Pacific Salmon and the Coalescent Effective Population Size

Pacific salmon include several species that are both commercially important and endangered. Understanding the causes of loss in genetic variation is essential for designing better conservation strategies. Here we use a coalescent approach to analyze a model of the complex life history of salmon, and derive the coalescent effective population (CES). With the aid of Kronecker products and a convergence theorem for Markov chains with two time scales, we derive a simple formula for the CES and thereby establish its existence. Our results may be used to address important questions regarding salmon biology, in particular about the loss of genetic variation. To illustrate the utility of our approach, we consider the effects of fluctuations in population size over time. Our analysis enables the application of several tools of coalescent theory to the case of salmon

An optimized kit-free method for making strand-specific deep sequencing libraries from RNA fragments

Deep sequencing of strand-specific cDNA libraries is now a ubiquitous tool for identifying and quantifying RNAs in diverse sample types. The accuracy of conclusions drawn from these analyses depends on precise and quantitative conversion of the RNA sample into a DNA library suitable for sequencing. Here, we describe an optimized method of preparing strand-specific RNA deep sequencing libraries from small RNAs and variably sized RNA fragments obtained from ribonucleoprotein particle footprinting experiments or fragmentation of long RNAs. Our approach works across a wide range of input amounts (400 pg to 200 ng), is easy to follow and produces a library in 2-3 days at relatively low reagent cost, all while giving the user complete control over every step. Because all enzymatic reactions were optimized and driven to apparent completion, sequence diversity and species abundance in the input sample are well preserved

Genome-wide functional analysis of human 5' untranslated region introns

Genes with short 5'UTR introns have higher expression than genes with no or long 5'UTR introns. Complex evolutionary forces act on these introns

RanBP2/Nup358 Potentiates the Translation of a Subset of mRNAs Encoding Secretory Proteins

In higher eukaryotes, most mRNAs that encode secreted or membrane-bound proteins contain elements that promote an alternative mRNA nuclear export (ALREX) pathway. Here we report that ALREX-promoting elements also potentiate translation in the presence of upstream nuclear factors. These RNA elements interact directly with, and likely co-evolved with, the zinc finger repeats of RanBP2/Nup358, which is present on the cytoplasmic face of the nuclear pore. Finally we show that RanBP2/Nup358 is not only required for the stimulation of translation by ALREX-promoting elements, but is also required for the efficient global synthesis of proteins targeted to the endoplasmic reticulum (ER) and likely the mitochondria. Thus upon the completion of export, mRNAs containing ALREX-elements likely interact with RanBP2/Nup358, and this step is required for the efficient translation of these mRNAs in the cytoplasm. ALREX-elements thus act as nucleotide platforms to coordinate various steps of post-transcriptional regulation for the majority of mRNAs that encode secreted proteins

A Common Class of Transcripts with 5\u27-Intron Depletion, Distinct Early Coding Sequence Features, and N1-Methyladenosine Modification [preprint]

Introns are found in 5\u27 untranslated regions (5\u27UTRs) for 35% of all human transcripts. These 5\u27UTR introns are not randomly distributed: genes that encode secreted, membrane-bound and mitochondrial proteins are less likely to have them. Curiously, transcripts lacking 5\u27UTR introns tend to harbor specific RNA sequence elements in their early coding regions. To model and understand the connection between coding-region sequence and 5\u27UTR intron status, we developed a classifier that can predict 5\u27UTR intron status with \u3e80% accuracy using only sequence features in the early coding region. Thus, the classifier identifies transcripts with 5\u27 proximal-intron-minus-like-coding regions ( 5IM transcripts). Unexpectedly, we found that the early coding sequence features defining 5IM transcripts are widespread, appearing in 21% of all human RefSeq transcripts. The 5IM class of transcripts is enriched for non-AUG start codons, more extensive secondary structure both preceding the start codon and near the 5\u27 cap, greater dependence on eIF4E for translation, and association with ER-proximal ribosomes. 5IM transcripts are bound by the Exon Junction Complex (EJC) at non-canonical 5\u27 proximal positions. Finally, N1-methyladenosines are specifically enriched in the early coding regions of 5IM transcripts. Taken together, our analyses point to the existence of a distinct 5IM class comprising ~20% of human transcripts. This class is defined by depletion of 5\u27 proximal introns, presence of specific RNA sequence features associated with low translation efficiency, N1-methyladenosines in the early coding region, and enrichment for non-canonical binding by the Exon Junction Complex

A common class of transcripts with 5\u27-intron depletion, distinct early coding sequence features, and N1-methyladenosine modification

Introns are found in 5\u27 untranslated regions (5\u27UTRs) for 35% of all human transcripts. These 5\u27UTR introns are not randomly distributed: Genes that encode secreted, membrane-bound and mitochondrial proteins are less likely to have them. Curiously, transcripts lacking 5\u27UTR introns tend to harbor specific RNA sequence elements in their early coding regions. To model and understand the connection between coding-region sequence and 5\u27UTR intron status, we developed a classifier that can predict 5\u27UTR intron status with \u3e 80% accuracy using only sequence features in the early coding region. Thus, the classifier identifies transcripts with 5\u27 proximal-intron-minus-like-coding regions ( 5IM transcripts). Unexpectedly, we found that the early coding sequence features defining 5IM transcripts are widespread, appearing in 21% of all human RefSeq transcripts. The 5IM class of transcripts is enriched for non-AUG start codons, more extensive secondary structure both preceding the start codon and near the 5\u27 cap, greater dependence on eIF4E for translation, and association with ER-proximal ribosomes. 5IM transcripts are bound by the exon junction complex (EJC) at noncanonical 5\u27 proximal positions. Finally, N1-methyladenosines are specifically enriched in the early coding regions of 5IM transcripts. Taken together, our analyses point to the existence of a distinct 5IM class comprising approximately 20% of human transcripts. This class is defined by depletion of 5\u27 proximal introns, presence of specific RNA sequence features associated with low translation efficiency, N1-methyladenosines in the early coding region, and enrichment for noncanonical binding by the EJC

Absence of Evidence for MHC–Dependent Mate Selection within HapMap Populations

The major histocompatibility complex (MHC) of immunity genes has been reported to influence mate choice in vertebrates, and a recent study presented genetic evidence for this effect in humans. Specifically, greater dissimilarity at the MHC locus was reported for European-American mates (parents in HapMap Phase 2 trios) than for non-mates. Here we show that the results depend on a few extreme data points, are not robust to conservative changes in the analysis procedure, and cannot be reproduced in an equivalent but independent set of European-American mates. Although some evidence suggests an avoidance of extreme MHC similarity between mates, rather than a preference for dissimilarity, limited sample sizes preclude a rigorous investigation. In summary, fine-scale molecular-genetic data do not conclusively support the hypothesis that mate selection in humans is influenced by the MHC locus

Genome Analysis Reveals Interplay between 5′UTR Introns and Nuclear mRNA Export for Secretory and Mitochondrial Genes

In higher eukaryotes, messenger RNAs (mRNAs) are exported from the nucleus to the cytoplasm via factors deposited near the 5′ end of the transcript during splicing. The signal sequence coding region (SSCR) can support an alternative mRNA export (ALREX) pathway that does not require splicing. However, most SSCR–containing genes also have introns, so the interplay between these export mechanisms remains unclear. Here we support a model in which the furthest upstream element in a given transcript, be it an intron or an ALREX–promoting SSCR, dictates the mRNA export pathway used. We also experimentally demonstrate that nuclear-encoded mitochondrial genes can use the ALREX pathway. Thus, ALREX can also be supported by nucleotide signals within mitochondrial-targeting sequence coding regions (MSCRs). Finally, we identified and experimentally verified novel motifs associated with the ALREX pathway that are shared by both SSCRs and MSCRs. Our results show strong correlation between 5′ untranslated region (5′UTR) intron presence/absence and sequence features at the beginning of the coding region. They also suggest that genes encoding secretory and mitochondrial proteins share a common regulatory mechanism at the level of mRNA export

Studies on the Evolution and Function of Introns in 5' Untranslated Regions

The function and evolution of introns have been topics of great interest since introns were discovered in the 1970s. Introns that interrupt protein-coding regions have the most obvious potential to affect coding sequences; therefore, their evolution have been studied most intensively. Splicing of introns within untranslated regions does not contribute directly to the diversity of proteins, yet ~35% of human transcripts contain introns within the 5' untranslated region (UTR). The evolution and possible functions of 5'UTR introns (5UIs) remain largely unexplored. Here we undertook a genome-wide functional analysis of 5UIs. Our main results are as follows: First, the distribution of these introns in the human genome is nonrandom. While genes with regulatory roles are enriched in having 5UIs, genes encoding proteins that are targeted to the endoplasmic reticulum and mitochondria are surprisingly depleted of these introns. Second, we offered and supported a model whereby gene encoding secretory and nuclear-encoded mitochondrial proteins share a common regulatory mechanism at the level of mRNA export, which is dependent on the absence of 5'UTR introns. Specifically, the upstream element in a given transcript, be it an intron or RNA elements near the 5' end of coding sequences (CDS), dictates the mRNA export pathway used. Finally, we discovered a strong correlation between existence of 5'UTR introns and sequence features near the 5' end of CDS. We developed an integrated machine-learning framework that can predict absence of 5UIs using solely the sequence near the 5' end of CDS. Our model achieved >80% accuracy when validated against nuclear-encoded mitochondrial transcripts. Specific RNA elements predictive of 5UI absence are found in ~40% of human transcripts spanning a wide spectrum of functions. By analyzing hundreds of large-scale datasets, we functionally characterized the transcripts with these RNA elements; revealing their association with translational regulation. These RNA elements were bound by proteins interacting with the Exon Junction Complex in vivo suggesting a molecular mechanism that links these elements to their downstream effects in mRNA export and translational regulation. While some 5'UTR introns might be evolving neutrally, our results, taken together, suggest that complex evolutionary forces are acting on this distinct class of introns

Coalescent effective population size as a function of the size of the last age class and the relative contributions to the first age class.

<p>The coalescent effective population size is graphed as <i>p₄</i>, <i>p₅</i> and <i>c₅</i> are allowed to vary and the other parameters are fixed. The total population size is 1000 (<i>N</i> = 1000). The other parameters are c₃ = 0.05, c₄ = 0.1, p₃ = 0.1 and p₄+p₅ = 0.9. The projection onto <i>p₅</i>−<i>c₅</i> plane was shown.</p