Re: Abstract for SAMSI meeting, Opening workshop '14 (i0samsi)

Abstract for
http://www.samsi.info/bio-ow

Human Genome Analysis

The ENCODE and modENCODE consortia have generated a resource
containing large amounts of transcriptomic data, extensive mapping of
chromatin states, as well as the binding locations of over 300
transcription-regulatory factors for human, worm and fly. The consortium performed
extensive data integration by constructing genome-wide co-expression
networks and transcriptional regulatory models, revealing fundamental
principles of transcription and network organization that are
conserved across the three highly divergent animals. 

I will give an overview of the data and some of the key analyses. 

In particular:

(1) A novel cross-species clustering algorithm to
integrate the co-expression networks of the three species, resulted at
conserved modules shared between the organisms. These modules are
enriched in developmental genes and exhibited hourglass behavior. 

(2) A global optimization algorithm to examine the
hierarchical organization of the regulatory network. 

Despite extensive rewiring of binding targets, high-level organization
principles such as a three-layer heirarchy are conserved across the
three species.

(3) The gene expression levels in the organisms, both coding
and non-coding, can be predicted consistently based on their upstream
histone marks. In fact, a "universal model" with a single set of
cross-organism parameters can predict expression level for both protein
coding genes and ncRNAs.

(4) Their have been many analyses of pseudogenes. 

(5) Finally, the extent of the non-coding, non-canonical
transcription is consistent between worm, fly and human.

encodenets.gersteinlab.org
encodeproject.org/comparative

Abstract for SAMSI meeting, Opening workshop '14 (i0samsi)

Abstract for

http://www.samsi.info/bio-ow

Human Genome Analysis

The ENCODE and modENCODE consortia have generated a resource
containing large amounts of transcriptomic data, extensive mapping of
chromatin states, as well as the binding locations of over 300
transcription-regulatory factors for human, worm and fly. We performed
extensive data integration by constructing genome-wide co-expression
networks and transcriptional regulatory models, revealing fundamental
principles of transcription and network organization that are
conserved across the three highly divergent animals. In particular:

(1) We developed a novel cross-species clustering algorithm to
integrate the co-expression networks of the three species, resulted at
conserved modules shared between the organisms. These modules are
enriched in developmental genes and exhibited hourglass behavior. They
were then used to align the stages in worm and fly development,
finding the normal embryo-to-embryo and larvae-to-larvae pairings in
addition to a novel pairing between worm embryo and fly pupae.

(2) We developed a global optimization algorithm to examine the
hierarchical organization of the regulatory network. We found that,
despite extensive rewiring of binding targets, high-level organization
principles such as a three-layer heirarchy are conserved across the
three species.

(3) We found the gene expression levels in the organisms, both coding
and non-coding, can be predicted consistently based on their upstream
histone marks. In fact, a "universal model" with a single set of
cross-organism parameters can predict expression level for both protein
coding genes and ncRNAs.

(4) Carrying out the same type of "predictions" for TFs,
we found that information in their binding is more localized to near the TSS
region than that of histone marks but is largely redundant with that
of the marks. Surprisingly, only a small number of TFs are necessary in the models
to successfully predict expression (e.g. ~5 of the >1000 in human).

(5) Finally, we found that the extent of the non-coding, non-canonical
transcription is consistent between worm, fly and human.

encodenets.gersteinlab.org

encodeproject.org/comparative

Re: Abstract for talk BioConference Live August 2014 Genetics and Genomics (i0bioconfweb0mg)

yes


On Mon, Aug 18, 2014 at 5:18 PM, Don Cruikshank
<don.cruikshank@labroots.com> wrote:
> Thanks Mark. I take it that you want us to replace the abstract that we already received from you???
>
> Don
>
> -----Original Message-----
> From: Mark Gerstein [mailto:mark@gersteinlab.org]
> Sent: Monday, August 18, 2014 1:47 PM
> To: Don Cruikshank
> Cc: glabstracts.mbglab@blogger.com; x57v@gersteinlab.org
> Subject: Abstract for talk BioConference Live August 2014 Genetics and Genomics (i0bioconfweb0mg)
>
> The ENCODE and modENCODE consortia have generated a resource containing large amounts of transcriptomic data, extensive mapping of chromatin states, as well as the binding locations of >300 transcription factors (TFs) for human, worm and fly. We performed extensive data integration by constructing genome-wide co-expression networks and transcriptional regulatory models, revealing fundamental principles of transcription conserved across the three highly divergent animals.
> In particular, we found the gene expression levels in the organisms, both coding and non-coding, can be predicted consistently based on their upstream histone marks. In fact, a "universal model" with a single set of cross-organism parameters can predict expression level for both protein coding genes and ncRNAs. Carrying out the same type of "predictions" for TFs, we found that information in their binding is more localized to near the TSS region than that of histone marks but is largely redundant with that of the marks.
> Surprisingly, only a small number of TFs are necessary in the models to successfully predict expression (e.g. ~5 of the >1000 in human).
>
>
> hashtag #BCLgenetics for this event
>
> http://www.bioconferencelive.com/events.php?event_id=17
>

RE: Abstract for talk BioConference Live August 2014 Genetics and Genomics (i0bioconfweb0mg)

Thanks Mark. I take it that you want us to replace the abstract that we already received from you???

Don

-----Original Message-----
From: Mark Gerstein [mailto:mark@gersteinlab.org]
Sent: Monday, August 18, 2014 1:47 PM
To: Don Cruikshank
Cc: glabstracts.mbglab@blogger.com; x57v@gersteinlab.org
Subject: Abstract for talk BioConference Live August 2014 Genetics and Genomics (i0bioconfweb0mg)

The ENCODE and modENCODE consortia have generated a resource containing large amounts of transcriptomic data, extensive mapping of chromatin states, as well as the binding locations of >300 transcription factors (TFs) for human, worm and fly. We performed extensive data integration by constructing genome-wide co-expression networks and transcriptional regulatory models, revealing fundamental principles of transcription conserved across the three highly divergent animals.
In particular, we found the gene expression levels in the organisms, both coding and non-coding, can be predicted consistently based on their upstream histone marks. In fact, a "universal model" with a single set of cross-organism parameters can predict expression level for both protein coding genes and ncRNAs. Carrying out the same type of "predictions" for TFs, we found that information in their binding is more localized to near the TSS region than that of histone marks but is largely redundant with that of the marks.
Surprisingly, only a small number of TFs are necessary in the models to successfully predict expression (e.g. ~5 of the >1000 in human).


hashtag #BCLgenetics for this event

http://www.bioconferencelive.com/events.php?event_id=17

Abstract for talk BioConference Live August 2014 Genetics and Genomics (i0bioconfweb0mg)

The ENCODE and modENCODE consortia have generated a resource
containing large amounts of transcriptomic data, extensive mapping of
chromatin states, as well as the binding locations of >300
transcription factors (TFs) for human, worm and fly. We performed
extensive data integration by constructing genome-wide co-expression
networks and transcriptional regulatory models, revealing fundamental
principles of transcription conserved across the three highly divergent animals.
In particular, we found the gene expression levels in the organisms, both coding
and non-coding, can be predicted consistently based on their upstream
histone marks. In fact, a "universal model" with a single set of
cross-organism parameters can predict expression level for both protein
coding genes and ncRNAs. Carrying out the same type of "predictions" for TFs,
we found that information in their binding is more localized to near the TSS
region than that of histone marks but is largely redundant with that
of the marks.
Surprisingly, only a small number of TFs are necessary in the models
to successfully predict expression (e.g. ~5 of the >1000 in human).


hashtag #BCLgenetics for this event

http://www.bioconferencelive.com/events.php?event_id=17

Abstract for Talk at Beyond the Genome (i0beyond)

Abstract for
http://www.beyond-the-genome.com/2014/

Human Genome Analysis

Plummeting sequencing costs have led to a great increase in the number
of personal genomes. Interpreting the large number of variants in
them, particularly in non-coding regions, is a central challenge for
genomics. We investigate patterns of selection in DNA elements from
the ENCODE project using the full spectrum of sequence variants from
1,092 individuals in the 1000 Genomes Project Phase 1, including
single-nucleotide variants (SNVs), short insertions and deletions
(indels) and structural variants (SVs). We analyze both coding and
non-coding regions, with the former corroborating the latter. We
identify a specific sub-group of non-coding categories that exhibit
very strong selection constraint, comparable to coding genes:
"ultra-sensitive" regions. We also find variants that are disruptive
due to mechanistic effects on transcription-factor binding (i.e.
"motif-breakers").

We make great use of networks -- contrasting them with linear
annotation -- and describe how we construct a practical instantiation
of the human regulatory network. Using connectivity information
between elements from protein-protein interaction and regulatory
networks, we find that variants in regions with higher network
centrality tend to be deleterious. Indels and SVs follow a similar
pattern as SNVs, with some notable exceptions (e.g. certain deletions
and enhancers).

Using these results, we develop a scheme and a practical tool to
prioritize non-coding variants based on their potential deleterious
impact. As a proof of principle, we experimentally validate and
characterize a small number of candidate variants prioritized by the
tool. Application of the tool to ~90 cancer genomes (breast, prostate
and medulloblastoma) reveals ~100 candidate non-coding cancer drivers.
This approach can be readily used in precision medicine to prioritize
variants.


References

Architecture of the human regulatory network derived from ENCODE data.
Gerstein et al. Nature 489: 91
[encodenets.gersteinlab.org]

Interpretation of genomic variants using a unified biological network approach.
E Khurana, Y Fu, J Chen, M Gerstein (2013). PLoS Comput Biol 9: e1002886.

Integrative annotation of variants from 1,092 humans: application to
cancer genomics
E Khurana et al. (2013) Science 342:1235587.
[funseq.gersteinlab.org]

Abstract for Epigenomics-Boston-2014 Summit (i0epi14)

Abstract for
http://www.beyond-the-genome.com/2014/program

Human Genome Analysis

The ENCODE and modENCODE consortia have generated a resource
containing large amounts of transcriptomic data, extensive mapping of
chromatin states, as well as the binding locations of over 300
transcription-regulatory factors for human, worm and fly. We performed
extensive data integration by constructing genome-wide co-expression
networks and transcriptional regulatory models, revealing fundamental
principles of transcription and network organization that are
conserved across the three highly divergent animals. In particular:

(1) We developed a novel cross-species clustering algorithm to
integrate the co-expression networks of the three species, resulted at
conserved modules shared between the organisms. These modules are
enriched in developmental genes and exhibited hourglass behavior. They
were then used to align the stages in worm and fly development,
finding the normal embryo-to-embryo and larvae-to-larvae pairings in
addition to a novel pairing between worm embryo and fly pupae.

(2) We developed a global optimization algorithm to examine the
hierarchical organization of the regulatory network. We found that,
despite extensive rewiring of binding targets, high-level organization
principles such as a three-layer heirarchy are conserved across the
three species.

(3) We found the gene expression levels in the organisms, both coding
and non-coding, can be predicted consistently based on their upstream
histone marks. In fact, a "universal model" with a single set of
cross-organism parameters can predict expressionlevel for both protein
coding genes and ncRNAs.

(4) Finally, we found that the extent of the non-coding, non-canonical
transcription is consistent between worm, fly and human.

encodenets.gersteinlab.org