Quantitative trait loci analysis for the developmental behavior of tiller number in rice (Oryza sativa L.)

Yan, Jianbing; Zhu, Jun; He, Chi; Benmoussa, Mebrouk; Wu, Ping

doi:10.1007/s001220050895

Cited by 184 publications

(141 citation statements)

References 23 publications

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“…Three QTL were detected to affect tiller number trajectories during a growing season in the field. The locations for two of the QTL detected on chromosome 1 are consistent with those estimated from basic interval mapping of single traits (42), but the third QTL detected on chromosome 9 was previously undetected by interval mapping. It seems that our model has not been able to detect many other QTL detected by Yan et al (42), which may be due to the difference in the threshold criteria used to claim the existence of a QTL between the two approaches.…”

Section: Discussionsupporting

confidence: 73%

Functional mapping for genetic control of programmed cell death

Cui

Zhu

2006

Physiological Genomics

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"Naturally occurring" or "programmed" cell death (PCD) in which the cell uses specialized cellular machinery to kill itself is a ubiquitous phenomenon that occurs early in organ development. Such a cell suicide mechanism that enables metazoans to control cell number and eliminate cells threatening the organism's survival has been thought to be under genetic control. In this report, we develop a novel statistical model for mapping specific genes or quantitative trait loci (QTL) that are responsible for the PCD process based on polymorphic molecular markers. This model incorporates the biological mechanisms of PCD that undergoes two different developmental stages, exponential growth and polynomial death. We derived a parametric approach to model the exponential growth and a nonparametric approach based on the Legendre function to model the polynomial death. A series of stationary and nonstationary models has been used to approximate the structure of the covariance matrix among cell numbers at a multitude of different times. The statistical behavior of our model is investigated through simulation studies and validated by a real example in rice.quantitative trait loci; semiparametric model; mean-covariance structure model; EM-Simplex algorithm; order selection

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Section: Discussionsupporting

confidence: 73%

Functional mapping for genetic control of programmed cell death

Cui

Zhu

2006

Physiological Genomics

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“…Many studies prior to understanding factors controlling and affecting the tillering capacity in rice in terms of genetics investigation Hussain et al 2014;Uddin et al 2016), and environmental factors (Assuero and Tognetti, 2009) have been conducted comprehensively. Genetically, tillering capacity is controlled by many genes (Yan et al 1998;Miyamoto et al 2004;Luo et al 2012). One of quantitative traits characters is the continuous phenotypic variation, which could be seen from the distribution of tillering capacity in the local upland rice cultivars from East and North Kalimantan (Figure 2).…”

Section: Tillering Capacitymentioning

confidence: 99%

Yield-related traits characterization of local upland rice cultivars originated from East and North Kalimantan, Indonesia

2017

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Abstract. Nurhasanah, Sadaruddin, Sunaryo W. 2017. Yield-related traits characterization of local upland rice cultivars originated from East and North Kalimantan. Biodiversitas 18: 1165-1172. In East and North Kalimantan, rice genetic diversities were very high. Most of the local rice cultivars existed in East and North Kalimantan, are upland rice cultivars. Unfortunately, most of those cultivars have not been optimally studied and characterized for rice breeding purposes. In this study, 146 upland rice cultivars originated from East and North Kalimantan were grown in the field which was further characterized their yield parameters. Tillering capacity, productive tiller, the size and structure of panicle as well as grain characteristics were characterized in the population to select potential superior cultivars. The results showed that the phenotypic variation of tillering capacity in those local upland rice was very high. Tiller number was varied from 2 to 66 tillers, with an average of 20.92 tillers and 25 cultivars had more than 30 tillers. Large range of productive tiller was also observed in the population, ranging from 14.8 to 100% of their tillering capacity, but most of the cultivars (80%) had more than 70% productive tiller. In addition, 9 cultivars had 100% productive tillers, in which all of the tillers generated panicles. Highly significant positive correlation (0.802 ** ) was observed between productive tiller and tillering capacity. The panicle length of the local upland rice cultivars was in range from 14.5 cm to 43.5 cm, with most of the panicle size population clustered in length of 20-30 cm. In addition, 8.2% cultivars had a dense/heavy category, while 22.6% were sparse, and the rest of 70.2% had no panicle secondary branch. Variation of grain characteristics of local upland rice in the East and North Kalimantan including grain weight, grain length and width, as well as length-to-width ratio was also discussed in this study.

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“…Several papers have shown that a region around RZ667 on chromosome 6 has a large effect on heading date Lin et al, 1998;Yamamoto et al, 1998). According to published papers and genetic maps, a major photoperiod-sensitivity gene (Se-1) may localize in the same region near RZ667 on chromosome 6 (Yokoo et al, 1980;Poonyarit et al, 1989;Mackill et al, 1993;Yan et al, 1998b;Maheswaran et al, 2000). Yano et al (2000) identifi ed a genomic region of 12 kb as a candidate for Hd-1, which is allelic to Se-1 and has high homology with CONSTANTS, a gene for fl owering time in Arabidopsis.…”

Section: I F F E R E N T G E N E S a R E E X P R E S S E D A T V A mentioning

confidence: 99%

“…Many researchers have attempted to dissect the genetic basis of heading date (Mackill et al, 1993;Li et al, 1995;Lin et al, 1998;Yamamoto et al, 1998;Xing et al, 2001;Yu et al, 2002), tiller number (Ray et al, 1996;Yan et al, 1998b;Li et al, 1999;Wu et al, 1999), and plant height (Beavis et al, 1991;Li et al, 1995;Lin et al, 1995;Huang et al, 1996;Yan et al, 1998a;Xing et al, 2001;Yu et al, 2002). However, most of them put their interests on identifi cation of quantitative trait loci (QTLs) for each individual trait.…”

mentioning

confidence: 99%