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Genes Genomics ; 42(9): 997-1010, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32676852


BACKGROUND: Waxy maize (Zea mays L. sinensis Kulesh) is a mutant of maize (Zea mays L.) with a mutation at Waxy1 (Wx1) gene locus. The seed of waxy maize has higher viscosity compared to regular maize. By now, we know little about the expression patterns of genes that involved in the seed development of waxy maize. OBJECTIVE: By analyzing the transcriptome data during waxy maize seed development, we attempt to dig out the genes that may influence the seed development of waxy maize. METHODS: The seeds of waxy maize inbred line SWL01 from six phases after pollination were used to do RNA-seq. Bioinformatics methods were used to analyze the expression patterns of the expressed genes, to identify the genes involved in waxy maize seed development. RESULTS: A total of 24,546 genes including 1611 transcription factors (TFs) were detected during waxy maize seed development. Coexpression analysis of expressed genes revealed the dynamic processes of waxy maize seed development. Particularly, 2457 genes including 177 TFs were specially expressed in waxy maize seed, some of which mainly involved in the process of seed dormancy and maturation. In addition, 2681, 5686, 4491, 4386, 3669 and 4624 genes were identified to be differential expressed genes (DEGs) at six phases compared to regular maize B73, and 113 DEGs among them may be key genes that lead the difference of seed development between waxy and regular maizes in milk stage. CONCLUSION: In summary, we elucidated the expression patterns of expressed genes during waxy maize seed development globally. A series of genes that associated with seed development were identified in our research, which may provide an important resource for functional study of waxy maize seed development to help molecular assisted breeding.

Theor Appl Genet ; 133(10): 2869-2879, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32607592


KEY MESSAGE: Genomic selection with a multiple-year training population dataset could accelerate early-stage testcross testing by skipping the first-stage yield testing, which significantly saves the time and cost of early-stage testcross testing. With the development of doubled haploid (DH) technology, the main task for a maize breeder is to estimate the breeding values of thousands of DH lines annually. In early-stage testcross testing, genomic selection (GS) offers the opportunity of replacing expensive multiple-environment phenotyping and phenotypic selection with lower-cost genotyping and genomic estimated breeding value (GEBV)-based selection. In the present study, a total of 1528 maize DH lines, phenotyped in multiple-environment trials in three consecutive years and genotyped with a low-cost per-sample genotyping platform of rAmpSeq, were used to explore how to implement GS to accelerate early-stage testcross testing. Results showed that the average prediction accuracy estimated from the cross-validation schemes was above 0.60 across all the scenarios. The average prediction accuracies estimated from the independent validation schemes ranged from 0.23 to 0.32 across all the scenarios, when the one-year datasets were used as training population (TRN) to predict the other year data as testing population (TST). The average prediction accuracies increased to a range from 0.31 to 0.42 across all the scenarios, when the two-years datasets were used as TRN. The prediction accuracies increased to a range from 0.50 to 0.56, when the TRN consisted of two-years of breeding data and 50% of third year's data converted from TST to TRN. This information showed that GS with a multiple-year TRN set offers the opportunity to accelerate early-stage testcross testing by skipping the first-stage yield testing, which significantly saves the time and cost of early-stage testcross testing.

Environ Sci Pollut Res Int ; 21(9): 6016-24, 2014 May.
Artigo em Inglês | MEDLINE | ID: mdl-24464080


Formaldehyde is classified as a human carcinogen that may cause nasopharyngeal cancer and probably leukemia. The effects of environmental and nutritional factors on fungal growth and the biodegradation of formaldehyde were investigated. Fungal strains SGFA1 and SGFA3 isolated from untreated sewage sediment samples collected from heavily formaldehyde-contaminated areas were identified using morphological characteristics and molecular techniques and named as Aspergillus nomius SGFA1 and Penicillium chrysogenum SGFA3. Results indicate that SGFA1 and SGFA3 completely consumed 3,000 and 900 mg l(-1) of formaldehyde, respectively, within 7 days under optimized conditions. Quantitative real-time PCR analyses and enzyme activity analyses demonstrated that glutathione-dependent formaldehyde dehydrogenase (GDFADH) and formate dehydrogenase (FDH) pathway may play a functional role in enhancing formaldehyde-degrading capability in SGFA1. Both fungi have potential use for remediation of formaldehyde pollution.

Poluentes Ambientais/metabolismo , Formaldeído/metabolismo , Fungos/metabolismo , Biodegradação Ambiental , Fungos/classificação , Fungos/genética , Fungos/isolamento & purificação , Genes Fúngicos
Mol Biol Rep ; 40(6): 3901-11, 2013 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-23559340


MADS-box genes encode important transcription factors in plants that are involved in many processes during plant growth and development. An investigation of the soybean genome revealed 106 putative MADS-box genes. These genes were classified into two classes, type I and type II, based on phylogenetic analysis. The soybean type II group has 72 members, which is higher than that of Arabidopsis, indicating that soybean type II genes have undergone a higher rate of duplication and/or a lower rate of gene loss after duplication. Soybean MADS-box genes are present on all chromosomes. Like Arabidopsis and rice MADS-box genes, soybean MADS-box genes expanded through tandem gene duplication and segmental duplication events. There are many duplicate genes distributed across the soybean genome, with two genomic regions, i.e., MADS-box gene hotspots, where MADS-box genes with high degrees of similarity are clustered. Analysis of high-throughput sequencing data from soybean at different developmental stages and in different tissues revealed that MADS-box genes are expressed in embryos of various stages and in floral buds. This expression pattern suggests that soybean MADS-box genes play an important role in soybean growth and floral development.

Perfilação da Expressão Gênica , Regulação da Expressão Gênica de Plantas , Genoma de Planta/genética , Proteínas de Domínio MADS/genética , Soja/genética , Motivos de Aminoácidos , Arabidopsis/genética , Cromossomos de Plantas/genética , Sequência Conservada/genética , Duplicação Gênica , Genes de Plantas/genética , Proteínas de Domínio MADS/química , Proteínas de Domínio MADS/metabolismo , Filogenia
Mol Biol Rep ; 38(6): 3605-13, 2011 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-21104018


The Arabidopsis gene FRO6(AtFRO6) encodes ferric chelate reductase and highly expressed in green tissues of plants. We have expressed the gene AtFRO6 under the control of a 35S promoter in transgenic tobacco plants. High-level expression of AtFRO6 in transgenic plants was confirmed by northern blot analysis. Ferric reductase activity in leaves of transgenic plants grown under iron-sufficient or iron-deficient conditions is 2.13 and 1.26 fold higher than in control plants respectively. The enhanced ferric reductase activity led to increased concentrations of ferrous iron and chlorophyll, and reduced the iron deficiency chlorosis in the transgenic plants, compared to the control plants. In roots, the concentration of ferrous iron and ferric reductase activity were not significantly different in the transgenic plants compared to the control plants. These results suggest that FRO6 functions as a ferric chelate reductase for iron uptake by leaf cells, and overexpression of AtFRO6 in transgenic plants can reduce iron deficiency chlorosis.

Adaptação Fisiológica , Arabidopsis/enzimologia , FMN Redutase/metabolismo , Doenças das Plantas/genética , Folhas de Planta/enzimologia , Tabaco/genética , Northern Blotting , Southern Blotting , Clorofila/metabolismo , FMN Redutase/genética , Vetores Genéticos/genética , Ferro/deficiência , Ferro/metabolismo , Plantas Geneticamente Modificadas , Transformação Genética