Publications by authors named "M Diekhans"
GENCODE produces comprehensive reference gene annotation for human and mouse. Entering its twentieth year, the project remains highly active as new technologies and methodologies allow us to catalog the genome at ever-increasing granularity. In particular, long-read transcriptome sequencing enables us to identify large numbers of missing transcripts and to substantially improve existing models, and our long non-coding RNA catalogs have undergone a dramatic expansion and reconfiguration as a result.
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- - Accurate gene annotations are essential for interpreting how genomes function, and the GENCODE consortium has spent twenty years creating reference annotations for human and mouse genomes, serving as a vital resource for researchers globally.
- - Previous annotations of long non-coding RNAs (lncRNAs) were incomplete and poorly organized, hindering research, prompting GENCODE to launch a comprehensive effort that resulted in adding nearly 18,000 novel human genes and over 22,000 novel mouse genes, significantly increasing the catalog of transcripts.
- - The new annotations not only show evolutionary patterns and link to genetic variants associated with traits but also improve understanding of previously unclear genomic functions, greatly advancing research into both human and mouse genetic diseases.
The UCSC Genome Browser (https://genome.ucsc.edu) is a widely utilized web-based tool for visualization and analysis of genomic data, encompassing over 4000 assemblies from diverse organisms.
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- The study presents detailed genomes of six ape species, achieving high accuracy and complete sequencing of all their chromosomes.
- It addresses complex genomic regions, leading to enhanced understanding of evolutionary relationships among these species.
- The findings will serve as a crucial resource for future research on human evolution and our closest ape relatives.
Article Synopsis
- * They generated over 427 million long-read sequences and found that longer, more accurate sequences yield better transcript detection, while increased read depth enhances quantification.
- * The study suggests that using reference-based tools works best for well-annotated genomes and recommends incorporating extra data to better identify rare transcripts, providing a benchmark for improving transcriptome analysis techniques in the future.