Chenwu Xu

Alfalfa benefits from Medicago truncatula: The RCT1 gene from M. truncatula confers broad-spectrum resistance to anthracnose in alfalfa

Alfalfa is economically the most important forage legume worldwide. A recurrent challenge to alfalfa production is the significant yield loss caused by disease. Although knowledge of molecular mechanisms underlying host resistance should facilitate the genetic improvement of alfalfa, the acquisition of such knowledge is hampered by alfalfas tetrasomic inheritance and outcrossing nature. However, alfalfa is congeneric with the reference legume Medicago truncatula, providing an opportunity to use M. truncatula as a surrogate to clone the counterparts of many agronomically important genes in alfalfa. In particular, the high degree of sequence identity and remarkably conserved genome structure and function between the two species enables M. truncatula genes to be used directly in alfalfa improvement. Here we report the map-based cloning of RCT1, a host resistance (R) gene in M. truncatula that confers resistance to multiple races of Colletotrichum trifolii, a hemibiotrophic fungal pathogen that causes anthracnose disease of alfalfa. RCT1 is a member of the Toll-interleukin-1 receptor/nucleotide-binding site/leucine-rich repeat (TIR-NBS-LRR) class of plant R genes and confers broad-spectrum anthracnose resistance when transferred into susceptible alfalfa plants. Thus, RCT1 provides a novel resource to develop anthracnose-resistant alfalfa cultivars and contributes to our understanding of host resistance against the fungal genus Colletotrichum. This work demonstrates the potential of using M. truncatula genes for genetic improvement of alfalfa.

Molecular Evolution of the CPP-like Gene Family in Plants: Insights from Comparative Genomics of Arabidopsis and Rice

CPP-like genes are members of a small family which features the existence of two similar Cys-rich domains termed CXC domains in their protein products and are distributed widely in plants and animals but do not exist in yeast. The members of this family in plants play an important role in development of reproductive tissue and control of cell division. To gain insights into how CPP-like genes evolved in plants, we conducted a comparative phylogenetic and molecular evolutionary analysis of the CPP-like gene family in Arabidopsis and rice. The results of phylogeny revealed that both gene loss and species-specific expansion contributed to the evolution of this family in Arabidopsis and rice. Both intron gain and intron loss were observed through intron/exon structure analysis for duplicated genes. Our results also suggested that positive selection was a major force during the evolution of CPP-like genes in plants, and most amino acid residues under positive selection were disproportionately located in the region outside the CXC domains. Further analysis revealed that two CXC domains and sequences connecting them might have coevolved during the long evolutionary period.

Mapping QTL for multiple traits using Bayesian statistics.

The value of a new crop species is usually judged by the overall performance of multiple traits. Therefore, in most quantitative trait locus (QTL) mapping experiments, researchers tend to collect phenotypic records for multiple traits. Some traits may vary continuously and others may vary in a discrete fashion. Although mapping QTLs jointly for multiple traits is more efficient than mapping QTLs separately for individual traits, the latter is still commonly practised in QTL mapping. This is primarily due to the lack of efficient statistical methods and computer software packages to implement the methods. Mapping multiple QTLs simultaneously in a single multivariate model has not been available, especially when categorical traits are involved. In the present study, we developed a Bayesian method to map QTLs of the entire genome for multiple traits with continuous, discrete or both types of phenotypic distribution. Instead of using the reversible jump Markov chain Monte Carlo (MCMC) for model selection, we adopt a parameter shrinkage approach to estimate the genetic effects of all marker intervals. We demonstrate the method by analysing a set of simulated data with both continuous and discrete traits. We also apply the method to mapping QTLs responsible for multiple disease resistances to the blast fungus of rice. A computer program written in SAS/IML that implements the method is freely available, on request, to academic researchers.

Genetic analysis of starch paste viscosity parameters in glutinous rice (Oryza sativa L.).

Starch paste viscosity plays an important role in estimating the cooking, eating, and processing quality of rice. The inheritance of starch paste viscosity in glutinous rice remains undefined. In the present study, 118 glutinous rice accessions were collected, and the genotypes of 17 starch synthesis-related genes (SSRG) were analyzed by using 43 gene-specific molecular markers. Association analysis indicated that 10 of 17 SSRGs were involved in controlling the rapid visco analyzer (RVA) profile parameters. Among these, the PUL gene was identified to play an important role in control of peak viscosity (PKV), hot paste viscosity (HPV), cool paste viscosity (CPV), breakdown viscosity (BDV), peak time (PeT), and paste temperature (PaT) in glutinous rice. Other SSRGs involved only a few RVA profile parameters. Furthermore, interactions between SSRGs were found being responsible for PeT, PaT, and BDV. Some of the RVA parameters, including PKV, HPV, CPV, CSV, and PaT, were mainly governed by single SSRG, whereas other parameters, such as BDV, SBV, and PeT, were controlled by a few SSRGs, functioning cooperatively. Further, three near-isogenic lines (NIL) of a japonica glutinous cv. Suyunuo as genetic background, with PUL, SSIII-1, and SSIII-2 alleles replaced with those of indica cv. Guichao 2, were employed to verify the genetic effects of the various genes, and the results were consistent with those obtained from the association analysis. These findings indicated that starch paste viscosity in glutinous rice had a complex genetic system, and the PUL gene played an important role in determining the RVA profile parameters in glutinous rice. These results provide important information for potentially improving the quality of glutinous rice.

Genomewide comparative phylogenetic and molecular evolutionary analysis of tubby-like protein family in Arabidopsis, rice, and poplar

Tubby-like proteins, which are characterized by a highly conserved tubby domain, play an important role in the maintenance and function of neuronal cells during postdifferentiation and development in mammals. In additional to the tubby domain, most tubby-like proteins in plants also possess an F-box domain. Plants also appear to harbor a large number of TLP genes. To gain insight into how TLP genes evolved in plants, we conducted a comparative phylogenetic and molecular evolutionary analysis of the tubby-like protein gene family in Arabidopsis, rice, and poplar. Genomewide screening identified 11 TLP genes in Arabidopsis, 14 in rice, and 11 in poplar. Phylogenetic trees, domain organizations, and intron/exon structures classified this family into three subfamilies and indicated that species-specific expansion contributed to the evolution of this family in plants. We determined that in rice and poplar, the tubby-like protein family had expanded mainly through segmental duplication events. Tissue-specific expression analysis indicated that functional diversification of the duplicated TLP genes was a major feature of long-term evolution. Our results also demonstrated that the tubby and F-box domains had co-evolved during the evolution of proteins containing both domains.

Molecular evolution and functional divergence of HAK potassium transporter gene family in rice （Oryza sativa L.）

The high-affinity K(+) (HAK) transporter gene family is the largest family in plant that functions as potassium transporter and is important for various aspects of plant life. In the present study, we identified 27 members of this family in rice genome. The phylogenetic tree divided the land plant HAK transporter proteins into 6 distinct groups. Although the main characteristic of this family was established before the origin of seed plants, they also showed some differences between the members of non-seed and seed plants. The HAK genes in rice were found to have expanded in lineage-specific manner after the split of monocots and dicots, and both segmental duplication events and tandem duplication events contributed to the expansion of this family. Functional divergence analysis for this family provided statistical evidence for shifted evolutionary rate after gene duplication. Further analysis indicated that both point mutant with positive selection and gene conversion events contributed to the evolution of this family in rice.

Mapping quantitative trait loci underlying triploid endosperm traits

Endosperm, which is derived from two polar nuclei fusing with one sperm, is a triploid tissue in cereals. Endosperm tissue determines the grain quality of cereals. Improving grain quality is one of the important breeding objectives in cereals. However, current statistical methods for mapping quantitative trait loci (QTL) under diploid genetic control have not been effective for dealing with endosperm traits because of the complexity of their triploid inheritance. In this paper, we derive for the first time the conditional probabilities of F3 endosperm QTL genotypes given different flanking marker genotypes in F2 plants. Using these probabilities, we develop a multiple linear regression method implemented via the iteratively reweighted least-squares (IRWLS) algorithm and a maximum likelihood method (ML) implemented via the expectation-maximization (EM) algorithm to map QTL underlying endosperm traits. We use the mean value of endosperm traits of F3 seeds as the dependent variable and the expectations of genotypic indicators for additive and dominance effect of a putative QTL flanked by a pair of markers as independent variables for IRWLS mapping. However, if an endosperm trait is measured quantitatively using a single endosperm sample, the ML mapping method can be used to separate the two dominance effects. Efficiency of the methods is verified through extensive Monte Carlo simulation studies. Results of simulation show that the proposed methods provide accurate estimates of both the QTL effects and locations with very high statistical power. With these methods, we are now ready to map endosperm traits, as we can for regular quantitative trait under diploid control.

Characterization of Rubisco Activase Genes in Maize: An α-isoform Gene Functions Alongside a β-isoform Gene

An α-isoform Rubisco activase gene contributes to the synthesis of a large polypeptide in maize. Rubisco activase (RCA) catalyzes the activation of Rubisco in vivo and plays a crucial role in regulating plant growth. In maize (Zea mays), only β-form RCA genes have been cloned and characterized. In this study, a genome-wide survey revealed the presence of an α-form RCA gene and a β-form RCA gene in the maize genome, herein referred to as ZmRCAα and ZmRCAβ, respectively. An analysis of genomic DNA and complementary DNA sequences suggested that alternative splicing of the ZmRCAβ precursor mRNA (premRNA) at its 3′ untranslated region could produce two distinctive ZmRCAβ transcripts. Analyses by electrophoresis and matrix-assisted laser desorption/ionization-tandem time-of-flight mass spectrometry showed that ZmRCAα and ZmRCAβ encode larger and smaller polypeptides of approximately 46 and 43 kD, respectively. Transcriptional analyses demonstrated that the expression levels of both ZmRCAα and ZmRCAβ were higher in leaves and during grain filling and that expression followed a specific cyclic day/night pattern. In 123 maize inbred lines with extensive genetic diversity, the transcript abundance and protein expression levels of these two RCA genes were positively correlated with grain yield. Additionally, both genes demonstrated a similar correlation with grain yield compared with three C4 photosynthesis genes. Our data suggest that, in addition to the β-form RCA-encoding gene, the α-form RCA-encoding gene also contributes to the synthesis of RCA in maize and support the hypothesis that RCA genes may play an important role in determining maize productivity.

A new statistical method for mapping QTLs underlying endosperm traits

Genetic expression for an endosperm trait in seeds of cereal crops may be controlled simultaneously by the triploid endosperm genotypes and the diploid maternal genotypes. However, current statistical methods for mapping quantitative trait loci (QTLs) underlying endosperm traits have not been effective in dealing with the putative maternal genetic effects. Combining the quantitative genetic model for diploid maternal traits with triploid endosperm traits, here we propose a new statistical method for mapping QTLs controlling endosperm traits with maternal genetic effects. This method applies the data set of both DNA molecular marker genotypes of each plant in segregation population and the quantitative observations of single endosperms in each plant to map QTL. The maximum likelihood method implemented via the expectation-maximization algorithm was used to the estimate parameters of a putative QTL. Since this method involves the maternal effect that may contribute to endosperm traits, it might be more congruent with the genetics of endosperm traits and more helpful to increasing the precision of QTL mapping. The simulation results show the proposed method provides accurate estimates of the QTL effects and locations with high statistical power.

Predicting rice hybrid performance using univariate and multivariate GBLUP models based on North Carolina mating design II

Genomic selection (GS) is more efficient than traditional phenotype-based methods in hybrid breeding. The present study investigated the predictive ability of genomic best linear unbiased prediction models for rice hybrids based on the North Carolina mating design II, in which a total of 115 inbred rice lines were crossed with 5 male sterile lines. Using 8 traits of the 575 (115 × 5) hybrids from two environments, both univariate (UV) and multivariate (MV) prediction analyses, including additive and dominance effects, were performed. Using UV models, the prediction results of cross-validation indicated that including dominance effects could improve the predictive ability for some traits in rice hybrids. Additionally, we could take advantage of GS even for a low-heritability trait, such as grain yield per plant (GY), because a modest increase in the number of top selection could generate a higher, more stable mean phenotypic value for rice hybrids. Thus this strategy was used to select superior potential crosses between the 115 inbred lines and those between the 5 male sterile lines and other genotyped varieties. In our MV research, an MV model (MV-ADV) was developed utilizing a MV relationship matrix constructed with auxiliary variates. Based on joint analysis with multi-trait (MT) or with multi-environment, the prediction results confirmed the superiority of MV-ADV over an UV model, particularly in the MT scenario for a low-heritability target trait (such as GY), with highly correlated auxiliary traits. For a high-heritability trait (such as thousand-grain weight), MT prediction is unnecessary, and UV prediction is sufficient.