Showing posts with label Publications. Show all posts
Showing posts with label Publications. Show all posts

March 19, 2021

Publication: High-throughput miRNA-sequencing of the human placenta: expression throughout gestation

High-throughput miRNA-sequencing of the human placenta: expression throughout gestation
Epigenomics, 2021 July; 13(13):995-1012. doi: 10.2217/epi-2021-0055. Epub 2021 May 25.

  • Next generation sequencing of small RNAs in human placenta, with emphasis on microRNAs (miRNAs)
  • N=113 late first trimester placenta samples from leftover tissue after chorionic villus sampling ("CVS", a prenatal diagnostic test)
    • This is the earliest timepoint that we can directly study human placenta in continuing (non-termination) pregnancies.
    • Chorionic villi are stringy tissue that grow on the outside of the placenta to maximize surface area with maternal tissue. They share the same genetics as the fetus.
  • N=47 third trimester placenta samples collected after delivery
  • miRNA profiles of:
    • All expressed miRNAs, normalized counts over 10
      • We considered lower expression thresholds, but expression was inconsistent across all patients
    • Similarly expressed miRNAs, P>=0.05, fold-change<=2, normalized counts>10
      • These miRNAs are fairly consistently expressed between first and third trimester
      • They are not significantly different between first and third trimester
      • Their expression may be altered by other variables (e.g. patient health, environmental factors, any developmental differences that affect pregnancy outcomes) - for future research!
    • Differentially expressed miRNAs (still significant after adjusting for multiple comparisons), FDR<0.05, fold-change>2, normalized counts>10
      • Note that all FDR<0.05 miRNAs are also P<0.05. The Benjamini-Hochberg false discovery rate P value adjustment is a stricter criteria than P<0.05.
      • These miRNAs change expression as the pregnancy progresses
    • Chromosome 14 and 19 microRNA cluster (C14MC, C19MC) members
      • These clusters are known to be expressed in placenta, per prior microarray studies
      • We identified many C14MC and C19MC expressed in first and third trimester, some similarly expressed and some significantly different between trimesters
      • C14MC produced some miRNAs very upregulated in first trimester
      • C19MC members were generally more highly expressed in both first and third trimester
      • Some of these miRNAs also enter maternal circulation, per prior research
    • Chromosome 13 has two small miRNA clusters significantly upregulated in first trimester placenta, with lower expression in third trimester. 
      • Two C13MC regions in human placenta identified for the first time

Authors:

Tania L Gonzalez,  Laura E Eisman, Nikhil V Joshi, Amy E Flowers, Di Wu, Yizhou Wang, Chintda Santiskulvong, Jie Tang, Rae A Buttle, Erica Sauro, Ekaterina L Clark, Rosemarie DiPentino, Caroline A Jefferies, Jessica L Chan, Yayu Lin,  Yazhen Zhu,  Yalda Afshar,  Hsian-Rong Tseng, Kent Taylor, John Williams III,  Margareta D Pisarska

Links:

August 15, 2020

Publication: Sexually dimorphic crosstalk at the maternal-fetal interface

Tianyanxin Sun*, Tania L Gonzalez*, Nan Deng, Rosemarie DiPentino, Ekaterina L Clark, Bora Lee, Jie Tang, Yizhou Wang, Barry R Stripp, Changfu Yao, Hsian-Rong Tseng, S Ananth Karumanchi, Alexander F Koeppel, Stephen D Turner, Charles R Farber, Stephen S Rich, Erica T Wang, John Williams, III, Margareta D Pisarska. 

"Sexually dimorphic crosstalk at the maternal-fetal interface". The Journal of Clinical Endocrinology & Metabolism, 105(12): e4831-e4847, 2020https://doi.org/10.1210/clinem/dgaa503

*Co-first authors.

Links

  • PubMed ID: 32772088
  • Journal of Clinical Endocrinology & Metabolism research article
    • Receptor-ligand gene expression
    • Cell markers of placenta cell types
    • Cell markers of trophoblast cell types within placenta (subanalysis)
    • Gene expression differences due to fetal sex
  • Preprint at bioRxiv
    • Includes additional information about the bulk RNA-seq of first trimester maternal-fetal interface using matched maternal decidua and placenta (CVS) RNA-seq
    • Includes additional details about the single cell RNA-seq tSNE plots and cell developmental trajectories
  • Sequencing data deposited into NCBI GEO superseries GSE131875
    • GSE131696: Single cell RNA-sequencing of CVS samples
      • N=6 placenta at late first trimester, 3 female and 3 male
      • See preprint for extended details on the cell differentiation trajectory of cytotrophoblasts (stem cell-like) into extravillous trophoblasts (migratory/invasive cells) and syncytiotrophoblasts (multi-nuclei fused cells that act as a protective barrier in placenta).
    • GSE131874: Total RNA-sequencing of matched maternal decidua and CVS tissue
      • N=4/group, 2 pregnancies with female fetus, 2 pregnancies with male fetus
      • N=8 samples total, 4 placenta and 4 decidua from 4 pregnancies
      • See preprint for matched CVS vs decidua differential gene expression analysis
      • We did not focus on this as much in the published version
    • All pregnancies continued to full term delivery & live births
  • Supplemental Figures deposited into FigShare.com
    • Collection: https://doi.org/10.6084/m9.figshare.c.4741742.v2
    • Figure S1 = PCA plot of matched chorionic villi and maternal decidua (bulk RNA-seq)
    • Figure S2 = Heatmaps of differentially expressed genes from pairwide comparison of placental cell clusters (single cell analysis)
    • Table S1 = Patient demographics and pregnancy outcomes
      • 4 pregnancies for bulk RNA-seq
      • 6 pregnancies for single cell RNA-seq
      • 7 pregnancies for immunohistochemistry to validate single cell RNA-seq
    • Table S2 = Placental cell markers from single cell RNA sequencing
    • Table S3 = Placental cell type-specific sexually dimorphic genes
    • Table S4 = Placenta receptors and ligands sexually dimorphic in both bulk and single cell RNA sequencing
    • Table S5 = Trophoblast subcluster markers in human first trimester
    • Links to figshare.com are correct in the final published version, but not the pre-proof PubMed Central version.


January 31, 2019

Publication: Early placenta gene expression from pregnancies with vs without infertility treatments

Differential gene expression during placentation in pregnancies conceived with different fertility treatments compared with spontaneous pregnancies.

Lee B, Koeppel AF, Wang ET, Gonzalez TL, Sun T, Kroener L, Lin Y, Joshi NV, Ghadiali T, Turner SD, Rich SS, Farber CR, Rotter JI, Ida Chen YD, Goodarzi MO, Guller S, Harwood B, Serna TB, Williams J 3rd, Pisarska MD.

Fertility and Sterility. 2019 Jan 2. pii: S0015-0282(18)32200-3. doi: 10.1016/j.fertnstert.2018.11.005.

Links


Layman's summary

One big question in maternal-fetal health research is: how do fertility treatments affect the baby's health and biology? There's some mixed evidence that babies born with the help of fertility treatments may have lower birth weights (though we didn't find this), higher risk of pregnancy complications, and greater risk of metabolic issues later in life. Are these differences due to the parents' innate biology (whatever led to the infertility in the first place) or due to the medical treatments?

To help figure this out, we compared placenta tissue from ongoing pregnancies to see if there were RNA differences between three groups: spontaneous (no infertility), NIFT (non-IVF fertility treatments, e.g. medicine to help stimulate ovulation), and IVF pregnancies. We got RNA from placenta tissue leftover after a late first trimester test called "chorionic villus sampling" (CVS). It is a prenatal diagnostic test that takes a very small biopsy of the placenta to indirectly check the baby's genetics and make sure the pregnancy is healthy. Using CVS tissue gives us a unique opportunity to study first trimester gene expression in pregnancies that lead to live births.

Results and discussion: Only a few individual genes were significantly different between groups, probably because there was a lot of variability within the patient groups. This is good news since it means that gene expression in late first trimester was pretty similar among all patients. We next looked for trends in pathways (groups of genes). Many immune-related pathways were significantly different in IVF vs spontaneous pregnancies, and some also different in the NIFT vs spontaneous pregnancies. Our lab is continuing to study what this means for patients.

Abstract

January 11, 2019

Publication: Maternal plasma has higher hormone levels in pregnancies conceived with infertility

Differences in First Trimester Maternal Metabolomic Profiles in Pregnancies Conceived from Fertility Treatments.

Sun T, Lee B, Kinchen J, Wang ET, Gonzalez TL, Chan JL, Rotter JI, Chen YI, Taylor K, Goodarzi MO, Rich SS, Farber CR, Williams J 3rd, Pisarska MD.

J Clin Endocrinol Metab. 2018 Nov 15. doi: 10.1210/jc.2018-01118.

Links

Highlights

  • We looked at metabolites circulating in maternal blood (specifically plasma) around late first trimester of pregnancy.
  • Hormone levels (beta-estradiol and progesterone) were higher in patients with infertility, compared to patients who did not receive fertility treatments.
  • ELISA assays with maternal plasma confirmed these results.

January 30, 2018

Publication: Sex differences in the late first trimester human placenta transcriptome

Data: Total RNA-seq of first trimester trimester placenta

Tania L. Gonzalez, Tianyanxin Sun, Alexander F. Koeppel, Bora Lee, Erica T. Wang, Charles R. Farber, Stephen S. Rich, Lauren W. Sundheimer, Rae A. Buttle, Yii-Der Ida Chen, Jerome I. Rotter, Stephen D. Turner, John WilliamsIII, Mark O. Goodarzi and Margareta D. Pisarska. Biology of Sex Differences 2018 Jan 15. Vol 9: issue 4.

Links

  • PubMed ID: 29335024
  • Biology of Sex Differences journal article [open access!]
  • NCBI GEO accession for RNA-seq data: GSE109082
  • Spreadsheet for genes above our FPKM threshold is "Additional file 2" (placenta transcriptome at time of chorionic villus sampling)
  • Spreadsheet for genes reaching our False Discovery Rate threshold is "Additional file 4" (genes significantly sex different)

December 8, 2017

August 5, 2015

Publication: Tight regulation of plant immune responses by combining promoter and suicide exon elements

Tania L. Gonzalez, Yan Liang, Bao N. Nguyen, Brian J. Staskawicz, Dominique Loqué, and Ming C. Hammond. Nucleic Acids Research 2015 Aug 18; 43(14): 7152–7161. doi: 10.1093/nar/gkv655


Links


HyP5SM model



  • Default retention of the "suicide exon" HyP5SM results in a non-productive mRNA.
  • Co-expression of OsL5 promotes protein expression of the gene of interest by altering HyP5SM splicing.
  • All parts of the HyP5SM gene expression system come from plant sequences.
  • The HyP5SM system is expected to function in all dicot plants.


What is HyP5SM and how does it regulate genes?

HyP5SM is an inducible gene regulation method for dicot plants. This method works by cloning in a DNA sequence (a splicing cassette made with hybrid monocot and dicot sequences) into your gene of interest. It is very flexible, can be inserted at various possible sites, and is not sensitive to nearby sequence. The splicing is controlled by a monocot (rice) splice factor which does not bind to the endogenous dicot homolog.

The "off" version of the RNA is degraded by nonsense mediated decay, a natural cleanup process that removes mRNAs with stop codons in the middle. This is why HyP5SM is called a "suicide exon", also sometimes referred to as a "poison exon". It is not dangerous to humans. It just results in targeted RNA breakdown by the plant, so the plant does not make the protein. HyP5SM works so well that it is able to regulate proteins that trigger plant immune responses (very sensitive phenotypes). This low background is the key benefit of HyP5SM and the reason why researchers might want to use it over inducible promoters. Inducible promoters are notoriously "leaky", showing measurable levels of protein even without induction. HyP5SM removes this background.

The "on" version of the RNA results in complete removal of the splicing cassette, and thus a protein which has no sequence alterations. Because the splicing cassette is completely removed, HyP5SM is a "traceless" gene induction system.

The HyP5SM inserted sequence is 100% of plant origin, a hybrid of endogenous Arabidopsis thaliana (dicot) and Oryza sativa (rice, monocot) P5SM sequences. There is no bacterial or other non-plant sequence required. 

I tested the sensitivity of the gene regulation by cloning HyP5SM into plant pathogen proteins to see if I could regulate the plant's effector-triggered immune responses, but the pathogen proteins are absolutely not required. They were just my genes of interest. You can use your own.


April 15, 2015

Publication: GEMM-I riboswitches from Geobacter sense the bacterial second messenger cyclic AMP-GMP

Colleen A. Kellenberger, Stephen C. Wilson, Scott F. Hickey, Tania L. Gonzalez, Yichi Su, Zachary F. Hallberg, Thomas F. Brewer, Anthony T. Iavarone, Hans K. Carlson, Yu-Fang Hsieh, and Ming C. Hammond

PNAS April 28, 2015 112 (17) 5383-5388; published ahead of print April 6, 2015 https://doi.org/10.1073/pnas.1419328112

Links


Highlight

  • We discovered a riboswitch subclass that prefers to bind cyclic AMP-GMP (cAG). Previously, it was assumed to bind cyclic di-GMP (cdiG) due to sequence similarity.
  • The anaerobic bacterium Geobacter sulfurreducens contains an operon regulated by the cAG-binding riboswitch.
  • Geobacter sulfurreducensand also produces cAG.
  • We developed a method to detect cAG inside living cells, a useful biotechnological tool to study cAG signaling.

R programming lesson #2: merging pdf files

Use R package "pdftools" to merge separate pdf into one pdf file. You will never need to use sketchy websites or pay for software ...