Transcriptome‐wide changes in testes reveal molecular differences in photoperiod‐induced seasonal reproductive life‐history states in migratory songbirds

Sharma, Aakansha; Das, Subhajit; Kumar, Vinod

doi:10.1002/mrd.23155

Cited by 7 publications

(8 citation statements)

References 41 publications

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“…1) [19][20][21] . Pseudo-aligners were introduced more recently and therefore have lower adoption but are beginning to see wider usage 22,23 . Here we present a benchmarking analysis of the five most popular isoform quantification methods: kallisto, RSEM, Cufflinks, HTSeq, and featureCounts, based on a survey of the literature ( Fig.…”

Section: Rna-seq Transcript Level Quantification Is Validated By Pcrmentioning

confidence: 99%

“…The raw read counts were quantified at the transcript level, using the following methods: the pseudo-aligner kallisto-v0.44.0 18 , the na ï ve read proportioning approach (NRP : http://bioinf.itmat.upenn.edu/BEERS/bp3/ ) based on transcriptome alignment , as well as the genome alignment based methods RSEM 6 , Cuffdiff (Cufflinks-v2.2.1) 4,35 , HTSeq-v0.9.1 3 , and featureCounts (Subread-v1.6.3) 5 . DESeq2-v1.22.2 [23] was used for differential analysis, both between hippocampus and liver; and also between estimated and true transcript counts. All visualizations were done with R-v3.4.3 packages 36 .…”

Section: Rna-seq Analysismentioning

confidence: 99%

“…There are many published methods for quantifying full-length isoforms, however the vast majority of studies performing isoform specific analysis have used Cufflinks, RSEM or some simple counting method following genome alignment (Fig 1) (20)(21)(22). Pseudo-aligners were introduced more recently and therefore have lower adoption but are beginning to see wider usage (23,24).…”

Section: Introductionmentioning

confidence: 99%

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Comparative evaluation of full-length isoform quantification from RNA-Seq

Sarantopoulou

Nayak

Brooks

et al. 2019

Preprint

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Full-length isoform quantification from RNA-Seq is a key goal in transcriptomics analyses and an area of active development. The fundamental difficulty stems from the fact that RNA transcripts are long, while RNA-Seq reads are typically short. We have generated realistic benchmarking data, and have performed a comprehensive comparative analysis of isoform quantification, including evaluating them on the level of differential expression analysis.Genome, transcriptome and pseudo alignment-based methods are included; and a naive approach is included to establish a baseline. Kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform considerably better than the naive approach. We determine the effect of structural parameters, such as number of exons or number of isoforms, on accuracy. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification should be employed selectively.Sarantopoulou et al, Benchmarking of FLI quantification for RNA-Seq -1

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Section: Rna-seq Transcript Level Quantification Is Validated By Pcrmentioning

confidence: 99%

Section: Rna-seq Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparative evaluation of full-length isoform quantification from RNA-Seq

Sarantopoulou

Nayak

Brooks

et al. 2019

Preprint

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“…1) [20][21][22]. Pseudo-aligners were introduced more recently and therefore have lower adoption but are beginning to see wider usage [23,24].…”

mentioning

confidence: 99%

Comparative evaluation of full-length isoform quantification from RNA-Seq

et al. 2021

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Background Full-length isoform quantification from RNA-Seq is a key goal in transcriptomics analyses and has been an area of active development since the beginning. The fundamental difficulty stems from the fact that RNA transcripts are long, while RNA-Seq reads are short. Results Here we use simulated benchmarking data that reflects many properties of real data, including polymorphisms, intron signal and non-uniform coverage, allowing for systematic comparative analyses of isoform quantification accuracy and its impact on differential expression analysis. Genome, transcriptome and pseudo alignment-based methods are included; and a simple approach is included as a baseline control. Conclusions Salmon, kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform dramatically better than the simple approach. We determine the structural parameters with the greatest impact on quantification accuracy to be length and sequence compression complexity and not so much the number of isoforms. The effect of incomplete annotation on performance is also investigated. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification and isoform level DE should still be employed selectively.

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“…The diverse and very extensive effects of testosterone on gene expression in HVC cells were unexpected. Comparable studies of transcriptomic changes following testosterone treatment or associated with seasonal phenotypes in birds, mammals, amphibians, and fish reported much less differentially expressed genes, both in peripheral tissues (Cheviron and Swanson, 2017;Dopico et al, 2015;Faber-Hammond et al, 2015;Morey et al, 2016;Sharma et al, 2019) and vertebrate brain areas (Bao et al, 2019;Peterson et al, 2013;Zhang et al, 2016;Zhao et al, 2021). A comparably large effect was only reported for seasonal changes in the testes (Tian et al, 2019).…”

Section: Fast Transient and Long-term Constant Regulation Of Large Tr...mentioning

confidence: 99%

From silence to song: Testosterone triggers extensive transcriptional changes in the female canary HVC

Frankl-Vilches

Bakker

et al. 2022

Preprint

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Like other canary reproductive behaviors, song production occurs seasonally and can be triggered by gonadal hormones. Adult female canaries treated with testosterone sing first songs after four days and progressively develop towards typical canary song structure over several weeks, a behavior that females otherwise rarely or never show. We compared gene regulatory networks in the song-controlling brain area HVC after 1 hour (h), 3 h, 8 h, 3 days (d), 7d, and 14d testosterone treatment with placebo-treated control females, paralleling HVC and song development. Rapid onset (1 h or less) of extensive transcriptional changes (2,700 genes) preceded the onset of song production by four days. The highest level of differential gene expression occurred at 14 days when song structure was most elaborate, and song activity was highest. The transcriptomes changed massively several times during the two-week of song production. A total of 9,710 genes were differentially expressed, corresponding to about 60% of the known protein-coding genes of the canary genome. Most (99%) of the differentially expressed genes were regulated only at specific stages. The differentially expressed genes were associated with diverse biological functions, of which cellular level occurring early and nervous system level occurring primarily after prolonged testosterone treatment. Thus, the development of adult songs requires restructuring the entire HVC, including most HVC cell types, rather than altering only neuronal subpopulations or cellular components. Parallel regulation directly by androgen and estrogen receptors and by other hub genes such as the transcription factor SP8, which are under steroidogenic control, lead to massive transcriptomic and neural changes in the specific behavior-controlling brain areas and gradual seasonal occurrence of singing behavior.

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Transcriptome‐wide changes in testes reveal molecular differences in photoperiod‐induced seasonal reproductive life‐history states in migratory songbirds

Cited by 7 publications

References 41 publications

Comparative evaluation of full-length isoform quantification from RNA-Seq

Comparative evaluation of full-length isoform quantification from RNA-Seq

Comparative evaluation of full-length isoform quantification from RNA-Seq

From silence to song: Testosterone triggers extensive transcriptional changes in the female canary HVC

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