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Jeffrey Rosenfeld

Rutgers, The State University of New Jersey

ORCID: 0000-0002-8750-2841

Publishes on Genomics and Phylogenetic Studies, Genomics and Rare Diseases, Machine Learning in Bioinformatics. 134 papers and 33.3k citations.

134Publications
33.3kTotal Citations

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Top publicationsby citations

The complete sequence of a human genome
Sergey Nurk, Sergey Koren, Arang Rhie et al.|Science|2022
Cited by 3.3kOpen Access

Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion-base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.

A Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes
Cited by 1.3kOpen Access

Genome-sequencing studies indicate that all humans carry many genetic variants predicted to cause loss of function (LoF) of protein-coding genes, suggesting unexpected redundancy in the human genome. Here we apply stringent filters to 2951 putative LoF variants obtained from 185 human genomes to determine their true prevalence and properties. We estimate that human genomes typically contain ~100 genuine LoF variants with ~20 genes completely inactivated. We identify rare and likely deleterious LoF alleles, including 26 known and 21 predicted severe disease-causing variants, as well as common LoF variants in nonessential genes. We describe functional and evolutionary differences between LoF-tolerant and recessive disease genes and a method for using these differences to prioritize candidate genes found in clinical sequencing studies.