index.Rmd

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title: The RNA landscape of the human placenta in health and disease 
author:
  - name: Sungsam Gong
    affil: 1
    orcid: '0000-0001-5796-4423'
  - name: Francesca Gaccioli
    affil: 1 
  - name: Justyna Dopierala
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  - name: Ulla Sovio 
    affil: 1
  - name: Gordon Smith 
    affil: 1
  - name: D Stephen Charnock-Jones 
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affiliation:
  - num: 1
    address: Department of Obstetrics and Gynaecology, University of Cambridge</br>NIHR Cambridge Biomedical Research Centre, Cambridge, United Kingdom 
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bibliography: myRef.bib
---

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```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
```

# Introduction
## Motivations
1. Placental dysfunction underlies a large proportion of maternal and perinatal morbidity and mortality, which is a half the total burden due to cancer.
2. The placental tissues are under-represented (or none) in multi-omics projects (e.g. GTEx; RoadMap).
3. Publicly available placenta transcrptome data lack the depth of coverage and the sample number.

# Materials & Methods 
1. 302 placental biopsies of the POP Study cohort[@PMID:19019223;@PMID:26360240;@PMCID:PMC5701771], of which 94 and 56 are from cases of preeclampsia (PE) and fetal growth restriction (FGR).
2. 324 total RNA-Seq datasets (~102 million reads per sample) 
3. 328 small RNA-Seq datasets (~20 million per sample)
4. TopHat2, StringTie and Cuffcompare

```{r fig1-sample, out.width="87%", fig.align='center', fig.cap="Number of placental biopsies and sequencing reads"}
knitr::include_graphics('Figures/SI.Fig1.jpeg')
```

# Results

## 1. Relative abundance and complexity of long and short RNAs in the placenta 
```{r fig2-complexity, out.width="88%", fig.align='center', fig.cap='Complexity of RNA transcripts in the placenta'}
knitr::include_graphics('Figures/complexity.jpg')
```

## 2. Genes expressed specifically in the placenta
```{r placenta-specific, out.width="87%", fig.align='center', fig.cap='Abundance level of genes expressed specifically in the placenta (a: protein-coding, b: lincRNA)'}
knitr::include_graphics('Figures/placenta_specific.jpg')
```

## 3. Highly abundant circular RNAs and short RNAs 
```{r fig3-manhattan, out.width="90%", fig.align='center', fig.cap='Manhattan plots showing relative abundance of short RNAs'}
knitr::include_graphics('Figures/manhattan.jpg')
```

## 4. A putative miRNA sponge 
```{r fig4-circRNA, out.width="100%", fig.align='center', fig.cap='A putative miRNA sponge and its targets miRNAs (sorry, data at non-disclosure stage)'}
knitr::include_graphics('Figures/circ_sponge.jpg')
```

## 5. Size distribution of placental small RNAs  
```{r fig5-smallRNA, out.width="73%", fig.align='center', fig.cap='Size distribution of placental small RNAs. (‘Mapped reads’: mapped at least 10x, ‘-miRNA’: ‘Mapped reads’ minus miRNA, ‘-miRNA-piRNA-exon’: ‘Mapped reads’ minus miRNA, piRNAs and exon)'}
knitr::include_graphics('Figures/smallRNA_size.jpg')
```

# Conclusions
1. More than 300 well phenotyped placentas sequenced to high depth.  
2. High quality data with strand-specific total-RNA (not poly-A+ selected).
3. Circular RNAs were characterised in the placenta.

# Data availability
* Manuscript in submission
* https://sung.github.io/Placenta_Transcriptome_GI2019 (this poster)
* https://www.obgyn.cam.ac.uk/placentome (will be open to public soon)
* https://www.ebi.ac.uk/ega/studies/EGAS00001002205

# References