QTL and QTL networks for cold tolerance at the reproductive stage detected using selective introgression in rice

Abstract

Low temperature stress is one of the major abiotic stresses limiting the productivity of Geng (japonica) rice grown the temperate regions as well as in tropical high lands worldwide. To develop rice varieties with improved cold tolerance (CT) at the reproductive stage, 84 BC2 CT introgression lines (ILs) were developed from five populations through backcross breeding. These CT ILs plus 310 random ILs from the same BC populations were used for dissecting genetic networks underlying CT in rice by detecting QTLs and functional genetic units (FGUs) contributing to CT. Seventeen major QTLs for CT were identified using five selective introgression populations and the method of segregation distortion. Of them, three QTLs were confirmed using the random populations and seven others locate in the regions with previously reported CT QTLs/genes. Using multi-locus probability tests and linkage disequilibrium (LD) analyses, 46 functional genetic units (FGUs) (37 single loci and 9 association groups or AGs) distributed in 37 bins (~20%) across the rice genome for CT were detected. Together, each of the CT loci (bins) was detected in 1.7 populations, including 18 loci detected in two or more populations. Putative genetic networks (multi-locus structures) underlying CT were constructed based on strong non-random associations between or among donor alleles at the unlinked CT loci/FGUs identified in the CT ILs, suggesting the presence of strong epistasis among the detected CT loci. Our results demonstrated the power and usefulness of using selective introgression for simultaneous improvement and genetic dissection of complex traits such as CT in rice.

Genomic Breeding of Green Super Rice Varieties and Their Deployment in Asia and Africa

“…Second, the genes introduced into these lines would be combined in a designed way to develop cultivars with favorable traits. The introgression breeding approach has been used for developing GSR, and demonstrates being robust in several successful applications (Li and Ali 2017;Feng et al 2018;Liang et al 2018), because of its advantage with simultaneous improvement and genetic dissection of complex traits by introgressing one or more target genes through the genome selection system. This approach resulted in many GSR varieties and their adoption across Asia and Africa in the IR64, Huanghuazhan (HHZ), and Weed Tolerant Rice 1(WTR1) recipient backgrounds (Ali et al 2018).…”

“…One important component of the GSR project was to resequence a core collection of 3024 rice germplasm accessions and phenotype the sequenced lines and GSR parents plus a large set of chromosomal segment substitution lines (CSSLs) for many green traits to discover and mine genes/QTLs associated with the green traits by genome-wide association analyses. As a result, a large number of loci associated with green traits were identified (Sun et al 2015;Zhu et al 2015;Lv et al 2016;Qiu et al 2017;Liang et al 2018). These newly detected QTLs or the cloned genes provide abundant genetic resources for the development of new GSR varieties.…”

Identification of main-effect quantitative trait loci (QTLs) for low-temperature stress tolerance germination- and early seedling vigor-related traits in rice (Oryza sativa L.)

“…Compared with other cereal crops, rice is more sensitive to low-temperature stress (LTS)/cold stress (CS) as it has originated from tropical regions (Saito et al 2001;Hasanuzzaman et al 2009;Zeng et al 2017). In the temperate, tropical, and even subtropical rice-growing regions, cold stress adversely affects the rice crop throughout various growth stages, from germination to harvesting, and causes significant yield losses because of poor germination and seedling establishment, stunted growth pattern, non-vigorous plants, vast spikelet sterility, delay in flowering, and lower grain filling (Ranawake et al 2014;Martínez-Eixarch and Ellis 2015;Schläppi et al 2017;Shakiba et al 2017;Liang et al 2018;Xiao et al 2018;Najeeb et al 2019 (unpublished). Therefore, to minimize these yield losses, particularly in cold-affected regions, it is imperative to identify and develop high-yielding rice cultivars showing tolerance of LTS.…”

“…To date, more than 550 QTLs have been reported for different growth stages (germination, seedling, and reproductive/booting stage) for tolerance of LTS by using DNA-based molecular markers on different genetic backgrounds derived from bi-parental mapping populations and diverse genetic resources of rice accessions (Liang et al 2018;Najeeb et al (2019) unpublished). Mapping of the stable QTLs for LTS at the reproductive/booting stage is more of a major challenge than at the seedling stage because of difficulties in accurate phenotypic screening and also the complexity of molecular genetics and physiological pathways.…”

“…Mapping of the stable QTLs for LTS at the reproductive/booting stage is more of a major challenge than at the seedling stage because of difficulties in accurate phenotypic screening and also the complexity of molecular genetics and physiological pathways. Liang et al (2018) noted more than 100 QTLs responsible for cold tolerance, particularly in the booting stage. However, despite further progress in the molecular genetic dissection of LTS tolerance in rice, few of them were confirmed to be stable QTLs across environments (Fujino et al 2008;Ji et al 2010;Li et al 2013;Cui et al 2013;Kim et al 2014;Zhu et al 2015).…”