Biology subjects

Wacholder, A. C.

Publications and source records attributed to Wacholder, A. C..

3 recordsLinked to original sources

bioRxiv2024

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

molecular biology↗

bioRxiv2019

Finding and extending ancient simple sequence repeat-derived regions in the human genome

BackgroundPreviously, 3% of the human genome has been annotated as simple sequence repeats (SSRs), similar to the proportion annotated as protein coding. The origin of much of the genome is not well annotated, however, and some of the unidentified regions are likely to be ancient SSR-derived regions not identified by current methods. The identification of these regions is complicated because SSRs appear to evolve through complex cycles of expansion and contraction, often interrupted by mutations that alter both the repeated motif and mutation rate. We applied an empirical, kmer-based, approach to identify genome regions that are likely derived from SSRs.\n\nResultsThe sequences flanking annotated SSRs are enriched for similar sequences and for SSRs with similar motifs, suggesting that the evolutionary remains of SSR activity abound in regions near obvious SSRs. Using our previously described P-clouds approach, we identified SSR-clouds, groups of similar kmers (or oligos) that are enriched near a training set of unbroken SSR loci, and then used the SSR-clouds to detect likely SSR-derived regions throughout the genome.\n\nConclusionsOur analysis indicates that the amount of likely SSR-derived sequence in the human genome is 6.77%, over twice as much as previous estimates, including millions of newly identified ancient SSR-derived loci. SSR-clouds identified poly-A sequences adjacent to transposable element termini in over 74% of the oldest class of Alu (roughly, AluJ), validating the sensitivity of the approach. Poly-As annotated by SSR-clouds also had a length distribution that was more consistent with their poly-A origins, with mean about 35 bp even in older Alus. This work demonstrate that the high sensitivity provided by SSR-Clouds improves the detection of SSR-derived regions and will enable deeper analysis of how decaying repeats contribute to genome structure.

genomics↗

bioRxiv2016

Strong and Fluctuating Sequence Constraints Drive Alu Evolution

Though Alu elements are the most common and well-studied transposable elements in the primate genome, Alu evolutionary dynamics remain poorly understood. To better understand these dynamics, we improved our recently introduced Bayesian transposable element ancestral reconstruction method to incorporate automated alignment and be more computationally efficient. We then used it to reconstruct the relationships among almost 800,000 Alu elements in the human genome. We identified the phylogenetic network relating 154 ancestral replicative Alu sequences, and found that the aligned ancestors vary at only 56 out of ~300 sites. We show that the limited number of variable sites among replicative Alu ancestors is best explained by strong sequence constraints on Alu replicative capacity. Moreover, the pattern of variation suggests that sequence constraints fluctuated over the course of Alu evolution, driving the extinction of older Alu subfamilies and the birth of newer ones. Previous analyses have taken the tight clustering of Alu sequences with age as evidence that all Alu sequences are descended from a small number of \"master elements.\" Our results imply instead that the clustering of Alu sequences with age results from fluctuating sequence constraints, and that there were over 4,000 replicative loci during the course of Alu evolution, most of which were disabled by mutation before mutating to new replicative sequences. We also predict which sites have been functionally important for replication, and how these sites have changed over time. The newly clarified dynamics of Alu evolution invalidate assumptions used in common method of transposable element classification and phylogenetics.\n\nSignificance StatementTransposable elements are genomic sequences that can insert copies of themselves elsewhere in the genome. Alu is the most abundant transposable element in primates, making up 10% of the human genome. Due to its ubiquity and tendency to cause genomic instability, Alu has played a major role in shaping primate genomes. Characterizing the trajectory of Alu evolution is important for understanding how the human genome evolved.\n\nPrevious analyses of Alu concluded that a tiny number of elements generated all copies, and existing classifications of Alu reflect that conclusion. In a whole-genome analysis, we determine that many more elements were replicative than previously understood, indicating that current classifications of Alu are flawed. We develop an alternative reconstruction of Alu evolutionary history.

genomics↗