Fast animal pose estimation using deep neural networks, bioRxiv, 2018-05-25

AbstractRecent work quantifying postural dynamics has attempted to define the repertoire of behaviors performed by an animal. However, a major drawback to these techniques has been their reliance on dimensionality reduction of images which destroys information about which parts of the body are used in each behavior. To address this issue, we introduce a deep learning-based method for pose estimation, LEAP (LEAP Estimates Animal Pose). LEAP automatically predicts the positions of animal body parts using a deep convolutional neural network with as little as 10 frames of labeled data for training. This framework consists of a graphical interface for interactive labeling of body parts and software for training the network and fast prediction on new data (1 hr to train, 185 Hz predictions). We validate LEAP using videos of freely behaving fruit flies (Drosophila melanogaster) and track 32 distinct points on the body to fully describe the pose of the head, body, wings, and legs with an error rate of <3% of the animal’s body length. We recapitulate a number of reported findings on insect gait dynamics and show LEAP’s applicability as the first step in unsupervised behavioral classification. Finally, we extend the method to more challenging imaging situations (pairs of flies moving on a mesh-like background) and movies from freely moving mice (Mus musculus) where we track the full conformation of the head, body, and limbs.

biorxiv animal-behavior-and-cognition 500+-users 2018

Genetic compensation is triggered by mutant mRNA degradation, bioRxiv, 2018-05-22

Genetic compensation by transcriptional modulation of related gene(s) (also known as transcriptional adaptation) has been reported in numerous systems1–3; however, whether and how such a response can be activated in the absence of protein feedback loops is unknown. Here, we develop and analyze several models of transcriptional adaptation in zebrafish and mouse that we show are not caused by loss of protein function. We find that the increase in transcript levels is due to enhanced transcription, and observe a correlation between the levels of mutant mRNA decay and transcriptional upregulation of related genes. To assess the role of mutant mRNA degradation in triggering transcriptional adaptation, we use genetic and pharmacological approaches and find that mRNA degradation is indeed required for this process. Notably, uncapped RNAs, themselves subjected to rapid degradation, can also induce transcriptional adaptation. Next, we generate alleles that fail to transcribe the mutated gene and find that they do not show transcriptional adaptation, and exhibit more severe phenotypes than those observed in alleles displaying mutant mRNA decay. Transcriptome analysis of these different alleles reveals the upregulation of hundreds of genes with enrichment for those showing sequence similarity with the mutated gene’s mRNA, suggesting a model whereby mRNA degradation products induce the response via sequence similarity. These results expand the role of the mRNA surveillance machinery in buffering against mutations by triggering the transcriptional upregulation of related genes. Besides implications for our understanding of disease-causing mutations, our findings will help design mutant alleles with minimal transcriptional adaptation-derived compensation.

biorxiv genetics 200-500-users 2018

Efficient long single molecule sequencing for cost effective and accurate sequencing, haplotyping, and de novo assembly, bioRxiv, 2018-05-17

Obtaining accurate sequences from long DNA molecules is very important for genome assembly and other applications. Here we describe single tube long fragment read (stLFR), a technology that enables this a low cost. It is based on adding the same barcode sequence to sub-fragments of the original long DNA molecule (DNA co-barcoding). To achieve this efficiently, stLFR uses the surface of microbeads to create millions of miniaturized barcoding reactions in a single tube. Using a combinatorial process up to 3.6 billion unique barcode sequences were generated on beads, enabling practically non-redundant co-barcoding with 50 million barcodes per sample. Using stLFR, we demonstrate efficient unique co-barcoding of over 8 million 20-300 kb genomic DNA fragments. Analysis of the genome of the human genome NA12878 with stLFR demonstrated high quality variant calling and phasing into contigs up to N50 34 Mb. We also demonstrate detection of complex structural variants and complete diploid de novo assembly of NA12878. These analyses were all performed using single stLFR libraries and their construction did not significantly add to the time or cost of whole genome sequencing (WGS) library preparation. stLFR represents an easily automatable solution that enables high quality sequencing, phasing, SV detection, scaffolding, cost-effective diploid de novo genome assembly, and other long DNA sequencing applications.

biorxiv genomics 0-100-users 2018

 

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