Huihui Yu

Parent-independent genotyping for constructing an ultrahigh-density linkage map based on population sequencing

Bar-coded multiplexed sequencing approaches based on new-generation sequencing technologies provide capacity to sequence a mapping population in a single sequencing run. However, such approaches usually generate low-coverage and error-prone sequences for each line in a population. Thus, it is a significant challenge to genotype individual lines in a population for linkage map construction based on low-coverage sequences without the availability of high-quality genotype data of the parental lines. In this paper, we report a method for constructing ultrahigh-density linkage maps composed of high-quality single-nucleotide polymorphisms (SNPs) based on low-coverage sequences of recombinant inbred lines. First, all potential SNPs were identified to obtain drafts of parental genotypes using a maximum parsimonious inference of recombination, making maximum use of SNP information found in the entire population. Second, high-quality SNPs were identified by filtering out low-quality ones by permutations involving resampling of windows of SNPs followed by Bayesian inference. Third, lines in the mapping population were genotyped using the high-quality SNPs assisted by a hidden Markov model. With 0.05× genome sequence per line, an ultrahigh-density linkage map composed of bins of high-quality SNPs using 238 recombinant inbred lines derived from a cross between two rice varieties was constructed. Using this map, a quantitative trait locus for grain width (GW5) was localized to its presumed genomic region in a bin of 200 kb, confirming the accuracy and quality of the map. This method is generally applicable in genetic map construction with low-coverage sequence data.

Gains in QTL Detection Using an Ultra-High Density SNP Map Based on Population Sequencing Relative to Traditional RFLP/SSR Markers

Huge efforts have been invested in the last two decades to dissect the genetic bases of complex traits including yields of many crop plants, through quantitative trait locus (QTL) analyses. However, almost all the studies were based on linkage maps constructed using low-throughput molecular markers, e.g. restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), thus are mostly of low density and not able to provide precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, we constructed an ultra-high density genetic map based on high quality single nucleotide polymorphisms (SNPs) from low-coverage sequences of a recombinant inbred line (RIL) population of rice, generated using new sequencing technology. The quality of the map was assessed by validating the positions of several cloned genes including GS3 and GW5/qSW5, two major QTLs for grain length and grain width respectively, and OsC1, a qualitative trait locus for pigmentation. In all the cases the loci could be precisely resolved to the bins where the genes are located, indicating high quality and accuracy of the map. The SNP map was used to perform QTL analysis for yield and three yield-component traits, number of tillers per plant, number of grains per panicle and grain weight, using data from field trials conducted over years, in comparison to QTL mapping based on RFLPs/SSRs. The SNP map detected more QTLs especially for grain weight, with precise map locations, demonstrating advantages in detecting power and resolution relative to the RFLP/SSR map. Thus this study provided an example for ultra-high density map construction using sequencing technology. Moreover, the results obtained are helpful for understanding the genetic bases of the yield traits and for fine mapping and cloning of QTLs.

Manipulating Broad-Spectrum Disease Resistance by Suppressing Pathogen-Induced Auxin Accumulation in Rice

Breeding crops with the quality of broad-spectrum disease resistance using genetic resources is one of the principal goals of crop improvement. However, the molecular mechanism of broad-spectrum resistance remains largely unknown. Here, we show that GH3-2, encoding an indole-3-acetic acid (IAA)-amido synthetase, mediates a broad-spectrum resistance to bacterial Xanthomonas oryzae pv oryzae and Xanthomonas oryzae pv oryzicola and fungal Magnaporthe grisea in rice (Oryza sativa). IAA, the major form of auxin in rice, results in rice more vulnerable to the invasion of different types of pathogens, which is at least partly due to IAA-induced loosening of the cell wall, the natural protective barrier of plant cells to invaders. X. oryzae pv oryzae, X. oryzae pv oryzicola, and M. grisea secrete IAA, which, in turn, may induce rice to synthesize its own IAA at the infection site. IAA induces the production of expansins, the cell wall-loosening proteins, and makes rice vulnerable to pathogens. GH3-2 is likely contributing to a minor quantitative trait locus for broad-spectrum resistance. Activation of GH3-2 inactivates IAA by catalyzing the formation of an IAA-amino acid conjugate, which results in the suppression of expansin genes. Thus, GH3-2 mediates basal resistance by suppressing pathogen-induced IAA accumulation. It is expected that, regulated by a pathogen-induced strong promoter, GH3-2 alone may be used for breeding rice with a broad-spectrum disease resistance.

A High-Density SNP Genotyping Array for Rice Biology and Molecular Breeding

A high-density single nucleotide polymorphism (SNP) array is critically important for geneticists and molecular breeders. With the accumulation of huge amounts of genomic re-sequencing data and available technologies for accurate SNP detection, it is possible to design high-density and high-quality rice SNP arrays. Here we report the development of a high-density rice SNP array and its utility. SNP probes were designed by screening more than 10 000 000 SNP loci extracted from the re-sequencing data of 801 rice varieties and an array named RiceSNP50 was produced on the Illumina Infinium platform. The array contained 51 478 evenly distributed markers, 68% of which were within genic regions. Several hundred rice plants with parent/F1 relationships were used to generate a high-quality cluster file for accurate SNP calling. Application tests showed that this array had high genotyping accuracy, and could be used for different objectives. For example, a core collection of elite rice varieties was clustered with fine resolution. Genome-wide association studies (GWAS) analysis correctly identified a characterized QTL. Further, this array was successfully used for variety verification and trait introgression. As an accurate high-throughput genotyping tool, RiceSNP50 will play an important role in both functional genomics studies and molecular breeding.

Rice functional genomics research: Progress and implications for crop genetic improvement

Rice is a staple food crop and has become a reference of monocot plant for functional genomic research. With the availability of high quality rice genome sequence, there has been rapid accumulation of functional genomic resources, including: large mutant libraries by T-DNA insertion, transposon tagging, and chemical mutagenesis; global expression profiles of the genes in the entire life cycle of rice growth and development; full-length cDNAs for both indica and japonica rice; sequences from resequencing large numbers of diverse germplasm accessions. Such resource development has greatly accelerated gene cloning. By the end of 2010, over 600 genes had been cloned using various methods. Many of the genes control agriculturally useful traits such as yield, grain quality, resistances to biotic and abiotic stresses, and nutrient-use efficiency, thus have potential utility in crop genetic improvement. This review was aimed to provide a comprehensive summary of such progress. We also presented our perspective for future studies.

A global analysis of QTLs for expression variations in rice shoots at the early seedling stage

Analyses of quantitative trait loci (QTLs) for expression levels (eQTLs) of genes reveal a genetic relationship between expression variation and the regulator, thus unlocking information for identifying the regulatory network. Oligo-nucleotide expression microarrays hybridized with RNA can simultaneously provide data for molecular markers and transcript abundance. In this study, we used an Affymetrix GeneChip Rice Genome Array to analyze eQTLs in rice shoots at 72 h after germination from 110 recombinant inbred lines (RILs) derived from a cross between Zhenshan 97 and Minghui 63. In total, 1632 single-feature polymorphisms (SFPs) plus 23 PCR markers were identified and placed into 601 recombinant bins, spanning 1459 cM in length, which were used as markers to genotype the RILs. We obtained 16,372 expression traits (e-traits) each with at least one eQTL, resulting in 26,051 eQTLs in total, including both cis- and trans-eQTLs. We also identified 171 eQTL hot spots in the rice genome, each of which controls transcript variations of many e-traits. Gene ontology analysis revealed an enrichment of certain functional categories of genes in some of the eQTL hot spots. In particular, eQTLs for e-traits involving the DNA metabolic process was significantly enriched in several eQTL hot spots on chromosomes 3, 5 and 10. Several e-traits co-localizing with cis-eQTLs showed significant correlations with hundreds of e-traits, indicating possible co-regulation. We also detected correlations between QTLs for shoot dry weight and eQTLs, revealing possible candidate genes for the trait. These results provided clues for the identification and characterization of the regulatory network in the whole genome at the transcriptional level.

Genomic survey, characterization and expression profile analysis of the peptide transporter family in rice ( Oryza sativa L.)

BackgroundPeptide transporter (PTR) family whose member can transport di-/tripeptides and nitrate is important for plant growth and development. Although the rice (Oryza sativa L.) genome has been sequenced for a few years, a genomic survey, characterization and expression profile analysis of the PTR family in this species has not been reported.ResultsIn this study, we report a comprehensive identification, characterization, phylogenetic and evolutionary analysis of 84 PTR family members in rice (OsPTR) as well as their whole-life expression patterns. Chromosomal distribution and sequence analysis indicate that nearly 70% of OsPTR members are involved in the tandem and segmental duplication events. It suggests that genome duplication might be a major mechanism for expansion of this family. Highly conserved motifs were identified in most of the OsPTR members. Meanwhile, expression profile of OsPTR genes has been analyzed by using Affymetrix rice microarray and real-time PCR in two elite hybrid rice parents, Minghui 63 and Zhenshan 97. Seven genes are found to exhibit either preferential or tissue-specific expression during different development stages of rice. Under phytohormone (NAA, GA3 and KT) and light/dark treatments, 14 and 17 OsPTR genes are differentially expressed respectively. Ka/Ks analysis of the paralogous OsPTR genes indicates that purifying selection plays an important role in function maintenance of this family.ConclusionThese investigations add to our understanding of the importance of OsPTR family members and provide useful reference for selecting candidate genes for functional validation studies of this family in rice.

Development of genomics-based genotyping platforms and their applications in rice breeding.

Breeding by design has been an aspiration of researchers in the plant sciences for a decade. With the rapid development of genomics-based genotyping platforms and available of hundreds of functional genes/alleles in related to important traits, however, it may now be possible to turn this enduring ambition into a practical reality. Rice has a relatively simple genome comparing to other crops, and its genome composition and genetic behavior have been extensively investigated. Recently, rice has been taken as a model crop to perform breeding by design. The essential process of breeding by design is to integrate functional genes/alleles in an ideal genetic background, which requires high throughput genotyping platforms to screen for expected genotypes. With large amount of genome resequencing data and high-throughput genotyping technologies available, quite a number of genomics-based genotyping platforms have been developed. These platforms are widely used in genetic mapping, integration of target traits via marker-assisted backcrossing (MABC), pyramiding, recurrent selection (MARS) or genomic selection (GS). Here, we summarize and discuss recent exciting development of rice genomics-based genotyping platforms and their applications in molecular breeding.

An expression quantitative trait loci-guided co-expression analysis for constructing regulatory network using a rice recombinant inbred line population

The ability to reveal the regulatory architecture of genes at the whole-genome level by constructing a regulatory network is critical for understanding the biological processes and developmental programmes of organisms. Here, we conducted an eQTL-guided function-related co-expression analysis to identify the putative regulators and construct gene regulatory network. We performed an eQTL analysis of 210 recombinant inbred lines (RILs) derived from a cross between two indica rice lines, Zhenshan 97 and Minghui 63, the parents of an elite hybrid, using data obtained by hybridizing RNA samples of flag leaves at the heading stage with Affymetrix whole-genome arrays. Making use of an ultrahigh-density single-nucleotide polymorphism bin map constructed by population sequencing, 13 647 eQTLs for 10 725 e-traits were detected, comprising 5079 cis-eQTLs (37.2%) and 8568 trans-eQTLs (62.8%). The analysis revealed 138 trans-eQTLs hotspots, each of which apparently regulates the expression variations of many genes. Co-expression analysis of functionally related genes within the framework of regulator–target relationships outlined by the eQTLs led to the identification of putative regulators in the system. The usefulness of the strategy was demonstrated with the genes known to be involved in flowering. We also applied this strategy to the analysis of QTLs for yield traits, which also suggested likely candidate genes. eQTL-guided co-expression analysis may provide a promising solution for outlining a framework for the complex regulatory network of an organism.

Rice GH3 gene family: Regulators of growth and development

Auxin is an indispensable hormone throughout the lifetime of nearly all plant species. Several aspects of plant growth and development are rigidly governed by auxin, from micro to macro hierarchies; auxin also has a close relationship with plant-pathogen interactions. Undoubtedly, precise auxin levels are vitally important to plants, which have many effective mechanisms to maintain auxin homeostasis. One mechanism is conjugating amino acid to excessive indole-3-acetic acid (IAA; main form of auxin) through some GH3 family proteins to inactivate it. Our previous study demonstrated that GH3-2 mediated broad-spectrum resistance in rice (Oryza sativa L.) by suppressing pathogen-induced IAA accumulation and downregulating auxin signaling. Here, we further investigated the expression pattern of GH3-2 and other GH3 family paralogues in the life cycle of rice and presented the possible function of GH3-2 on rice root development by histochemical analysis of GH3-2 promoter:GUS reporter transgenic plants.