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Zhikang Li

Publications and source records attributed to Zhikang Li.

8 recordsLinked to original sources
PubMed2025

Multi-Omics insights into OsZFP252-OsGA20ox5 mediated drought tolerance in rice through stomatal and vascular regulation.

Rice growth is highly dependent on water availability, and drought stress significantly impacts its entire life cycle. However, previous studies lack systematic investigations into drought-responsive candidate genes across the full life cycle of rice. This study integrates transcriptomic and phenotypic data from two rice lines, IR64 (drought-sensitive) and DK151 (drought-tolerant), under varied environmental conditions at distinct growth stages. Using k-means clustering, 13 369 genes were categorized into 17 distinct expression patterns, revealing drought-responsive genes specifically upregulated or downregulated under drought stress. Weighted co-expression network analysis (WGCNA) further identified four gene modules strongly correlated with drought-related phenotypes, co-localizing 2859 drought-responsive genes through both approaches. Proteomics and metabolomics were supplemented at the booting stage, where phenotypic and transcriptomic differences under drought were most pronounced. Integrated omics results demonstrate gibberellin (GA) and abscisic acid (ABA) pathways play a key role during drought tolerance in rice, and 79 high-confidence drought-resistant candidate genes were prioritized from the 2859 drought-responsive genes. Among these, Gibberellin 20-oxidase 5 (OsGA20ox5) was identified as a key negative regulator of drought tolerance. Furthermore, the transcription factor zinc finger protein 252 (OsZFP252) directly binds to the OsGA20ox5 promoter, repressing its expression and enhancing ABA biosynthesis, thereby improving drought tolerance by increasing stomatal closure and expanding vascular bundle water transport capacity. Notably, the drought-tolerant haplotype 2-4 (Hap2-4) of OsGA20ox5 provides valuable insights for drought-resistant breeding.

Oryza↗
PubMed2006

Promoter mutations of an essential gene for pollen development result in disease resistance in rice.

Disease resistance and sexual reproductive development are generally considered as separate biological processes, regulated by different sets of genes. Here we show that xa13, a recessive allele conferring disease resistance against bacterial blight, one of the most devastating rice diseases worldwide, plays a key role in both disease resistance and pollen development. The dominant allele, Xa13, is required for both bacterial growth and pollen development. Promoter mutations in Xa13 cause down-regulation of expression during host-pathogen interaction, resulting in the fully recessive xa13 that confers race-specific resistance. The recessive xa13 allele represents a new type of plant disease resistance.

Alleles↗
PubMed2005

Targeting xa13, a recessive gene for bacterial blight resistance in rice.

Bacterial blight, caused by Xanthomonas oryzae pv. oryzae (Xoo), is one of the most serious diseases of rice worldwide. Thirty bacterial blight resistance (R) genes (21 dominant genes and 9 recessive genes) in rice have been identified. They are the main sources for the genetic improvement of rice for resistance to Xoo. However, little is known about the recessive R genes. To clone and characterize the recessive R genes, we fine-mapped xa13, a fully recessive gene for Xoo resistance, to a DNA fragment of 14.8 kb using the map-based cloning strategy and a series of sequence-based molecular markers. Sequence analysis of this fragment indicated that this region contains only two apparently intact candidate genes (an extensin-like gene and a homologue of nodulin MtN3) and the 5' end of a predicted hypothetical gene. These results will greatly facilitate the isolation and characterization of xa13. Four PCR-based markers, E6a, SR6, ST9 and SR11 that were tightly linked to the xa13 locus, were also developed. These markers will be useful tools for the marker-assisted selection of xa13 in breeding programs.

Chromosomes, Plant↗
PubMed2005

QTL mapping of root traits in a doubled haploid population from a cross between upland and lowland japonica rice in three environments.

To genetically dissect drought resistance associated with japonica upland rice, we evaluated a doubled haploid (DH) population from a cross between two japonica cultivars for seven root traits under three different growing conditions (upland, lowland and upland in PVC pipe). The traits included basal root thickness (BRT), total root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW), ratio of root fresh weight to shoot fresh weight (RFW/SFW) and ratio of root dry weight to shoot dry weight (RDW/SDW). The BRT was significantly correlated with the index of drought resistance, which was defined as the ratio of yield under the stress of the upland condition to that under the normal lowland condition. A complete genetic linkage map with 165 molecular markers covering 1,535 cM was constructed. Seven additive quantitative trait loci (QTLs) and 15 pairs of epistatic loci for BRT and RN were identified under upland and lowland conditions, and 12 additive QTLs and 17 pairs of epistatic QTLs for BRT, RN, MRL, RFW, RFW/SFW and RDW/SDW were identified under the PVC pipe condition. Four additive QTLs and one pair of epistatic QTLs controlling IDR were also found. These QTLs individually explained up to 25.6% of the phenotypic variance. QTL x environment (Q x E) interactions were detected for all root traits, and the contributions of these interactions ranged from 1.1% to 19.9%. Five co-localized QTLs controlling RFW and RDW, RFW/SFW, RDW/SDW and IDR, BRT and RN, RN, MRL and IDR were found. Four types of QTLs governing BRT and RN were classified by their detection in the upland and lowland conditions. Some common QTLs for root traits across different backgrounds were also revealed. These co-localized QTLs and common QTLs will facilitate marker-assisted selection for root traits in rice breeding programs.

Adaptation, Physiological↗
PubMed2004

Joint mapping of quantitative trait Loci for multiple binary characters.

Joint mapping for multiple quantitative traits has shed new light on genetic mapping by pinpointing pleiotropic effects and close linkage. Joint mapping also can improve statistical power of QTL detection. However, such a joint mapping procedure has not been available for discrete traits. Most disease resistance traits are measured as one or more discrete characters. These discrete characters are often correlated. Joint mapping for multiple binary disease traits may provide an opportunity to explore pleiotropic effects and increase the statistical power of detecting disease loci. We develop a maximum-likelihood method for mapping multiple binary traits. We postulate a set of multivariate normal disease liabilities, each contributing to the phenotypic variance of one disease trait. The underlying liabilities are linked to the binary phenotypes through some underlying thresholds. The new method actually maps loci for the variation of multivariate normal liabilities. As a result, we are able to take advantage of existing methods of joint mapping for quantitative traits. We treat the multivariate liabilities as missing values so that an expectation-maximization (EM) algorithm can be applied here. We also extend the method to joint mapping for both discrete and continuous traits. Efficiency of the method is demonstrated using simulated data. We also apply the new method to a set of real data and detect several loci responsible for blast resistance in rice.

Algorithms↗
PubMed2003

A high-density genetic recombination map of sequence-tagged sites for sorghum, as a framework for comparative structural and evolutionary genomics of tropical grains and grasses.

We report a genetic recombination map for Sorghum of 2512 loci spaced at average 0.4 cM ( approximately 300 kb) intervals based on 2050 RFLP probes, including 865 heterologous probes that foster comparative genomics of Saccharum (sugarcane), Zea (maize), Oryza (rice), Pennisetum (millet, buffelgrass), the Triticeae (wheat, barley, oat, rye), and Arabidopsis. Mapped loci identify 61.5% of the recombination events in this progeny set and reveal strong positive crossover interference acting across intervals of </=50 cM. Significant variations in DNA marker density are related to possible centromeric regions and to probable chromosome structural rearrangements between Sorghum bicolor and S. propinquum, but not to variation in levels of intraspecific allelic richness. While cDNA and genomic clones are similarly distributed across the genome, SSR-containing clones show different abundance patterns. Rapidly evolving hypomethylated DNA may contribute to intraspecific genomic differentiation. Nonrandom distribution patterns of multiple loci detected by 357 probes suggest ancient chromosomal duplication followed by extensive rearrangement and gene loss. Exemplifying the value of these data for comparative genomics, we support and extend prior findings regarding maize-sorghum synteny-in particular, 45% of comparative loci fall outside the inferred colinear/syntenic regions, suggesting that many small rearrangements have occurred since maize-sorghum divergence. These genetically anchored sequence-tagged sites will foster many structural, functional and evolutionary genomic studies in major food, feed, and biomass crops.

Biological Evolution↗
PubMed2002

Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.).

A total of 2414 new di-, tri- and tetra-nucleotide non-redundant SSR primer pairs, representing 2240 unique marker loci, have been developed and experimentally validated for rice (Oryza sativa L.). Duplicate primer pairs are reported for 7% (174) of the loci. The majority (92%) of primer pairs were developed in regions flanking perfect repeats > or = 24 bp in length. Using electronic PCR (e-PCR) to align primer pairs against 3284 publicly sequenced rice BAC and PAC clones (representing about 83% of the total rice genome), 65% of the SSR markers hit a BAC or PAC clone containing at least one genetically mapped marker and could be mapped by proxy. Additional information based on genetic mapping and "nearest marker" information provided the basis for locating a total of 1825 (81%) of the newly designed markers along rice chromosomes. Fifty-six SSR markers (2.8%) hit BAC clones on two or more different chromosomes and appeared to be multiple copy. The largest proportion of SSRs in this data set correspond to poly(GA) motifs (36%), followed by poly(AT) (15%) and poly(CCG) (8%) motifs. AT-rich microsatellites had the longest average repeat tracts, while GC-rich motifs were the shortest. In combination with the pool of 500 previously mapped SSR markers, this release makes available a total of 2740 experimentally confirmed SSR markers for rice, or approximately one SSR every 157 kb.

Chromosome Mapping↗