Peer Review #1 of "A practical guide to build de-novo assemblies for single tissues of non-model organisms: the example of a Neotropical frog (v0.2)"

The European bison is a non-model organism; thus, most of its genetic and genomic analyses have been performed using cattle-specific resources, such as BovineSNP50 BeadChip or Illumina Bovine 800 K HD Bead Chip. The problem with non-specific tools is the potential loss of evolutionary diversified information (ascertainment bias) and species-specific markers. Here, we have used a genotyping-by-sequencing (GBS) approach for genotyping 256 samples from the European bison population in Bialowieza Forest (Poland) and performed an analysis using two integrated pipelines of the STACKS software: one is de novo (without reference genome) and the other is a reference pipeline (with reference genome). Moreover, we used a reference pipeline with two different genomes, i.e., Bos taurus and European bison. Genotyping by sequencing (GBS) is a useful tool for SNP genotyping in non-model organisms due to its cost effectiveness. Our results support GBS with a reference pipeline without PCR duplicates as a powerful approach for studying the population structure and genotyping data of non-model organisms. We found more polymorphic markers in the reference pipeline in comparison to the de novo pipeline. The decreased number of SNPs from the de novo pipeline could be due to the extremely low level of heterozygosity in European bison. It has been confirmed that all the de novo/Bos taurus and Bos taurus reference pipeline obtained SNPs were unique and not included in 800 K BovineHD BeadChip.

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The brain transcriptome of the wolf spider, Schizocosa ocreata

BMC Research Notes ◽

10.1186/s13104-021-05648-y ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Daniel Stribling ◽

Peter L. Chang ◽

Justin E. Dalton ◽

Christopher A. Conow ◽

Malcolm Rosenthal ◽

...

Keyword(s):

Gene Expression ◽

De Novo ◽

Transcriptome Assembly ◽

Model Organisms ◽

De Novo Transcriptome Assembly ◽

De Novo Transcriptome ◽

Wolf Spiders ◽

Schizocosa Ocreata ◽

Genomic Studies ◽

The Brain

Abstract Objectives Arachnids have fascinating and unique biology, particularly for questions on sex differences and behavior, creating the potential for development of powerful emerging models in this group. Recent advances in genomic techniques have paved the way for a significant increase in the breadth of genomic studies in non-model organisms. One growing area of research is comparative transcriptomics. When phylogenetic relationships to model organisms are known, comparative genomic studies provide context for analysis of homologous genes and pathways. The goal of this study was to lay the groundwork for comparative transcriptomics of sex differences in the brain of wolf spiders, a non-model organism of the pyhlum Euarthropoda, by generating transcriptomes and analyzing gene expression. Data description To examine sex-differential gene expression, short read transcript sequencing and de novo transcriptome assembly were performed. Messenger RNA was isolated from brain tissue of male and female subadult and mature wolf spiders (Schizocosa ocreata). The raw data consist of sequences for the two different life stages in each sex. Computational analyses on these data include de novo transcriptome assembly and differential expression analyses. Sample-specific and combined transcriptomes, gene annotations, and differential expression results are described in this data note and are available from publicly-available databases.

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Microbial Functional Responses to Cholesterol Catabolism in Denitrifying Sludge

mSystems ◽

10.1128/msystems.00113-18 ◽

2018 ◽

Vol 3 (5) ◽

Cited By ~ 6

Author(s):

Sean Ting-Shyang Wei ◽

Yu-Wei Wu ◽

Tzong-Huei Lee ◽

Yi-Shiang Huang ◽

Cheng-Yu Yang ◽

...

Keyword(s):

16S Rrna ◽

De Novo ◽

Anthropogenic Impacts ◽

Sequence Similarity ◽

Community Level ◽

Model Organisms ◽

Substrate Uptake ◽

Functional Responses ◽

Content Type ◽

Rare Biosphere

ABSTRACTThe 2,3-secopathway, the pathway for anaerobic cholesterol degradation, has been established in the denitrifying betaproteobacteriumSterolibacterium denitrificans. However, knowledge of how microorganisms respond to cholesterol at the community level is elusive. Here, we applied mesocosm incubation and 16S rRNA sequencing to reveal that, in denitrifying sludge communities, three betaproteobacterial operational taxonomic units (OTUs) with low (94% to 95%) 16S rRNA sequence similarity toStl. denitrificansare cholesterol degraders and members of the rare biosphere. Metatranscriptomic and metabolite analyses show that these degraders adopt the 2,3-secopathway to sequentially catalyze the side chain and sterane of cholesterol and that two molybdoenzymes—steroid C25 dehydrogenase and 1-testosterone dehydrogenase/hydratase—are crucial for these bioprocesses, respectively. The metatranscriptome further suggests that these betaproteobacterial degraders display chemotaxis and motility toward cholesterol and that FadL-like transporters may be the key components for substrate uptake. Also, these betaproteobacteria are capable of transporting micronutrients and synthesizing cofactors essential for cellular metabolism and cholesterol degradation; however, the required cobalamin is possibly provided by cobalamin-de novo-synthesizing gamma-, delta-, and betaproteobacteria via the salvage pathway. Overall, our results indicate that the ability to degrade cholesterol in sludge communities is reserved for certain rare biosphere members and that C25 dehydrogenase can serve as a biomarker for sterol degradation in anoxic environments.IMPORTANCESteroids are ubiquitous and abundant natural compounds that display recalcitrance. Biodegradation via sludge communities in wastewater treatment plants is the primary removal process for steroids. To date, compared to studies for aerobic steroid degradation, the knowledge of anaerobic degradation of steroids has been based on only a few model organisms. Due to the increase of anthropogenic impacts, steroid inputs may affect microbial diversity and functioning in ecosystems. Here, we first investigated microbial functional responses to cholesterol, the most abundant steroid in sludge, at the community level. Our metagenomic and metatranscriptomic analyses revealed that the capacities for cholesterol approach, uptake, and degradation are unique traits of certain low-abundance betaproteobacteria, indicating the importance of the rare biosphere in bioremediation. Apparent expression of genes involved in cofactorde novosynthesis and salvage pathways suggests that these micronutrients play important roles for cholesterol degradation in sludge communities.

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TransFlow: a modular framework for assembling and assessing accurate de novo transcriptomes in non-model organisms

BMC Bioinformatics ◽

10.1186/s12859-018-2384-y ◽

2018 ◽

Vol 19 (S14) ◽

Cited By ~ 6

Author(s):

Pedro Seoane ◽

Marina Espigares ◽

Rosario Carmona ◽

Álvaro Polonio ◽

Julia Quintana ◽

...

Keyword(s):

De Novo ◽

Model Organisms ◽

Modular Framework

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AStrap: identification of alternative splicing from transcript sequences without a reference genome

Bioinformatics ◽

10.1093/bioinformatics/bty1008 ◽

2018 ◽

Vol 35 (15) ◽

pp. 2654-2656 ◽

Cited By ~ 5

Author(s):

Guoli Ji ◽

Wenbin Ye ◽

Yaru Su ◽

Moliang Chen ◽

Guangzao Huang ◽

...

Keyword(s):

Machine Learning ◽

Alternative Splicing ◽

Single Molecule ◽

Reference Genome ◽

De Novo ◽

Supplementary Information ◽

Model Organisms ◽

Sequencing Data ◽

Extensive Evaluation ◽

Reference Genomes

Abstract Summary Alternative splicing (AS) is a well-established mechanism for increasing transcriptome and proteome diversity, however, detecting AS events and distinguishing among AS types in organisms without available reference genomes remains challenging. We developed a de novo approach called AStrap for AS analysis without using a reference genome. AStrap identifies AS events by extensive pair-wise alignments of transcript sequences and predicts AS types by a machine-learning model integrating more than 500 assembled features. We evaluated AStrap using collected AS events from reference genomes of rice and human as well as single-molecule real-time sequencing data from Amborella trichopoda. Results show that AStrap can identify much more AS events with comparable or higher accuracy than the competing method. AStrap also possesses a unique feature of predicting AS types, which achieves an overall accuracy of ∼0.87 for different species. Extensive evaluation of AStrap using different parameters, sample sizes and machine-learning models on different species also demonstrates the robustness and flexibility of AStrap. AStrap could be a valuable addition to the community for the study of AS in non-model organisms with limited genetic resources. Availability and implementation AStrap is available for download at https://github.com/BMILAB/AStrap. Supplementary information Supplementary data are available at Bioinformatics online.

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