Genetic Characteristics Analysis Of Ronomic Traits And Fine Mapping Of The Main Effect QTL In Seedling Stage Of CSSLs With ’Xieyou 9308’

The soil nitrogen(N), phosphorus(P) and potassium(K) deficiency is one of the important factors restricting rice production. Under low N, P and K stress conditions, rice will show a series of morphological, physiological and biochemical changes on abiotic stress such as reducing plant height to promote root growth and increasing activity of various enzymes and so on. Different rice genotypes are with different utilization efficiency of N, P and K. In this experiment, using chromosome segment substitution lines(CSSL) as material, genetic characteristics are analyzed on traits related to utilization efficiency of N, P and K. such as relative plant height(RPH), relative root length(RRL), relative dry weight of root(RDWR), relative dry weight of shoot(RDWS), relative total dry weight(RTDW), relative root number(RRN) and relative root-shoot ratio(RRS). And identification and fine mapping of previously located main effect QTL is done. Main results are as follows:1. Agar rice farming technology is a new technology which is a solid matrix of soilless culture technology explored after hundreds of trial by our research team. Agar and nutrient solution are used for configuration of culture media in this technology. Prepared agar media is put into a specially-made cabinet slot. Rice germination seeds will be planted on it after condensation. Rice plant growth in soil environment can be better simulated by using this technology of rice cultivation. Making root growth with a certain amount of resistance, the situation is closer to grow in soil environment. It has significant advantages than the hydroponic conditions of rice cultivation technology. In addition, this technology also makes it easy to test various growth traits during rice seedling stage such as physiology and biochemistry, stress, protein extracting and rice cultivation method of root scan-determination, and it is not limited by time and space effects, easy and convenient to manage.2. Using ‘zhong hui 9308’ in background of CSSLs as material, a total 76 strains, genetic characteristics are analyzed on six traits in terms of PH, RL, RN, DWS, DWR and TDW. Under low N treatment, average value of CSSLs groups RPH, RRL, RRN, RDWS, RDWR and RTDW are 88.9%, 121.0%, 116.9%, 96.5%, 132.9% and 104.9%. Frequency distribution of each trait of CSSLs groups is in line with a continuous distribution except the RDWR has two peaks. Amplitude range presents bidirectional transgressive separation. Skewness and kurtosis are less than or close to 1. Those are controlled by polygene of quantitative traits. Correlation analysis shows: there are no significant differences in correlation of pair trait such as RPH with RRL, RRN, RDWR and RRL with RRN. Differences are highly significant among the remaining traits. Under low phosphorus treatment, average value of CSSLs groups RPH, RRL, RRN, RDWS, RDWR and RTDW are 97.5%, 121.1%, 121.2%, 109.6%, 133.7% and 114.9%. All traits are between two parents except of relative RL. Correlation analysis shows: RPH with RRL and RDWR is significantly related. Other traits in pair have reached extremely significant correlation. Therein, the correlation coefficients of RDWS, RDWR with RTDW are maximum of 0.97 and 0.91 respectively. The correlation coefficients of all traits in pair are greater than 0.1 and most of them are between 0.4 and 0.7. Under low potassium treatment, average value of CSSLs groups RPH, RRL, RRN, RDWS, RDWR and RTDW are 87.7%, 105.9%, 114.2%, 101.6%, 117.4% and 105.1%. Six traits are between two parents. Correlation analysis shows: correlation between RPH and RRL is not significant. Other traits in pair have reached extremely significant correlation. Therein, RPH with RRL is significantly related. The remaining has reached extremely significant correlation. The correlation coefficient of RDWS with RTDW is maximum of 0.97. The correlation coefficients of all traits in pair are greater than 0.01.3. Using CSSLs of advanced backcross population BC4F3 as material, a major QTL-q RL4 controlling RL is identified successfully. Finally q RL4 is located on chromosome 4, in an area of 624.6 kb near the centromere. Controlling RDWR of QTL-q RDWR4, controlling RDWS of QTL-q RDWS4 and controlling the RTDW of QTL-q RTDW4 are all near q RL4. Therefore, this interval could be pleiotropic, also may contain multiple genes due to large interval. There are four QTL in chromosome 4, between molecular marker RM307 and RM5953, controlling RDWR, relative tillering, RDWS and RTDW respectively. From correlation analysis, RDWR and RDWS with RTDW are highly related. This may be pleiotropic. It can be concluded that q RL4 is a new QTL controlling RL combined with previous results. According to the Rice Annotation Project(RAP3) database(http://rapdb.dna.affrc.go.jp/), q RL4 has 89 candidate genes in this interval. It’s impossible to predict precise q RL4 of candidate genes due to too many candidate genes. The next work of this paper is to narrow the scope of the q RL4 interval, find and clone genes and carry out functional verification tests.