Transcriptomic Insight into the Melon Morphology of Toothed Whales for Aquatic Molecular Developments

Aquatic habitats are home to large animals such as marine mammals. Toothed whales have special fat deposits in the forehead region (called the melon) of their heads that are associated with echolocation underwater. This fat is also important industrially for human use. Due to the lack of gene expression information on the melon fat of toothed whales, we investigated the melon morphology via the transcriptomic approach. Four parts of the melons of three individual Risso’s dolphins were used for total RNA extraction, cDNA library preparation, and sequencing via next-generation sequencing (NGS) technologies. After the downstream analysis of raw sequence data, we determined that the outer layer of the melon’s ML4 region played multifunctional roles. The 36 differentially expressed genes of outer melon included ASB5, MYH13, MYOM2, and MYOM3. These genes are associated with muscle function and energy metabolism. Gene clustering and functional enrichment analyses also represented enrichments, such as the pentose phosphate pathway and morphogenesis related to lipid metabolism and muscle functions. This study will be crucial for muscle and fat functional-related molecular studies on aquatic mammals. Additionally, the study presents potential pathways, such as melon fat biosynthesis, for sustainable future developments.

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Global nutrient transport in a world of giants

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1502549112 ◽

2015 ◽

Vol 113 (4) ◽

pp. 868-873 ◽

Cited By ~ 152

Author(s):

Christopher E. Doughty ◽

Joe Roman ◽

Søren Faurby ◽

Adam Wolf ◽

Alifa Haque ◽

...

Keyword(s):

Surface Waters ◽

Marine Mammals ◽

Recent Literature ◽

Late Quaternary ◽

Nutrient Transport ◽

Anadromous Fish ◽

Upward Movement ◽

The Past ◽

Large Animals ◽

Continental Interior

The past was a world of giants, with abundant whales in the sea and large animals roaming the land. However, that world came to an end following massive late-Quaternary megafauna extinctions on land and widespread population reductions in great whale populations over the past few centuries. These losses are likely to have had important consequences for broad-scale nutrient cycling, because recent literature suggests that large animals disproportionately drive nutrient movement. We estimate that the capacity of animals to move nutrients away from concentration patches has decreased to about 8% of the preextinction value on land and about 5% of historic values in oceans. For phosphorus (P), a key nutrient, upward movement in the ocean by marine mammals is about 23% of its former capacity (previously about 340 million kg of P per year). Movements by seabirds and anadromous fish provide important transfer of nutrients from the sea to land, totalling ∼150 million kg of P per year globally in the past, a transfer that has declined to less than 4% of this value as a result of the decimation of seabird colonies and anadromous fish populations. We propose that in the past, marine mammals, seabirds, anadromous fish, and terrestrial animals likely formed an interlinked system recycling nutrients from the ocean depths to the continental interiors, with marine mammals moving nutrients from the deep sea to surface waters, seabirds and anadromous fish moving nutrients from the ocean to land, and large animals moving nutrients away from hotspots into the continental interior.

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EdClust: A heuristic sequence clustering method with higher sensitivity

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720021500360 ◽

2021 ◽

Author(s):

Ming Cao ◽

Qinke Peng ◽

Ze-Gang Wei ◽

Fei Liu ◽

Yi-Fan Hou

Keyword(s):

Large Scale ◽

Sequence Data ◽

Clustering Algorithms ◽

Clustering Methods ◽

Sequencing Data ◽

Clustering Method ◽

Cluster Number ◽

Sequence Clustering ◽

Downstream Analysis ◽

Heuristic Clustering

The development of high-throughput technologies has produced increasing amounts of sequence data and an increasing need for efficient clustering algorithms that can process massive volumes of sequencing data for downstream analysis. Heuristic clustering methods are widely applied for sequence clustering because of their low computational complexity. Although numerous heuristic clustering methods have been developed, they suffer from two limitations: overestimation of inferred clusters and low clustering sensitivity. To address these issues, we present a new sequence clustering method (edClust) based on Edlib, a C/C[Formula: see text] library for fast, exact semi-global sequence alignment to group similar sequences. The new method edClust was tested on three large-scale sequence databases, and we compared edClust to several classic heuristic clustering methods, such as UCLUST, CD-HIT, and VSEARCH. Evaluations based on the metrics of cluster number and seed sensitivity (SS) demonstrate that edClust can produce fewer clusters than other methods and that its SS is higher than that of other methods. The source codes of edClust are available from https://github.com/zhang134/EdClust.git under the GNU GPL license.

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Phylogenetic Characterization of the Palyam Serogroup Orbiviruses

Viruses ◽

10.3390/v11050446 ◽

2019 ◽

Vol 11 (5) ◽

pp. 446 ◽

Cited By ~ 3

Author(s):

Karen Ebersohn ◽

Peter Coetzee ◽

Louwrens P. Snyman ◽

Robert Swanepoel ◽

Estelle H. Venter

Keyword(s):

Phylogenetic Analysis ◽

Sequence Data ◽

Evolutionary Relationship ◽

Full Genome Sequence ◽

African Horse Sickness Virus ◽

Gene Encoding ◽

Phylogenetic Characterization ◽

Next Generation Sequencing Ngs ◽

High Degree

The Palyam serogroup orbiviruses are associated with abortion and teratogenesis in cattle and other ruminants. Of the 13 different serotypes that have been identified, the full genome sequence of only one, Kasba, has been published. We undertook to perform Next Generation Sequencing (NGS) and phylogenetic analysis on 12 Palyam serotypes plus field isolates of the African serotypes in our possession. The Palyam serogroup was found to be most closely related to the African horse sickness virus group and showed the most distant evolutionary relationship to the equine encephalosis viruses (EEV). Amino acid sequence analysis revealed that the gene encoding VP7 was the most conserved within serotypes and VP2 and VP5 showed the highest degree of variation. A high degree of sequence identity was found for isolates from the same geographical region. The phylogenetic analysis revealed two clades where the African serotypes were all very closely related in one clade and the other clade contained the Australian and Asian serotypes and one African serotype, Petevo. It was evident from the sequence data that the geographical origin of Palyam serogroup viruses played an important role in the development of the different serotypes.

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Frequent LOH of CYP2D6 in ER+ breast cancer determined by next-generation sequencing (NGS).

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.534 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. 534-534

Author(s):

Mark J. Ratain ◽

James Sun ◽

Yusuke Nakamura ◽

Nancy J Cox ◽

Tarek Sahmoud ◽

...

Keyword(s):

Breast Cancer ◽

Sequence Data ◽

Biological Significance ◽

Gene Copy Number ◽

Gene Copy ◽

Full Cohort ◽

Next Generation Sequencing Ngs ◽

Apparent Association

534 Background: The role of CYP2D6 genetic variation in predicting response to tamoxifen in ER+ breast cancer is a subject of ongoing debate. There has been great variability in approaches to both genotyping and phenotyping, and in particular many investigators have extracted DNA from breast cancer samples rather than peripheral blood. We hypothesized that CYP2D6 gene copy number alterations are common in ER+ breast cancer, affecting genotype results, and used NGS to characterize CYP2D6 in patients with ER+ disease. Methods: CYP2D6 sequencing was performed as part of a comprehensive NGS profile of cancer-related genes for 261 predominantly relapsed and metastatic ER+ breast cancer FFPE specimens. Sequence data were resolved into genotypes according to the * allele nomenclature. Tumor LOH was determined at CYP2D6, and its error impact on genotyping methods was estimated. To assess biological significance, the prevalence of CYP2D6 alleles and LOH in ER+ disease was compared against a control set of 99 ER- tumors. Results: CYP2D6 allele frequencies in our full cohort (ER+, 261; ER-, 99) were consistent with prior studies; 64.4%, 16.8%, 9.0% vs. 63.1%, 17.2%, 7.0% for *1/*2, *4, and *41 respectively, and 1%-2% for the rarer alleles *9, *10, and *5. The rate of CYP2D6 LOH was higher in ER+ disease (41% vs. 26%, p<0.01), with all excess arising from copy-loss (as opposed to copy-neutral) changes (22% vs. 7%, p<0.002). The estimated impact of LOH on germline genotype assessment from tumor was considerable; an assay sensitive at >20% minor allele frequency (e.g., Sanger sequencing) can misclassify >10% of heterozygotes, leading to significant Hardy-Weinberg disequilibrium (e.g., p=8.3x10-8 for *4). Interestingly, an enrichment of reduced or non-functional CYP2D6 alleles in ER+ samples was observed (61% vs. 47%, p<0.03). Conclusions: Our results demonstrate the distorting effect of extensive LOH on genotype assessment of CYP2D6 in breast cancer. Therefore, tumor DNA should not be routinely used for determination of germline 2D6 genotype, although it appears possible to use NGS. The apparent association between reduced function CYP2D6 alleles and ER+ breast cancer in our dataset requires further investigation.

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Identification of Potentially Functional Circular RNAs hsa_circ_0070934 and hsa_circ_0004315 as Prognostic Factor of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

10.21203/rs.3.rs-948198/v1 ◽

2021 ◽

Author(s):

Pejman Morovat ◽

Saman Morovat ◽

Arash M. Ashrafi ◽

Shahram Teimourian

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Prognostic Factor ◽

Sequence Data ◽

Functional Enrichment ◽

Differentially Expressed ◽

Circular Rnas ◽

Ppi Network ◽

Hub Genes ◽

Cerna Network

Abstract Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, which has a high mortality rate and poor treatment outcomes with yet unknown molecular basis. It seems that gene expression plays a pivotal role in the pathogenesis of the disease. Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in various malignancies by acting as competitive endogenous RNAs (ceRNAs). However, the potential pathogenesis roles of the ceRNA network among circRNA/miRNA/mRNA in HCC are unclear. In this study, first, the HCC circRNA expression data were obtained from three Gene Expression Omnibus microarray datasets (GSE164803, GSE94508, GSE97332), and the differentially expressed circRNAs (DECs) were identified using R limma package. Also, the liver hepatocellular carcinoma (LIHC) miRNA and mRNA sequence data were retrieved from TCGA, and differentially expressed miRNAs (DEMIs) and mRNAs (DEGs) were determined using the R DESeq2 package. Second, CSCD website was used to uncover the binding sites of miRNAs on DECs. The DECs' potential target miRNAs were revealed by conducting an intersection between predicted miRNAs from CSCD and downregulated DEMIs. Third, some related genes were uncovered by intersecting targeted genes predicted by miRWalk and targetscan online tools with upregulated DEGs. The ceRNA network was then built using the Cytoscape software. The functional enrichment and the overall survival time of these potential targeted genes were analyzed, and a PPI network was constructed in the STRING database. Network visualization was performed by Cytoscape, and ten hub genes were detected using the CytoHubba plugin tool. Four DECs (hsa_circ_0000520, hsa_circ_0008616, hsa_circ_0070934, hsa_circ_0004315) were obtained and six miRNAs (hsa-miR-542-5p, hsa-miR-326, hsa-miR-511-5p, hsa-miR-195-5p, hsa-miR-214-3p, and hsa-miR-424-5p) which are regulated by the above DECs were identified. Then 543 overlapped genes regulated by six miRNAs mentioned above were predicted. Functional enrichment analysis showed that these genes are mostly associated with cancer regulation functions. Ten hub genes (TTK،AURKB, KIF20A، KIF23، CEP55، CDC6، DTL، NCAPG، CENPF، PLK4) have been screened from the PPI network of the 204 survival-related genes. KIF20A, NCAPG, TTK, PLK4, and CDC6 were selected for the highest significant p-values. In the end, a circRNA-miRNA-mRNA regulatory axis was established for five final selected hub genes. This study implies the potential pathogenesis of the obtained network and proposes that the two DECs (has_circ_0070934 and has_circ_0004315) may be important prognostic factor for HCC.

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Fast-Bonito: A Faster Basecaller for Nanopore Sequencing

10.1101/2020.10.08.318535 ◽

2020 ◽

Author(s):

Zhimeng Xu ◽

Yuting Mai ◽

Denghui Liu ◽

Wenjun He ◽

Xinyuan Lin ◽

...

Keyword(s):

Network Architecture ◽

Original Version ◽

Neuron Network ◽

Base Calling ◽

Oxford Nanopore ◽

Speed Up ◽

Downstream Analysis ◽

Next Generation Sequencing Ngs ◽

Oxford Nanopore Technologies ◽

Generation Sequencing

AbstractOxford Nanopore Technologies (ONT) is a promising sequencing technology that could generate relatively longer sequencing reads compared to the next generation sequencing (NGS) technology. The base calling process is very important for TGS. It translates the original electrical signals from the sequencer to the nucleotide sequence. By doing that, the base calling could significantly influence the accuracy of downstream analysis. Bonito is a recently developed basecaller based on deep neuron network, the neuron network architecture of which is composed of a single convolutional layer followed by three stacked bidirectional GRU layers. Although Bonito achieved the state-of-the-art accuracy, its speed is so slow that it is not likely to be used in production. We therefore implement Fast-Bonito, which introduces systematic optimization to speed up Bonito. Fast-Bonito archives 53.8% faster than the original version on NVIDIA V100 and could be further speed up by HUAWEI Ascend 910 NPU, achieving 565% faster than the original version. The accuracy of Fast-Bonito is also slightly higher than the original Bonito.

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Demystification of RNAseq Quality Control

JITA - Journal of Information Technology and Applications (Banja Luka) - APEIRON ◽

10.7251/jit2102073d ◽

2021 ◽

Vol 22 (2) ◽

Author(s):

Dragana Dudić ◽

Bojana Banović Đeri ◽

Vesna Pajić ◽

Gordana Pavlović-Lažetić

Keyword(s):

Quality Control ◽

Next Generation Sequencing ◽

Rna Sequencing ◽

Next Generation ◽

Comprehensive Guidance ◽

Dna And Rna ◽

Control Evaluation ◽

Downstream Analysis ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

Next Generation Sequencing (NGS) analysis has become a widely used method for studying the structure of DNA and RNA, but complexity of the procedure leads to obtaining error-prone datasets which need to be cleansed in order to avoid misinterpretation of data. We address the usage and proper interpretations of characteristic metrics for RNA sequencing (RNAseq) quality control, implemented in and reported by FastQC, and provide a comprehensive guidance for their assessment in the context of total RNAseq quality control of Illumina raw reads. Additionally, we give recommendations how to adequately perform the quality control preprocessing step of raw total RNAseq Illumina reads according to the obtained results of the quality control evaluation step; the aim is to provide the best dataset to downstream analysis, rather than to get better FastQC results. We also tested effects of different preprocessing approaches to the downstream analysis and recommended the most suitable approach.

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PHARP: A pig haplotype reference panel for genotype imputation

10.1101/2021.06.03.446888 ◽

2021 ◽

Author(s):

Zhen Wang ◽

Zhenyang Zhang ◽

Zitao Chen ◽

Jiabao Sun ◽

Caiyun Cao ◽

...

Keyword(s):

Complex Traits ◽

Sequence Data ◽

Genotype Imputation ◽

Reference Panel ◽

Whole Genome Sequence ◽

Sequencing Data ◽

Large White ◽

Downstream Analysis ◽

Low Coverage ◽

Analytical Tools

Pigs not only function as a major meat source worldwide but also are commonly used as an animal model for studying human complex traits. A large haplotype reference panel has been used to facilitate efficient phasing and imputation of relatively sparse genome-wide microarray chips and low-coverage sequencing data. Using the imputed genotypes in the downstream analysis, such as GWASs, TWASs, eQTL mapping and genomic prediction (GS), is beneficial for obtaining novel findings. However, currently, there is still a lack of publicly available and high-quality pig reference panels with large sample sizes and high diversity, which greatly limits the application of genotype imputation in pigs. In response, we built the pig Haplotype Reference Panel (PHARP) database. PHARP provides a reference panel of 2,012 pig haplotypes at 34 million SNPs constructed using whole-genome sequence data from more than 49 studies of 71 pig breeds. It also provides Web-based analytical tools that allow researchers to carry out phasing and imputation consistently and efficiently. PHARP is freely accessible at http://alphaindex.zju.edu.cn/PHARP/index.php. We demonstrate its applicability for pig commercial 50K SNP arrays, by accurately imputing 2.6 billion genotypes at a concordance rate value of 0.971 in 81 Large White pigs (~ 17x sequencing coverage). We also applied our reference panel to impute the low-density SNP chip into the high-density data for three GWASs and found novel significantly associated SNPs that might be casual variants.

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Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses

Viruses ◽

10.3390/v12070758 ◽

2020 ◽

Vol 12 (7) ◽

pp. 758 ◽

Cited By ~ 1

Author(s):

Keylie M. Gibson ◽

Margaret C. Steiner ◽

Uzma Rentia ◽

Matthew L. Bendall ◽

Marcos Pérez-Losada ◽

...

Keyword(s):

De Novo ◽

Sequence Data ◽

Consensus Sequence ◽

Sequence Assembly ◽

Next Generation ◽

Consensus Sequences ◽

Bioinformatic Tools ◽

Hiv Gp120 ◽

Next Generation Sequencing Ngs ◽

Ngs Data

Next-generation sequencing (NGS) offers a powerful opportunity to identify low-abundance, intra-host viral sequence variants, yet the focus of many bioinformatic tools on consensus sequence construction has precluded a thorough analysis of intra-host diversity. To take full advantage of the resolution of NGS data, we developed HAplotype PHylodynamics PIPEline (HAPHPIPE), an open-source tool for the de novo and reference-based assembly of viral NGS data, with both consensus sequence assembly and a focus on the quantification of intra-host variation through haplotype reconstruction. We validate and compare the consensus sequence assembly methods of HAPHPIPE to those of two alternative software packages, HyDRA and Geneious, using simulated HIV and empirical HIV, HCV, and SARS-CoV-2 datasets. Our validation methods included read mapping, genetic distance, and genetic diversity metrics. In simulated NGS data, HAPHPIPE generated pol consensus sequences significantly closer to the true consensus sequence than those produced by HyDRA and Geneious and performed comparably to Geneious for HIV gp120 sequences. Furthermore, using empirical data from multiple viruses, we demonstrate that HAPHPIPE can analyze larger sequence datasets due to its greater computational speed. Therefore, we contend that HAPHPIPE provides a more user-friendly platform for users with and without bioinformatics experience to implement current best practices for viral NGS assembly than other currently available options.

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(w)HOL(e)ISTIC gene ontology and pathway analysis of data using open source web tools

10.21203/rs.2.20371/v1 ◽

2020 ◽

Author(s):

Damarius S. Fleming ◽

Laura Miller

Keyword(s):

Gene Ontology ◽

Open Source ◽

Biological Networks ◽

Genomic Databases ◽

Network Analyses ◽

Go Enrichment ◽

Downstream Analysis ◽

Species Specific ◽

Stage 1 ◽

Next Generation Sequencing Ngs

Abstract Objective Downstream analysis of next generation sequencing (NGS) experiments provides researchers a means of deciphering their results. These downstream analyses elucidate clusters of genes or networks of biological interest under the conditions being studied. One convention for examining gene interactions is to conduct downstream investigations based on gene ontology (GO), pathway, and network analyses of statistically significant genes of interest. Unfortunately, the software available for these types of analyses is expensive, not species specific, and subject to gaps in annotation. These difficulties can cause studies to omit this downstream step, limiting the utility of the data. In order to facilitate pathway and network analyses of candidate gene lists from NGS studies, a workflow was constructed based on the use of open-sourced freely available software and genomic databases termed the “(w)HOL(e)ISTIC GO enrichment” approach.Results Overlap of multiple open-source software was used to annotate, analyze, and visualize biological networks. It is a 3-stage process in which stage 1 (Annotation) is the generation of alias identifiers. Stage 2 (Analysis) is a two-part process generating ontologies and networks with statistical inferences. Stage 2 relies on information from databases such as Reactome, KEGG, and InterPro. Stage 3 (Visualization) allows for figure creation.

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