scholarly journals Trichoderma reesei Rad51 tolerates mismatches in hybrid meiosis with diverse genome sequences

2021 ◽  
Vol 118 (8) ◽  
pp. e2007192118
Author(s):  
Wan-Chen Li ◽  
Chia-Yi Lee ◽  
Wei-Hsuan Lan ◽  
Tai-Ting Woo ◽  
Hou-Cheng Liu ◽  
...  
Keyword(s):  
Trichoderma Reesei ◽  
Single Molecule ◽  
Amino Acid Residues ◽  
Sequencing Technology ◽  
Structural Variations ◽  
Genome Sequences ◽  
Third Generation Sequencing ◽  
L1 And L2 ◽  
Generation Sequencing ◽  
Better Than

Most eukaryotes possess two RecA-like recombinases (ubiquitous Rad51 and meiosis-specific Dmc1) to promote interhomolog recombination during meiosis. However, some eukaryotes have lost Dmc1. Given that mammalian and yeast Saccharomyces cerevisiae (Sc) Dmc1 have been shown to stabilize recombination intermediates containing mismatches better than Rad51, we used the Pezizomycotina filamentous fungus Trichoderma reesei to address if and how Rad51-only eukaryotes conduct interhomolog recombination in zygotes with high sequence heterogeneity. We applied multidisciplinary approaches (next- and third-generation sequencing technology, genetics, cytology, bioinformatics, biochemistry, and single-molecule biophysics) to show that T. reesei Rad51 (TrRad51) is indispensable for interhomolog recombination during meiosis and, like ScDmc1, TrRad51 possesses better mismatch tolerance than ScRad51 during homologous recombination. Our results also indicate that the ancestral TrRad51 evolved to acquire ScDmc1-like properties by creating multiple structural variations, including via amino acid residues in the L1 and L2 DNA-binding loops.

scholarly journals Apollo: a sequencing-technology-independent, scalable and accurate assembly polishing algorithm

2020 ◽  
Vol 36 (12) ◽  
pp. 3669-3679 ◽  
Author(s):  
Can Firtina ◽  
Jeremie S Kim ◽  
Mohammed Alser ◽  
Damla Senol Cali ◽  
A Ercument Cicek ◽  
...  
Keyword(s):  
Genome Analysis ◽  
Supplementary Information ◽  
Third Generation ◽  
Sequencing Technology ◽  
Base Pairs ◽  
Sequencing Technologies ◽  
Third Generation Sequencing ◽  
Long Reads ◽  
Generation Sequencing ◽  
Large Genomes

Abstract Motivation Third-generation sequencing technologies can sequence long reads that contain as many as 2 million base pairs. These long reads are used to construct an assembly (i.e. the subject’s genome), which is further used in downstream genome analysis. Unfortunately, third-generation sequencing technologies have high sequencing error rates and a large proportion of base pairs in these long reads is incorrectly identified. These errors propagate to the assembly and affect the accuracy of genome analysis. Assembly polishing algorithms minimize such error propagation by polishing or fixing errors in the assembly by using information from alignments between reads and the assembly (i.e. read-to-assembly alignment information). However, current assembly polishing algorithms can only polish an assembly using reads from either a certain sequencing technology or a small assembly. Such technology-dependency and assembly-size dependency require researchers to (i) run multiple polishing algorithms and (ii) use small chunks of a large genome to use all available readsets and polish large genomes, respectively. Results We introduce Apollo, a universal assembly polishing algorithm that scales well to polish an assembly of any size (i.e. both large and small genomes) using reads from all sequencing technologies (i.e. second- and third-generation). Our goal is to provide a single algorithm that uses read sets from all available sequencing technologies to improve the accuracy of assembly polishing and that can polish large genomes. Apollo (i) models an assembly as a profile hidden Markov model (pHMM), (ii) uses read-to-assembly alignment to train the pHMM with the Forward–Backward algorithm and (iii) decodes the trained model with the Viterbi algorithm to produce a polished assembly. Our experiments with real readsets demonstrate that Apollo is the only algorithm that (i) uses reads from any sequencing technology within a single run and (ii) scales well to polish large assemblies without splitting the assembly into multiple parts. Availability and implementation Source code is available at https://github.com/CMU-SAFARI/Apollo. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Long-range single-molecule mapping of chromatin modification in eukaryotes

2021 ◽  
Author(s):  
Zhe Weng ◽  
Fengying Ruan ◽  
Weitian Chen ◽  
Zhe Xie ◽  
Yeming Xie ◽  
...  
Keyword(s):  
Histone Modification ◽  
Long Range ◽  
Single Molecule ◽  
Protein A ◽  
Chromatin Modification ◽  
Protein Binding Sites ◽  
Short Read Sequencing ◽  
Third Generation Sequencing ◽  
Long Read ◽  
Generation Sequencing

The epigenetic modifications of histones are essential marks related to the development and disease pathogenesis, including human cancers. Mapping histone modification has emerged as the widely used tool for studying epigenetic regulation. However, existing approaches limited by fragmentation and short-read sequencing cannot provide information about the long-range chromatin states and represent the average chromatin status in samples. We leveraged the advantage of long read sequencing to develop a method "BIND&MODIFY" for profiling the histone modification of individual DNA fiber. Our approach is based on the recombinant fused protein A-EcoGII, which tethers the methyltransferase EcoGII to the protein binding sites and locally labels the neighboring DNA regions through artificial methylations. We demonstrate that the aggregated BIND&MODIFY signal matches the bulk-level ChIP-seq and CUT&TAG, observe the single-molecule heterogenous histone modification status, and quantify the correlation between distal elements. This method could be an essential tool in the future third-generation sequencing ages.

scholarly journals Nanopore base-calling from a perspective of instance segmentation

2019 ◽  
Author(s):  
Yao-zhong Zhang ◽  
Arda Akdemir ◽  
Georg Tremmel ◽  
Seiya Imoto ◽  
Satoru Miyano ◽  
...  
Keyword(s):  
Supplementary Information ◽  
Sequencing Technology ◽  
One Dimensional ◽  
Sequential Dependencies ◽  
Base Calling ◽  
Third Generation Sequencing ◽  
Pass Through ◽  
Segmentation Task ◽  
Generation Sequencing ◽  
Instance Segmentation

AbstractBackgroundNanopore sequencing is a rapidly developing third-generation sequencing technology, which can generate long nucleotide reads of molecules within a portable device in real time. Through detecting the change of ion currency signals during a DNA/RNA fragment’s pass through a nanopore, genotypes are determined. Currently, the accuracy of nanopore base-calling has a higher error rate than short-read base-calling. Through utilizing deep neural networks, the-state-of-the art nanopore base-callers achieve base-calling accuracy in a range from 85% to 95%.ResultIn this work, we proposed a novel base-calling approach from a perspective of instance segmentation. Different from the previous sequence labeling approaches, we formulated the base-calling problem as a multi-label segmentation task. Meanwhile, we proposed a refined U-net model which we call UR-net that can model sequential dependencies for a one-dimensional segmentation task. The experiment results show that the proposed base-caller URnano achieves competitive results compared to recently proposed CTC-featured base-caller Chiron, on the same amount of training and test data for in-domain evaluation. Our results show that formulating the base-calling problem as a one-dimensional segmentation task is a promising approach.AvailabilityThe source code and data are available at https://github.com/yaozhong/[email protected] informationSupplementary data are available at attachment online.

scholarly journals The study of transcriptomes of symbiotic tissue of pea using the third-generation sequencing technology Oxford Nanopore

2020 ◽  
Author(s):  
E. S. Gribchenko
Keyword(s):  
Nanopore Sequencing ◽  
Third Generation ◽  
Nitrogen Fixing ◽  
Sequencing Technology ◽  
The Third ◽  
Third Generation Sequencing ◽  
Oxford Nanopore ◽  
Mycorrhizal Roots ◽  
Gene Isoforms ◽  
Generation Sequencing

The transcriptome profiles the cv. Frisson mycorrhizal roots and inoculated nitrogen-fixing nodules were investigated using the Oxford Nanopore sequencing technology. A database of gene isoforms and their expression has been created.

scholarly journals SMOOTH-seq: single-cell genome sequencing of human cells on a third-generation sequencing platform

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiaoying Fan ◽  
Cheng Yang ◽  
Wen Li ◽  
Xiuzhen Bai ◽  
Xin Zhou ◽  
...  
Keyword(s):  
Single Cell ◽  
Genome Sequencing ◽  
Single Molecule ◽  
Human Cancer ◽  
Whole Genome ◽  
Third Generation ◽  
Sequencing Platform ◽  
Human Cancer Cell Lines ◽  
Third Generation Sequencing ◽  
Generation Sequencing

AbstractThere is no effective way to detect structure variations (SVs) and extra-chromosomal circular DNAs (ecDNAs) at single-cell whole-genome level. Here, we develop a novel third-generation sequencing platform-based single-cell whole-genome sequencing (scWGS) method named SMOOTH-seq (single-molecule real-time sequencing of long fragments amplified through transposon insertion). We evaluate the method for detecting CNVs, SVs, and SNVs in human cancer cell lines and a colorectal cancer sample and show that SMOOTH-seq reliably and effectively detects SVs and ecDNAs in individual cells, but shows relatively limited accuracy in detection of CNVs and SNVs. SMOOTH-seq opens a new chapter in scWGS as it generates high fidelity reads of kilobases long.

scholarly journals Quantifying the Benefit Offered by Transcript Assembly on Single-Molecule Long Reads

2019 ◽  
Author(s):  
Laura H. Tung ◽  
Mingfu Shao ◽  
Carl Kingsford
Keyword(s):  
Single Molecule ◽  
Error Rates ◽  
Human Transcriptome ◽  
Sequencing Technologies ◽  
Third Generation Sequencing ◽  
Long Reads ◽  
Long Read ◽  
Transcript Assembly ◽  
Novel Isoforms ◽  
Generation Sequencing

AbstractThird-generation sequencing technologies benefit transcriptome analysis by generating longer sequencing reads. However, not all single-molecule long reads represent full transcripts due to incomplete cDNA synthesis and the sequencing length limit of the platform. This drives a need for long read transcript assembly. We quantify the benefit that can be achieved by using a transcript assembler on long reads. Adding long-read-specific algorithms, we evolved Scallop to make Scallop-LR, a long-read transcript assembler, to handle the computational challenges arising from long read lengths and high error rates. Analyzing 26 SRA PacBio datasets using Scallop-LR, Iso-Seq Analysis, and StringTie, we quantified the amount by which assembly improved Iso-Seq results. Through combined evaluation methods, we found that Scallop-LR identifies 2100–4000 more (for 18 human datasets) or 1100–2200 more (for eight mouse datasets) known transcripts than Iso-Seq Analysis, which does not do assembly. Further, Scallop-LR finds 2.4–4.4 times more potentially novel isoforms than Iso-Seq Analysis for the human and mouse datasets. StringTie also identifies more transcripts than Iso-Seq Analysis. Adding long-read-specific optimizations in Scallop-LR increases the numbers of predicted known transcripts and potentially novel isoforms for the human transcriptome compared to several recent short-read assemblers (e.g. StringTie). Our findings indicate that transcript assembly by Scallop-LR can reveal a more complete human transcriptome.

scholarly journals Third generation indexing for third generation sequencing

2020 ◽  
Author(s):  
Abdulqader Jighly
Keyword(s):  
Dna Sequences ◽  
De Novo ◽  
Total Error ◽  
Error Rates ◽  
Routine Activity ◽  
Considerable Proportion ◽  
Third Generation ◽  
Structural Variations ◽  
Third Generation Sequencing ◽  
Generation Sequencing

AbstractIndexing of DNA sequences is the art of sorting massive genomic data in a user-friendly structure to enable rapid accessing and comparing of different patterns in the data. Current genome assemblers use general algorithms for string indexing that do not exploit the special structural arrangement of genomes. Here, I am proposing a new algorithm that indexes only the configuration of microsatellite motifs along reads assuming that the order of microsatellites will be the same in overlapped sequences. The index size is >1000 times smaller than currently used indices and it has higher tolerance to the high error rates produced by third generation sequencing platforms. The results showed that the proposed algorithm can rapidly detect overlaps among considerable proportion of uncorrected long reads (~50% of all simulated base pairs with average read size of 8.16 kb and total error rates of 14.4%) to build large initial contigs. Unassembled reads can be then mapped to these contigs or can be assembled with them with currently used algorithms. Thus, the proposed algorithm can efficiently be used as an initial stage to significantly reduce the number of pairwise sequence comparisons among reads and/or references and improve the performance of different software but not replacing them. The algorithm was also useful for comparative genomics and detect large locally colinear blocks and structural variations among ten saccharomyces cerevisiae strains. The proposed algorithm has the power to make de novo assembly of individuals as routine activity which can lead to more accurate variant calling and pan genomics.

scholarly journals CODEC enables 'single duplex' sequencing

2021 ◽  
Author(s):  
Jin H. Bae ◽  
Ruolin Liu ◽  
Erica Nguyen ◽  
Justin Rhoades ◽  
Timothy Blewett ◽  
...  
Keyword(s):  
Single Molecule ◽  
Cancer Diagnostics ◽  
Third Generation ◽  
Aging Research ◽  
Third Generation Sequencing ◽  
Double Stranded Dna ◽  
Duplex Sequencing ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing ◽  
Limited Accuracy

Detecting mutations as rare as a single molecule is crucial in many fields such as cancer diagnostics and aging research but remains challenging. Third generation sequencers can read a double-stranded DNA molecule (a 'single duplex') in whole to identify true mutations on both strands apart from false mutations on either strand but with limited accuracy and throughput. Although next generation sequencing (NGS) can track dissociated strands with Duplex Sequencing, the need to sequence each strand independently severely diminishes its throughput. Here, we developed a hybrid method called Concatenating Original Duplex for Error Correction (CODEC) that combines the massively parallel nature of NGS with the single-molecule capability of third generation sequencing. CODEC physically links both strands to enable NGS to sequence a single duplex with a single read pair. By comparing CODEC and Duplex Sequencing, we showed that CODEC achieved a similar error rate (10-6) with 100 times fewer reads and conferred 'single duplex' resolution to most major NGS workflows.

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