Search results for: transcriptome

Authors: Parvaneh Mahmoudi, Ahmad Moeni, Seyed Mojtaba Khayam Nekoei, Mohsen Mardi, Mehrshad Zeinolabedini, Ghasem Hosseini Salekdeh

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Saffron (Crocus sativus L.) is one of the most important spice and medicinal plants. The three-branch style of C. sativus flowers are the most important economic part of the plant and known as saffron, which has several medicinal properties. Despite the economic and biological significance of this plant, knowledge about its molecular characteristics is very limited. In the present study, we, for the first time, constructed a comprehensive dataset for C. sativus stigma through de novo transcriptome sequencing. We performed de novo transcriptome sequencing of C. sativus stigma using the Illumina paired-end sequencing technology. A total of 52075128 reads were generated and assembled into 118075 unigenes, with an average length of 629 bp and an N50 of 951 bp. A total of 66171unigenes were identified, among them, 66171 (56%) were annotated in the non-redundant National Center for Biotechnology Information (NCBI) database, 30938 (26%) were annotated in the Swiss-Prot database, 10273 (8.7%) unigenes were mapped to 141 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database, while 52560 (44%) and 40756 (34%) unigenes were assigned to Gen Ontology (GO) categories and Eukaryotic Orthologous Groups of proteins (KOG), respectively. In addition, 65 candidate genes involved in three stages of crocin biosynthesis were identified. Finally, transcriptome sequencing of saffron stigma was used to identify 6779 potential microsatellites (SSRs) molecular markers. High-throughput de novo transcriptome sequencing provided a valuable resource of transcript sequences of C. sativus in public databases. In addition, most of candidate genes potentially involved in crocin biosynthesis were identified which could be further utilized in functional genomics studies. Furthermore, numerous obtained SSRs might contribute to address open questions about the origin of this amphiploid spices with probable little genetic diversity.

Keywords: saffron, transcriptome, NGS, bioinformatic

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Authors: Juan Jose Filgueira, Daniela Londono-Serna, Liliana Maria Hoyos

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Carnation (Dianthus caryophyllus) is one of the most important products of exportation in the floriculture industry worldwide. Fusariosis is the disease that causes the highest losses on farms, in particular the one produced by Fusarium oxysporum f.sp. dianthi, called vascular wilt. Gene identification and metabolic routes of the genes that participate in the building of the plant response to Fusarium are some of the current targets in the carnation breeding industry. The techniques for the identifying of resistant genes in the plants, is the analysis of the transcriptome obtained during the host-pathogen interaction. In this work, we report the cell transcriptome of different varieties of carnation that present differential response from Fusarium oxysporum f.sp. dianthi attack. The cells of the different hybrids produced in the outbreeding program were cultured in vitro and elicited with the parasite in a dual culture. The isolation and purification of mRNA was achieved by using affinity chromatography Oligo dT columns and the transcriptomes were obtained by using Illumina NGS techniques. A total of 85,669 unigenes were detected in all the transcriptomes analyzed and 31,000 annotations were found in databases, which correspond to 36.2%. The library construction of genic expression techniques used, allowed to recognize the variation in the expression of genes such as Germin-like protein, Glycosyl hydrolase family and Cinnamate 4-hydroxylase. These have been reported in this study for the first time as part of the response mechanism to the presence of Fusarium oxysporum.

Keywords: Carnation, Fusarium, vascular wilt, transcriptome

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Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

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The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

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Authors: Jihye Hwang, Eun Hwa Choi, Su Youn Baek, Bia Park, Gyeongmin Kim, Chorong Shin, Joon Ha Lee, Jae-Sam Hwang, Ui Wook Hwang

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White-spotted flower chafers are widely distributed in Asian countries and traditionally used for the treatment of chronic fatigue, blood circulation, and paralysis in the oriental medicine field. The evolution and development of insect wings and metamorphosis remain under-discovered subjects in arthropod evolutionary researches. Gene expression abundance analyses along with developmental stages based on the large-scale RNA-seq data are also still rarely done. Here we report the de novo assembly of a Protestia brevitarsis seulensis transcriptome along four different developmental stages (egg, larva, pupa, and adult) to explore its development and evolution of wings and metamorphosis. The de novo transcriptome assembly consists of 23,551 high-quality transcripts and is approximately 96.7% complete. Out of 8,545 transcripts, 5,183 correspond to the possible orthologs with Drosophila melanogaster. As a result, we could found 265 genes related to wing development and 19 genes related to metamorphosis. The comparison of transcript expression abundance with different developmental stages revealed developmental stage-specific transcripts especially working at the stage of wing development and metamorphosis of P. b. seulensis. This transcriptome quantification along the developmental stages may provide some meaningful clues to elucidate the genetic modulation mechanism of wing development and metamorphosis obtained during the insect evolution.

Keywords: white-spotted flower chafers, transcriptomics, RNA-seq, network biology, wing development, metamorphosis

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Authors: Darshan Panda, Lambodar Behera, M. J. Baig, Sudhanshu Sekhar

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Low light intensity is a significant limitation for grain yield and quality in rice. However, yield is not significantly reduced in low-light tolerant rice varieties. The work, therefore, planned for comparative transcriptome profiling under low light stress to decipher the genes involved and molecular mechanism of low light tolerance in rice. At the active tillering stage, 50% low light exposure for one day, three days, and five days were given to Swarnaprabha (low light tolerant) and IR8 (low light sensitive) rice varieties. Illumina (HiSeq) platform was used for transcriptome sequencing. A total of 6,652 and 12,042 genes were differentially expressed due to low light intensity in Swarnaprabha and IR8, respectively, as compared to control. CAB, LRP, SBPase, MT15, TF PCL1, and Photosystem I & II complex related gene expressions were mostly increased in Swarnaprabha upon the longer duration of low light exposure, which was not found in IR8 as compared to control. Their expressions were validated by qRT-PCR. The overall study suggested that the maintenance of grain yield in the tolerant variety under low light might be the result of accelerated expression of the genes, which enable the plant to keep the photosynthetic processes moving at the same pace even under low light.

Keywords: rice, low light, photosynthesis, yield

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Authors: Omar Ali, Adesh Ramsubhag, Jayaraj Jayaraman

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Seaweed extracts have been reported as plant biostimulants which could be a safer, organic alternative to harsh pesticides. The incentive to use seaweed-based biostimulants is becoming paramount in sustainable agriculture. The current study, therefore, screened a commercial extract of A. nodosum in tomatoes, cultivated in Trinidad to showcase the multiple beneficial effects. Foliar treatment with an A. nodosum commercial extract led to significant increases in fruit yield and a significant reduction of incidence of bacterial spots and early blight diseases under both greenhouse and field conditions. Investigations were carried out to reveal the possible mechanisms of action of this biostimulant through defense enzyme assays and transcriptome profiling via RNA sequencing of tomato. Studies into disease control mechanisms by A. nodosum showed that the extract stimulated the activity of enzymes such as peroxidase, phenylalanine ammonia-lyase, chitinase, polyphenol oxidase, and β-1,3-glucanase. Additionally, the transcriptome survey revealed the upregulation and enrichment of genes responsible for the biosynthesis of growth hormones, defense enzymes, PR proteins and defense-related secondary metabolites, as well as genes involved in the nutrient mobilization, photosynthesis and primary and secondary metabolic pathways. The results of the transcriptome study also demonstrated the cross-talks between growth and defense responses, confirming the bioelicitor and biostimulant value of seaweed extracts in plants. These effects could potentially implicate the benefits of seaweed extract and validate its usage in sustainable crop production.

Keywords: A. nodosum, biostimulants, elicitor, enzymes, growth responses, seaweeds, tomato, transcriptome analysis

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Authors: Yujie Zhou, Hee-Seong Byun, Sang-In Bak, Eui-Joon Kil, Kyung Joo Min, Vivek Chavan, Won Kyong Cho, Sukchan Lee, Seung-Woo Hong, Tae-Sun Park

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Fast neutron irradiation (FNI) can cause mutations on plant genome but, in the most of cases, these irradiated plants have not shown significant characteristics phenotypically. In this study, we utilized RNA-Seq to generate a high-resolution transcriptome map of the tomato (Solanum lycopersicum) genome effected by FNI. To quantify the different transcription levels in tomato irradiated by FNI, tomato seeds were irradiated by using MC-50 cyclotron (KIRAMS, Korea) for 0, 30 and 90 minutes, respectively. To investigate the effects on the pre-soaking condition, experimental groups were divided into dry and soaked seeds, which were soaked for 8 hours before irradiation. There was no noticeable difference in the percentage germination (PG) among dry seeds, while irradiated soaked seeds have about 10 % lower PG compared to the unirradiated control group. Using whole transcriptome sequencing by HiSeq 2000, we analyzed the differential gene expression in response to different time of FNI in dry and soaked seeds. More than 1.4 million base pair reads were mapped onto the tomato reference genome and the expression pattern differences between irradiated and unirradiated seeds were assessed. In 0, 30 and 90 minutes irradiation, 12,135, 28,495 and 28,675 transcripts were generated, respectively. Gene ontology analysis suggested the different enrichment of transcripts involved in response to different FNI. The present study showed that FNI effects on plant gene expression, which can become a new parameters for evaluating the responses against FNI on plants. In addition, the comparative analysis of differentially expressed genes in D and S seeds by FNI will also give us a chance to deep explore novel candidate genes for FNI, which could be a good model system to understand the mechanisms behind the adaption of plant to space biology research.

Keywords: tomato (solanum lycopersicum), fast neutron irradiation, RNA-sequence, transcriptome expression

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Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani

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Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.

Keywords: Escherichia coli, gene regulation, network, time-series

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Authors: Vun Yee Thien, Kenneth Francis Rodrigues, Clemente Michael Vui Ling Wong, Wilson Thau Lym Yong

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Transcriptomes associated with the process of photosynthesis have offered insights into the mechanism of gene regulation in terrestrial plants; however, limited information is available as far as macroalgae are concerned. This investigation aims to decipher the underlying mechanisms associated with photosynthesis in the red alga, Kappaphycus alvarezii, by performing a differential expression analysis on a de novo assembled transcriptomes. Comparative analysis of gene expression was designed to examine the alteration of light qualities and its effect on physiological mechanisms in the red alga. High-throughput paired-end RNA-sequencing was applied to profile the transcriptome of K. alvarezii irradiated with different wavelengths of light (blue 492-455 nm, green 577-492 nm and red 780-622 nm) as compared to the full light spectrum, resulted in more than 60 million reads individually and assembled using Trinity and SOAPdenovo-Trans. The transcripts were annotated in the NCBI non-redundant (nr) protein, SwissProt, KEGG and COG databases with a cutoff E-value of 1e-5 and nearly 30% of transcripts were assigned to functional annotation by Blast searches. Differential expression analysis was performed using edgeR. The DEGs were designated to six categories: BL (blue light) regulated, GL (green light) regulated, RL (red light) regulated, BL or GL regulated, BL or RL regulated, GL or RL regulated, and either BL, GL or RL regulated. These DEGs were mapped to terms in KEGG database and compared with the whole transcriptome background to search for genes that regulated by light quality. The outcomes of this study will enhance our understanding of molecular mechanisms underlying light-induced responses in red algae.

Keywords: de novo transcriptome sequencing, differential gene expression, Kappaphycus alvareziired, red alga

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Authors: Ricardo de Oliveira Orsi, Aline Astolfi, Daniel Diego Mendes, Isabella Cristina de Castro Lippi, Jaine da Luz Scheffer, Yan Souza Lima, Juliana Lunardi, Giovanna do Padro Ribeiro, Samir Moura Kadri

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NECTAR Brazilian group (Center of Education, Science, and Technology in Rational Beekeeping) conducted studies on the pesticides honey bees effects using the transcriptome sequencing (RNA-Seq) analyzes for gene expression studies. In this way, we analyzed the effects of Pyraclostrobin and Fipronil on the honey bees with 21 old-days (forager) in laboratory conditions. For this, frames containing sealed brood were removed from the beehives and maintenance on the stove (32°C and 75% humidity) until the bees were born. So, newly emerged workers were marked on the pronotum with a non-toxic pen and reintroduced into their original hives. After 21 days, 120 marked bees were collected with an entomological forces and immediately stored in Petri dishes, perforated to ensure ventilation, and kept fasted for 3 hours. These honeybees were exposed to food contaminated or not with the sublethal dose of Pyraclostrobin (850 ppb/bee) or Fipronil (2.5 ppb/bee). After four hours of exposure, 15 bees from each treatment were referred to transcriptome analysis. Total RNA analysis was extracted from the brain pools (03 brains per pool) using the TRIzol® reagent protocol according to the manufacturer's instructions. cDNA libraries were constructed, and the FASTQC program was used to check adapter content and assess the quality of raw reads. Differential expression analysis was performed with the DESeq2 package. Genes that had an adjusted value of less than 0.05 were considered to be significantly up-regulated. Regarding the Pyraclostrobin, alterations were observed in the pattern of 17 gene related to of antioxidant system, cellular respiration, glucose metabolism, and regulation of juvenile hormone and the hormone insulin. Glyphosate altered the 10 gene related to the digestive system, exoskeleton composition, vitamin E transport, and antioxidant system. The results indicate that the necessity of studies using the sublethal doses to evaluate the pesticides uses and risks on crops and its effects on the honey bees.

Keywords: beekeeping, honey bees, pesticides, transcriptome

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Authors: Ozhan Simsek, Dicle Donmez, Burhanettin Imrak, Ahsen Isik Ozguven, Yildiz Aka Kacar

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Pomegranate (Punica granatum L.) is known to be one of the oldest edible fruit tree species, with a wide geographical global distribution. Fruits from the two defined varieties (Hicaznar and 33N26) were taken at intervals after pollination and fertilization at different sizes. Seed samples were used for transcriptome sequencing. Primary sequencing was produced by Illumina Hi-Seq™ 2000. Firstly, we had raw reads, and it was subjected to quality control (QC). Raw reads were filtered into clean reads and aligned to the reference sequences. De novo analysis was performed to detect genes expressed in seeds of pomegranate varieties. We performed downstream analysis to determine differentially expressed genes. We generated about 27.09 gb bases in total after Illumina Hi-Seq sequencing. All samples were assembled together, we got 59,264 Unigenes, the total length, average length, N50, and GC content of Unigenes are 84.547.276 bp, 1.426 bp, 2,137 bp, and 46.20 %, respectively. Unigenes were annotated with 7 functional databases, finally, 42.681(NR: 72.02%), 39.660 (NT: 66.92%), 30.790 (Swissprot: 51.95%), 20.212 (COG: 34.11%), 27.689 (KEGG: 46.72%), 12.328 (GO: 20.80%), and 33,833 (Interpro: 57.09%) Unigenes were annotated. With functional annotation results, we detected 42.376 CDS, and 4.999 SSR distribute on 16.143 Unigenes.

Keywords: next generation sequencing, SSR, RNA-Seq, Illumina

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Authors: Thomais Tsoulia, Arvind Y. M. Sundaram, Stine Braaen, Øyvind Haugland, Espen Rimstad, Øystein Wessel, Maria K. Dahle

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Fish red blood cells (RBC) are nucleated, and in addition to their function in gas exchange, they have been characterized as mediators of immune responses. Salmonid RBC are the major target cells of Piscineorthoreovirus (PRV), a virus associated with heart and skeletal muscle inflammation (HSMI) in farmed Atlantic salmon. The activation of antiviral response genesin RBChas previously been described in ex vivo and in vivo PRV-infection models, but not explored in the initial virus encounter phase. In the present study, mRNA transcriptome responses were explored in erythrocytes from individual fish, kept ex vivo, and exposed to purified PRV for 24 hours. The responses were compared to responses in macrophage-like salmon head kidney (SHK-1) and endothelial-like Atlantic salmon kidney (ASK) cells, none of which support PRV replication. The comparative analysis showed that the antiviral response to PRV was strongest in the SHK-1 cells, with a set of 80 significantly induced genes (≥ 2-fold upregulation). In RBC, 46 genes were significantly upregulated, while ASK cells were not significantly responsive. In particular, the transcriptome analysis of RBC revealed that PRV significantly induced interferon regulatory factor 1 (IRF1) and interferon-induced protein with tetratricopeptide repeats 5-like (IFIT9). However, several interferon-regulated antiviral genes which have previously been reported upregulated in PRV infected RBC in vivo (myxovirus resistance (Mx), interferon-stimulated gene 15 (ISG15), toll-like receptor 3 (TLR3)), were not significantly induced after 24h of virus stimulation. In contrast to RBC, these antiviral response genes were significantly upregulated in SHK-1. These results confirm that RBC are involved in the innate immune response to viruses, but with a delayed antiviral response compared to SHK-1. A notable difference is that interferon regulatory factor 1 (IRF-1) is the most strongly induced gene in RBC, but not among the significantly induced genes in SHK-1. Putative differences in the binding, recognition, and response to PRV, and any link to effects on the ability of PRV to replicate remains to be explored.

Keywords: antiviral responses, atlantic salmon, piscine orthoreovirus-1, red blood cells, RNA-seq

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Authors: Elena G. Salina, Vadim A. Makarov

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With the emergence of primary resistance to the current drugs and wide distribution of latent tuberculosis infection, a need for new compounds with a novel mode of action is growing steadily. Copper-mediated innate immunity and antibacterial toxicity propose novel strategies in TB drug discovery and development. Transcriptome of M. tuberculosis was obtained by RNA-seq, intracellular copper content was measured by ISP MS and complexes of 1-hydroxy-2-thiopyridines with copper were detected by HPLC.1-hydroxy-2-thiopyridine derivatives were found to be highly active in vitro against both actively growing and dormant non-culturable M. tuberculosis. Transcriptome response to 1-hydroxy-2-thiopyridines revealed signs of copper toxicity in M. tuberculosis bacilli. Indeed, Cu was found to accumulate inside cells treated with 1-hydroxy-2-thiopyridines. These compounds were found to form stable charged lipophylic complexes with Cu²⁺ ions which transport into mycobacterial cell. Subsequent metabolic destruction of the complex led to transformation of 1-hydroxy-2-thiopyridines into 2-methylmercapto-2-ethoxycarbonylpyridines, which did not possess antitubercular activity and releasing of free Cu²⁺ in the cytoplasm. 1-hydroxy-2-thiopyridines are a potent class of Cu-dependent inhibitors of M. tuberculosis which may control M. tuberculosis infection by impairment of copper homeostasis. Acknowledgment: This work was financially supported by the Ministry of Education and Science of the RussianFederation (Agreement No 14.616.21.0065; unique identifier RFMEFI61616X0065).

Keywords: copper toxicity, drug discovery, M. tuberculosis inhibitors, 2-thiopyridines

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Authors: Ashish Kumar Pathak, Ritika Sharma, Vishal Nath, Sudhir Pratap Singh, Rakesh Tuli

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Litchi is a sub-tropical fruit crop with genotypes bearing delicious juicy fruits with variable seed size (bold to rudimentary size). Small seed size is a desirable trait in litchi, as it increases consumer acceptance and fruit processing. The biochemical activities in mid- stage ovules (e.g. 16, 20, 24 and 28 days after anthesis) determine the fate of seed and fruit development in litchi. Comprehensive ovule-specific transcriptome analysis was performed in two litchi genotypes with contrasting seed size to gain molecular insight on determinants of seed fates in litchi fruits. The transcriptomic data was de-novo assembled in 1,39,608 trinity transcripts, out of which 6,325 trinity transcripts were differentially expressed between the two contrasting genotypes. Differential transcriptional pattern was found among ovule development stages in contrasting litchi genotypes. The putative genes for salicylic acid, jasmonic acid and brassinosteroid pathway were down-regulated in ovules of small-seeded litchi. Embryogenesis, cell expansion, seed size and stress related trinity transcripts exhibited altered expression in small-seeded genotype. The putative regulators of seed maturation and seed storage were down-regulated in small-seed genotype.

Keywords: Litchi, seed, transcriptome, defence

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Authors: Selisha A. Sooklal, Phelelani Mpangase, Shaun Aron, Karl Rumbold

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Organically bound fluorine (C-F bond) is extremely rare in nature. Despite this, the first fluorinated secondary metabolite, fluoroacetate, was isolated from the plant Dichapetalum cymosum (commonly known as Gifblaar). However, the enzyme responsible for fluorination (fluorinase) in Gifblaar was never isolated and very little progress has been achieved in understanding this process in higher plants. Fluorinated compounds have vast applications in the pharmaceutical, agrochemical and fine chemicals industries. Consequently, an enzyme capable of catalysing a C-F bond has great potential as a biocatalyst in the industry considering that the field of fluorination is virtually synthetic. As with any biocatalyst, a range of these enzymes are required. Therefore, it is imperative to expand the exploration for novel fluorinases. This study aimed to gain molecular insights into secondary metabolite biosynthesis in Gifblaar using a high-throughput sequencing-based approach. Mechanical wounding studies were performed using Gifblaar leaf tissue in order to induce expression of the fluorinase. The transcriptome of the wounded and unwounded plant was then sequenced on the Illumina HiSeq platform. A total of 26.4 million short sequence reads were assembled into 77 845 transcripts using Trinity. Overall, 68.6 % of transcripts were annotated with gene identities using public databases (SwissProt, TrEMBL, GO, COG, Pfam, EC) with an E-value threshold of 1E-05. Sequences exhibited the greatest homology to the model plant, Arabidopsis thaliana (27 %). A total of 244 annotated transcripts were found to be differentially expressed between the wounded and unwounded plant. In addition, secondary metabolic pathways present in Gifblaar were successfully reconstructed using Pathway tools. Due to lack of genetic information for plant fluorinases, a transcript failed to be annotated as a fluorinating enzyme. Thus, a local database containing the 5 existing bacterial fluorinases was created. Fifteen transcripts having homology to partial regions of existing fluorinases were found. In efforts to obtain the full coding sequence of the Gifblaar fluorinase, primers were designed targeting the regions of homology and genome walking will be performed to amplify the unknown regions. This is the first genetic data available for Gifblaar. It has provided novel insights into the mechanisms of metabolite biosynthesis and will allow for the discovery of the first eukaryotic fluorinase.

Keywords: biocatalyst, fluorinase, gifblaar, transcriptome

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Authors: Zhang Lei, Zhao Qingrong, Wang Chen, Zhang Sufang, Zhang Hanguo

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Larch is the main afforestation and timber tree species in Northeast China, and drought is one of the main factors limiting the growth of Larch and other organisms in Northeast China. In order to further explore the mechanism of Larch drought resistance, PEG was used to simulate drought stress. The full-length sequencing of Larch embryogenic callus under PEG simulated drought stress was carried out by combining Illumina-Hiseq and SMRT-seq. A total of 20.3Gb clean reads and 786492 CCS reads were obtained from the second and third generation sequencing. The de-redundant transcript sequences were predicted by lncRNA, 2083 lncRNAs were obtained, and the target genes were predicted, and a total of 2712 target genes were obtained. The de-redundant transcripts were further screened, and 1654 differentially expressed genes (DEGs )were obtained. Among them, different DEGs respond to drought stress in different ways, such as oxidation-reduction process, starch and sucrose metabolism, plant hormone pathway, carbon metabolism, lignin catabolic/biosynthetic process and so on. This study provides basic full-length sequencing data for the study of Larch drought resistance, and excavates a large number of DEGs in response to drought stress, which helps us to further understand the function of Larch drought resistance genes and provides a reference for in-depth analysis of the molecular mechanism of Larch drought resistance.

Keywords: larch, drought stress, full-length transcriptome sequencing, differentially expressed genes

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Authors: Ricardo Godoy, Herbert Venthur, Hector Jimenez, Andres Quiroz, Ana Mutis

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In agriculture, grape production has great economic importance at global level, considering that in 2013 it reached 7.4 million hectares (ha) covered by plantations of this fruit worldwide. Chile is the number one exporter in the world with 800,000 tons. However, these values have been threatened by the attack of the grapevine moth, Lobesia botrana (Denis & Schiffermuller) (Lepidoptera: Tortricidae), since its detection in 2008. Nowadays, the use of semiochemicals, in particular the major component of the sex pheromone, (E,Z)-7.9-dodecadienil acetate, are part of mating disruption methods to control L. botrana. How insect pests can recognize these molecules, is being part of huge efforts to deorphanize their olfactory mechanism at molecular level. Thus, an interesting group of proteins has been identified in the antennae of insects, where odorant-binding proteins (OBPs) are known by transporting molecules to odorant receptors (ORs) and a co-receptor (ORCO) causing a behavioral change in the insect. Other proteins such as chemosensory proteins (CSPs), ionotropic receptors (IRs), odorant degrading enzymes (ODEs) and sensory neuron membrane proteins (SNMPs) seem to be involved, but few studies have been performed so far. The above has led to an increasing interest in insect communication at a molecular level, which has contributed to both a better understanding of the olfaction process and the design of new pest management strategies. To date, it has been reported that the ORs can detect one or a small group of odorants in a specific way. Therefore, the objective of this study is the identification of genes that encode these ORs using the antennal transcriptome of L. botrana. Total RNA was extracted for females and males of L. botrana, and the antennal transcriptome sequenced by Next Generation Sequencing service using an Illumina HiSeq2500 platform with 50 million reads per sample. Unigenes were assembled using Trinity v2.4.0 package and transcript abundance was obtained using edgeR. Genes were identified using BLASTN and BLASTX locally installed in a Unix system and based on our own Tortricidae database. Those Unigenes related to ORs were characterized using ORFfinder and protein Blastp server. Finally, a phylogenetic analysis was performed with the candidate amino acid sequences for LbotORs including amino acid sequences of other moths ORs, such as Bombyx mori, Cydia pomonella, among others. Our findings suggest 61 genes encoding ORs and one gene encoding an ORCO in both sexes, where the greatest difference was found in the OR6 because of the transcript abundance according to the value of FPKM in females and males was 1.48 versus 324.00. In addition, according to phylogenetic analysis OR6 is closely related to OR1 in Cydia pomonella and OR6, OR7 in Epiphyas postvittana, which have been described as pheromonal receptors (PRs). These results represent the first evidence of ORs present in the antennae of L. botrana and a suitable starting point for further functional studies with selected ORs, such as OR6, which is potentially related to pheromonal recognition.

Keywords: antennal transcriptome, lobesia botrana, odorant receptors (ORs), phylogenetic analysis

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Authors: Li-Te Lin, Chia-Jung Li, Kuan-Hao Tsui

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Cuproptosis, a newly identified cell death mechanism, has attracted attention for its association with various diseases. However, the genetic interplay between cuproptosis and ovarian aging remains largely unexplored. This study aims to address this gap by analyzing datasets related to ovarian aging and cuproptosis. Spatial transcriptome analyses were conducted in the ovaries of both young and aged female mice to elucidate the role of FDX1. Comprehensive bioinformatics analyses, facilitated by R software, identified FDX1 as a potential cuproptosis-related gene with implications for ovarian aging. Clinical infertility biopsies were examined to validate these findings, showing consistent results in elderly infertile patients. Furthermore, pharmacogenomic analyses of ovarian cell lines explored the intricate association between FDX1 expression levels and sensitivity to specific small molecule drugs. Spatial transcriptome analyses revealed a significant reduction in FDX1 expression in aging ovaries, supported by consistent findings in biopsies from elderly infertile patients. Pharmacogenomic investigations indicated that modulating FDX1 could influence drug responses in ovarian-related therapies. This study pioneers the identification of FDX1 as a cuproptosis-related gene linked to ovarian aging. These findings not only contribute to understanding the mechanisms of ovarian aging but also position FDX1 as a potential diagnostic biomarker and therapeutic target. Further research may establish FDX1's pivotal role in advancing precision medicine and therapies for ovarian-related conditions.

Keywords: cuproptosis, FDX1, ovarian aging, biomarker

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Authors: Jin Young Kim, Kwon Kyoo Kang

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The SGR1 (STAYGREEN1) protein is a critical regulator of plant leaves in chlorophyll degradation and senescence. The functions and mechanisms of tomato SGR1 action are poorly understood and worthy of further investigation. To investigate the function of the SGR1 gene, we generated a SGR1-knockout (KO) null line via clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9-mediated gene editing and conducted RNA sequencing and gas chromatography tandem mass spectrometry (GC-MS/MS) analysis to identify the differentially expressed genes. The SlSGR1 (Solanum lycopersicum SGR1) knockout null line clearly showed a turbid brown color with significantly higher chlorophyll and carotenoid content compared to wild-type (WT) fruit. Differential gene expression analysis revealed 728 differentially expressed genes (DEGs) between WT and sgr1 #1-6 line, including 263 and 465 downregulated and upregulated genes, respectively, for which fold change was >2, and the adjusted p-value was <0.05. Most of the DEGs were related to photosynthesis and chloroplast function. In addition, the pigment, carotenoid changes in sgr1 #1-6 line was accumulated of key primary metabolites such as sucrose and its derivatives (fructose, galactinol, raffinose), glycolytic intermediates (glucose, G6P, Fru6P) and tricarboxylic acid cycle (TCA) intermediates (malate and fumarate). Taken together, the transcriptome and metabolite profiles of SGR1-KO lines presented here provide evidence for the mechanisms underlying the effects of SGR1 and molecular pathways involved in chlorophyll degradation and carotenoid biosynthesis.

Keywords: tomato, CRISPR/Cas9, null line, RNA-sequencing, metabolite profiling

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Authors: Tettey Afi Pamela, Sotaro Fujii, Hidetoshi Saito, Kawaii Koichiro

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Introduction: Organisms employ adaptive mechanisms when faced with any stressor or risk of being wiped out. This has made it possible for them to survive in harsh environmental conditions such as increasing temperature, low pH, and anoxia. Some of the mechanisms they utilize include the expression of heat shock proteins, synthesis of cryoprotectants, and anhydrobiosis. Heat shock proteins (HSPs) have been widely studied to determine their involvement in stress tolerance among various organism, of which chironomid species have been no exception. We examined the survival and expression of genes encoding five (5) heat shock proteins (HSP70, HSP67, HSP60, HSP27, and HSP23) from Chironomus sulfurosus larvae reared from 1st instar at 25°C, 30°C, 35°C, and 40°C. Results: The highest survival rate was recorded at 30°C, followed by 25°C, then 35°C. Only a small percentage of C. sulfurosus survived at 40°C (14.5%). With regards to HSPs expression, some HSPs responded to an increase in high temperature. The relative expression levels were lowest at 30°C for HSP70, HSP60, HSP27, and HSP23. At 25°C and 40°C, HSP70, HSP67, HSP60, HSP27, and HSP23 had the highest expression. At 35°C, all had the lowest expression. Discussion: The expression of heat shock proteins varies from one species to another. We designated the genes HSP 70, HSP 67, HSP 60, HSP 27, and HSP 23 genes based on transcriptome analysis of C. sulfurosus. Our study can be termed as a long-heat shock study as C. sulfurosus was reared from the first instar to the fourth instar, and this might have led to a continuous induction of HSPs at 25°C. 40°C had the lowest survival but highest HSPs expression as C. sulfurosus larvae had to utilize HSPs for sustenance. These results and future high-throughput studies at both the transcriptome and proteome level will improve the information needed to predict the future geographic distribution of these species within the context of global warming.

Keywords: chironomid, heat shock proteins, high temperature, heat shock protein expression

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Authors: Abhaydeep Pandey, Shweta Shukla, Saptamita Goswami, Bhaswati Bandyopadhyay, Vishnampettai Ramachandran, Sudhanshu Vrati, Arup Banerjee

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Background: Long non-coding RNAs (lncRNAs) are the important regulators of gene expression and play important role in viral replication and disease progression. The role of lncRNA genes in the pathogenesis of Dengue virus-mediated pathogenesis is currently unknown. Methods: To gain additional insights, we utilized an unbiased RNA sequencing followed by in silico analysis approach to identify the differentially expressed lncRNA and genes that are associated with dengue disease progression. Further, we focused our study on lncRNAs NEAT1 (Nuclear Paraspeckle Assembly Transcript 1) as it was found to be differentially expressed in PBMC of dengue infected patients. Results: The expression of lncRNAs NEAT1, as compared to dengue infection (DI), was significantly down-regulated as the patients developed the complication. Moreover, pairwise analysis on follow up patients confirmed that suppression of NEAT1 expression was associated with rapid fall in platelet count in dengue infected patients. Severe dengue patients (DS) (n=18; platelet count < 20K) when recovered from infection showing high NEAT1 expression as it observed in healthy donors. By co-expression network analysis and subsequent validation, we revealed that coding gene; IFI27 expression was significantly up-regulated in severe dengue cases and negatively correlated with NEAT1 expression. To discriminate DI from dengue severe, receiver operating characteristic (ROC) curve was calculated. It revealed sensitivity and specificity of 100% (95%CI: 85.69 – 97.22) and area under the curve (AUC) = 0.97 for NEAT1. Conclusions: Altogether, our first observations demonstrate that monitoring NEAT1and IFI27 expression in dengue patients could be useful in understanding dengue virus-induced disease progression and may be involved in pathophysiological processes.

Keywords: dengue, lncRNA, NEAT1, transcriptome

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Authors: Leo Nnamdi Ozurumba-Dwight

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Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Sajewicz-Krukowska Joanna, Domańska-Blicharz Katarzyna, Tarasiuk Karolina, Marzec-Kotarska Barbara

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Astroviral infections pose a significant problem in the poultry industry, leading to multiple adverse effects such as decreased egg production, breeding disorders, poor weight gain, and even increased mortality. Commonly observed chicken astrovirus (CAstV) was recently reported to be responsible for "white chicks syndrome" associated with increased embryo/chick mortality. The CAstV-mediated pathogenesis in chicken occurs due to complex interactions between the infectious pathogen and the immune system. Many aspects of CAstV-chicken interactions remain unclear, and there is no information available regarding gene expression changes in the chicken's spleen in response to CAstV infection. We aimed to investigate the molecular background triggered by CAstV infection. Ten 21-day-old SPF White Leghorn chickens were divided into two groups of 5 birds each. One group was inoculated with CAstV, and the other was used as the negative control. On 4th dpi, spleen samples were collected and immediately frozen at -70°C for RNA isolation. We analysed transcriptional profiles of the chickens' spleens at the 4th day following infection using RNA-seq to establish differentially expressed genes (DEGs). The RNA-seq findings were verified by quantitative real-time PCR (qRT-PCR). A total of 31959 transcripts were identified in response to CAstV infection. Eventually 45 DEGs (p-value<0.05; Log2Foldchange>1)were recognized in the spleen after CAstV infection (26 upregulated DEGs and 19 downregulated DEGs). qRT-PCR performed on 4 genes (IFIT5, OASL, RASD1, DDX60) confirmed RNAseq results. Top differentially expressed genes belonged to novel putative IFN-induced CAstV restriction factors. Most of the DEGs were associated with RIG-I–like signalling pathway or, more generally, with an innate antiviral response(upregulated: BLEC3, CMPK2, IFIT5, OASL, DDX60, IFI6, and downregulated: SPIK5, SELENOP, HSPA2, TMEM158, RASD1, YWHAB). The study provided a global analysis of host transcriptional changes that occur during CAstV infection in vivo and proved the cell cycle in the spleen and immune signalling in chickens were predominantly affected upon CAstV infection.

Keywords: chicken astrovirus, CastV, RNA-seq, transcriptome, spleen

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Authors: Ethel E. Phiri, Lionel Hartzenberg, Percy Chimwamuromba, Emmanuel Nepolo, Jens Kossmann, James R. Lloyd

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Orphan crops are underresearched and underutilized food plant species that have not been categorized as major food crops, but have the potential to be economically and agronomically significant. They have been documented to have the ability to tolerate extreme environmental conditions. However, limited research has been conducted to uncover their potential as food crop species. The New Partnership for Africa’s Development (NEPAD) has classified Marama bean, Tylosema esculentum, as an orphan crop. The plant is one of the 101 African orphan crops that must have their genomes sequenced, assembled, and annotated in the foreseeable future. Marama bean is a perennial leguminous plant that primarily grows in poor, arid soils in southern Africa. The plants produce large tubers that can weigh as much as 200kg. While the foliage provides fodder, the tuber is carbohydrate rich and is a staple food source for rural communities in Namibia. Also, the edible seeds are protein- and oil-rich. Marama Bean plants respond rapidly to increased temperatures and severe water scarcity without extreme consequences. Advances in molecular biology and biotechnology have made it possible to effectively transfer technologies between model- and major crops to orphan crops. In this research, the aim was to assemble the first transcriptomic analysis of Marama Bean RNA-sequence data. Many model plant species have had their genomes sequenced and their transcriptomes assembled. Therefore the availability of transcriptome data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this research will eventually evaluate the potential use of Marama Bean as a crop species to improve its value in agronomy. data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this researc will eventually evaluate the potential use of Marama bean as a crop species to improve its value in agronomy.

Keywords: 101 African orphan crops, RNA-Seq, Tylosema esculentum, underutilised crop plants

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Authors: Ahmed Bahieldin, Ahmed Atef, Jamal S. M. Sabir, Nour O. Gadalla, Sherif Edris, Ahmed M. Alzohairy, Nezar A. Radhwan, Mohammed N. Baeshen, Ahmed M. Ramadan, Hala F. Eissa, Sabah M. Hassan, Nabih A. Baeshen, Osama Abuzinadah, Magdy A. Al-Kordy, Fotouh M. El-Domyati, Robert K. Jansen

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Wild salt-tolerant barley (Hordeum spontaneum) is the ancestor of cultivated barley (Hordeum vulgare or H. vulgare). Although the cultivated barley genome is well studied, little is known about genome structure and function of its wild ancestor. In the present study, RNA-Seq analysis was performed on young leaves of wild barley treated with salt (500 mM NaCl) at four different time intervals. Transcriptome sequencing yielded 103 to 115 million reads for all replicates of each treatment, corresponding to over 10 billion nucleotides per sample. Of the total reads, between 74.8 and 80.3% could be mapped and 77.4 to 81.7% of the transcripts were found in the H. vulgare unigene database (unigene-mapped). The unmapped wild barley reads for all treatments and replicates were assembled de novo and the resulting contigs were used as a new reference genome. This resultedin94.3 to 95.3%oftheunmapped reads mapping to the new reference. The number of differentially expressed transcripts was 9277, 3861 of which were uni gene-mapped. The annotated unigene- and de novo-mapped transcripts (5100) were utilized to generate expression clusters across time of salt stress treatment. Two-dimensional hierarchical clustering classified differential expression profiles into nine expression clusters, four of which were selected for further analysis. Differentially expressed transcripts were assigned to the main functional categories. The most important groups were ‘response to external stimulus’ and ‘electron-carrier activity’. Highly expressed transcripts are involved in several biological processes, including electron transport and exchanger mechanisms, flavonoid biosynthesis, reactive oxygen species (ROS) scavenging, ethylene production, signaling network and protein refolding. The comparisons demonstrated that mRNA-Seq is an efficient method for the analysis of differentially expressed genes and biological processes under salt stress.

Keywords: electron transport, flavonoid biosynthesis, reactive oxygen species, rnaseq

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Authors: Nisha Govender, Siju Senan, Zeti-Azura Hussein, Wickneswari Ratnam

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Jatropha curcas, a well-described bioenergy crop has been extensively accepted as future fuel need especially in tropical regions. Ideal planting material required for large-scale plantation is still lacking. Breeding programmes for improved J. curcas varieties are rendered difficult due to limitations in genetic diversity. Using a combined transcriptome and physiological data, we investigated the molecular and physiological differences in high and low yielding Jatropha curcas to address plausible heritable variations underpinning these differences, in regard to photosynthesis, a key metabolism affecting yield potentials. A total of 6 individual Jatropha plant from 4 accessions described as high and low yielding planting materials were selected from the Experimental Plot A, Universiti Kebangsaan Malaysia (UKM), Bangi. The inflorescence and shoots were collected for transcriptome study. For the physiological study, each individual plant (n=10) from the high and low yielding populations were screened for agronomic traits, chlorophyll content and stomatal patterning. The J. curcas transcriptomes are available under BioProject PRJNA338924 and BioSample SAMN05827448-65, respectively Each transcriptome was subjected to functional annotation analysis of sequence datasets using the BLAST2Go suite; BLASTing, mapping, annotation, statistical analysis and visualization Large-scale phenotyping of the number of fruits per plant (NFPP) and fruits per inflorescence (FPI) classified the high yielding Jatropha accessions with average NFPP =60 and FPI > 10, whereas the low yielding accessions yielded an average NFPP=10 and FPI < 5. Next generation sequencing revealed genes with differential expressions in the high yielding Jatropha relative to the low yielding plants. Distinct differences were observed in transcript level associated to photosynthesis metabolism. DEGs collection in the low yielding population showed comparable CAM photosynthetic metabolism and photorespiration, evident as followings: phosphoenolpyruvate phosphate translocator chloroplastic like isoform with 2.5 fold change (FC) and malate dehydrogenase (2.03 FC). Green leaves have the most pronounced photosynthetic activity in a plant body due to significant accumulation of chloroplast. In most plants, the leaf is always the dominant photosynthesizing heart of the plant body. Large number of the DEGS in the high-yielding population were found attributable to chloroplast and chloroplast associated events; STAY-GREEN chloroplastic, Chlorophyllase-1-like (5.08 FC), beta-amylase (3.66 FC), chlorophyllase-chloroplastic-like (3.1 FC), thiamine thiazole chloroplastic like (2.8 FC), 1-4, alpha glucan branching enzyme chloroplastic amyliplastic (2.6FC), photosynthetic NDH subunit (2.1 FC) and protochlorophyllide chloroplastic (2 FC). The results were parallel to a significant increase in chlorophyll a content in the high yielding population. In addition to the chloroplast associated transcript abundance, the TOO MANY MOUTHS (TMM) at 2.9 FC, which code for distant stomatal distribution and patterning in the high-yielding population may explain high concentration of CO2. The results were in agreement with the role of TMM. Clustered stomata causes back diffusion in the presence of gaps localized closely to one another. We conclude that high yielding Jatropha population corresponds to a collective function of C3 metabolism with a low degree of CAM photosynthetic fixation. From the physiological descriptions, high chlorophyll a content and even distribution of stomata in the leaf contribute to better photosynthetic efficiency in the high yielding Jatropha compared to the low yielding population.

Keywords: chlorophyll, gene expression, genetic variation, stomata

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Authors: Likith Reddy Pinninti, Fredrik Ribsskog Staven, Leslie Robert Noble, Jorge Manuel de Oliveira Fernandes, Deepti Manjari Patel, Torstein Kristensen

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Understanding fish behavior is essential to improve animal welfare in aquaculture research. Behavioral traits can have a strong influence on fish health and habituation. To identify the genes and biological pathways responsible for lumpfish behavior, we performed an experiment to understand the interspecies relationship (mutualism) between the lumpfish and salmon. Also, we tested the correlation between the gene expression data vs. observational/physiological data to know the essential genes that trigger stress and swimming behavior in lumpfish. After the de novo assembly of the brain transcriptome, all the samples were individually mapped to the available lumpfish (Cyclopterus lumpus L.) primary genome assembly (fCycLum1.pri, GCF_009769545.1). Out of ~16749 genes expressed in brain samples, we found 267 genes to be statistically significant (P > 0.05) found only in odor and control (1), model and control (41) and salmon and control (225) groups. However, genes with |LogFC| ≥0.5 were found to be only eight; these are considered as differentially expressed genes (DEG’s). Though, we are unable to find the differential genes related to the behavioral traits from RNA-Seq data analysis. From the correlation analysis, between the gene expression data vs. observational/physiological data (serotonin (5HT), dopamine (DA), 3,4-Dihydroxyphenylacetic acid (DOPAC), 5-hydroxy indole acetic acid (5-HIAA), Noradrenaline (NORAD)). We found 2495 genes found to be significant (P > 0.05) and among these, 1587 genes are positively correlated with the Noradrenaline (NORAD) hormone group. This suggests that Noradrenaline is triggering the change in pigmentation and skin color in lumpfish. Genes related to behavioral traits like rhythmic, locomotory, feeding, visual, pigmentation, stress, response to other organisms, taxis, dopamine synthesis and other neurotransmitter synthesis-related genes were obtained from the correlation analysis. In KEGG pathway enrichment analysis, we find important pathways, like the calcium signaling pathway and adrenergic signaling in cardiomyocytes, both involved in cell signaling, behavior, emotion, and stress. Calcium is an essential signaling molecule in the brain cells; it could affect the behavior of fish. Our results suggest that changes in calcium homeostasis and adrenergic receptor binding activity lead to changes in fish behavior during stress.

Keywords: behavior, De novo, lumpfish, salmon

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Almudena Espin Perez, Tyler Risom, Carl Pelz, Isabel English, Robert M. Angelo, Rosalie Sears, Andrew J. Gentles

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Pancreatic ductal adenocarcinoma (PDAC) is one of the most deadly malignancies. The role of the tumor microenvironment (TME) is gaining significant attention in cancer research. Despite ongoing efforts, the nature of the interactions between tumors, immune cells, and stromal cells remains poorly understood. The cell-intrinsic properties that govern cell lineage plasticity in PDAC and extrinsic influences of immune populations require technically challenging approaches due to the inherently heterogeneous nature of PDAC. Understanding the cell lineage plasticity of PDAC will improve the development of novel strategies that could be translated to the clinic. Members of the team have demonstrated that the acquisition of ductal to neuroendocrine lineage plasticity in PDAC confers therapeutic resistance and is a biomarker of poor outcomes in patients. Our approach combines computational methods for deconvolving bulk transcriptomic cancer data using CIBERSORTx and high-throughput single-cell imaging using Multiplexed Ion Beam Imaging (MIBI) to study lineage plasticity in PDAC and its relationship to the infiltrating immune system. The CIBERSORTx algorithm uses signature matrices from immune cells and stroma from sorted and single-cell data in order to 1) infer the fractions of different immune cell types and stromal cells in bulked gene expression data and 2) impute a representative transcriptome profile for each cell type. We studied a unique set of 300 genomically well-characterized primary PDAC samples with rich clinical annotation. We deconvolved the PDAC transcriptome profiles using CIBERSORTx, leveraging publicly available single-cell RNA-seq data from normal pancreatic tissue and PDAC to estimate cell type proportions in PDAC, and digitally reconstruct cell-specific transcriptional profiles from our study dataset. We built signature matrices and optimized by simulations and comparison to ground truth data. We identified cell-type-specific transcriptional programs that contribute to cancer cell lineage plasticity, especially in the ductal compartment. We also studied cell differentiation hierarchies using CytoTRACE and predict cell lineage trajectories for acinar and ductal cells that we believe are pinpointing relevant information on PDAC progression. Collaborators (Angelo lab, Stanford University) has led the development of the Multiplexed Ion Beam Imaging (MIBI) platform for spatial proteomics. We will use in the very near future MIBI from tissue microarray of 40 PDAC samples to understand the spatial relationship between cancer cell lineage plasticity and stromal cells focused on infiltrating immune cells, using the relevant markers of PDAC plasticity identified from the RNA-seq analysis.

Keywords: deconvolution, imaging, microenvironment, PDAC

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