Biology subjects

Gingeras, T. R.

Publications and source records attributed to Gingeras, T. R..

8 recordsLinked to original sources

bioRxiv2024

MaizeCODE reveals bi-directionally expressed enhancers that harbor molecular signatures of maize domestication.

Modern maize was domesticated from Teosinte parviglumis, with subsequent introgressions from Teosinte mexicana, yielding increased kernel row number, loss of the hard fruit case and dissociation from the cob upon maturity, as well as fewer tillers. Molecular approaches have identified several transcription factors involved in the development of these traits, yet revealed that a complex regulatory network is at play. MaizeCODE deploys ENCODE strategies to catalog regulatory regions in the maize genome, generating histone modification and transcription factor ChIP-seq in parallel with transcriptomics datasets in 5 tissues of 3 inbred lines which span the phenotypic diversity of maize, as well as the teosinte inbred TIL11. Integrated analysis of these datasets resulted in the identification of a comprehensive set of regulatory regions in each inbred, and notably of distal enhancers which were differentiated from gene bodies by their lack of H3K4me1. Many of these distal enhancers expressed non- coding enhancer RNAs bi-directionally, reminiscent of "super enhancers" in animal genomes. We show that pollen grains are the most differentiated tissue at the transcriptomic level, and share features with endosperm that may be related to McClintocks chromosome breakage- fusion-bridge cycle. Conversely, ears have the least conservation between maize and teosinte, both in gene expression and within regulatory regions, reflecting conspicuous morphological differences selected during domestication. The identification of molecular signatures of domestication in transcriptional regulatory regions provides a framework for directed breeding strategies in maize.

plant biology↗

bioRxiv2021

Ground tissue circuitry regulates organ complexity in cereal roots

Most plant roots have multiple cortex layers that make up the bulk of the organ and play key roles in physiology, such as flood tolerance and symbiosis. However, little is known about the formation of cortical layers outside of the highly reduced anatomy of the model Arabidopsis. Here we use single-cell RNAseq to rapidly generate a cell resolution map of the maize root, revealing an alternative configuration of the tissue formative SHORT-ROOT (SHR) signaling pathway adjacent to an expanded cortex. We show that maize SHR protein is hypermobile, moving at least eight cell layers into the cortex. Higher-order SHR mutants in both maize and Setaria have reduced numbers of cortical layers, showing that the SHR pathway controls expansion of cortical tissue in grasses that sets up anatomical complexity and a host of key traits. One sentence summarySingle-cell RNA-seq maps the maize root transcriptome uncovering a mechanism that regulates cortex layer number.

genomics↗

bioRxiv2021

Pan-genome Analysis in Sorghum Highlights the Extent of Genomic Variation and Sugarcane Aphid Resistance Genes

Sorghum bicolor, one of the most important grass crops around the world, harbors a high degree of genetic diversity. We constructed chromosome-level genome assemblies for two important sorghum inbred lines, Tx2783 and RTx436. The final high-quality reference assemblies consist of 19 and 18 scaffolds, respectively, with contig N50 values of 25.6 and 20.3 Mb. Genes were annotated using evidence-based and de novo gene predictors, and RAMPAGE data demonstrate that transcription start sites were effectively captured. Together with other public sorghum genomes, BTx623, RTx430, and Rio, extensive structural variations (SVs) of various sizes were characterized using Tx2783 as a reference. Genome-wide scanning for disease resistance (R) genes revealed high levels of diversity among these five sorghum accessions. To characterize sugarcane aphid (SCA) resistance in Tx2783, we mapped the resistance region on chromosome 6 using a recombinant inbred line (RIL) population and found a SV of 191 kb containing a cluster of R genes in Tx2783. Using Tx2783 as a backbone, along with the SVs, we constructed a pan-genome to support alignment of resequencing data from 62 sorghum accessions, and then identified core and dispensable genes using this population. This study provides the first overview of the extent of genomic structural variations and R genes in the sorghum population, and reveals potential targets for breeding of SCA resistance.

genomics↗

bioRxiv2019

A limited set of transcriptional programs define major histological types and provide the molecular basis for a cellular taxonomy of the human body

We have produced RNA sequencing data for a number of primary cells from different locations in the human body. The clustering of these primary cells reveals that most cells in the human body share a few broad transcriptional programs, which define five major cell types: epithelial, endothelial, mesenchymal, neural and blood cells. These act as basic components of many tissues and organs. Based on gene expression, these cell types redefine the basic histological types by which tissues have been traditionally classified. We identified genes whose expression is specific to these cell types, and from these genes, we estimated the contribution of the major cell types to the composition of human tissues. We found this cellular composition to be a characteristic signature of tissues, and to reflect tissue morphological heterogeneity and histology. We identified changes in cellular composition in different tissues associated with age and sex and found that departures from the normal cellular composition correlate with histological phenotypes associated to disease. One Sentence SummaryA few broad transcriptional programs define the major cell types underlying the histology of human tissues and organs.

genomics↗

bioRxiv2018

Dynamics of microRNA expression during mouse prenatal development

MicroRNAs (miRNAs) play a critical role as post-transcriptional regulators of gene expression. The ENCODE project profiled the expression of miRNAs in a comprehensive set of tissues during a time-course of mouse embryonic development and captured the expression dynamics of 785 miRNAs. We found distinct tissue and developmental stage specific miRNA expression clusters, with an overall pattern of increasing tissue specific expression as development proceeds. Comparative analysis of conserved miRNAs in mouse and human revealed stronger clustering of expression patterns by tissue types rather than by species. An analysis of messenger RNA gene expression clusters compared with miRNA expression clusters identifies the potential role of specific miRNA expression clusters in suppressing the expression of mRNAs specific to other developmental programs in the tissue where these microRNAs are expressed during embryonic development. Our results provide the most comprehensive timecourse of miRNA expression as an integrated part of the ENCODE reference dataset for mouse embryonic development.

genomics↗

bioRxiv2017

The fractured landscape of RNA-seq alignment: The default in our STARs

Many tools are available for RNA-seq alignment and expression quantification, with comparative value being hard to establish. Benchmarking assessments often highlight methods good performance, but are focused on either model data or fail to explain variation in performance. This leaves us to ask, what is the most meaningful way to assess different alignment choices? And importantly, where is there room for progress? In this work, we explore the answers to these two questions by performing an exhaustive assessment of the STAR aligner. We assess STARs performance across a range of alignment parameters using common metrics, and then on biologically focused tasks. We find technical metrics such as fraction mapping or expression profile correlation to be uninformative, capturing properties unlikely to have any role in biological discovery. Surprisingly, we find that changes in alignment parameters within a wide range have little impact on both technical and biological performance. Yet, when performance finally does break, it happens in difficult regions, such as X-Y paralogs and MHC genes. We believe improved reporting by developers will help establish where results are likely to be robust or fragile, providing a better baseline to establish where methodological progress can still occur.

bioinformatics↗

bioRxiv2017

Conserved noncoding transcription and core promoter regulatory code in early Drosophila development

Multicellular development is largely determined by transcriptional regulatory programs that orchestrate the expression of thousands of protein-coding and noncoding genes. To decipher the genomic regulatory code that specifies these programs, and to investigate globally the developmental relevance of noncoding transcription, we profiled genome-wide promoter activity throughout embryonic development in 5 Drosophila species. We show that core promoters, generally not thought to play a significant regulatory role, in fact impart broad restrictions on the developmental timing of gene expression on a genome-wide scale. We propose a hierarchical model of transcriptional regulation during development in which core promoters define broad windows of opportunity for expression, by defining a limited range of transcription factors from which they are able to receive regulatory inputs. This two-tiered mechanism globally orchestrates developmental gene expression, including noncoding transcription on a scale that defies our current understanding of ontogenesis. Indeed, noncoding transcripts are far more prevalent than ever reported before, with [~]4,000 long noncoding RNAs expressed during embryogenesis. Over 1,500 are functionally conserved throughout the melanogaster subgroup, and hundreds are under strong purifying selection. Overall, this work introduces a hierarchical model for the developmental regulation of transcription, and reveals the central role of noncoding transcription in animal development.

genetics↗

bioRxiv2017

High-throughput annotation of full-length long noncoding RNAs with Capture Long-Read Sequencing (CLS)

Accurate annotations of genes and their transcripts is a foundation of genomics, but no annotation technique presently combines throughput and accuracy. As a result, reference gene collections remain incomplete: many gene models are fragmentary, while thousands more remain uncatalogued-particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), combining targeted RNA capture with third-generation long-read sequencing. We present an experimental re-annotation of the GENCODE intergenic lncRNA population in matched human and mouse tissues, resulting in novel transcript models for 3574 / 561 gene loci, respectively. CLS approximately doubles the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enable us to definitively characterize the genomic features of lncRNAs, including promoter- and gene-structure, and protein-coding potential. Thus CLS removes a longstanding bottleneck of transcriptome annotation, generating manual-quality full-length transcript models at high-throughput scales.\n\nAbbreviations

genomics↗