Target Capture Research Articles

Frequent allopolyploidy with distant progenitors in the moss genera Physcomitrium and Entosthodon (Funariaceae) identified via subgenome phasing of targeted nuclear genes.

Allopolyploids represent a new frontier in species discovery among embryophytes. Within mosses, allopolyploid discovery is challenged by low morphological complexity. The rapid expansion of sequencing approaches in addition to computational developments to identifying genome merger and whole-genome duplication using variation among nuclear loci representing homeologs has allowed for increased allopolyploid discovery among mosses. Here, we test a novel approach to phasing homeologs within loci and phasing loci across subgenomes, or subgenome assignment, called Homologizer, in the family Funariaceae. We confirm the intergeneric hybrid nature of Entosthodon hungaricus, and the allopolyploid origin of Physcomitrium eurystomum and one population of Physcomitrium collenchymatum. We also reveal that hybridization gave rise to Physcomitrium immersum, as well as to yet unrecognized lineages sharing the phenotype of Physcomitrium pyriforme and Physcomitrium sphaericum. Our findings demonstrate the utility of our approach when working with polyploid genomes, and its value in identifying progenitor species using target capture data.

High-Performance Cannabinoid Sensor Empowered by Plant Hormone Receptors and Antifouling Magnetic Nanorods.

The misuse of cannabinoids and their synthetic variants poses significant threats to public health, necessitating the development of advanced techniques for detection of these compounds in biological or environmental samples. Existing methods face challenges like lengthy sample pretreatment and laborious antifouling steps. Herein, we present a novel sensing platform using magnetic nanorods coated with zwitterionic polymers for the simple, rapid, and sensitive detection of cannabinoids in biofluids. Our technique utilizes the engineered derivatives of the plant hormone receptor Pyrabactin Resistance 1 (PYR1) as drug recognition elements and employs the chemical-induced dimerization (CID) mechanism for signal development. Additionally, the magnetic nanorods facilitate efficient target capture and reduce the assay duration. Moreover, the zwitterionic polymer coating exhibits excellent antifouling capability, preserving excellent sensor performance in complex biofluids. Our sensors detect cannabinoids in undiluted biofluids like serum, saliva, and urine with a low limit of detection (0.002 pM in saliva and few pM in urine and serum) and dynamic ranges spanning up to 9 orders of magnitude. Moreover, the PYR1 derivatives demonstrate high specificity even in the presence of multiple interfering compounds. This work opens new opportunities for sensor development, showcasing the excellent performance of antifouling magnetic nanorods that can be compatible with different recognition units, including receptors and antibodies, for detecting a variety of targets.

Assessment and validation of enrichment and target capture approaches to improve Mycobacterium tuberculosis WGS from direct patient samples.

Within-host Mycobacterium tuberculosis (Mtb) diversity may detect antibiotic resistance or predict tuberculosis treatment failure and is best captured through sequencing directly from sputum. Here, we compared three sample pre-processing steps for DNA decontamination and studied the yield of a new target enrichment protocol for optimal whole-genome sequencing (WGS) from direct patient samples. Mtb-positive NALC-NaOH-treated patient sputum sediments were pooled, and heat inactivated, split in replicates, and treated by either a wash, DNase I, or benzonase digestion. Levels of contaminating host DNA and target Mtb DNA were assessed by quantitative PCR (qPCR), followed by WGS with and without custom dsDNA target enrichment. The pre-treatment sample has a high host-to-target ratio of DNA (6,168 ± 1,638 host copies/ng to 212.3 ± 59.4 Mtb copies/ng) that significantly decreased with all three treatments. Benzonase treatment resulted in the highest enrichment of Mtb DNA at 100-fold compared with control (3,422 ± 2,162 host copies/ng to 11,721 ± 7,096 Mtb copies/ng). The custom dsDNA probe panel successfully enriched libraries from as little as 0.45 pg of Mtb DNA (100 genome copies). Applied to direct sputum the dsDNA target enrichment panel increased the percent of sequencing reads mapping to the Mtb target for all three pre-processing methods. Comparing the results of the benzonase sample sequenced both with and without enrichment, the percent of sequencing reads mapping to the Mtb increased to 90.95% from 1.18%. We demonstrate a low limit of detection for a new custom dsDNA Mtb target enrichment panel that has a favorable cost profile. The results also demonstrate that pre-processing to remove contaminating extracellular DNA prior to cell lysis and DNA extraction improves the host-to-Mtb DNA ratio but is not adequate to support average coverage WGS without target capture.

Adaptive Capture Control of a Continuum Manipulator With Self-Powered Sensors

Perception is an essential component of an intelligent autonomous system. However, the traditional sensors used in robotics and industrial are limited when considering high mobility, wide distribution, and possible wireless operation of the sensors in sensor networks. The self-powered sensing solves the most shackling issue in the current sensing field, thus enabling many previously unattainable application scenarios. In this paper, a novel variable-length continuum manipulator with self-powered sensors is designed, and an adaptive capture control scheme based on deep learning prediction is proposed for the envelope grasp of a fixed cylinder target and the hook grasp of a ring target moving in a small range. First, adaptive capture parameters of the manipulator are generated according to a target’s size and position. Then, deep neural networks are utilized to accurately predict the bending angle of the manipulator with a large displacement motion at the tip of the continuum manipulator. Finally, based on the feedback data from the driving motor’s built-in angular velocity sensor on the continuum manipulator, a set of capture criteria are presented to identify the envelope and capture states of the target. The capture experimental results on a prototype reveal that the generated parameters highly match the targets. The prediction method’s accuracy is higher than that of conventional feedforward neural networks. The capture criteria based on the feedback data from driving motor’s built-in angular velocity sensor can correctly identify the target capture states. In additional, the future research of the adaptive capture control based on self-powered sensors is discussed.

Phylogenomics of Fresh and Formalin Specimens Resolves the Systematics of Old World Mud Snakes (Serpentes: Homalopsidae) and Expands Biogeographic Inference

Our knowledge of the biodiversity of Asia and Australasia continues to expand with more focused studies on systematics of various groups and their biogeography. Historically, fluctuating sea levels and cyclic connection and separation of now-disjunct landmasses have been invoked to explain the accumulation of biodiversity via species pump mechanisms. However, recent research has shown that geological shifts of the mainland and species dispersal events may be better explanations of the biodiversity in these regions. We investigate these processes using the poorly studied and geographically widespread Mud Snakes (Serpentes: Homalopsidae) using a target capture approach of ~4,800 nuclear loci from fresh tissues and supplemental mitochondrial data from formalin tissues from museum specimens. We use these datasets to reconstruct the first resolved phylogeny of the group, identify their biogeographic origins, and test hypotheses regarding the roles of sea-level change and habitat selection on their diversification. Divergence dating and ancestral range estimation yielded support for an Oligocene origin and diversification from mainland Southeast Asia and Sundaland in the rear-fanged group ~20 million years ago, followed by eastward and westward dispersal. GeoHiSSE models indicate that niche expansion of ancestral, rear-fanged lineages into aquatic environments did not impact their diversification rates. Our results highlight that Pleistocene sea-level changes and habitat specificity did not primarily lead to the extant species richness of Homalopsidae and that, alternatively, geological shifts in mainland Southeast Asia may have been a major driver of diversity in this group. We also emphasize the importance of using fresh and degraded tissues, and both nuclear and mitochondrial DNA, for filling knowledge gaps in poorly known but highly diverse and conceptually important groups. Here, Homalopsidae represents a non-traditional but effective model study system for understanding transitions between terrestrial, marine, and freshwater environments.

Space Manipulator Collision Avoidance Using a Deep Reinforcement Learning Control

Recent efforts in on-orbit servicing, manufacturing, and debris removal have accentuated some of the challenges related to close-proximity space manipulation. Orbital debris threatens future space endeavors driving active removal missions. Additionally, refueling missions have become increasingly viable to prolong satellite life and mitigate future debris generation. The ability to capture cooperative and non-cooperative spacecraft is an essential step for refueling or removal missions. In close-proximity capture, collision avoidance remains a challenge during trajectory planning for space manipulators. In this research, a deep reinforcement learning control approach is applied to a three-degrees-of-freedom manipulator to capture space objects and avoid collisions. This approach is investigated in both free-flying and free-floating scenarios, where the target object is either cooperative or non-cooperative. A deep reinforcement learning controller is trained for each scenario to effectively reach a target capture location on a simulated spacecraft model while avoiding collisions. Collisions between the base spacecraft and the target spacecraft are avoided in the planned manipulator trajectories. The trained model is tested for each scenario and the results for the manipulator and base motion are detailed and discussed.

More than magnetic isolation: Dynabeads as strong Raman reporters toward simultaneous capture and identification of targets

AbstractDynabeads are superparamagnetic particles used for the immunomagnetic purification of cells and biomolecules. Post‐capture, however, target identification relies on tedious culturing, fluorescence staining, and/or target amplification. Raman spectroscopy presents a rapid detection alternative, but current implementations target cells themselves with weak Raman signals. We present antibody‐coated Dynabeads as strong Raman reporter labels whose effect can be considered a Raman parallel of immunofluorescent probes. Recent developments in techniques for separating target‐bound Dynabeads from unbound Dynabeads make such an implementation feasible with high specificity. We deploy Dynabeads anti‐Salmonella to bind and identify Salmonella enterica, a major foodborne pathogen. Dynabeads present major peaks around 1000 and 1600 cm−1 from aliphatic and aromatic C‐C stretching of the polystyrene coating and near 1350 cm−1 from the ɣ‐Fe2O3 and Fe3O4 core, confirmed with electron dispersive X‐ray (EDX) imaging. Minor to no contributions are made from the surface antibodies themselves as confirmed by Raman analysis of surface‐activated, antibody‐free beads. Dynabeads' Raman signature can be measured in dry and liquid samples even at single shot ~30 × 30 μm area imaging using 0.5 s, 7‐mW laser acquisition with single and clustered beads providing a 44‐ and 68‐fold larger Raman intensity compared with the signature from cells. Higher polystyrene and iron oxide content in clusters yields larger signal intensity, and conjugation to bacteria strengthens clustering as a bacterium can bind to more than one bead as observed via transmission electron microscopy (TEM). Our findings shed light on the intrinsic Raman reporter nature of Dynabeads. When combined with emerging techniques for the separation of target‐bound Dynabeads from unbound Dynabeads such as using centrifugation through a density media bilayer, they have the potential to demonstrate their dual function for target isolation and detection without tedious staining steps or unique plasmonic substrate engineering, advancing their applications in heterogeneous samples like food, water, and blood.

Efficient capture and highly sensitive analysis of okadaic acid by three-dimensional covalent organic frameworks with hydroxyl surface engineering

A novel three-dimensional covalent organic framework (3D-COF) with content-tunable and active hydroxyl groups (OH) on the pore walls was developed and adopted for the high-performance capture of okadaic acid (OA) marine toxins. Using pore-surface engineering, the integration of linear building blocks (4,4′-diamino-3,3′-biphenyldiol, BD(OH)2 and benzidine, BD) with the 3D structural building block backbone (4,4′,4′',4′''-methane-tetrayltetrabenzaldehyde, TFPM) was achieved. By adjusting the ratio of BD(OH)2, functional multicomponent-COFs [OH]x-BD-TFPM COFs (X = 25%) were synthesized, which offered ideal access to convert a conventional COF into a functional platform with multiple-mode interactions of hydrophobic and hydrophilic groups for OA capture. [OH]x-BD-TFPM was characterized using SEM, XRD, FT-IR, and BET. The adsorption features and analytical performance of OA were screened and evaluated. Optimization of dispersive solid-phase extraction using [OH]25-BD-TFPM was accomplished, and the method was verified for sensitive quantitative detection of OA in clam and mussel samples. Coupled with LC-MS/MS, the resultant [OH]25-BD-TFPM COF demonstrated the ability to analyze OA, and the limit of detection for OA in shellfish was determined to be 0.005 μg/kg. A significant improvement in trace OA detection was observed compared to previously reported SPE materials without adjustable hydrophilic interactions. The recoveries of OA in the fortified clam and mussel samples were in the ranges of 93.9‒105.1% and 96.7‒110.2%, respectively. This study highlights that OH-group surface engineering in channel walls is a facile and powerful strategy for developing functional 3D-COFs with multiple interactions for high-performance target capture.

Dazzle: surface patterns that impede interception

Abstract ‘Dazzle coloration’ describes a wide variety of high-contrast patterns allegedly providing protection against attack during motion. Previous research falls into three broad groups. First, studies using humans demonstrate that certain surface patterns can cause significant misperceptions in controlled laboratory conditions, although the effects are inconsistent in both direction and magnitude. Second, experiments on target capture or tracking also show effects that are strongly dependent upon the test paradigm. It has not been established that these laboratory findings generalize to other species, or to the real world. Third, mainly comparative studies build a case for longitudinal striping being involved in escape strategies in some squamate reptiles. We suggest that: (1) the concept of dazzle conflates a description of appearance with presumed function; (2) some effects attributed to dazzle have not been distinguished clearly from other mechanisms of protective coloration; and (3) confusion persists over the evidence necessary to attribute a dazzle function to markings. We refine the definition of dazzle to exclude appearance: dazzle is coloration that interferes with target interception, as a result of misperception of its speed, trajectory and/or range. Our review clarifies discussion of dazzle, and sets out a coherent and practical framework for future research.

Upconverting Nanoparticle-Based Photoactive Probes for Highly Efficient Labeling and Isolation of Target Proteins.

Photoaffinity labeling (PAL) has blossomed into a powerful and versatile tool for capture and identification of biomolecular targets. However, low labeling efficiency for specific targets such as lectins, the tedious process for protein purification, inevitable cellular photodamage, and less tissue penetration of UV light are significant challenges. Herein, we reported a near-infrared (NIR) light-driven photoaffinity labeling approach using upconverting nanoparticle (UCNP)-based photoactive probes, which were constructed by assembling photoactive groups and ligands onto NaYF4:Yb,Tm nanoparticles. The novel probes were easily prepared and functionalized, and the labeled proteins can be isolated and purified through simple centrifugation and washing. The advantages of this approach were demonstrated by labeling and isolation of peanut agglutinin (PNA), asialoglycoprotein receptor (ASGPR), and human carbonic anhydrase II (hCAII) from mixed proteins or cell lysates with good selectivity and efficiency, especially for PNA and ASGPR, two lectins that showed low binding affinity to their ligands. More importantly, successful labeling of PNA through pork tissues and ASGPR in mice strongly proved the good tissue penetrating capacity of NIR light and the application potential of UCNP-based photoactive probes for protein labeling in vivo. Biosafety of this approach was experimentally validated by enzyme, cell, and animal work, and we demonstrated that NIR light caused minimal photodamage to enzyme activity compared to UV light, and the UCNP-based photoactive probe presents good biosafety both in vitro and in vivo. We believe that this novel PAL approach will provide a promising tool for study of ligand-protein interactions and identification of biomolecular targets.

Image based target capture of free floating space manipulator under unknown dynamics

Target capture is the basis of many space missions. With free-floating space manipulators(FFSM) are more and more widely used in various space tasks, using FFSM to catch space targets has become a research hotspot. In this research, we propose an end-to-end capture strategy under unknown dynamics based on deep reinforcement learning, which directly controls the manipulator with the raw camera image as the input. The algorithm take imitation learning for pre-training. The policy after pre-training process will explore high-reward regions in the state space with higher probability. This will improve the efficiency of DRL exploring in the high-dimensional state space composed of images. We built a simulation environment in CoppeliaSim to train and test our algorithm. The results show that our algorithm has achieved good results in end-to-end target capture task without dynamic modeling and is more efficient than pure model free reinforcement learning.

Collaborative Search and Target Capture of AUV Formations in Obstacle Environments

When performing cooperative search operations underwater, multi-autonomous underwater vehicles formations may encounter array-type obstacles such as gullies and bumps. To safely traverse the obstacle domain, this paper balances convergence time, transformation distance and sensor network power consumption, and proposes a Formation Comprehensive Cost (FCC) model to achieve collision avoidance of the formations. The FCC model is used instead of the fitness function of the genetic algorithm to solve the assignment of capture positions and the improved neural self-organizing map (INSOM) algorithm is proposed to achieve efficient path-planning during the capture process. The simulation experiments in 3D space verify that the proposed scheme can improve the efficiency of robot deployment while ensuring safety.

Highly selective photocatalytic CO2 reduction and hydrogen evolution facilitated by oxidation induced nitrogen vacancies on g-C3N4

The introduction of nitrogen vacancies into polymeric carbon nitride (PCN) has been attested to be a reliable strategy to enhance photocatalytic performance. Nitrogen vacancies were considered as active sites to promote the adsorption of target molecules and capture photoexcited electrons to inhibit the recombination of charge pairs, accelerate photoinduced electrons to participate in photocatalytic reaction. In this paper, a series of PCN with rich nitrogen vacancies were prepared by etching of chromic acid solution. Sample 20KCSCN had the highest photocatalytic performance whose evolution efficiency of CO2 to CO and CH4 can reach 3.9 and 0.5 μmol·g−1·h−1, respectively. These evolution efficiencies are 2.9 and 4 times higher than that of the PCN. Meanwhile, 20KCSCN demonstrates high CO conversion selectivity and stability. The successful introduction of nitrogen vacancies not only increases the active sites of PCN surface, but also optimizes the optical structure, which dramatically boosts the separation of photoexcited charge pairs and the reduction capacity of photogenerated electrons. The enhancement mechanism for photocatalytic CO2 reduction performance of PCN was proposed. Besides, photocatalytic H2 evolution experiments were performed on all samples to confirm the universality of PCN photocatalytic activity enhancement etched by chromic acid solution. H2 evolution rate on 20KCSCN can reach 652 μmol·g−1·h−1, which is 1.6-fold higher than that on PCN (254 μmol·g−1·h−1) after 4 h irradiation under a 300 W Xe lamp. This work offers new venue for introducing nitrogen vacancies in PCN to regulate photoexcited charge pairs transfer. The photocatalytic enhancement of CO2 reduction could be used to alleviate the serious issue of excessive CO2 emission and energy crisis.

Target Capturing in an Ellipsoidal Region with a Swarm of Quadcopter Agents with Different Social Value Orientation Parameters

Target Capturing in an Ellipsoidal Region with a Swarm of Quadcopter Agents with Different Social Value Orientation Parameters

HARPS: An Online POMDP Framework for Human-Assisted Robotic Planning and Sensing

The ability of autonomous robots to model, communicate, and act on semantic “soft data” remains challenging. The human-assisted robotic planning and sensing (HARPS) framework is presented for active semantic sensing and planning in human–robot teams to address these gaps by formally combining the benefits of online sampling-based partially observable Markov decision process policies, multimodal human–robot interaction, and Bayesian data fusion. HARPS lets humans impose model structure and extend the range of soft data by sketching and labeling new semantic features in uncertain environments. Dynamic model updating lets robotic agents actively query humans for novel and relevant semantic data, thereby improving model and state beliefs for improved online planning. Simulations of a unmanned aerial vehicle-enabled target search in a large-scale partially structured environment show significant improvements in time and beliefs required for interception versus conventional planning with robot-only sensing. A human subject study in the same environment shows an average doubling in dynamic target capture rate compared to the lone robot case and highlights the robustness of HARPS over a range of user characteristics and interaction modalities.

LoCoLotive: In silico mining for low-copy nuclear loci based on target capture probe sets and arbitrary reference genomes.

Universal target enrichment probe kits are used to circumvent the individual identification of loci suitable for phylogenetic studies in a given taxon. Under certain circumstances, however, target capture can be inefficient and costly, and lower numbers of marker loci may be sufficient. We therefore propose a computational pipeline that enables the easy identification of a subset of promising candidate loci for a taxon of interest. Target sequences used for probe design are filtered based on an assembled reference genome, resulting in presumably intron-containing single-copy loci as present in the reference taxon. The applicability of the proposed approach is demonstrated based on two probe kits (universal and family-specific) in combination with several publicly available reference genomes. Guided by commercial probe kits, LoCoLotive enables fast and cost-efficient marker mining. Its accuracy mainly depends on the quality of the reference genome and its relatedness to the taxa under study.

Target capture sequencing for the first Nigerian genotype I ASFV genome.

African swine fever (ASF) is a contagious viral disease that affects domestic pigs and wild boars, causing significant economic losses globally. After the first Nigerian outbreak in 1997, there have been frequent reports of ASF in pig-producing regions in the country. To facilitate control, it is important to understand the genotype and phylogenetic relationship of ASF viruses (ASFVs). Recent genetic analysis of Nigerian ASFV isolates has revealed the presence of both genotypes I and II; this is based on analysis of a few selected genes. Phylogenetic analysis of ASFV whole genomes highlights virus origins and evolution in greater depth. However, there is currently no information on the ASFV genome from Nigerian isolates. Two ASFV-positive samples were detected during a random survey of 150 Nigerian indigenous pig samples collected in 2016. We assembled near-complete genomes of the two ASFV-positive samples using in-solution hybrid capture sequencing. The genome-wide phylogenetic tree assigned these two genomes into p72 genotype I, particularly close to the virulent Benin 97/1 strain. The two ASFVs share 99.94 and 99.92 % genomic sequence identity to Benin97/1. This provides insight into the origin and relationship of ASFV strains from Nigeria and Italy. The study reports for the first time the determination of near-complete genomes of ASFV using in-solution hybrid capture sequencing, which represents an important advance in understanding the global evolutionary landscape of ASFVs.

Drift in the tropics: Phylogenetics and biogeographical patterns in Combretaceae

AbstractAimThe aim of this study was to further advance our understanding of the species‐rich, and ecologically important angiosperm family Combretaceae to provide new insights into their evolutionary history. We assessed phylogenetic relationships in the family using target capture data and produced a dated phylogenetic tree to assess fruit dispersal modes and patterns of distribution.LocationTropical and subtropical regions.Time PeriodCretaceous to present.Major Taxa StudiedFamily Combretaceae is a member of the rosid clade and comprises 10 genera and more than 500 species, predominantly assigned to genera Combretum and Terminalia, and occurring on all continents and in a wide range of ecosystems.MethodsWe use a target capture approach and the Angiosperms353 universal probes to reconstruct a robust dated phylogenetic tree for the family. This phylogenetic framework, combined with seed dispersal traits, biome data and biogeographic ranges, allows the reconstruction of the biogeographical history of the group.ResultsAncestral range reconstructions suggest a Gondwanan origin (Africa/South America), with several intercontinental dispersals within the family and few transitions between biomes. Relative abundance of fruit dispersal types differed by both continent and biome. However, intercontinental colonizations were only significantly enhanced by water dispersal (drift fruit), and there was no evidence that seed dispersal modes influenced biome shifts.Main ConclusionsOur analysis reveals a paradox as drift fruit greatly enhanced dispersal distances at intercontinental scale but did not affect the strong biome conservatism observed.

Usher Syndrome on the Island of Ireland: A Genotype-Phenotype Review.

Usher syndrome (USH) is a genetically heterogeneous group of autosomal recessive (AR) syndromic inherited retinal degenerations (IRDs) representing 50% of deaf-blindness. All subtypes include retinitis pigmentosa, sensorineural hearing loss, and vestibular abnormalities. Thorough phenotyping may facilitate genetic diagnosis and intervention. Here we report the clinical/genetic features of an Irish USH cohort. USH patients were selected from the Irish IRD registry (Target 5000). Patients were examined clinically (deep-phenotyping) and genetically using a 254 IRD-associated gene target capture sequencing panel, USH2A exon, and whole genome sequencing. The study identified 145 patients (24.1% USH1 [n = 35], 73.8% USH2 [n = 107], 1.4% USH3 [n = 2], and 0.7% USH4 [n = 1]). A genetic diagnosis was reached in 82.1%, the majority (80.7%) being MYO7A or USH2A genotypes. Mean visual acuity and visual field (VF) were 0.47 ± 0.58 LogMAR and 31.3° ± 32.8°, respectively, at a mean age of 43 years. Legal blindness criteria were met in 40.7%. Cataract was present in 77.4%. ADGRV1 genotypes had the most VF loss, whereas USH2A patients had greater myopia and CDH23 had the most astigmatism. Variants absent from gnomAD non-Finnish Europeans and ClinVar represented more than 20% of the variants identified and were detected in ADGRV1, ARSG, CDH23, MYO7A, and USH2A. USH is a genetically diverse group of AR IRDs that have a profound impact on affected individuals and their families. The prevalence and phenotype/genotype characteristics of USH in Ireland have, as yet, gone unreported. Understanding the genotype of Irish USH patients may guide clinical and genetic characterization facilitating access to existing/novel therapeutics.

Identification of T-DNA structure and insertion site in transgenic crops using targeted capture sequencing.

The commercialization of GE crops requires a rigorous safety assessment, which includes a precise DNA level characterization of inserted T-DNA. In the past, several strategies have been developed for identifying T-DNA insertion sites including, Southern blot and different PCR-based methods. However, these methods are often challenging to scale up for screening of dozens of transgenic events and for crops with complex genomes, like potato. Here, we report using target capture sequencing (TCS) to characterize the T-DNA structure and insertion sites of 34 transgenic events in potato. This T-DNA is an 18 kb fragment between left and right borders and carries three resistance (R) genes (RB, Rpi-blb2 and Rpi-vnt1.1 genes) that result in complete resistance to late blight disease. Using TCS, we obtained a high sequence read coverage within the T-DNA and junction regions. We identified the T-DNA breakpoints on either ends for 85% of the transgenic events. About 74% of the transgenic events had their T-DNA with 3R gene sequences intact. The flanking sequences of the T-DNA were from the potato genome for half of the transgenic events, and about a third (11) of the transgenic events have a single T-DNA insertion mapped into the potato genome, of which five events do not interrupt an existing potato gene. The TCS results were confirmed using PCR and Sanger sequencing for 6 of the best transgenic events representing 20% of the transgenic events suitable for regulatory approval. These results demonstrate the wide applicability of TCS for the precise T-DNA insertion characterization in transgenic crops.