The impact of non tree-like evolution such as horizontal gene transfers and hybridization on species biology
Evolution and adaptation of animals in the absence of sexual reproduction and the underlying mechanisms
Genomic signatures of adaptation to a parasitic life-style

More at https://edanchin.org/

More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leidosbiomed&id=2040

What Are lncRNAs?

lncRNAs are RNA transcripts longer than 200 nucleotides that do not code for proteins. Despite their non-coding nature, they play diverse roles in gene regulation, including chromatin remodeling, transcriptional control, and post-transcriptional processing. Unlike messenger RNAs (mRNAs), lncRNAs often function as scaffolds, decoys, or guides in cellular machinery, influencing biological processes such as cell differentiation, immune response, and even cancer metastasis.

Challenges in lncRNA Research

Identifying and understanding lncRNAs pose unique challenges:

1. High Sequence Variability: Unlike protein-coding genes, lncRNAs exhibit low sequence conservation across species, making functional predictions difficult.
2. Low Expression Levels: lncRNAs are often expressed at low levels, complicating their detection in transcriptomic data.
3. Diverse Functions: The multifunctional nature of lncRNAs requires advanced computational tools to decipher their roles in complex networks.

Bioinformatics: A Crucial Ally in lncRNA Research

Bioinformatics bridges the gap between raw biological data and meaningful insights, making it indispensable in lncRNA research. Here’s how:

1. Identification and Annotation

High-throughput sequencing technologies like RNA-seq generate vast amounts of data. Bioinformatics tools such as StringTie, Cufflinks, and HISAT2 help assemble and annotate lncRNAs from this data. Additionally, databases like NONCODE, LNCipedia, and Ensembl provide curated repositories of lncRNA sequences and annotations.

2. Functional Prediction

Bioinformatics algorithms predict the potential functions of lncRNAs by analyzing their interactions with DNA, RNA, and proteins. Tools like LncRNA2Function and RIblast utilize sequence motifs and secondary structure predictions to hypothesize about the roles of specific lncRNAs.

3. Network Construction

lncRNAs often act as regulatory hubs. Bioinformatics platforms such as Cytoscape enable the visualization of lncRNA-mediated networks, elucidating their roles in pathways like cell cycle regulation and apoptosis.

4. Epigenetic Studies

lncRNAs are known to interact with chromatin-modifying complexes, influencing gene expression epigenetically. Tools like ChIP-seq and ATAC-seq, combined with computational pipelines, identify these interactions and map them to the genome.

5. Clinical Applications

Bioinformatics aids in the discovery of lncRNA biomarkers for diseases like cancer and neurodegenerative disorders. Machine learning models analyze differential expression profiles, helping prioritize lncRNAs with therapeutic potential.

Case Study: lncRNAs in Cancer Research

lncRNAs such as HOTAIR and MALAT1 have been implicated in cancer progression. Bioinformatics analyses have revealed their roles in promoting metastasis and altering the tumor microenvironment. For example, transcriptome analysis in cancer patients identifies lncRNA expression signatures, enabling precision medicine approaches.

Future Directions

The fusion of bioinformatics with experimental biology is unlocking the secrets of lncRNAs. Advances in artificial intelligence, single-cell sequencing, and structural modeling promise to overcome current limitations. Here are some promising directions:

• Integrative Analysis: Combining multi-omics data to understand the interplay of lncRNAs with other biomolecules.
• CRISPR Screens: Leveraging bioinformatics to design CRISPR-based functional screens for lncRNAs.
• Therapeutic Development: Using bioinformatics to design lncRNA-based therapeutics, including antisense oligonucleotides and RNA interference tools.

Conclusion

lncRNAs are the hidden gems of the genome, and bioinformatics is the key to unearthing their full potential. As research progresses, lncRNAs could pave the way for novel diagnostics, targeted therapies, and personalized medicine, revolutionizing our approach to complex diseases.

The journey into the world of lncRNAs is only beginning, and bioinformatics will continue to play a pivotal role in decoding these molecular mysteries. Whether you’re a researcher, clinician, or bioinformatics enthusiast, the study of lncRNAs offers a fascinating frontier of discovery.

Address of the bookmark: http://www.genengnews.com/keywordsandtools/print/3/32115/

1 Falcon https://github.com/PacificBiosciences/pb-assembly

2 Canu assembler http://canu.readthedocs.io/en/latest/index.html

3 Miniasm assembler https://github.com/lh3/miniasm

4 PBJelly scaffolding tool https://sourceforge.net/projects/pb-jelly/

5 ARCS scaffolding tool https://github.com/bcgsc/arcs

6 Redundans reduction and scaffolding tool https://github.com/Gabaldonlab/redundans

7 Arrow error correction https://github.com/PacificBiosciences/ GenomicConsensus

8 PILON error correction https://github.com/broadinstitute/pilon/wiki

9 BUSCO single copy gene markers http://busco.ezlab.org/

10 Bandage graph assembly viewer https://rrwick.github.io/Bandage/

11 Gepard dotter http://cube.univie.ac.at/gepard

12 MUMmer aligner and plotter http://mummer.sourceforge.net/

https://github.com/gaitat/GenomeUPlot

Address of the bookmark: https://github.com/gaitat/GenomeUPlot

• Step 1. Run mugsy to get multiple sequence alignment results.
• Step 2 & 3. Extraction of the Coordinates of Core Blocks, Construction of Synteny Blocks and Generating Signed Permutations.
• Step 4. Generate pairwise genome rearrangement scenarios and find repeats at the breakpoints of each rearrangement events.

https://github.com/DanwangJessica/GRSR

Address of the bookmark: https://github.com/DanwangJessica/GRSR

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

ftp://ftp.ncbi.nih.gov/genomes/

https://hgdownload.soe.ucsc.edu/downloads.html

Address of the bookmark: ftp://ftp.ncbi.nih.gov/genomes/

Address of the bookmark: http://www.vital-it.ch/