Penn, M. | bioRxiv Science

bioRxiv2023

Sherlock - A flexible, low-resource tool for processing camera-trapping images

1O_LIThe use of camera traps to study wildlife has increased markedly in the last two decades. Camera surveys typically produce large datasets which require processing to isolate images containing the species of interest. This is time consuming and costly, particularly if there are many empty images that can result from false triggers. Computer vision technology can assist with data processing, but existing artificial intelligence algorithms are limited by the requirement of a training dataset, which itself can be challenging to acquire. Furthermore, deep-learning methods often require powerful hardware and proficient coding skills. C_LIO_LIWe present Sherlock, a novel algorithm that can reduce the time required to process camera trap data by removing a large number of unwanted images. The code is adaptable, simple to use and requires minimal processing power. C_LIO_LIWe tested Sherlock on 240 596 camera trap images collected from 46 cameras placed in a range of habitats on farms in Cornwall, UK, and set the parameters to find European badgers (Meles meles). The algorithm correctly classified 91.9% of badger images and removed 49.3% of the unwanted empty images. When testing model parameters, we found that faster processing times were achieved by reducing both the number of sampled pixels and bouncing attempts (the number of paths explored to identify a disturbance), with minimal implications for model sensitivity and specificity. When Sherlock was tested on two sites which contained no livestock in their images, its performance greatly improved and it removed 92.3% of the empty images. C_LIO_LIThough further refinements may improve its performance, Sherlock is currently an accessible, simple and useful tool for processing camera trap data. C_LI

ecology↗

bioRxiv2019

The genomic diversification of clonally propagated grapevines

Vegetatively propagated clones accumulate somatic mutations. The purpose of this study was to better understand the consequences of clonal propagation and involved defining the nature of somatic mutations throughout the genome. Fifteen Zinfandel winegrape clone genomes were sequenced and compared to one another using a highly contiguous genome reference produced from one of the clones, Zinfandel 03.\n\nThough most heterozygous variants were shared, somatic mutations accumulated in individual and subsets of clones. Overall, heterozygous mutations were most frequent in intergenic space and more frequent in introns than exons. A significantly larger percentage of CpG, CHG, and CHH sites in repetitive intergenic space experienced transition mutations than genic and non-repetitive intergenic spaces, likely because of higher levels of methylation in the region and the increased likelihood of methylated cytosines to spontaneously deaminate. Of the minority of mutations that occurred in exons, larger proportions of these were putatively deleterious when they occurred in relatively few clones.\n\nThese data support three major conclusions. First, repetitive intergenic space is a major driver of clone genome diversification. Second, clonal propagation is associated with the accumulation of putatively deleterious mutations. Third, the data suggest selection against deleterious variants in coding regions such that mutations are less frequent in coding than noncoding regions of the genome.

genomics↗