SUMMARYTo clarify the molecular bases of flowering time evolution in crop domestication, here we investigate the evolutionary fates of a set of four recently duplicated genes in soybean: FT2a, FT2b, FT2c and FT2d that are homologues of the floral inducer FLOWERING LOCUS T (FT). While FT2a maintained the flowering inducer function, other genes went through contrasting evolutionary paths. FT2b evolved attenuated expression potentially associated with a transposon insertion in the upstream intergenic region, while FT2c and FT2d obtained a transposon insertion and structural rearrangement, respectively. In contrast to FT2b and FT2d whose mutational events occurred before the separation of G. max and G. soja, the evolution of FT2c is a G. max lineage specific event. The FT2c allele carrying a transposon insertion is nearly fixed in soybean landraces and differentiates domesticated soybean from wild soybean, indicating that this allele spread at the early stage of soybean domestication. The domesticated allele causes later flowering than the wild allele under short day and exhibits a signature of selection. These findings suggest that FT2c may have underpinned the evolution of photoperiodic flowering regulation in soybean domestication and highlight the evolutionary dynamics of this agronomically important gene family.

Photoperiodic flowering, a plant response to seasonal photoperiod changes in the control of reproductive transition, is an important agronomic trait that has been a central target of crop domestication and modern breeding programs. However, our understanding about the molecular mechanisms of photoperiodic flowering regulation in crop species is lagging behind. To better understand the regulatory gene networks controlling photoperiodic flowering of soybeans, we elucidated global gene expression patterns under different photoperiod regimes using the near isogenic lines (NILs) of maturity loci (E loci). Transcriptome signatures identified the unique roles of the E loci in photoperiodic flowering and a set of genes controlled by these loci. To elucidate the regulatory gene networks underlying photoperiodic flowering regulation, we developed the network inference algorithmic package CausNet that integrates sparse linear regression and Granger causality heuristics, with Gaussian approximation of bootstrapping to provide reliability scores for predicted regulatory interactions. Using the transcriptome data, CausNet inferred regulatory interactions among soybean flowering genes. Published reports in the literature provided empirical verification for several of CausNet's inferred regulatory interactions. We further confirmed the inferred regulatory roles of the flowering suppressors GmCOL1a and GmCOL1b using GmCOL1 RNAi transgenic soybean plants. Combinations of the alleles of GmCOL1 and the major maturity locus E1 demonstrated positive interaction between these genes, leading to enhanced suppression of flowering transition. Our work provides novel insights and testable hypotheses in the complex molecular mechanisms of photoperiodic flowering control in soybean and lays a framework for de novo prediction of biological networks controlling important agronomic traits in crops.