Advances in RNA-sequencing (RNA-seq) technologies have provided an unprecedented opportunity to explore the gene expression landscape across individuals, tissues, and environments by efficiently profiling the RNA sequences present in the samples. When a reference genome sequence or a transcriptome of the sample is available, mapping-based RNA-seq analysis protocols align the RNA-seq reads to the reference sequences, identify novel transcripts, and quantify the abundance of expressed transcripts.The reads that fail to map to the human reference, known as unmapped reads, are a large and often overlooked output of standard RNA-seq analyses. Even in carefully executed experiments, the unmapped reads can comprise a considerable fraction of the complete set of reads produced, and can arise due to technical sequencing produced by low-quality and error-prone copies of the nascent RNA sequence being sampled. Reads can also remain unmapped due to unknown transcripts, recombined Band T cell receptor sequences, A-to-G mismatches from A-to-I RNA editing, trans-splicing, gene fusion, circular RNAs, and the presence of non-host RNA sequences (e.g. bacterial, fungal, and viral organisms). Unmapped reads represent a rich resource for the study of B and T cell receptor repertoires and the human microbiome system—without incurring the expense of additional targeted sequencing.This book introduces and describes the Read Origin Protocol (ROP), a tool that identifies the origin of both mapped and unmapped reads. The protocol first identifies human reads using a standard high-throughput algorithm to map them onto a reference genome and transcriptome. After alignment, reads are grouped into genomic (e.g. CDS, UTRs, introns) and repetitive (e.g. SINEs, LINEs, LTRs) categories. The rest of the ROP protocol characterizes the remaining unmapped reads, which failed to map to the human reference sequences.

Advances in RNA-sequencing (RNA-seq) technologies have provided an unprecedented opportunity to explore the gene expression landscape across individuals, tissues, and environments by efficiently profiling the RNA sequences present in the samples. When a reference genome sequence or a transcriptome of the sample is available, mapping-based RNA-seq analysis protocols align the RNA-seq reads to the reference sequences, identify novel transcripts, and quantify the abundance of expressed transcripts.The reads that fail to map to the human reference, known as unmapped reads, are a large and often overlooked output of standard RNA-seq analyses. Even in carefully executed experiments, the unmapped reads can comprise a considerable fraction of the complete set of reads produced, and can arise due to technical sequencing produced by low-quality and error-prone copies of the nascent RNA sequence being sampled. Reads can also remain unmapped due to unknown transcripts, recombined Band T cell receptor sequences, A-to-G mismatches from A-to-I RNA editing, trans-splicing, gene fusion, circular RNAs, and the presence of non-host RNA sequences (e.g. bacterial, fungal, and viral organisms). Unmapped reads represent a rich resource for the study of B and T cell receptor repertoires and the human microbiome system—without incurring the expense of additional targeted sequencing.This book introduces and describes the Read Origin Protocol (ROP), a tool that identifies the origin of both mapped and unmapped reads. The protocol first identifies human reads using a standard high-throughput algorithm to map them onto a reference genome and transcriptome. After alignment, reads are grouped into genomic (e.g. CDS, UTRs, introns) and repetitive (e.g. SINEs, LINEs, LTRs) categories. The rest of the ROP protocol characterizes the remaining unmapped reads, which failed to map to the human reference sequences.

Research in the ?eld of gene regulation is evolving rapidly in an ever-changing s- enti?c environment. Microarray techniques and comparative genomics have enabled more comprehensive studies of regulatory genomics and are proving to be powerful tools of discovery. The application of chromatin immunoprecipitation and microarrays (chIP-on-chip) to directly study the genomic binding locations of transcription factors has enabled more comprehensive modeling of regulatory networks. In addition, c- plete genome sequences and the comparison of numerous related species has dem- strated that conservation in non-coding DNA sequences often provides evidence for cis-regulatory binding sites. That said, much is still to be learned about the regulatory networks of these sequenced genomes. Systematic methods to decipher the regulatory mechanism are also crucial for c- roboratingthese regulatorynetworks.Thecoreof thesemethodsarethe motifdiscovery algorithms that can help predict cis-regulatory elements. These DNA-motif discovery programsarebecomingmoresophisticatedandare beginningto leverageevidencefrom comparative genomics (phylogenetic footprinting) and chIP-on-chip studies.How to use these new sources of evidence is an active area of research.

This book constitutes the thoroughly refereed post-proceedings of two joint RECOMB 2005 satellite events: the First Annual Workshop on Systems Biology, RSB 2005 and the Second Annual Workshop on Regulatory Genomics, RRG 2005, held in San Diego, CA, USA in December 2005. It contains 21 revised full papers that address a broad variety of topics in systems biology and regulatory genomics.

Advances in RNA-sequencing (RNA-seq) technologies have provided an unprecedented opportunity to explore the gene expression landscape across individuals, tissues, and environments by efficiently profiling the RNA sequences present in the samples. When a reference genome sequence or a transcriptome of the sample is available, mapping-based RNA-seq analysis protocols align the RNA-seq reads to the reference sequences, identify novel transcripts, and quantify the abundance of expressed transcripts.The reads that fail to map to the human reference, known as unmapped reads, are a large and often overlooked output of standard RNA-seq analyses. Even in carefully executed experiments, the unmapped reads can comprise a considerable fraction of the complete set of reads produced, and can arise due to technical sequencing produced by low-quality and error-prone copies of the nascent RNA sequence being sampled. Reads can also remain unmapped due to unknown transcripts, recombined Band T cell receptor sequences, A-to-G mismatches from A-to-I RNA editing, trans-splicing, gene fusion, circular RNAs, and the presence of non-host RNA sequences (e.g. bacterial, fungal, and viral organisms). Unmapped reads represent a rich resource for the study of B and T cell receptor repertoires and the human microbiome system—without incurring the expense of additional targeted sequencing.This book introduces and describes the Read Origin Protocol (ROP), a tool that identifies the origin of both mapped and unmapped reads. The protocol first identifies human reads using a standard high-throughput algorithm to map them onto a reference genome and transcriptome. After alignment, reads are grouped into genomic (e.g. CDS, UTRs, introns) and repetitive (e.g. SINEs, LINEs, LTRs) categories. The rest of the ROP protocol characterizes the remaining unmapped reads, which failed to map to the human reference sequences.

Advances in RNA-sequencing (RNA-seq) technologies have provided an unprecedented opportunity to explore the gene expression landscape across individuals, tissues, and environments by efficiently profiling the RNA sequences present in the samples. When a reference genome sequence or a transcriptome of the sample is available, mapping-based RNA-seq analysis protocols align the RNA-seq reads to the reference sequences, identify novel transcripts, and quantify the abundance of expressed transcripts.The reads that fail to map to the human reference, known as unmapped reads, are a large and often overlooked output of standard RNA-seq analyses. Even in carefully executed experiments, the unmapped reads can comprise a considerable fraction of the complete set of reads produced, and can arise due to technical sequencing produced by low-quality and error-prone copies of the nascent RNA sequence being sampled. Reads can also remain unmapped due to unknown transcripts, recombined Band T cell receptor sequences, A-to-G mismatches from A-to-I RNA editing, trans-splicing, gene fusion, circular RNAs, and the presence of non-host RNA sequences (e.g. bacterial, fungal, and viral organisms). Unmapped reads represent a rich resource for the study of B and T cell receptor repertoires and the human microbiome system—without incurring the expense of additional targeted sequencing.This book introduces and describes the Read Origin Protocol (ROP), a tool that identifies the origin of both mapped and unmapped reads. The protocol first identifies human reads using a standard high-throughput algorithm to map them onto a reference genome and transcriptome. After alignment, reads are grouped into genomic (e.g. CDS, UTRs, introns) and repetitive (e.g. SINEs, LINEs, LTRs) categories. The rest of the ROP protocol characterizes the remaining unmapped reads, which failed to map to the human reference sequences.

Research in the ?eld of gene regulation is evolving rapidly in an ever-changing s- enti?c environment. Microarray techniques and comparative genomics have enabled more comprehensive studies of regulatory genomics and are proving to be powerful tools of discovery. The application of chromatin immunoprecipitation and microarrays (chIP-on-chip) to directly study the genomic binding locations of transcription factors has enabled more comprehensive modeling of regulatory networks. In addition, c- plete genome sequences and the comparison of numerous related species has dem- strated that conservation in non-coding DNA sequences often provides evidence for cis-regulatory binding sites. That said, much is still to be learned about the regulatory networks of these sequenced genomes. Systematic methods to decipher the regulatory mechanism are also crucial for c- roboratingthese regulatorynetworks.Thecoreof thesemethodsarethe motifdiscovery algorithms that can help predict cis-regulatory elements. These DNA-motif discovery programsarebecomingmoresophisticatedandare beginningto leverageevidencefrom comparative genomics (phylogenetic footprinting) and chIP-on-chip studies.How to use these new sources of evidence is an active area of research.

This book constitutes the thoroughly refereed post-proceedings of two joint RECOMB 2005 satellite events: the First Annual Workshop on Systems Biology, RSB 2005 and the Second Annual Workshop on Regulatory Genomics, RRG 2005, held in San Diego, CA, USA in December 2005. It contains 21 revised full papers that address a broad variety of topics in systems biology and regulatory genomics.