Improved AFLP protocol using dual-suppression PCR and its application to species with large genomes

2011 ◽  
Vol 11 (5) ◽  
pp. 854-861 ◽  
Author(s):  
LANHUA GUAN ◽  
SUSUMU SHIRAISHI
2020 ◽  
Vol 36 (12) ◽  
pp. 3669-3679 ◽  
Author(s):  
Can Firtina ◽  
Jeremie S Kim ◽  
Mohammed Alser ◽  
Damla Senol Cali ◽  
A Ercument Cicek ◽  
...  

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.


Genome ◽  
2009 ◽  
Vol 52 (6) ◽  
pp. 566-575 ◽  
Author(s):  
Harpinder S. Randhawa ◽  
Jaswinder Singh ◽  
Peggy G. Lemaux ◽  
Kulvinder S. Gill

Gene distribution is highly uneven in the large genomes of barley and wheat; however, location, order, and gene density of gene-containing regions are very similar between the two genomes. Flanking sequences from 35 unique, single-copy, barley Ds insertion events were physically mapped using wheat nullisomic-tetrasomic, ditelosomic, and deletion lines. Of the 35 sequences, 23 (66%) detected 34 loci mapping on all 7 homoeologous wheat groups. Seven sequences were not mapped owing to lack of polymorphism and the remaining 5 (14%) were barley-specific. All 34 loci physically mapped to the previously identified gene-rich regions (GRRs) of wheat, making the contained genes candidates for targeted mutagenesis by remobilization. Transpositions occurred preferentially into GRRs with higher recombination rates. The GRRs containing 17 of the 23 Ds insertions accounted for 60%–89% of the respective arm’s recombination. The remaining 6 (17%) insertions mapped to GRRs with <15% of the arm’s recombination. Overall, kb/cM estimates for the Ds-containing GRRs were twofold higher than those for regions without insertions. These results suggest that all genes may be targeted by transposon-based gene cloning, although the transposition frequency for genes present in recombination-poor regions is significantly less than that present in highly recombinogenic regions.


2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Juan Manuel Crescente ◽  
Diego Zavallo ◽  
Marcelo Helguera ◽  
Leonardo Sebastián Vanzetti

2021 ◽  
Vol 70 (1) ◽  
pp. 156-169
Author(s):  
Deepak Ohri

Abstract Gymnosperms show a significantly higher mean (1C=18.16, 1Cx=16.80) and a narrow range (16.89-fold) of genome sizes as compared with angiosperms. Among the 12 families the largest ranges of 1C values is shown by Ephedraceae (4.73-fold) and Cupressaceae (4.45-fold) which are partly due to polyploidy as 1Cx values vary 2.41 and 1.37-fold respectively. In rest of the families which have only diploid taxa the range of 1C values is from 1.18-fold (Cycadaeae) to 4.36-fold (Podocarpaceae). The question is how gymnosperms acquired such big genome sizes despite the rarity of recent instances of polyploidy. A general survey of different families and genera shows that gymnosperms have experienced both increase and decrease in their genome size during evolution. Various genomic components which have accounted for these large genomes have been discussed. The major contributors are the transposable elements particularly LTR-retrotransposons comprising of Ty3gypsy, Ty1copia and gymny superfamilies which are most widespread. The genomes of gymnosperms have been acquiring diverse LTR-RTs in their long evolution in the absence of any efficient mechanism of their elimination. The epigenetic machinery which silences these large tracts of repeat sequences into the stretches of heterochromatin and the adaptive value of these silenced repeat sequences need further investigation.


1995 ◽  
Vol 11 (2) ◽  
pp. 63-68 ◽  
Author(s):  
Steven D. Tanksley ◽  
Martin W. Ganal ◽  
Gregory B. Martin
Keyword(s):  

Data in Brief ◽  
2016 ◽  
Vol 8 ◽  
pp. 1438-1442
Author(s):  
Sri A’jilah Samsir ◽  
Hamidun Bunawan ◽  
Choong Chee Yen ◽  
Normah Mohd Noor

2003 ◽  
Vol 68 (0) ◽  
pp. 189-194 ◽  
Author(s):  
R.A. GIBBS ◽  
G.M. WEINSTOCK
Keyword(s):  

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