Genome

Mei (Prunus mume Sieb. et Zucc., 2n = 2x = 16) is a popular ornamental plant widely cultivated in East Asia. Being an important member of the genus Prunus and a species domesticated for over 3000 years, it plays a pivotal role in phylogenic studies of the Rosaceae. Besides, it owns many highlighted ornamental features, such as colorful corollas, pleasant fragrance, and weeping trait (Chen 1996; Zhang et al. 2015). Weeping trees, characterized by soft and pendant branches, are used worldwide as landscape plants due to their aesthetic value in our living environment. Because of specific structure design, weeping trees are believed to play a pivotal role in understanding the genetic mechanism of plant architecture and have drawn increasing attention during the past decades (Barthélémy and Caraglio 2007; Petersen and Krost 2013; Yamanouchi et al. 2009). However, the underlying genetic and molecular principles for weeping trait remain an unresolved mystery. Developing weeping cultivar with higher ornamental value is still a laborious job. Thus, dissecting the genetic basis of weeping trait is an urgent step for effective breeding of weeping cultivars, especially the woody ornamental plants. The development of a genome-level resource for mei will assist the exploration and improvement of genetic studies of this important ornamental plant, and will provide a better perceptive of weeping trait in Prunus.

Genome-wide polymorphisms identification is crucial to study the genetic basis of phenotypic differences within species (Causse et al. 2013; Srivastava et al. 2014), since they are major determinants of phenotypic variations, and their interaction with the environment is vital for the expression of a trait (Subbaiyan et al. 2012). With the release of the mei genome and the development of next-generation sequencing (NGS) techniques (Zhang et al. 2012), it is now much more feasible to learn genome-wide genetic variation through large-scale re-sequencing of whole genomes in a cost-effective way (Bentley 2006). The detection of a massive number of DNA polymorphisms, such as single nucleotide polymorphisms (SNPs) and insertions-deletions (InDels), is one of the most important applications of NGS techniques (Huang et al. 2013; Varshney et al. 2009). SNPs have gained importance over other DNA markers because of their inherent advantage of high abundance, high-throughput capability, and cost-effectiveness (Henry and Edwards 2009). In addition to massive number of SNPs, InDels have also become valuable DNA markers being applied for QTL mapping and marker-assisted selection with characteristics of much cheaper charge, relatively simple genotyping, and easy transferability between populations (Hayashi et al. 2006; Pan et al. 2008). SNPs and InDels have already been wildly employed in breeding programs for marker-assisted selection, quantitative trait locus mapping, and association mapping (Ma et al. 2014; McCouch et al. 2010; Ren et al. 2010; Zou et al. 2014). Besides, the distributions of SNPs and InDels within a genome also affect the expression and function of genes. Among these genetic variants, non-synonymous and large-effect DNA polymorphisms are particularly important as they are predicted to alter protein function. Therefore, detecting polymorphisms related to functional changes of genes is critical for investigating the reasons for phenotypic differences (Jain et al. 2014). Moreover, the statistic of annotation results of genome-wide genes containing variants can explain the genetic basis of weeping trait to some extent.

With this background, the present study was carried out with the aim of discovering genome-wide identical DNA polymorphisms in a weeping cultivar of mei compared with three mei upright cultivars, with the reference genome of mei using as a “bridge.” Whole-genome re-sequencing of two mei cultivars were carried out using the Illumina Hiseq 2000 platform. The sequence reads generated were then mapped to the high-quality reference genome sequences of mei, and mutual genome-wide variations were uncovered through comprehensive detection of SNPs and InDels across the genomes among different tree architectures. Furthermore, DNA polymorphisms in QTLs conferring weeping trait were detected and annotated. The discovery and annotation of the genetic variations in this study will provide vital clues that will help to unravel the genetic basis of weeping trait and provide promising functional markers in mei.