QTL mapping for agronomic traits using multi-parent advanced generation inter-cross (MAGIC) populations derived from diverse elite indica rice lines

Abstract

In rice many QTL have been reported for yield and related traits using various bi-parental mapping populations. However, few of the well characterized genes/QTL have been successfully used in breeding for improved trait performance. One of the reasons is that the mapping populations used are irrelevant to breeding. Association mapping has also been used in identifying marker-trait associations that are effective in more complex background. However, the results from association mapping using diversity panels are difficult to be exploited in breeding, since most of the accessions had poor performance in many important agronomic traits. In this study, a genome-wide association study (GWAS) was performed using three multiparent advanced generation inter-cross (MAGIC) populations derived from elite indica lines (DC1, DC2 and 8-way) to identify QTL for 14 traits including yield, yield components and other related traits. The three MAGIC populations were phenotyped in the dry season (DS) and wet season (WS) of 2014 at the headquarters of the International Rice Research Institute (IRRI) and genotyped with a Rice SNP chip containing 4,500 markers. A total of 26 QTL on all chromosomes except 7, 9 and 11 were identified for 10 traits in the DS or WS. Six, two, 12, 10 and 20 out of the 26 QTL were identified in the DC1, DC2, 8-way, DC12 (DC1+DC2) and RMPRIL (DC1+DC2+8-way) populations, respectively. Nine of the QTL corresponded to known QTL/genes, including qFLW4 for FLW, qTGW3 and qTGW5 for TGW, qFGN4 for FGN, qSBN4 for SBN, qPH1.1 and qPH1.2 for PH, qHD3 and qHD6 for HD. All these nine QTL were identifiable using the RMPRIL population while only eight, seven, six and one could be identified using the 8-way, DC12, DC1 and DC2 populations, respectively. The 8-way population was more powerful than the DC1, DC2 and DC12 populations. The joint analysis, which combines different populations (e.g. DC12 and RMPRIL), increased the number of QTL identified and mapping resolution. The study showed that MAGIC populations derived from diverse elite parental lines can be used to detect QTL, which are ideal for linking gene identification and practical breeding. GWAS using such MAGIC populations had higher detection power (compared to assembled populations) and higher resolution (compared to biparental populations). The identified QTL are directly applicable, since the populations are good breeding populations as well.

Genome-Wide Association Study of Grain Size Traits in Indica Rice Multiparent Advanced Generation Intercross (MAGIC) Population

“…The first two PCs, which accounted for most of the variation, were plotted to observe any subgroups in both populations under study. Results showed two subgroupings in the DC1 as previously reported by Meng et al (2016), whereas no subgrouping was observed in the BIM population ( Supplementary Figure 1).…”

“…Two MAGIC populations developed at the International Rice Research Institute (IRRI) were used: (1) a four-parent MAGIC population, DC1, previously characterized by Meng et al (2016), and (2) an eight-parent MAGIC population reported by Bandillo et al (2013), which we referred to as Bandillo indica MAGIC (BIM) population in this study. The parents used to develop both populations were presented in Supplementary Table 1.…”

“…The decay of LD along with physical distances was computed for both the DC1 and BIM populations. A critical value of the determination coefficients r 2 > 0.2 was used to be the appropriate threshold for LD (Meng et al, 2016). A scatter r 2 against physical distance showed a clean pattern of LD decay in the DC1 and BIM populations.…”

“…MAGIC has more allelic and phenotypic diversity ensuring that more QTLs segregate within the population (Cavanagh et al, 2008;. Furthermore, it has a better control over population structure and kinship, and has been proven effective in identifying major genes via association mapping (Bandillo et al, 2013;Meng et al, 2016Meng et al, , 2017Descalsota et al, 2018;Ogawa et al, 2018;Ponce et al, 2018).…”

Breeding wheat for drought adaptation: Development of selection tools for root architectural traits

“…The MAGIC strategy has been used in wheat for mapping QTL underlying complex traits such as plant height and grain hectolitre weight (Huang et al, 2012). MAGIC populations are in development for other crop species, including rice (Bandillo et al, 2013;Meng et al, 2016) and wheat (Cavanagh et al, 2008;Mackay et al, 2014;Delhaize et al, 2015).…”