Funmap2: an R package for QTL mapping using longitudinal phenotypes

Time-sequential detection of quantitative trait loci and candidate genes underlying the dynamic growth of Salix suchowensis

Elucidating the genetic factors underlying long-term biological processes remains challenging since the relevant genes and their effects may vary across different developmental stages. In this study, we carried out a large-scale field trial of the progeny of an F1 full-sib pedigree of Salix suchowensis and measured plant height and ground diameter periodically over a time course of 240 days. With the obtained data, we characterized plant growth rhythms and performed time-sequential analyses of quantitative trait loci underlying the dynamic growth of the plants. The dynamic mapping of quantitative trait loci revealed that stem height and ground diameter were under the control of four quantitative trait loci, and the effects of these quantitative trait loci varied greatly throughout the growth process, in which two quantitative trait loci were found to exert a pleiotropic effect determining the correlation between stem height and ground diameter. The analysis of candidate genes in the target genetic intervals showed that the pleiotropic effect of the two quantitative trait loci arises from the colocalization of genes with independent effects on stem height and ground diameter. Further examination of the expression patterns of the candidate genes indicated that height and circumference growth involve different activities of leaf and cambium tissues. This study provides unprecedented information to help us understand the dynamic growth of plants and presents an applicable strategy for elucidating the genetic mechanism underlying a long-term biological process by using plant growth as an example.

Heterophylly Quantitative Trait Loci Respond to Salt Stress in the Desert Tree Populus euphratica

Heterophylly, or leaf morphological changes along plant shoot axes, is an important indicator of plant eco-adaptation to heterogeneous microenvironments. Despite extensive studies on the genetic control of leaf shape, the genetic architecture of heterophylly remains elusive. To identify genes related to heterophylly and their associations with plant saline tolerance, we conducted a leaf shape mapping experiment using leaves from a natural population of Populus euphratica. We included 106 genotypes grown under salt stress and salt-free (control) conditions using clonal seedling replicates. We developed a shape tracking method to monitor and analyze the leaf shape using principal component (PC) analysis. PC1 explained 42.18% of the shape variation, indicating that shape variation is mainly determined by the leaf length. Using leaf length along shoot axes as a dynamic trait, we implemented a functional mapping-assisted genome-wide association study (GWAS) for heterophylly. We identified 171 and 134 significant quantitative trait loci (QTLs) in control and stressed plants, respectively, which were annotated as candidate genes for stress resistance, auxin, shape, and disease resistance. Functions of the stress resistance genes ABSCISIC ACIS-INSENSITIVE 5-like (ABI5), WRKY72, and MAPK3 were found to be related to many tolerance responses. The detection of AUXIN RESPONSE FACTOR17-LIKE (ARF17) suggests a balance between auxin-regulated leaf growth and stress resistance within the genome, which led to the development of heterophylly via evolution. Differentially expressed genes between control and stressed plants included several factors with similar functions affecting stress-mediated heterophylly, such as the stress-related genes ABC transporter C family member 2 (ABCC2) and ABC transporter F family member (ABCF), and the stomata-regulating and reactive oxygen species (ROS) signaling gene RESPIRATORY BURST OXIDASE HOMOLOG (RBOH). A comparison of the genetic architecture of control and salt-stressed plants revealed a potential link between heterophylly and saline tolerance in P. euphratica, which will provide new avenues for research on saline resistance-related genetic mechanisms.