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+From: RWWilliams, rwilliams\@uthsc.edu, labwilliams\@gmail
+
+To: Many (and now about ready for a blog)
+
+Date: 14Feb2021
+
+Version: Extended cut of 15Feb2021 v2
+
+Dear colleagues (particularly those interested in alcohol and drug
+addiction, brain proteomics, dopamine, causal modeling),
+
+You could either go tobogganing today or tomorrow OR learn a bit about a
+cool new rat brain proteomics-genetics data set generated by Xusheng
+Wang (University of North Dakota) and colleagues, including Jumin Peng
+at St. Jude Children\'s Research Hospital, and Michal Pravenec at the
+Czech Academy of Science. This is an open, but not yet final,
+quantitative proteomics data for the whole brain for 21 strains of rat
+(male and female isogenic littermates) from the HXB/BXH family---part of
+the Hybrid Rat Diversity Panel.
+
+For those of you on this list at NIH, first, thank you for all of your
+support over more than 20 years that has made this Valentine\'s primer
+possible---starting with the NIH Human Brain Project and continuing now
+with a NIDA P30. I hope you will be impressed not only by the data that
+Xusheng generated, but by the FAIR-ness and ease of analysis of highly
+valuable smart quadratic data.
+
+What the heck is *smart quadratic data*? Please see an extended
+discussion on this topic (verging on a rant in sections) given at the
+University of Virginia in the Data Science program, 20Nov2020:
+ ***<https://youtu.be/4ZhnXU8gV44> ***
+
+> **Footnote on this presentation**: Do you wonder why translation fails
+> from animal models to human clinical care? 1-N-der? NIH has funded *n
+> = 1* biomedical experimental research for about 70 years without
+> blinking. Anyone who read Roger J. Williams\'s *Biochemical
+> Individuality* when it came out in 1956 should have known better
+> (***https://en.wikipedia.org/wiki/Roger_J._Williams***). My excuse
+> is that I was four years old, but James Shannon was 52 years old.
+> Elias Zerhouni was 5 years old, Francis Collins was 6 years old, and
+> Eric Lander was about --9 months old. But it is now 2021 and in this
+> glorious \"post-genomics\" era of highly accurate personalized health
+> care and prevention (not) we should grow up and embrace the diversity
+> and complexity of living systems. *Necessary and sufficient*---only in
+> your reductive dreams. Want more of this: see *Herding Cats---the
+> Sociology of Data Integration*, 2009: PMID: 20228863
+> https://doi.org/10.3389/neuro.01.016.2009
+
+Many of you have given talks with a hierarchy of traits. I remember a
+lovely talk that Nora Volkow gave to the Human Brain Project teams in
+about 2005---from gene variants at the bottom to variable outcome
+measures at the top---susceptible vs resistant, fast vs slow
+metabolizer, will relapse, won\'t replase. I would say we have made only
+modest progress at true holistic integration, and few biomedical
+researcher know much about causal quantitative modeling. We absolutely
+need the proteome tier to model addiction, and we need proteomes from
+dozen of brain regions and hundreds is not thousands of individuals to
+model risk and make reasonable predictions. Otherwise we are just
+flapping our hands and lips. The work by Xusheng and others shows that
+we are finally ready to come out of the proteomics \"winter\". The
+technolgy is mature; batch effect is well controlled; cost is about the
+same as Affymetrix arrays were in 2005. Several new proteomic data sets
+in GeneNetwork prove it, but only Xusheng\'s data is directly relevant
+to addiction.
+
+End of context; on with the topic at hand:
+
+One small molecule of great fame---dopamine---and its modulation,
+variation, and contribution to addiction
+
+![](media/image1.png)
+
+QUESTION: 
+
+> **What proteins related to dopamine and its many roles in behavior are
+> strongly modulated by DNA variants, and can we determine what gene
+> variants are related both to dopamine function and substance use
+> disorders. **
+>
+> The Red Hot Chili Peppers ask this question in *This is the Place.*
+>
+> \"[Can I isolate your gene? Can I kiss your
+> dopamine?](https://genius.com/Red-hot-chili-peppers-this-is-the-place-lyrics#note-1422525)
+>
+> \...
+>
+> A master piece of DNA caught in a flashing ray\"
+>
+> (The lyrics are* *on the horror of drug addiction. The lead, Anthony
+> Kiedis, has relapsed several times. The PG version of the
+> song: ***<https://www.youtube.com/watch?v=gqgm7ViA2Ag>  ***and the
+> typical RHCP shirtless version for the cool
+> kids:*** <https://www.youtube.com/watch?v=8Dkvwu3aWkY>***
+
+**Step 1. **To answer the BIG Question, we are going to review all
+genes/proteins in NCBI **Gene Reference into Function**---RIF for
+short---that are related in some way to *dopamine*. 
+
+There are two ways to do this:
+
+1\. Link
+to [***https://www.genenetwork.org***](https://www.genenetwork.org) and
+set up the **Select and search **screen to look as shown below:
+
+![](media/image2.png)
+
+Note that in the **Combined** field above, I have entered the string
+
+> **RIF=dopamine   LRS=(15 999)** 
+
+This string will retrieve all proteins in the Hybrid Rat Diversity Panel
+(the HXB/BXD family in this specific case) that are expressed reasonably
+well (just over 8,000 proteins and over 200,000 peptide fragments) in
+the whole brain.  
+
+The second part of the search string (LRS\...) finds all proteins that
+have strong linkage---a likelihood ratio statistic score of at least 15.
+This is equivalent to a LOD score of 3.3, and this is a value that is
+often close to the genome-wide significance level. The other value, 999,
+is just a high upper limit.
+
+The second way to find these proteins is a bit easier---just paste this
+URL into your browser:
+
+> [***https://genenetwork.org/search?species=rat&group=HXBBXH&type=Whole+Brain+Proteome&dataset=UND\_NIDA\_HXB-BXH\_WBPr\_log2z8\_0221&search\_terms\_or=&search\_terms\_and=RIF%3Ddopamine+LRS%3D%2815+999%29&FormID=searchResult***](https://genenetwork.org/search?species=rat&group=HXBBXH&type=Whole+Brain+Proteome&dataset=UND_NIDA_HXB-BXH_WBPr_log2z8_0221&search_terms_or=&search_terms_and=RIF%3Ddopamine+LRS%3D%2815+999%29&FormID=searchResult)
+
+(This link can be shared, and will work *in perpetuity throughout the
+known universe; *I phrase I steal from the Walt Disney Company legal
+department with trepidation.)  
+
+**Step 2**. At this point if you are following along, you should have a
+list of 115 proteins that are abundantly expressed in brain AND are
+linked to *dopamine* AND that have reasonable genetic linkage in the HXB
+family to a particular genome coordinate (usually a SNP). The **Search
+Results** table should look like the screenshot below. 
+
+![](media/image3.png)
+
+I have highlighted the row 8---the ARNTL protein---a major transcription
+factor involved in circadian rhythms that is upregulated by DRD2
+signaling (PMID: 16606840 in PNAS, 2006)
+
+**Step 3.** To begin to answer the second question---is there a major
+modulator of multiple dopamine-associated proteins---we need to re-sort
+this table using the column labeled **Peak Location**. In this
+screenshot below I have scrolled over to the right to display the **Peak
+Location** column after having performing the sort. All of these
+proteins map to Chr 1 at about 43.7 megabases (Mb).
+
+![](media/image4.png)
+
+We see ARNTL again and eight other proteins that are genetically
+downstream of one or many DNA variants located on the proximal part of
+chromosome 1 (Chr 1). The **Peak LOD** scores range between 4.1 and 7.1.
+
+If you scroll down this list (and you should), you will find another
+region of the rat genome that is highly linked with dopamine-associated
+proteins---Chr 19 at about 60 Mb. But before we head to Chr 19, let\'s
+continue to work with this proximal part of Chr 1 and try to figure out
+why the variation in expression of this band of nine proteins map to
+this part of the rat genome. Step 3 below is a long step---my
+apologysorry. Perhaps time for a coffee break.
+
+**Step 3** involves mapping one or more of these nine proteins. I will
+pick SYT7 since it has the highest expression (9 log2 units of
+expression) and the second highest LOD score (6.8).
+
+You can either click on the UNIPROT identifier---**Q62747 **in the
+window, or you can just paste this URL command into a browser:
+
+> [***https://genenetwork.org/show\_trait?trait\_id=Q62747&dataset=UND\_NIDA\_HXB-BXH\_WBPr\_log2z8\_0221***](https://genenetwork.org/show_trait?trait_id=Q62747&dataset=UND_NIDA_HXB-BXH_WBPr_log2z8_0221)
+
+If all goes well, your browser will display this content (and much more
+too):
+
+![](media/image5.png)
+
+
+Before we map SYT7 protein expression, you may be curious to know how
+this protein has been linked to dopamine. 
+
+The answer is one click away. Tap on the **GeneWiki** button,
+highlighted below in grey.
+
+![](media/image6.png)
+
+A **GeneWiki** window will open, and RIF number 18 explains the
+association with *dopamine* and also links to a 2011 paper (PMID
+21576241) on somatodendritic dopamine release and the involvement of
+synaptotagmin 7 (SYT7).\
+\
+Again we pause briefly for \"data due diligence\". In the **Statistics**
+**histogram** window you will note that the distribution of SYT7 protein
+levels in 21 strains has a hint of bimodality---that is a good thing.
+
+<img src="media/image7.png" width="300">
+
+There are no outliers, so we can map these logged protein expression
+data \"as given\" without further normalization.
+
+We can now finally proceed to the actual mapping of variation in protein
+expression---using for the first time infinite marker maps for
+chromosome of all of the HXB/BXH family, and using the
+updated GEMMA linear mixed model mapping function in GeneNetwork.
+
+Open the **Mapping Tools** window
+
+![](media/image8.png)
+
+In the screenshot above I have mapped variation in SYT7 protein level
+using the new **Genotypes file: Experimental (smoothed)**
+
+These are genotypes based on whole genome sequencing of the HXB/BXH
+family using linked-read 10X Chromium DNA libraries at a mean sequence
+coverage of just over 45X. Libraries were prepared at HudsonAlpha and
+sequenced on an Illumina Novaseq across the street from NIH at *The
+American Genome Center* (TAGC, thanks Michal, Melinda, Hao, Clifton,
+Jonathan, David, Hakan, Tristan, Victor, Jun, many others\....).
+
+The Manhattan plot of variation in SYT7 protein expression should look
+like this: 
+
+![](media/image9.png)
+
+Beneath the Manahattan plot there is a **Mapping Statistics** table that
+provides estimates a SNP coordinates (Rnor6 assembly) calculated by
+GEMMA with --logP values and additive effects (log2 scale).
+
+![](media/image10.png)
+
+A --logP value of 5.27 is good---normally at or above genome-wide
+threshold of significance. (This assertion does need more support, and
+we are testing thresholds using using other mapping methods, including
+R/qtl\'s and WebQTL\'s standard interval mapping methods, and using
+permutation tests.)
+
+**Step 4.** What is the approximate confidence interval of the SYT7
+protein expression quantitative trait locus (QTL) on Chr 1? To answer
+this question we need to sort the **Mapping Statistics** by
+the **Position** column. Once sorted, we have to decide how wide a
+confidence interval is appropriate given the density of DNA variants,
+gene density, and --logP values. Karl Broman and others recommend a drop
+in the --logP linkage statistic of about 1.5 on either side of the peak,
+or plateau in this case. For the QTL map of SYT7 the confidence interval
+encompasses an stretch of DNA from about 35 megabases (Mb) to 43 Mb.
+
+Normally, in an interval this large, we would just hit the pause button
+and spend more time increasing the sample size (in progress already by
+Xusheng Wang and colleagues). But for the sake of this Valentine\'s day
+email, I am going to forge ahead to get to the box of chocolates and
+that essential dopamine kiss in nucleus accumbens that is so rewarding.\
+\
+**Step 5**. What genes are located along this part of Chr 1? 
+
+To answer this question, click on the chromosome number, **1** in this
+case.
+
+This will generate a chromosome-specific view; part shown below.
+
+<img src="media/image11.png" width="300">
+
+The QTL peak is a \"non-recombinant\" plateau that extends from 35.5 to
+45 Mb---confirming visually what we had already determined from the
+--logP values.  The blue blocks along the top are gene \"models\" and
+the lighter blue dots are the linkage values at different SNP locations.
+You can zoom to a map with specific start- and end-coordinates. 
+
+You can keep zooming in on a specific region of a chromosome by clicking
+on the pink horizontal bar alonge the top. Here is the plateau region of
+the SYT7 protein expression QTL.
+
+![](media/image12.png)
+
+As you can tell from the screenshot, there are lots of genes---real and
+putative---that call this part of Chr 1 home.
+
+Underneath each map an **Interval Analyst** table of all genes and
+pseudogenes in a specific interval. In this case, there are about 130
+gene, of which 32+ are protein-coding. 
+
+Let me list them out throught to about 44 Mb.
+
+ADAMTS16 
+
+ICE1 
+
+MED10 
+
+UBE2QL1 
+
+NSUN2 
+
+SRD5A1 
+
+PAPD7 
+
+ADCY2 
+
+FASTKD3 
+
+MTRR 
+
+ZFP874B 
+
+ZFP748 
+
+PPP1R14C 
+
+IYD 
+
+PLEKHG1 
+
+MTHFD1L 
+
+AKAP12 
+
+ZBTB2 
+
+RMND1 
+
+ARNTL1 
+
+ESR1 
+
+SYNE1 
+
+MYCT1 
+
+VIP 
+
+CCDC170 
+
+FBXO5 
+
+MTRF1L 
+
+RGS17 
+
+OPRM1 
+
+IPCEF1 
+
+CNKSR3 
+
+Anything catch your eye? Actually, lots to catch the eye
+here---perhaps too much. 
+
+The gene/\'protein that most of you will catch is **OPRM1**---the mu
+opioid receptor. 
+
+Variants in this gene and locus are definitely controllers of morphine
+response---particularly so in the BXD mouse family (Paige Lemen, Hao
+Chen, Guy Mittleman, and Price Dickson have a strong abstract on this at
+the upcoming 2021 NIDA Genetics meeting). Also true in *Homo sapiens*
+based on initial GWAS analysis.\
+\
+**Step 6**. How do we evaluate the strength of these candidates as
+controller of some subset of the nine proteins with variable expression
+that map to this region?
+
+Simple---clip out all of those positional candidate genes and paste them
+into the search **Get Any** window of GeneNetwork. It should look like
+this:
+
+ ![](media/image13.png)
+
+About 12 of these proteins have reasonably high expression in the rat
+brain, and three of these also are associated with reasonably strong
+cis-acting modulation---FASTKD3, PPP1R14C, and MTRR. That means that DNA
+variant in or around these genes modulate both mRNA expression but much
+more importantly, also the protein level.
+
+You can review these three candidates at your leisure. 
+
+PPP1R14C (aka KEPI)---see PMID: 11812771
+
+MTRR: not much related to CNS function---mainly cancer and development
+
+FASKD3: not much CNS but key in mitochondrial function
+
+Ok, time to go out and sled.
+
+Any one that made it this far---bravo---you have persistence.
+
+Any questions about the proteomics to Xusheng Wang.
+
+Any questions about the genotypes and HXB sequence to Hao Chen.
+
+Any questions about mapping to Pjotr Prins and me.
+
+Any questions about GeneNetwork user interface to me.
+
+> [[Can I isolate your gene? Can I kiss your
+> dopamine?]{.underline}](https://genius.com/Red-hot-chili-peppers-this-is-the-place-lyrics#note-1422525)\....
+>
+> A perfect piece of DNA caught in a flashing ray
+>
+> A master piece of DNA caught in a flashing ray
+
+Thanks RHCP for thinking of us NIDA- and NIAAA-funded genetics
+researchers.
+
+\-- 
+
+Rob
+
+ps. You may want to know about OPRM1 as a great position and biological
+candidate gene---is it causal. Unfortunately expression is not
+consistently high in this proteomics analysis and we will have to look
+at bit harder to find peptide fragments for this protein. Coming soon to
+a webservice near you.
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