Wednesday, February 28, 2018

meiofauna diversity

meiofauna diversity, good topic for image analysis

reference: "multispecies coalescent delineate structure, not species. "

cytochrome oxidase subunit 1, phylogeny study
"cryptic diversity"

haplotype network show population structures, ototyphlonemertes duplex

spatial-phylo plot, which tool?

oil spill effect on meiofauna, population genomics study

global genomics initiative,

genome initiative workfow,
library prep, WGS, quality check. contamination genome, genome assemble.
Annelida
Nemertea

meta barcoding genes on 18S (nuclear) and COI (mitochondrial). however, 18S is not informative, COI lacks universal primers

Metagenomics, unknown pools of worms,
poor reference genomes

PALADIN: protein alignment for functional profiling whole metagenome shotgun data

assembled mitochondrial genomes from meta-genomes

signal strength in WGS: single cell organism versus multi cell organisms




Sunday, February 25, 2018

Synthetical lethals in cellmap genetic networks



Guo: I think this is explained in the paper, van Leeuwen et al.,  "Exploring genetic suppression interactions on a global scale", Science (2016), 354:aag0839.

This paper mentioned synthetic letality but did not explicitly define if it is a positive or negative interaction. However, I think genetic interactions derived by synthetic lethality should be negative effect. As the positive effect indicates that if mutation of gene A causes a reduced fitness, the double mutation of A and B restored the fitness, and hence gene B is a genetic suppressor of gene A.

I cannot find it on the CellMap website. However, from the NxN database and the fitness data I identified 2191 negative GI's , in which the double mutant fitness (DMF) is lower than 0.1. You may use different criterion, e.g., 159 interactions with DMF <= 0; or 193 with DMF <= 0.01, etc.
See the attached csv file (ranked by the DMF). 

According to DCell paper, Ma et al, synthetic leathal is an example of negative genetic interaction.  see its Figure 3, negative interaction between pmt1D and ire1D. 




Friday, February 23, 2018

Female meiotic drive, Mimulus

Finseth

CenH3

female gametogensis is asymmetric, only one egg but 3 poly bodies. So, there is advantage for genes to be meiotic drivers.

Malik & Hensoff 2001, centromeric drive model. Cost associated with meiotic drive.

Mimulus best case of centromere meiotic drive. Fishman et al 2005, 2008. 
strong hetero-specific drive. M nasutus vs M. guttatus

weak conspecific drive in M. guttatus

Do CenH3 and centromer co-evolve?
Most abundant repeats in WG tend to be centromeric repeats

Finseth found many codons with >2 omega.
Finseth look for GWS in F2 plants, 122 individuals, 1247 markers (14 linkage groups, 14 chromosomes)

Look for genetic suppresor of CenH3 meiotic drive using genewise linkage disequilibrum (r^2),
D in nonrecombining block, suggesting recent selective sweep (Q: how is genetic surfing excluded? )

CenH3A and CenH3B

plan for population

Mimulus does not grow in TN?

Silene in TN
dioecious species
gynodiecious species
hermaphrodites

Reference
https://en.wikipedia.org/wiki/Mimulus

https://www.nature.com/articles/s41598-017-17932-8


Saturday, February 17, 2018

cell size and aging

In yeast, cell size is an indicator for cell's remaining replicative lifespan, based on Jo 2015. So, the limit of cell size could be aging itself.

Friday, February 16, 2018

Monday, February 5, 2018

bluejeans video conferences

gatech uses bluejeans.com for video conference

UAB, aging biology update


Aging Biology Update is brought to you by the UAB Nathan Shock Center and was compiled by Jessica M. Hoffman, Steven N. Austad, and Heather K. Patterson.

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Friday, February 2, 2018

latex, multiple panel figure


More at:
https://tex.stackexchange.com/questions/271518/multiple-panel-figure-with-figures-side-by-side/271522

multiple panel figure in latex. The arrangement is partly controlled by "%", unbelievable.

\documentclass{article}
\usepackage{graphicx}
\usepackage{subcaption}

\begin{document}

\begin{figure}
\centering

\begin{subfigure}[t] {0.4\textwidth}
\centering
\includegraphics[width=\linewidth]{FiguresTables/pdf/BY4742.pdf}
  \caption{}
  \label{Figure:fig_a}
\end{subfigure}
%
\begin{subfigure}[t] {0.4\textwidth}
\centering
     \includegraphics[width=\linewidth]{FiguresTables/pdf/sir2.pdf}
  \caption{}
  \label{Figure:fig_b}
\end{subfigure}

\medskip

\begin{subfigure}[t] {0.4\textwidth}
\centering
     \includegraphics[width=\linewidth]{FiguresTables/pdf/fob1.pdf}
  \caption{}
  \label{Figure:fig_c}
\end{subfigure}
%
\begin{subfigure}[t] {0.4\textwidth}
\centering
     \includegraphics[width=\linewidth]{FiguresTables/pdf/hxk2.pdf}
  \caption{}
  \label{Figure:fig_d}
\end{subfigure}


\begin{minipage}[t]{0.4\textwidth}
\caption{Try a multi-panel figure}
\end{minipage}

\end{figure}

\end{document}



See also: subcaption is more recent that subfigure or subfig
https://tex.stackexchange.com/questions/122314/figures-what-is-the-difference-between-using-subfig-or-subfigure

cellmap, gin, postive and negative interactions


Cellmap contain positive and negative interactions for the same gene-pairs, an apparent quality problem. It seems false disovery rate may be used here to improve the annotations.

Thursday, February 1, 2018

Yeast essential genes, quality check



Their RLSs ranges from ~6 to >40. Other genes such as SOD1, although its mutation leads to an RLS of ~3, it is not considered as an essential gene (not in all essential sets I mentioned).

Here's another example: shown below are the entries of several genes in the SGA_ExE, CellMap table, followed by the measured RLS for the mutated strain:
YDR364C (736, 16.4), YGR092W (5237, 9.8), YHR191C (2127, 8.0), YLR268W (2769, 23.0).
These genes also appear in the SGA_NxN table with 3k-7k entries.

Overall, two steps are needed to clean up the data:

  1. The RLS set itself also has some problem: For example, swh1 and osh1 are two names of the same gene YAR042W, and these two tests have mean RLSs of 22.4 and 26.4, respectively. I found 9 such cases. Apparently we can only use 1 (may be average of the two tests) for them.
  2.  For the essential genes, I think, we may start with the DEG set that based on the yeast deletion collection, and set some criteria: a). did not appear in the RLS set; b). did not appear in the NxN CellMap table; and c). did not labeled nonessential in the growth-fit set. These three criteria give 70, 65 and 73 overlaps, respectively, and overall there are 91 genes should be removed from the DEG set. Of these genes, 70 have RLS data, but 21 do not.