RNA sequencing reveals a diverse and dynamic repertoire of the Xenopus tropicalis transcriptome over development

Abstract

The Xenopus embryo has provided key insights into fate specification, the cell cycle, and other fundamental developmental and cellular processes, yet a comprehensive understanding of its transcriptome is lacking. Here, we used paired end RNA sequencing (RNA-seq) to explore the transcriptome of Xenopus tropicalis in 23 distinct developmental stages. We determined expression levels of all genes annotated in RefSeq and Ensembl and showed for the first time on a genome-wide scale that, despite a general state of transcriptional silence in the earliest stages of development, approximately 150 genes are transcribed prior to the midblastula transition. In addition, our splicing analysis uncovered more than 10,000 novel splice junctions at each stage and revealed that many known genes have additional unannotated isoforms. Furthermore, we used Cufflinks to reconstruct transcripts from our RNA-seq data and found that~13.5% of the final contigs are derived from novel transcribed regions, both within introns and in intergenic regions. We then developed a filtering pipeline to separate protein-coding transcripts from noncoding RNAs and identified a confident set of 6686 noncoding transcripts in 3859 genomic loci. Since the current reference genome,

Histone titration against the genome sets the DNA-to-cytoplasm threshold for the Xenopus midblastula transition

“…Moreover, histones are repressive to exogenous transcription in Xenopus embryos and extract (10,12). Because nucleosomal histones are present across the genome, histone titration could directly regulate the diverse zygotic gene set associated with the MBT (30,33). Finally, histones bind DNA nonspecifically, which is consistent with the observation that many different DNA sources can shift the timing of the MBT (1).…”

Amphibian molecular ecology and how it has informed conservation

“…Open shrub habitat and river crossings facilitate migration between populations, while elevation differences decrease gene flow Johansson et al (2005) Common frog (Rana temporaria) 7 microsats Agricultural fragmentation has markedly different impacts on the species in different parts of its range Funk et al (2005) Columbia spotted frog (R. luteiventris) 6 microsats There is a high degree of gene flow among low-elevation populations, and elevation changes serve as barriers to gene flow have recently been sequenced and assembled, including members of three salamander families [Hynobius chinensis (Che et al 2014), A. mexicanum , Notophthalmus viridescens (Looso et al 2013)] and three anuran families [X. tropicalis (Hellsten et al 2010;Tan et al 2013), X. laevis (Morin et al 2006), Pseudacris regilla/Rana (Lithobates) clamitans (Robertson & Cornman 2014), Rana chensinensis/Rana kukunoris (Yang et al 2012), Rana muscosa/Rana sierrae (Rosenblum et al 2012), Odorrana margaretae (Qiao et al 2013), Espadarana prosoblepon/Rana (Lithobates) yavapaiensis (Savage et al 2014)]. Several of these taxa are endangered in the wild, and the availability of these transcriptome resources will allow researchers to design target-capture arrays using DNA sequence data for a large variety of amphibian species.…”

Comparative epigenomics in distantly related teleost species identifies conserved cis-regulatory nodes active during the vertebrate phylotypic period

“…Based on previous studies, we selected embryos within the pharyngula period for these two organisms (Irie and Kuratani 2011). For Xenopus, previously published data from stage 24-26 embryos were included in our study (Tan et al 2013). For mouse, we performed a complete RNA sequencing analysis in duplicate using 10.5-d embryos (Pearson correlation between replicates = 0.75).…”

“…Raw RNA sequence data from medaka and mouse, and previously published Xenopus (Tan et al 2013) and zebrafish (Collins et al 2012;Choudhuri et al 2013) data, were aligned with the oryLat2 (October 2005), mm9 (July 2007), xenTro2 (August 2005), and danRer7 (July 2010) genome versions, respectively, using TopHat ). To minimize errors due to the variability between species annotations, we took into account only the number of mapped reads that overlapped with the Ensembl coding sequences of those genes present in our orthologs list.…”