Tweet
I want to do differential gene expression analysis on some Nile Tilapia RNA-Seq data using the Cufflinks-Cuffdiff method. I aligned the sequence reads to the UCSC Nile Tilapia genome with >80% mapping efficiency. I downloaded the annotation GTF file from Ensembl and converted it using the "Make ensembl GTP compatible with Cufflinks" work flow. This workflow adds "chr" in front of the chromosome number. Then I ran cufflinks on the paired-end mapped data with either the original and converted GTF file. However, the counts were 0 for all gene and transcript expression. I noticed the the chromosome names of the Tilapia gtf file are strange. They are "GL831133.1" instead of 1,2,3. I also got zero counts using HTseq-count with either the original and converted GTF file. Does anyone know a good reference annotation file that work for Tilapia? Thanks!
-
-
Ensembl hasn't bothered to include oreNil2, which is what you got from UCSC. If UCSC doesn't provide an annotation then perhaps none exists. -
Looks like Nile tilapia is available in UCSC Table Browser. You should be able to get a GTF file (which should match your sequence) from there.
Clade (Vertebrate) --> Genome (Nile Tilapia) --> group (Genes and Gene Predictions) --> Track (Choose one you want, RefSeq is available) --> Region (Genome) --> Output format (GTF) --> Provide a file name (e.g. tilapia_annot.gtf) --> Save/Use with HTseq-count of featureCounts.Comment
-
Yes, it turns out that the UCSC genome is OreNil2.0 and the ensembl annotation is OreNil1.0. I downloaded the ensembl tilapia genome (OreNil1.0) and did the tophat alignment again. This time, I could run cufflinks and HTseq with the ensembl annotation.Comment
-
Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.
The systematic characterization of the human proteome has...07-20-2026, 11:48 AM -
Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
...07-09-2026, 11:10 AM -
Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.
There is no single reason why many patients don’t respond to treatment as expected. Cancer is...07-08-2026, 05:17 AM
Comment