Genome structure of  Rosa multiflora , a wild ancestor of cultivated roses

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Abstract

The draft genome sequence of a wild rose ( Rosa multiflora Thunb.) was determined using Illumina MiSeq and HiSeq platforms. The total length of the scaffolds was 739,637,845 bp, consisting of 83,189 scaffolds, which was close to the 711 Mbp length estimated by k-mer analysis. N50 length of the scaffolds was 90,830 bp, and extent of the longest was 1,133,259 bp. The average GC content of the scaffolds was 38.9%. After gene prediction, 67,380 candidates exhibiting sequence homology to known genes and domains were extracted, which included complete and partial gene structures. This large number of genes for a diploid plant may reflect heterogeneity of the genome originating from self-incompatibility in R. multiflora. According to CEGMA analysis, 91.9% and 98.0% of the core eukaryotic genes were completely and partially conserved in the scaffolds, respectively. Genes presumably involved in flower color, scent and flowering are assigned. The results of this study will serve as a valuable resource for fundamental and applied research in the rose, including breeding and phylogenetic study of cultivated roses.

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A new generation of homology search tools based on probabilistic inference.

Sean R. Eddy (2009)

Many theoretical advances have been made in applying probabilistic inference methods to improve the power of sequence homology searches, yet the BLAST suite of programs is still the workhorse for most of the field. The main reason for this is practical: BLAST's programs are about 100-fold faster than the fastest competing implementations of probabilistic inference methods. I describe recent work on the HMMER software suite for protein sequence analysis, which implements probabilistic inference using profile hidden Markov models. Our aim in HMMER3 is to achieve BLAST's speed while further improving the power of probabilistic inference based methods. HMMER3 implements a new probabilistic model of local sequence alignment and a new heuristic acceleration algorithm. Combined with efficient vector-parallel implementations on modern processors, these improvements synergize. HMMER3 uses more powerful log-odds likelihood scores (scores summed over alignment uncertainty, rather than scoring a single optimal alignment); it calculates accurate expectation values (E-values) for those scores without simulation using a generalization of Karlin/Altschul theory; it computes posterior distributions over the ensemble of possible alignments and returns posterior probabilities (confidences) in each aligned residue; and it does all this at an overall speed comparable to BLAST. The HMMER project aims to usher in a new generation of more powerful homology search tools based on probabilistic inference methods.

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The genome of the pear ( Pyrus bretschneideri Rehd.)

Jun Jun Wu, Zhiwen Wang, Zebin Shi … (2013)

The draft genome of the pear ( Pyrus bretschneideri ) using a combination of BAC-by-BAC and next-generation sequencing is reported. A 512.0-Mb sequence corresponding to 97.1% of the estimated genome size of this highly heterozygous species is assembled with 194× coverage. High-density genetic maps comprising 2005 SNP markers anchored 75.5% of the sequence to all 17 chromosomes. The pear genome encodes 42,812 protein-coding genes, and of these, ∼28.5% encode multiple isoforms. Repetitive sequences of 271.9 Mb in length, accounting for 53.1% of the pear genome, are identified. Simulation of eudicots to the ancestor of Rosaceae has reconstructed nine ancestral chromosomes. Pear and apple diverged from each other ∼5.4–21.5 million years ago, and a recent whole-genome duplication (WGD) event must have occurred 30–45 MYA prior to their divergence, but following divergence from strawberry. When compared with the apple genome sequence, size differences between the apple and pear genomes are confirmed mainly due to the presence of repetitive sequences predominantly contributed by transposable elements (TEs), while genic regions are similar in both species. Genes critical for self-incompatibility, lignified stone cells (a unique feature of pear fruit), sorbitol metabolism, and volatile compounds of fruit have also been identified. Multiple candidate SFB genes appear as tandem repeats in the S -locus region of pear; while lignin synthesis-related gene family expansion and highly expressed gene families of HCT , C3′H , and CCOMT contribute to high accumulation of both G-lignin and S-lignin. Moreover, alpha-linolenic acid metabolism is a key pathway for aroma in pear fruit.

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Integration of mapped RNA-Seq reads into automatic training of eukaryotic gene finding algorithm

Alexandre Lomsadze, Paul D. Burns, Mark Borodovsky (2014)

We present a new approach to automatic training of a eukaryotic ab initio gene finding algorithm. With the advent of Next-Generation Sequencing, automatic training has become paramount, allowing genome annotation pipelines to keep pace with the speed of genome sequencing. Earlier we developed GeneMark-ES, currently the only gene finding algorithm for eukaryotic genomes that performs automatic training in unsupervised ab initio mode. The new algorithm, GeneMark-ET augments GeneMark-ES with a novel method that integrates RNA-Seq read alignments into the self-training procedure. Use of ‘assembled’ RNA-Seq transcripts is far from trivial; significant error rate of assembly was revealed in recent assessments. We demonstrated in computational experiments that the proposed method of incorporation of ‘unassembled’ RNA-Seq reads improves the accuracy of gene prediction; particularly, for the 1.3 GB genome of Aedes aegypti the mean value of prediction Sensitivity and Specificity at the gene level increased over GeneMark-ES by 24.5%. In the current surge of genomic data when the need for accurate sequence annotation is higher than ever, GeneMark-ET will be a valuable addition to the narrow arsenal of automatic gene prediction tools.

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Author and article information

Journal

Journal ID (nlm-ta): DNA Res

Journal ID (iso-abbrev): DNA Res

Journal ID (publisher-id): dnares

Title: DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes

Publisher: Oxford University Press

ISSN (Print): 1340-2838

ISSN (Electronic): 1756-1663

Publication date (Print): April 2018

Publication date (Electronic): 16 October 2017

Publication date PMC-release: 16 October 2017

Volume: 25

Issue: 2

Pages: 113-121

Affiliations

[1 ]Suntory Global Innovation Center Ltd, Seika-cho, Soraku-gun, Kyoto 619-0284, Japan

[2 ]Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan

[3 ]Graduate School of Life Sciences, Tohoku University, Aoba-ku, Sendai, Miyagi 980-8577, Japan

[4 ]Graduate School of Bioagricultural Sciences, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan

Author notes

To whom correspondence should be addressed. Tel. +81 50 3182 0451. Fax. +81 774 98 6262. Email: Yoshikazu_Tanaka@ 123456suntory.co.jp

Noriko Nakamura and Hideki Hirakawa contributed equally to this work.

Edited by Dr. Katsumi Isono

Article

Publisher ID: dsx042

DOI: 10.1093/dnares/dsx042

PMC ID: 5909451

PubMed ID: 29045613

SO-VID: 7e0bde0b-c0c7-4fc1-a7ea-cfacd420a9dd

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

History

Date received : 12 June 2017

Date accepted : 19 September 2017

Page count

Pages: 9

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Genome structure of Rosa multiflora, a wild ancestor of cultivated roses

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Arabidopsis genomics

Most cited references 43

A new generation of homology search tools based on probabilistic inference.

The genome of the pear ( Pyrus bretschneideri Rehd.)

Integration of mapped RNA-Seq reads into automatic training of eukaryotic gene finding algorithm

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Cited by 37

Most referenced authors 2,143