Elife , IF:7.08 , 2019 Oct , V8 doi: 10.7554/eLife.47676
ASPEN, a methodology for reconstructing protein evolution with improved accuracy using ensemble models.
Program in Computational and Systems Biology, Washington University, St. Louis, United States.; Department for Biomedical Engineering, Washington University, St. Louis, United States.; Department of Biochemistry and Molecular Biology, University of Massachusetts, Amherst, United States.; Center for Biological Systems Engineering, Washington University, St. Louis, United States.; Department of Biomedical Engineering, University of Virginia, Charlottesville, United States.; Center for Public Health Genomics, University of Virginia, Charlottesville, United States.
Evolutionary reconstruction algorithms produce models of the evolutionary history of proteins or species. Such algorithms are highly sensitive to their inputs: the sequences used and their alignments. Here, we asked whether the variance introduced by selecting different input sequences could be used to better identify accurate evolutionary models. We subsampled from available ortholog sequences and measured the distribution of observed relationships between paralogs produced across hundreds of models inferred from the subsamples. We observed two important phenomena. First, the reproducibility of an all-sequence, single-alignment reconstruction, measured by comparing topologies inferred from 90% subsamples, directly correlates with the accuracy of that single-alignment reconstruction, producing a measurable value for something that has been traditionally unknowable. Second, topologies that are most consistent with the observations made in the ensemble are more accurate and we present a meta algorithm that exploits this property to improve model accuracy.
PMID: 31621582
Elife , IF:7.08 , 2019 Oct , V8 doi: 10.7554/eLife.48508
Bacterial survival in microscopic surface wetness.
Department of Plant Pathology and Microbiology, Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University, Rehovot, Israel.
Plant leaves constitute a huge microbial habitat of global importance. How microorganisms survive the dry daytime on leaves and avoid desiccation is not well understood. There is evidence that microscopic surface wetness in the form of thin films and micrometer-sized droplets, invisible to the naked eye, persists on leaves during daytime due to deliquescence - the absorption of water until dissolution - of hygroscopic aerosols. Here, we study how such microscopic wetness affects cell survival. We show that, on surfaces drying under moderate humidity, stable microdroplets form around bacterial aggregates due to capillary pinning and deliquescence. Notably, droplet-size increases with aggregate-size, and cell survival is higher the larger the droplet. This phenomenon was observed for 13 bacterial species, two of which - Pseudomonas fluorescens and P. putida - were studied in depth. Microdroplet formation around aggregates is likely key to bacterial survival in a variety of unsaturated microbial habitats, including leaf surfaces.
PMID: 31610846
Depress Anxiety , IF:4.702 , 2019 Oct , V36 (10) : P950-959 doi: 10.1002/da.22935
Unique and predictive relationships between components of cognitive vulnerability and symptoms of depression.
Department of Psychology, Harvard University, Cambridge, Massachusetts.; Department of Psychology, Rutgers University, New Brunswick, New Jersey.; Department of Psychological Methods, University of Amsterdam, Amsterdam, Netherlands.; Department of Psychology, Temple University, Philadelphia, Pennsylvania.; Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin.
BACKGROUND: Cognitive vulnerability theories of depression outline multiple, distinct inferential biases constitutive of cognitive vulnerability to depression. These include attributing negative events to internal, stable, and global factors, assuming that negative events will lead to further negative consequences, and inferring that negative events reflect negative characteristics about the self. Extant research has insufficiently examined these biases as distinct, limiting our understanding of how the individual cognitive vulnerability components interrelate and confer risk for depression symptoms. Thus, we conducted exploratory network analyses to examine the relationships among the five components of negative cognitive style and explore how components may differentially relate to depressive symptoms in adolescents. METHODS: Participants completed measures of negative cognitive style twice over a two-year period. We estimated Graphical Gaussian Models using contemporaneous data and computed a cross-lagged panel network using temporal data from baseline and 2-year follow-up. RESULTS: Results reveal interesting structural dynamics among facets of negative cognitive style and depressive symptoms. For example, results point to biases towards stable and future-oriented inferences as highly influential among negative cognitive style components. The temporal model revealed the internal attributions component to be heavily influenced by depressive symptoms among adolescents, whereas stable and global attributions most influenced future symptoms. CONCLUSIONS: This study presents novel approaches for investigating cognitive style and depression. From this perspective, perhaps more precise predictions can be made about how cognitive risk factors will lead to the development or worsening of psychopathology.
PMID: 31332887
BMC Genomics , IF:3.594 , 2019 Oct , V20 (1) : P750 doi: 10.1186/s12864-019-6144-9
Genome-wide identification, expression profiles and regulatory network of MAPK cascade gene family in barley.
State Key Laboratory of Crop Stress Biology in Arid Areas and College of Agronomy, Northwest A&F University, 3 Taicheng Road, Yangling, 712100, Shaanxi, China.; College of Life Science, Jiangxi Agricultural University, Nanchang, 330045, Jiangxi, China.; State Key Laboratory of Crop Stress Biology in Arid Areas and College of Agronomy, Northwest A&F University, 3 Taicheng Road, Yangling, 712100, Shaanxi, China. small@nwsuaf.edu.cn.
BACKGROUND: Mitogen-activated protein kinase (MAPK) cascade is a conserved and universal signal transduction module in organisms. Although it has been well characterized in many plants, no systematic analysis has been conducted in barley. RESULTS: Here, we identified 20 MAPKs, 6 MAPKKs and 156 MAPKKKs in barley through a genome-wide search against the updated reference genome. Then, phylogenetic relationship, gene structure and conserved protein motifs organization of them were systematically analyzed and results supported the predictions. Gene duplication analysis revealed that segmental and tandem duplication events contributed to the expansion of barley MAPK cascade genes and the duplicated gene pairs were found to undergone strong purifying selection. Expression profiles of them were further investigated in different organs and under diverse abiotic stresses using the available 173 RNA-seq datasets, and then the tissue-specific and stress-responsive candidates were found. Finally, co-expression regulatory network of MAPK cascade genes was constructed by WGCNA tool, resulting in a complicated network composed of a total of 72 branches containing 46 HvMAPK cascade genes and 46 miRNAs. CONCLUSION: This study provides the targets for further functional study and also contribute to better understand the MAPK cascade regulatory network in barley and beyond.
PMID: 31623562
BMC Plant Biol , IF:3.497 , 2019 Oct , V19 (1) : P432 doi: 10.1186/s12870-019-2026-1
Genome-wide identification and characterization of TALE superfamily genes in cotton reveals their functions in regulating secondary cell wall biosynthesis.
State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China.; College of Plant Science & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.; State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China. henglingwei@163.com.; State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Anyang, 455000, Henan, China. ysx195311@163.com.
BACKGROUND: Cotton fiber length and strength are both key traits of fiber quality, and fiber strength (FS) is tightly correlated with secondary cell wall (SCW) biosynthesis. The three-amino-acid-loop-extension (TALE) superclass homeoproteins are involved in regulating diverse biological processes in plants, and some TALE members has been identified to play a key role in regulating SCW formation. However, little is known about the functions of TALE members in cotton (Gossypium spp.). RESULTS: In the present study, based on gene homology, 46, 47, 88 and 94 TALE superfamily genes were identified in G. arboreum, G. raimondii, G. barbadense and G. hirsutum, respectively. Phylogenetic and evolutionary analysis showed the evolutionary conservation of two cotton TALE families (including BEL1-like and KNOX families). Gene structure analysis also indicated the conservation of GhTALE members under selection. The analysis of promoter cis-elements and expression patterns suggested potential transcriptional regulation functions in fiber SCW biosynthesis and responses to some phytohormones for GhTALE proteins. Genome-wide analysis of colocalization of TALE transcription factors with SCW-related QTLs revealed that some BEL1-like genes and KNAT7 homologs may participate in the regulation of cotton fiber strength formation. Overexpression of GhKNAT7-A03 and GhBLH6-A13 significantly inhibited the synthesis of lignocellulose in interfascicular fibers of Arabidopsis. Yeast two-hybrid (Y2H) experiments showed extensive heteromeric interactions between GhKNAT7 homologs and some GhBEL1-like proteins. Yeast one-hybrid (Y1H) experiments identified the upstream GhMYB46 binding sites in the promoter region of GhTALE members and defined the downstream genes that can be directly bound and regulated by GhTALE heterodimers. CONCLUSION: We comprehensively identified TALE superfamily genes in cotton. Some GhTALE members are predominantly expressed during the cotton fiber SCW thicking stage, and may genetically correlated with the formation of FS. Class II KNOX member GhKNAT7 can interact with some GhBEL1-like members to form the heterodimers to regulate the downstream targets, and this regulatory relationship is partially conserved with Arabidopsis. In summary, this study provides important clues for further elucidating the functions of TALE genes in regulating cotton growth and development, especially in the fiber SCW biosynthesis network, and it also contributes genetic resources to the improvement of cotton fiber quality.
PMID: 31623554
G3 (Bethesda) , IF:2.781 , 2019 Oct , V9 (10) : P3139-3152 doi: 10.1534/g3.119.400347
Genome-Wide Association and Gene Co-expression Network Analyses Reveal Complex Genetics of Resistance to Goss's Wilt of Maize.
Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108.; Department of Plant Pathology, University of Nebraska, Lincoln, NE 68503-0722.; Center for Plant Science Innovation, University of Nebraska, Lincoln, NE 68588-0660, and.; Department of Agronomy and Horticulture, University of Nebraska, Lincoln, NE 68503-0915.; Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108 lore0149@umn.edu.
Goss's bacterial wilt and leaf blight is a disease of maize caused by the gram positive bacterium Clavibacter michiganensis subsp. nebraskensis (Cmn). First discovered in Nebraska, Goss's wilt has now spread to major maize growing states in the United States and three provinces in Canada. Previous studies conducted using elite maize inbred lines and their hybrids have shown that resistance to Goss's wilt is a quantitative trait. The objective of this study was to further our understanding of the genetic basis of resistance to Goss's wilt by using a combined approach of genome-wide association mapping and gene co-expression network analysis. Genome-wide association analysis was accomplished using a diversity panel consisting of 555 maize inbred lines and a set of 450 recombinant inbred lines (RILs) from three bi-parental mapping populations, providing the most comprehensive screening of Goss's wilt resistance to date. Three SNPs in the diversity panel and 10 SNPs in the combined dataset, including the diversity panel and RILs, were found to be significantly associated with Goss's wilt resistance. Each significant SNP explained 1-5% of the phenotypic variation for Goss's wilt (total of 8-11%). To augment the results of genome-wide association mapping and help identify candidate genes, a time course RNA sequencing experiment was conducted using resistant (N551) and susceptible (B14A) maize inbred lines. Gene co-expression network analysis of this time course experiment identified one module of 141 correlated genes that showed differential regulation in response to Cmn inoculations in both resistant and susceptible lines. SNPs inside and flanking these genes explained 13.3% of the phenotypic variation. Among 1,000 random samples of genes, only 8% of samples explained more phenotypic variance for Goss's wilt resistance than those implicated by the co-expression network analysis. While a statistically significant enrichment was not observed (P < 0.05), these results suggest a possible role for these genes in quantitative resistance at the field level and warrant more research on combining gene co-expression network analysis with quantitative genetic analyses to dissect complex disease resistance traits. The results of the GWAS and co-expression analysis both support the complex nature of resistance to this important disease of maize.
PMID: 31362973
Heliyon , 2019 Oct , V5 (10) : Pe02530 doi: 10.1016/j.heliyon.2019.e02530
PVCTools: parallel variation calling tools.
China Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou, 450001, China.; Computer Science and Technology, Sichuan University, Chengdu, 450000, China.; Zhengzhou Tongbiao Environmental Testing Co., LTD, Zhengzhou, 450001, China.
As the development of sequencing technology, it is now possible to sequence individuals of each species. Although a number of different tools have been developed to detect individual variations, most of them cannot be run in parallel modes. To accelerate variation detection, PVCTools is introduced in this study. PVCTools splits the reference genome and alignment files into small pieces and runs them in parallel mode. Meanwhile, boundary noise is also considered in PVCTools. From the result of three different sets of test data, PVCTools performs much faster than most other current tools. At the same time, it keeps similar accuracy with other tools. PVCTools is free and open source software. The development of sequencing technology and growing sample numbers will make performance improvements such as PVCTools increasingly interesting.
PMID: 31667383