as our host approximating “canola” because canola varieties performed poorly in our greenhouse trials and were too stunted to support normal larval growth. We compared caterpillar performance on Brassica to that on Raphanus sativus (radish), both purchased as organic produce. Raphanus has a different profile of chemical defenses than the genus Brassica (glucosinolates, [38]), but is still a commonly used host in the MN population in either community gardens or as feral radish. We predicted the ND population would perform relatively better on the Brassica host than on Raphanus, as the former is more closely related to canola.
Using general linear models that controlled for sex (Table 1), there were significant population-by-host interactions for both wing length (P = 0.006) and wing area (P = 0.009) as well as a marginally significant interaction for development time (P = 0.065). For both measures of body size, the ND population was significantly smaller than the MN population when raised on Raphanus, the host more distantly related to canola (Fig. 1). For development time, both populations developed more slowly on radish (Fig. 1), and females developed more quickly than males (Table 1, Additional file 1). Contrary to expectations, the MN population had significantly faster development time on the Brassica host, relative to the ND population (Fig. 1). However, the difference in development time is rather small—shifting from about 21 to 22 days—and unlikely to have a meaningful impact on fitness, especially compared to other factors. Given the extreme temperature dependence of development time, it’s also possible this trait is not the best performance measure for comparing these populations, especially given climate differences between the sites. The populations were reared simultaneously in the same climate chamber, in replicate and interspersed cups, so it is unlikely that temperature fluctuations during rearing could account for the observed difference in development time. Taken together, these results suggest that the nonagricultural (MN) population does indeed have a broader host breadth than the agricultural (ND) population, out-performing them on some metrics on host plants less closely related to canola.
Differences in performance metrics for the nonagricultural (purple) and agricultural (green) populations when raised on different plant hosts. *Significant phenotypic differences between populations from a general linear model (P < 0.05)
After describing these initial differences in performance between the two populations, we performed a second, more extensive common garden experiment where we additionally harvested gut tissue for measures of gene expression (see below). In this experiment, we were prevented from doing additional phenotypic comparisons between populations because individuals from the agricultural population were more likely to go into diapause as pupae regardless of diet (80.15% from ND vs. 0% from MN, N = 258, Χ2 = 215.9, P < 0.0001). This suggests additional genetic differentiation between the populations – the agricultural population from northern North Dakota may have a different threshold of diapause induction due to the shorter growing season relative to southern Minnesota or the harvesting of canola in mid-August. Comparing agricultural and nonagricultural populations at the same latitude would help to distinguish these two hypotheses. While this population difference in diapause induction may represent an adaptation to abiotic conditions rather than an adaptation to an agricultural environment per se, it still represents a significant difference between the two populations in a common garden.
Our controlled laboratory experiments suggest significant phenotypic differentiation in fitness proxies between these agricultural (ND) and nonagricultural (MN) populations of cabbage whites on the two hosts. Most striking is the reduced body size observed in the ND population when raised on the nonagricultural host plant, which suggests that the ND population has a reduced capability to utilize suitable host plants outside of the genus Brassica. Such changes are likely associated with genetic differentiation in genes related to larval feeding. Future experiments comparing the niche breadth of these two populations would be strengthened by including North Dakota canola varieties and a range of other host plants. Given our struggles growing high quality canola in greenhouse conditions, this would likely be best accomplished with organic agricultural plots of a range of host plants, with leaves harvested daily for lab rearing in common climatic conditions.
There are currently limited genomic resources for Pieris rapae to facilitate studies that investigate the genetic basis of the adaptation to specific host plants, such as we observe in the agricultural population. Although transcriptome assemblies have recently been completed for Pieris rapae [39, 40], these studies had limited representation of the caterpillar stages and tissues that are relevant to address the hypothesis that changes in gene expression in the gut contribute to adaptation to agricultural environments. To address this limitation, we set out to more fully characterize the transcriptome in the digestive tract of Pieris rapae caterpillars.
To do this, we collected gut tissue from 6 descendants of butterflies collected from the ND population reared on either Brassica or Raphanus. We chose to focus on a single population in order to minimize the genetic variability, thus simplifying the transcriptome assembly. Of these, four caterpillars were collected at the 5th instar stage, and two were collected as 2nd instars. In addition, for one of the 5th instar larvae, we also sequenced RNA from the fat body, a tissue that also plays a critical role in insect metabolism and energy storage [41]. All samples were sequenced in a single lane of an Illumina HiSeq2000. A summary of the combined sequencing results is presented in Table 2.
We assembled high-quality sequencing reads using the Trinity transcriptome assembly platform [42, 43]. After filtering small and fragmented contigs, and removing genes that matched plant or bacterial contaminants, the resulting assembly contained 31,624 contigs (i.e. transcripts) from 17,595 unique clusters (unigenes). From each transcript cluster, we selected the contig with the longest predicted open reading frame (ORF) to represent the consensus sequence of the unigene. Unless otherwise noted, all analyses were performed on the set of consensus unigene sequences, to minimize the probability that a given gene was represented multiple times in each statistic. The characteristics of the final transcriptome assembly are summarized in Table 2.
The final unigene sequences were compared against the arthropod Benchmarking Universal Single-Copy Orthologues (BUSCO) [44]. The arthropod BUSCOs are a set of 2675 proteins that are expected to be present as a single-copy gene in all arthropod species, and can be used as a benchmark for assessing the completeness of a gene set. A significant fraction (21.0%) of BUSCO genes were not found among the Pieris rapae unigenes, likely because our transcriptome was assembled from a narrow range of tissues and stages. Of the BUSCOs that were matched to assembled unigenes, the majority were found in a single copy, and most recovered the complete protein sequence (Table 2). Thus, despite using a limited set of tissues and developmental stages, we have nevertheless assembled a high quality transcriptome that covers a significant fraction of the expected genes in Pieris rapae.
Most of the assembled transcripts show significant sequence similarity to existing protein databases (Table 3), indicative of the high quality of our final assembled transcripts. Of the representative sequences selected for each unigene, 11,049 (62.8%) showed significant sequence similarity (BLASTx, E value < 10-5) to the silk moth (Bombyx mori) protein database. Similarly, a majority of unigenes (70.2%) showed significant similarity to proteins in the NCBI non-redundant (nr) protein database (BLASTx, E value < 10-5). Fewer (51.3%) matched Drosophila proteins, likely due to the longer divergence time from Lepidoptera. Nearly half of the assembled sequences matched entries in the high-quality, manually curated Swiss-Prot protein database [45].
Using the significant hits to the nr protein database, we used the functional mapping software Blast2GO [46,47,48] to assign gene ontology (GO) terms from the generic GO-Slim dictionary [49, 50] to the unigenes in our Pieris rapae transcriptome. In all, 7464 unigenes (42.4%) were successfully annotated with at least 1 GO term using default parameters for annotating GO matches. As expected, we saw many genes mapping to biological process terms such as carbohydrate metabolic process (215 unigenes), lipid metabolic process (194), or more generally to biosynthetic process (832 unigenes) (Additional file 2). Other key functions of the gut, including transport (269), response to stress (225), immune system function (59), and homeostatic processes (80), were also represented in the expressed genes. The molecular function term with the highest representation in our transcriptome was ion binding (2092), followed by oxidoreductase activity (506).
We also used BlastKOALA [51] to assign our genes to pathways in the KEGG ontology [52, 53]. 4554 unigenes (25.9%) could be assigned to KEGG pathways (Fig. 2; Table 3). Many genes were annotated as belonging to at least one of the major metabolic pathways, including carbohydrate, lipid, and amino acid metabolism. The largest KEGG category was the signal transduction proteins, of which we annotated 527 genes. Notably, we identified components of several organismal system pathways, including digestive and excretory systems, immune system, and development, which we expect to be expressed in gut tissue or at early developmental stages.
Number of annotated unigenes assigned to major KEGG ontologies from the Pieris rapae transcriptome
Variant discovery and annotation
Demultiplexed sequence reads from the 96 samples used to examine population divergence were cleaned and trimmed as described above. Reads were then aligned to the Pieris rapae gut transcriptome assembly with bowtie2 [85] with the “sensitive” preset parameter options. To simplify the downstream analysis, only the representative consensus sequence for each unigene was used as reference for the alignment.
We performed SNP and indel discovery and genotyping across all 96 samples simultaneously with the Genome Analysis Toolkit (GATK; [94]) using hard filtering parameters appropriate for RNA-seq data. Prior to variant discovery, reads in regions identified as possible indels were realigned according to GATK Best Practices recommendations [95, 96]. Because the distribution of RNA-seq reads does not match the expectation of genome wide sequence reads, we chose not to filter reads tagged as duplicates. However, the SNP sets obtained with and without the duplicate read filter were very similar—87.4% of the SNPs we identified in our data were also present when the duplicate reads were removed.
Genetic variants were identified using GATK HaplotypeCaller. The minimum phred-scaled confidence threshold for calling and emitting variants was set to 20. We chose to focus on biallelic SNPs, since calling indels may be complicated by differential splicing patterns in genes, especially given that we are only focusing on a single representative transcript for each potential unigene. We filtered called biallelic SNPs using the following criteria based on current recommendations from GATK’s Best Practices recommendations for RNA-seq data: SNPs were removed if they had a FisherStrand score greater than 30, if the depth-corrected quality score of the variant call was less than 2, and if there were more than 3 SNPs within a 35bp window. In addition, we required a sequence depth of at least 25 reads at each SNP. Among the SNPs passing these filters, we required that individual genotype calls have a quality score of at least 20—individuals with a low quality genotype at a given SNP were marked as “no call” for that SNP. After removing low quality individual genotype calls, we removed SNPs that were present in less than 16 individuals in each population, in order to focus on the more informative sites for population analyses. This approach precludes analysis of many genes with low levels of overall expression; however, we expect that many of the genes of interest for gut function should be expressed at sufficient levels for SNP analysis. Finally, we removed SNPs with a minor allele frequency <1%, as these are more likely to result from sequencing errors.
We used the software package SnpEff (version 4.2) [97] to determine whether identified SNPs were synonymous, nonsynonymous, or noncoding. Any SNPs in unigenes that were not predicted to have functional ORFs by TransDecoder were classified as noncoding. If the unigene did contain a predicted ORF, then SNPs that were located outside of the ORF region were classified as noncoding UTR variants.
Angels:- “White Butterflies Inside Your House…. ” A Special Moment | The Lord Helps with Ros(272)
FAQ
What does it mean to see white butterflies?
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Purity and Innocence:The color white is often associated with purity and innocence, and white butterflies embody this symbolism.
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Healing:White butterflies can symbolize healing, both physically and spiritually, suggesting a journey of recovery and renewal.
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Spiritual Connection:Some believe that seeing a white butterfly can be a sign from a deceased loved one, offering comfort and reassurance.
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Transformation and Rebirth:Butterflies, in general, are symbols of transformation, rebirth, and personal growth, and white butterflies can represent a new beginning or a positive shift in one’s life.
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Freedom:Butterflies, starting as earthly creatures and eventually flying away, are often associated with freedom, and seeing a white butterfly may indicate a journey of healing that results in newfound freedom of body or spirit.
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Encouragement and Support:The appearance of a white butterfly might be seen as encouragement, support, or a reminder of spiritual connections, offering a sense of hope and guidance.
What kind of butterflies are white?
- Cabbage White: Pieris rapae. …
- West Virginia White: Pieris virginiensis. …
- Mustard White: Pieris oleracea. …
- Sulphur Butterflies: Genus Colias. …
- Chiricahua Pine White: Neophasia terlooii. …
- Western Pine White: Neophasia menapia. …
- Great Southern White: Ascia monuste. …
- Florida White: Appias drusilla.
Are white butterflies rare to see?
There are four common and widespread species of white butterfly that are frequently seen in gardens and many other habitats. These are the Large White, Small White, Green-veined White and Orange-tip.
What are the white butterflies in my yard?
Cabbage White Butterfly; Imported Cabbageworm (Pieris rapae)
The Imported Cabbage worm is also known as the cabbage white butterfly (see adult picture below). You are familiar with this common insect in your garden or on your farm. It associates with broccoli, cauliflower, and other cabbage family plants.
Where can you find a white butterfly?
You can only find this white butterfly in the extreme South of the US, particularly in New Mexico and Arizona. It’s here that the Chiricahua White butterfly is one of the largest white butterflies as it has a wingspan of at least 45mm that can be as long as 58mm. 36. Arctic White
What is a white butterfly?
A white butterfly is a butterfly in the Pieridae family with white wings and black marginal markings. The Pieridae family also includes orange-tip and sulfur butterflies, with approximately 1,100 species in total.
What is The wingspan of a white butterfly?
White butterflies in the US have a wingspan between 29 and 96mm and they can have different patterns and color variations even within the same species, particularly between males and females. These butterflies live in all types of terrains and altitudes.
Are there white butterflies on the west coast?
Anna’s Blue (Plebejus anna) is another native white and off-white butterfly species on The West Coast. This species can appear white, off-white, and even yellow. Its white color is dominant. Butterflies of the species have white wings with black dots.
What does an adult white butterfly look like?
The adult white butterflies have a wingspan of 37 to 63 mm (1.5 to 2.5 inches). Sexual seasonal dimorphism in pattern and colour occur in many species.
Is it difficult to identify white butterflies?
White butterflies can be one of the hardest common butterfly species to identify accurately, especially for beginners. It can be challenging to compare distinguishing features using guide books, where each butterfly species usually has its own separate dedicated section.