Further mapping of quantitative trait loci for female sterility in wheat (Triticum aestivum L.)

Genomic prediction of dichotomous traits with Bayesian logistic models

Bayesian methods are a popular choice for genomic prediction of genotypic values. The methodology is well established for traits with approximately Gaussian phenotypic distribution. However, numerous important traits are of dichotomous nature and the phenotypic counts observed follow a Binomial distribution. The standard Gaussian generalized linear models (GLM) are not statistically valid for this type of data. Therefore, we implemented Binomial GLM with logit link function for the BayesB and Bayesian GBLUP genomic prediction methods. We compared these models with their standard Gaussian counterparts using two experimental data sets from plant breeding, one on female fertility in wheat and one on haploid induction in maize, as well as a simulated data set. With the aid of the simulated data referring to a bi-parental population of doubled haploid lines, we further investigated the influence of training set size (N), number of independent Bernoulli trials for trait evaluation (n i ) and genetic architecture of the trait on genomic prediction accuracies and abilities in general and on the relative performance of our models. For BayesB, we in addition implemented finite mixture Binomial GLM to account for overdispersion. We found that prediction accuracies increased with increasing N and n i . For the simulated and experimental data sets, we found Binomial GLM to be superior to Gaussian models for small n i , but that for large n i Gaussian models might be used as ad hoc approximations. We further show with simulated and real data sets that accounting for overdispersion in Binomial data can markedly increase the prediction accuracy.

Inheritance of long staple fiber quality traits of Gossypium barbadense in G. hirsutum background using CSILs

Gossypium hirsutum is a high yield cotton species that exhibits only moderate performance in fiber qualities. A promising but challenging approach to improving its phenotypes is interspecific introgression, the transfer of valuable traits or genes from the germplasm of another species such as G. barbadense, an important cultivated extra long staple cotton species. One set of chromosome segment introgression lines (CSILs) was developed, where TM-1, the genetic standard in G. hirsutum, was used as the recipient parent and the long staple cotton G. barbadense Hai7124 was used as the donor parent by molecular marker-assisted selection (MAS) in BC(5)S(1–4) and BC(4)S(1–3) generations. After four rounds of MAS, the CSIL population was comprised of 174 lines containing 298 introgressed segments, of which 86 (49.4%) lines had single introgressed segments. The total introgressed segment length covered 2,948.7 cM with an average length of 16.7 cM and represented 83.3% of tetraploid cotton genome. The CSILs were highly varied in major fiber qualities. By integrated analysis of data collected in four environments, a total of 43 additive quantitative trait loci (QTL) and six epistatic QTL associated with fiber qualities were detected by QTL IciMapping 3.0 and multi-QTL joint analysis. Six stable QTL were detected in various environments. The CSILs developed and the analyses presented here will enhance the understanding of the genetics of fiber qualities in long staple G. barbadense and facilitate further molecular breeding to improve fiber quality in Upland cotton.

Phenotypic characterization and genetic analysis of a partially female-sterile mutant in Brassica napus

mfs is a partially female-sterile Brassica napus mutant derived from a spontaneous mutation. When the mutant is crossed as a female, very poor seed set is obtained, whereas it is fertile as a pollen donor. The floret of the mutant consisted of almost equal-length stamens, a short pistil, a flat style and ovary, and the stigma was chapped. Measures of pollen viability and pollen tube growth in vitro indicated that the mutation enhanced pollen viability. The papillae of mfs consisted of two conjoint bilobed domes, and the papillar cells were sparse, oblate and large at anthesis, but become withered and senesced quickly afterward. Pollen grains could germinate over the papillar cells, but pollen tubes could not penetrate into it. After flower opening, the number of organelles in mfs papillar cell decreased, the structure of it distinctly degenerated, and vacuolization was abnormally high. Genetic analysis of 3 F2 populations and 3 BC1F1 populations suggested that the mutant trait was controlled by two recessive genes.

Mapping quantitative trait loci for seed size traits in soybean (Glycine max L. Merr.)

Seed size traits in soybean--length, width and thickness--and their corresponding ratios--length-to-width, length-to-thickness and width-to-thickness--play a crucial role in determining seed appearance, quality and yield. In this study, an attempt was made to detect quantitative trait loci (QTL) for the aforementioned seed size traits in F(2:3), F(2:4) and F(2:5) populations from the direct and reciprocal crosses of Lishuizhongzihuang with Nannong 493-1, using multi-QTL joint analysis (MJA) along with composite interval mapping (CIM). A total of 121 main-effect QTL (M-QTL), six environmental effects, eight environment-by-QTL interactions, five cytoplasmic effects and 92 cytoplasm-by-QTL interactions were detected. Fifty-two common M-QTL across MJA and CIM, 21 common M-QTL in more than two populations and 5 M-QTL in all three populations showed the stability of the results. Five M-QTL had higher heritability, greater than 20%. In addition, 28 cytoplasm-by-QTL and 4 environment-by-QTL interactions were confirmed by CIM. Most M-QTL were clustered in eight chromosomal regions. Our results provide a good foundation for fine mapping, cloning and designed molecular breeding of favorable genes related to soybean seed size traits.

Functional mapping of quantitative trait loci associated with rice tillering

Several biologically significant parameters that are related to rice tillering are closely associated with rice grain yield. Although identification of the genes that control rice tillering and therefore influence crop yield would be valuable for rice production management and genetic improvement, these genes remain largely unidentified. In this study, we carried out functional mapping of quantitative trait loci (QTLs) for rice tillering in 129 doubled haploid lines, which were derived from a cross between IR64 and Azucena. We measured the average number of tillers in each plot at seven developmental stages and fit the growth trajectory of rice tillering with the Wang-Lan-Ding mathematical model. Four biologically meaningful parameters in this model--the potential maximum for tiller number (K), the optimum tiller time (t(0)), and the increased rate (r), or the reduced rate (c) at the time of deviation from t(0)--were our defined variables for multi-marker joint analysis under the framework of penalized maximum likelihood, as well as composite interval mapping. We detected a total of 27 QTLs that accounted for 2.49-8.54% of the total phenotypic variance. Nine common QTLs across multi-marker joint analysis and composite interval mapping showed high stability, while one QTL was environment-specific and three were epistatic. We also identified several genomic segments that are associated with multiple traits. Our results describe the genetic basis of rice tiller development, enable further marker-assisted selection in rice cultivar development, and provide useful information for rice production management.