Researchers at the University of California, Davis have developed a scalable, plant-based method using somatic embryogenesis to produce high yields of water-soluble melanin externally from walnut tissues.

Together with Researchers at the University of Texas at Austin, researchers at the University of California, Davis have developed a method for synthesizing long polynucleotides using scaffolded cooperative binding and enzymatic ligation to improve yield, modification compatibility, and assembly accuracy.

Brief description not available

Brief description not available

Brief description not available

Researchers at the University of California, Davis have developed alacto-oligosaccharide (GOS) formulations selectively promote growth of beneficial Bifidobacteria species by tailoring oligosaccharide chain lengths.

Brief description not available

Researchers at the University of California, Davis have developed a diagnostic screen using DNA methylation and genetic variant analysis from newborn blood spots that enables early prediction of autism spectrum disorder (ASD) risk.

Researchers at the University of California, Davis have developed a technology that introduces an approach to creating semi-living, non-replicating cellular systems for advanced therapeutic applications.

Researchers at the University of California, Davis have developed novel antisense oligonucleotide (ASO) therapies that enhance ADNP protein expression to address haploinsufficiency in ADNP syndrome.

Researchers at the University of California, Davis have developed a computer-implemented method to identify viral mutations that enhance transmission and predict their prevalence in populations over time.

The Major Histocompatibility Complex (MHC), is a genomic region that expresses proteins involved in immune system functions and that are important for organ transplantation. In humans, this type of gene is referred to as the Human Leukocyte Antigen (HLA). The HLA region is haplotypic, with all of the region inherited from one parent. HLA is highly polymorphic within the human population, both in terms of protein structure as well as genomic variability.This high genomic diversity makes accurate genotyping difficult using methods such as short-read sequencing. That said, current long-read sequencing methods and analysis can yield incomplete and inaccurate results. 

Clustered regularly interspaced short palindromic repeats (CRISPR) screening is a cornerstone of functional genomics, enabling genome-wide knockout studies to identify genes involved in specific cellular processes or disease pathways. The success of CRISPR screens depends critically on the design of effective guide RNA (gRNA) libraries that maximize on-target activity while minimizing off-target effects. Current CRISPR screening lacks tools that can natively integrate next-generation sequencing (NGS) data for context-specific gRNA design, despite the wealth of genomic and transcriptomic information available from modern sequencing approaches. Traditional gRNA design tools have relied on static libraries with limited genome annotations and outdated scoring methods, lacking the flexibility to incorporate context-specific genomic information. Off-target effects are also a concern, with CRISPR-Cas9 systems tolerating up to three mismatches between single guide RNA (sgRNA) and genomic DNA, potentially leading to unintended mutations that could disrupt essential genes and compromise genomic integrity. Additionally, standard CRISPR library preparation methods can introduce bias through PCR amplification and cloning steps, resulting in non-uniform gRNA representation.

Professor Linlin Zhao and their team from the University of California, Riverside have developed mTAP, a new chemical probe engineered to selectively bind to abasic sites within mitochondrial DNA without affecting nuclear DNA. Unlike non-specific agents, mTAP is equipped with a mitochondria-targeting group, ensuring its precise localization. This invention is advantageous over current technology because its mechanism of action involves forming a stable chemical bond with damaged DNA sites, thereby protecting mtDNA from enzymatic cleavage and maintaining its replication and transcriptional activities.    Fig 1: The UCR mitochondria-targeting water-soluble probe mTAP exclusively reacts with mitochondrial abasic sites, and retains mitochondrial DNA levels under genotoxic stress which are responsible for certain mitochondrial diseases. 

The enzyme Rubisco, largely found in plants, algae, and photosynthetic bacteria, is responsible for the majority of biological carbon fixation on Earth. However, it has slow kinetics and has resisted decades of protein engineering efforts to improve its catalytic rate. UC Berkeley researchers have designed an in-vivo system that allows large libraries of Rubisco sequences to be functionally screened for improved enzymatic properties. They generated an E. coli strain whose growth rate is linked to Rubisco performance, allowing for pooled assays and the use of deep sequencing as a readout. This system allows for much higher throughput screening of Rubisco than any previous method and significantly increases opportunities to identify catalytically superior Rubisco sequences. 

The rapid and accurate analysis of real-time quantitative polymerase chain reaction (qPCR) data is critical for precise disease diagnostics, genetic research, and pathogen detection. However, manual interpretation is prone to human error, and current automated systems often struggle with noise and variability, leading to misdiagnosis or inaccurate results. Researchers at UC Berkeley have developed a Deep Learning System for Enhanced qPCR Data Analysis that addresses these challenges. The system utilizes an advanced deep learning model to analyze raw qPCR data in real-time, significantly improving diagnostic accuracy by identifying subtle patterns and anomalies that are difficult for human experts or conventional software to detect. This innovative approach leads to more reliable and faster results compared to traditional methods.

CRISPR-derived nucleases offer unprecedented precision and ease of use for targeting specific genomic sites. However, the efficient delivery of gene editing tools into plant cells remains a significant hurdle. Current methods rely on a laborious and time-consuming tissue culture pipeline and can induce undesirable changes to the genome and epigenome. To circumvent these limitations, one alternative is to use plant viral vectors for the delivery of compact gene editors and their guide RNA (gRNA). UC Berkeley and UC Davis inventors found that the use of tobacco rattle virus (TRV) vectors to deliver reRNA and variant TnpB proteins to plants results in surprisingly high efficiencies of genome editing not only in the infiltrated cells, but also systemically (e.g., seeds and non-infiltrated leaves). Delivery via TRV caused systemic viral spread into the shoot apical and floral meristematic regions, leading to unexpectedly high efficiencies of genome editing in non-infiltrated cells (i.e., spread of genome editing), for example, surprisingly high efficiencies of genome editing in non-infiltrated systemic leaves as well as in the germline (e.g., seeds).

Nucleic acid therapies hold vast therapeutic potential. FDA approved therapies include mRNA vaccines against SARS-COV2 and CRISPR/CAS9 treatment to treat sickle cell.  Both therapies use non-viral methods to deliver designer nucleic acid therapies to cells. However, a limitation of these approaches is the lack of organ and cell-specific delivery. Controlling gene delivery and expression in various cell subsets is challenging. UC Berkeley researchers have shown that the nanoscale topology of CpG oligodeoxynucleotide (CpG-ODN) motifs can be used to stimulate various immune cell subsets and alter gene expression from exogenously delivered mRNA in distinct immune cell subsets. CpG-ODNs of different classes are known to induce different inflammatory profiles in immune cells based on the structure and nanoscale topology of the short DNA strand. The researchers have found novel nanostructures which can be used to present or deliver CpGs to various cell subsets and regulate gene expression in these subsets.

Achieving precise and tunable control over endogenous gene expression in eukaryotic cells remains a significant challenge, particularly for therapeutic applications or detailed biological studies where fine-tuning is required rather than complete on/off switching. This innovation, developed by UC Berkeley researchers, addresses this by providing a novel, programmable method for transcriptional tuning. The innovation is a two-domain fusion protein comprising the transcriptional repression domain (TRD) of the methyl-CpG-binding domain (MBD) protein MeCP2 linked to a dead Cas9 (dCas9) domain. When combined with a single guide RNA (sgRNA) that targets a specific endogenous gene, this fusion protein partially inhibits, or "tunes," the expression of that gene. Unlike traditional methods like RNAi or full CRISPR interference (CRISPRi), which often aim for complete knockdown, this system offers a highly specific and titratable way to dial down gene expression, providing a distinct advantage in studies requiring subtle modulation of gene dosage or for developing dose-dependent therapeutic strategies.

A cornerstone of bacterial molecular biology is the ability to genetically manipulate the microbe under study. Manipulating the genomes of bacteria is critical to many fields. Such manipulations are made by genetic engineering, which often requires new pieces of DNA to be added to the genome. It is often difficult to move genes into a recalcitrant destination organism due to surveillance systems (CRISPR, Restriction Modification) of the destination/host which degrade invading DNA . It may be commercially desirable to evade these systems in the destination organism. However, evading these systems may require significant experimental effort to design and implement.

A groundbreaking method for the efficient isolation and preservation of high-purity small extracellular vesicles (sEVs - exosomes) from biofluids using a novel EXO-PEG-TR reagent.

Most tumors are extremely complex, having many oncogene drivers and are, therefore, not as amenable to a CRISPR-mediated therapies. Pediatric low-grade glioma (pLGG) is a type of brain cancer that arises during childhood. Some interventions exist, including surgery and inhibitor drugs, but there is no cure for pLGG. In contrast to most types of cancer (which feature a host of driver oncogenes), pLGG tumors tend to arise due to a single driver oncogene mutation. This aspect makes pLGG a potential target for a genome editing intervention. Because CRISPR enzymes can precisely discriminate between wild-type and mutant sequences in a single cell, enzymes such as Cas9 can target a mutant oncogene site without impacting the corresponding wild-type locus in a non-cancer cell. UC Berkeley researchers have developed a CRISPR-based strategies for anti-cancer genome editing.  The invention consists of a suite of genome editing strategies with the capacity to selectively inactivate the oncogene underlying tumor pathology, for example, mutations in pLGG. Deployed via a delivery strategy with the capacity for broad genome editing of brain cells, our strategy will have the capacity to halt – and potentially reverse – tumor growth.

Researchers from UC San Diego developed a new technology that facilitates pooling of nuclear expressed antisense RNAs (NEARs) to identify consequential RNA processing events such as alternative or constitutive RNA splicing or polyadenylation.This technology will identify a phenotype of interest and/or a group of RNA processing events (for example RNA splicing sites of interest or alternatively spliced exons), and transduce cells with a library of NEARs targeting these events. Applications include: Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman",serif;} Research tool. As screens to identify exons of phenotypic relevance in a high throughput manner.Therapeutic target identification. To identify therapeutic targets of cancer cell suppression, such as poison exons in cancer specific transcripts.Therapeutic discovery. As a therapeutic agent to identify therapeutic NEARs for splicing related disorders.  

Hybridization capture approaches allow targeted high-throughput sequencing analysis at reduced costs compared to shotgun sequencing. Hybridization capture is particularly useful in analyses of genomic data from ancient, environmental, and forensic samples, where target content is low, DNA is fragmented and multiplex PCR or other targeted approaches often fail. Hybridization capture involves the use of "bait" nucleotides that capture genomic sequences that are of particular interest for the researcher. Current bait synthesis methods require large-scale oligonucleotide chemical synthesis and/or in vitro transcription. Both RNA and DNA bait generation requires synthesizing template oligonucleotides using phosphoramidite chemistry. Microarray-based synthesis generates oligonucleotides in femtomole scales with high chemical coupling error rates. Templates synthesized at small-scale require enzymatic amplification before use in hybridization capture.The solution proposed here involves a simple and highly efficient method to generate target probes using isothermal amplification. Target sequences are circularized and then amplified by rolling circle amplification. This method generates concatemers comprising thousands of copies of the target seqeuence. Restriction digestion of the amplified product then produces probes to use in target enrichment applications. 

Bento is an open-source software toolkit that uses single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene-gene colocalization. The toolkit is compatible with datasets produced by commercial and academic platforms. Bento is integrated with the open-source single-cell analysis software ecosystem.