Clustered CTCF binding is an evolutionary mechanism to maintain topologically associating domains, bioRxiv, 2019-06-13

ABSTRACTCTCF binding contributes to the establishment of higher order genome structure by demarcating the boundaries of large-scale topologically associating domains (TADs). We have carried out an experimental and computational study that exploits the natural genetic variation across five closely related species to assess how CTCF binding patterns stably fixed by evolution in each species contribute to the establishment and evolutionary dynamics of TAD boundaries. We performed CTCF ChIP-seq in multiple mouse species to create genome-wide binding profiles and associated them with TAD boundaries. Our analyses reveal that CTCF binding is maintained at TAD boundaries by an equilibrium of selective constraints and dynamic evolutionary processes. Regardless of their conservation across species, CTCF binding sites at TAD boundaries are subject to stronger sequence and functional constraints compared to other CTCF sites. TAD boundaries frequently harbor rapidly evolving clusters containing both evolutionary old and young CTCF sites as a result of repeated acquisition of new species-specific sites close to conserved ones. The overwhelming majority of clustered CTCF sites colocalize with cohesin and are significantly closer to gene transcription start sites than nonclustered CTCF sites, suggesting that CTCF clusters particularly contribute to cohesin stabilization and transcriptional regulation. Overall, CTCF site clusters are an apparently important feature of CTCF binding evolution that are critical the functional stability of higher order chromatin structure.

biorxiv genomics 100-200-users 2019

Teaching R in the undergraduate ecology classroom approaches, lessons learned, and recommendations, bioRxiv, 2019-06-11

AbstractEcology requires training in data management and analysis. In this paper, we present data from the last 10 years demonstrating the increase in the use of R, an open-source programming environment, in ecology and its prevalence as a required skill in job descriptions. Because of its transparent and flexible nature, R is increasingly used for data management and analysis in the field of ecology. Consequently, job postings targeting candidates with a bachelor’s degree and a required knowledge of R have increased over the past ten years. We discuss our experiences teaching undergraduates R in two advanced ecology classes using different approaches. One approach, in a course with a field lab, focused on collecting, cleaning, and preparing data for analysis. The other approach, in a course without a field lab, focused on analyzing existing data sets and applying the results to content discussed in the lecture portion of the course. Our experiences determined that each approach had strengths and weaknesses. We recommend that above all, instructors of ecology and related subjects should be encouraged to include R in their coursework. Furthermore, instructors should be aware of the following learning R is a separate skill from learning statistics; writing R assignments is a significant time sink for course preparation; and, there is a tradeoff between teaching R and teaching content. Determining how one’s course fits into the curriculum and identifying resources outside of the classroom for students’ continued practice will ensure that R training is successful and will extend beyond a one-semester course.

biorxiv scientific-communication-and-education 0-100-users 2019

 

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