PhastWeb: a web interface for evolutionary conservation scoring of multiple sequence alignments using phastCons and phyloP.

SUMMARY: The Phylogenetic Analysis with Space/Time models (PHAST) package is a widely used software package for comparative genomics that has been freely available for download since 2002. Here, we introduce a web interface (phastWeb) that makes it possible to use two of the most popular programs in PHAST, phastCons and phyloP, without downloading and installing the PHAST software. This interface allows users to upload a sequence alignment and either upload a corresponding phylogeny or have one estimated from the alignment. After processing, users can visualize alignments and conservation scores as genome browser tracks and download estimated tree models and raw scores for further analysis. Altogether, this resource makes key features of the PHAST package conveniently available to a broad audience. AVAILABILITY AND IMPLEMENTATION: PhastWeb is freely available on the web at http://compgen.cshl.edu/phastweb/. The website provides instructions as well as examples.

Extreme purifying selection against point mutations in the human genome.

Large-scale genome sequencing has enabled the measurement of strong purifying selection in protein-coding genes. Here we describe a new method, called ExtRaINSIGHT, for measuring such selection in noncoding as well as coding regions of the human genome. ExtRaINSIGHT estimates the prevalence of "ultraselection" by the fractional depletion of rare single-nucleotide variants, after controlling for variation in mutation rates. Applying ExtRaINSIGHT to 71,702 whole genome sequences from gnomAD v3, we find abundant ultraselection in evolutionarily ancient miRNAs and neuronal protein-coding genes, as well as at splice sites. By contrast, we find much less ultraselection in other noncoding RNAs and transcription factor binding sites, and only modest levels in ultraconserved elements. We estimate that ~0.4-0.7% of the human genome is ultraselected, implying ~ 0.26-0.51 strongly deleterious mutations per generation. Overall, our study sheds new light on the genome-wide distribution of fitness effects by combining deep sequencing data and classical theory from population genetics.

An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes.

High-throughput genotyping has enabled discovery of genetic variants associated with an increased risk of developing prostate cancer using genome-wide association studies (GWAS). The goal of this study was to associate GWAS information of patients with primary organ-confined and metastatic prostate cancer using gene expression data and to identify molecular networks and biological pathways enriched for genetic susceptibility variants involved in the 2 disease states. The analysis revealed gene signatures for the 2 disease states and a gene signature distinguishing the 2 patient groups. In addition, the analysis revealed molecular networks and biological pathways enriched for genetic susceptibility variants. The discovered pathways include the androgen, apoptosis, and insulinlike growth factor signaling pathways. This analysis established putative functional bridges between GWAS discoveries and the biological pathways involved in primary organ-confined and metastatic prostate cancer.

Integrative Analysis of MicroRNA-Mediated Gene Signatures and Pathways Modulating White Blood Cell Count in Childhood Acute Lymphoblastic Leukemia.

MicroRNAs (miRNAs) regulate the expression of protein-coding genes and represent potential biomarkers for childhood acute lymphoblastic leukemia (ALL). However, information linking miRNAs with their messenger RNA (mRNA) target genes modulating white blood cell (WBC) count is lacking. Here, we analyzed miRNAs and gene expression data from pediatric patients with ALL to identify a signature of miRNAs involved in ALL and their mRNA target genes, molecular networks, and biological pathways modulating WBC. We discovered a signature of miRNAs differentially expressed in ALL and a signature of mRNA target genes distinguishing patients with high WBC from patients with low WBC. In addition, we identified molecular networks and biological pathways, among them PI3/AKT, JAK/STAT, IL-17, TGF-ß, apoptosis, IL-15, STAT3, IGF-1, FGF, mTOR, VEGF, NF-kB, and P53 signaling pathways, enriched for or targeted by miRNAs. The discovered miRNAs and their target genes and pathways represent potential clinically actionable biomarkers and therapeutic targets.

Molecular Analysis of Central Nervous System Disease Spectrum in Childhood Acute Lymphoblastic Leukemia.

Treatment of the central nervous system (CNS) is an essential therapeutic component in childhood acute lymphoblastic leukemia (ALL). The goal of this study was to identify molecular signatures distinguishing patients with CNS disease from those without the disease in pediatric patients with ALL. We analyzed gene expression data from 207 pediatric patients with ALL. Patients without CNS were classified as CNS1, while those with mild and advanced CNS disease were classified as CNS2 and CNS3, respectively. We compared gene expression levels among the three disease classes. We identified gene signatures distinguishing the three disease classes. Pathway analysis revealed molecular networks and biological pathways dysregulated in response to CNS disease involvement. The identified pathways included the ILK, WNT, B-cell receptor, AMPK, ERK5, and JAK signaling pathways. The results demonstrate that transcription profiling could be used to stratify patients to guide therapeutic decision-making in pediatric ALL.

Integrative genomic analysis for the discovery of biomarkers in prostate cancer.

Genome-wide association studies (GWAS) have achieved great success in identifying single nucleotide polymorphisms (SNPs, herein called genetic variants) and genes associated with risk of developing prostate cancer. However, GWAS do not typically link the genetic variants to the disease state or inform the broader context in which the genetic variants operate. Here, we present a novel integrative genomics approach that combines GWAS information with gene expression data to infer the causal association between gene expression and the disease and to identify the network states and biological pathways enriched for genetic variants. We identified gene regulatory networks and biological pathways enriched for genetic variants, including the prostate cancer, IGF-1, JAK2, androgen, and prolactin signaling pathways. The integration of GWAS information with gene expression data provides insights about the broader context in which genetic variants associated with an increased risk of developing prostate cancer operate.