A Step toward Next-Generation Advancements in the Internet of Things Technologies.

The Internet of Things (IoT) devices generate a large amount of data over networks; therefore, the efficiency, complexity, interfaces, dynamics, robustness, and interaction need to be re-examined on a large scale. This phenomenon will lead to seamless network connectivity and the capability to provide support for the IoT. The traditional IoT is not enough to provide support. Therefore, we designed this study to provide a systematic analysis of next-generation advancements in the IoT. We propose a systematic catalog that covers the most recent advances in the traditional IoT. An overview of the IoT from the perspectives of big data, data science, and network science disciplines and also connecting technologies is given. We highlight the conceptual view of the IoT, key concepts, growth, and most recent trends. We discuss and highlight the importance and the integration of big data, data science, and network science along with key applications such as artificial intelligence, machine learning, blockchain, federated learning, etc. Finally, we discuss various challenges and issues of IoT such as architecture, integration, data provenance, and important applications such as cloud and edge computing, etc. This article will provide aid to the readers and other researchers in an understanding of the IoT's next-generation developments and tell how they apply to the real world.

Overexpression of LT, an Oncoprotein Derived from the Polyomavirus SV40, Promotes Somatic Embryogenesis in Cotton.

Although genetic transformation has opened up a new era for cotton molecular breeding, it still suffers from the limitation problem of long transformation periods, which slows down the generation of new cotton germplasms. In this study, LT gene (SV40 large T antigen), which promotes the transformation efficiency of animal cells, was codon-optimized. Its overexpression vector was transformed into cotton. It was observed that EC (embryogenic callus) formation period was 33% shorter and transformation efficiency was slightly higher in the LT T0 generation than that of control. RNA-seq data of NEC (non-embryonic callus) and EC from LT and control revealed that more DEGs (differential expression genes) in NEC were identified than that of EC, indicating LT mainly functioned in NEC. Further KEGG, GO, and transcription factor analyses showed that DEGs were significantly enriched in brassinosteroid biosynthesis pathways and that bHLH, MYB, and AP2/ERF were the top three gene families, which are involved in EC formation. In addition, the key genes related to the auxin pathway were differentially expressed only in LT overexpression NEC, which caused early response, biosynthesis, and transportation of the hormone, resulting in EC earlier formation. In summary, the results demonstrated that LT can promote somatic embryogenesis in cotton, which provides a new strategy for improving cotton transformation and shortening EC formation time.

Activation of ABA Receptors Gene GhPYL9-11A Is Positively Correlated with Cotton Drought Tolerance in Transgenic Arabidopsis.

The sensitivity to abscisic acid (ABA) by its receptors, pyrabactin resistance-like proteins (PYLs), is considered a most important factor in activating the ABA signal pathway in response to abiotic stress. However, it is still unknown which PYL is the crucial ABA receptor mediating response to drought stress in cotton (Gossypium hirsutum L.). Here, we reported the identification and characterization of highly induced ABA receptor GhPYL9-11A in response to drought in cotton. It is observed that GhPYL9-11A was highly induced by ABA treatment. GhPYL9-11A binds to protein phosphatase 2Cs (PP2Cs) in an ABA-independent manner. Moreover, the GhPYL-11A-PP2C interactions are partially disrupted by mutations, proline (P84) and histidine (H111), in the gate-latch region. Transgenic Arabidopsis overexpressing GhPYL9-11A plants were hypersensitive to ABA during seed germination and early seedling stage. Further, the increased in root growth and up regulation of drought stress-related genes in transgenic Arabidopsis as compared to wild type confirmed the potential role of GhPYL9-11A in abiotic stress tolerance. Consistently, the expression level of GhPYL9-11A is on average higher in drought-tolerant cotton cultivars than in drought-sensitive cottons under drought treatment. In conclusion, the manipulation of GhPYL9-11A expression could be a useful strategy for developing drought-tolerant cotton cultivars.

Molecular markers and cotton genetic improvement: current status and future prospects.

Narrow genetic base and complex allotetraploid genome of cotton (Gossypium hirsutum L.) is stimulating efforts to avail required polymorphism for marker based breeding. The availability of draft genome sequence of G. raimondii and G. arboreum and next generation sequencing (NGS) technologies facilitated the development of high-throughput marker technologies in cotton. The concepts of genetic diversity, QTL mapping, and marker assisted selection (MAS) are evolving into more efficient concepts of linkage disequilibrium, association mapping, and genomic selection, respectively. The objective of the current review is to analyze the pace of evolution in the molecular marker technologies in cotton during the last ten years into the following four areas: (i) comparative analysis of low- and high-throughput marker technologies available in cotton, (ii) genetic diversity in the available wild and improved gene pools of cotton, (iii) identification of the genomic regions within cotton genome underlying economic traits, and (iv) marker based selection methodologies. Moreover, the applications of marker technologies to enhance the breeding efficiency in cotton are also summarized. Aforementioned genomic technologies and the integration of several other omics resources are expected to enhance the cotton productivity and meet the global fiber quantity and quality demands.