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Improvements in long-read data and scaffolding technologies have enabled rapid generation of reference-quality assemblies for complex genomes. Still, an assessment of critical sequence depth and read length is important for allocating limited resources. To this end, we have generated eight assemblies for the complex genome of the maize inbred line NC358 using PacBio datasets ranging from 20 to 75 × genomic depth and with N50 subread lengths of 11–21 kb. Assemblies with ≤30 × depth and N50 subread length of 11 kb are highly fragmented, with even low-copy genic regions showing degradation at 20 × depth. Distinct sequence-quality thresholds are observed for complete assembly of genes, transposable elements, and highly repetitive genomic features such as telomeres, heterochromatic knobs, and centromeres. In addition, we show high-quality optical maps can dramatically improve contiguity in even our most fragmented base assembly. This study provides a useful resource allocation reference to the community as long-read technologies continue to mature. Sequence depth and read length determine the quality of genome assembly. Here, the authors leverage a set of PacBio reads to develop guidelines for sequencing and assembly of complex plant genomes in order to allocate finite resources using maize as an example.

High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species 1 – 4 . To address this issue, the international Genome 10K (G10K) consortium 5 , 6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences. The Vertebrate Genome Project has used an optimized pipeline to generate high-quality genome assemblies for sixteen species (representing all major vertebrate classes), which have led to new biological insights.

Engineering motif-specific 'hot spots' into an antibody scaffold yields antibodies with high affinity to targets containing phosphoserine, phosphothreonine or phosphotyrosine. Aberrant changes in post-translational modifications (PTMs) such as phosphate groups underlie a majority of human diseases. However, detection and quantification of PTMs for diagnostic or biomarker applications often require PTM-specific monoclonal antibodies (mAbs), which are challenging to generate using traditional antibody-selection methods. Here we outline a general strategy for producing synthetic, PTM-specific mAbs by engineering a motif-specific 'hot spot' into an antibody scaffold. Inspired by a natural phosphate-binding motif, we designed and selected mAb scaffolds with hot spots specific for phosphoserine, phosphothreonine or phosphotyrosine. Crystal structures of the phospho-specific mAbs revealed two distinct modes of phosphoresidue recognition. Our data suggest that each hot spot functions independently of the surrounding scaffold, as phage display antibody libraries using these scaffolds yielded >50 phospho- and target-specific mAbs against 70% of target peptides. Our motif-specific scaffold strategy may provide a general solution for rapid, robust development of anti-PTM mAbs for signaling, diagnostic and therapeutic applications.

Structural biologists currently confront serious challenges in the effective interpretation of experimental data due to two contradictory situations: a severe lack of structural data for certain classes of proteins, and an incredible abundance of data for other classes. The challenge with small data sets is how to extract sufficient information to draw meaningful conclusions, while the challenge with large data sets is how to curate, categorize, and search the data to allow for its meaningful interpretation and application to scientific problems. Here, we develop computational strategies to address both sparse and abundant data sets. In the category of sparse data sets, we focus our attention on the problem of transmembrane (TM) protein structure determination. As X-ray crystallography and NMR data is notoriously difficult to obtain for TM proteins, we develop a novel algorithm which uses low-resolution data from protein cross-linking or scanning mutagenesis studies to produce models of TM helix oligomers and show that our method produces models with an accuracy on par with X-ray crystallography or NMR for a test set of known TM proteins. Turning to instances of data abundance, we examine how to mine the vast stores of protein structural data in the Protein Data Bank (PDB) to aid in the design of proteins with novel binding properties. We show how the identification of an anion binding motif in an antibody structure allowed us to develop a phosphate binding module that can be used to produce novel antibodies to phosphorylated peptides – creating antibodies to 7 novel phospho-peptides to illustrate the utility of our approach. We then describe a general strategy for designing binders to a target protein epitope based upon recapitulating protein interaction geometries which are over-represented in the PDB. We follow this by using data describing the transition probabilities of amino acids to develop a novel set of degenerate codons to create more efficient gene libraries. We conclude by describing a novel, real-time, all-atom structural search engine, giving researchers the ability to quickly search known protein structures for a motif of interest and providing a new interactive paradigm of protein design.

Recent improvements in the quality and yield of long-read data and scaffolding technology have made it possible to rapidly generate reference-quality assemblies for complex genomes. Still, generating these assemblies is costly, and an assessment of critical sequence depth and read length to obtain high-quality assemblies is important for allocating limited resources. To this end, we have generated eight independent assemblies for the complex genome of the maize inbred line NC358 using PacBio datasets ranging from 20-75x genomic depth and N50 read lengths of 11-21 kb. Assemblies with 30x or less depth and N50 read length of 11 kb were highly fragmented, with even the low-copy genic fraction of the genome showing degradation at 20x depth. Distinct sequence-quality thresholds were observed for complete assembly of genes, transposable elements, and highly repetitive genomic features such as telomeres, heterochromatic knobs and centromeres. This study provides a useful resource allocation reference to the community as long-read technologies continue to mature. Footnotes * https://github.com/HuffordLab/Maize_NC358

Mobile health technology and activity tracking with wearable sensors enable continuous unobtrusive monitoring of movement and biophysical parameters. Advancements in clothing‐based wearable devices have employed textiles as transmission lines, communication hubs, and various sensing modalities; this area of research is moving towards complete integration of circuitry into textile components. A current limitation for motion tracking is the need for communication protocols demanding physical connection of textile with rigid devices, or vector network analyzers (VNA) with limited portability and lower sampling rates. Inductor–capacitor (LC) circuits are ideal candidates as textile sensors can be easily implemented with textile components and allow wireless communication. In this paper, the authors report a smart garment that can sense movement and wirelessly transmit data in real time. The garment features a passive LC sensor circuit constructed of electrified textile elements that sense strain and communicate through inductive coupling. A portable, lightweight reader (fReader) is developed for achieving a faster sampling rate than a downsized VNA to track body movement, and for wirelessly reading sensor information suitable for deployment with a smartphone. The smart garment–fReader system monitors human movement in real‐time and exemplifies the potential of textile‐based electronics moving forward. A movement‐tracking wearable device is presented that employs all‐textile components for sensing and wireless communication with an external custom reader. An LC circuit is fabricated with a sensing textile capacitor, stitched transmission lines, and an embroidered inductive coil. The custom reader overcomes the limitations of vector network analyzers, with the capability of tracking movement in real time.

The primary objective of this study was to compare plantar pressure (peak forefoot and rearfoot pressure, center of pressure displacement and distance) between maximal and traditional running shoes in recreationally active individuals. A secondary objective was to assess differences in ankle kinematics and vertical ground reaction forces between shoe conditions. A repeated-measures experimental design compared the two shoe conditions (maximal vs. traditional) within the same participants. Twenty recreationally active adults (11 females, 9 males) performed five overground running trials in a maximal and traditional shoe. Plantar pressure, vertical ground reaction forces, and ankle kinematics were measured using a combination of pressure insoles, motion capture, and force plates. Two-tailed paired t-tests with Benjamini–Yekutieli corrections were used to assess differences between shoe conditions (α = 0.05), while effect sizes (Cohen's d) quantified the magnitude of observed differences. Peak forefoot plantar pressure was significantly lower in the maximal shoe (p = .01, d = 0.47), while center of pressure displacement (p = .03, d = 0.39) and distance (p = .01, d = 0.40) were also significantly shorter in the maximal shoe. No significant differences were observed in vertical ground reaction forces (VIP, VAP, AVLR) or ankle kinematics (p > .05). Maximal shoes reduce forefoot plantar pressure and center of pressure displacement and distance compared to traditional shoes in recreational runners. These findings suggest that maximal shoes may help with load management for injuries where decreased forefoot plantar pressure is desired.

Objective: Handheld dynamometers are common tools for assessing/monitoring muscular strength and endurance. Health/fitness Bluetooth load sensors may provide a cost-effective alternative; however, research is needed to evaluate the validity and reliability of such devices. This study assessed the validity and reliability of two commercially available Bluetooth load sensors (Activ5 by Activbody and Progressor by Tindeq). Methods: Four tests were conducted on each device: stepped loading, stress relaxation, simulated exercise, and hysteresis. Each test type was repeated three times using the Instron ElectroPuls mechanical testing device (a gold-standard system). Test–retest reliability was assessed through intraclass correlations. Agreement with the gold standard was assessed with Pearson’s correlation, interclass correlation, and Lin’s concordance correlation. Results: The Activ5 and Progressor had excellent test–retest reliability across all four tests (ICC(3,1) ≥ 0.999, all p ≤ 0.001). Agreement with the gold standard was excellent for both the Activ5 (ρ ≥ 0.998, ICC(3,1) ≥ 0.971, ρc ≥ 0.971, all p’s ≤ 0.001) and Progressor (ρ ≥ 0.999, ICC(3,1) ≥ 0.999, ρc ≥ 0.999, all p’s ≤ 0.001). Measurement error increased for both devices as applied load increased. Conclusion: Excellent test–retest reliability was found, suggesting that both devices can be used in a clinical setting to measure patient progress over time; however, the Activ5 consistently had poorer agreement with the gold standard (particularly at higher loads).

The vertical ground reaction force (vGRF) and its passive and active peaks are important gait parameters and of great relevance for musculoskeletal injury analysis and prevention, the detection of gait abnormities, and the evaluation of lower-extremity prostheses. Most currently available methods to estimate the vGRF require a force plate. However, in real-world scenarios, gait monitoring would not be limited to a laboratory setting. This paper reports a novel solution using machine learning algorithms to estimate the vGRF and the timing and magnitude of its peaks from data collected by a single inertial measurement unit (IMU) on one of the lower limb locations. Nine volunteers participated in this study, walking on a force plate-instrumented treadmill at various speeds. Four IMUs were worn on the foot, shank, distal thigh, and proximal thigh, respectively. A random forest model was employed to estimate the vGRF from data collected by each of the IMUs. We evaluated the performance of the models against the gold standard measurement of the vGRF generated by the treadmill. The developed model achieved a high accuracy with a correlation coefficient, root mean square error, and normalized root mean square error of 1.00, 0.02 body weight (BW), and 1.7% in intra-participant testing, and 0.97, 0.10 BW, and 7.15% in inter-participant testing, respectively, for the shank location. The difference between the reference and estimated passive force peak values was 0.02 BW and 0.14 BW with a delay of −0.14% and 0.57% of stance duration for the intra- and inter-participant testing, respectively; the difference between the reference and estimated active force peak values was 0.02 BW and 0.08 BW with a delay of 0.45% and 1.66% of stance duration for the intra- and inter-participant evaluation, respectively. We concluded that vertical ground reaction force can be estimated using only a single IMU via machine learning algorithms. This research sheds light on the development of a portable wearable gait monitoring system reporting the real-time vGRF in real-life scenarios.