A pothole video dataset for semantic segmentation

This paper introduces a video dataset for semantic segmentation of road potholes. This dataset contains 619 high-resolution videos captured in January 2023, covering locations in eight villages within the Hulu Sungai Tengah regency of South Kalimantan, Indonesia. The dataset is divided into three main folders, namely train, val, and test. The train, val, and test folders contain 372 videos for training, 124 videos for validation, and 123 videos for testing, respectively. Each of these main folders has two subfolders, ``RGB'' for the video in the RGB format and ``mask'' for the ground truth segmentation. These videos are precisely two seconds long, containing 48 frames each, and all are in MP4 format. The dataset offers remarkable flexibility, accommodating various research needs, from full-video segmentation to frame extraction. It enables researchers to create ground truth annotations and change the combination of videos in the folders according to their needs. This resource is an asset for researchers, engineers, policymakers, and anyone interested in advancing algorithms for pothole detection and analysis. This dataset allows for benchmarking semantic segmentation algorithms, conducting comparative studies on pothole detection methods, and exploring innovative approaches, offering valuable contributions to the computer vision community.

Metagenomic data of bacterial 16S rRNA in the cemetery soil samples in Surakarta City, Indonesia

Cemetery soils most likely contain degradative bacteria which possibly have beneficial potencies. However, the bacterial exploration in these potencies is still limitedly conducted in Indonesia. The raw sequence data of total bacteria in the cemetery soils through metagenomic analysis have been revealed. The data were obtained by collecting soil samples from six spots of two major Cemetery areas, which were Pracimaloyo (P) and Bonoloyo (B), in Surakarta City, Central Java, Indonesia. The six sample spots consisted of two samples from P area with respectively 20 cm and 140 cm depths and four samples of each two samples from B area with 20 and 40 cm depths. The total DNA was subsequently extracted from the collected soils using ZymoBIOMICS DNA Miniprep Kit. The total DNA then was amplified using a couple of 16S rRNA primers through Illumina HiSeq 2500 PE250 (Novogen, Korea) environment system. The raw sequence data has been submitted to the National Center for Biotechnology Information (NCBI) with project ID PRJNA997385. The archived sequence can be accessed in the NCBI website with the following URLs https://www.ncbi.nlm.nih.gov/sra/PRJNA997385. A brief analysis of the sequence data showed that the most common phyla in 20 cm-depths were Proteobacteria (29.5%), Actinobacteria (21.6%), and Firmicutes (19.2%), while Actinobacteria were the most found in 140 cm-depths with 34.2% followed by Proteobacteria (21.9%) and Firmicutes (16.6%). This data would be the first report of total bacterial sequence from cemetery soils in Indonesia.

Life history data from the gateway to global ageing data platform: resources for studying life courses across Europe

Research from a range of disciplines highlights the need to adopt a life course perspective that considers earlier life courses to explain outcomes in later life (e.g. later life health, cognitive ageing or retirement behaviour). This includes a more comprehensive assessment of earlier life courses over time and of how they are shaped by societal and political contexts. But quantitative data with detailed information on life courses that allow to address these questions are rare. Or, in case the data are available, the data are rather difficult to handle and appears to be underused. This contribution introduces the harmonized life history data from the gateway to global ageing data platform from two European Surveys, SHARE and ELSA, with data from 30 European countries. Besides providing some details on the collection of life history data in the two surveys, we also describe the way how raw data were rearranged in a user-friendly state sequence format and additionally give some examples based on the resulting data. This illustrates the potential of collected life history data from SHARE and ELSA, clearly going beyond the description of single aspects of the life course. By providing harmonized data of two prominent studies on ageing in Europe in a user-friendly format, the gateway to global ageing data platform provides a unique data source that is easily accessible for research, and permits to study life course and their links to later life in a cross-national perspective.

Genome wide association analysis on semen volume and milk yield using different strategies of imputation to whole genome sequence in French dairy goats

Background

Goats were domesticated 10,500 years ago to supply humans with useful resources. Since then, specialized breeds that are adapted to their local environment have been developed and display specific genetic profiles. The VarGoats project is a 1000 genomes resequencing program designed to cover the genetic diversity of the Capra genus. In this study, our main objective was to assess the use of sequence data to detect genomic regions associated with traits of interest in French Alpine and Saanen breeds.

Results

Direct imputation from the GoatSNP50 BeadChip genotypes to sequence level was investigated in these breeds using FImpute and different reference panels: within-breed, all Capra hircus sequenced individuals, European goats and French mainland goats. The best results were obtained with the French goat panel with allele and genotype concordance rates reaching 0.86 and 0.75 in the Alpine and 0.86 and 0.73 in the Saanen breed respectively. Mean correlations tended to be low in both breeds due to the high proportion of variants with low frequencies.

For association analysis, imputation was performed using FImpute for 1129 French Alpine and Saanen males using within-breed and French panels on 23,338,436 filtered variants. The association results of both imputation scenarios were then compared. In Saanen goats, a large region on chromosome 19 was significantly linked to semen volume and milk yield in both scenarios. Significant variants for milk yield were annotated for 91 genes on chromosome 19 in Saanen goats. For semen volume, the annotated genes include YBOX2 which is related to azoospermia or oligospermia in other species. New signals for milk yield were detected on chromosome 2 in Alpine goats and on chromosome 5 in Saanen goats when using a multi-breed panel.

Conclusion

Even with very small reference populations, an acceptable imputation quality can be achieved in French dairy goats. GWAS on imputed sequences confirmed the existence of QTLs and identified new regions of interest in dairy goats. Adding identified candidates to a genotyping array and sequencing more individuals might corroborate the involvement of identified regions while removing potential imputation errors.

Characterisation of the tongue worm, Linguatula serrata (Pentastomida: Linguatulidae), in Australia

We describe adult males and females and a nymph belonging to Linguatula serrata in Australia, based on light and scanning electron microscopies. In addition, 18S and Cox1 sequence data have also been provided and were compared with similar sequences in GenBank. Our specimens had identical 18S sequences and limited genetic distance in Cox1 region which fell within the intra-specific range observed for Linguatula spp. suggesting that they all belong to one species. Phylogenetic analyses showed that Australian specimens were grouped with L. serrata in Europe where the species was first found and described. A number of L. serrata from Iran and Bangladesh formed a distinct group. The genetic distance between these Linguatula and Australian/European L. serrata ranged from 0.46% to 2.21% which is larger than the genetic distance observed between L. arctica and Australian/European L. serrata (0.12%) suggesting that they belong to a different species. As pointed out previously by several other authors, L. serrata comprises more than one species and those from the Palearctic region (including Iran and Bangladesh) should not be automatically named L. serrata unless there is enough evidence for the identification. To accurately address the complex taxonomy of Linguatula spp. a detailed morphological and genetic characterisation of numerous developmental stages of the parasite is necessary, to ensure morphological differences are not due to development. This however may not be achievable in the near future due to significant reduction in expertise as well as research funding awarded in this area of research to understand the basics of our planet.

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Detailed description of Australian tongue worms.

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First genetic characterization of Linguatula serrata in Australia.

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Specific identification of Linguatula serrata in Australia.

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Taxonomic status of L. dingophila could be valid but requires further investigation.

Population genetic analysis of trematode Parasaccocoelium mugili Zhukov, 1971 (Haploporidae Nicoll, 1914) from the Russian Far East and Vietnam based on ribosomal ITS and mitochondrial COI gene partial sequence data

Intraspecific variation of Parasaccocoelium mugili collected from mullet fish of the south of Russian Far East and Vietnam has previously been estimated on the basis of two molecular markers: ribosomal internal transcribed spacer 1 (ITS1) rDNA and mitochondrial cytochrome oxidase I (COI) gene sequences. In the present study, molecular identification of this species from the Kievka River, Primorye and from Vietnam was performed by analysis of 28S rDNA sequences. Analysis of ITS1 rDNA sequences variation revealed two highly differentiated main groups, representing trematode specimens from the two regions. Genetic variation within each region was relatively low. Mitochondrial COI gene sequence data analysis revealed fixed nucleotide and amino acid substitutions, and supported the existence of two genetically different groups associated with geographical origin. Analysis of the COI gene fragments showed extremely high variation within Russian and Vietnamese P. mugili samples. Our results for P. mugili most probably represent a case of initial step of allopotric speciation for this trematode, caused by living strategy of its definitive host at evolutionary scale. Mitochondrial DNA sequence data show that existence of gene flow between local populations of P. mugili in the Primorye Region caused by definitive hosts can be proposed.

FastqPuri: high-performance preprocessing of RNA-seq data

Background

RNA sequencing (RNA-seq) has become the standard means of analyzing gene and transcript expression in high-throughput. While previously sequence alignment was a time demanding step, fast alignment methods and even more so transcript counting methods which avoid mapping and quantify gene and transcript expression by evaluating whether a read is compatible with a transcript, have led to significant speed-ups in data analysis. Now, the most time demanding step in the analysis of RNA-seq data is preprocessing the raw sequence data, such as running quality control and adapter, contamination and quality filtering before transcript or gene quantification. To do so, many researchers chain different tools, but a comprehensive, flexible and fast software that covers all preprocessing steps is currently missing.

Results

We here present FastqPuri, a light-weight and highly efficient preprocessing tool for fastq data. FastqPuri provides sequence quality reports on the sample and dataset level with new plots which facilitate decision making for subsequent quality filtering. Moreover, FastqPuri efficiently removes adapter sequences and sequences from biological contamination from the data. It accepts both single- and paired-end data in uncompressed or compressed fastq files. FastqPuri can be run stand-alone and is suitable to be run within pipelines. We benchmarked FastqPuri against existing tools and found that FastqPuri is superior in terms of speed, memory usage, versatility and comprehensiveness.

Conclusions

FastqPuri is a new tool which covers all aspects of short read sequence data preprocessing. It was designed for RNA-seq data to meet the needs for fast preprocessing of fastq data to allow transcript and gene counting, but it is suitable to process any short read sequencing data of which high sequence quality is needed, such as for genome assembly or SNV (single nucleotide variant) detection. FastqPuri is most flexible in filtering undesired biological sequences by offering two approaches to optimize speed and memory usage dependent on the total size of the potential contaminating sequences. FastqPuri is available at https://github.com/jengelmann/FastqPuri. It is implemented in C and R and licensed under GPL v3.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2799-0) contains supplementary material, which is available to authorized users.

AnnotationBustR: an R package to extract subsequences from GenBank annotations

BACKGROUND

DNA sequences are pivotal for a wide array of research in biology. Large sequence databases, like GenBank, provide an amazing resource to utilize DNA sequences for large scale analyses. However, many sequence records on GenBank contain more than one gene or are portions of genomes. Inconsistencies in the way genes are annotated and the numerous synonyms a single gene may be listed under provide major challenges for extracting large numbers of subsequences for comparative analysis across taxa. At present, there is no easy way to extract portions from many GenBank accessions based on annotations where gene names may vary extensively.

RESULTS

The R package AnnotationBustR allows users to extract sequences based on GenBank annotations through the ACNUC retrieval system given search terms of gene synonyms and accession numbers. AnnotationBustR extracts subsequences of interest and then writes them to a FASTA file for users to employ in their research endeavors.

CONCLUSION

FASTA files of extracted subsequences and accession tables generated by AnnotationBustR allow users to quickly find and extract subsequences from GenBank accessions. These sequences can then be incorporated in various analyses, like the construction of phylogenies to test a wide range of ecological and evolutionary hypotheses.

Genome-wide association study on chicken carcass traits using sequence data imputed from SNP array

Chicken carcass traits are economically important for the chicken industry. Detecting which genes affect chicken carcass traits is of great benefit to the genetic improvement of this important agricultural species. To investigate the genetic mechanism of carcass traits in chickens, we carried out a genome-wide association study (GWAS). A total of 435 Chinese indigenous chickens were phenotyped for carcass weight (CW), eviscerated weight with giblets (EWG), and eviscerated weight (EW) after slaughter at 91 days and were genotyped using a 600-K single nucleotide polymorphism (SNP) genotyping array. Twenty-four birds were selected for sequencing, and the 600 K SNP panel data were imputed to sequence data with the 24 birds as the reference. Univariate GWASs were performed with GEMMA software using the whole genome sequence data imputed from SNP chip data. Finally, 3, 25, and 63 suggestively significant SNPs were identified to be associated with carcass weight (CW), eviscerated weight with giblets (EWG), and eviscerated weight (EW), respectively. Six candidate genes, RNF219, SCEL, MYCBP2, ETS1, APLP2, and PRDM10 were detected. SCEL and MYCBP2 were potentially associated with these three traits, RNF219 and APLP2 were potentially associated with EWG and EW, and ETS1 and PRDM10 were only potentially associated with EWG and EW, respectively. Compared with forefathers' research, 10 reported QTLs associated with CW were located within a 5-Mb distance near the SNPs with P value lower than 1×10^-5. This study enriched the knowledge of the genetic mechanisms of chicken carcass traits.

Anomaly detection based on a dynamic Markov model

Anomaly detection in sequence data is becoming more and more important in a wide variety of application domains such as credit card fraud detection, health care in medical field, and intrusion detection in cyber security. In the existing anomaly detection approaches, Markov chain techniques are widely accepted for their simple realization and few parameters. However, the short memory property of a classical Markov model ignores the interaction among data, and the long memory property of a higher order Markov model clouds the relationship between the previous data and current test data, and reduces the reliability of the model. Besides, both of these models cannot successfully describe the sequences changing with a tendency. In this paper, we propose an anomaly detection approach based on a dynamic Markov model. This approach segments sequence data by a sliding window. In the sliding window, we define the states of data according to the value of the data and establish a higher order Markov model with a proper order consequently, to balance the length of the memory property and keep up with the trend of sequences. In addition, an anomaly substitution strategy is proposed to prevent the detected anomalies from impacting the building of the models and keep anomaly detection continuously. The experimental results using simulated datasets and real-world datasets have demonstrated that the proposed approach improves the adaptability and stability of anomaly detection in sequence data.

MIxS-HCR: a MIxS extension defining a minimal information standard for sequence data from environments pertaining to hydrocarbon resources

Here we introduce a MIxS extension to facilitate the recording and cataloguing of metadata from samples related to hydrocarbon resources. The proposed MIxS-HCR package incorporates the core features of the MIxS standard for marker gene (MIMARKS) and metagenomic (MIMS) sequences along with a hydrocarbon resources customized environmental package. Adoption of the MIxS-HCR standard will enable the comparison and better contextualization of investigations related to hydrocarbon rich environments. The insights from such standardized way of reporting could be highly beneficial for the successful development and optimization of hydrocarbon recovery processes and management of microbiological issues in petroleum production systems.