In vitro and clinical data analysis of Osteopontin as a prognostic indicator in colorectal cancer

Osteopontin (OPN) has been shown to promote colorectal cancer (CRC) progression; however, the mechanism of OPN‐induced CRC progression is largely unknown. In this study, we found that OPN overexpression led to enhanced anchorage‐independent growth, cell migration and invasion in KRAS gene mutant cells but to a lesser extent in KRAS wild‐type cells. OPN overexpression also induced PI3K signalling, expression of Snail and Matrix metallopeptidase 9 (MMP9), and suppressed the expression of E‐cadherin in KRAS mutant cells. In human CRC specimens, a high‐level expression of OPN significantly predicted poorer survival in CRC patients and OPN expression was positively correlated with MMP9 expression, and negatively correlated with E‐cadherin expression. Furthermore, we have found that 15 genes were co‐upregulated in OPN highly expression CRC and a list of candidate drugs that may have potential to reverse the secreted phosphoprotein 1 (SPP1) gene signature by connectivity mapping. In summary, OPN is a potential prognostic indicator and therapeutic target for colon cancer.     

Comparative genomics analysis reveals gene family expansion and changes of expression patterns associated with natural adaptations of flowering time and secondary metabolism in yellow <Emphasis Type="Italic">Camellia</Emphasis>

Yellow-flowering species are unique in the genus Camellia not only for their bright yellow pigments but also the health-improving substances in petals. However, little is known regarding the biosynthesis pathways of pigments and secondary metabolites. Here, we performed comparative genomics studies in two yellow-flowered species of the genus Camellia with distinctive flowering periods. We obtained 112,190 and 89,609 unigenes from Camellia nitidissima and Camellia chuongtsoensis, respectively, and identified 9547 gene family clusters shared with various plant species and 3414 single-copy gene families. Global gene expression analysis revealed six comparisons of differentially expressed gene sets in different developmental stages of floral bud. Through the identification of orthologous pairs, conserved and specific differentially expressed genes (DEGs) between species were compared. Functional enrichment analysis suggested that the gibberellin (GA) biosynthesis pathway might be related to the alteration of flowering responses. Furthermore, the expression patterns of secondary metabolism pathway genes were analyzed between yellow- and red-flowered Camellias. We showed that the key enzymes involved in glycosylation of flavonoids displayed differential expression patterns, indicating that the direct glycosylation of flavonols rather than anthocyanins was pivotal to coloration and health-improving metabolites in the yellow Camellia petals. Finally, the gene family analysis of UDP-glycosyltransferases revealed an expansion of group C members in C. nitidissima. Through comparative genomics analysis, we demonstrate that changes of gene expression and gene family members are critical to the variation of natural traits. This work provides valuable insights into the molecular regulation of trait adaptations of floral pigmentation and flowering timing.     

Global patterns of Rhododendron diversity: The role of evolutionary time and diversification rates

Aim

Understanding the evolution of the latitudinal diversity gradient (i.e. increase in species diversity towards the tropics) is a prominent issue in ecology and biogeography. Disentangling the relative contributions of environment and evolutionary history in shaping this gradient remains a major challenge because their relative importance has been found to vary across regions and taxa. Here, using the global distributions and a molecular phylogeny of Rhododendron, one of the largest genera of flowering plants, we aim to compare the relative contributions of contemporary environment, evolutionary time and diversification rates in generating extant species diversity patterns.

Location

Global.

Time period

Undefined.

Major taxa studied

Rhododendron.

Methods

We compiled the global distributions of all Rhododendron species, and constructed a dated molecular phylogeny using nine chloroplast genes and seven nuclear regions. By integrating these two datasets, we estimated the temporal trends of Rhododendron diversification, and explored the global patterns of its species diversity, net diversification rates, and species ages. Next, we reconstructed the geographical ancestral area of the clade. Finally, we compared the relative contribution of contemporary environment, time‐for‐speciation, and diversification rates on the species diversity pattern of Rhododendron.

Results

In contrast to the predictions of the time‐for‐speciation hypothesis, we found that although Rhododendron originated at a temperate latitude, its contemporary species diversity is highest in the tropics/subtropics, suggesting an into‐the‐tropics colonization for this genus. We found that the elevated diversification induced by heterogeneous environmental conditions in the tropics/subtropics shapes the global pattern of Rhododendron diversity.

Main conclusions

Our findings support tropical and subtropical mountains as not only biodiversity and endemism hotspots, but also as cradles for the diversification of Rhododendron. Our study emphasizes the need of unifying ecological and evolutionary approaches in order to gain comprehensive understanding of the mechanisms underlying the global patterns of plant diversity.     

Deep learning for DNase I hypersensitive sites identification

Background

The DNase I hypersensitive sites (DHSs) are associated with the cis-regulatory DNA elements. An efficient method of identifying DHSs can enhance the understanding on the accessibility of chromatin. Despite a multitude of resources available on line including experimental datasets and computational tools, the complex language of DHSs remains incompletely understood.

Methods

Here, we address this challenge using an approach based on a state-of-the-art machine learning method. We present a novel convolutional neural network (CNN) which combined Inception like networks with a gating mechanism for the response of multiple patterns and longterm association in DNA sequences to predict multi-scale DHSs in Arabidopsis, rice and Homo sapiens.

Results

Our method obtains 0.961 area under curve (AUC) on Arabidopsis, 0.969 AUC on rice and 0.918 AUC on Homo sapiens.

Conclusions

Our method provides an efficient and accurate way to identify multi-scale DHSs sequences by deep learning.

     

Nonadaptive female pursuit of extrapair copulations can evolve through hitchhiking

Mounting evidence has indicated that engaging in extrapair copulations (EPCs) might be maladaptive or detrimental to females. It is unclear why such nonadaptive female behavior evolves. In this study, we test two hypotheses about the evolution of female EPC behavior using population genetic models. First, we find that both male preference for allocating extra effort to seek EPCs and female pursuit behavior without costs can be maintained and remain polymorphic in a population via frequency‐dependent selection. However, both behaviors cannot evolve when females with pursuit behavior suffer from a decline in male parental care. Second, we present another novel way in which female pursuit behavior can evolve; indirect selection can act on this behavior through a ratchet‐like mechanism involving oscillating linkage disequilibria between the target EPC pursuit locus and two other loci determining male mate choice and a female sexual signal. Although the overall positive force of such indirect selection is relatively weak, our results suggest that it may still play a role in promoting the evolution of female EPC behavior when this behavior is nonadaptive (i.e., it is neutral) or only somewhat maladaptive (e.g., males only occasionally lower parental care when their mates pursue EPCs).     

Quorum Sensing Is a Language of Chemical Signals and Plays an Ecological Role in Algal-Bacterial Interactions

Algae are ubiquitous in the marine environment, and the ways in which they interact with bacteria are of particular interest in the field of marine ecology. The interactions between primary producers and bacteria impact the physiology of both partners, alter the chemistry of their environment, and shape microbial diversity. Although algal-bacterial interactions are well known and studied, information regarding the chemical-ecological role of this relationship remains limited, particularly with respect to quorum sensing (QS), which is a system of stimuli and response correlated to population density. In the microbial biosphere, QS is pivotal in driving community structure and regulating behavioral ecology, including biofilm formation, virulence, antibiotic resistance, swarming motility, and secondary metabolite production. Many marine habitats, such as the phycosphere, harbor diverse populations of microorganisms and various signal languages (such as QS-based autoinducers). QS-mediated interactions widely influence algal-bacterial symbiotic relationships, which in turn determine community organization, population structure, and ecosystem functioning. Understanding infochemicals-mediated ecological processes may shed light on the symbiotic interactions between algae host and associated microbes. In this review, we summarize current achievements about how QS modulates microbial behavior, affects symbiotic relationships, and regulates phytoplankton chemical-ecological processes. Additionally, we present an overview of QS-modulated co-evolutionary relationships between algae and bacterioplankton, and consider the potential applications and future perspectives of QS.