scholarly journals Massively multiplex single-molecule oligonucleosome footprinting

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Nour J Abdulhay ◽  
Colin P McNally ◽  
Laura J Hsieh ◽  
Sivakanthan Kasinathan ◽  
Aidan Keith ◽  
...  

Our understanding of the beads-on-a-string arrangement of nucleosomes has been built largely on high-resolution sequence-agnostic imaging methods and sequence-resolved bulk biochemical techniques. To bridge the divide between these approaches, we present the single-molecule adenine methylated oligonucleosome sequencing assay (SAMOSA). SAMOSA is a high-throughput single-molecule sequencing method that combines adenine methyltransferase footprinting and single-molecule real-time DNA sequencing to natively and nondestructively measure nucleosome positions on individual chromatin fibres. SAMOSA data allows unbiased classification of single-molecular 'states' of nucleosome occupancy on individual chromatin fibres. We leverage this to estimate nucleosome regularity and spacing on single chromatin fibres genome-wide, at predicted transcription factor binding motifs, and across human epigenomic domains. Our analyses suggest that chromatin is comprised of both regular and irregular single-molecular oligonucleosome patterns that differ subtly in their relative abundance across epigenomic domains. This irregularity is particularly striking in constitutive heterochromatin, which has typically been viewed as a conformationally static entity. Our proof-of-concept study provides a powerful new methodology for studying nucleosome organization at a previously intractable resolution and offers up new avenues for modeling and visualizing higher order chromatin structure.

Author(s):  
Nour J Abdulhay ◽  
Colin P McNally ◽  
Laura J Hsieh ◽  
Sivakanthan Kasinathan ◽  
Aidan Keith ◽  
...  

ABSTRACTOur understanding of the beads-on-a-string arrangement of nucleosomes has been built largely on high-resolution sequence-agnostic imaging methods and sequence-resolved bulk biochemical techniques. To bridge the divide between these approaches, we present the single-molecule adenine methylated oligonucleosome sequencing assay (SAMOSA). SAMOSA is a high-throughput single-molecule sequencing method that combines adenine methyltransferase footprinting and single-molecule real-time DNA sequencing to natively and nondestructively measure nucleosome positions on individual chromatin fibres. SAMOSA data allows unbiased classification of single-molecular ‘states’ of nucleosome occupancy on individual chromatin fibres. We leverage this to estimate nucleosome regularity and spacing on single chromatin fibres genome-wide, at predicted transcription factor binding motifs, and across both active and silent human epigenomic domains. Our analyses suggest that chromatin is comprised of a diverse array of both regular and irregular single-molecular oligonucleosome patterns that differ subtly in their relative abundance across epigenomic domains. This irregularity is particularly striking in constitutive heterochromatin, which has typically been viewed as a conformationally static entity. Our proof-of-concept study provides a powerful new methodology for studying nucleosome organization at a previously intractable resolution, and offers up new avenues for modeling and visualizing higher-order chromatin structure.1-sentence summaryHigh-throughput single-molecule real-time footprinting of chromatin arrays reveals heterogeneous patterns of oligonucleosome occupancy.


2016 ◽  
Author(s):  
Diego D. Cambuy ◽  
Felipe H. Coutinho ◽  
Bas E. Dutilh

AbstractIn modern-day metagenomics, there is an increasing need for robust taxonomic annotation of long DNA sequences from unknown micro-organisms. Long metagenomic sequences may be derived from assembly of short-read metagenomes, or from long-read single molecule sequencing. Here we introduce CAT, a pipeline for robust taxonomic classification of long DNA sequences. We show that CAT correctly classifies contigs at different taxonomic levels, even in simulated metagenomic datasets that are very distantly related from the sequences in the database. CAT is implemented in Python and the required scripts can be freely downloaded from Github.


2016 ◽  
Author(s):  
Amit Gur ◽  
Edward Buckler ◽  
Joseph Burger ◽  
Yaakov Tadmor ◽  
Iftach Klapp

Project objectives: 1) Characterization of variation for yield heterosis in melon using Half-Diallele (HDA) design. 2) Development and implementation of image-based yield phenotyping in melon. 3) Characterization of genetic, epigenetic and transcriptional variation across 25 founder lines and selected hybrids. The epigentic part of this objective was modified during the course of the project: instead of characterization of chromatin structure in a single melon line through genome-wide mapping of nucleosomes using MNase-seq approach, we took advantage of rapid advancements in single-molecule sequencing and shifted the focus to Nanoporelong-read sequencing of all 25 founder lines. This analysis provides invaluable information on genome-wide structural variation across our diversity 4) Integrated analyses and development of prediction models Agricultural heterosis relates to hybrids that outperform their inbred parents for yield. First generation (F1) hybrids are produced in many crop species and it is estimated that heterosis increases yield by 15-30% globally. Melon (Cucumismelo) is an economically important species of The Cucurbitaceae family and is among the most important fleshy fruits for fresh consumption Worldwide. The major goal of this project was to explore the patterns and magnitude of yield heterosis in melon and link it to whole genome sequence variation. A core subset of 25 diverse lines was selected from the Newe-Yaar melon diversity panel for whole-genome re-sequencing (WGS) and test-crosses, to produce structured half-diallele design of 300 F1 hybrids (MelHDA25). Yield variation was measured in replicated yield trials at the whole-plant and at the rootstock levels (through a common-scion grafted experiments), across the F1s and parental lines. As part of this project we also developed an algorithmic pipeline for detection and yield estimation of melons from aerial-images, towards future implementation of such high throughput, cost-effective method for remote yield evaluation in open-field melons. We found extensive, highly heritable root-derived yield variation across the diallele population that was characterized by prominent best-parent heterosis (BPH), where hybrids rootstocks outperformed their parents by 38% and 56 % under optimal irrigation and drought- stress, respectively. Through integration of the genotypic data (~4,000,000 SNPs) and yield analyses we show that root-derived hybrids yield is independent of parental genetic distance. However, we mapped novel root-derived yield QTLs through genome-wide association (GWA) analysis and a multi-QTLs model explained more than 45% of the hybrids yield variation, providing a potential route for marker-assisted hybrid rootstock breeding. Four selected hybrid rootstocks are further studied under multiple scion varieties and their validated positive effect on yield performance is now leading to ongoing evaluation of their commercial potential. On the genomic level, this project resulted in 3 layers of data: 1) whole-genome short-read Illumina sequencing (30X) of the 25 founder lines provided us with 25 genome alignments and high-density melon HapMap that is already shown to be an effective resource for QTL annotation and candidate gene analysis in melon. 2) fast advancements in long-read single-molecule sequencing allowed us to shift focus towards this technology and generate ~50X Nanoporesequencing of the 25 founders which in combination with the short-read data now enable de novo assembly of the 25 genomes that will soon lead to construction of the first melon pan-genome. 3) Transcriptomic (3' RNA-Seq) analysis of several selected hybrids and their parents provide preliminary information on differentially expressed genes that can be further used to explain the root-derived yield variation. Taken together, this project expanded our view on yield heterosis in melon with novel specific insights on root-derived yield heterosis. To our knowledge, thus far this is the largest systematic genetic analysis of rootstock effects on yield heterosis in cucurbits or any other crop plant, and our results are now translated into potential breeding applications. The genomic resources that were developed as part of this project are putting melon in the forefront of genomic research and will continue to be useful tool for the cucurbits community in years to come. 


2013 ◽  
Vol 20 (11) ◽  
pp. 1333-1339 ◽  
Author(s):  
Georges St Laurent ◽  
Michael R Tackett ◽  
Sergey Nechkin ◽  
Dmitry Shtokalo ◽  
Denis Antonets ◽  
...  

2019 ◽  
Author(s):  
Vinayak V Viswanadham ◽  
Vinay S Mahajan ◽  
Shiv Pillai

ATAC-seq exploits the observation that the pattern of transposition of a hyperactive Tn5 transposase in native chromatin mirrors genome-wide chromatin accessibility. It has been suggested that transposition observed around transcription factor binding motifs can be used to assess their occupancy in the form of footprints. However, we show that the vast majority of footprints observed at transcription factor motifs in ATAC-seq data spuriously arise from the intrinsic sequence-dependent transposition site bias of Tn5 and are also observed in naked DNA. We demonstrate that the Tn5 transposition bias can be corrected using existing tools for sequence bias correction and a novel estimate of global occupancy in order to produce more reliable estimates of footprints.


BMC Genomics ◽  
2010 ◽  
Vol 11 (1) ◽  
pp. 519 ◽  
Author(s):  
Mun-Kit Choy ◽  
Mehregan Movassagh ◽  
Hock-Guan Goh ◽  
Martin R Bennett ◽  
Thomas A Down ◽  
...  

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