About me

Tania L. Gonzalez, PhD

Project Scientist at Cedars-Sinai Medical Center

Publications and Links


Current Work

Project Scientist, Cedars-Sinai Medical Center (4/2021-current)
Postdoctoral Scientist, Cedars-Sinai Medical Center (1/2016-4/2021)
Los Angeles, CA
  • Project scientist in the lab of Dr. Margareta Pisarska
    • Hybrid role: wetlab (perform experiments & train others) and drylab (bioinformatics & data visualization)
  • Placenta gene expression, genetics, epigenetics, and cell biology
  • Next generation sequencing: human genome, transcriptome, methylome, data curation and upload to NCBI GEO
  • Maternal-fetal communication (decidua, placenta, and plasma RNA-seq)
  • Pregnancy differences due to fetal sex, mode of conception (infertility treatments or natural conception), and complications (preeclampsia, placenta previa)
  • Biosafety officer, BSL2+ biosafety forms & inventory, equipment set-up & maintenance
  • Pisarska lab website

Additional education during my current position:
  • "Summer Institute in Statistical Genetics (SISG)" (7/2018, University of Washington-Seattle)
  • "Introduction to Linux and High-Performance Computing" workshops (annually 2016-2020 & 2022, Cedars-Sinai)
  • "Pluripotent Stem Cell Culture Techniques Training Course" (Oct 3-13, 2017, Cedars-Sinai)

Education

PhD: Molecular and Cell Biology, University of California, Berkeley (12/18/2015)
  • PhD candidate in the lab of Professor Ming Hammond
  • Coursework in biochemistry, biophysics, structural biology, molecular evolution, and methods and logic.
  • RNA biology, structure and biochemistry
  • Alternative splicing regulation & evaluation of novel splice product sequences
  • Synthetic biology, engineering of gene expression systems, site selection & optimization 
  • Host-pathogen interactions of plants and bacteria
  • Dissertation on alternative splicing regulation in plants. I developed a dual gene control system with an inducible promoter & a traceless splicing cassette (no change to the final protein). I created an "on/off" switch with background low enough to regulate proteins that trigger plant immune responses. My system was able to regulate the hypersensitive response of effector-triggered immunity, something which could not be properly regulated with only inducible promoters.
  • Hammond lab website (old link) - Dr Ming C Hammond moved to University of Utah
  • Cal Alumni profile page (cal.berkeley.edu)
  • Graduate student instructor for MCB 110 & MCB 110L, molecular biology course & lab
Additional off-site courses:

  • "Frontiers and Techniques in Plant Science" (Summer 2013 at Cold Spring Harbor Lab): a boot camp on the latest research and experimental techniques for plant molecular biology.



BS: Biochemistry and Molecular Cell Biology, University of California, Davis (6/10/2010)
  • Undergraduate researcher in the labs of Professors Judy Callis and Anne Britt
  • Coursework in biochemistry, genetics, microbiology, organic chemistry, plant development, virology, mathematical modeling, bioinformatics and programming (Pascal, Perl, MATLAB)
  • Britt lab website (plant biology research, 2 quarters)
  • Callis lab website (plant biochemistry research, 3 years)
  • CLIMB program (bioinformatics research training program, 1 year)  
  • Academic Assistance & Tutoring Centers (calculus tutor, 1 year) - previously called "Learning Skills Center"


Organisms studied

  • Humans
    • Transcriptomics: Total, mRNA, and small RNA-sequencing; qRT-PCR validation
    • Epigenetics: DNA methylation analysis and annotation (Infinium MethylationEPIC array), LINE-1 assay (ELISA-based global methylation assay)
    • Primary cell culture: fibroblast, epithelial cells
    • Human cell lines: HTR8/SVneo, BeWo, JEG-3, HEK293T
    • DNA/RNA/miRNA extraction from human tissue, plasma, and primary cells
      • Expert with small tissue samples and low volumes
      • Developed protocols for improved yield and quality
      • RIN > 8 (excellent RNA integrity for next generation sequencing)
    • Gene knockdowns and overexpression, western blotting, qRT-PCR, etc.
    • Biosafety level 2+ (BSL2+) regulations, inventory, and paperwork
      • Prepared lab for human samples of unknown COVID-19 status (required upgrade from BSL2 to BSL2+)
    • Nuclei isolation with mixed success
  • Plants
    • Arabidopsis thaliana
    • Nicotiana benthamiana
    • Nicotiana tabacum
    • Genetics and RNA: Transformations, genotyping, DNA/RNA extraction, identifying novel splice products, molecular cloning, synthetic biology, plasmid design, de novo gene design, site directed mutagenesis
    • Protein biochemistry: inducible protein regulation, crude protein extraction, protein purification for protein-protein complex studies and antibody generation, western blots
    • Dual protein fluorescence analysis: leaf scans, fluorescence data analysis
    • Effector-triggered immunity: host-pathogen responses and molecular mechanisms
  • Bacteria
    • Escherichia coli (E. coli) for molecular cloning and protein production
    • Agrobacterium tumefaciens for plant transformations
    • Geobacter sulfurreducens for riboswitch characterization; required strict anaerobic culture, glove boxes, removing oxygen from media, etc.
    • Molecular cloning of plasmids 2.5 kb to 16 kb by TOPO A, restriction digest, Gateway cloning
    • Fusion protein expression and purification
    • Microscopy
  • Yeast
    • Some experience with yeast cell culture while teaching undergraduate lab sections
    • Temperature-sensitive mutations and phenotypes
  • In vitro molecular techniques
    • All kinds of PCR: regular PCR, step-down PCR, ligation PCR, RT-PCR for splice factor analysis, qRT-PCR for gene expression quantification, site directed mutagenesis
    • Gel electrophoresis for DNA, RNA, and protein
    • Amazing sterile technique (sterile seed germination on sucrose plates, human cell culture, and bacteria that grow slower than E. coli all require above average sterilize technique)
    • In vitro translation assays

Bioinformatics

  • NGS data annotation with various databases 
    • Ensembl/biomart, miRBase, GENCODE, NCBI, Human Protein Atlas
  • Differential expression analysis 
    • DESeq2, edgeR
    • Batch correction
  • Linear regressions, correlation modeling
    • Generalized linear models
    • Multiple regression analysis
    • Coding optimization for DNA methylation analysis (>800,000 rows of data)
    • Pearson correlations
  • Clustering analysis
    • Principal components analysis
    • Heatmaps with dendrograms
  • Gene enrichment analysis
    • Ingenuity Pathway Analysis, gene ontology, KEGG, missMethyl
  • DNA methylation data annotation and visualization
    • Manhattan plots
    • Quantile-quantile (QQ) plots
  • Data visualization
    • ggplot2, plotly, matplotlib, circos plots (circlize), RColorBrewer, heatmaply, base R
    • Interactive plots, html widgets
  • Data filtering and annotation expert
    • [R] biomaRt, limma, tidyr, tidyverse, dplyr, reshape2
    • [Python] pandas, numpy, matplotlib
    • Integration of different datasets (e.g. methylation and RNA-seq data)
    • Human Protein Atlas
  • Sequence alignments 
    • BLAST, Clustal W and Omega, and various software (Lasergene Suite, BioEdit, etc)
    • Intron identification and alignment matching across species
    • Conserved sequence identification
  • Formal education in higher level mathematics and statistics (UC Davis, UC Berkeley)
    • Linear algebra
    • Differential equations
    • Cell biophysics
    • Physical chemistry
    • Enzyme kinetics
    • Mendelian genetics
    • Sequence alignment theory (e.g. molecular clock, gap open vs gap extension penalties)
    • Mathematical modeling (e.g. eigenvalues, bathtub dynamics, Hidden-Markov Models)
    • Structural biochemistry crystallography theory

 

Programming languages 

  • R - use daily for data analysis, data visualization, subsetting, and annotation
  • Linux command line - use to interact with Cedars-Sinai's high performance computing system, my home Linux server, and Linux-only bioinformatics tools
  • Perl - learned from the UC Davis bioinformatics intro course, still use for hobbies and occasional NCBI database searches
  • Python - self-taught and use infrequently for data analysis
  • (Linux bash .sh scripts) - introduced at Cedars-Sinai's high performance computing workshops, but I prefer to use a combination of Linux command line and Perl or Python or R scripts when possible.
  • (MATLAB) - learned in bioinformatics research program, used for mathematical models of disease spread, don't use anymore
  • (Pascal) - learned in introduction to programming college course, don't use anymore
  • (JavaScript) - 1st language, used from middle school to college, use occasionally for hobbies

Funding sources

These are grants that supported me and my work, including grants where I am staff not PI.
  • Clinical & Translational Science Institute (CTSI) Award #V196 (June 2022)
    • "This work was funded in part by Cedars-Sinai in support of CTSI grant UL1TR001881"
    • Role: co-investigator
  • National Institutes of Health
    • R01 AI154535
    • R01 HD074368 
    • R01 HD091773
    • T32 DK007770
      • "Training Program in Endocrinology, Diabetes, and Metabolism"
      • Ruth L. Kirschstein National Research Service Award
      • https://grantome.com/grant/NIH/T32-DK007770-15
      • Training award that supported the first two years of my postdoctoral career
      • Role: postdoctoral fellow
    • U01 EB026421
  • Burroughs Wellcome Fund, CASI 1007224
    • Provided funding to my PI and helped support me during graduate school
    • Role: staff
  • UC Berkeley Chancellor's Opportunity Fellowship (2010-2012)

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Last updated: April 2024
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