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  • 2020-2024  (13)
  • Biodiversity Research  (13)
  • 1
    Online Resource
    Online Resource
    The metabolomic physics of complex diseases
    Proceedings of the National Academy of Sciences ; 2023
    In:  Proceedings of the National Academy of Sciences Vol. 120, No. 42 ( 2023-10-17)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 120, No. 42 ( 2023-10-17)
    Abstract: Human diseases involve metabolic alterations. Metabolomic profiles have served as a vital biomarker for the early identification of high-risk individuals and disease prevention. However, current approaches can only characterize individual key metabolites, without taking into account the reality that complex diseases are multifactorial, dynamic, heterogeneous, and interdependent. Here, we leverage a statistical physics model to combine all metabolites into bidirectional, signed, and weighted interaction networks and trace how the flow of information from one metabolite to the next causes changes in health state. Viewing a disease outcome as the consequence of complex interactions among its interconnected components (metabolites), we integrate concepts from ecosystem theory and evolutionary game theory to model how the health state-dependent alteration of a metabolite is shaped by its intrinsic properties and through extrinsic influences from its conspecifics. We code intrinsic contributions as nodes and extrinsic contributions as edges into quantitative networks and implement GLMY homology theory to analyze and interpret the topological change of health state from symbiosis to dysbiosis and vice versa. The application of this model to real data allows us to identify several hub metabolites and their interaction webs, which play a part in the formation of inflammatory bowel diseases. The findings by our model could provide important information on drug design to treat these diseases and beyond.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2308496120
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
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  • 2
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    Long‐read genome assembly and genetic architecture of fruit shape in the bottle gourd
    Wiley ; 2021
    In:  The Plant Journal Vol. 107, No. 3 ( 2021-08), p. 956-968
    Details
    In: The Plant Journal, Wiley, Vol. 107, No. 3 ( 2021-08), p. 956-968
    Abstract: The bottle gourd ( Lagenaria siceraria , Cucurbitaceae) is an important horticultural crop exhibiting tremendous diversity in fruit shape. The genetic architecture of fruit shape variation in this species remains unknown. We assembled a long‐read‐based, high‐quality reference genome (ZAAS_Lsic_2.0) with a contig N50 value over 390‐fold greater than the existing reference genomes. We then focused on dissection of fruit shape using a one‐step geometric morphometrics‐based functional mapping approach. We identified 11 quantitative trait loci (QTLs) responsible for fruit shape (fsQTLs), reconstructed their visible effects and revealed syntenic relationships of bottle gourd fsQTLs with 12 fsQTLs previously reported in cucumber, melon or watermelon. Homologs of several well‐known and newly identified fruit shape genes, including SUN , OFP , AP2 and auxin transporters, were comapped with bottle gourd QTLs.
    Type of Medium: Online Resource
    ISSN: 0960-7412 , 1365-313X
    URL: Issue
    URL: Article
    DOI: 10.1111/tpj.v107.3
    DOI: 10.1111/tpj.15358
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2020961-7
    SSG: 12
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  • 3
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    idopNetwork: A network tool to dissect spatial community ecology
    Wiley ; 2023
    In:  Methods in Ecology and Evolution Vol. 14, No. 9 ( 2023-09), p. 2272-2283
    Details
    In: Methods in Ecology and Evolution, Wiley, Vol. 14, No. 9 ( 2023-09), p. 2272-2283
    Abstract: 网络模型已被用作表征复杂系统内部工作的工具。而从网络中提取的拓扑和功能信息量取决于网络推理的方法和网络数据的类型。 本文提出了一种跨学科的计算模型，能从任何数据域（包括静态数据）重建信息丰富(informative)，动态(dynamic)，全方位(omnidirectional)以及个性化(personalized)的网络（idopNetwork。 本研究将idopNetwork实现为基于R的绘图工具，使用来自不同空间位置的多个物种的丰度数据来构建表征空间变化的种间相互作用网络。该工具提供了一个统一的框架，集成了包括基于异速生长的曲线拟合、功能聚类、基于LASSO的变量选择、拟动态常微分方程求解、物种丰度分解和网络可视化，以将不同空间的物种集合到特定位置的网络中。 本研究通过使用来自肠道微生物群和植物微生物群的两个数据集，分析宿主体内不同器官通过微生物群在空间上相互连接以证明该工具的实用性。鉴于生物多样性和组织在不同尺度的生物地理上有所不同，idopNetwork将广泛应用于建模和估算物种间的交互作用，挖掘其跨空间的不同功能。
    Type of Medium: Online Resource
    ISSN: 2041-210X , 2041-210X
    URL: Issue
    URL: Article
    DOI: 10.1111/mee3.v14.9
    DOI: 10.1111/2041-210X.14172
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2528492-7
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  • 4
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    The genetic control of leaf allometry in the common bean, Phaseolus vulgaris
    Springer Science and Business Media LLC ; 2020
    In:  BMC Genetics Vol. 21, No. 1 ( 2020-12)
    Details
    In: BMC Genetics, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2020-12)
    Abstract: To maximize photosynthetic efficiency, plants have evolved a capacity by which leaf area scales allometrically with leaf mass through interactions with the environment. However, our understanding of genetic control of this allometric relationship remains limited. Results We integrated allometric scaling laws expressed at static and ontogenetic levels into genetic mapping to identify the quantitative trait loci (QTLs) that mediate how leaf area scales with leaf mass and how such leaf allometry, under the control of these QTLs, varies as a response to environment change. A major QTL detected by the static model constantly affects the allometric growth of leaf area vs. leaf mass for the common bean ( Phaseolus vulgaris ) in two different environments. The ontogenetic model identified this QTL plus a few other QTLs that determine developmental trajectories of leaf allometry, whose expression is contingent heavily upon the environment. Conclusions Our results gain new insight into the genetic mechanisms of how plants program their leaf morphogenesis to adapt to environmental perturbations.
    Type of Medium: Online Resource
    ISSN: 1471-2156
    URL: Article
    DOI: 10.1186/s12863-020-00838-2
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2041497-3
    detail.hit.zdb_id: 3058779-7
    SSG: 12
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  • 5
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    A framework to model a web of linkage disequilibria for natural allotetraploid populations
    Wiley ; 2022
    In:  Methods in Ecology and Evolution Vol. 13, No. 2 ( 2022-02), p. 358-366
    Details
    In: Methods in Ecology and Evolution, Wiley, Vol. 13, No. 2 ( 2022-02), p. 358-366
    Abstract: Linkage disequilibrium (LD) is an important genetic parameter used to infer the genetic diversity of natural populations and their evolutionary history. Traditionally, LD is defined as the non‐random association of non‐alleles at different loci in gametes for diploids, but has a limited use for polyploids. We formulate a framework to define tetraploid‐specific LD including (a) Hardy–Weinberg disequilibria at each locus, (b) composite digenic disequilibrium, (c) trigenic disequilibrium and (d) composite quadrigenic disequilibrium at different loci. These four types of disequilibria affect population variation singly or jointly through a web. We implement the EM algorithm to estimate each disequilibrium parameter and test its significance in allotetraploid populations. We perform computer simulation to examine the statistical properties of our computational model. Through analysing a population genetic data of allotetraploid switchgrass, we chart the genomic distribution of LD on different chromosomes from which the evolutionary history of switchgrass is inferred, demonstrating the practical usefulness of the model. We have developed a statistical model for LD analysis in allotetraploids. The model can be generalized as a tool to study the population diversity and evolution of polyploid populations.
    Type of Medium: Online Resource
    ISSN: 2041-210X , 2041-210X
    URL: Issue
    URL: Article
    DOI: 10.1111/mee3.v13.2
    DOI: 10.1111/2041-210X.13757
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2528492-7
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  • 6
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    HiG was: how to compute longitudinal GWAS data in population designs
    Oxford University Press (OUP) ; 2020
    In:  Bioinformatics Vol. 36, No. 14 ( 2020-07-30), p. 4222-4224
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 36, No. 14 ( 2020-07-30), p. 4222-4224
    Abstract: Genome-wide association studies (GWAS), particularly designed with thousands and thousands of single-nucleotide polymorphisms (SNPs) (big p) genotyped on tens of thousands of subjects (small n), are encountered by a major challenge of p ≪ n. Although the integration of longitudinal information can significantly enhance a GWAS’s power to comprehend the genetic architecture of complex traits and diseases, an additional challenge is generated by an autocorrelative process. We have developed several statistical models for addressing these two challenges by implementing dimension reduction methods and longitudinal data analysis. To make these models computationally accessible to applied geneticists, we wrote an R package of computer software, HiGwas, designed to analyze longitudinal GWAS datasets. Functions in the package encompass single SNP analyses, significance-level adjustment, preconditioning and model selection for a high-dimensional set of SNPs. HiGwas provides the estimates of genetic parameters and the confidence intervals of these estimates. We demonstrate the features of HiGwas through real data analysis and vignette document in the package. Availability and implementation https://github.com/wzhy2000/higwas. Contact rwu@phs.psu.edu Supplementary information Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4803 , 1367-4811
    URL: Article
    DOI: 10.1093/bioinformatics/btaa294
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 1468345-3
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  • 7
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    A statistical framework for recovering pseudo-dynamic networks from static data
    Oxford University Press (OUP) ; 2022
    In:  Bioinformatics Vol. 38, No. 9 ( 2022-04-28), p. 2481-2487
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 38, No. 9 ( 2022-04-28), p. 2481-2487
    Abstract: The collection of temporal or perturbed data is often a prerequisite for reconstructing dynamic networks in most cases. However, these types of data are seldom available for genomic studies in medicine, thus significantly limiting the use of dynamic networks to characterize the biological principles underlying human health and diseases. Results We proposed a statistical framework to recover disease risk-associated pseudo-dynamic networks (DRDNet) from steady-state data. We incorporated a varying coefficient model with multiple ordinary differential equations to learn a series of networks. We analyzed the publicly available Genotype-Tissue Expression data to construct networks associated with hypertension risk, and biological findings showed that key genes constituting these networks had pivotal and biologically relevant roles associated with the vascular system. We also provided the selection consistency of the proposed learning procedure and evaluated its utility through extensive simulations. Availability and implementation DRDNet is implemented in the R language, and the source codes are available at https://github.com/chencxxy28/DRDnet/. Supplementary information Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4803 , 1367-4811
    URL: Article
    DOI: 10.1093/bioinformatics/btac038
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 1468345-3
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  • 8
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    Genome-wide association studies of callus differentiation for the desert tree, Populus euphratica
    Oxford University Press (OUP) ; 2020
    In:  Tree Physiology Vol. 40, No. 12 ( 2020-12-05), p. 1762-1777
    Details
    In: Tree Physiology, Oxford University Press (OUP), Vol. 40, No. 12 ( 2020-12-05), p. 1762-1777
    Abstract: Callus differentiation is a key developmental process in plant regeneration from cells. A better understanding of the genetic architecture of callus differentiation timing can help improve tissue transformation and the efficiency of artificial propagation. In this study, we investigated genotypic variation in callus differentiation capacity among 297 diverse P. euphratica trees sampled from a natural population. We employed a genome-wide association study (GWAS) of binary and growth-based parameters to identify loci and characterize the genetic architecture and genetic network underlying regulation of callus differentiation in P. euphratica. The results of this GWAS experiment suggested potential associations controlling whether the callus could differentiate and the process of callus differentiation. We identified multiple significant quantitative trait loci (QTLs), including the genes LOG1 and LOG7 and a locus containing WOX1. We reconstructed a genetic network that visualizes how each QTL interacts uniquely with other variants, and several core QTLs were detected that are involved in the degree of callus differentiation, providing potential targets for selection. This study represents one of the first to identify genetic variants affecting callus differentiation in a forest tree. Our results suggest that callus differentiation may be a typical qualitative-quantitative trait controlled by a major gene as well as polygenes across the genome of P. euphratica. This GWAS will help to design more complex and specific molecular tools for systematically manipulating organ regeneration.
    Type of Medium: Online Resource
    ISSN: 1758-4469
    URL: Article
    DOI: 10.1093/treephys/tpaa098
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 1473475-8
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  • 9
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    Concentration properties of biopolymers via dead-end forward osmosis
    Elsevier BV ; 2024
    In:  International Journal of Biological Macromolecules Vol. 270 ( 2024-06), p. 132338-
    Details
    In: International Journal of Biological Macromolecules, Elsevier BV, Vol. 270 ( 2024-06), p. 132338-
    Type of Medium: Online Resource
    ISSN: 0141-8130
    URL: Article
    DOI: 10.1016/j.ijbiomac.2024.132338
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
    detail.hit.zdb_id: 1483284-7
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  • 10
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    The ties of brotherhood between japonica and indica rice for regional adaptation
    Springer Science and Business Media LLC ; 2022
    In:  Science China Life Sciences Vol. 65, No. 7 ( 2022-07), p. 1369-1379
    Details
    In: Science China Life Sciences, Springer Science and Business Media LLC, Vol. 65, No. 7 ( 2022-07), p. 1369-1379
    Type of Medium: Online Resource
    ISSN: 1674-7305 , 1869-1889
    URL: Article
    DOI: 10.1007/s11427-021-2019-x
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2546732-3
    detail.hit.zdb_id: 2133225-3
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