Design of aBrassica rapacore collection for association mapping studiesThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Abstract

A Brassica rapa collection of 239 accessions, based on two core collections representing different morphotypes from different geographical origins, is presented and its use for association mapping is illustrated for flowering time. We analyzed phenotypic variation of leaf and seed pod traits, plant architecture, and flowering time using data collected from three field experiments and evaluated the genetic diversity with a set of SSR markers. The Wageningen University and Research Centre (WUR) and the Vavilov Research Institute of Plant Industry (VIR) core collections had similar representations of most morphotypes, as illustrated by the phenotypic and genetic variation within these groups. The analysis of population structure revealed five subgroups in the collection, whereas previous studies of the WUR core collection indicated four subgroups; the fifth group identified consisted mainly of oil accessions from the VIR core collection, winter oils from Pakistan, and a number of other types. A very small group of summer oils is described, that is not related to other oil accessions. A candidate gene approach was chosen for association mapping of flowering time with a BrFLC1 biallelic CAPS marker and a BrFLC2 multiallelic SSR marker. The two markers were significantly associated with flowering time, but their effects were confined to certain morphotypes and (or) alleles. Based on these results, we discuss the optimal design for an association mapping population and the need to fix the heterogeneous accessions to facilitate phenotyping and genotyping.

Optimizing isothiocyanate formation during enzymatic glucosinolate breakdown by adjusting pH value, temperature and dilution in Brassica vegetables and Arabidopsis thaliana

“…oleifera (DC.) Metzger f. annua), both part of the Vavilov Research Institute of Plant Industry (VIR) B. rapa core collection61 (kindly provided by Anna Artemyeva, VIR, St. Petersburg, Russia), were selected for the experiments and grown in a climate chamber.…”

Population Structure and Phylogenetic Relationships in a Diverse Panel of Brassica rapa L.

“…Previous population genetic and phylogenetic studies aimed at disentangling the relationships among subspecies of B. rapa have used an array of molecular marker types including isozyme, restriction fragment length polymorphism (RFLP), random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), and simple sequence repeat (SSR) (McGrath and Quiros, 1992; Das et al, 1999; Zhao et al, 2005, 2007, 2010; Takuno et al, 2007; Del Carpio et al, 2011a,b; Guo et al, 2014). More recent studies have capitalized on whole-genome sequencing and single nucleotide polymorphism (SNP) genotyping approaches such as amplicon sequencing (AmpSeq) and genotyping-by-sequencing (GBS) (Cheng et al, 2016a,b; Tanhuanpää et al, 2016).…”

“…For example, Guo et al (2014) found three main groups related to geographic origin (Europe/North Africa, East Asia, and “mixed”) from genotyping 51 SSRs in 173 accessions. However, using AFLP markers other studies used 160 accessions and found four groups (Zhao et al, 2007; Del Carpio et al, 2011a) or used 239 accessions and found five groups (Zhao et al, 2010) that reflected broad morphotype varieties. Recently, using 209 SNPs, Tanhuanpää et al (2016) identified three main groups related to morphotype and flowering habit of 61 accessions.…”

Association Mapping of Seed Oil and Protein Content in Sesamum indicum L. Using SSR Markers

“…Even though Wei et al [12] performed the association analysis of seed oil and protein content and fatty acid composition within 216 Chinese sesame accessions using 79 molecular primer pairs (including SSRs, SRAPs and AFLPs), only one association marker (M15E10-3) was identified under two environments. Therefore, in order to precisely detect the genes or markers associated with oil and protein content traits and to improve the sesame breeding, more efficient markers and germplasm resources with larger phenotypic variation need to be applied [16], [17].…”

“…Compared with the traditional linkage analysis based on mapping populations, association mapping offers higher precision for locating QTLs and selecting molecular markers [16], [18]. Till now, association mapping has been extensively used for analyzing important agronomic and quantity traits in wheat, maize, cotton, oilseed rape and other crops [18]–[22].…”