https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-6568-2

Address of the bookmark: https://github.com/HuffordLab/GenomeQC

1. SPAdes: An assembler specifically designed for single-cell and multi-cell bacterial genomes, as well as small eukaryotic genomes.

2. ABySS: A parallelized assembler for large genomes that uses de Bruijn graphs.

3. Velvet: Another de Bruijn graph-based assembler optimized for short-read sequencing data.

4. SOAPdenovo: A de Bruijn graph-based assembler designed for short reads, widely used for assembling large and complex genomes.

5. MaSuRCA: A hybrid assembler that combines data from multiple sequencing technologies, such as Illumina and PacBio.

6. Canu: A long-read assembler optimized for PacBio and Oxford Nanopore sequencing data.

7. Flye: A long-read assembler suitable for bacterial and small eukaryotic genomes.

8. SMARTdenovo: An assembler designed for long reads, particularly suited for PacBio data.

9. SPAdes Long Read (SPAdesLR): An extension of SPAdes for long-read data, such as those from PacBio or Nanopore.

10. Minia: An assembler optimized for low memory consumption, suitable for small and medium-sized genomes.

11. Unicycler: A hybrid assembler that combines short and long reads for circular bacterial genome assembly.

12. wtdbg2: A de Bruijn graph assembler for long reads, efficient for very large genomes.

13. Shasta: A long-read assembler that uses the Overlap-Layout-Consensus approach, suitable for PacBio and Nanopore data.

14. Sparc: An assembler designed to handle noisy long reads from Nanopore sequencing.

15. CANA: An assembler for metagenomic data, particularly for complex and diverse microbial communities.

16. Ra Assembler: A metagenome assembler for long reads, designed for highly complex metagenomic samples.

Please note that the field of bioinformatics is constantly evolving, and new assembly tools may have emerged since my last update. Additionally, the performance of these tools can vary depending on the characteristics of the sequencing data and the genome being assembled. When selecting an assembly tool, consider the specific requirements of your project, the available data types, and the computational resources at your disposal. Always refer to the respective tool's documentation and publications for the most up-to-date information and recommendations.

• AssemblyMapper : reference-guided genome assembly
• GapFiller : long-reads based gap filling
• TeloExplorer : telomere identification
• CentroMiner : centromere candidate prediction

https://academic.oup.com/hr/article/10/8/uhad127/7197191?login=false 

Address of the bookmark: http://www.atcgn.com:8080/quarTeT/home.html

To address the challenges of describing and estimating virodiversity, a team of investigators from Center for Infection and Immunity (CII) and EcoHealth Alliance began in jungles of Bangladesh - home to the flying fox.

Reference:

http://economictimes.indiatimes.com/news/news-by-industry/et-cetera/mammals-harbour-at-least-320000-new-viruses/articleshow/22253268.cms

http://www.bbc.co.uk/news/science-environment-23932400

The vital metaphase stage of cell division, when the sister chromatids migrated to the centre and lined up in a row, and pulled apart using attached microtubules in such a way that half the DNA ends up in each daughter cell. However, before the mitotic spindle‐mediated movement gets start and pulled DNA apart, the chromosomes are free to undergo recombination which involves the exchange of genetic material either between multiple chromosomes or between different regions of the same chromosome.

During recombination, the precise breakage of each strand, exchange between the strands, and sealing of the resulting recombined molecules happens. The “chromosomal breakpoints” refers to these places where they break. Mostly, this process occurs with a high degree of accuracy at high frequency in both eukaryotic and prokaryotic cells. But occasionally this “break and sealing/ break and reattach” process goes wrong and the reattachment happens in the wrong place which usually create disaster (with few exceptions).These chromosome disaster or abnormalities involve the gain, loss or rearrangement of visible amounts of genetic material during cell division. These abnormalities are of two type, the first one is numerical abnormalities  where severe disorders are caused by the loss or gain of whole chromosomes, which affect the copy number of hundreds or even thousands of genes. The second are structural abnormalities which can be unbalanced or balanced. The former are similar to numerical abnormalities in that genetic material is either gained or lost. The natural defects in chromosome segregation are linked to cancer and several genetic diseases (http://en.wikipedia.org/wiki/List_of_genetic_disorders). Therefore, the enzymes involved in regulating cell division are still the attractive drug targets for many diseases.

Apart from certain chromosome abnormalities, these “crossing over” of segments of maternal and paternal chromosomes to form hybrid chromosomes have some evolutionary importance and considered as a driver of genetic variation. Moreover, the chromosome breakage in evolution is considered to be non-random in nature(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.0020014). In addition the study of breakpoint regions and non-breakpoint (stable) regions of chromosomes indicates both the regions evolved in distinctly different ways ( http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). These breakage may lead to genetic diseases or participate to chromosomal rearranmgnets and contributed in development of new species.

I will try to explain the genome hotspots/Evolutionary Breakpoint Regions(EBRs)/fragile regions/weak fragments/  in my next blog.

Software for recombination detection:

RAT http://cbr.jic.ac.uk/dicks/software/RAT/

Breakpointer https://github.com/ruping/Breakpointer

DRP http://web.cbio.uct.ac.za/~darren/rdp.html

RB-finder http://www.ncbi.nlm.nih.gov/pubmed/18707535

LDhat2.0 http://ldhat.sourceforge.net/LDhat2.0/instructions.shtml

Reference:

http://www.nature.com/scitable/topicpage/genetic-recombination-514#

Image: Wikipedia , sciencelearn.org.nz

Recommended Articles:

http://www.friendshipcircle.org/blog/2012/05/22/13-chromosomal-disorders-youve-never-heard-of/

http://web.udl.es/usuaris/e4650869/docencia/segoncicle/genclin98/recursos_classe_%28pdf%29/revisionsPDF/chromosyndromes.pdf

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2775595/table/T2/

http://learn.genetics.utah.edu/content/disorders/chromosomal/

http://www.ncert.nic.in/html/learning_basket/biology/cc&cd.pdf