Dataset Information

Quantitative profiling of N⁶-methyladenosine at single-base resolution in stem-differentiating xylem of Populus trichocarpa using Nanopore direct RNA sequencing.

ABSTRACT: There are no comprehensive methods to identify N⁶-methyladenosine (m⁶A) at single-base resolution for every single transcript, which is necessary for the estimation of m⁶A abundance. We develop a new pipeline called Nanom6A for the identification and quantification of m⁶A modification at single-base resolution using Nanopore direct RNA sequencing based on an XGBoost model. We validate our method using methylated RNA immunoprecipitation sequencing (MeRIP-Seq) and m⁶A-sensitive RNA-endoribonuclease-facilitated sequencing (m6A-REF-seq), confirming high accuracy. Using this method, we provide a transcriptome-wide quantification of m⁶A modification in stem-differentiating xylem and reveal that different alternative polyadenylation (APA) usage shows a different ratio of m⁶A.

SUBMITTER: Gao Y

PROVIDER: S-EPMC7791831 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Quantitative profiling of N6-methyladenosine at single-base resolution in stem-differentiating xylem of Populus trichocarpa using Nanopore direct RNA sequencing.

Gao Yubang Y Liu Xuqing X Wu Bizhi B Wang Huihui H Xi Feihu F Kohnen Markus V MV Reddy Anireddy S N ASN Gu Lianfeng L

Genome biology 20210107 1

There are no comprehensive methods to identify N6-methyladenosine (m6A) at single-base resolution for every single transcript, which is necessary for the estimation of m6A abundance. We develop a new pipeline called Nanom6A for the identification and quantification of m6A modification at single-base resolution using Nanopore direct RNA sequencing based on an XGBoost model. We validate our method using methylated RNA immunoprecipitation sequencing (MeRI ...[more]

PMID: 33413586

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Project description:Our greater understanding of the importance of N-linked glycosylation in biological systems has spawned the field of glycomics and development of analytical tools to address the many challenges regarding our ability to characterize and quantify this complex and important modification as it relates to biological function. One of the unmet needs of the field remains a systematic method for characterization of glycans in new biological systems. This study presents a novel workflow for identification of glycans using Individuality Normalization when Labeling with Isotopic Glycan Hydrazide Tags (INLIGHT™) strategy developed in our lab. This consists of monoisotopic mass extraction followed by peak pair identification of tagged glycans from a theoretical library using an in-house program. Identification and relative quantification could then be performed using the freely available bioinformatics tool Skyline. These studies were performed in the biological context of studying the N-linked glycome of differentiating xylem of the poplar tree, a widely studied model woody plant, particularly with respect to understanding lignin biosynthesis during wood formation. Through our workflow, we were able to identify 502 glycosylated proteins including 12 monolignol enzymes and 1 peroxidase (PO) through deamidation glycosite analysis. Finally, our novel semi-automated workflow allowed for rapid identification of 27 glycans by intact mass and by NAT/SIL peak pairing from a library containing 1573 potential glycans, eliminating the need for extensive manual analysis. Implementing Skyline for relative glycan quantification allowed for improved accuracy and precision of quantitative measurements over current processing tools which we attribute to superior algorithms correction for baseline variation and MS1 peak filtering. Graphical abstract Workflow for FANGS-INLIGHT glycosite profiling of plant xylem and monolignol proteins followed by INLIGHT tagging with semi-automated identification of glycans by light-heavy peak pairs. Finally, manual validation and relative quantification was performed in Skyline.

Project description:Forest trees generally show high levels of local adaptation and efforts focusing on understanding adaptation to climate will be crucial for species survival and management. Here, we address fundamental questions regarding the molecular basis of adaptation in undomesticated forest tree populations to past climatic environments by employing an integrative quantitative genetics and landscape genomics approach. Using this comprehensive approach, we studied the molecular basis of climate adaptation in 433 Populus trichocarpa (black cottonwood) genotypes originating across western North America. Variation in 74 field-assessed traits (growth, ecophysiology, phenology, leaf stomata, wood, and disease resistance) was investigated for signatures of selection (comparing QST-FST) using clustering of individuals by climate of origin (temperature and precipitation). 29,354 SNPs were investigated employing three different outlier detection methods and marker-inferred relatedness was estimated to obtain the narrow-sense estimate of population differentiation in wild populations. In addition, we compared our results with previously assessed selection of candidate SNPs using the 25 topographical units (drainages) across the P. trichocarpa sampling range as population groupings. Narrow-sense QST for 53% of distinct field traits was significantly divergent from expectations of neutrality (indicating adaptive trait variation); 2,855 SNPs showed signals of diversifying selection and of these, 118 SNPs (within 81 genes) were associated with adaptive traits (based on significant QST). Many SNPs were putatively pleiotropic for functionally uncorrelated adaptive traits, such as autumn phenology, height, and disease resistance. Evolutionary quantitative genomics in P. trichocarpa provides an enhanced understanding regarding the molecular basis of climate-driven selection in forest trees and we highlight that important loci underlying adaptive trait variation also show relationship to climate of origin. We consider our approach the most comprehensive, as it uncovers the molecular mechanisms of adaptation using multiple methods and tests. We also provide a detailed outline of the required analyses for studying adaptation to the environment in a population genomics context to better understand the species' potential adaptive capacity to future climatic scenarios.

Dataset Information

Quantitative profiling of N⁶-methyladenosine at single-base resolution in stem-differentiating xylem of Populus trichocarpa using Nanopore direct RNA sequencing.

Publications

Quantitative profiling of N<sup>6</sup>-methyladenosine at single-base resolution in stem-differentiating xylem of Populus trichocarpa using Nanopore direct RNA sequencing.

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