UCLA Technology Center for Genomics & Bioinformatics (UCLA TCGB) (http://pathology.ucla.edu/tcgb), directed by Dr. Xinmin Li, has 8 Ph.D. level scientists and a total staff of 12, who together have 76 years combined genomics experience. This high throughput genomic Center equipped with all major next generation sequencing instruments, sophisticated bioinformatics tools and big data management systems including:
1.Nucleic acids isolation and QC
With the state of the art instruments and well established data analysis and management systems, the UCLA TCGB offers a wide range of genomic services including:
1.Automated DNA/RNA isolation & quality evaluation
2.Next generation sequencing services
These state-of-the-art NGS and microarray services are offered at a cost-effective and timely manner to serve basic science, translational and clinical researchers. The TCGB clientele include researchers generally unfamiliar with whole genome and bioinformatics approaches as well as experts seeking more sophisticated solutions. In addition to providing comprehensive genomic services, the UCLA TCGB provides “beyond service” assistance in
science and technology which includes fostering new ideas, facilitating project collaboration and integration across biomedical disciplines and developing new applications to advance the quality of the science. The UCLA TCGB also provides educational training to faculty, staff and students and strives to raise awareness of new directions and major discoveries in the areas of genomics and bioinformatics. By providing the above services, the UCLA TCGB has supported a wide range of translational investigations, including:
In summary, the UCLA TCGB provides next-generation sequencing (NGS)/microarray platforms, an integrated bioinformatics pipeline and technical/intellectual expertise, which has significantly facilitated scientific findings and yielded numerous high impact publications including:
Hugo W, Shi H, Sun L, Piva M, Song C, Kong X, Moriceau G, Hong A, Dahlman KB, Johnson
DB, Sosman JA, Ribas A, Lo RS. Non‐genomic and Immune Evolution of Melanoma Acquiring
MAPKi Resistance. Cell . 2015;162:1271‐85. PMC4821508
Tong AJ, Liu X, Thomas BJ, Lissner MM, Baker MR, Senagolage MD, Allred AL, Barish GD,
Smale ST. A Stringent Systems Approach Uncovers Gene‐Specific Mechanisms Regulating
Inflammation. Cell . 2016;165:165‐79. PMC4808443
York AG, Williams KJ, Argus JP, Zhou QD, Brar G, Vergnes L, Gray EE, Zhen A, Wu NC,
Yamada DH, Cunningham CR, Tarling EJ, Wilks MQ, Casero D, Gray DH, Yu AK, Wang ES,
Brooks DG, Sun R, Kitchen SG, Wu TT, Reue K, Stetson DB, Bensinger SJ. Limiting
Cholesterol Biosynthetic Flux Spontaneously Engages Type I IFN Signaling. Cell .
Van Handel B, Montel‐Hagen A, Sasidharan R, Nakano H, Ferrari R, Boogerd CJ,
Schredelseker J, Wang Y, Hunter S, Org T, Zhou J, Li X, Pellegrini M, Chen JN, Orkin SH,
Kurdistani SK, Evans SM, Nakano A, Mikkola HK. Scl represses cardiomyogenesis in
prospective hemogenic endothelium and endocardium. Cell .2012;150:590‐605. PMC3624753
Bhatt DM, Pandya‐Jones A, Tong AJ, Barozzi I, Lissner MM, Natoli G, Black DL, Smale ST.
Transcript dynamics of proinflammatory genes revealed by sequence analysis of subcellular
RNA fractions. Cell . 2012;150:279‐90. PMC3405548
Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH, Hu‐Lieskovan S, Berent‐Maoz B, Pang J,
Chmielowski B, Cherry G, Seja E, Lomeli S, Kong X, Kelley MC, Sosman JA, Johnson DB,
Ribas A, Lo RS. Genomic and Transcriptomic Features of Response to Anti‐PD‐1
Therapy in Metastatic Melanoma. Cell . 2016;165:35‐44. PMC4808437
Sridharan R, Gonzales‐Cope M, Chronis C, Bonora G, McKee R, Huang C, Patel S, Lopez D,
Mishra N, Pellegrini M, Carey M, Garcia BA, Plath K. Proteomic and genomic approaches
reveal critical functions of H3K9 methylation and heterochromatin protein‐1γ in reprogramming
to pluripotency. Nat Cell Biol . 2013;15:872‐82. PMC3733997
Kautz L, Jung G, Valore EV, Rivella S, Nemeth E, Ganz T. Identification of erythroferrone as
an erythroid regulator of iron metabolism. Nat Genet . 2014;46:678‐84. PMC4104984
Casero D, Sandoval S, Seet CS, Scholes J, Zhu Y, Ha VL, Luong A, arekh C, Crooks GM..
Long non‐coding RNA profiling of human lymphoid progenitor cells reveals transcriptional
divergence of B cell and T cell lineages. Nat Immunol . 2015;16:1282‐91. PMC4653072
Pharoah PD et. Al., GWAS meta‐analysis and replication identifies three new susceptibility
loci for ovarian cancer. Nat Genet. 2013 Apr;45(4):362-70, 370e1-2. doi: 10.1038/ng.2564.
Bojesen SE Multiple independent variants at the TERT locus are associated with telomere
length and risks of breast and ovarian cancer Nat Genet. 2013 Apr;45(4):371-84, 384e1-2. doi:
Schjerven H, McLaughlin J, Arenzana TL, Frietze S, Cheng D, Wadsworth SE, Lawson GW,
Bensinger SJ, Farnham PJ, Witte ON, Smale ST. Selective regulation of lymphopoiesis and
leukemogenesis by individual zinc fingers of Ikaros. Nat Immunol . 2013;14:1073‐83.
Kidani Y, Elsaesser H, Hock MB, Vergnes L, Williams KJ, Argus JP, Marbois BN,
Komisopoulou E, Wilson EB, Osborne TF, Graeber TG, Reue K, Brooks DG, Bensinger SJ.
Sterol regulatory elementbinding proteins are essential for the metabolic programming of
effector T cells and adaptive immunity. Nat Immunol . 2013;14:489‐99. PMC3652626
Kohn LA, Hao QL, Sasidharan R, Parekh C, Ge S, Zhu Y, Mikkola HK, Crooks GM. Lymphoid
priming in human bone marrow begins before expression of CD10 with upregulation of
L‐selectin. Nat Immunol . 2012;13:963‐71. PMC3448017
Yu B, Chang J, Liu Y, Li J, Kevork K, Al‐Hezaimi K, Graves DT, Park NH, Wang CY. Wnt4
signaling prevents skeletal aging and inflammation by inhibiting nuclear factor‐κB. Nat Med .
Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, Walsh LA, Postow
MA, Wong P, Ho TS, Hollmann TJ, Bruggeman C, Kannan K, Li Y, Elipenahli C, Liu C,
Harbison CT, Wang L, Ribas A, Wolchok JD, Chan TA. Genetic basis for clinical
response to CTLA‐4 blockade in melanoma. N Engl J Med. 2014;371:2189‐99. PMC4315319
Bianco P, Cao X, Frenette PS, Mao JJ, Robey PG, Simmons PJ, Wang CY. The meaning, the
sense and the significance: translating the science of mesenchymal stem cells into medicine.
Nat Med . 2013;19:35‐42. PMC3998103
Stroud H, Do T, Du J, Zhong X, Feng S, Johnson L, Patel DJ,Jacobsen SE. Non‐CG
methylation patterns shape the epigeneticlandscape in Arabidopsis. Nat Struct Mol Biol .
Obenauf AC, Zou Y, Ji AL, Vanharanta S, Shu W, Shi H, Kong X, Bosenberg MC, Wiesner T,
Rosen N, Lo RS, Massagué J. Therapyinduced tumour secretomes promote resistance and
tumour progression. Nature . 2015;520:368‐72. PMC4507807
Johnson LM, Du J, Hale CJ, Bischof S, Feng S, Chodavarapu RK, Zhong X, Marson G,
Pellegrini M, Segal DJ, Patel DJ, Jacobsen SE. SRA‐ and SET‐domain‐containing proteins link
RNA polymerase V occupancy to DNA methylation. Nature . 2014;507:124‐8. PMC3963826
Law JA, Du J, Hale CJ, Feng S, Krajewski K, Palanca AM, Strahl BD, Patel DJ, Jacobsen SE.
Polymerase IV occupancy at RNAdirected DNA methylation sites requires SHH1. Nature .
Janzen DM, Tiourin E, Salehi JA, Paik DY, Lu J, Pellegrini M, Memarzadeh S. Corrigendum:
An apoptosis‐enhancing drug overcomes platinum resistance in a tumour‐initiating
subpopulation of ovarian cancer. Nat Commun . 2016;7:10703. PMC4748230
Janzen DM, Tiourin E, Salehi JA, Paik DY, Lu J, Pellegrini M, Memarzadeh S. An
apoptosis‐enhancing drug overcomes platinum resistance in a tumour‐initiating subpopulation
of ovarian cancer. Nat Commun . 2015;6:7956. PMC4532886
Bahn JH, Ahn J, Lin X, Zhang Q, Lee JH, Civelek M, Xiao X. Genomic analysis of ADAR1
binding and its involvement in multiple RNA processing pathways. Nat Commun .
Müller J, Krijgsman O, Tsoi J, Robert L, Hugo W, Song C, Kong X, Possik PA,
Cornelissen‐Steijger PD, Foppen MH, Kemper K, Goding CR, McDermott U, Blank C, Haanen
J, Graeber TG, Ribas A, Lo RS, Peeper DS, Geukes Foppen MH. Low MITF/AXL ratio
predicts early resistance to multiple targeted drugs in melanoma. Nat Commun . 2014;5:5712.
Marusiak AA, Edwards ZC, Hugo W, Trotter EW, Girotti MR, Stephenson NL, Kong X, Gartside
MG, Fawdar S, Hudson A, Breitwieser W, Hayward NK, Marais R, Lo RS, Brognard J. Mixed
lineage kinases activate MEK independently of RAF to mediate resistance to RAF inhibitors.
Nat Commun . 2014;5:3901. PMC4046110
Shi H, Moriceau G, Kong X, Lee MK, Lee H, Koya RC, Ng C, Chodon T, Scolyer RA, Dahlman
KB, Sosman JA, Kefford RF, Long GV, Nelson SF, Ribas A, Lo RS. Melanoma whole-exome
sequencing identifies (V600E)B-RAF amplification-mediated acquired B-RAF inhibitor
resistance. Nat Commun. 2012;3:724
Chromium™ Single Cell 3’ Library Construction
Chromium™ Single Cell 5’ Immune Library Construction (Single Cell V(D)J + 5’ Gene Expression)
Chromium™ Single Cell ATAC Solution
Chromium Single Cell Multiome ATAC + 3’ Gene Expression
Price on request
$76.6/sample for RNA library (polyA selection), $102.2/sample for RNA library (with rRNA depletion)
30X coverage (400 million 2x150 clusters): $1049.78. Turnaround time: 3-4 weeks
$76.6/sample for RNA library (polyA selection), $102.2/sample for RNA library (with rRNA depletion), $89.5/sample for DNA library, $136.4/Methy-Seq library, $216.45/whole exome seq library construction & capturing, prices for 10X single cell sequencing, spatial gene expression and other libraries, please visit UCLA TCGB website.
Novaseq 2X150 S4 sequencing: $6298.65/lane (4 -5 billion PE reads), Novase 2X50 S2: $5717.25/lane (3.3 -4.1 billion PE reads), Novaseq 2X100 S2 sequencing : $6848.4/lane (3.3 -4.1 billion PE reads), Novaseq 2X150 S2 sequencing: $7466.65/lane (3.3 -4.1 billion PE reads), Novaseq 2X50 S1 sequencing : $3306.5/lane (650 -800 million PE reads), Novaseq 2X100 S1 sequencing : $3894.2/lane (650 -800 million PE reads), Novaseq 2X150 S1 sequencing : $4430.2/lane (650 -800 million PE reads), Novaseq 2X50 SP sequencing : $2321.5/lane (325-400 million PE reads), Novaseq 2X100 SP sequencing : $2904.45/lane (325-400 million PE reads), Novaseq 2X150 SP sequencing : $3123.85/lane (325-400 million PE reads), NextSeq500 Sequencing V2 SR 1X75: $2458.7/high output flowcell (400 million reads), Hiseq3000 Sequencing 1X50: $1627.45/lane (>600 million PE reads) Hiseq3000 Sequencing PE 1X50: $1500/lane (>300 million reads), Oxford Nanopore GridION long read sequencing: $2419.65, price on Miseq and others on request. Turnaround time: 1-3 weeks, Deliverables: - Fastq file. If data analysis is requested, file type will depend on researcher
qRT-PCR analysis/gene/sample: $86.85 Turnaround time: 1 weeks
"Technology Center for Genomics & Bioinformatics have always delivered high quality genomic data when contracted for our research projects. I would strongly recommend contracting their services for your own research projects."
"Great experience with this company. I will definitely send samples again."
"As indicated previously, my experience with the Technology Center for Genomics & Bioinformatics has been excellent: good time turn over to perform RNA-seq, good communication and feedback and excellence in professionalism. I will continue to use this core."
"The people we were working with were professional and quick. The output data were of good quality, we've specially checked that twice."
"Very helpful and very supportive of the current and future research 1 thank you Fawzia Bardag-Gorce, PhD."
"The work provided by the Technology Centre for Genomics & Bioinformatics was excellent. Results were provided quickly, all my questions were answered in details through the Science Exchange website which I found easy and convenient to use. Downloading of the original files was also easy. I will definitely work again with this team. Coralie Poizat, Ph.D. Director, Cardiovascular Research Program King Faisal Specialist Hospital & Research Centre Riyadh11211, Saudi Arabia Associate Research Professor San Diego State University San Diego, California, USA"
"Very pleased with TCGB. Fast, easy to work with, and very responsive to questions!"
"They were really efficient in the job!!"
"Very fast and professional"
"Quickly and good service"
"The quality of sequencing is good."
"Professional attitude. Extremely fast turnaround time. High Quality Data. Affordable price."
"Very quick TAT and good service."
"the CMC team is very professional, high efficiency and high quality sequencing results. highly recommend."
"Science Exchange was an unknown entity to me when I first heard of their services. Overall, their excellent, rapid, and repeated communication were the key aspects of what became an extremely valuable RNA-Seq study. Based on their rapid and effective communication as well as cost for services, we next engaged them in analysis of our data. This was also a fast and effective study. We have plans to use their services in another study in the coming months."
"Great service and quick turnaround."
"fast turnaround, high-quality data, quick and professional responses"
"Great job and rapid turnaround!!"
"The quality service should be fast, cost-effective, and friendly support and communication. UCLA Clinical Microarray Core facility has them all. Thanks."
"Very fast turn around. Good job."
"UCLA's Clinical Microarray Core was fantastic! The director of the facility spent time directly on my order and I am very satisfied. All of the folks from this facility were professional and I would highly recommend this group."
"ABSOLUTELY. We are so pleased with our interactions with Xinmin and his staff who were responsive, friendly, helpful, and thorough. We work in a non-model organism that requires outside-the-box thinking; Xinmin was enthusiastic and attentive to our unique concerns. Our project was completed in FIVE days when other facilities quoted 4 - 6 weeks. We will certainly be working with the Clinical Microarray Core for all future RNA seq projects."
"Xinmin's Lab runs very efficient and communicates friendly! Highly recommend!"
"Highly recommended! Excellent service at a reasonable price."
"We analyzed the NGS data and are very happy with the speed of delivery and quality of the data generated by the UCLA Clinical Microarray Core. For NGS we would definitely choose UCLA again."
My current supervisor, Mikael Sigvardsson, professor in Experimental Hematology, LInköping University, Sweden, mediated the contact since we needed help to analyze small amounts of DNA with ChIP-seq.
The staff has been very helpful and they are also extremely skilled at what they do since library preparation and deep sequencing from DNA amounts to small to measure with standard methods. Moreover, the service has been fast provided and during all the time there has been a very good communication.
As mentioned above I have extremelu well appreciated the experience to work with the Clinical Microarray Core and I have, as a customer felt very important and well handled. Moreover, I feel that I work with very good scientists that take their job very serious and I would therefore any day of the week recommend the Clinical Microarray Core at UCLA to anyone who are in need of such service.
Jonas Ungerbäck, Ph.D, Linköping University, Sweden.
I have worked with the CMC for the past 5 years. Dr. Li and Jamie Zhou are absolutely indispensable when it comes to performing microarray or NGS experiments. Consistently, the service they provide is honest, expedient and of the highest quality. On a few occasions, the samples I submitted were of too poor quality to be used; Dr. Li and Jamie immediately contacted me to know how I wished to proceed, thus avoiding wasted time and money. On a more personal note, they and the CMC staff are just wonderful people to work with that will go to the ends of the Earth to help generate quality data. This dedication and passion are rare qualities and should be treasured; I will continue to work exclusively with Dr. Li, Jamie and the CMC as long and I have sequencing needs!
I am a Senior Research Associate in the Cornea Genetics Laboratory at UCLA, directed by Dr. Anthony J. Aldave. We have used the UCLA Clinical Microarray Core (CMC) services on numerous occasions over the last two years.
We've had RNA and DNA processed through the core and have utilized a number of their technology platforms. For gene expression we used the Affymetrix 1.1ST arrays. We've also used the Affymetrix CytoScanHD array for both copy number analysis and genotyping, the latter of which we are using for relatedness analysis between supposed unrelated individuals. Lastly, we've utilized their DNA-seq capabilities (Illumina Hi-Seq) for both whole exome and region capture sequencing. We plan on using their services for RNA-seq in the near future. All of the data that we've received has been of the highest quality. Dr. Li and his staff have also been very helpful with questions that we have had, both before pursuing a particular approach and after receiving the data.
We've also attended two courses on data analysis and a seminar on utilizing third-party software for the analysis of our data. These have been instrumental in our ability to analyze our data in a manner that allows us to make the most biologically meaningful conclusions.
Probably most importantly, the data received from the core are directly leading to the publication of important findings into the genetics and functional processes underpinning the development of several corneal dystrophies.
I have been most impressed with Dr. Li's willingness to sit down with me to discuss experimental design, so that we are making the most experimentally valid and cost-effective choices. I highly recommend the UCLA Clinical Microarray Core