Evidence of an additional centre of apple domestication in Iran, with contributions from the Caucasian crab apple Malus orientalis Uglitzk. to the cultivated apple gene pool.

Divergence processes in crop-wild fruit tree complexes in pivotal regions for plant domestication such as the Caucasus and Iran remain little studied. We investigated anthropogenic and natural divergence processes in apples in these regions using 26 microsatellite markers amplified in 550 wild and cultivated samples. We found two genetically distinct cultivated populations in Iran that are differentiated from Malus domestica, the standard cultivated apple worldwide. Coalescent-based inferences showed that these two cultivated populations originated from specific domestication events of Malus orientalis in Iran. We found evidence of substantial wild-crop and crop-crop gene flow in the Caucasus and Iran, as has been described in apple in Europe. In addition, we identified seven genetically differentiated populations of wild apple (M. orientalis), not introgressed by the cultivated apple. Niche modelling combined with genetic diversity estimates indicated that these wild populations likely resulted from range changes during past glaciations. This study identifies Iran as a key region in the domestication of apple and M. orientalis as an additional contributor to the cultivated apple gene pool. Domestication of the apple tree therefore involved multiple origins of domestication in different geographic locations and substantial crop-wild hybridization, as found in other fruit trees. This study also highlights the impact of climate change on the natural divergence of a wild fruit tree and provides a starting point for apple conservation and breeding programmes in the Caucasus and Iran.

Transcriptome profiling of fully open flowers in a frost-tolerant almond genotype in response to freezing stress.

Spring frost is a major limiting abiotic stress for the cultivation of almonds [Prunus dulcis (Mill.)] in Mediterranean areas or the Middle East. Spring frost, in particular, damages almond fully open flowers, resulting to significant reduction in yield. Little is known about the genetic factors expressed after frost stress in Prunus spp. as well as in almond fully open flowers. Here, we provide the molecular signature of pistils of fully open flowers from a frost-tolerant almond genotype. The level of frost tolerance in this genotype was determined for all three flowering stages and was confirmed by comparing it to two other cultivars using several physiological analyses. Afterwards, comprehensive expression profiling of genes expressed in fully open flowers was performed after being exposed to frost temperatures (during post-thaw period). Clean reads, 27,104,070 and 32,730,772, were obtained for non-frost-treated and frost-treated (FT) libraries, respectively. A total of 62.24 Mb was assembled, generating 50,896 unigenes and 66,906 transcripts. Therefore, 863 upregulated genes and 555 downregulated genes were identified in the FT library. Functional annotation showed that most of the upregulated genes were related to various biological processes involved in responding to abiotic stress. For the first time, a highly expressed cold-shock protein was identified in the reproductive organ of fruit trees. The expression of six genes was validated by RT-PCR. As the first comprehensive analysis of open flowers in a frost-tolerant almond genotype, this study represents a key step toward the molecular breeding of fruit tree species for frost tolerance.

Correction to: Transcriptome profiling of fully open flowers in a frost­tolerant almond genotype in response to freezing stress.

In the original publication of the article, the affiliation of the third author has been incorrectly published as University of Yazd. However, the correct affiliation is Yazd University.

In silico prediction of long intergenic non-coding RNAs in sheep.

Long non-coding RNAs (lncRNAs) are transcribed RNA molecules >200 nucleotides in length that do not encode proteins and serve as key regulators of diverse biological processes. Recently, thousands of long intergenic non-coding RNAs (lincRNAs), a type of lncRNAs, have been identified in mammalians using massive parallel large sequencing technologies. The availability of the genome sequence of sheep (Ovis aries) has allowed us genomic prediction of non-coding RNAs. This is the first study to identify lincRNAs using RNA-seq data of eight different tissues of sheep, including brain, heart, kidney, liver, lung, ovary, skin, and white adipose. A computational pipeline was employed to characterize 325 putative lincRNAs with high confidence from eight important tissues of sheep using different criteria such as GC content, exon number, gene length, co-expression analysis, stability, and tissue-specific scores. Sixty-four putative lincRNAs displayed tissues-specific expression. The highest number of tissues-specific lincRNAs was found in skin and brain. All novel lincRNAs that aligned to the human and mouse lincRNAs had conserved synteny. These closest protein-coding genes were enriched in 11 significant GO terms such as limb development, appendage development, striated muscle tissue development, and multicellular organismal development. The findings reported here have important implications for the study of sheep genome.

Weighted Gene Co-expression Network Analysis of Endometriosis and Identification of Functional Modules Associated With Its Main Hallmarks.

Although many genes have been identified using high throughput technologies in endometriosis (ES), only a small number of individual genes have been analyzed functionally. This is due to the complexity of the disease that has different stages and is affected by various genetic and environmental factors. Many genes are upregulated or downregulated at each stage of the disease, thus making it difficult to identify key genes. In addition, little is known about the differences between the different stages of the disease. We assumed that the study of the identified genes in ES at a system-level can help to better understand the molecular mechanism of the disease at different stages of the development. We used publicly available microarray data containing archived endometrial samples from women with minimal/mild endometriosis (MMES), mild/severe endometriosis (MSES) and without endometriosis. Using weighted gene co-expression analysis (WGCNA), functional modules were derived from normal endometrium (NEM) as the reference sample. Subsequently, we tested whether the topology or connectivity pattern of the modules was preserved in MMES and/or MSES. Common and specific hub genes were identified in non-preserved modules. Accordingly, hub genes were detected in the non-preserved modules at each stage. We identified sixteen co-expression modules. Of the 16 modules, nine were non-preserved in both MMES and MSES whereas five were preserved in NEM, MMES, and MSES. Importantly, two non-preserved modules were found in either MMES or MSES, highlighting differences between the two stages of the disease. Analyzing the hub genes in the non-preserved modules showed that they mostly lost or gained their centrality in NEM after developing the disease into MMES and MSES. The same scenario was observed, when the severeness of the disease switched from MMES to MSES. Interestingly, the expression analysis of the new selected gene candidates including CC2D2A, AEBP1, HOXB6, IER3, and STX18 as well as IGF-1, CYP11A1 and MMP-2 could validate such shifts between different stages. The overrepresented gene ontology (GO) terms were enriched in specific modules, such as genetic disposition, estrogen dependence, progesterone resistance and inflammation, which are known as endometriosis hallmarks. Some modules uncovered novel co-expressed gene clusters that were not previously discovered.

Comparison of hematopoietic cancer stem cells with normal stem cells leads to discovery of novel differentially expressed SSRs.

Tandem repeat expansion in the transcriptomics level has been considered as one of the underlying causes of different cancers. Cancer stem cells are a small portion of cancer cells within the main neoplasm and can remain alive during chemotherapy and re-induce tumor growth. The EST-SSR background of cancer stem cells and possible roles of expressed SSRs in altering normal stem cells to cancer ones have not been investigated yet. Here, SSR distributions in hematopoietic normal and cancer stem cells were compared based on the expressed EST-SSR. One hundred eighty nine and 223 EST-SSRs were identified in cancer and normal stem cells, respectively. The EST-SSR expression pattern was significantly different between normal and cancer stem cells. The frequencies of AC/GT and TA/TA EST-SSRs were about 10% higher in cancer than normal stem cells. Remarkably, the number of triplets in cancer stem cells was 1.5 times higher than that in normal stem cells. GAT EST-SSR was frequent in cancer stem cells, but, conversely, normal stem cells did not express GAT EST-SSR. We suggest this EST-SSR as a novel triplet in cancer stem cell induction. Translating EST-SSRs to amino acids demonstrated that Asp and Ile were more abundant in cancer stem cells compared to normal stem cells. Finally, Gene Ontology (GO) enrichment analysis was carried out on genes containing triplet SSRs and showed that SSRs intentionally visit some specific GO classes. Interestingly, a NF-kappa (nuclear factor-kB) binding transcription factor was significantly hit by SSR instability which is a hallmark for leukemia stem cells. NF-kappa is an over represented transcription factor during cancer progression. It seems that there is a crosstalk between the NF-kB transcription factor and expressed GAT tandem repeat which negatively regulate apoptosis. In addition to better understanding of tumorigenesis, the findings of this study offer new DNA markers for diagnostic purposes and identifying at risk populations. In addition, a new approach for gene discovery in cancer by target analysis of differentially expressed EST-SSRs between cancer and normal stem cells is presented here.

Predicting distinct organization of transcription factor binding sites on the promoter regions: a new genome-based approach to expand human embryonic stem cell regulatory network.

Self-proliferation and differentiation into distinct cell types have been made stem cell as a promising target for regenerative medicine. Several key genes can regulate self-renewal and pluripotency of embryonic stem cells (hESCs). They work together and build a transcriptional hierarchy. Coexpression and coregulation of genes control by common regulatory elements on the promoter regions. Consequently, distinct organization and combination of transcription factor binding sites (TFBSs modules) on promoter regions, in view of order and distance, lead to a common specific expression pattern within a set of genes. To gain insights into transcriptional regulation of hESCs, we selected promoter regions of eleven common expressed hESC genes including SOX2, LIN28, STAT3, NANOG, LEFTB, TDGF1, POU5F1, FOXD3, TERF1, REX1 and GDF3 to predict activating regulatory modules on promoters and discover key corresponding transcription factors. Then, promoter regions in human genome were explored for modules and 328 genes containing the same modules were detected. Using microarray data, we verified that 102 of 328 genes commonly upregulate in hESCs. Also, using output data of DNA-protein interaction assays, we found that 42 of all predicted genes are targets of SOX2, NANOG and POU5F1. Additionally, a protein interaction network of hESC genes was constructed based on biological processes, and interestingly, 126 downregulated genes along with upregulated ones identified by promoter analysis were predicted in the network. Based on the results, we suggest that the identified genes, coregulating with common hESC genes, represent a novel approach for gene discovery based on whole genome promoter analysis irrespective of gene expression. Altogether, promoter profiling can be used to expand hESC transcriptional regulatory circuitry by analysis of shared functional sequences between genes. This approach provides a clear image on underlying regulatory mechanism of gene expression profile and offers a novel approach in designing gene networks of stem cell.

Protein interaction network of Arabidopsis thaliana female gametophyte development identifies novel proteins and relations.

Although the female gametophyte in angiosperms consists of just seven cells, it has a complex biological network. In this study, female gametophyte microarray data from Arabidopsis thaliana were integrated into the Arabidopsis interactome database to generate a putative interaction map of the female gametophyte development including proteome map based on biological processes and molecular functions of proteins. Biological and functional groups as well as topological characteristics of the network were investigated by analyzing phytohormones, plant defense, cell death, transporters, regulatory factors, and hydrolases. This approach led to the prediction of critical members and bottlenecks of the network. Seventy-four and 24 upregulated genes as well as 171 and 3 downregulated genes were identified in subtracted networks based on biological processes and molecular function respectively, including novel genes such as the pathogenesis-related protein 4, ER type Ca(2+) ATPase 3, dihydroflavonol reductase, and ATP disulfate isomerase. Biologically important relationships between genes, critical nodes, and new essential proteins such as AT1G26830, AT5G20850, CYP74A, AT1G42396, PR4 and MEA were found in the interactome's network. The positions of novel genes, both upregulated and downregulated, and their relationships with biological pathways, in particular phytohormones, were highlighted in this study.