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\begin{document}

\title{Transcriptome Annotation for Non-model and Semi-model Species (Review)}



\author[1]{Lisa Cohen}%
\author[2]{Tamer Mansour}%
\author[1]{Erica Scott}%
\affil[1]{University of California, Davis}%
\affil[2]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 26, 2024}


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\textbf{Background}

\par\null

Given an organism to study with RNA-seq, it may have a reference genome
or not. In either case, why can't we annotate everything else to the
quality of the human or mouse annotations?

Considerations in this review will include software, pipelines, problems
and best practices.

\par\null

\textbf{Workflow}

The overall workflow of data-\textgreater{}results will serve as the
organization for the paper. The focus is not about each step of this
workflow (see Conesa et al. 2016). Instead, how will each step affect
the annotation?

\par\null

\emph{1. Data acquisition}:~

Library prep:

Effect of different library preps -- both (comment 6 in discussion)

~ ~ - poly(A)-selection

~ ~ - ribo-zero (ribosomal subtraction)

Type of RNA

~~~~- Coding

~~~~- Non\_coding:~Non-coding RNA (comment 9 in discussion)

RNA-seq Data type:

~~~~- ONP

~~~~- PacBio

~~~~- Illumina

Cost benefits of PacBio / Oxford Nanopore sequencing (24e, ~

~~~~

\emph{2. Pre-processing} :

Filtration of RNAseq transcriptomes -- both (7,

- quality trimming

- adapter trimming

Best practices (Matt McManus' paper): Less trimming, the better

- diginorm: helps with low-coverage discovery vs. reference-based will
cause to be more fragmented, and sometimes lose junctions between exons
(unpublished horse transcriptome)

\par\null

\emph{3. Assembly}, split the paper into 2 categories:

~~~~- \textbf{reference-based}: quality of genome is limiting factor,
concept needs to be developed that says if your genome quality is good,
then you should do reference-based mapping, or if your quality is poor,
then do de novo assembly~

Effect of genome quality on transcriptome assembly -- both (4,5,24a,27

Review of Genome-based annotation pipelines (3,15,

~-~pipelines: e.g. Maker \& PASA

~ ~ - \textbf{de novo assembly}

\par\null

\emph{4. Annotation:} this is the meat of what we're talking about in
the paper:~

How to give your gene a name (12, 13,16,18,21,22,23

It's a mess.

~ ~ - spotlight the mess

~ ~ - plan for how to solving the mess

Software: ~dammit, Trinotate

\par\null

\emph{5. Databases and Archiving}

- No universal formatting for description column in gtf, affects
downstream analyses

Major genome annotation databases (2,19,26, 24c,29

Functional annotations (8,11,14,20,24b,28, 24f, 24g

\par\null

\textbf{Assignments for everyone:}

Write down examples faced with trouble with annotation:

- getting (archiving)

- applying

- using downstream

If you were able to solve, what is the best way to go around?

\par\null

Coordinate in groups:

\textbf{reference-based:}

- Daniel

- Erica

- Hussein

\textbf{de novo assembly:}

- Lisa

- Harriet

- Tessa

- Camille

\par\null

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