Transcription factor motif evolution with gains and losses of social behavior

Monday, November 11, 2024

12:18 PM – 12:30 PM MST

Location: Phoenix Convention Center, 222 B, PCC

Presenting Author(s)

Savanna Grace Ploessl (she/her/hers)

Graduate Student Assistant
University of Kentucky
Lexington, Kentucky

Co-Author(s)

BJ

Beryl Jones

University of Kentucky
Lexington, Kentucky

Understanding how changes in gene regulation promote the emergence of novel phenotypes is an important question in evolutionary biology. Bees are an ideal group of organisms to study the origins of sociality since they have independently gained and lost social behavior repeatedly. Evidence suggests that transcription factor (TF) motif presence expands in the genomes of social bees, but downstream consequences of motif expansions are not well understood. We used published genomes to compare predicted occurrences of TF binding across 20 bee species spanning 115 million years of evolution. First, we ask whether there are specific TFs and/or target genes consistently modified during social evolution. Next, we take advantage of reversions of sociality (i.e., social to solitary transitions) in sweat bee lineages to ask whether regulatory complexity secondarily decreases when social behavior is lost. Finally, we identify gene regulatory changes linked to sociality through comparison of motif changes and associated genes between ancestrally solitary, social, and secondarily solitary lineages. Our findings are consistent with previous research, corroborating TF motifs which expanded during gains of sociality. We further discovered that many motifs experience partial or complete contractions when sociality is lost, in some cases affecting the same predicted target genes. These results point to extensive turnover in motif presence and suggest there may be costs to the expanded regulatory complexity of social species when social behavior is no longer expressed. More broadly, our results reveal how motif changes may contribute to the evolution of novel phenotypes through modification of existing regulatory networks.