Jianlong Xu

Identification and Fine Mapping of a Stably Expressed QTL for Cold Tolerance at the Booting Stage Using an Interconnected Breeding Population in Rice.

Cold stress is one of the major abiotic stresses that impede rice production. A interconnected breeding (IB) population consisted of 497 advanced lines developed using HHZ as the recurrent parent and eight diverse elite indica lines as the donors were used to identify stably expressed QTLs for CT at the booting stage. A total of 41,754 high-quality SNPs were obtained through re-sequencing of the IB population. Phenotyping was conducted under field conditions in two years and three locations. Association analysis identified six QTLs for CT on the chromosomes 3, 4 and 12. QTL qCT-3-2 that showed stable CT across years and locations was fine-mapped to an approximately 192.9 kb region. Our results suggested that GWAS applied to an IB population allows better integration of gene discovery and breeding. QTLs can be mapped in high resolution and quickly utilized in breeding.

Complex molecular mechanisms underlying seedling salt tolerance in rice revealed by comparative transcriptome and metabolomic profiling

Highlight Comprehensive analyses of phenotypic, metabolic, and transcriptome data from two genotypes with contrasting salt tolerance provided a more complete picture of the molecular mechanisms underlying seedling tolerance in rice.

Dissecting Genetic Networks Underlying Complex Phenotypes: The Theoretical Framework

Great progress has been made in genetic dissection of quantitative trait variation during the past two decades, but many studies still reveal only a small fraction of quantitative trait loci (QTLs), and epistasis remains elusive. We integrate contemporary knowledge of signal transduction pathways with principles of quantitative and population genetics to characterize genetic networks underlying complex traits, using a model founded upon one-way functional dependency of downstream genes on upstream regulators (the principle of hierarchy) and mutual functional dependency among related genes (functional genetic units, FGU). Both simulated and real data suggest that complementary epistasis contributes greatly to quantitative trait variation, and obscures the phenotypic effects of many ‘downstream’ loci in pathways. The mathematical relationships between the main effects and epistatic effects of genes acting at different levels of signaling pathways were established using the quantitative and population genetic parameters. Both loss of function and “co-adapted” gene complexes formed by multiple alleles with differentiated functions (effects) are predicted to be frequent types of allelic diversity at loci that contribute to the genetic variation of complex traits in populations. Downstream FGUs appear to be more vulnerable to loss of function than their upstream regulators, but this vulnerability is apparently compensated by different FGUs of similar functions. Other predictions from the model may account for puzzling results regarding responses to selection, genotype by environment interaction, and the genetic basis of heterosis.

Genome-Wide Association Study of Grain Appearance and Milling Quality in a Worldwide Collection of Indica Rice Germplasm

Grain appearance quality and milling quality are the main determinants of market value of rice. Breeding for improved grain quality is a major objective of rice breeding worldwide. Identification of genes/QTL controlling quality traits is the prerequisite for increasing breeding efficiency through marker-assisted selection. Here, we reported a genome-wide association study in indica rice to identify QTL associated with 10 appearance and milling quality related traits, including grain length, grain width, grain length to width ratio, grain thickness, thousand grain weight, degree of endosperm chalkiness, percentage of grains with chalkiness, brown rice rate, milled rice rate and head milled rice rate. A diversity panel consisting of 272 indica accessions collected worldwide was evaluated in four locations including Hangzhou, Jingzhou, Sanya and Shenzhen representing indica rice production environments in China and genotyped using genotyping-by-sequencing and Diversity Arrays Technology based on next-generation sequencing technique called DArTseq™. A wide range of variation was observed for all traits in all environments. A total of 16 different association analysis models were compared to determine the best model for each trait-environment combination. Association mapping based on 18,824 high quality markers yielded 38 QTL for the 10 traits. Five of the detected QTL corresponded to known genes or fine mapped QTL. Among the 33 novel QTL identified, qDEC1.1 (qGLWR1.1), qBRR2.2 (qGL2.1), qTGW2.1 (qGL2.2), qGW11.1 (qMRR11.1) and qGL7.1 affected multiple traits with relatively large effects and/or were detected in multiple environments. The research provided an insight of the genetic architecture of rice grain quality and important information for mining genes/QTL with large effects within indica accessions for rice breeding.

Harnessing the hidden genetic diversity for improving multiple abiotic stress tolerance in rice (Oryza sativa L.)

To develop superior rice varieties with improved yield in most rainfed areas of Asia/Africa, we started an introgression-breeding program for simultaneously improving yield and tolerances of multiple abiotic stresses. Using eight BC1 populations derived from a widely adaptable recipient and eight donors plus three rounds of phenotypic selection, we developed 496 introgression lines (ILs) with significantly higher yield under drought, salt and/or non-stress conditions in 5 years. Six new varieties were released in the Philippines and Pakistan and many more are being evaluated in multi-location yield trials for releasing in several countries. Marker-facilitated genetic characterization revealed three interesting aspects of the breeding procedure: (1) the donor introgression pattern in specific BC populations was characteristic; (2) introgression frequency in different genomic regions varied considerably, resulting primarily from strong selection for the target traits; and (3) significantly lower heterozygosity was observed in BC progenies selected for drought and salinity tolerance. Applying strong phenotypic selection under abiotic stresses in early segregating generations has major advantages for not only improving multiple abiotic stress tolerance but also achieving quicker homozygosity in early generations. This breeding procedure can be easily adopted by small breeding programs in developing countries to develop high-yielding varieties tolerant of abiotic stresses. The large set of trait-specific ILs can be used for genetic mapping of genes/QTL that affect target and non-target traits and for efficient varietal development by designed QTL pyramiding and genomics-based recurrent selection in our Green Super Rice breeding technology.

Drought-tolerance QTLs commonly detected in two sets of reciprocal introgression lines in rice

Abstract. Drought is one of the major abiotic stresses limiting rice (Oryza sativa L.) production. Quantitative trait loci (QTLs) for drought tolerance (DT) at the reproductive stage were identified with two sets of reciprocal introgression lines derived from Lemont × Teqing. In total, 29 and 23 QTLs were identified in the Teqing and Lemont backgrounds, respectively, during the reproductive stage under drought and irrigated conditions for spikelet number per panicle, seed fertility, filled grain weight per panicle, plant height, and grain yield per plant. Most of these QTLs showed obvious differential expressions in response to drought stress. Another 21 QTLs were detected by the ratio of trait values under drought stress relative to the normal irrigation conditions in the two backgrounds. For 28 DT QTLs, the Teqing alleles at 23 loci had increased trait values and could improve DT under drought stress. Only five (17.9%) DT QTLs (QSnp1b, QSnp3a, QSnp11, QSf8, and QGyp2a) were consistently detected in the two backgrounds, clearly suggesting overwhelming genetic background effects on QTL detection for DT. Seven of the DT QTL regions identified were found to share the same genomic regions with previously reported DT-related genes. Introgressing or pyramiding of favourable alleles from Teqing at the validated QTLs (QSnp3a, QSnp11 and QGyp2a) into Lemont background may improve DT level of Lemont.

New Candidate Genes Affecting Rice Grain Appearance and Milling Quality Detected by Genome-Wide and Gene-Based Association Analyses

Appearance and milling quality are two crucial properties of rice grains affecting its market acceptability. Understanding the genetic base of rice grain quality could considerably improve the high quality breeding. Here, we carried out an association analysis to identify QTL affecting nine rice grain appearance and milling quality traits using a diverse panel of 258 accessions selected from 3K Rice Genome Project and evaluated in two environments Sanya and Shenzhen. Genome-wide association analyses using 22,488 high quality SNPs identified 72 QTL affecting the nine traits. Combined gene-based association and haplotype analyses plus functional annotation allowed us to shortlist 19 candidate genes for seven important QTL regions affecting the grain quality traits, including two cloned genes (GS3 and TUD), two fine mapped QTL (qGRL7.1 and qPGWC7) and three newly identified QTL (qGL3.4, qGW1.1, and qGW10.2). The most likely candidate gene(s) for each important QTL were also discussed. This research demonstrated the superior power to shortlist candidate genes affecting complex phenotypes by the strategy of combined GWAS, gene-based association and haplotype analyses. The identified candidate genes provided valuable sources for future functional characterization and genetic improvement of rice appearance and milling quality.

QTL mapping and candidate gene analysis of ferrous iron and zinc toxicity tolerance at seedling stage in rice by genome-wide association study

BackgroundFerrous iron (Fe) and zinc (Zn) at high concentration in the soil cause heavy metal toxicity and greatly affect rice yield and quality. To improve rice production, understanding the genetic and molecular resistance mechanisms to excess Fe and Zn in rice is essential. Genome-wide association study (GWAS) is an effective way to identify loci and favorable alleles governing Fe and Zn toxicty as well as dissect the genetic relationship between them in a genetically diverse population.ResultsA total of 29 and 31 putative QTL affecting shoot height (SH), root length (RL), shoot fresh weight (SFW), shoot dry weight (SDW), root dry weight (RDW), shoot water content (SWC) and shoot ion concentrations (SFe or SZn) were identified at seedling stage in Fe and Zn experiments, respectively. Five toxicity tolerance QTL (qSdw3a, qSdw3b, qSdw12 and qSFe5 / qSZn5) were detected in the same genomic regions under the two stress conditions and 22 candidate genes for 10 important QTL regions were also determined by haplotype analyses.ConclusionRice plants share partial genetic overlaps of Fe and Zn toxicity tolerance at seedling stage. Candidate genes putatively affecting Fe and Zn toxicity tolerance identified in this study provide valuable information for future functional characterization and improvement of rice tolerance to Fe and Zn toxicity by marker-assisted selection or designed QTL pyramiding.

Examining Two Sets of Introgression Lines in Rice (Oryza sativa L.) Reveals Favorable Alleles that Improve Grain Zn and Fe Concentrations

In the modern world, the grain mineral concentration (GMC) in rice (Oryza sativa L.) not only includes important micronutrient elements such as iron (Fe) and zinc (Zn), but it also includes toxic heavy metal elements, especially cadmium (Cd) and lead (Pb). To date, the genetic mechanisms underlying the regulation of GMC, especially the genetic background and G × E effects of GMC, remain largely unknown. In this study, we adopted two sets of backcross introgression lines (BILs) derived from IR75862 (a Zn-dense rice variety) as the donor parent and two elite indica varieties, Ce258 and Zhongguangxiang1, as recurrent parents to detect QTL affecting GMC traits including Fe, Zn, Cd and Pb concentrations in two environments. We detected a total of 22 loci responsible for GMC traits, which are distributed on all 12 rice chromosomes except 5, 9 and 10. Six genetic overlap (GO) regions affecting multiple elements were found, in which most donor alleles had synergistic effects on GMC. Some toxic heavy metal-independent loci (such as qFe1, qFe2 and qZn12) and some regions that have opposite genetic effects on micronutrient (Fe and Zn) and heavy metal element (Pb) concentrations (such as GO-IV) may be useful for marker-assisted biofortification breeding in rice. We discuss three important points affecting biofortification breeding efforts in rice, including correlations between different GMC traits, the genetic background effect and the G × E effect.

Genome-wide and gene-based association mapping for rice eating and cooking characteristics and protein content

Rice eating and cooking quality and protein content (PC) are important properties affecting consumers’ preferences, nutrition and health. Linkage QTL mapping and association studies are usually applied to genetically dissect related traits, which could be further facilitated by high density SNP markers and gene annotation based on reference genome to rapid identify candidate genes associated with interested traits. Here, we carried out an association study for apparent amylose content (AC), gel consistency (GC), gelatinization temperature (GT) and PC evaluated in two environments using a diverse panel of 258 accessions from 3 K Rice Genome Project. Wide phenotypic variations were observed in this panel. Genome-wide association study using 22,488 high quality SNPs identified 19 QTL affecting the four traits. Combining gene-based association study and haplotype analyses plus functional annotation allowed us to shortlist nine candidate genes for four important QTL regions affecting AC, GC and GT, including two cloned genes (Wx and ALK), and seven novels. The research suggested that GWAS and gene-based association analysis followed by haplotype analysis is an effective way to detect candidate genes. The identified genes and QTL provided valuable sources for future functional characterization and genetic improvement of rice eating and cooking quality and PC.