Wang, A.-y., Li, Y. and Zhang, C.-q. 2012. QTL mapping for stay-green in maize ( Zea mays ). Can. J. Plant Sci. 92: 249–256. Stay-green is a desirable character for crop production. In order to explore the genetic basis for stay-green traits in maize, 112 polymorphic simple sequence repeat (SSR) markers were used to analyze 189 F2 individuals derived from a single cross of inbred lines A150-3-2 (a stay-green inbred line) and Mo17 (a normal inbred line). A total of 14 quantitative trait loci (QTLs) were detected for three stay-green related traits, green leaf area per plant at 30 d after flowering (GLA2), green leaf area per plant at the grain-ripening stage (GLA3), and left green leaf number per plant at the grain-ripening stage (LLN). Single QTL explained from 3.16 to 12.50% of the phenotypic variance. Among them, three were major QTLs. In addition, we analyzed the other two traits, green leaf area per plant in the whole growing period (GLA1) and total leaf number per plant in the whole growing period (TLN), and detected eight QTLs for them. Our results will be helpful to the maize breeders for marker-assisted selection.
Nonoverlapping sequential pattern mining is an important type of sequential pattern mining (SPM) with gap constraints, which not only can reveal interesting patterns to users but also can effectively reduce the search space using the Apriori (anti-monotonicity) property. However, the existing algorithms do not focus on attributes of interest to users, meaning that existing methods may discover many frequent patterns that are redundant. To solve this problem, this article proposes a task called nonoverlapping three-way sequential pattern (NTP) mining, where attributes are categorized according to three levels of interest: strong, medium, and weak interest. NTP mining can effectively avoid mining redundant patterns since the NTPs are composed of strong and medium interest items. Moreover, NTPs can avoid serious deviations (the occurrence is significantly different from its pattern) since gap constraints cannot match with strong interest patterns. To mine NTPs, an effective algorithm is put forward, called NTP-Miner, which applies two main steps: support (frequency occurrence) calculation and candidate pattern generation. To calculate the support of an NTP, depth-first and backtracking strategies are adopted, which do not require creating a whole Nettree structure, meaning that many redundant nodes and parent–child relationships do not need to be created. Hence, time and space efficiency is improved. To generate candidate patterns while reducing their number, NTP-Miner employs a pattern join strategy and only mines patterns of strong and medium interest. Experimental results on stock market and protein datasets show that NTP-Miner not only is more efficient than other competitive approaches but can also help users find more valuable patterns. More importantly, NTP mining has achieved better performance than other competitive methods in clustering tasks. Algorithms and data are available at: https://github.com/wuc567/Pattern-Mining/tree/master/NTP-Miner .
A novel type of adsorptive material, sodium dodecylbenzenesulfonate (SDBS)-citrate-layered double hydroxide (LDH), was synthesized by modifying Mg-Al LDH with both SDBS and citrate using the ionexchange method for the first time. Modified LDH was characterized by powder X-ray diffraction, Fourier transform infrared spectroscopy, low-temperature N 2 adsorption, and elemental analysis. Results indicated that DBS -and citrate 3 -anions were intercalated in the LDH interlayers, and surface hydrophobicity increased after modification. SDBS-citrate-LDH can simultaneously adsorb p-cresol and Cu 2 + (or Cd 2 + ) from the mixed solution. p-Cresol adsorption was attributed to a partition retention mechanism (adsolubilization of p-cresol into the interlayer three-dimensional organic phase formed by DBS -anions). Cu 2 + (or Cd 2 + ) adsorption was dominated by formation of complexes between Cu 2 + (or Cd 2 + ) and citrate 3 -anions in the interlayer of modified LDH. Negative values of DG o and DH o observed for p-cresol, Cu 2 + , and Cd 2 + adsorption confirmed the spontaneity and exothermic nature, respectively, of the removal process. Negative value of DS o revealed decreased randomness after adsorption. All results indicated potential application of SDBS-citrate-LDH in treating wastewater containing both organic compounds and heavy metals, which are frequently encountered together.
Spinal muscular atrophy (SMA) is a common autosomal recessive neuromuscular disorder caused by mutations of the survival of motor neuron 1 (SMN1) gene. Approximately 90-95% of SMA patients have a homozygous deletion of SMN1, and 5-10% of patients are believed to have subtle mutations. The molecular diagnosis of SMN1 subtle mutations is hampered by a highly homologous SMN2 gene. It is important to establish a rational molecular diagnostic procedure for SMN1 subtle mutations. We analyzed the SMN1 mutations in nine nonhomozygous patients by the following procedures: multiplex ligation-dependent probe amplification, genomic sequencing, T-A cloning on cDNA or genomic level, and/or real-time quantitative analysis. By the above molecular diagnostic procedure, six SMN1 subtle mutations, including c.5C>G(p.Ala2Gly), c.22_23 insA (p.Ser8LysfsX23), c.40G>T(p.Glu14X), c.43C>T(p.Gln15X), c.683T>A(p.Leu228X), and c.56delT(p.Val19GlyfsX21), were identified in nine Chinese patients. p.Glu14X has not been reported previously. Compared with the level of full-length SMN1 transcripts in the healthy carriers (14.1±4.5), the patient with p.Ala2Gly had no significant reduction (13.9±3.64, p=0.955). However, the levels in the patients carrying other mutations were significantly reduced (0.27±0.139 to 13.9±3.64, p=0.000-0.004). We present a reliable and rational diagnostic procedure for SMN1 subtle mutations, which would be helpful in molecular diagnosis of SMA compound heterozygotes. Our work extends the SMN1 mutation spectrum.
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