Genomic adaptation to agricultural environments: cabbage white butterflies (Pieris rapae) as a case study

• Published in: BMC genomics Vol. 18; no. 1; p. 412
• Main Authors: Sikkink, Kristin L, Kobiela, Megan E, Snell-Rood, Emilie C
• Format: Journal Article
• Language: English
• Published: England BioMed Central 26.05.2017; BMC
• Subjects: Adaptation; Adaptation, Physiological; Agricultural management; Agricultural resources; Agriculture; Animals; Brassica oleracea; Butterflies & moths; Canola; Case studies; Catalytic activity; Crops; de novo transcriptome; Diapause; Divergence; Environment; Fertilizers; Gene expression; Gene Expression Profiling; Genes; Genetic diversity; Genetic variance; Genomics; Host plants; Hypotheses; Intestinal Mucosa - metabolism; Lepidoptera - genetics; Lepidoptera - physiology; Molecular Sequence Annotation; Niche breadth; Pesticides; Phenotype; Phenotypic variations; Pieris rapae; Population; Population divergence; Population structure; Radishes; Ribonucleic acid; RNA; Single nucleotide polymorphism; Studies; United States > US; North Dakota; Minnesota; de novo transcriptome; Population divergence; Single nucleotide polymorphism
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-017-3787-2

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.