Zhikang Li

Evaluation of near-isogenic lines of rice introgressed with QTLs for root depth through marker-aided selection

Abstract Drought is one of the main abiotic constraints in rice. A deep root system contributes efficiently to maintaining the water status of the crop through a stress period. After identifying QTLs affecting root parameters in a doubled-haploid (DH) population of rice derived from the cross IR64/Azucena, we started a marker-assisted backcross program to transfer the Azucena allele at four QTLs for deeper roots (on chromosomes 1, 2, 7 and 9) from selected DH lines into IR64. We selected the backcross progenies strictly on the basis of their genotypes at the marker loci in the target regions up to the BC3F2. We assessed the proportion of alleles remaining from Azucena in the non-target areas of the BC3F2 plants, which was in the range expected for the backcross stage reached. Twenty nine selected BC3F3 near-isogenic lines (NILs) were developed and compared to IR64 for the target root traits and three non-target traits in replicated experiments. Of the three tested NILs carrying target 1, one had significantly improved root traits over IR64. Three of the seven NILs carrying target 7 alone, as well as three of the eigth NILs carrying both targets 1 and 7, showed significantly improved root mass at depth. Four of the six NILs carrying target 9 had significantly improved maximum root length. Five NILs carrying target 2 were phenotyped, but none had a root phenotype significantly different from that of IR64. A re-analysis of the initial data with the composite interval mapping technique revealed two linked QTLs with opposite effects in this area. Some NILs were taller than IR64 and all had a decreased tiller number because of a likely co-introgression of linked QTLs. The usefulness of NILs, the efficiency of marker-aided selection for QTLs and the relationship between root traits are discussed. The NILs with an improved root system will permit testing the importance of root depth for water-limited environments.

SNP-Seek database of SNPs derived from 3000 rice genomes.

We have identified about 20 million rice SNPs by aligning reads from the 3000 rice genomes project with the Nipponbare genome. The SNPs and allele information are organized into a SNP-Seek system (http://www.oryzasnp.org/iric-portal/), which consists of Oracle database having a total number of rows with SNP genotypes close to 60 billion (20 M SNPs × 3 K rice lines) and web interface for convenient querying. The database allows quick retrieving of SNP alleles for all varieties in a given genome region, finding different alleles from predefined varieties and querying basic passport and morphological phenotypic information about sequenced rice lines. SNPs can be visualized together with the gene structures in JBrowse genome browser. Evolutionary relationships between rice varieties can be explored using phylogenetic trees or multidimensional scaling plots.

Locating QTLs controlling constitutive root traits in the rice population IAC 165 × Co39

Drought is an important constraint to productivity in rainfed rice environments. Improvement in the various components of rice drought tolerance is now possible through the identification and manipulation of DNA markers linked with genes controlling these quantitative traits. A recombinant inbred line population was derived from the cross IAC165 × Co39. A molecular map was built that contained 182 RFLP and microsatellite markers. Segregation distortions were limited to a few chromosomal segments. Constitutive root traits, including maximum root length, root thickness and root dry weight in various layers, were measured on 125 lines in a greenhouse replicated experiment. QTL analysis was performed using composite interval mapping. Between 1and 4 main effect QTLs, which explained individually between 5.5 and 24.8% of the variability, were identified for each trait. The most important genomic regions, which carried QTLs for several traits, were found on chromosomes 1, 4, 9, 11 and 12.The QTL locations were in good agreement with previous studies on these traits, confirming the value of the QTLs in a different genetic background. Epistasis represented a non-negligible component of the observed variability for some of the traits but was not detected for others. These results add to the understanding of the genetic control of root morphology in rice, which is necessary to strengthen marker-aided selection programs to improve varieties for water-limited environments.

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.

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.

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.