Probes for KIT

Hedgehog-interacting protein (HHIP) sequesters Hedgehog ligands to repress Smoothened (SMO)-mediated recruitment of the GLI family of transcription factors. Allelic variation in HHIP confers risk of chronic obstructive pulmonary disease and other smoking-related lung diseases, but underlying mechanisms are unclear. Using single-cell and cell-type-specific translational profiling, we show that HHIP expression is highly enriched in medial habenula (MHb) neurons, particularly MHb cholinergic neurons that regulate aversive behavioral responses to nicotine. HHIP deficiency dysregulated the expression of genes involved in cholinergic signaling in the MHb and disrupted the function of nicotinic acetylcholine receptors (nAChRs) through a PTCH-1/cholesterol-dependent mechanism. Further, CRISPR/Cas9-mediated genomic cleavage of the <i>Hhip</i> gene in MHb neurons enhanced the motivational properties of nicotine in mice. These findings suggest that HHIP influences vulnerability to smoking-related lung diseases in part by regulating the actions of nicotine on habenular aversion circuits.

GenoLab M is a recently developed next-generation sequencing (NGS) platform from GeneMind Biosciences. To establish the performance of GenoLab M, we present the first report to benchmark and compare the WGS and WES sequencing data of the GenoLab M sequencer to NovaSeq 6000 and NextSeq 550 platform in various types of analysis. For WGS, thirty-fold sequencing from Illumina NovaSeq platform and processed by GATK pipeline is currently considered as the golden standard. Thus this dataset is generated as a benchmark reference in this study.GenoLab M showed an average of 94.62% of Q20 percentage for base quality, while the NovaSeq was slightly higher at 96.97%. However, GenoLab M outperformed NovaSeq or NextSeq at a duplication rate, suggesting more usable data after deduplication. For WGS short variant calling, GenoLab M showed significant accuracy improvement over the same depth dataset from NovaSeq, and reached similar accuracy to NovaSeq 33X dataset with 22x depth. For 100X WES, the F-score and Precision in GenoLab M were higher than NovaSeq or NextSeq, especially for InDel calling.GenoLab M is a promising NGS platform for high-performance WGS and WES applications. For WGS, 22X depth in the GenoLab M sequencing platform offers a cost-effective alternative to the current mainstream 33X depth on Illumina.

Mammals are frequently exposed to various environmental stimuli, and to determine whether to approach or avoid these stimuli, the brain must assign emotional valence to them. Therefore, it is crucial to investigate the neural circuitry mechanisms involved in the mammalian brain's processing of emotional valence. Although the central amygdala (CeA) and the ventral tegmental area (VTA) individually encode different or even opposing emotional valences, it is unclear whether there are common upstream input neurons that innervate and control both these regions, and it is interesting to know what emotional valences of these common upstream neurons. In this study, we identify three major brain regions containing neurons that project to both the CeA and the VTA, including the posterior bed nucleus of the stria terminalis (pBNST), the pedunculopontine tegmental nucleus (PPTg), and the anterior part of the basomedial amygdala (BMA). We discover that these neural populations encode distinct emotional valences. Activating neurons in the pBNST produces positive valence, enabling mice to overcome their innate avoidance behavior. Conversely, activating neurons in the PPTg produces negative valence and induces anxiety-like behaviors in mice. Neuronal activity in the BMA, on the other hand, does not influence valence processing. Thus, our study has discovered three neural populations that project to both the CeA and the VTA and has revealed the distinct emotional valences these populations encode. These results provide new insights into the neurological mechanisms involved in emotional regulation.

Human middle temporal gyrus (MTG) is a vulnerable brain region in early Alzheimer's disease (AD), but little is known about the molecular mechanisms underlying this regional vulnerability. Here we utilize the 10 × Visium platform to define the spatial transcriptomic profile in both AD and control (CT) MTG. We identify unique marker genes for cortical layers and the white matter, and layer-specific differentially expressed genes (DEGs) in human AD compared to CT. Deconvolution of the Visium spots showcases the significant difference in particular cell types among cortical layers and the white matter. Gene co-expression analyses reveal eight gene modules, four of which have significantly altered co-expression patterns in the presence of AD pathology. The co-expression patterns of hub genes and enriched pathways in the presence of AD pathology indicate an important role of cell-cell-communications among microglia, oligodendrocytes, astrocytes, and neurons, which may contribute to the cellular and regional vulnerability in early AD. Using single-molecule fluorescent in situ hybridization, we validated the cell-type-specific expression of three novel DEGs (e.g., KIF5A, PAQR6, and SLC1A3) and eleven previously reported DEGs associated with AD pathology (i.e., amyloid beta plaques and intraneuronal neurofibrillary tangles or neuropil threads) at the single cell level. Our results may contribute to the understanding of the complex architecture and neuronal and glial response to AD pathology of this vulnerable brain region.