Biology subjects

Collier, P. G.

Publications and source records attributed to Collier, P. G..

4 recordsLinked to original sources

bioRxiv2023

Pronounced early differentiation underlies zebra finch gonadal germ cell development.

The diversity of germ cell developmental strategies has been well documented across many vertebrate clades. However, much of our understanding of avian primordial germ cell (PGC) specification and differentiation has derived from only one species, the chicken (Gallus gallus). Of the three major classes of birds, chickens belong to Galloanserae, representing less than 4% of species, while nearly 95% of extant bird species belong to Neoaves. This represents a significant gap in our knowledge of germ cell development across avian species, hampering efforts to adapt genome editing and reproductive technologies developed in chicken to other birds. We therefore applied single-cell RNA sequencing to investigate inter-species differences in germ cell development between chicken and zebra finch (Taeniopygia castanotis), a Neoaves songbird species and a common model of vocal learning. Analysis of early embryonic male and female gonads revealed the presence of two distinct early germ cell types in zebra finch and only one in chicken. Both germ cell types expressed zebra finch Germline Restricted Chromosome (GRC) genes, present only in songbirds among birds. One of the zebra finch germ cell types expressed the canonical PGC markers, as did chicken, but with expression differences in several signaling pathways and biological processes. The second zebra finch germ cell cluster was marked by proliferation and fate determination markers, indicating beginning of differentiation. Notably, these two zebra finch germ cell populations were present in both male and female zebra finch gonads as early as HH25. Using additional chicken developmental stages, similar germ cell heterogeneity was identified in the more developed gonads of females, but not males. Overall, our study demonstrates a substantial heterochrony in zebra finch germ cell development compared to chicken, indicating a richer diversity of avian germ cell developmental strategies than previously known.

cell biology↗

bioRxiv2021

Single-nuclei isoform RNA sequencing reveals combination patterns of transcript elements across human brain cell types

Single-nuclei RNA-Seq is being widely employed to investigate cell types, especially of human brain and other frozen samples. In contrast to single-cell approaches, however, the majority of single-nuclei RNA counts originate from partially processed RNA leading to intronic cDNAs, thus hindering the investigation of complete isoforms. Here, using microfluidics, PCR-based artifact removal, target enrichment, and long-read sequencing, we developed single-nuclei isoform RNA-sequencing ( SnISOr-Seq), and applied it to the analysis of human adult frontal cortex samples. We found that exons associated with autism exhibit coordinated and more cell-type specific inclusion than exons associated with schizophrenia or ALS. We discovered two distinct modes of combination patterns: first, those distinguishing cell types in the human brain. These are enriched in combinations of TSS-exon, exon-polyA site, and distant (non-adjacent) exon pairs. Second, those with all isoform combinations found within one neural cell type, which are enriched in adjacent exon pairs. Furthermore, adjacent exon pairs are predominantly mutually associated, while distant pairs are frequently mutually exclusive. Finally, we observed that human-specific exons are as tightly coordinated as conserved exons, pointing to an efficient evolutionary mechanism underpinning coordination. SnISOr-Seq opens the door to single-nuclei long-read isoform analysis in the human brain, and in any frozen, archived or hard-to-dissociate sample.

genomics↗

bioRxiv2021

Extensive OMICS resource for Sf21 and Tni cell lines

Insect-derived cell lines, from Spodoptera frugiperda (Sf21) and from Trichoplusia ni (Tni), are the two most widely used cell lines for recombinant protein expression in combination with the Baculoviral Expression Vector System (BEVS). Genomic sequences and annotations are still incomplete for Sf21 and absent for Tni. In this study, we present an approach using different sequencing data types, including short-read sequencing, long synthetic and Oxford Nanopore reads, to build genomes. The Sf21 and Tni assemblies contain 4,020 scaffolds of 463 Mb in size with N50 of 364 Kb and 2,954 scaffolds of 332 Mb in size with N50 of 326 Kb, respectively. Furthermore, we built a new gene prediction workflow, which integrates transcriptome and proteome information using pre-existing tools. Using this approach, we predicted 21,506 Sf21 and 14,159 Tni genes, generated and integrated proteomic datasets to validate predicted genes and could identify 5577 and 4919 proteins in the Sf21 and Tni cell lines respectively. This integrative approach could be theoretically applied to any uncharacterized genome and result in valuable new resources. With this information available, Sf21 and Tni cells will become even better tools for protein expression and could be used in a wider range of applications, from promoter identification to genome engineering and editing.

genomics↗

bioRxiv2018

Single-cell isoform RNA sequencing (ScISOr-Seq) across thousands of cells reveals isoforms of cerebellar cell types.

Full-length isoform sequencing has advanced our knowledge of isoform biology1-11. However, apart from applying full-length isoform sequencing to very few single cells12,13, isoform sequencing has been limited to bulk tissue, cell lines, or sorted cells. Single splicing events have been described for <=200 single cells with great statistical success14,15, but these methods do not describe full-length mRNAs. Single cell short-read 3 sequencing has allowed identification of many cell sub-types16-23, but full-length isoforms for these cell types have not been profiled. Using our new method of single-cell-isoform-RNA-sequencing (ScISOr-Seq) we determine isoform-expression in thousands of individual cells from a heterogeneous bulk tissue (cerebellum), without specific antibody-fluorescence activated cell sorting. We elucidate isoform usage in high-level cell types such as neurons, astrocytes and microglia and finer sub-types, such as Purkinje cells and Granule cells, including the combination patterns of distant splice sites6-9,24,25, which for individual molecules requires long reads. We produce an enhanced genome annotation revealing cell-type specific expression of known and 16,872 novel (with respect to mouse Gencode version 10) isoforms (see isoformatlas.com).\n\nScISOr-Seq describes isoforms from >1,000 single cells from bulk tissue without cell sorting by leveraging two technologies in three steps: In step one, we employ microfluidics to produce amplified full-length cDNAs barcoded for their cell of origin. This cDNA is split into two pools: one pool for 3 sequencing to measure gene expression (step 2) and another pool for long-read sequencing and isoform expression (step 3). In step two, short-read 3-sequencing provides molecular counts for each gene and cell, which allows clustering cells and assigning a cell type using cell-type specific markers. In step three, an aliquot of the same cDNAs (each barcoded for the individual cell of origin) is sequenced using Pacific Biosciences (\"PacBio\")1,2,4,5,26 or Oxford Nanopore3. Since these long reads carry the single-cell barcodes identified in step two, one can determine the individual cell from which each long read originates. Since most single cells are assigned to a named cluster, we can also assign the cells cluster name (e.g. \"Purkinje cell\" or \"astrocyte\") to the long read in question (Fig 1A) - without losing the cell of origin of each long read.\n\nO_FIG O_LINKSMALLFIG WIDTH=180 HEIGHT=200 SRC=\"FIGDIR/small/364950_fig1.gif\" ALT=\"Figure 1\">\nView larger version (66K):\norg.highwire.dtl.DTLVardef@4df0cdorg.highwire.dtl.DTLVardef@fc4beborg.highwire.dtl.DTLVardef@1dc485forg.highwire.dtl.DTLVardef@1138a3e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1:C_FLOATNO (A) Outline of our ScISOr-Seq approach. (B) TSNE-plot depicting cell clusters, marker genes and names given to clusters, including: Bergman glia (BG), External granule cell layer neurons (EGL), Internal granule cell layer and other neurons in the interior of the cerebellum (IGL), two clusters of Purkinje cell layer neurons (PCL), oligodendrocyte progenitor cells (OPCs), Atoh1+ neuronal progenitors, Ptf1a+ neuronal progenitors and other neuronal progenitors (NPCs) (C) In-situ hybridization images from the Allen Brain Atlas depicting expression of marker genes in specific layers. (D) Expression patterns of selected marker genes across cell types.\n\nC_FIG

molecular biology↗