Browsing by Author "Wang, Zhi"

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Characterization of chromatin accessibility and gene expression reveal the key genes involved in cotton fiber elongation
(Wiley, 2023-07) Chen, Guoquan; Liu, Zhao; Li, Shengdong; Liu, Lili; Wang, Zhi; Mendu, Venugopal; Li, Fuguang; Yang, Zuoren
Cotton (Gossypium hirsutum L.) is an important economic crop, and cotton fiber is one of the longest plant cells, which provides an ideal model for the study of cell elongation and secondary cell wall synthesis. Cotton fiber length is regulated by a variety of transcription factors (TF) and their target genes; however, the mechanism of fiber elongation mediated by transcriptional regulatory networks is still unclear to a large extent. Here, we used a comparative assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) assay and RNA-seq analysis to identify fiber elongation transcription factors and genes using the short-fiber mutant ligon linless-2 (Li2) and wild type (WT). A total of 499 differential target genes were identified and GO analysis shows that differential genes are mainly involved in plant secondary wall synthesis and microtubule-binding processes. Analysis of the genomic regions preferentially accessible (Peak) has identified a number of overrepresented TF-binding motifs, highlighting sets of TFs that are important for cotton fiber development. Using ATAC-seq and RNA-seq data, we have constructed a functional regulatory network of each TF regulatory target gene and also the network pattern of TF regulating differential target genes. Further, to obtain the genes related to fiber length, the differential target genes were combined with FLGWAS data to identify the genes highly related to fiber length. Our work provides new insights into cotton fiber elongation.
Ethnobotany and diversity of medicinal plants used by the Buyi in eastern Yunnan, China
(2020-10) Xiong, Yong; Sui, Xueyi; Ahmed, Selena; Wang, Zhi; Long, Chunlin
The Buyi are a socio-linguistic group in Yunnan Province of southwest China that have a long history of using medicinal plants as part of their indigenous medical system. Given the limited written documentation of the Buyi indigenous medical system, the objective of this paper is to document the medicinal plants of the Buyi and associated traditional knowledge and transmission. Field research was conducted in four villages in Lubuge Township of Luoping County in Yunnan Province using ethnobotanical methodologies including participatory observation, semi-structured interviews, key informant interviews, and focus group discussions to elicit information on medicinal plants. In total, 120 informants (including 15 key informants who are healers) were interviewed. This study found that a total of 121 medicinal plant species belonging to 64 families are used by the Buyi including by local healers to treat different diseases. Among the medicinal plants recorded in this study, 56 species (46%) have not previously been documented in the scientific literature as having medicinal value, highlighting the pressing need for ethnobotanical documentation in indigenous communities. The most frequently used medicinal part was the leaf (24.9% of documented plants), and the most common preparation method was decoction (62.8% of medicinal). Medicinal plants were mainly used to treat rheumatism (12.4% of plants), trauma and injuries (9.6%). The documented plants are also used for other non-medicinal purposes including food, fodder, fencing, and ornamental. In addition, 35 of the medicinal plants are considered poisonous and are used by local Buyi healers for medicine. The traditional Buyi beliefs and practices associated with the documented medicinal plants likely contributes to their conservation in the environments and around Buyi communities. This study further highlights that ethnomedicinal knowledge of the Buyi is at risk of disappearing due to increased introduction and use of modern medicine in Buyi communities, livelihood changes, rapid modernization, and urbanization. Research, policy, and community programs are urgently needed to conserve the biocultural diversity associated with the Buyi medical system including ethnobotanical knowledge towards supporting both environmental and human wellbeing.
Measuring the predictability of life outcomes with a scientific mass collaboration
(2020-04) Salganik, Matthew J.; Lundberg, Ian; Kindel, Alexander T.; Ahearn, Caitlin E.; Al-Ghoneim, Khaled; Almaatouq, Abdullah; Altschul, Drew M.; Brand, Jennie E.; Carnegie, Nicole B.; Compton, Ryan James; Datta, Debanjan; Davidson, Thomas; Filippova, Anna; Gilroy, Connor; Goode, Brian J.; Jahani, Eaman; Kashyap, Ridhi; Kirchner, Antje; McKay, Stephen; Morgan, Allison; Pentland, Alex; Polimis, Kivan; Raes, Louis; Rigobon, Daniel E.; Roberts, Claudia V.; Stanescu, Diana M.; Suhara, Yoshihiko; Usmani, Adaner; Wang, Erik H.; Baer-Bositis, Livia; Buchi, Moritz; Chung, Bo-Ryehn; Eggert, William; Faletto, Gregory; Fan, Zhilin; Freese, Jeremy; Gadgil, Tejomay; Gagne, Josh; Gao, Yue; Halpern-Manners, Andrew; Hashim, Sophia P.; Hausen, Sonia; He, Guanhua; Higuera, Kimberly; Hogan, Bernie; Horwitz, Ilana M.; Hummel, Lisa M.; Jain, Naman; Jin, Kun; Jurgens, David; Kaminski, Patrick; Karapetyan, Areg; Kim, E. H.; Leizman, Ben; Liu, Naijia; Moser, Malte; Mack, Andrew E.; Mahajan, Mayank; Mandell, Noah; Marahrens, Helge; Mercado-Garcia, Diana; Mocz, Viola; Mueller-Gastell, Katariina; Musse, Ahmed; Niu, Qiankun; Nowak, William; Omidvar, Hamidreza; Or, Andrew; Ouyang, Karen; Pinto, Katy M.; Porter, Ethan; Porter, Kristin E.; Qian, Crystal; Rauf, Tamkinat; Sargsyan, Anahit; Schaffner, Thomas; Schnabel, Landon; Schonfeld, Bryan; Sender, Ben; Tang, Jonathan D.; Tsurkov, Emma; van Loon, Austin; Varol, Onur; Wang, Xiafei; Wang, Zhi; Wang, Flora; Weissman, Samantha; Whitaker, Kristie; Wolters, Maria K.; Woon, Wei Lee; Wu, James; Wu, Catherine; Yang, Kengran; Yin, Jingwen; Zhao, Bingyu; Zhu, Chenyun; Brooks-Gunn, Jeanne; Engelhardt, Barbara E.; Hardt, Moritz; Knox, Dean; Levy, Karen; Narayanan, Arvind; Stewart, Brandon M.; Watts, Duncan J.; McLanahan, Sara
How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.