Integration of mapped RNA-Seq reads into automatic training of eukaryotic gene finding algorithm

Abstract We present a new approach to automatic training of a eukaryotic ab initio gene finding algorithm. With the advent of Next-Generation Sequencing, automatic training has become paramount, allowing genome annotation pipelines to keep pace with the speed of genome sequencing. Earlier we developed GeneMark-ES, currently the only gene finding algorithm for eukaryotic genomes that performs automatic training in unsupervised ab initio mode. The new algorithm, GeneMark-ET augments GeneMark-ES with a novel method that integrates RNA-Seq read alignments into the self-training procedure. Use of ‘assembled’ RNA-Seq transcripts is far from trivial; significant error rate of assembly was revealed in recent assessments. We demonstrated in computational experiments that the proposed method of incorporation of ‘unassembled’ RNA-Seq reads improves the accuracy of gene prediction; particularly, for the 1.3 GB genome of Aedes aegypti the mean value of prediction Sensitivity and Specificity at the gene level increased over GeneMark-ES by 24.5%. In the current surge of genomic data when the need for accurate sequence annotation is higher than ever, GeneMark-ET will be a valuable addition to the narrow arsenal of automatic gene prediction tools.

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Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi

10.1101/219287 ◽

2017 ◽

Author(s):

Jens Keilwagen ◽

Frank Hartung ◽

Michael Paulini ◽

Sven O. Twardziok ◽

Jan Grau

Keyword(s):

Ab Initio ◽

Gene Prediction ◽

Nematode Species ◽

Intron Position ◽

Rna Seq ◽

Sequencing Data ◽

Protein Coding ◽

Protein Coding Genes ◽

Multiple Reference ◽

Transcript Identification

MotivationGenome annotation is of key importance in many research questions. The identification of protein-coding genes is often based on transcriptome sequencing data, ab-initio or homology-based prediction. Recently, it was demonstrated that intron position conservation improves homology-based gene prediction, and that experimental data improves ab-initio gene prediction.ResultsHere, we present an extension of the gene prediction tool GeMoMa that utilizes amino acid sequence conservation, intron position conservation and optionally RNA-seq data for homology-based gene prediction. We show on published benchmark data for plants, animals and fungi that GeMoMa performs better than the gene prediction programs BRAKER1, MAKER2, and CodingQuarry, and purely RNA-seq-based pipelines for transcript identification. In addition, we demonstrate that using multiple reference organisms may help to further improve the performance of GeMoMa. Finally, we apply GeMoMa to four nematode species and to the recently published barley reference genome indicating that current annotations of protein-coding genes may be refined using GeMoMa predictions.AvailabilityGeMoMa has been published under GNU GPL3 and is freely available at http://www.jstacs.de/index.php/[email protected]

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Faculty of 1000 evaluation for Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences.

F1000 - Post-publication peer review of the biomedical literature ◽

10.3410/f.726079641.793513319 ◽

2016 ◽

Author(s):

Wolfgang Huber

Keyword(s):

Transcript Level ◽

Rna Seq ◽

Gene Level

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LiDAR-Based Glass Detection for Improved Occupancy Grid Mapping

Sensors ◽

10.3390/s21072263 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2263

Author(s):

Haileleol Tibebu ◽

Jamie Roche ◽

Varuna De Silva ◽

Ahmet Kondoz

Keyword(s):

Laser Scanner ◽

Point Clouds ◽

Light Detection And Ranging ◽

Test Results ◽

New Approach ◽

Occupancy Grid ◽

Laser Scanners ◽

Novel Method ◽

Occupancy Grid Mapping ◽

Cartesian Coordinate

Creating an accurate awareness of the environment using laser scanners is a major challenge in robotics and auto industries. LiDAR (light detection and ranging) is a powerful laser scanner that provides a detailed map of the environment. However, efficient and accurate mapping of the environment is yet to be obtained, as most modern environments contain glass, which is invisible to LiDAR. In this paper, a method to effectively detect and localise glass using LiDAR sensors is proposed. This new approach is based on the variation of range measurements between neighbouring point clouds, using a two-step filter. The first filter examines the change in the standard deviation of neighbouring clouds. The second filter uses a change in distance and intensity between neighbouring pules to refine the results from the first filter and estimate the glass profile width before updating the cartesian coordinate and range measurement by the instrument. Test results demonstrate the detection and localisation of glass and the elimination of errors caused by glass in occupancy grid maps. This novel method detects frameless glass from a long range and does not depend on intensity peak with an accuracy of 96.2%.

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A new simpler approach to measure the strength of toe plantar flexion requiring no mechanical restraint with a light-weight device

Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine ◽

10.1177/09544119211002932 ◽

2021 ◽

pp. 095441192110029

Author(s):

Yuko Komuro ◽

Yuji Ohta

Keyword(s):

Plantar Flexion ◽

Mean Value ◽

Simple Approach ◽

Light Weight ◽

New Approach ◽

Mean Values ◽

Mechanical Restraint ◽

Significant Difference ◽

Ankle Joints ◽

The Mean

Conventionally, the strength of toe plantar flexion (STPF) is measured in a seated position, in which not only the target toe joints but also the knee and particularly ankle joints, are usually restrained. We have developed an approach for the measurement of STPF which does not involve restraint and considers the interactions of adjacent joints of the lower extremities. This study aimed to evaluate this new approach and comparing with the seated approach. A thin, light-weight, rigid plate was attached to the sole of the foot in order to immobilize the toe area. Participants were 13 healthy young women (mean age: 24 ± 4 years). For measurement of STPF with the new approach, participants were instructed to stand, raise the device-wearing leg slightly, plantar flex the ankle, and push the sensor sheet with the toes to exert STPF. The sensor sheet of the F-scan II system was inserted between the foot sole and the plate. For measurement with the seated approach, participants were instructed to sit and push the sensor with the toes. They were required to maintain the hip, knee, and ankle joints at 90°. The mean values of maximum STPF of the 13 participants obtained with each approach were compared. There was no significant difference in mean value of maximum STPF when the two approaches were compared (new: 59 ± 23 N, seated: 47 ± 33 N). The coefficient of variation of maximum STPF was smaller for data obtained with the new approach (new: 39%, seated: 70%). Our simple approach enables measurement of STPF without the need for the restraints that are required for the conventional seated approach. These results suggest that the new approach is a valid method for measurement of STPF.

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New approach in the application of lignin for the synthesis of hybrid materials

Pure and Applied Chemistry ◽

10.1515/pac-2016-1009 ◽

2017 ◽

Vol 89 (1) ◽

pp. 161-171 ◽

Cited By ~ 17

Author(s):

Beata Podkościelna ◽

Marta Goliszek ◽

Olena Sevastyanova

Keyword(s):

Suspension Polymerization ◽

Nitrogen Adsorption ◽

Experimental Protocol ◽

New Approach ◽

Surface Areas ◽

Adsorption Data ◽

Novel Method ◽

Derivatives Of ◽

Polymerization Method ◽

Nitrogen Adsorption Data

AbstractIn this study, a novel method for the synthesis of hybrid, porous microspheres, including divinylbenzene (DVB), triethoxyvinylsilane (TEVS) and methacrylated lignin (L-Met), is presented. The methacrylic derivatives of kraft lignin were obtained by reaction with methacryloyl chloride according to a new experimental protocol. The course of the modification of lignin was confirmed by attenuated total reflectance (ATR-FTIR) and nuclear magnetic resonance (NMR) spectroscopy. The emulsion-suspension polymerization method was employed to obtain copolymers of DVD, TEVS and L-Met in spherical forms. The porous structures and morphologies of the obtained lignin-containing functionalized microspheres were investigated by low-temperature nitrogen adsorption data and scanning electron microscopy (SEM). The microspheres are demonstrated to be mesoporous materials with specific surface areas in the range of 430–520 m2/g. The effects of the lignin component on the porous structure, shape, swelling and thermal properties of the microspheres were evaluated.

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Swimming downstream: statistical analysis of differential transcript usage following Salmon quantification

F1000Research ◽

10.12688/f1000research.15398.1 ◽

2018 ◽

Vol 7 ◽

pp. 952 ◽

Cited By ~ 26

Author(s):

Michael I. Love ◽

Charlotte Soneson ◽

Rob Patro

Keyword(s):

Software Package ◽

Gene Expression Analysis ◽

Real Data ◽

Transcript Level ◽

Bioinformatic Analysis ◽

Rna Seq ◽

Statistical Framework ◽

Gene Level ◽

Show Evidence ◽

Differential Gene

Detection of differential transcript usage (DTU) from RNA-seq data is an important bioinformatic analysis that complements differential gene expression analysis. Here we present a simple workflow using a set of existing R/Bioconductor packages for analysis of DTU. We show how these packages can be used downstream of RNA-seq quantification using the Salmon software package. The entire pipeline is fast, benefiting from inference steps by Salmon to quantify expression at the transcript level. The workflow includes live, runnable code chunks for analysis using DRIMSeq and DEXSeq, as well as for performing two-stage testing of DTU using the stageR package, a statistical framework to screen at the gene level and then confirm which transcripts within the significant genes show evidence of DTU. We evaluate these packages and other related packages on a simulated dataset with parameters estimated from real data.

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TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders

Bioinformatics ◽

10.1093/bioinformatics/bth315 ◽

2004 ◽

Vol 20 (16) ◽

pp. 2878-2879 ◽

Cited By ~ 527

Author(s):

W. H. Majoros ◽

M. Pertea ◽

S. L. Salzberg

Keyword(s):

Ab Initio ◽

Open Source ◽

Eukaryotic Gene

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ASPic-GeneID: A Lightweight Pipeline for Gene Prediction and Alternative Isoforms Detection

BioMed Research International ◽

10.1155/2013/502827 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 4

Author(s):

Tyler Alioto ◽

Ernesto Picardi ◽

Roderic Guigó ◽

Graziano Pesole

Keyword(s):

Ab Initio ◽

Gene Annotation ◽

Gene Prediction ◽

Gene Prediction Program ◽

C Elegans ◽

Prediction Program ◽

First Pass ◽

Main Components ◽

Genome Projects ◽

Alternative Isoforms

New genomes are being sequenced at an increasingly rapid rate, far outpacing the rate at which manual gene annotation can be performed. Automated genome annotation is thus necessitated by this growth in genome projects; however, full-fledged annotation systems are usually home-grown and customized to a particular genome. There is thus a renewed need for accurateab initiogene prediction methods. However, it is apparent that fullyab initiomethods fall short of the required level of sensitivity and specificity for a quality annotation. Evidence in the form of expressed sequences gives the single biggest improvement in accuracy when used to inform gene predictions. Here, we present a lightweight pipeline for first-pass gene prediction on newly sequenced genomes. The two main components are ASPic, a program that derives highly accurate, albeit not necessarily complete, EST-based transcript annotations from EST alignments, and GeneID, a standard gene prediction program, which we have modified to take as evidence intron annotations. The introns output by ASPic CDS predictions is given to GeneID to constrain the exon-chaining process and produce predictions consistent with the underlying EST alignments. The pipeline was successfully tested on the entireC. elegansgenome and the 44 ENCODE human pilot regions.

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The Identification of Boll Weevil, Anthonomus grandis grandis (Coleoptera: Curculionidae), Genes Involved in Pheromone Production and Pheromone Biosynthesis

Insects ◽

10.3390/insects12100893 ◽

2021 ◽

Vol 12 (10) ◽

pp. 893

Author(s):

Lindsey C. Perkin ◽

Jose L. Perez ◽

Charles P.-C. Suh

Keyword(s):

Control Strategies ◽

Boll Weevil ◽

Pheromone Biosynthesis ◽

Anthonomus Grandis ◽

Pheromone Production ◽

Rna Seq ◽

Level Control ◽

Production Development ◽

Gene Level ◽

One Step

Eradication programs for the boll weevil, Anthonomus grandis grandis Boheman (Coleoptera: Curculionidae), rely almost exclusively on pheromone traps to indicate the need for insecticide applications. However, the effectiveness of traps in detecting weevil populations is reduced during certain times of the year, particularly when cotton is actively fruiting. Consequently, this could result in fields becoming heavily infested with weevils. It is widely speculated that the lack of weevil captures in traps during this period is largely due to the overwhelming amount of pheromone released by weevils in the field, which outcompete the pheromone released from traps. Thus, this work sought to identify genes involved in pheromone production so that new control methods that target these genes can be explored. We conducted an RNA-seq experiment that revealed 2479 differentially expressed genes between pheromone-producing and non-pheromone-producing boll weevils. Of those genes, 1234 were up-regulated, and 1515 were down-regulated, and most had gene annotations associated with pheromone production, development, or immunity. This work advances our understanding of boll weevil pheromone production and brings us one step closer to developing gene-level control strategies for this cotton pest.

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