Whole genome discovery of regulatory genes responsible for the response of chicken to heat stress.

Long noncoding RNAs (lncRNAs) are functional bridges connecting the genome with phenotypes by interacting with DNA, mRNA, and proteins. Using publically available acute heat stress (AHS)-related RNA-seq data, we discovered novel lncRNAs and tested their association with AHS along with ~ 8800 known lncRNAs and ~ 28,000 mRNA transcripts. Our pipeline discovered a total of 145 potentially novel-lncRNAs. One of them (Fishcomb_p-value = 0.06) along with another novel transcript (annotated as protein-coding; Fishcomb_p-value = 0.03) were identified as significantly associated with AHS. We found five known-lncRNAs and 134 mRNAs transcripts that were significantly associated with AHS. Four novel lncRNAs interact cis-regulated with 12 mRNA transcripts and are targeted by 11 miRNAs. Also six meta-lncRNAs associate with 134 meta-mRNAs through trans-acting co-expression, each targeted by 15 and 216 miRNAs, respectively. Three of the known-lncRNAs significantly co-expressed with almost 97 of the significant mRNAs (Pearson correlation p-value < 0.05). We report the mentioned three known-lncRNAs (ENSGALT00000099876, ENSGALT00000107573, and ENSGALT00000106323) as the most, significantly regulatory elements of AHS in chicken. It can be concluded that in order to alleviate the adverse effects of AHS on chicken, the manipulation of the three regulatory lncRNAs could lead to a more desirable result than the manipulation of the most significant mRNAs.

Different transcription of novel, functional long non-coding RNA genes by UV-B in green algae, Volvox carteri / Transcripción diferente de genes de ARN largos no codificantes novedosos y funcionales mediante UV-B en algas verdes, Volvox carteri

Long non-coding RNAs (lncRNAs) are identified as important regulatory molecules related to diverse biological processes. In recent years, benefiting from the rapid development of high-throughput sequencing technology, RNA-seq, and analysis methods, more lncRNAs have been identified and discovered in various plant and algal species. However, so far, only limited studies related to algal lncRNAs are available. Volvox carteri f. nagariensis is the best multicellular model organism to study in developmental and evolutionary biology; therefore, studying and increasing information about this species is important. This study identified lncRNAs in the multicellular green algae Volvox carteri and 1457 lncRNAs were reported, using RNA-seq data and with the help of bioinformatics tools and software. This study investigated the effect of low-dose UV-B radiation on changes in the expression profile of lncRNAs in gonidial and somatic cells. The differential expression of lncRNAs was analyzed between the treatment (UV-B) and the control (WL) groups in gonidial and somatic cells. A total of 37 and 26 lncRNAs with significant differential expression in gonidial and somatic cells, respectively, were reported. Co-expression analysis between the lncRNAs and their neighbor protein-coding genes (in the interval of ± 10 Kb) was accomplished. In gonidial cells, 184 genes with a positive correlation and 13 genes with a negative correlation (greater than 0.95), and in somatic cells, 174 genes with a positive correlation, and 18 genes with a negative correlation were detected. Functional analysis of neighboring coding genes was also performed based on gene ontology. The results of the current work may help gain deeper insight into the regulation of gene expression in the studied model organism, Volvox carteri.(AU)

Different transcription of novel, functional long non-coding RNA genes by UV-B in green algae, Volvox carteri.

Long non-coding RNAs (lncRNAs) are identified as important regulatory molecules related to diverse biological processes. In recent years, benefiting from the rapid development of high-throughput sequencing technology, RNA-seq, and analysis methods, more lncRNAs have been identified and discovered in various plant and algal species. However, so far, only limited studies related to algal lncRNAs are available. Volvox carteri f. nagariensis is the best multicellular model organism to study in developmental and evolutionary biology; therefore, studying and increasing information about this species is important. This study identified lncRNAs in the multicellular green algae Volvox carteri and 1457 lncRNAs were reported, using RNA-seq data and with the help of bioinformatics tools and software. This study investigated the effect of low-dose UV-B radiation on changes in the expression profile of lncRNAs in gonidial and somatic cells. The differential expression of lncRNAs was analyzed between the treatment (UV-B) and the control (WL) groups in gonidial and somatic cells. A total of 37 and 26 lncRNAs with significant differential expression in gonidial and somatic cells, respectively, were reported. Co-expression analysis between the lncRNAs and their neighbor protein-coding genes (in the interval of ± 10 Kb) was accomplished. In gonidial cells, 184 genes with a positive correlation and 13 genes with a negative correlation (greater than 0.95), and in somatic cells, 174 genes with a positive correlation, and 18 genes with a negative correlation were detected. Functional analysis of neighboring coding genes was also performed based on gene ontology. The results of the current work may help gain deeper insight into the regulation of gene expression in the studied model organism, Volvox carteri.

Comprehensive Gene Expression Profiling Analysis of Adipose Tissue in Male Individuals from Fat- and Thin-Tailed Sheep Breeds.

It has been shown that tail fat content varies significantly among sheep breeds and plays a significant role in meat quality. Recently, significant efforts have been made to understand the physiological, biochemical, and genomic regulation of fat deposition in sheep tails in order to unravel the mechanisms underlying energy storage and adipose tissue lipid metabolism. RNA-seq has enabled us to provide a high-resolution snapshot of differential gene expression between fat- and thin-tailed sheep breeds. Therefore, three RNA-seq datasets were meta-analyzed for the current work to elucidate the transcriptome profile differences between them. Specifically, we identified hub genes, performed gene ontology (GO) analysis, carried out enrichment analyses of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and validated hub genes using machine learning algorithms. This approach revealed a total of 136 meta-genes, 39 of which were not significant in any of the individual studies, indicating the higher statistical power of the meta-analysis. Furthermore, the results derived from the use of machine learning revealed POSTN, K35, SETD4, USP29, ANKRD37, RTN2, PRG4, and LRRC4C as substantial genes that were assigned a higher weight (0.7) than other meta-genes. Among the decision tree models, the Random Forest ones surpassed the others in adipose tissue predictive power fat deposition in fat- and thin-tailed breeds (accuracy > 0.85%). In this regard, combining meta-analyses and machine learning approaches allowed for the identification of three important genes (POSTN, K35, SETD4) related to lipid metabolism, and our findings could help animal breeding strategies optimize fat-tailed breeds' tail sizes.

Gene expression networks and functionally enriched pathways involved in the response of domestic chicken to acute heat stress.

Heat stress in poultry houses, especially in warm areas, is one of the main environmental factors that restrict the growth of broilers or laying performance of layers, suppresses the immune system, and deteriorates egg quality and feed conversion ratio. The molecular mechanisms underlying the response of chicken to acute heat stress (AHS) have not been comprehensively elucidated. Therefore, the main object of the current work was to investigate the liver gene expression profile of chickens under AHS in comparison with their corresponding control groups, using four RNA-seq datasets. The meta-analysis, GO and KEGG pathway enrichment, WGCNA, machine-learning, and eGWAS analyses were performed. The results revealed 77 meta-genes that were mainly related to protein biosynthesis, protein folding, and protein transport between cellular organelles. In other words, under AHS, the expression of genes involving in the structure of rough reticulum membrane and in the process of protein folding was adversely influenced. In addition, genes related to biological processes such as "response to unfolded proteins," "response to reticulum stress" and "ERAD pathway" were differentially regulated. We introduce here a couple of genes such as HSPA5, SSR1, SDF2L1, and SEC23B, as the most significantly differentiated under AHS, which could be used as bio-signatures of AHS. Besides the mentioned genes, the main findings of the current work may shed light to the identification of the effects of AHS on gene expression profiling of domestic chicken as well as the adaptive response of chicken to environmental stresses.

Investigation of chicken housekeeping genes using next-generation sequencing data.

Accurate normalization of the gene expression assays, using housekeeping genes (HKGs), is critically necessary. To do so, selection of a proper set of HKGs for a specific experiment is of great importance. Despite many studies, there is no consensus about the suitable set of HKGs for implementing in the quantitative real-time PCR analyses of chicken tissues. A limited number of HKGs have been widely used. However, wide utilization of a little number of HKGs for all tissues is challenging. The emergence of high-throughput gene expression RNA-seq data has enabled the simultaneous comparison of the stability of multiple HKGs. Therefore, employing the average coefficient of variations of at least three datasets per tissue, we sorted all reliably expressed genes (REGs; with FPKM ≥ 1 in at least one sample) and introduced the top 10 most suitable and stable reference genes for each of the 16 chicken tissues. We evaluated the consistency of the results of five tissues using the same methodology on other datasets. Furthermore, we assessed 96 previously widely used HKGs (WU-HKGs) in order to challenge the accuracy of the previous studies. The New Tuxedo software suite was used for the main analyses. The results revealed novel, different sets of reference genes for each of the tissues with 17 common genes among the top 10 genes lists of 16 tissues. The results did disprove the suitability of WU-HKGs such as Actb, Ldha, Scd, B2m, and Hprt1 for any of the tissues examined. On the contrary, a total of 6, 13, 14, 23, and 32 validated housekeeping genes (V-HKGs) were discovered as the most stable and suitable reference genes for muscle, spleen, liver, heart, and kidney tissues, respectively. Although we identified a few new HKGs usable for multiple tissues, the selection of suitable HKGs is required to be tissue specific. The newly introduced reference genes from the present study, despite lacking experimental validation, will be able to contribute to the more accurate normalization for future expression analysis of chicken genes.

Effects of supplementary inulin on ewes milk composition and rumen fermentation parameters.

This experiment aimed to investigate the effects of inulin supplementation on milk production and composition, feed intake, nutrient digestibility and rumen fermentation parameters in lactating ewes. The experimental treatments were (1) control group (basal diet), (2) basal diet plus 2% inulin (w/w) and (3) basal diet plus 4% inulin (w/w). The experiment was carried out for 21 d in a fully randomized design involving eighteen Ghezel ewes. Production and composition (percentages of fat, protein, lactose and fat-free solids and fatty acid profiles) of milk were measured. Faeces were collected in the last 3 days of the experiment to determine digestibility. On the last day of the experiment, rumen fluid samples were taken from the esophagus 3 h after feeding and fermentation parameters (pH, ammonia nitrogen (N-NH3), volatile fatty acids (VFA) and protozoal population) were examined. Daily milk production was not significantly affected by inulin supplementation, but the fat and protein content of the milk was increased whilst urea nitrogen (MUN) and unsaturated fatty acids were decreased (P < 0.05). The dry matter (DM) intake results showed that there was no significant difference between different diets. The highest digestibility of DM and NDF belonged to the inulin fed group (P < 0.05). Inulin consumption numerically increased the pH of the rumen fluid of the animals and significantly decreased the rumen N-NH3 value (P < 0.05). Inulin supplementation also significantly increased total VFA, acetate, and butyrate levels (P < 0.05). In general, it can be concluded that inulin supplementation can improve rumen fermentation, DM and NDF digestibility,as well as compositional aspects of the ewe's milk production.

A meta-analysis of microarray data revealed hub genes and transcription factors involved in drought stress response in rice (Oryza sativa L.).

Although there are various studies attempted to clarify the genetic mechanism of plant response to drought stress that reduces crop yield, a meta-analysis can integrate the results of them to provide a better picture of the issue. Therefore, in this study, several microarray datasets of rice were meta-analysed under drought stress and normal condition using the R packages. Accordingly, differentially expressed genes (meta-DEGs) were identified. The results showed 643 and 677 upregulated and downregulated genes, respectively. The significant common Gene Ontology (GO) terms between the up- and downregulated genes were responses to abiotic stimulus , water deprivation , oxygen-containing compound and abscisic acid . The transcription factors (TF) survey showed that bHLH under drought stress activates up genes 42% more than down genes while bzip Homeodomain activates down genes 54% more than up genes. The hub downregulated genes obtained from this study were mainly related to photosynthesis and the hub upregulated genes were mainly related to stress tolerance which include heat shock proteins (HSPs), late embryogenesis abundant (LEAs), calmodulin-like protein (CML), phosphatase 2C (PP2Cs) and IAA genes. Moreover, this meta-analysis data were compared with other experimental data and the results confirmed the up and down expression of them. Our findings can provide novel insights into the molecular mechanism of rice (Oryza sativa L.) response to drought stress.

Identification of differentially expressed genes in salt-tolerant oilseed sunflower (Helianthus annuus L.) genotype by RNA sequencing.

BACKGROUND: Sunflower (Helianthus annuus L.) is widely planted as an oilseed crop worldwide. Salt stress is one of the major abiotic stresses that negatively affect crop growth and productivity. To counter the negative impact of salt stress, plants have developed avoidance and tolerance mechanisms. Developing salt-tolerant genotypes requires understanding the molecular basis of adaptive mechanisms in depth. Although using model plants i.e., Arabidopsis has improved our understanding of salt tolerant mechanisms, the relative impotence and regulation mechanisms vary among plant species due to differences in genetic and metabolic backgrounds. On the other hand, sunflower is a highly polymorphic plant due to its cross-pollinated behavior which provides different salt-tolerant genotypes available for comparative analyses. METHODS AND RESULTS: In order to gain a better view of molecular mechanisms involved in salt tolerance in sunflower, RNA sequencing analysis was realized by evaluating a tolerant genotype (AS5305) with two biological replicates under control and salt stress conditions in a controlled environment. Salinity stress was applied from NaCl resource at the 8-leaf stage and samplings were done at 24 h post salt stress application. Sequencing data were analyzed using tuxedo software suite. Blast2GO software and the KEGG database were used to identify the functional tasks of each of the assembled transcripts. Analysis of genes with robust expression (i.e., with FPKM > 1 in at least one sample) revealed a total of 121 significantly expressed genes between the saline-stressed and control samples. The differential expression of 11 genes was confirmed by real-time PCR. In the following, the cDNA of MYB44 as one of the selected candidate genes involved in salt tolerance was isolated, cloned, and sequenced for comparison. CONCLUSIONS: Overall, the results of the current study may pave the way for the accurate selection of genes involved in salinity to be used in molecular-genetics-assisted breeding programs. In addition, making use of the identified genes may help relieve the damages arising from the salt stress in sunflowers.

Integrative Systems Biology Analysis Elucidates Mastitis Disease Underlying Functional Modules in Dairy Cattle.

Background: Mastitis is the most prevalent disease in dairy cattle and one of the most significant bovine pathologies affecting milk production, animal health, and reproduction. In addition, mastitis is the most common, expensive, and contagious infection in the dairy industry. Methods: A meta-analysis of microarray and RNA-seq data was conducted to identify candidate genes and functional modules associated with mastitis disease. The results were then applied to systems biology analysis via weighted gene coexpression network analysis (WGCNA), Gene Ontology, enrichment analysis for the Kyoto Encyclopedia of Genes and Genomes (KEGG), and modeling using machine-learning algorithms. Results: Microarray and RNA-seq datasets were generated for 2,089 and 2,794 meta-genes, respectively. Between microarray and RNA-seq datasets, a total of 360 meta-genes were found that were significantly enriched as "peroxisome," "NOD-like receptor signaling pathway," "IL-17 signaling pathway," and "TNF signaling pathway" KEGG pathways. The turquoise module (n = 214 genes) and the brown module (n = 57 genes) were identified as critical functional modules associated with mastitis through WGCNA. PRDX5, RAB5C, ACTN4, SLC25A16, MAPK6, CD53, NCKAP1L, ARHGEF2, COL9A1, and PTPRC genes were detected as hub genes in identified functional modules. Finally, using attribute weighting and machine-learning methods, hub genes that are sufficiently informative in Escherichia coli mastitis were used to optimize predictive models. The constructed model proposed the optimal approach for the meta-genes and validated several high-ranked genes as biomarkers for E. coli mastitis using the decision tree (DT) method. Conclusion: The candidate genes and pathways proposed in this study may shed new light on the underlying molecular mechanisms of mastitis disease and suggest new approaches for diagnosing and treating E. coli mastitis in dairy cattle.

Molecular mechanisms of fat deposition: IL-6 is a hub gene in fat lipolysis, comparing thin-tailed with fat-tailed sheep breeds.

Tail fat content affects meat quality and varies significantly among different breeds of sheep. Ghezel (fat-tailed) and Zel (thin-tailed) are two important Iranian local sheep breeds with different patterns of fat storage. The current study presents the transcriptome characterization of tail fat using RNA sequencing in order to get a better comprehension of the molecular mechanism of lipid storage in the two mentioned sheep breeds. Seven (Zel  =  4 and Ghezel  =  3) 7-month-old male lambs were used for this experiment. The results of sequencing were analyzed with bioinformatics methods, including differentially expressed genes (DEGs) identification, functional enrichment analysis, structural classification of proteins, protein-protein interaction (PPI) and network and module analyses. Some of the DEGs, such as LIPG, SAA1, SOCS3, HIF-1 α , and especially IL-6, had a close association with lipid metabolism. Furthermore, functional enrichment analysis revealed pathways associated with fat deposition, including "fatty acid metabolism", "fatty acid biosynthesis" and "HIF-1 signaling pathway". The structural classification of proteins showed that major down-regulated DEGs in the Zel (thin-tailed) breed were classified under transporter class and that most of them belonged to the solute carrier transporter (SLC) families. In addition, DEGs under the transcription factor class with an important role in lipolysis were up-regulated in the Zel (thin-tailed) breed. Also, network analysis revealed that IL-6 and JUNB were hub genes for up-regulated PPI networks, and HMGCS1, VPS35 and VPS26A were hub genes for down-regulated PPI networks. Among the up-regulated DEGs, the IL-6 gene seems to play an important role in lipolysis of tail fat in thin-tailed sheep breeds via various pathways such as tumor necrosis factor (TNF) signaling and mitogen-activated protein kinase (MAPK) signaling pathways. Due to the probable role of the IL-6 gene in fat lipolysis and also due to the strong interaction of IL-6 with the other up-regulated DEGs, it seems that IL-6 accelerates the degradation of lipids in tail fat cells.

Combined QTL mapping and RNA-Seq profiling reveals candidate genes associated with cadmium tolerance in barley.

The high toxicity of cadmium (Cd) and its ready uptake by plants has become a major agricultural problem. To investigate the genetic architecture and genetic regulation of Cd tolerance in barley, we conducted quantitative trait loci (QTL) analysis in the phenotypically polymorphic Oregon Wolfe Barley (OWB) mapping population, derived from a cross between Rec and Dom parental genotypes. Through evaluating the Cd tolerance of 87 available doubled haploid lines of the OWB mapping population at the seedling stage, one minor and one major QTL were detected on chromosomes 2H and 6H, respectively. For chlorosis and necrosis traits, the major QTL explained 47.24% and 38.59% of the phenotypic variance, respectively. RNA-Seq analysis of the parental seedlings under Cd treatment revealed 542 differentially expressed genes between Cd-tolerant Rec and Cd-susceptible Dom genotypes. By analyzing sequence variations in transcribed sequences of the parental genotypes, 155,654 SNPs and 1,525 InDels were identified between the two contrasting genotypes and may contribute to Cd tolerance. Finally, by integrating the data from the identified QTLs and RNA-Seq analysis, 16 Cd tolerance-related candidate genes were detected, nine of which were metal ion transporters. These results provide promising candidate genes for further gene cloning and improving Cd tolerance in barley.

Corrigendum: Cross-Species Meta-Analysis of Transcriptomic Data in Combination With Supervised Machine Learning Models Identifies the Common Gene Signature of Lactation Process.

[This corrects the article DOI: 10.3389/fgene.2018.00235.].

The comparative analysis of phenotypic and whole transcriptome gene expression data of ascites susceptible versus ascites resistant chickens.

Ascites syndrome (AS) is a metabolic disorder that mainly occurs at later ages of meat-type chickens. Despite many research, there is no consensus about the origin of this syndrome. Our main purpose were to investigate the syndrome using both phenotypic and RNA-Seq data to elucidate the most causative factors predisposing the birds to AS. Phenotypic data analysis showed that AS indicator traits (AITs) were moderate to high heritable. Inexistence of consistent direct genetic correlation between AITs and growth related traits, indicated that neither faster growth rate nor heavier body weight is the most causative factor affecting the susceptibility of broilers to AS. However, respiratory capacity was revealed to be the most probable factor predisposing the birds to AS, as both lung weight and lung percentage were negatively correlated with AITs. Transcriptomic data analysis revealed 125 differentially expressed genes (DEGs) between the ascitic and healthy groups. Up-regulated genes in ascitic group enriched mainly in gas transport biological process, while down-regulated genes involved in defense response to bacteria, biological adhesion, cell adhesion, killing of cells of another organism and cell division. Genetic association of the DEGs with human cardiovascular diseases suggested excessive heart problems of the ascitic chicks. Heart is, probably, the first tissue suffering from the incompetence of small respiratory system of the AS-susceptible chickens. In other word, tissue hypoxia, that causes free radicals to concentrate in heart cells, may be the commencement of events that finally result to heart failure, suffocation and death of chicks due to the AS.

Cross-Species Meta-Analysis of Transcriptomic Data in Combination With Supervised Machine Learning Models Identifies the Common Gene Signature of Lactation Process.

Lactation, a physiologically complex process, takes place in mammary gland after parturition. The expression profile of the effective genes in lactation has not comprehensively been elucidated. Herein, meta-analysis, using publicly available microarray data, was conducted identify the differentially expressed genes (DEGs) between pre- and post-peak milk production. Three microarray datasets of Rat, Bos Taurus, and Tammar wallaby were used. Samples related to pre-peak (n = 85) and post-peak (n = 24) milk production were selected. Meta-analysis revealed 31 DEGs across the studied species. Interestingly, 10 genes, including MRPS18B, SF1, UQCRC1, NUCB1, RNF126, ADSL, TNNC1, FIS1, HES5 and THTPA, were not detected in original studies that highlights meta-analysis power in biosignature discovery. Common target and regulator analysis highlighted the high connectivity of CTNNB1, CDD4 and LPL as gene network hubs. As data originally came from three different species, to check the effects of heterogeneous data sources on DEGs, 10 attribute weighting (machine learning) algorithms were applied. Attribute weighting results showed that the type of organism had no or little effect on the selected gene list. Systems biology analysis suggested that these DEGs affect the milk production by improving the immune system performance and mammary cell growth. This is the first study employing both meta-analysis and machine learning approaches for comparative analysis of gene expression pattern of mammary glands in two important time points of lactation process. The finding may pave the way to use of publically available to elucidate the underlying molecular mechanisms of physiologically complex traits such as lactation in mammals.