Domestication is a long-term evolutionary experiment that offers a great model for population genetics to study the effects and interactions of various evolutionary drivers including the genetics drift of both the domestication bottleneck and subsequent recolonization after domestication, artificial selection (most likely polygenetic) and natural selection and its association with phenotypes and fitness effects, recombination, divergence with gene exchange (i.e introgression, sometimes adaptive) between cultivars and progenitors and so on.
Structural variation (SV) is the great hidden source of genetic diversity. More and more evidence suggests direct associations between SVs and phenotypes. The spectrum of SVs shifted from the wild progenitors to cultivars, which associated with the interactions of various evolutionary factors and phenotypes. In grapevines, we are the first in plants to study the population genetics of SVs during domestication.
Transposable elements (TE) is the most common type of structural variants in plant genomes, which is predominately deleterious under moderate to strong purifying selection (Zhou et al. 2019 Nature Plants). We found different site frequency spectrum (SFS) among TE families. SINE and mariner insertions were found at especially low frequency, suggesting stronger purifying selection at these families (Kou et al. 2020 MBE). At the same time, we also study the genomic regulatory networks among TEs, RNAs, chromatin structures, and other types of variants (SNPs, indels, and non-TE SVs) under the evolutionary genomics framework. In maize, we found the long non-coding RNAs (lncRNAs) were mainly derived from TEs (TE-lncRNAs), and these TE-lncRNAs play important roles in gene regulatory networks under stress conditions (heat, cold, salt and drought)(Lv et al. 2019 BMC Genomics).
Evolutionary genomic analyses of crops found that there were more deleterious variants in cultivars comparing to its wild progenitors, suggesting a cost of domestication. These deleterious included SNPs and indels (Zhou et al. PNAS in grapevine; Liu et al. 2017 MBE in rice; Gaut et al. 2018 Nature Plants as a review) and SVs (Zhou et al. 2019 Nature Plants in grapevine; Kou et al. 2020 MBE in rice).
Climate change is one of the major challenges in the future. Using genomic data, population genetics, landscape genomics, and climate modeling, we will understand how plants responded to past climate change and whether the adaptive potentials of plant populations will catch up with the speed of future climate change. This knowledge will be very important for future landscape planning and agricultural production.