Michael Lutz, from the Duke University Medical Center, discussed a recently published software tool that can now be used in a pipeline with SMRT Sequencing data to find structural variant…
Mithun (Bos frontalis), also called gayal, is an endangered bovine species, under the tribe bovini with 2n?=?58 XX chromosome complements and reared under the tropical rain forests region of India, China, Myanmar, Bhutan and Bangladesh. However, the origin of this species is still disputed and information on its genomic architecture is scanty so far. We trust that availability of its whole genome sequence data and assembly will greatly solve this problem and help to generate many information including phylogenetic status of mithun. Recently, the first genome assembly of gayal, mithun of Chinese origin, was published. However, an improved reference genome assembly would still benefit in understanding genetic variation in mithun populations reared under diverse geographical locations and for building a superior consensus assembly. We, therefore, performed deep sequencing of the genome of an adult female mithun from India, assembled and annotated its genome and performed extensive bioinformatic analyses to produce a superior de novo genome assembly of mithun.We generated ˜300 Gigabyte (Gb) raw reads from whole-genome deep sequencing platforms and assembled the sequence data using a hybrid assembly strategy to create a high quality de novo assembly of mithun with 96% recovered as per BUSCO analysis. The final genome assembly has a total length of 3.0 Gb, contains 5,015 scaffolds with an N50 value of 1?Mb. Repeat sequences constitute around 43.66% of the assembly. The genomic alignments between mithun to cattle showed that their genomes, as expected, are highly conserved. Gene annotation identified 28,044 protein-coding genes presented in mithun genome. The gene orthologous groups of mithun showed a high degree of similarity in comparison with other species, while fewer mithun specific coding sequences were found compared to those in cattle.Here we presented the first de novo draft genome assembly of Indian mithun having better coverage, less fragmented, better annotated, and constitutes a reasonably complete assembly compared to the previously published gayal genome. This comprehensive assembly unravelled the genomic architecture of mithun to a great extent and will provide a reference genome assembly to research community to elucidate the evolutionary history of mithun across its distinct geographical locations.
The ability to generate long sequencing reads and access long-range linkage information is revolutionizing the quality and completeness of genome assemblies. Here we use a hybrid approach that combines data from four genome sequencing and mapping technologies to generate a new genome assembly of the honeybee Apis mellifera. We first generated contigs based on PacBio sequencing libraries, which were then merged with linked-read 10x Chromium data followed by scaffolding using a BioNano optical genome map and a Hi-C chromatin interaction map, complemented by a genetic linkage map.Each of the assembly steps reduced the number of gaps and incorporated a substantial amount of additional sequence into scaffolds. The new assembly (Amel_HAv3) is significantly more contiguous and complete than the previous one (Amel_4.5), based mainly on Sanger sequencing reads. N50 of contigs is 120-fold higher (5.381 Mbp compared to 0.053 Mbp) and we anchor >?98% of the sequence to chromosomes. All of the 16 chromosomes are represented as single scaffolds with an average of three sequence gaps per chromosome. The improvements are largely due to the inclusion of repetitive sequence that was unplaced in previous assemblies. In particular, our assembly is highly contiguous across centromeres and telomeres and includes hundreds of AvaI and AluI repeats associated with these features.The improved assembly will be of utility for refining gene models, studying genome function, mapping functional genetic variation, identification of structural variants, and comparative genomics.
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