Direct Lineage Reprogramming: Novel Factors involved in Lineage ReprogrammingAhmed Madni
Direct linage reprogramming has got a major focus in biomedical field. The production of specific functional cell type from totally different cell lineage is called lineage reprogramming. In other words, it is induction of functional cell type from another linage without passing through intermediate stage of pluripotent.
Direct Lineage Reprogramming: Novel Factors involved in Lineage ReprogrammingAhmed Madni
Direct linage reprogramming has got a major focus in biomedical field. The production of specific functional cell type from totally different cell lineage is called lineage reprogramming. In other words, it is induction of functional cell type from another linage without passing through intermediate stage of pluripotent.
Brief Introduction of Protein-Protein Interactions (PPIs)Creative Proteomics
For more information, please visit https://www.creative-proteomics.com/services/protein-protein-interaction-networks.htm. Protein-protein interactions play important roles in various biological processes. PPIs can be classified based on different factors, including composition, affinity, and lifetime.
Brief Introduction of Protein-Protein Interactions (PPIs)Creative Proteomics
For more information, please visit https://www.creative-proteomics.com/services/protein-protein-interaction-networks.htm. Protein-protein interactions play important roles in various biological processes. PPIs can be classified based on different factors, including composition, affinity, and lifetime.
A brief introduction to two techniques used to study protein interactions: Yeast two hybrid (Y2H) system and Chromatin immunoprecipitation(ChIP)
I hope it helps and please comment if I've made any mistakes.
This presentation consists of topics related to oncogene, proto oncogene, Tumor suppresor gene, Ras gene family and structure and functions of tumor suppressor gene.
COMPETENCY 3Integrate credible and relevant sources into coursewLynellBull52
COMPETENCY 3
Integrate credible and relevant sources into coursework to enhance clarity and support claims.
CRITERION
Reflect on how credibility and relevance of a chosen resource were determined.
Your result: Non-Performance
Distinguished
Reflects on how credibility and relevance of a chosen resource were determined. Notes how specific aspects of the assessment were used to determine relevance.
Proficient
Reflects on how credibility and relevance of a chosen resource were determined.
Basic
Explains the concepts of credibility and relevance in general terms, but does not specifically address how this was used to determine if the specific resource was credible and relevant.
Non-Performance
Does not explain the concepts of credibility and relevance in general terms.
Faculty Comments:
I did not see a discussion of source credibility/relevance. For this assignment you were are also required to locate an article in the library about time organizing strategies (outlined in Part I). Then, you were asked in Part II to reflect on how you determined the credibility and relevance of your chosen library resource to support your task prioritization.
ONCOLOGY LETTERS 19: 595-605, 2020
Abstract. Numerous types of molecular mechanisms mediate
the development of cancer. Non-coding RNAs (ncRNAs) are
being increasingly recognized to play important role in medi-
ating the development of diseases, including cancer. Long
non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are
the two most widely studied ncRNAs. Thus far, lncRNAs are
known to have biological roles through a variety of mecha-
nisms, including genetic imprinting, chromatin remodeling,
cell cycle control, splicing regulation, mRNA decay and
translational regulation, and miRNAs regulate gene expres-
sion through the degradation of mRNAs and lncRNAs.
Although ncRNAs account for a major proportion of the total
RNA, the mechanisms underlying the physiological or patho-
logical processes mediated by various types of ncRNAs, and
the specific interaction mechanisms between miRNAs and
lncRNAs in various physiological and pathological processes,
remain largely unknown. Thus, further research in this field
is required. In general, the interaction mechanisms between
miRNAs and lncRNAs in human cancer have become
important research topics, and the study thereof has led to
the recent development of related technologies. By providing
examples and descriptions, and performing chart analysis, the
present study aimed to review the interaction mechanisms and
research approaches for these two types of ncRNAs, as well
as their roles in the occurrence and development of cancer.
These details have far‑reaching significance for the utilization
of these molecules in the diagnosis and treatment of cancer.
Contents
1. Introduction
2. Interactions between lncRNAs and miRNAs
3. Methods of research in to lncRNAs and miRNAs
4. lncRNAs and miRNAs in cancer
5. Conclusion
1. Introduction
In 1993, Lee e ...
Light Regulates Plant Alternative Splicing through the Control of Transcripti...ShreyaMandal4
This slide presentation introduces the world of Regulatory aspects of light i.e one critical source of energy on Post Transcriptional processing in plants
Austin Neurology & Neurosciences is an open access, peer reviewed, scholarly journal dedicated to publish articles covering all areas of Neurology & Neurological Sciences.
The journal aims to promote research communications and provide a forum for doctors, researchers, physicians and healthcare professionals to find most recent advances in all areas of Neurology & Neurological Sciences. Austin Neurology & Neurosciences accepts original research articles, reviews, mini reviews, case reports and rapid communication covering all aspects of neurology & neurosciences.
Austin Neurology & Neurosciences strongly supports the scientific up gradation and fortification in related scientific research community by enhancing access to peer reviewed scientific literary works. Austin Publishing Group also brings universally peer reviewed journals under one roof thereby promoting knowledge sharing, mutual promotion of multidisciplinary science.
Architecture of the human regulatory network derived from encode dataAnax Fotopoulos
Transcription factors bind in a combinatorial fashion to specify the on-and-off states of genes; the ensemble of
these binding events forms a regulatory network, constituting the wiring diagram for a cell. To examine the
principles of the human transcriptional regulatory network, we determined the genomic binding information of
119 transcription-related factors in over 450 distinct experiments. We found the combinatorial, co-association of
transcription factors to be highly context specific: distinct combinations of factors bind at specific genomic locations.
In particular, there are significant differences in the binding proximal and distal to genes. We organized all the
transcription factor binding into a hierarchy and integrated it with other genomic information (for example,
microRNA regulation), forming a dense meta-network. Factors at different levels have different properties; for
instance, top-level transcription factors more strongly influence expression and middle-level ones co-regulate
targets to mitigate information-flow bottlenecks. Moreover, these co-regulations give rise to many enriched
network motifs (for example, noise-buffering feed-forward loops). Finally, more connected network components
are under stronger selection and exhibit a greater degree of allele-specific activity (that is, differential binding to the
two parental alleles). The regulatory information obtained in this study will be crucial for interpreting personal genome
sequences and understanding basic principles of human biology and disease.
Genomics, Transcriptomics, Proteomics, Metabolomics - Basic concepts for clin...Prasenjit Mitra
This set of slides gives an overview regarding the various omics technologies available and how they can be used for improvement in clinical setting or research
Yeast two hybrid system / protein-protein interaction
POSTER FINAL
1. THE ROLE OF PRION-LIKE PROTEINS IN HUMAN DISEASES: TAF15 AND HNRPDL
JÚLIA VENTURA MOLINA
(JUNE 2014)
Basis of the algorithms for prion-like domains prediction
Unlike traditional algorithms designed to identify aggregation-prone
amyloidogenic regions, these algorithms are based on the amino acid
propensity from a set of yeast protein sequences. Those sequences do not
share sequential characteristics common to β-sheet-amyloid forming regions.
Prion-like domains (PrLD) Algorithms
Putative Prion-like containing proteins
1 2
4
3
Introduction: Prions are proteins that induce a variety of infectious self-templating amyloid forms. Able to confer phenotypic changes between individuals and even
between species, promoting survival by generating diverse and heritable phenotypic traits in response to specific environmental stress. Priogenicity is not due to the protein
structure but to the amino acid composition sequence. Strikingly, approximately 1% of human proteins harbour a Prion-Like domain (PrLD) of similar low complexity sequence
and amino acid composition to priogenic domains of yeast proteins. The low complexity sequence is enriched in glycine as well as the uncharged polar amino acids (asparagine,
glutamine, tyrosine and serine). The 20% of PrLD-containing proteins are RNA-binding proteins, transcription factors and granule assembly RNP mediators. The PrLD is required
for optimal RNA-binding proteins functionality, that’s the reason of why are so common in this kind of proteins: are necessary for alternative splicing activity, stable RNA binding
and for optimal RNA annealing activity and also mediate protein-protein interactions.
References:
[1] Couthouis et al. A yeast functional screen predicts new candidate ALS disease genes. PNAS, December 27, 2011; Vol.108 Nº 52
[2] Vladimir Espinosa et al. PrionScan: an online database of predicted prion domains in complete proteomes. BMC Genomics, 2014; 15:102
[3] Jenny Blechingberg et al. FET-proteins in Stress and Transcription. Gene Expression Responses to FUS, EWS, and TAF15 Reduction and
Stress Granule Sequestration Analyses Identifies FET- Protein non-Redundant Functions. PLOS ONE, September 2012; Vol. 7, Issue 9.
[4] Adelene Y. Tan and James L. Manley. The TET family proteins: Functions and Roles in disease. Journal of cell biology, September 24, 2009;
doi: 10.1093, Vol. 1, Nº 82-92.
Algorithm Window-size Basis Rank of values
PAPA 41 amino acids • According to FoldIndex
• Q/N-rich domains
From 0.5 to -1
PrionScan 60 amino acids 29 yeast protein sequences From 100 to
threshold (-50).
y
=
0.598x
+
148.25
R²
=
0.44858
0
500
1000
1500
2000
2500
3000
3500
4000
4500
0
1000
2000
3000
4000
5000
PrionScan
PAPA
(LOCATION)
y = 144.87x - 8.7841
R² = 0.01396
-‐50.000
-‐30.000
-‐10.000
10.000
30.000
50.000
70.000
90.000
110.000
130.000
0
0.05
0.1
0.15
0.2
0.25
PrionScan
PAPA
(SCORE)
PrLD
mechanism
Cellular
interaction/
signaling
RNP
granules
Cancer
Bet-
hedging
Amyloid
diseases
Subcellular
shuttling
Q/N-rich NLSRRM ZFN Q/N-rich
Misfolded protein FOLDING
FIBRILLATION
Different strains
of fibrilsNative structure
Free
Energy
Amyloid fibers Amyloid plaque
Native protein
STRESS
CONDITIONS
C- TerN- Ter
Mechanisms
Features
Transcription and splicing coupling
Roles in transcription Roles in splicing
• TET family proteins function in
RNAP II transcription by
interacting with TFIID and
subunits of RNAP II itself
(Rbp3,5,7).This association
affects:
1) Promoters choice
2) Recruitment of RNA
processing factors
• N-Ter acts as a transcriptional
activator when fused to DNA-
binding domains.
• The C-Ter of the TET
family proteins is able
to interact with
splicing factors
affecting the patters
of alternative splicing.
It’s possible that connect
transcription and splicing,
since the N-Ter mediates
interactions with RNAP II
and the C- Ter binds to
specific splicing factors.
So may recruit splicing
factors to the RNAP II,
which coordinates
pre-mRNA processing
events.
TAF15 domains organization
• TAF15 RNAP II gene encodes a member of the
FET family of RNA-binding proteins.
• Have been recently a focus of study due to its
similarity to other RNA-binding proteins
involved in severe diseases and for the evidence
of prion-like behaviour.
RRM
Plays an essential role in TAF15 subcellular localization:
It’s controled by Post-transcriptional modifications
that regulate RNA binding or protein-protein
interactions. It’s a common domain among proteins
involved in post-transcription regulation.
Q/N-
rich
Involved in DNA-binding, leads chromosomal
translocations: functioning like a transcription
activation domain. These events are considered
cancer-driving forces.
ZFN A single-stranded RNA recognitioon domain.
NLS
TAF15 PY-motif within the C-Ter, responsible for
nuclear retention.
Most mutation disease-linked were found to affect the
NLS.
Related diseases
Associated mutations
Associated
diseases
TAF15 in disease development
Cancer
(Acute Leukemia,
Extraskeletal myxoid
chondrosarcoma)
• Involved in differentiation, stress response and cell
spreading.
• Chromosomal translocations: The fusion joins the
N-Ter domain to various DNA-binding proteins,
functioning like a transcriptional activation domain.
Amyloid diseases
(Familial Amyotrophic
Lateral Sclerosis,
Frontotemporal lobular
dementia)
• Have been shown that numerous RNA-binding
proteins, harbouring a prion-like domain, are
involved in several amyloid diseases forming part of
insoluble aggregates. Mutations in these proteins
alter RNA metabolism homeostasis.
• The multifunctionality of prion-like containing proteins makes
them vulnerable targets for cancer-causing as such events
could affect several cellular control systems simultaneously.
Because are on the top of the regulation network, and are
essential to maintain RNA metabolism homeostasis.
• The development of bioinformatics tools is essential to
identify new putative candidates. Hopefully, further studies
of RNA‑binding proteins containing PrLD and sharing similar
structure would provide a conceptual framework for testing
hypotheses about the role of RNA‑binding proteins in
pathogenesis.
• Although there are many more questions to be answered
about prion-mechanisms, these studies have opened up new
avenues for therapeutic interventions in neurodegenerative
disorders.
HNRPDL predicted by PAPA algorithm (shown in the following figure) is a putative PrLD
protein since when analyzing structure and interaction partners we find out many
features overlapping with those observed in FET-family proteins.
Conclusions
FET family proteins: TAF15
5PAPA prediction: HNRPDL
Stress
Response
MUTATIONS
Due to algorithms are based on different criteria, to obtain significant results we
make a position and score correlation. It seems (as shown in the graphs above) that
using a higher threshold, then discarding the proteins lower valued, the position
correlation would be linear.
Domains
ds/ssDNA binding
HuR nucleocytoplasmic shuttling
RRM
NLS
poliA/G binding protein
Gly/Tyr-rich
Some recent studies
are paying attention
on identifying TAF15
variants related with
pathological amyloid
inclusions.
A