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| 1 | Identification of genomic regions determining flower and pod numbers development in soybean (Glycine max L.)显示文摘Flower and pod numbers per plant are important agronomic traits underlying soybean yield. So far quantitative trait loci (QTL) detected for flower and pod-related traits have mainly focused on the final stage, and might therefore have ignored genetic effects expressed during a specific developmental stage. Here, dynamic expressions of QTL for flower and pod numbers were identified using 152 recom-binant inbred lines (RILs) and a linkage map of 306 markers. Wide genetic variation was found among RILs; 17 unconditional and 18 conditional QTL were detected for the two traits at different developmental stages over two years. Some QTL were detected only at one stage and others across two or more stages, indicating that soybean flower and pod numbers development may be governed by time-dependent gene expression. Three main QTL (qfn-Chr18-2, qfn-Chr20-1, and qfn-Chr19) were detected for flower number, and two main QTL (qpn-Chr11 and qpn-Chr20) were detected for pod number. The phenotypic variation explained by them ranged from 6.1% to 34.7%. The markers linked to these QTL could be used in marker-assisted selection for increasing soybean flower and pod numbers, with the ultimate aim of increasing soybean yield. Comparison of the QTL regions for flower and pod numbers traits with the related genes reported previously showed that seven and four related genes were located in the QTL regions of qfn-Chr11 and qfn-Chr19, respectively. These results provide a basis for fine mapping and cloning of flower and pod development-related genes. | Dan Zhang, Hao Cheng, Hui Wang, Hengyou Zhang, Chunying Liu, Deyue Yu National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China | 2010 | Journal of Genetics and Genomics2010，37，8： | 11 |
| 2 | GmFtsH25 overexpression increases soybean seed yield by enhancing photosynthesis and photosynthates显示文摘Increasing plant photosynthetic capacity is a promising approach to boost yields,but it is particularly challenging in C3crops,such as soybean(Glycine max(L.)Merr.).Here,we identified GmFtsH25,encoding a member of the filamentation temperature-sensitive protein H protease family,as a major gene involved in soybean photosynthesis,using linkage mapping and a genome-wide association study.Overexpressing GmFtsH25 resulted in more grana thylakoid stacks in chloroplasts and increased photosynthetic efficiency and starch content,while knocking out GmFtsH25 produced the opposite phenotypes.GmFtsH25 interacted with photosystem I light harvesting complex 2(GmLHCa2),and this interaction may contribute to the observed enhanced photosynthesis.GmFtsH25 overexpression lines had superior yield traits,such as yield per plant,compared to the wild type and knockout lines.Additionally,we identified an elite haplotype of GmFtsH25,generated by natural mutations,which appears to have been selected during soybean domestication.Our study sheds light on the molecular mechanism by which GmFtsH25 modulates photosynthesis and provides a promising strategy for improving the yields of soybean and other crops. | Li Wang Yuming Yang Zhongyi Yang Wenlong Li Dezhou Hu Huilian Yu Xiao Li Hao Cheng Guizhen Kan Zhijun Che Dan Zhang Hengyou Zhang Hui Wang Fang Huang Deyue Yu | 2023 | Journal of Integrative Plant Biology2023，65，4： | 2 |
| 3 | Reclaiming the Efficiency of Opportunistic Routing in Wireless Multi-Hop Networks显示文摘Opportunistic routing(OR) is an effective way to guarantee transmission reliability in wireless multi-hop networks.However,little research focuses on transmission efficiency.Thus,an analytical model based on open queuing network with Markov chains was proposed to evaluate the efficiency.By analyzing two typical ORs,we find duplicate transmission and collision avoidance overhead are the root reasons behind inefficiency.Therefore,a new scheme called dual priority cooperative opportunistic routing(DPCOR) was proposed.In DPCOR,forwarding candidates are configured with dual priority,which enables the network to classify forwarding candidates more effectively so as to reduce the back-off time and obtain more diversity gain.Theoretical analysis and simulation results show DPCOR achieves significant performance improvement with less time overhead compared with traditional routings and typical ORs. | WANG Dongyang WU Muqing WANG Hengyou LAI Xiaoyang LV Bo | 2014 | China Communications2014，11，8： | 1 |
| 4 | Low-rank matrix recovery with total generalized variation for defending adversarial examples显示文摘Low-rank matrix decomposition with first-order total variation(TV)regularization exhibits excellent performance in exploration of image structure.Taking advantage of its excellent performance in image denoising,we apply it to improve the robustness of deep neural networks.However,although TV regularization can improve the robustness of the model,it reduces the accuracy of normal samples due to its over-smoothing.In our work,we develop a new low-rank matrix recovery model,called LRTGV,which incorporates total generalized variation(TGV)regularization into the reweighted low-rank matrix recovery model.In the proposed model,TGV is used to better reconstruct texture information without over-smoothing.The reweighted nuclear norm and Li-norm can enhance the global structure information.Thus,the proposed LRTGV can destroy the structure of adversarial noise while re-enhancing the global structure and local texture of the image.To solve the challenging optimal model issue,we propose an algorithm based on the alternating direction method of multipliers.Experimental results show that the proposed algorithm has a certain defense capability against black-box attacks,and outperforms state-of-the-art low-rank matrix recovery methods in image restoration. | Wen LI Hengyou WANG Lianzhi HUO Qiang HE Linlin CHEN Zhiquan HE Wing W.Y.Ng | 2024 | Frontiers of Information Technology & Electronic Engineering2024，25，3： | 0 |
| 5 | RNA m^(6)A reader YTHDF2 facilitates precursor miR-126 maturation to promote acute myeloid leukemia progression显示文摘As the most common internal modification of mRNA,Ne-methyladenosine(m^(6)A)and its regulators modulate gene expression and play critical roles in various biological and patholog-ical processes including tumorigenesis.It was reported previously that m^(6)A methyltransferase(writer),methyltransferase-like 3(METTL3)adds m^(6)A in primary microRNAs(pri-miRNAs)and fa-cilitates its processing into precursor miRNAs(pre-miRNAs).However,it is unknown whether m^(6)A modification also plays a role in the maturation process of pre-miRNAs and(if so)whether such a function contributes to tumorigenesis.Here,we found that YTHDF2 is aberrantly overexpressed in acute myeloid leukemia(AML)patients,especially in relapsed patients,and plays an onco-genic role in AML.Moreover,YTHDF2 promotes expression of miR-126-3p(also known as miR-126,as it is the main product of precursor miR-126(pre-miR-126)),a miRNA that was reported as an oncomiRNA in AML,through facilitating the processing of pre-miR-126 into mature miR-126.Mechanistically,YTHDF2 recognizes m^(6)A modification in pre-miR-126 and recruits AGO2,a regulator of pre-miRNA processing,to promote the maturation of pre-miR-126.YTHDF2 posi-tively and negatively correlates with miR-126 and miR-126's downstream target genes,respec-tively,in AML patients,and forced expression of miR-126 could largely rescue YTHDF2/Ythdf2 depletion-mediated suppression on AML cell growth/proliferation and leukemogenesis,indi-cating that miR-126 is a functionally important target of YTHDF2 in AML.Overall,our studies not only reveal a previously unappreciated YTHDF2/miR-126 axis in AML and highlight the ther-apeutic potential of targeting this axis for AML treatment,but also suggest that m^(6)A plays a role in pre-miRNA processing that contributes to tumorigenesis. | Zheng Zhang Keren Zhou Li Han Andrew Small Jianhuang Xue Huilin Huang Hengyou Weng Rui Su Brandon Tan Chao Shen Wei Li Zhicong Zhao Ying Qing Xi Qin Kitty Wang Keith Leung Mark Boldin Chun-Wei Chen David Ann Zhijian Qian Xiaolan Deng Jianjun Chen Zhenhua Chen | 2024 | Genes & Diseases2024，11，1： | 0 |
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