The genes of the sex-determination pathway are highly conserved in Diptera, most notably at the terminal gene, doublesex (dsx), and its upstream regulatory genes transformer (tra) and transformer-2 ( tra-2). From cycle 11, cellularisation genes including serendipity α ( sryα), nullo, bottleneck ( bnk) and slow as molasses ( slam) are activated. Some of the earliest genes to be transcribed are involved in sex determination, such as sisterless A ( sisA) during nuclear cycle 8. Activation of zygotic transcription is controlled, in part, by the zelda ( zld) protein, which interacts with specific heptamer motifs (TAGteam sites) located in the regulatory regions upstream of genes targeted for early, pre-blastoderm transcription. ĭuring these early stages, transcription from the zygotic genome must be initiated. melanogaster early embryo have the distinctive expression profile of maternal transcripts and about two thirds of these decrease markedly over the first 6.5h of development. At least 30% of the transcripts in the D. Proteins such as SMAUG (SMG) and microRNAs are required to regulate degradation of maternal mRNAs in the developing embryo. In Drosophila melanogaster, egg activation is triggered by osmotic and physical stimulation and occurs independently of fertilisation. Our data contribute fundamental information to sex-determination research, and provide candidates for the sourcing of gene promoters for transgenic pest-management strategies of tephritid fruit flies.Įarly stages of embryonic development involve large changes to the RNA transcript profile, as maternal transcripts, deposited during oogenesis, are targeted for degradation, and activation of the zygotic genome takes place. Conclusionsīactrocera jarvisi provides an excellent model for embryonic studies due to available Y-chromosome markers and the compact time frame for zygotic transcription and the sex-determined state. No strong candidates for transcripts derived solely from the Y chromosome were recovered from the poly(A+) fraction. jarvisi, including transcripts highly upregulated prior to cellularisation. Transcripts for sixteen sex-determination and two cellularisation gene homologues of Drosophila melanogaster (Diptera: Drosophilidae) were identified in early embryos of B. Embryos were individually sexed using a Y-chromosome marker, allowing the sex-specific poly(A +) transcriptome of single-sex embryo pools to be deep-sequenced and assembled de novo. Resultsīactrocera jarvisi embryos were collected over two pre-blastoderm time periods, 2-3h and 3-5h after egg laying. Here we investigate the poly(A +) transcriptome in early male and female embryos of the horticultural pest Bactrocera jarvisi (Diptera: Tephritidae). The male sex in tephritid fruit flies is determined by the presence of a Y chromosome, and it is believed that a transcript from the Y-chromosome sets in motion a cascade that determines male development, as part of the greater maternal to zygotic transition (MTZ). Transcripts are generated at different stages of early development, and those involved in sex determination and cellularisation are some of the earliest to be activated. Otherwise you would have to clone yourself a version of the Qiime2 repo and manually change the q2-dada2 script to include justConcatenate, this is likely more of a hassle than its worth to be honest.Developing embryos are provided with maternal RNA transcripts and proteins, but transcription from the zygotic nuclei must be activated to control continuing embryonic development. That being said if you still really wanted to use justConcatenate, I would just stick with the native DADA2 in R then import your result into Qiime2 after. Without proper merging I would stick with just the forward reads. When your reads do not have sufficient overlap, I wouldn’t trust using paired end reads (on any software), how do you know the true position of those reads and the profile of the insertion? Not to mention it is nearly impossible to compare to other datasets too. What are the primers you are using and what is the length of the overlap region with those, what sequencing platform did you use, and how long are your sequences? (2x300?) Ultimately you will need a minimum of 12 nt overlap between your forward and reverse reads for DADA2 to merge them.Ĭan you describe your set up and perhaps we can help with that before looking at other options. The optimization of DADA2 truncating parameters in order to get proper merging has been thoroughly covered in the forum.
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