De novo domestication: a new way for crop design and breeding.

The impending global climate change presents significant challenges to agricultural production. It is imperative to find approaches to ensure sustained growth in food production while reducing agricultural input, in order to meet the needs of worldwide people for nutritious food supply. One of the effective strategies to address this challenge is still the development of new crop varieties with high yield, stable yield, environmental friendliness and rich nutrition. The creation of new crop cultivars depends largely on the expansion of genetic resources and the innovation of breeding techniques. De novo domestication is an innovative breeding strategy for developing new crop varieties. It involves utilizing undomesticated or semi-domesticated plants with desirable traits as founder species for breeding. The process involves rapid domestication of wild plants through the redesign of agronomic traits and the introduction of domestication genes to meet diverse human needs. In this review, we overview the history of crop domestication and genetic improvement, clarify the necessity of enriching crop diversity, and emphasize the significance of wild plants' genetic diversity in expanding the scope for crop redesign. Breeding strategy innovation is the key to accelerate crop breeding. We also discuss the feasibility and prospects of rapid developing new crops through de novo domestication.

Improving QTL mapping resolution based on genotypic sampling--a case using a RIL population.

The QTL mapping results were compared with the genotypically selected and random samples of the same size on the base of a RIL population. The results demonstrated that there were no obvious differences in the trait distribution and marker segregation distortion between the genotypically selected and random samples with the same population size. However, a significant increase in QTL detection power, sensitivity, specificity, and QTL resolution in the genotypically selected samples were observed. Moreover, the highly significant effect was detected in small size of genotypically selected samples. In QTL mapping, phenotyping is a more sensitive limiting factor than genotyping so that the selection of samples could be an attractive strategy for increasing genome-wide QTL mapping resolution. The efficient selection of samples should be more helpful for QTL maker assistant selection, fine mapping, and QTL cloning.

[QTL mapping of five agronomic traits in maize].

Agronomic traits have significant influence on stability and adaptability in maize production. In this investigation, using a population with 266 F2:3 families from Yuyu22 (Zong3 x 87-1), two-location field tests were conducted in Wuhan and Xiangfan in 2001, with a randomized complete block design, to characterize five agronomic traits: ear height, tassel branch number, stalk diameter, days to pollen, and days to silk. Correlation analysis of field performance indicated that ear height, tassel branch number and stalk diameter were significantly positive correlative with single-plant yield, days to pollen and days to silk were highly positive correlative with each other, and tassel branch number was significantly positive correlative with stalk diameter too. Utilizing data of field tests and molecular markers, Composite Interval Mapping (CIM) method was used to localize the quantitative trait loci of these traits and 500 times permutation test was conducted to have proper LOD threshold value. As the results, total seven QTL of ear height, nine QTL of tassel branch number, eight QTL of stalk diameter, nine QTL of days to pollen, and seven QTL of days to silk were mapped on 10 chromosomes of maize; all of these QTL distributed unevenly on chromosomes and trended to cluster together. According to analysis of this investigation, the phenotype correlations of quantitative traits may result from the correlations of QTL controlling those traits. Those will be helpful to further understand genetic basis of agronomic traits in maize.

[Comparative analyses of QTL for important agronomic traits between maize and rice].

The objective of this study was to assess syntenic relationships of quantitative trait loci (QTL) for important agronomic traits between maize and rice based on the comparative genomic map of maize and rice using two F(2:3) populations. Through the comparisons, it was observed that there were extensive conserved relationships of maize QTL affected plant height, row number, and kernels per row with rice QTL affected plant height, tillers per plant, and grains per panicle respectively. Sixteen of 45 QTL affecting five different maize traits were conserved compared with 12 of 38 QTL affecting five different rice traits, which provided some useful information for locating, isolating and cloning maize QTL by using the rice genomic data. In this study, one QTL in rice usually had two conserved QTL in maize, further supporting the hypothesis that there is a polyploidization event during maize evolution. It was interested in observing that there were QTL rich regions on chromosomes in maize and rice, where QTL affecting different traits were usually clustered. These results revealed that the QTL affected the same or similar traits in maize and rice may have the common origin. These results will be helpful to map, isolate and clone QTL in large genome crops, such as maize, by using rice genome information, as well as to understand the evolutionary forces that structured the organization of the grass genomes.

[Genetic analysis of segregation distortion of molecular markers in maize F2 population].

A genetic linkage map of maize was constructed using 150 SSR and 24 RFLP markers, with F2 population from an elite hybrid (Zong3 x 87-1). Among 174 markers, covering whole maize 10 chromosomes, 49 markers (28.1%) showed the genetic distortion (P < 0.05). Of the total segregation distortion markers, 11 markers (22.5%) deviated toward male parent, Zong3, while 12 markers (24.5%) deviated toward female parent, 87-1, besides 25 markers (51.0%) distorted to heterozygote. Only one marker distorted to both parents. Totally, 14 segregation distortion regions (SDRs) were detected among 9 different chromosomes. Four of them were located in near regions where gametophyte genes were mapped, indicating that segregation distortion may be caused by gametophyte genes partially. Two segregation distortion regions, SDR6-1 and SDR7-1, detected in this study, seemed to be new segregation distortion regions. In this paper, reasons for segregation distortion and effects of segregation distortion on genetic mapping and QTL analysis were discussed. Regarding to QTL analysis with single locus, segregation distortion would not affect QTL mapping, but regarding to analysis of digenic interactions for epistasis, the fewer distortion markers and larger size population would be needed.