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Perdomo, J. E.

Publications and source records attributed to Perdomo, J. E..

3 recordsLinked to original sources

Passive muscle forces in Drosophila are large but insufficient to support a flys weight

Movement of a limb is shaped by active forces generated by muscle contraction but also by passive forces within individual muscles and joints. In small animals such as insects, the contribution of passive forces to limb movement can match the active forces. However, most measurements of passive forces are limited to the femur-tibia joint in large insects. Here we take advantage of genetic tools in Drosophila to measure passive torques at multiple joints in the flys leg. We genetically inactivate all the motor neurons to assess passive forces. We find that the passive torques are well approximated by a linear spring, i.e., the passive torques linearly increase with angular deviation from the rest angle. The torques are much larger than the gravitational torque due to the leg itself. We estimate that the passive torques are seventy times smaller than necessary to support the weight of the animal. We also inactivated all the motor neurons in a freely standing fly and found that, as predicted from the model, the fly falls when the motor neurons are inactivated. We found that the height at which a fly stands, and, therefore the active forces vary. The flys height affects the time to initiate a fall. The time it takes for the fall is consistent with the active forces decaying with a time constant of [~]100 ms. Thus, although passive forces are strong and will have a large effect on limb kinematics, they are not strong enough to support the weight of the fly.

neuroscience↗

LongReadSum: A fast and flexible quality control and signal summarization tool for long-read sequencing data

While several well-established quality control (QC) tools are available for short reads sequencing data, there is a general paucity of computational tools that provide long read metrics in a fast and comprehensive manner across all major sequencing platforms (such as PacBio, Oxford Nanopore, Illumina Complete Long Read) and data formats (such as ONT POD5, FAST5, basecall summary files and PacBio unaligned BAM). Additionally, none of the current tools provide support for summarizing Oxford Nanopore basecall signal or comprehensive base modification (methylation) information from genomic data. Furthermore, nowadays a single PromethION flowcell on the Oxford Nanopore platform can generate terabytes of signal data, which cannot be handled by existing tools designed for small-scale flowcells. To address these challenges, here we present LongReadSum, a multi-threaded C++ tool which provides fast and comprehensive QC reports on all major aspects of sequencing data (such as read, base, base quality, alignment, and base modification metrics) and produce basecalling signal intensity information from the Oxford Nanopore platform. We demonstrate use cases to analyze cDNA sequencing, direct mRNA sequencing, reduced representation methylation sequencing (RRMS) through adaptive sequencing, as well as whole genome sequencing (WGS) data using diverse long-read platforms.

bioinformatics↗

High density SNP array and reanalysis of genome sequencing uncovers CNVs associated with neurodevelopmental disorders in KOLF2.1J iPSCs

The KOLF2.1J iPSC line was recently proposed as a reference iPSC to promote the standardization of research studies in the stem cell field. Due to overall good performance differentiating to neural cell lineages, high gene editing efficiency, and absence of genetic variants associated to neurological disorders KOLF2.1J iPSC line was particularly recommended for neurodegenerative disease modeling. However, our work uncovers that KOLF2.1J hPSCs carry heterozygous small copy number variants (CNVs) that cause DTNBP1, JARID2 and ASTN2 haploinsufficiencies, all of which are associated with neurological disorders. We further determine that these CNVs arose in vitro over the course of KOLF2.1J iPSC generation from a healthy donor-derived KOLF2 iPSC line and affect the expression of DNTBP1, JARID2 and ASTN2 proteins in KOLF2.1J iPSCs and neural progenitors. Therefore, our study suggests that KOLF2.1J iPSCs carry genetic variants that may be deleterious for neural cell lineages. This data is essential for a careful interpretation of neural cell studies derived from KOLF2.1J iPSCs and highlights the need for a catalogue of iPSC lines that includes a comprehensive genome characterization analysis.

genetics↗