Third generation long-read sequencing of HIV-1 transcripts discloses cell type specific and temporal regulation of RNA splicing

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Oct 23, 2013 (3 years and 11 months ago)

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Third generation long
-
read
sequencing of HIV
-
1 transcripts
discloses cell type specific and
temporal regulation of RNA splicing

Frederic Bushman


International AIDS Meeting

Washington DC, 2012

Splicing factors prominent in
genome
-
wide siRNA
screens

HIV RNAs spliced to yield at
least 40 mRNAs

Sensitivity suggests
unexploited opportunity for
intervention?

Relevant ORFs remain to be
discovered?

Bushman et al. 2009 PLoS Path

Why Study HIV Splicing?

Approach


Amplification:

18 primer pairs



Canonical splicing



Rare splicing



New splicing

cDNA

Template Mix

Break
Emulsion

Sequence

RainDance Technologies
: Single Molecule Droplet PCR

Tewhey et al.,
Nature Biotechnology
, 2009

RainDance Technologies

b cDNA prep from infected cells

a Primer Library

Overlapping primer pairs amplify cDNA maintaining ratios

Primer

PCR

Pacific Biosciences:
Single molecule sequencing

Fixed
polymerase



Phosphate
-
labeled nucleotides

High throughput single molecule real
-
time sequencing provides long
reads, maintaining linkage between exons

Error mitigated by

1.
Alignment to 10kb HIV genome

2.
SMRTbell

approach…

www.pacificbiosciences.com

930,294 HIV sequences of up to 2629 bp

Pacific Biosciences: Sequence Output

Cell Type

Mappable
Reads

Median Raw
Read
-
length

Longest HIV
Sequence

HOS

(18,24,48hpi)

88,975

3678 bp

2105
bp

Primary CD4T

(7 donors triplicate,
48hpi)

841,319

2595 bp

2629
bp

2 Novel Splice Donors

Scott Sherrill
-
Mix

11 Novel Splice Acceptors

Scott Sherrill
-
Mix

Novel Splice Sites

Genetic Map

Exons

SD Splice Donor

SA Splice Acceptor

* site does not adhere to consensus

Complete message
population of HIV
-
1
89.6

in CD4
+

T cells


77 complete message
structures


Evidence for 36 additional
transcripts from partial
reads


Total:
113 mRNAs


19 novel transcripts
including a new completely
spliced class (~1kb)

Scott Sherrill
-
Mix

Novel Acceptor A8c

Novel splice acceptor A8c creates new ORFs in HIV
-
1
89.6

Dynamic Transcript Populations

Mutually exclusive acceptors :

Temporal, cell
-
type and intra
-
human variability

Dynamic Transcript Populations

Conclusions

Long read single molecule sequencing works
well to delineate HIV message populations

At least 113 different HIV
-
1 transcripts

1 kb class of
RNAs

prominent in HIV
89.6

Differential splicing by cell type, time after
infection, and among cells from human
subjects


Credits

Bushman laboratory

Former Bushman Lab

Collaborators

Troy Brady



Gary Wang



Charles Berry

Kyle
Bittinger




Brett
Beitzel



Sumit

Chanda

Rohini

Sinha



Mary Lewinski



John Young

Scott Sherrill
-
Mix


Astrid Schroder


Renate Koenig

Frances Male



Angela
Ciuffi




Joe
Ecker

Christian Hoffmann

Heather Marshall Rose

Craig Hyde


Nirav

Malani



Jeremy Leipzig


Mark Yeager

Brendan Kelly



Matt Culyba



Kushol

Gupta

Young Hwang



Rick Mitchell



Greg Van
Duyne

Stephanie
Grunberg

Tracy Diamond


Masahiro Yamashita

Serena
Dollive



Emily
Charlson


Mike
Emerman

Alexandra Bryson


Shannah

Roth



Francis Collins

Sam Minot



Karen Ocwieja



Philippe
Leboulch

Spencer Barton


Keshet

Ronen



Alain Fischer

Aubrey Bailey



Greg
Peterfreund


Marina
Cavazzana
-
Calvo






Rithun

Mukherjee


Salima

Hacien
-
Bey
-
Abina







Jennifer Hwang


Rik

Gijsbers







Kristine Yoder



Zeger

Debyser






Rebecca
Custers
-
Allen






RNA in infected cells is 14% viral.


Ratios among HIV message forms


HIV infection associated with
intron

retention in cellular genes

Solexa/Illumina

Hi
Seq


100 base paired end reads


2 uninfected samples

3 infected samples

HIV
89.6

in human T
-
cells


~ 1 Billion sequence reads

Both human and HIV