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Ramp sequences increase translational speed and accuracy when rare, slowly-translated codons are found at the beginnings of genes. Here, the results of the first analysis of ramp sequences in a phylogenetic construct are presented. Ramp sequences were compared from 247 vertebrates (114 Mammalian and 133 non-mammalian), where the presence and absence of ramp sequences was analyzed as a binary character in a parsimony and maximum likelihood framework. Additionally, ramp sequences were mapped to the Open Tree of Life synthetic tree to determine the number of parallelisms and reversals that occurred, and those results were compared to random permutations. Parsimony and maximum likelihood analyses of the presence and absence of ramp sequences recovered phylogenies that are highly congruent with established phylogenies. Additionally, 81% of vertebrate mammalian ramps and 81.2% of other vertebrate ramps had less parallelisms and reversals than the mean from 1000 randomly permuted trees. A chi-square analysis of completely orthologous ramp sequences resulted in a p-value < 0.001 as compared to random chance. Ramp sequences recover comparable phylogenies as other phylogenomic methods. Although not all ramp sequences appear to have a phylogenetic signal, more ramp sequences track speciation than expected by random chance. Therefore, ramp sequences may be used in conjunction with other phylogenomic approaches if many orthologs are taken into account. However, phylogenomic methods utilizing few orthologs should be cautious in incorporating ramp sequences because individual ramp sequences may provide conflicting signals.

A recent genome-wide association study (GWAS) of 59 cerebrospinal fluid (CSF) proteins with a connection to Alzheimer's disease (AD) demonstrated an association between increased levels of chemokine ligand 2 (CCL2) with an atypical chemokine receptor chemokine-binding protein 2 variant V41A (ACKR2-V41A; rs2228467). High levels of CCL2 are associated with increased risk of AD development as well as other inflammatory diseases. In this study we characterized the biological function of the ACKR2-V41A receptor compared to the wild type allele by measuring its ligand binding affinity, CCL2 scavenging efficiency, and cell activation sensitivity. We transfected Chinese hamster ovary cells with plasmids carrying wild type ACKR2 (ACKR2-WT) or the mutant ACKR2-V41A receptor. Binding affinity assays showed that ACKR2-V41A has a lower binding affinity for CCL2 and CCL4 than ACKR2-WT. CCL2 scavenging results aligned with binding affinity assays, with ACKR2-V41A cells scavenging CCL2 with a lower efficiency than ACKR2-WT. Cell activation assays also showed that ACKR2-V41A cells had significantly lower receptor upregulation (β-Arrestin-dependent signaling pathway) upon stimulation compared to ACKR2-WT cells. These findings provide molecular and biological mechanistic insights into the GWAS association of ACKR2-V41A with increased levels of CCL2 in CSF and possibly other chemokine ligands. Increased CCL2 levels are associated with accelerated cognitive decline and increased risk of AD. Understanding how this atypical chemokine receptor allele increases serum markers of inflammation could lead to novel therapeutic solutions for AD.

Genome-wide association studies of 146 plasma protein levels in 818 individuals revealed 56 genome-wide significant associations (28 novel) with 47 analytes. Loci associated with plasma levels of 39 proteins tested have been previously associated with various complex traits such as heart disease, inflammatory bowel disease, Type 2 diabetes and multiple sclerosis. These data suggest that these plasma protein levels may constitute informative endophenotypes for these complex traits. We found three potential pleiotropic genes: ABO for plasma SELE and ACE levels, FUT2 for CA19-9 and CEA plasma levels and APOE for ApoE and CRP levels. We also found multiple independent signals in loci associated with plasma levels of ApoH, CA19-9, FetuinA, IL6r and LPa. Our study highlights the power of biological traits for genetic studies to identify genetic variants influencing clinically relevant traits, potential pleiotropic effects and complex disease associations in the same locus., (© 2016. The Author(s).)

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD). These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case-control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer's disease in seven independent case-control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer's disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer's disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer's disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.