| 2. |
- Elsik, Christine G., et al.
(author)
-
The Genome Sequence of Taurine Cattle : A Window to Ruminant Biology and Evolution
- 2009
-
In: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 324:5926, s. 522-528
-
Journal article (peer-reviewed)abstract
- To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.
|
|
| 4. |
- Ratnakumar, Abhirami, et al.
(author)
-
Using paired-end sequences to optimise parameters for alignment of sequence reads against related genomes
- 2010
-
In: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 11, s. 458-
-
Journal article (peer-reviewed)abstract
- Background: The advent of cheap high through-put sequencing methods has facilitated low coverage skims of a large number of organisms. To maximise the utility of the sequences, assembly into contigs and then ordering of those contigs is required. Whilst sequences can be assembled into contigs de novo, using assembled genomes of closely related organisms as a framework can considerably aid the process. However, the preferred search programs and parameters that will optimise the sensitivity and specificity of the alignments between the sequence reads and the framework genome(s) are not necessarily obvious. Here we demonstrate a process that uses paired-end sequence reads to choose an optimal program and alignment parameters. Results: Unlike two single fragment reads, in paired-end sequence reads, such as BAC-end sequences, the two sequences in the pair have a known positional relationship in the original genome. This provides an additional level of confidence over match scores and e-values in the accuracy of the positional assignment of the reads in the comparative genome. Three commonly used sequence alignment programs: MegaBLAST, Blastz and PatternHunter were used to align a set of ovine BAC-end sequences against the equine genome assembly. A range of different search parameters, with a particular focus on contiguous and discontiguous seeds, were used for each program. The number of reads with a hit and the number of read pairs with hits for the two end sequences in the tail-to-tail paired-end configuration were plotted relative to the theoretical maximum expected curve. Of the programs tested, MegaBLAST with short contiguous seed lengths (word size 8-11) performed best in this particular task. In addition the data also provides estimates of the false positive and false negative rates, which can be used to determine the appropriate values of additional parameters, such as score cut-off, to balance sensitivity and specificity. To determine whether the approach also worked for the alignment of shorter reads, the first 240 bases of each BAC end sequence were also aligned to the equine genome. Again, contiguous MegaBLAST performed the best in optimising the sensitivity and specificity with which sheep BAC end reads map to the equine and bovine genomes. Conclusions: Paired-end reads, such as BAC-end sequences, provide an efficient mechanism to optimise sequence alignment parameters, for example for comparative genome assemblies, by providing an objective standard to evaluate performance.
|
|
