Mapping neuroanatomy is a foundational goal towards understanding brain function. Electron microscopy (EM) has been the gold standard for connectivity analysis because nanoscale resolution is necessary to unambiguously resolve synapses. However, molecular information that specifies cell types is often lost in EM reconstructions. To address this, we devise a light microscopy approach for connectivity analysis of defined cell types called spectral connectomics. We combine multicolor labeling (Brainbow) of neurons with multi-round immunostaining Expansion Microscopy (miriEx) to simultaneously interrogate morphology, molecular markers, and connectivity in the same brain section. We apply this strategy to directly link inhibitory neuron cell types with their morphologies. Furthermore, we show that correlative Brainbow and endogenous synaptic machinery immunostaining can define putative synaptic connections between neurons, as well as map putative inhibitory and excitatory inputs. We envision that spectral connectomics can be applied routinely in neurobiology labs to gain insights into normal and pathophysiological neuroanatomy.

10Identifying the cellular origins and mapping the dendritic and axonal arbors of neurons have 11 been century old quests to understand the heterogeneity among these brain cells. Classical 12 chemical and genetic methods take advantage of light microscopy and sparse labeling to 13 unambiguously, albeit inefficiently, trace a few neuronal lineages or reconstruct their 14 morphologies in each sampled brain. To improve the analysis throughput, we designed Bitbow, 15 a digital format of Brainbow which exponentially expands the color palette to provide tens of 16 thousands of spectrally resolved unique labels. We generated transgenic Bitbow Drosophila 17 lines, established statistical tools, and streamlined sample preparation, image processing and 18 data analysis pipelines to allow conveniently mapping neural lineages, studying neuronal 19 morphology and revealing neural network patterns with an unprecedented speed, scale and 20 resolution. 21 One way to generate more unique labels for lineage tracing is to localize the same FPs to 48 different subcellular compartments. In strategies such as CLoNe and MAGIC, Brainbow 49 cassettes targeted to cytoplasm, cell membrane, nucleus, and/or mitochondria were co-50 electroporated with transposase for genome integration, which allowed the differentiation of 51 neighboring progenies in chick and mouse embryos with fewer color collisions 26,27 . However, 52 the number of expression cassettes being integrated in each cell is random in these 53 experiments, leading to uncertainty in each color's appearance probability which complicates 54 quantitative analysis. The Raeppli strategy solves this problem by generating a transgenic 55 Drosophila which utilizes 4 FPs to create up to 4 x 4 = 16 membrane and nucleus color 56 combinations 16 . In parallel, strategies such as TIE-DYE and MultiColor FlpOut (MCFO) attempt to 57 generate more color combinations by stochastically removing the expression stops from each 58 3 FP module 15,28 . While inserting 3 different modules into 3 genomic loci allows generating up to 59 2 3 -1=7 unique labels, it is difficult to insert more modules to more genomic loci in a single 60 transgenic animal. 61 Here we present Bitbow, a digital format of Brainbow to greatly expand the unique color 62 pool from a single transgenic cassette. Unlike the original Brainbow, whose FP choices are 63 exclusive in one cassette, Bitbow allows each FP to independently express in an ON or OFF state 64 upon recombination. Color coding by each FP's binary status is similar to the information coding 65 by each bit in computer memory, thus leading to the name Bitbow. In a recent study, we 66 implemented the Bitbow1 design to target 5 spectrally distinct FPs to the nucleus for lineage 67 tracing 33 . Here, we present novel Bitbow1 flies which encode up to 32,767 unique "colors" 68 (Bitbow codes) in a single transgenic animal. This allows reliable lineage tracing without 69 complicated statistical tests 33 . To better enable morphology tracing, we generated Bitbow2, 70 which...

The Drosophila type II neuroblast lineages present an attractive model to investigate the neurogenesis and differentiation process as they adapt to a process similar to that in the human outer subventricular zone. We perform targeted single-cell mRNA sequencing in third instar larval brains to study this process of the type II NB lineage. Combining prior knowledge, in silico analyses, and in situ validation, our multi-informatic investigation describes the molecular landscape from a single developmental snapshot. 17 markers are identified to differentiate distinct maturation stages. 30 markers are identified to specify the stem cell origin and/or cell division numbers of INPs, and at least 12 neuronal subtypes are identified. To foster future discoveries, we provide annotated tables of pairwise gene-gene correlation in single cells and MiCV, a web tool for interactively analyzing scRNA-seq datasets. Taken together, these resources advance our understanding of the neural differentiation process at the molecular level.

Chronic lymphocytic leukemia (CLL) occurs in 2 major forms: aggressive and indolent. Low miR-29b expression in aggressive CLL is associated with poor prognosis. Indiscriminate miR-29b overexpression in the B-lineage of mice causes aberrance, thus warranting the need for selective introduction of miR-29b into B-CLL cells for therapeutic benefit. The oncofetal antigen receptor tyrosine kinase orphan receptor 1 (ROR1) is expressed on malignant B-CLL cells, but not normal B cells, encouraging us with ROR1-targeted delivery for therapeutic miRs. Here, we describe targeted delivery of miR-29b to ROR1+ CLL cells leading to downregulation of DNMT1 and DNMT3A, modulation of global DNA methylation, decreased SP1, and increased p21 expression in cell lines and primary CLL cells in vitro. Furthermore, using an Eμ-TCL1 mouse model expressing human ROR1, we report the therapeutic benefit of enhanced survival via cellular reprograming by downregulation of DNMT1 and DNMT3A in vivo. Gene expression profiling of engrafted murine leukemia identified reprogramming of cell cycle regulators with decreased SP1 and increased p21 expression after targeted miR-29b treatment. This finding was confirmed by protein modulation, leading to cell cycle arrest and survival benefit in vivo. Importantly, SP1 knockdown results in p21-dependent compensation of the miR-29b effect on cell cycle arrest. These studies form a basis for leukemic cell–targeted delivery of miR-29b as a promising therapeutic approach for CLL and other ROR1+ B-cell malignancies.

Direct cDNA preamplification protocols developed for single-cell RNA-seq have enabled transcriptome profiling of precious clinical samples and rare cells without sample pooling or RNA extraction. Currently, there is no algorithm optimized to reveal and remove noisy transcripts in limiting-cell RNA-seq (lcRNA-seq) data for downstream analyses. Herein, we present CLEAR, a workflow that identifies reliably quantifiable transcripts in lcRNA-seq data for differentially expressed gene (DEG) analysis. Libraries at three input amounts of FACS-derived CD5+ and CD5-cells from a chronic lymphocytic leukemia patient were used to develop CLEAR. When using CLEAR transcripts vs. using all transcripts, downstream analyses revealed more shared transcripts across different input RNA amounts, improved Principal Component Analysis (PCA) separation, and yielded more DEGs between cell types. As proof-of-principle, CLEAR was applied to an in-house lcRNA-seq dataset and two public datasets. When imputation is used, CLEAR is also adaptable to large clinical studies and for single cell analyses. AUTHOR CONTRIBUTIONSConceived and designed the experiments: L.A.