Functional organization of the maternal and paternal human 4D Nucleome

Abstract

Summary Every human somatic cell inherits a maternal and a paternal genome, which work together to give rise to cellular phenotypes. However, the allele-specific relationship between gene expression and genome structure through the cell cycle is largely unknown. By integrating haplotype-resolved genome-wide chromosome conformation capture, mature and nascent mRNA, and protein binding data from a B lymphoblastoid cell line, we investigate this relationship both globally and locally. We introduce the maternal and paternal 4D Nucleome, enabling detailed analysis of the mechanisms and dynamics of genome structure and gene function for diploid organisms. Our analyses find significant coordination between allelic expression biases and local genome conformation, and notably absent expression bias in universally essential cell cycle and glycolysis genes. We propose a model in which coordinated biallelic expression reflects prioritized preservation of essential gene sets.

Identification of Microproteins in Hep3B Cells at Different Cell Cycle Stages

“…As a result, a total of 657 microproteins were identified, including 369 from bottom-up and 323 from top-down (Table S1). Recent work by Lindsly et al identified genes with cell cycle-biased expression (CBE), including 229 CBE genes from RNA-seq and 164 from Bru-seq . By association analysis between identified microproteins in this work and the 4D-nucleome data of the cell cycle, seven microproteins in our data can find CBE evidence on a transcriptional level.…”

TP53-inducible putative long noncoding RNAs encode functional polypeptides that suppress cell proliferation

“…Of the differentially expressed genes we detected, some may be directly regulated by TP53LC04; the others may be indirectly caused by the TP53LC04-related cell phenotype, which remains for further study. Recently, Lindsly et al (2021) had reported 229 genes with cell-cycle-biased expression (CBE) from the cell-cycle-sorted cells for RNA-seq. By integrative analysis, we also identified five differentially expressed genes in our data that could be found in the CBE evidence at a transcriptional level.…”

Genomic Imprinting in the New Omics Era: A Model for Systems-Level Approaches

“…All this highlights the great interest of studying how GI may influence phenotypes across mammals. Some strategies are emerging to identify the impact of very subtle changes related to GI on intermediate molecular phenotypes ( Greenwald et al, 2019 ; Lindsly et al, 2021 ). At a higher phenotypic level, we know from familial and association studies that GI contributes to complex phenotypes, including syndromic disorders ( Eggermann et al, 2021 ), cancer ( Goovaerts et al, 2018 ) and several other developmental phenotypes in both humans ( Workalemahu et al, 2020 ) and other mammals ( Freking et al, 2002 ; Van Laere et al, 2003 ).…”

“…In particular, High-throughput 3C (Hi-C) showed the enrichment for imprinted genes in chromatin loops ( Greenwald et al, 2019 ). Current efforts lay the foundation for identifying differences in 3D structure between maternal and paternal alleles in imprinted clusters ( Tan et al, 2018 ; Lindsly et al, 2021 ). In addition, chromatin accessibility analyses like Assay for Transposase-Accessible Chromatin with high-throughput Sequencing (ATAC-Seq) or Chromatin Overall Omic-scale Landscape Sequencing (COOL-Seq) make it possible to test the existence of such a parental asymmetry at a lower level of chromatin organization ( Wu et al, 2016 ; Gu et al, 2019 ).…”