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1.
BMC Plant Biol ; 20(1): 280, 2020 Jun 17.
Article in English | MEDLINE | ID: mdl-32552738

ABSTRACT

BACKGROUND: Cultivated grasses are an important source of food for domestic animals worldwide. Increased knowledge of their genomes can speed up the development of new cultivars with better quality and greater resistance to biotic and abiotic stresses. The most widely grown grasses are tetraploid ryegrass species (Lolium) and diploid and hexaploid fescue species (Festuca). In this work, we characterized repetitive DNA sequences and their contribution to genome size in five fescue and two ryegrass species as well as one fescue and two ryegrass cultivars. RESULTS: Partial genome sequences produced by Illumina sequencing technology were used for genome-wide comparative analyses with the RepeatExplorer pipeline. Retrotransposons were the most abundant repeat type in all seven grass species. The Athila element of the Ty3/gypsy family showed the most striking differences in copy number between fescues and ryegrasses. The sequence data enabled the assembly of the long terminal repeat (LTR) element Fesreba, which is highly enriched in centromeric and (peri)centromeric regions in all species. A combination of fluorescence in situ hybridization (FISH) with a probe specific to the Fesreba element and immunostaining with centromeric histone H3 (CENH3) antibody showed their co-localization and indicated a possible role of Fesreba in centromere function. CONCLUSIONS: Comparative repeatome analyses in a set of fescues and ryegrasses provided new insights into their genome organization and divergence, including the assembly of the LTR element Fesreba. A new LTR element Fesreba was identified and found in abundance in centromeric regions of the fescues and ryegrasses. It may play a role in the function of their centromeres.


Subject(s)
Chromosomes, Plant , Festuca/genetics , Genome, Plant/genetics , Lolium/genetics , Repetitive Sequences, Nucleic Acid , Centromere/genetics
2.
Plant J ; 92(3): 495-508, 2017 Nov.
Article in English | MEDLINE | ID: mdl-28779536

ABSTRACT

The identification of mutations in targeted genes has been significantly simplified by the advent of TILLING (Targeting Induced Local Lesions In Genomes), speeding up the functional genomic analysis of animals and plants. Next-generation sequencing (NGS) is gradually replacing classical TILLING for mutation detection, as it allows the analysis of a large number of amplicons in short durations. The NGS approach was used to identify mutations in a population of Solanum lycopersicum (tomato) that was doubly mutagenized by ethylmethane sulphonate (EMS). Twenty-five genes belonging to carotenoids and folate metabolism were PCR-amplified and screened to identify potentially beneficial alleles. To augment efficiency, the 600-bp amplicons were directly sequenced in a non-overlapping manner in Illumina MiSeq, obviating the need for a fragmentation step before library preparation. A comparison of the different pooling depths revealed that heterozygous mutations could be identified up to 128-fold pooling. An evaluation of six different software programs (camba, crisp, gatk unified genotyper, lofreq, snver and vipr) revealed that no software program was robust enough to predict mutations with high fidelity. Among these, crisp and camba predicted mutations with lower false discovery rates. The false positives were largely eliminated by considering only mutations commonly predicted by two different software programs. The screening of 23.47 Mb of tomato genome yielded 75 predicted mutations, 64 of which were confirmed by Sanger sequencing with an average mutation density of 1/367 Kb. Our results indicate that NGS combined with multiple variant detection tools can reduce false positives and significantly speed up the mutation discovery rate.


Subject(s)
Ethyl Methanesulfonate/adverse effects , Genomics/methods , Mutagens/adverse effects , Mutation/drug effects , Software , Solanum lycopersicum/genetics , Alleles , Gene Library , Heterozygote , High-Throughput Nucleotide Sequencing , Reverse Genetics , Sequence Analysis, DNA
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