The experimental results demonstrate that our approach significantly outperforms the baselines.N6-methyladenosine [m(6)A/m6A] methylation is one of the most common RNA modifications in eukaryotic cell mRNA and plays an important regulatory role in mRNA metabolism, splicing, translocation, stability, and translation. Previous studies have demonstrated that the m6A modification is highly associated with tumor cell proliferation, migration, and invasion. In the present study, five m6A regulatory factors have been revealed, namely heterogeneous nuclear ribonucleoprotein A2/B1(HNRNPA2B1), heterogeneous nuclear ribonucleoprotein C (HNRNPC), Vir like m6A methyltransferase associated protein (KIAA1429/VIRMA), RNA binding motif protein 15 (RBM15) and methyltransferase like 3 (METTL3), which are closely related to the overall survival (OS) of patients with lung adenocarcinoma (LUAD). These five m6A regulatory factors exhibited potential prognostic value for the 1, 3, and 5-years survival outcomes of LUAD patients. Our findings revealed that several signaling pathways, such as cell cycle, DNA replication, RNA degradation, RNA polymerase, nucleotide excision repair and basal transcription factors, are activated in the high-risk group of LUAD patients.Climate changes and environmental stresses have a consequential association with crop plant growth and yield, meaning it is necessary to cultivate crops that have tolerance toward the changing climate and environmental disturbances such as water stress, temperature fluctuation, and salt toxicity. Recent studies have shown that trans-acting regulatory elements, including microRNAs (miRNAs) and transcription factors (TFs), are emerging as promising tools for engineering naive improved crop varieties with tolerance for multiple environmental stresses and enhanced quality as well as yield. However, the interwoven complex regulatory function of TFs and miRNAs at transcriptional and post-transcriptional levels is unexplored in Oryza sativa. To this end, we have constructed a multiple abiotic stress responsive TF-miRNA-gene regulatory network for O. sativa using a transcriptome and degradome sequencing data meta-analysis approach. The theoretical network approach has shown the networks to be dense, scale-free, and sf miRNAs and TFs. Furthermore, it advances current understanding of multiple abiotic stress tolerance mechanisms.The transportation is a crucial phase in beef cattle industry, and the annual losses caused by beef cattle transport stress are substantial. Several studies have described the effect of long distance transportation stress on animal health, such as disorder in nervous, endocrine, immune, and metabolic system. However, molecular mechanisms underlying short distance transportation stress is still poorly understood. Present study aims to investigate the effect of short distance transportation by measuring the hematological indices and transcriptomic analysis. In this study, a total 10 Qinchuan cattle were used to compare the molecular characteristics of blood before and after transportation. We have found that a stress-related marker „white blood cell count (WBC)” increased significantly after transportation. The decrease in triglyceride (TG), cholestenone (CHO), high-density lipoprotein (HDL), and low-density lipoprotein (LDL) showed that energy expenditure was increased after transportation, but not enough to a and WGCNA indicated that the disorder of B cell differentiation, proliferation, survival, and apoptosis were the potential molecular mechanism in short distance transportation stress. In conclusion, our results provide the novel insight about potential biomarkers for short distance transportation stress, which may serve as for diagnosing and preventing this condition in beef industry.Inherited hearing loss is extremely heterogeneous both clinically and genetically. In addition, the spectrum of deafness-causing genetic variants differs greatly among geographical areas and ethnicities. The identification of the causal mutation in affected families allows early diagnosis, clinical follow-up, and genetic counseling. A large consanguineous family of Moroccan origin affected by autosomal recessive sensorineural hearing loss (ARSNHL) was subjected to genome-wide linkage analysis and exome sequencing. Exome-wide variant analysis and prioritization identified the SLC22A4 p.C113Y missense variant (rs768484124) as the most likely cause of ARSNHL in the family, falling within the unique significant (LOD score>3) linkage region on chromosome 5. Indeed, the same variant was previously reported in two Tunisian ARSNHL pedigrees. The variant is present in the homozygous state in all six affected individuals, but also in one normal-hearing sibling, suggesting incomplete penetrance. The mutation is absent in about 1,000 individuals from the Greater Middle East Variome study cohort, including individuals from the North African population, as well as in an additional seven deaf patients from the same geographical area, recruited and screened for mutations in the SLC22A4 gene. This study represents the first independent replication of the involvement of SLC22A4 in ARSNHL, highlighting the importance of the gene, and of the p.C113Y mutation, at least in the Northwest African population.Rheumatoid arthritis (RA) is an incurable disease that afflicts 0.5-1.0% of the global population though it is less threatening at its early stage. Therefore, improved diagnostic efficiency and prognostic outcome are critical for confronting RA. Although machine learning is considered a promising technique in clinical research, its potential in verifying the biological significance of gene was not fully exploited. The performance of a machine learning model depends greatly on the features used for model training; therefore, the effectiveness of prediction might reflect the quality of input features. In the present study, we used weighted gene co-expression network analysis (WGCNA) in conjunction with differentially expressed gene (DEG) analysis to select the key genes that were highly associated with RA phenotypes based on multiple microarray datasets of RA blood samples, after which they were used as features in machine learning model validation. A total of six machine learning models were used to validate the biological significance of the key genes based on gene expression, among which five models achieved good performances [area under curve (AUC) >0.85], suggesting that our currently identified key genes are biologically significant and highly representative of genes involved in RA. Combined with other biological interpretations including Gene Ontology (GO) analysis, protein-protein interaction (PPI) network analysis, as well as inference of immune cell composition, our current study might shed a light on the in-depth study of RA diagnosis and prognosis.Animal growth and development are regulated by neural and endocrine growth axes, in which cell proliferation plays key roles. Recently, many research showed that circular RNAs were involved in hepatocyte and myoblast proliferation. Previously, we identified a circular RNA derived from the chicken GHR gene, named circGHR. However, the function of circGHR is unclear. The objective of this study was to investigate circGHR expression pattern and its roles in cell proliferation. Results indicated that circGHR was a closed-loop structure molecule, and it was richer in the nucleus of hepatocytes and myoblast. Real-time PCR showed that circGHR was increased from E13 to the 7th week in the liver but decreased in the thigh and breast muscle. The CCK-8 assay displayed that circGHR promoted cell proliferation. Simultaneously, the biomarker genes PCNA, CCND1, and CDK2 and the linear transcripts GHR and GHBP were upregulated when circGHR was overexpressed. Altogether, these data exhibited that circGHR could promote cell proliferation possibly by regulating GHR mRNA and GHBP expression.Dehorning is the process of physically removing horns to protect animals and humans from injury, but the process is costly, unpleasant, and faces increasing public scrutiny. Genetic selection for polled (hornless), which is genetically dominant to horned, is a long-term solution to eliminate the need for dehorning. However, due to the limited number of polled Australian Brahman bulls, the northern Australian beef cattle population remains predominantly horned. The potential to use gene editing to produce high-genetic-merit polled cattle was recently demonstrated. To further explore the concept, this study simulated introgression of the POLLED allele into a tropically adapted Australian beef cattle population via conventional breeding or gene editing (top 1% or 10% of seedstock bulls/year) for 3 polled mating schemes and compared results to baseline selection on genetic merit (Japan Ox selection index, $JapOx) alone, over the course of 20 years. The baseline scenario did not significantly decrease the 20-year e the number of polled animals in this population. Moreover, these scenarios illustrate how gene editing could be a tool for accelerating the development of high-genetic-merit homozygous polled sires to mitigate the current trade-off of slower genetic gain associated with decreasing HORNED allele frequency in the Australian Brahman population.The Tibetan Plateau (TP) is considered to be one of the last terrestrial environments conquered by the anatomically modern human. Understanding of the genetic background of highland Tibetans plays a pivotal role in archeology, anthropology, genetics, and forensic investigations. Here, we genotyped 22 forensic genetic markers in 1,089 Tibetans residing in Nagqu Prefecture and collected 1,233,013 single nucleotide polymorphisms (SNPs) in the highland East Asians (Sherpa and Tibetan) from the Simons Genome Diversity Project and ancient Tibetans from Nepal and Neolithic farmers from northeastern Qinghai-Tibetan Plateau from public databases. We subsequently merged our two datasets with other worldwide reference populations or eastern ancient Eurasians to gain new insights into the genetic diversity, population movements, and admixtures of high-altitude East Asians via comprehensive population genetic statistical tools [principal component analysis (PCA), multidimensional scaling plot (MDS), STRUCTURE/ADMIXTURE, fopulation migrations and interactions between highland and lowland regions, but also evidenced that late Neolithic farmers permanently colonized into the TP by adopting cold-tolerant barley agriculture that was mediated via the acculturation of idea via the millet farmer and not via the movement of barley agriculturalist as no obvious western Eurasian admixture signals were identified in our analyzed modern and ancient populations. Besides, results from the qpAdm-based admixture proportion estimation and qpGraph-based phylogenetic relationship reconstruction consistently demonstrated that all ancient and modern highland East Asians harbored and shared the deeply diverged Onge/Hoabinhian-related eastern Eurasian lineage, suggesting a common Paleolithic genetic legacy existed in high-altitude East Asians as the first layer of their gene pool.

This study aimed to explore the regulatory mechanism of hsa-miR-143-3p and lncRNA RP11-363N22.3-functioning upstream of

-in exosomes derived from human mesenchymal stem cells (hMSCs) in pancreatic cancer.

Western blotting and quantitative PCR were used to determine gene expression.

, cell proliferation, apoptosis, and cell cycle and invasion were evaluated using CCK-8 assay, flow cytometry, and transwell assays, respectively.

, the effect of hsa-miR143-3p was investigated using a tumorigenesis test in nude mice. The association between hsa-miR-143-3p and lncRNA RP11-363N22.3 was investigated using the dual-luciferase assay.

hsa-miR-143-3p expression significantly increased in hMSC exosomes than in those in human pancreatic cancer cell line (CFPAC-1) exosomes.

, compared to the MOCK (CFPAC-1 only) group, cell proliferation and invasion were inhibited and apoptosis was induced in the inhibitor NC (CFPAC-1 + MSC-hsa-miR-3p inhibitor NC) group, while these changes were reversed in the inhibitor (CFPAC-1 + MSC-hsa-miR-3p inhibitor) group. The expression of lncRNA RP11-363N22.3 and genes related to miR-143 significantly decreased in the inhibitor NC group compared to the MOCK group, and increased in the inhibitor group compared to inhibitor NC group. A targeted combinatorial effect was observed between lncRNA RP11-363N22.3 and hsa-miR-143-3p.

, the tumor volume of the mimics (CFPAC-1 + MSC-hsa-miR-143-3p mimics) group was smaller than that of the mimics NC (CFPAC-1 + MSC-hsa-miR-143-3p mimics NC) and MOCK groups. H&E staining showed that there were no obvious pathological changes in MOCK and mimic NC groups, while cell necrosis was seen in some regions in mimic groups.

hsa-miR-143-3p may promote apoptosis and suppress cell growth and invasion in pancreatic cancer.

hsa-miR-143-3p may promote apoptosis and suppress cell growth and invasion in pancreatic cancer.The COVID-19 disease for Novel coronavirus (SARS-CoV-2) has turned out to be a global pandemic. The high transmission rate of this pathogenic virus demands an early prediction and proper identification for the subsequent treatment. However, polymorphic nature of this virus allows it to adapt and sustain in different kinds of environment which makes it difficult to predict. On the other hand, there are other pathogens like SARS-CoV-1, MERS-CoV, Ebola, Dengue, and Influenza as well, so that a predictor is highly required to distinguish them with the use of their genomic information. To mitigate this problem, in this work COVID-DeepPredictor is proposed on the framework of deep learning to identify an unknown sequence of these pathogens. COVID-DeepPredictor uses Long Short Term Memory as Recurrent Neural Network for the underlying prediction with an alignment-free technique. In this regard, k-mer technique is applied to create Bag-of-Descriptors (BoDs) in order to generate Bag-of-Unique-Descriptors (BoUDs) as vo The code, training, and test datasets used for COVID-DeepPredictor are available at http//www.nitttrkol.ac.in/indrajit/projects/COVID-DeepPredictor/.While it is expected for gene length to be associated with factors such as intron number and evolutionary conservation, we are yet to understand the connections between gene length and function in the human genome. In this study, we show that, as expected, there is a strong positive correlation between gene length, transcript length, and protein size as well as a correlation with the number of genetic variants and introns. Among tissue-specific genes, we find that the longest transcripts tend to be expressed in the blood vessels, nerves, thyroid, cervix uteri, and the brain, while the smallest transcripts tend to be expressed in the pancreas, skin, stomach, vagina, and testis. We report, as shown previously, that natural selection suppresses changes for genes with longer transcripts and promotes changes for genes with smaller transcripts. We also observe that genes with longer transcripts tend to have a higher number of co-expressed genes and protein-protein interactions, as well as more associated publications. In the functional analysis, we show that bigger transcripts are often associated with neuronal development, while smaller transcripts tend to play roles in skin development and in the immune system. Furthermore, pathways related to cancer, neurons, and heart diseases tend to have genes with longer transcripts, with smaller transcripts being present in pathways related to immune responses and neurodegenerative diseases. Based on our results, we hypothesize that longer genes tend to be associated with functions that are important in the early development stages, while smaller genes tend to play a role in functions that are important throughout the whole life, like the immune system, which requires fast responses.[This corrects the article DOI 10.3389/fgene.2020.00995.].Defined as chronic excessive accumulation of adiposity, obesity results from long-term imbalance between energy intake and expenditure. The mechanisms behind how caloric imbalance occurs are complex and influenced by numerous biological and environmental factors, especially genetics, and diet. Population-based diet recommendations have had limited success partly due to the wide variation in physiological responses across individuals when they consume the same diet. Thus, it is necessary to broaden our understanding of how individual genetics and diet interact relative to the development of obesity for improving weight loss treatment. To determine how consumption of diets with different macronutrient composition alter adiposity and other obesity-related traits in a genetically diverse population, we analyzed body composition, metabolic rate, clinical blood chemistries, and circulating metabolites in 22 strains of mice from the Collaborative Cross (CC), a highly diverse recombinant inbred mouse population, before and after 8 weeks of feeding either a high protein or high fat high sucrose diet. At both baseline and post-diet, adiposity and other obesity-related traits exhibited a broad range of phenotypic variation based on CC strain; diet-induced changes in adiposity and other traits also depended largely on CC strain. In addition to estimating heritability at baseline, we also quantified the effect size of diet for each trait, which varied by trait and experimental diet. Our findings identified CC strains prone to developing obesity, demonstrate the genotypic and phenotypic diversity of the CC for studying complex traits, and highlight the importance of accounting for genetic differences when making dietary recommendations.The mangrove oysters (Crassostrea gasar) are molluscs native to the Amazonia region and their exploration and farming has increased considerably in recent years. These animals are farmed on beds built in the rivers of the Amazonia estuaries and, therefore, the composition of their microbiome should be directly influenced by environmental conditions. Our work aimed to evaluate the changes in bacterial composition of oyster’s microbiota at two different seasons (rainy and dry). For this purpose, we amplified and sequenced the V3-V4 regions of the 16S rRNA gene. Sequencing was performed on the Illumina MiSeq platform. According to the rarefaction curve, the sampling effort was sufficient to describe the bacterial diversity in the samples. Alpha-diversity indexes showed that the bacterial microbiota of oysters is richer during the rainy season. This richness is possibly associated with the diversity at lower taxonomic levels, since the relative abundance of bacterial phyla in the two seasons remained relatively constant. The main phyla found include Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria. Similar results were found for the species Crassostrea gigas, Crassostrea sikamea, and Crassostrea corteziensis. Beta-diversity analysis showed that the bacterial composition of oyster’s gut microbiota was quite different in the two seasons. Our data demonstrate the close relationship between the environment and the microbiome of these molluscs, reinforcing the need for conservation and sustainable management of estuaries in the Amazonia.The correct development of a diploid sporophyte body and a haploid gametophyte relies on a strict coordination between cell divisions in space and time. During plant reproduction, these divisions have to be temporally and spatially coordinated with cell differentiation processes, to ensure a successful fertilization. Armadillo BTB Arabidopsis protein 1 (ABAP1) is a plant exclusive protein that has been previously reported to control proliferative cell divisions during leaf growth in Arabidopsis. Here, we show that ABAP1 binds to different transcription factors that regulate male and female gametophyte differentiation, repressing their target genes expression. During male gametogenesis, the ABAP1-TCP16 complex represses CDT1b transcription, and consequently regulates microspore first asymmetric mitosis. In the female gametogenesis, the ABAP1-ADAP complex represses EDA24-like transcription, regulating polar nuclei fusion to form the central cell. Therefore, besides its function during vegetative development, this work shows that ABAP1 is also involved in differentiation processes during plant reproduction, by having a dual role in regulating both the first asymmetric cell division of male gametophyte and the cell differentiation (or cell fusion) of female gametophyte.One of the greatest inputs of available nitrogen into the biosphere occurs through the biological N2-fixation to ammonium as result of the symbiosis between rhizobia and leguminous plants. These interactions allow increased crop yields on nitrogen-poor soils. Exopolysaccharides (EPS) are key components for the establishment of an effective symbiosis between alfalfa and Ensifer meliloti, as bacteria that lack EPS are unable to infect the host plants. Rhizobium favelukesii LPU83 is an acid-tolerant rhizobia strain capable of nodulating alfalfa but inefficient to fix nitrogen. Aiming to identify the molecular determinants that allow R. favelukesii to infect plants, we studied its EPS biosynthesis. LPU83 produces an EPS I identical to the one present in E. meliloti, but the organization of the genes involved in its synthesis is different. The main gene cluster needed for the synthesis of EPS I in E. meliloti, is split into three different sections in R. favelukesii, which probably arose by a recent event of horizontal gene transfer. A R. favelukesii strain devoided of all the genes needed for the synthesis of EPS I is still able to infect and nodulate alfalfa, suggesting that attention should be directed to other molecules involved in the development of the symbiosis.The specific variation in the functional ionome was studied in Brassica napus and Triticum aestivum plants subjected to micronutrient or beneficial mineral nutrient deprivation. Effects of these deprivations were compared to those of macronutrient deprivation. In order to identify early events, plants were harvested after 22 days, i.e., before any significant reduction in growth relative to control plants. Root uptake, tissue concentrations and relative root nutrient contents were analyzed revealing numerous interactions with respect to the 20 elements quantified. The assessment of the functional ionome under individual mineral nutrient deficiency allows the identification of a large number of interactions between elements, although it is not totally exhaustive, and gives access to specific ionomic signatures that discriminate among deficiencies in N, P, S, K, Ca, Mn, Fe, Zn, Na, Si, and Se in both species, plus Mg, Cl, Cu, and Mo in wheat. Ionome modifications and components of ionomic signatures are discussed in relation to well-known mechanisms that may explain crosstalks between mineral nutrients, such as between Na and K, V, Se, Mo and S or Fe, Zn and Cu. More surprisingly, when deprived of beneficial nutrients such as Na, Si, Co, or Se, the plant ionome was strongly modified while these beneficial nutrients contributed greatly to the leaf ionomic signature of most mineral deficiencies.The chromatin modification H3K27me3 is involved in almost every developmental stage in Arabidopsis. Much remains unknown about the dynamic regulation of this histone modification in flower development and control of self-fertility. Here we demonstrate that the H3K27me3-specific demethylases ELF6 and JMJ13 antagonistically regulate carpel and stamen growth and thus modulate self-fertility. Transcriptome and epigenome data are used to identify potential targets of ELF6 and JMJ13 responsible for these physiological functions. We find that ELF6 relieves expansin genes of epigenetic silencing to promote cell elongation in the carpel, enhancing carpel growth and therefore encouraging out-crossing. On the other hand, JMJ13 activates genes of the jasmonic acid regulatory network alongside the auxin responsive SAUR26, to inhibit carpel growth, enhance stamen growth, and overall promote self-pollination. Our evidence provides novel mechanisms of self-fertility regulation in A. thaliana demonstrating how chromatin modifying enzymes govern the equilibrium between flower self-pollination and out-crossing.Several citrus varieties show gametophytic self-incompatibility (GSI), which can contribute to seedless fruit production in several cultivars. This study investigated the genes regulating this trait through RNA-seq performed using styles collected from the flowers of Japanese citrus cultivars 'Hyuganatsu,’ 'Tosabuntan,’ 'Hassaku,’ 'Banpeiyu,’ and 'Sweet Spring’. We screened the transcripts of putative T2 RNases, i.e., the protein family including all S-RNases from S-RNase-based GSI plants, and constructed a phylogenetic tree using the screened T2 RNases and S-RNases retrieved from citrus genome databases and a public database. Three major clusters (class I-III) were formed, among which, the class III cluster contained family specific subclusters formed by S-RNase and a citrus-specific cluster monophyletic to the S-RNase clusters. From the citrus class III cluster, six transcripts were consistent with the S haplotypes previously determined in Japanese citrus accessions, sharing characteristics such as isoelectric point, extracellular localization, molecular weight, intron number and position, and tissue-specific expression with S-RNases. One T2 RNase gene in self-incompatible Hyuganatsu was significantly down-regulated in the styles of a self-compatible mutant of Hyuganatsu in RNA-seq and qPCR analyses. In addition, the inheritance pattern of some T2 RNase genes was consistent with the pattern of the S haplotype in the progeny population of Hyuganatsu and Tosabuntan. As all results supported citrus self-incompatibility being based on S-RNase, we believe that six T2 RNase genes were S-RNases. The homology comparison between the six T2 RNases and S-RNases recently reported in Chinese citrus revealed that three out of six T2 RNases were identical to S-RNases from Chinese citrus. Thus, the other three T2 RNases were finally concluded to be novel citrus S-RNases involved in self-incompatibility.Effective assessment of pathogen growth can facilitate screening for disease resistance, mapping of resistance loci, testing efficacy of control measures, or elucidation of fundamental host-pathogen interactions. Current methods are often limited by subjective assessments, inability to detect pathogen growth prior to appearance of symptoms, destructive sampling, or limited capacity for replication and quantitative analysis. In this work we sought to develop a real-time, in vivo, high-throughput assay that would allow for quantification of pathogen growth. To establish such a system, we worked with the broad host-range, highly destructive, soil-borne oomycete pathogen, Phytophthora capsici. We used an isolate expressing red fluorescence protein (RFP) to establish a microtiter plate, real-time assay to quantify pathogen growth in live tissue. The system was successfully used to monitor P. capsici growth in planta on cucumber (Cucumis sativus) fruit and pepper (Capsicum annuum) leaf samples in relation to different levels of host susceptibility. These results demonstrate usefulness of the method in different species and tissue types, allowing for highly replicated, quantitative time-course measurements of pathogen growth in vivo. Analyses of pathogen growth during initial stages of infection preceding symptom development show the importance of very early stages of infection in determining disease outcome, and provide insight into points of inhibition of pathogen growth in different resistance systems.Automated species classification from 3D point clouds is still a challenge. It is, however, an important task for laser scanning-based forest inventory, ecosystem models, and to support forest management. Here, we tested the performance of an image classification approach based on convolutional neural networks (CNNs) with the aim to classify 3D point clouds of seven tree species based on 2D representation in a computationally efficient way. We were particularly interested in how the approach would perform with artificially increased training data size based on image augmentation techniques. Our approach yielded a high classification accuracy (86%) and the confusion matrix revealed that despite rather small sample sizes of the training data for some tree species, classification accuracy was high. We could partly relate this to the successful application of the image augmentation technique, improving our result by 6% in total and 13, 14, and 24% for ash, oak and pine, respectively. The introduced approach is hence not only applicable to small-sized datasets, it is also computationally effective since it relies on 2D instead of 3D data to be processed in the CNN. Our approach was faster and more accurate when compared to the point cloud-based „PointNet” approach.The middle layer is an essential cell layer of the anther wall located between the endothecium and tapetum in Arabidopsis. Based on sectioning, the middle layer was found to be degraded at stage 7, which led to the separation of the tapetum from the anther wall. Here, we established techniques for live imaging of the anther. We created a marker line with fluorescent proteins expressed in all anther layers to study anther development. Several staining methods were used in the intact anthers to study anther cell morphology. We clarified the initiation, development, and degradation of the middle layer in Arabidopsis. This layer is initiated from both the inner and outer secondary parietal cells at stage 4, stopped cell division at stage 6, and finally degraded at stage 11. The neighboring cell layers, the epidermis, and endothecium continued cell division until stage 10, which led to a thin middle layer. The degradation of the tapetum cell wall at stage 7 lead to its isolation from the anther wall. This work presents fundamental information on the development of the middle layer, which facilitates the further investigation of anther development and plant fertility. These live imaging methods could be useful in future studies.Adaptation of viticulture to climate change includes exploration of new geographical areas, new training systems, new management practices, or new varieties, both for rootstocks and scions. Molecular tools can be defined as molecular approaches used to study DNAs, RNAs, and proteins in all living organisms. We present here the current knowledge about molecular tools and their potential usefulness in three aspects of grapevine adaptation to the ongoing climate change. (i) Molecular tools for understanding grapevine response to environmental stresses. A fine description of the regulation of gene expression is a powerful tool to understand the physiological mechanisms set up by the grapevine to respond to abiotic stress such as high temperatures or drought. The current knowledge on gene expression is continuously evolving with increasing evidence of the role of alternative splicing, small RNAs, long non-coding RNAs, DNA methylation, or chromatin activity. (ii) Genetics and genomics of grapevine stress tolerance.t the genetic information along the whole genome to predict a phenotype. Modern technologies are also able to generate mutations that are possibly interesting for generating new phenotypes but the most promising one is the direct editing of the genome at a precise location.The American cranberry (Vaccinium macrocarpon Ait.) is an iconic North American fruit crop of great cultural and economic importance. Cranberry can be considered a fruit crop model due to its unique fruit nutrient composition, overlapping generations, recent domestication, both sexual and asexual reproduction modes, and the existence of cross-compatible wild species. Development of cranberry molecular resources started very recently; however, further genetic studies are now being limited by the lack of a high-quality genome assembly. Here, we report the first chromosome-scale genome assembly of cranberry, cultivar Stevens, and a draft genome of its close wild relative species Vaccinium microcarpum. More than 92% of the estimated cranberry genome size (492 Mb) was assembled into 12 chromosomes, which enabled gene model prediction and chromosome-level comparative genomics. Our analysis revealed two polyploidization events, the ancient γ-triplication, and a more recent whole genome duplication shared with other members of the Ericaeae, Theaceae and Actinidiaceae families approximately 61 Mya. Furthermore, comparative genomics within the Vaccinium genus suggested cranberry-V. microcarpum divergence occurred 4.5 Mya, following their divergence from blueberry 10.4 Mya, which agrees with morphological differences between these species and previously identified duplication events. Finally, we identified a cluster of subgroup-6 R2R3 MYB transcription factors within a genomic region spanning a large QTL for anthocyanin variation in cranberry fruit. Phylogenetic analysis suggested these genes likely act as anthocyanin biosynthesis regulators in cranberry. Undoubtedly, these new cranberry genomic resources will facilitate the dissection of the genetic mechanisms governing agronomic traits and further breeding efforts at the molecular level.Researchers in phylogenetic systematics typically choose a few individual representatives of every species for sequencing based on convenience (neighboring populations, herbarium specimens, samples provided by experts, garden plants). However, few studies are based on original material, type material or topotypic material (living specimens from the locality where the type material was collected). The use of type or topotypic material in phylogenetic studies is paramount particularly when taxonomy is complex, such as that of Antirrhinum (Plantaginaceae). In this paper, we used topotypic materials of Antirrhinum at the species level (34 species proposed by previous authors), 87 specimens representing the species distributions and >50,000 informative nucleotide characters (from ∼4,000 loci) generated by the genotyping-by-sequencing (GBS) technique (i) to test two explicit taxonomic hypotheses widely followed by local taxonomic treatments; (ii) to robustly estimate phylogenetic relationships; (iii) to investigaterrhinum diversification are strongly supported, with no evidence of hybridization between major clades. Our results also suggest incipient speciation in some geographic areas and point to future avenues of research in evolution and systematics of Antirrhinum.Tandem repeats can occupy a large portion of plant genomes and can either cause or result from chromosomal rearrangements, which are important drivers of dysploidy-mediated karyotype evolution and speciation. To understand the contribution of tandem repeats in shaping the extant Senna tora dysploid karyotype, we analyzed the composition and abundance of tandem repeats in the S. tora genome and compared the chromosomal distribution of these repeats between S. tora and a closely related euploid, Senna occidentalis. Using a read clustering algorithm, we identified the major S. tora tandem repeats and visualized their chromosomal distribution by fluorescence in situ hybridization. We identified eight independent repeats covering ~85 Mb or ~12% of the S. tora genome. The unit lengths and copy numbers had ranges of 7-5,833 bp and 325-2.89 × 106, respectively. Three short duplicated sequences were found in the 45S rDNA intergenic spacer, one of which was also detected at an extra-NOR locus. The canonical plant telomeric repeat (TTTAGGG)n was also detected as very intense signals in numerous pericentromeric and interstitial loci. StoTR05_180, which showed subtelomeric distribution in Senna occidentalis, was predominantly pericentromeric in S. tora. The unusual chromosomal distribution of tandem repeats in S. tora not only enabled easy identification of individual chromosomes but also revealed the massive chromosomal rearrangements that have likely played important roles in shaping its dysploid karyotype.The floral transition stage is pivotal for sustaining plant populations and is affected by several environmental factors, including photoperiod. However, the mechanisms underlying photoperiodic flowering responses are not fully understood. Herein, we have shown that exposure to an extended photoperiod effectively induced early flowering in Arabidopsis plants, at a range of different nitrate concentrations. However, these photoperiodic flowering responses were attenuated when the nitrate levels were suboptimal for flowering. An extended photoperiod also improved the root nitrate uptake of by NITRATE TRANSPORTER 1.1 (NRT1.1) and NITRATE TRANSPORTER 2.1 (NRT2.1), whereas the loss of function of NRT1.1/NRT2.1 in the nrt1.1-1/2.1-2 mutants suppressed the expression of the key flowering genes CONSTANS (CO) and FLOWERING LOCUS T (FT), and reduced the sensitivity of the photoperiodic flowering responses to elevated levels of nitrate. These results suggest that the upregulation of root nitrate uptake during extended photoperiods, contributed to the observed early flowering. The results also showed that the sensitivity of photoperiodic flowering responses to elevated levels of nitrate, were also reduced by either the replacement of nitrate with its assimilation intermediate product, ammonium, or by the dysfunction of the nitrate assimilation pathway. This indicates that nitrate serves as both a nutrient source for plant growth and as a signaling molecule for floral induction during extended photoperiods.Blood oranges (Citrus sinensis L. Osbeck cv. Sanguinello) fruit were treated with 24-epibrassinolide (Br) at 1, 5, and 10 μM previous to storage at 5°C during 42 days. The samples were analyzed after 14, 28, and 42 days plus 2 days at 20°C. Chilling injury was reduced in Br-treated fruit based on the lower percentage of electrolyte leakage and visual symptoms of peel dehydration and browning. Treated fruit showed lower acidity losses, due to retention of the main organic acids’ concentration (citric and malic acids), as well as was higher content of sugars (sucrose, fructose, and glucose), especially in those fruit treated with the highest concentration (10 μM). Total phenolics and hydrophilic total antioxidant activity (H-TAA) decreased in control fruit over storage, while Br-treated fruit showed significantly higher concentration. In addition, total anthocyanins were enhanced in Br-treated oranges, which were correlated with color Hue angle. Overall, the application of Br at 10 μM provides results increasing the storability of blood oranges and their content on bioactive compounds with antioxidant activity.In subtropical regions, chilling stress is one of the major constraints for sugarcane cultivation, which hampers yield and sugar production. Two recently released sugarcane cultivars, moderately chilling tolerant Guitang 49 and chilling tolerant Guitang 28, were selected. The experiments were conducted in the controlled environment, and seedlings were exposed to optimum (25°C/15°C), chilling (10°C/5°C), and recovery (25°C/15°C) temperature conditions. PSII heterogeneity was studied in terms of reducing side and antenna size heterogeneity. Under chilling, reducing side heterogeneity resulted in increased number of QB non-reducing centers, whereas antenna side heterogeneity resulted in enhanced number of inactive β centers in both cultivars, but the magnitude of change was higher in Guitang 49 than Guitang 28. Furthermore, in both cultivars, quantum efficiency of PSII, status of water splitting complex, and performance index were adversely affected by chilling, along with reduction in net photosynthesis rate and nighttime respiration and alterations in leaf optical properties. The extents of negative effect on these parameters were larger in Guitang 49 than in Guitang 28. These results reveal a clear differentiation in PSII heterogeneity between differentially chilling tolerant cultivars. Based on our studies, it is concluded that PSII heterogeneity can be used as an additional non-invasive and novel technique for evaluating any type of environmental stress in plants.Seed dispersal is crucial to gene flow among plant populations. Although the effects of geographic distance and barriers to gene flow are well studied in many systems, it is unclear how seed dispersal mediates gene flow in conjunction with interacting effects of geographic distance and barriers. To test whether distinct seed dispersal modes (i.e., hydrochory, anemochory, and zoochory) have a consistent effect on the level of genetic connectivity (i.e., gene flow) among populations of riverine plant species, we used unlinked single-nucleotide polymorphisms (SNPs) for eight co-distributed plant species sampled across the Rio Branco, a putative biogeographic barrier in the Amazon basin. We found that animal-dispersed plant species exhibited higher levels of genetic diversity and lack of inbreeding as a result of the stronger genetic connectivity than plant species whose seeds are dispersed by water or wind. Interestingly, our results also indicated that the Rio Branco facilitates gene dispersal for all plant species analyzed, irrespective of their mode of dispersal. Even at a small spatial scale, our findings suggest that ecology rather than geography play a key role in shaping the evolutionary history of plants in the Amazon basin. These results may help improve conservation and management policies in Amazonian riparian forests, where degradation and deforestation rates are high.This study aims to provide an effective image analysis method for clover detection and botanical composition (BC) estimation in clover-grass mixture fields. Three transfer learning methods, namely, fine-tuned DeepLab V3+, SegNet, and fully convolutional network-8s (FCN-8s), were utilized to detect clover fractions (on an area basis). The detected clover fraction (CF detected ), together with auxiliary variables, viz., measured clover height (H clover ) and grass height (H grass ), were used to build multiple linear regression (MLR) and back propagation neural network (BPNN) models for BC estimation. A total of 347 clover-grass images were used to build the estimation model on clover fraction and BC. Of the 347 samples, 226 images were augmented to 904 images for training, 25 were selected for validation, and the remaining 96 samples were used as an independent dataset for testing. Testing results showed that the intersection-over-union (IoU) values based on the DeepLab V3+, SegNet, and FCN-8s were 0.73, 0.57, and 0.60, respectively. The root mean square error (RMSE) values for the three transfer learning methods were 8.5, 10.6, and 10.0%. Subsequently, models based on BPNN and MLR were built to estimate BC, by using either CF detected only or CF detected , grass height, and clover height all together. Results showed that BPNN was generally superior to MLR in terms of estimating BC. The BPNN model only using CF detected had a RMSE of 8.7%. In contrast, the BPNN model using all three variables (CF detected , H clover , and H grass ) as inputs had an RMSE of 6.6%, implying that DeepLab V3+ together with BPNN can provide good estimation of BC and can offer a promising method for improving forage management.Defective citrus fruits are manually sorted at the moment, which is a time-consuming and cost-expensive process with unsatisfactory accuracy. In this paper, we introduce a deep learning-based vision system implemented on a citrus processing line for fast on-line sorting. For the citrus fruits rotating randomly on the conveyor, a convolutional neural network-based detector was developed to detect and temporarily classify the defective ones, and a SORT algorithm-based tracker was adopted to record the classification information along their paths. The true categories of the citrus fruits were identified through the tracked historical information, resulting in high detection precision of 93.6%. Moreover, the linear Kalman filter model was applied to predict the future path of the fruits, which can be used to guide the robot arms to pick out the defective ones. Ultimately, this research presents a practical solution to realize on-line citrus sorting featuring low costs, high efficiency, and accuracy.Long non-coding RNA (lncRNA) is a crucial regulatory mechanism in the plant response to biotic and abiotic stress. However, their roles in potato (Solanum tuberosum L.) resistance to Phytophthora infestans (P. infestans) largely remain unknown. In this study, we identify 2857 lncRNAs and 33,150 mRNAs of the potato from large-scale published RNA sequencing data. Characteristic analysis indicates a similar distribution pattern of lncRNAs and mRNAs on the potato chromosomes, and the mRNAs were longer and had more exons than lncRNAs. Identification of alternative splicing (AS) shows that there were a total of 2491 lncRNAs generated from AS and the highest frequency (46.49%) of alternative acceptors (AA). We performed R package TCseq to cluster 133 specific differentially expressed lncRNAs from resistance lines and found that the lncRNAs of cluster 2 were upregulated. The lncRNA targets were subject to KEGG pathway enrichment analysis, and the interactive network between lncRNAs and mRNAs was constructed by using GENIE3, a random forest machine learning algorithm. Transient overexpression of StLNC0004 in Nicotiana benthamiana significantly suppresses P. infestans growth compared with a control, and the expression of extensin (NbEXT), the ortholog of the StLNC0004 target gene, was significantly upregulated in the overexpression line. Together, these results suggest that lncRNAs play potential functional roles in the potato response to P. infestans infection.Mixed-species forest plantation is a sound option to facilitate ecological restoration, plant diversity and ecosystem functions. Compatible species combinations are conducive to reconstruct plant communities that can persist at a low cost without further management and even develop into natural forest communities. However, our understanding of how the compatibility of mycorrhizal types mediates species coexistence is still limited, especially in a novel agroforestry system. Here, we assessed the effects of mycorrhizal association type on the survival and growth of native woody species in mixed-species Eucalyptus plantations. To uncover how mycorrhizal type regulates plant-soil feedbacks, we first conducted a pot experiments by treating distinct mycorrhizal plants with soil microbes from their own or other mycorrhizal types. We then compared the growth response of arbuscular mycorrhizal plants and ectomycorrhizal plants to different soil microbial compositions associated with Eucalyptus plants. We found that typtus plants induced an unfavorable soil community, impeding coexistence with other mycorrhizal plants. Our study provides consistent observational and experimental evidence that mycorrhizal-mediated plant-microbial feedback on species coexistence among woody species. These findings are with important implications to optimize the species combinations for better design of mixed forest plantations.Cultivated rice (Oryza sativa L.) is frequently exposed to multiple stresses, including Schizotetranychus oryzae mite infestation. Rice domestication has narrowed the genetic diversity of the species, leading to a wide susceptibility. This work aimed to analyze the response of two African rice species (Oryza barthii and Oryza glaberrima), weedy rice (O. sativa f. spontanea), and O. sativa cv. Nipponbare to S. oryzae infestation. Surprisingly, leaf damage, histochemistry, and chlorophyll concentration/fluorescence indicated that the African species present a higher level of leaf damage, increased accumulation of H2O2, and lower photosynthetic capacity when compared to O. sativa plants under infested conditions. Infestation decreased tiller number, except in Nipponbare, and caused the death of O. barthii and O. glaberrima plants during the reproductive stage. While infestation did not affect the weight of 1,000 grains in both O. sativa, the number of panicles per plant was affected only in O. sativa f. spontaneo mite infestation.Genomics and high throughput phenomics have the potential to revolutionize the field of wheat (Triticum aestivum L.) breeding. Genomic selection (GS) has been used for predicting various quantitative traits in wheat, especially grain yield. However, there are few GS studies for grain protein content (GPC), which is a crucial quality determinant. Incorporation of secondary correlated traits in GS models has been demonstrated to improve accuracy. The objectives of this research were to compare performance of single and multi-trait GS models for predicting GPC and grain yield in wheat and to identify optimal growth stages for collecting secondary traits. We used 650 recombinant inbred lines from a spring wheat nested association mapping (NAM) population. The population was phenotyped over 3 years (2014-2016), and spectral information was collected at heading and grain filling stages. The ability to predict GPC and grain yield was assessed using secondary traits, univariate, covariate, and multivariate GS models for within and across cycle predictions. Our results indicate that GS accuracy increased by an average of 12% for GPC and 20% for grain yield by including secondary traits in the models. Spectral information collected at heading was superior for predicting GPC, whereas grain yield was more accurately predicted during the grain filling stage. Green normalized difference vegetation index had the largest effect on the prediction of GPC either used individually or with multiple indices in the GS models. An increased prediction ability for GPC and grain yield with the inclusion of secondary traits demonstrates the potential to improve the genetic gain per unit time and cost in wheat breeding.Traditional phenotyping techniques have long been a bottleneck in breeding programs and genotype- phenotype association studies in potato, as these methods are labor-intensive and time consuming. In addition, depending on the trait measured and metric adopted, they suffer from varying degrees of user bias and inaccuracy, and hence these challenges have effectively prevented the execution of large-scale population-based field studies. This is true not only for commercial traits (e.g., yield, tuber size, and shape), but also for traits strongly associated with plant performance (e.g., canopy development, canopy architecture, and growth rates). This study demonstrates how the use of point cloud data obtained from low-cost UAV imaging can be used to create 3D surface models of the plant canopy, from which detailed and accurate data on plant height and its distribution, canopy ground cover and canopy volume can be obtained over the growing season. Comparison of the canopy datasets at different temporal points enabled the identification of distinct patterns of canopy development, including different patterns of growth, plant lodging, maturity and senescence.