scholarly journals High-throughput sequencing is revealing genetic associations with avian plumage color

The Auk ◽  
2019 ◽  
Vol 136 (4) ◽  
Author(s):  
Erik R Funk ◽  
Scott A Taylor
Keyword(s):  
High Throughput Sequencing ◽  
Large Body ◽  
Bird Species ◽  
Genetic Associations ◽  
Plumage Color ◽  
Protein Coding ◽  
Avian Evolution ◽  
Color Changes ◽  
Coding Regions ◽  
Color Differences

Abstract Avian evolution has generated an impressive array of patterns and colors in the ~10,000 bird species that exist on Earth. Recently, a number of exciting studies have utilized whole-genome sequencing to reveal new details on the genetics of avian plumage color. These findings provide compelling evidence for genes that underlie plumage variation across a wide variety of bird species (e.g., juncos, warblers, seedeaters, and estrildid finches). While much is known about large, body-wide color changes, these species exhibit discrete color differences across small plumage patches. Many genetic differences appear to be located in regulatory regions of genes rather than in protein-coding regions, suggesting gene expression is playing a large role in the control of these color patches. Taken together, these studies have the potential to broadly facilitate further research of sexual selection and evolution in these charismatic taxa.

scholarly journals Multilocus Characterization, Gene Expression Analysis of Putative Immunodominant Protein Coding Regions, and Development of Recombinase Polymerase Amplification Assay for Detection of ‘Candidatus Phytoplasma Pruni’ in Prunus avium

2019 ◽  
Vol 109 (6) ◽  
pp. 983-992 ◽  
Author(s):  
Dan Edward V. Villamor ◽  
Kenneth C. Eastwell
Keyword(s):  
High Throughput Sequencing ◽  
Sweet Cherry ◽  
Prunus Avium ◽  
Protein A ◽  
Recombinase Polymerase Amplification ◽  
Sequencing Data ◽  
Coding Region ◽  
Protein Coding ◽  
Coding Regions ◽  
Reverse Transcription Pcr

Western X (WX) disease, caused by ‘Candidatus Phytoplasma pruni’, is a devastating disease of sweet cherry resulting in the production of small, bitter-flavored fruits that are unmarketable. Escalation of WX disease in Washington State prompted the development of a rapid detection assay based on recombinase polymerase amplification (RPA) to facilitate timely removal and replacement of diseased trees. Here, we report on a reliable RPA assay targeting putative immunodominant protein coding regions that showed comparable sensitivity to polymerase chain reaction (PCR) in detecting ‘Ca. Phytoplasma pruni’ from crude sap of sweet cherry tissues. Apart from the predominant strain of ‘Ca. Phytoplasma pruni’, the RPA assay also detected a novel strain of phytoplasma from several WX-affected trees. Multilocus sequence analyses using the immunodominant protein A (idpA), imp, rpoE, secY, and 16S ribosomal RNA regions from several ‘Ca. Phytoplasma pruni’ isolates from WX-affected trees showed that this novel phytoplasma strain represents a new subgroup within the 16SrIII group. Examination of high-throughput sequencing data from total RNA of WX-affected trees revealed that the imp coding region is highly expressed, and as supported by quantitative reverse transcription PCR data, it showed higher RNA transcript levels than the previously proposed idpA coding region of ‘Ca. Phytoplasma pruni’.

scholarly journals ORFik: a comprehensive R toolkit for the analysis of translation

2021 ◽  
Author(s):  
Håkon Tjeldnes ◽  
Kornel Labun ◽  
Yamila Torres Cleuren ◽  
Katarzyna Chyżyńska ◽  
Michał Świrski ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Ribosome Profiling ◽  
Open Reading Frames ◽  
Sequencing Data ◽  
Protein Coding ◽  
Coding Regions ◽  
High Throughput Sequencing Data ◽  
Upstream Open Reading Frames ◽  
User Friendly

ABSTRACT•BackgroundWith the rapid growth in the use of high-throughput methods for characterizing translation and the continued expansion of multi-omics, there is a need for back-end functions and streamlined tools for processing, analyzing, and characterizing data produced by these assays.•ResultsHere, we introduce ORFik, a user-friendly R/Bioconductor toolbox for studying translation and its regulation. It extends GenomicRanges from the genome to the transcriptome and implements a framework that integrates data from several sources. ORFik streamlines the steps to process, analyze, and visualize the different steps of translation with a particular focus on initiation and elongation. It accepts high-throughput sequencing data from ribosome profiling to quantify ribosome elongation or RCP-seq/TCP-seq to also quantify ribosome scanning. In addition, ORFik can use CAGE data to accurately determine 5’UTRs and RNA-seq for determining translation relative to RNA abundance. ORFik supports and calculates over 30 different translation-related features and metrics from the literature and can annotate translated regions such as proteins or upstream open reading frames. As a use-case, we demonstrate using ORFik to rapidly annotate the dynamics of 5’ UTRs across different tissues, detect their uORFs, and characterize their scanning and translation in the downstream protein-coding regions.•Availabilityhttp://bioconductor.org/packages/ORFik

scholarly journals RNAsamba: coding potential assessment using ORF and whole transcript sequence information

2019 ◽  
Author(s):  
Antonio P. Camargo ◽  
Vsevolod Sourkov ◽  
Marcelo F. Carazzolle
Keyword(s):  
High Throughput Sequencing ◽  
Model Organisms ◽  
Sequence Information ◽  
Protein Coding ◽  
Rna Molecules ◽  
Coding Regions ◽  
Sequencing Technologies ◽  
Partial Length ◽  
Non Coding Rnas ◽  
Coding Potential

AbstractMotivationThe advent of high-throughput sequencing technologies made it possible to obtain large volumes of genetic information, quickly and inexpensively. Thus, many efforts are devoted to unveil the biological roles of genomic elements, being one of the main tasks the identification of protein-coding and long non-coding RNAs.ResultsWe describe RNAsamba, a tool to predict the coding potential of RNA molecules from sequence information using a deep-learning model that processes both the whole sequence and the ORF to look for patterns that distinguish coding and non-coding RNAs. We evaluated the model in the classification of coding and non-coding transcripts of humans and five other model organisms and show that RNAsamba mostly outperforms other state-of-the-art methods. We also show that RNAsamba can identify coding signals in partial-length ORFs and UTR sequences, evidencing that its model is not dependent on the presence of complete coding regions. RNAsamba is a fast and easy tool that can provide valuable contributions to genome annotation pipelines.Availability and implementationThe source code of RNAsamba is freely available at:https://github.com/apcamargo/RNAsamba.

scholarly journals The open targets post-GWAS analysis pipeline

2020 ◽  
Vol 36 (9) ◽  
pp. 2936-2937 ◽  
Author(s):  
Gareth Peat ◽  
William Jones ◽  
Michael Nuhn ◽  
José Carlos Marugán ◽  
William Newell ◽  
...  
Keyword(s):  
Drug Targets ◽  
Gene Expression Regulation ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Protein Coding ◽  
Data Resource ◽  
Coding Regions ◽  
Genome Wide ◽  
Causal Genes ◽  
Interactive Data

Abstract Motivation Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data. Results We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource. Availability and implementation The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io.

scholarly journals Chloroplast genome variation and phylogenetic relationships of Atractylodes species

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yiheng Wang ◽  
Sheng Wang ◽  
Yanlei Liu ◽  
Qingjun Yuan ◽  
Jiahui Sun ◽  
...  
Keyword(s):  
Chloroplast Genome ◽  
High Throughput Sequencing ◽  
Phylogenetic Analyses ◽  
Herbal Medicines ◽  
Structural Genomic ◽  
Protein Coding ◽  
Chloroplast Genomes ◽  
Original Plant ◽  
Morphological Differences ◽  
Rna Genes

Abstract Background Atractylodes DC is the basic original plant of the widely used herbal medicines “Baizhu” and “Cangzhu” and an endemic genus in East Asia. Species within the genus have minor morphological differences, and the universal DNA barcodes cannot clearly distinguish the systemic relationship or identify the species of the genus. In order to solve these question, we sequenced the chloroplast genomes of all species of Atractylodes using high-throughput sequencing. Results The results indicate that the chloroplast genome of Atractylodes has a typical quadripartite structure and ranges from 152,294 bp (A. carlinoides) to 153,261 bp (A. macrocephala) in size. The genome of all species contains 113 genes, including 79 protein-coding genes, 30 transfer RNA genes and four ribosomal RNA genes. Four hotspots, rpl22-rps19-rpl2, psbM-trnD, trnR-trnT(GGU), and trnT(UGU)-trnL, and a total of 42–47 simple sequence repeats (SSR) were identified as the most promising potentially variable makers for species delimitation and population genetic studies. Phylogenetic analyses of the whole chloroplast genomes indicate that Atractylodes is a clade within the tribe Cynareae; Atractylodes species form a monophyly that clearly reflects the relationship within the genus. Conclusions Our study included investigations of the sequences and structural genomic variations, phylogenetics and mutation dynamics of Atractylodes chloroplast genomes and will facilitate future studies in population genetics, taxonomy and species identification.

scholarly journals Illuminating the Plant Rhabdovirus Landscape through Metatranscriptomics Data

Viruses ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1304
Author(s):  
Nicolás Bejerman ◽  
Ralf G. Dietzgen ◽  
Humberto Debat
Keyword(s):  
Plant Species ◽  
High Throughput Sequencing ◽  
Plant Viruses ◽  
The Novel ◽  
Coding Regions ◽  
Public Data ◽  
Invaluable Tool ◽  
Sequencing Platforms ◽  
Viral Sequences ◽  
Plant Rhabdovirus

Rhabdoviruses infect a large number of plant species and cause significant crop diseases. They have a negative-sense, single-stranded unsegmented or bisegmented RNA genome. The number of plant-associated rhabdovirid sequences has grown in the last few years in concert with the extensive use of high-throughput sequencing platforms. Here, we report the discovery of 27 novel rhabdovirus genomes associated with 25 different host plant species and one insect, which were hidden in public databases. These viral sequences were identified through homology searches in more than 3000 plant and insect transcriptomes from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) using known plant rhabdovirus sequences as the query. The identification, assembly and curation of raw SRA reads resulted in sixteen viral genome sequences with full-length coding regions and ten partial genomes. Highlights of the obtained sequences include viruses with unique and novel genome organizations among known plant rhabdoviruses. Phylogenetic analysis showed that thirteen of the novel viruses were related to cytorhabdoviruses, one to alphanucleorhabdoviruses, five to betanucleorhabdoviruses, one to dichorhaviruses and seven to varicosaviruses. These findings resulted in the most complete phylogeny of plant rhabdoviruses to date and shed new light on the phylogenetic relationships and evolutionary landscape of this group of plant viruses. Furthermore, this study provided additional evidence for the complexity and diversity of plant rhabdovirus genomes and demonstrated that analyzing SRA public data provides an invaluable tool to accelerate virus discovery, gain evolutionary insights and refine virus taxonomy.

scholarly journals Protein-coding structured RNAs: A computational survey of conserved RNA secondary structures overlapping coding regions in drosophilids

Biochimie ◽  
2011 ◽  
Vol 93 (11) ◽  
pp. 2019-2023 ◽  
Author(s):  
Sven Findeiß ◽  
Jan Engelhardt ◽  
Sonja J. Prohaska ◽  
Peter F. Stadler
Keyword(s):  
Secondary Structures ◽  
Protein Coding ◽  
Rna Secondary Structures ◽  
Coding Regions

Structure and expression of canary myc family genes

1991 ◽  
Vol 11 (3) ◽  
pp. 1770-1776
Author(s):  
R G Collum ◽  
D F Clayton ◽  
F W Alt
Keyword(s):  
Untranslated Region ◽  
Untranslated Regions ◽  
Coding Region ◽  
Protein Coding ◽  
Coding Regions ◽  
Neuronal Precursors ◽  
Myc Gene ◽  
Mature Neurons

We found that the canary N-myc gene is highly related to mammalian N-myc genes in both the protein-coding region and the long 3' untranslated region. Examined coding regions of the canary c-myc gene were also highly related to their mammalian counterparts, but in contrast to N-myc, the canary and mammalian c-myc genes were quite divergent in their 3' untranslated regions. We readily detected N-myc and c-myc expression in the adult canary brain and found N-myc expression both at sites of proliferating neuronal precursors and in mature neurons.

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