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The MIT synthetic chemist Gobind Khorana won the 1968 Nobel Prize in Chemistry for his work which successfully was able to make chains of Ribonucleic acids. The chemistry was difficult at the time but he won the prize for making specific sequences of RNA bases which were then fed to cells, resulting in specific amino acid chains, which ultimately deciphered ...
9
The read length has absolutely nothing to do with what you are sequencing. It is a characteristic of the sequencing technology you use. NGS sequencing techniques typically produce this sort of short read you're seeing. The read length does not change because you are sequencing a longer molecule. You would still get ~250nt reads even if you were sequencing an ...
8
The Next-Gen sequencers cannot sequence a very long stretch of DNA with good reliability (~150 for the recent model- HiSeq2000; even less for older models such as GA (40), GA-II (70), GA-IIx (90)). For increasing the confidence in a certain hit, it was sequenced from both the ends.
For example, if you have selected 500bp DNA fragment, then after ligating ...
8
You should really read about both these file formats. As swbarnes mentioned, FASTQ and GTF hold different kind of information. GTF stores the annotation of a reference sequence. For example a GTF for a genome sequence will have the information about the locations of features such as genes, transcripts, exons, start codon etc.
FASTQ stores the sequence of a ...
7
There are some databases in which you can search for E.coli gene expression data:
GenExpDB: E. coli Gene Expression Database
Many Microbe Microarrays Database (M3D): A resource of microbial
gene expression data
Stanford MicroArray Database (use the search tool to find relevant organisms)
Colombos (COLlection Of Microarrays for Bacterial OrganismS)
...
6
RNA-seq data usually provides a snapshot in time of the transcriptome of that which is being sequenced. Single-cell sequencing is possible, but less common than RNA-seq on a sample (containing many cells).
You are correct that RNA-seq provides one with knowledge of RNA sequences, like AUGGUCAUCAG and so on. However, one will not necessarily have ...
6
In RNA sequencing, the RNA is fragmented, DNA is synthesized complementary to the RNA fragments, which is followed by a complementary strand synthesis. Fragmentation can be done after the cDNA synthesis too.
This DNA is then amplified to form a cluster that is sequenced. Most Next-Gen sequencing approaches sequence a short segment of the DNA (it has ...
6
It would appear that the current policy at GenBank is to represent all genomic sequences as DNA, even though this is not made explicit in any of the easily retrievable documentation on their website or in their publications. The way in which one determines the nature of the genome is from the first (LOCUS) line in the report, which, in the case of SARS-CoV-2 ...
6
A standard pipeline for DGE would be Salmon for (pseudo)mapping + DESeq2 for statistical analysis.
Salmon is one of a set of modern, fast and accurate mapping software. Requires a transcriptome to be defined.
DESeq2 is a mature R (Bioconductor) package which can handle reasonably complex designs, including time series, but not mixed models. The vignettes are ...
5
You will likely need a tool to "map" the reads on the reference genome.
You may find such a reference genome, together with annotations, here:
ftp://ussd-ftp.illumina.com/.
Mapping tools such as bowtie2 or bwa take fastq files and reference genomes and output mapping results in a format called sam.
You then have a lot of options to estimate gene expression....
4
Yes, it was odd that they said that. The second protocol with the polyA based method had another purpose though, which was "examine the reproducibility of period-regulated genes in an independent genetic background". I would suspect this was its main purpose, and not so much to look at fragment bias, which has already been done in other papers. They didnt ...
4
In Illumina sequencing, the DNA is (usually randomly) sheared into fragments. For paired end sequencing, fragments of a specific size range are selected and then sequenced from both sides.
This results in two reads for each fragment. As read length is fixed, also the remaining "middle part" of the fragment is in a specific size range. In some cases there is ...
4
Good question, a lot of this is still being figured out. Here's what's known so far:
Fragmentation methods based on restriction enzymes aren't random.
Reverse-transcription performed with poly dT-oligomers, which bind to the 3' poly-A tails, is strongly biased towards 3’ end of transcripts.
Reverse-transcription with random hexamers results in an under-...
4
The process of sequencing was, and can be, assisted by cloning a DNA fragment into a known site in a plasmid designed to help sequencing. That cloning site is flanked by a known sequence(s) that can use standard primers
In the figure "A" and "B" are just reference points on either side of the Cloning site. Of course, the plasmid extends on either side of ...
4
In RNA sequencing, total RNA is extracted, then mRNAs are purified out from the sample using polyT columns (since mRNAs have a polyA tail, this will attach to a polyT DNA chunk that is attached to some solid surface). This step is necessary because ribosomal RNAs are much more abundant than mRNAs, and for sequencing you only want to use mRNAs. Then the ...
4
Have you discovered wormbase yet? It will become your new best friend. In worms gene names reflect the loss-of-function (lf) phenotype. Daf means "abnormal DAuer Formation," so daf-2 was the second daf gene identified (ref). The mutations are called alleles and each worm lab has their own allele designation. e was for England and in that lab's strain list ...
4
The frequency of the bases in the genome isn't equal to 0.25, the frequency depends on what kind of organism you mean. However let's take a look at some of them:
bacteria, most of the time we can see a bias towards some bases, this could be a GC bias, for example if the bacteria lives in extreme conditions, because GC can vorm three hydrogen bonds compared ...
4
Q: Why not just extract the proteins…
A: It’s not just a question of extracting the proteins, you would need to separate them and then isolate each of them. There is currently no practical way to do this for say, 10,000 proteins, which in any case may have multiple forms. The beauty of the RNAseq method is that it does not require physical separation or ...
4
Textbook example of multinomial distribution is multiple dice toss. The fair dice has following probabilities:
side 1: 16,66666666%
side 2: 16,66666666%
side 3: 16,66666666%
side 4: 16,66666666%
side 5: 16,66666666%
side 6: 16,66666666%
Lets roll a typical fair dice n = 20 times:
6 5 1 1 3 5 4 3 1 2 4 4 6 6 2 2 5 6 5 2
So this particular outcome of above ...
3
messenger RNA has a poli A tail at its 5´ end. thus when the poly-dT hybridize the mRNA in the reverse transcription the cDNA will carry this poly-dT at its 3`end. Thus, as reverse transcription will always start at the 3´ and of the mRNA its is more likely that this region is better rev. transcribed. Bigger the mRNA is bigger will be this concern.
About ...
3
I guess this arises because of the default cufflinks option --total-hits-norm in which it normalizes the FPKMs with total reads including the ones that are not mapped to a known gene or a predicted gene from the assembly. In the genes.fpkm_tracking file the FPKM values are reported for known/predicted genes. It is certainly possible that the number of genes ...
3
There is something called GEO, which is maintained by the NIH and is a massive collection of data obtained from RNA seq, microarray, etc. experiments. One thing you can do is search for a paper that has done what you are looking for. The paper may have a GEO accession number, and you can use that number at the GEO website to find the data you want. You may ...
3
q-value is the corrected p-value to account for multiple testing (i.e. you are testing thousands of genes). Those with q-value <0.05 are significant experiment-wise. Cuffdiff uses Benjamini-Hochberg correction to compute FDR (i.e. q-value). The calculation does not depend on the number of replicates it's based on the distribution of p-values those, yes, ...
3
A fastq contains sequences. A gtf contains coordinates of where features like exons fall in a reference sequence. You can't interconvert them, that makes no sense.
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Your question is not very clear. What should the contents of your GTF file be? Typically, GTF files contain information about where exons are located in a set of DNA sequences. Determining the location and exon/intron structure of genes is no simple technical task (i.e. a "conversion" as stated in your question), but rather a large area of active research. ...
3
The Tuxedo Suite (Tophat, Bowtie and cufflinks) used to to process RNA_seq data, assuming that is the origin of your .fastq files, should work for you.
https://ccb.jhu.edu/software/tophat/index.shtml
3
If you google HG00105, among the first hits is geo accession GSM649517 with the title HG00105/NA12878.
Channel1:
Characteristics gender: Male
cell line: lymphoblast cell line HG00105
ethnicity: British from England and Scotland, UK (1000 Genomes codes: GBR)
Channel2:
gender: female
cell line: lymphoblast cell line NA12878
ethnicity: Northwest European ...
3
It is difficult to draw any conclusion without further experimentation. There may be many other factors that prevent the expression of the gene including factors like post-transcriptional regulators. Some histone modifications like the ones you are mentioning are also a bit dicey and there can be bivalent modifications too. However, if there is a strong ...
3
While I also agree @bli that R and Python (in particular Bioconductor) have more than enough packages for you to compare gene expression. You shouldn't align your reads with bwa or bowtie because they don't take introns into consideration. You should use TopHat or STAR.
3
The most common and simplest normalization method for spikes is the Total Count Normalization. It's actually what you're doing here, so what you're doing here is correct. TCM is a useful algorithm for normalizing sequencing depth, that includes your spike amounts.
https://academic.oup.com/bib/article-lookup/doi/10.1093/bib/bbs046
has reference on the TCM ...
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