Molecular Parallelism Underlies Convergent Highland Adaptation of Maize Landraces

Abstract

Convergent phenotypic evolution provides some of the strongest evidence for adaptation. However, the extent to which recurrent phenotypic adaptation has arisen via parallelism at the molecular level remains unresolved, as does the evolutionary origin of alleles underlying such adaptation. Here, we investigate genetic mechanisms of convergent highland adaptation in maize landrace populations and evaluate the genetic sources of recurrently selected alleles. Population branch excess statistics reveal strong evidence of parallel adaptation at the level of individual SNPs, genes and pathways in four independent highland maize populations, even though most SNPs show unique patterns of local adaptation. The majority of selected SNPs originated via migration from a single population, most likely in the Mesoamerican highlands. Polygenic adaptation analyses of quantitative traits reveal that alleles affecting flowering time are significantly associated with elevation, indicating the flowering time pathway was targeted by highland adaptation. In addition, repeatedly selected genes were significantly enriched in the flowering time pathway, indicating their significance in adapting to highland conditions. Overall, our study system represents a promising model to study convergent evolution in plants with potential applications to crop adaptation across environmental gradients.

An adaptive teosintemexicanaintrogression modulates phosphatidylcholine levels and is associated with maize flowering time

“…The genes High PhosphatidylCholine 1 ( HPC1 , Zm00001d039542 ) and Lyso-Phosphatidylcholine Acyl Transferase 1 ( ZmLPCAT1 , Zm00001d017584 ), which are involved in phospholipid remodeling, had SNPs within their coding sequence with significantly high −log(P) values (Figure 2A-B), indicating strong elevation-dependent allele frequency changes (Figure 2C-D). We then used the same set of 600 glycerolipid metabolism-related genes to identify selection signals using the Population Branch Excess (PBE) (46) statistic across four highland populations: Southwestern US (SWUS), Mexican Highlands (MH), Guatemalan Highlands (GH) and Andes (24). We established that, of the 153 glycerolipid-related genes that were PBE outliers in the Mexican Highlands, 38 were also pcadapt PC1 outliers (Sup.…”

Drainage-structuring of ancestral variation and a common functional pathway shape limited genomic convergence in natural high- and low-predation guppies

“…[10–12]); or different genes in the same functional pathways (eg. [13–16]). Further, variation among lineages may arise through one of three modes: either de novo mutations (eg.…”

Population genomics of parallel adaptation

“…To date, there seem to be relatively few cases of an independent genetic basis to adaptive traits (Fang et al, 2020;Gould & Stinchcombe, 2017). In contrast, there are several recently described cases where there appears to be a parallel genetic basis (Holliday et al, 2016;Nelson & Cresko, 2018;Pool et al, 2017;Preite et al, 2019;Yang et al, 2018;Yeaman et al, 2016;Wang et al, 2020).…”

“…Some of these are clear cases of independent evolution despite many years of separate evolutionary histories (e.g. conifers separated by ~ 140 million years; Yeaman et al., 2016), while others clearly implicate gene flow from nearby populations (Wang et al 2020). For sticklebacks, genetic parallelism is seen on finer geographic scales (Alaska and the Pacific Northwest; e.g.…”

“…Even for cases in which parallel phenotypic evolution is not shared at the level of nucleotide substitutions or genes, we see merit in determining whether there is parallelism at other levels of biological organization (e.g. genetic pathways, developmental processes or hormonal signalling, different modification of the same morphological structures; Rosenblum et al., 2014; Wessinger & Hileman, 2020; Wang et al, 2020). Continued investigation on this front will reveal the degree of genetic lability and constraint in adaptation.…”