The James Webb Space Telescope Mission

Twenty-six years ago a small committee report, building on earlier studies, expounded a compelling and poetic vision for the future of astronomy, calling for an infrared-optimized space telescope with an aperture of at least $4m$. With the support of their governments in the US, Europe, and Canada, 20,000 people realized that vision as the $6.5m$ James Webb Space Telescope. A generation of astronomers will celebrate their accomplishments for the life of the mission, potentially as long as 20 years, and beyond. This report and the scientific discoveries that follow are extended thank-you notes to the 20,000 team members. The telescope is working perfectly, with much better image quality than expected. In this and accompanying papers, we give a brief history, describe the observatory, outline its objectives and current observing program, and discuss the inventions and people who made it possible. We cite detailed reports on the design and the measured performance on orbit.Comment: Accepted by PASP for the special issue on The James Webb Space Telescope Overview, 29 pages, 4 figure

The Science Performance of JWST as Characterized in Commissioning

This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.Comment: 5th version as accepted to PASP; 31 pages, 18 figures; https://iopscience.iop.org/article/10.1088/1538-3873/acb29

Longevity and plasticity of CFTR provide an argument for noncanonical SNP organization in hominid DNA.

Like many other ancient genes, the cystic fibrosis transmembrane conductance regulator (CFTR) has survived for hundreds of millions of years. In this report, we consider whether such prodigious longevity of an individual gene--as opposed to an entire genome or species--should be considered surprising in the face of eons of relentless DNA replication errors, mutagenesis, and other causes of sequence polymorphism. The conventions that modern human SNP patterns result either from purifying selection or random (neutral) drift were not well supported, since extant models account rather poorly for the known plasticity and function (or the established SNP distributions) found in a multitude of genes such as CFTR. Instead, our analysis can be taken as a polemic indicating that SNPs in CFTR and many other mammalian genes may have been generated--and continue to accrue--in a fundamentally more organized manner than would otherwise have been expected. The resulting viewpoint contradicts earlier claims of 'directional' or 'intelligent design-type' SNP formation, and has important implications regarding the pace of DNA adaptation, the genesis of conserved non-coding DNA, and the extent to which eukaryotic SNP formation should be viewed as adaptive

Computer Simulation of SNP Accrual in the Setting of a Transition Bias Leads to Enhancement of Conservative Mutations.

<p>SNPs were stochastically placed in 1) an artificial, assembled gene containing 1480 codons arranged randomly (i.e. random codons were used to generate a 4440 bp sequence), 2) the CFTR coding sequence (1480 codons), or 3) a GC-rich region of CFTR. The computer-generated positions to be mutated were selected randomly, and the choice of base replacement (e.g. with or without a particular transition bias) derived as above, according to the CFTR mutation database (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone-0109186-t002" target="_blank">Table 2</a>), or rates observed for exonic or intronic SNPs (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone-0109186-t001" target="_blank">Table 1</a>). The ratios for non-conservative (Ncon) to conservative (Con) SNPs are shown. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone-0109186-t005" target="_blank">Table 5</a> is the result of 10 simulation runs per sequence, indicating significant differences even after small numbers of SNP incorporation.</p><p>Computer Simulation of SNP Accrual in the Setting of a Transition Bias Leads to Enhancement of Conservative Mutations.</p

Transition Bias in Human SNPs.

<p>Incidence of six possible SNP configurations (transition and transversion) for CFTR intronic regions, and coding sequence from CFTR and 97 other human genes containing at least one exonic SNP (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone-0109186-g002" target="_blank">Figure 2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone.0109186.s003" target="_blank">Table S2</a>). Underlined = transition mutations. The <i>p</i> values (based on an assumption of equal probability for any individual base replacement) indicate a strong bias in favor of transitions over transversions in both the human CFTR intronic DNA and the exonic sequences of 98 human genes. Transition∶transversion ratio for CFTR intronic SNPs = 2.1; for exonic SNPs in 98 genes = 3.6.</p><p>*p = 8.5×10⁻²⁰.</p><p>**p = 5.7×10⁻⁷⁰.</p><p>Transition Bias in Human SNPs.</p

HapMap minor allelic frequencies (MAFs) plotted against gene sequence position.

<p>Frequency data for SNPs in CFTR (<u>Panel A</u>) or NF1 (<u>Panel B</u>) were collated for each of the ethnicities shown: JPT (Japanese in Tokyo, 45 individuals); CHB (Han Chinese in Beijing, 45 individuals); CEU (or CEPH, Utah residents with ancestry from northern and eastern Europe, 90 individuals); and YRI (Yoruba in Ibidan, Nigeria, 90 individuals). MAF refers to the relative frequency (1000 = 100% incidence) of the minor allele at each SNP position. Solid arrows/red circles depict areas indicative of a haplotype block (also referred to as MAF block) in the genes as shown; broken arrows describe sites of genomic recombination. In order to generate a MAF block diagram, allele frequency data was downloaded from UCSC genome table browser (<a href="http://genome.ucsc.edu/cgi-bin/hg:tables" target="_blank">http://genome.ucsc.edu/cgi-bin/hg:tables</a>). After downloading, SNPs with MAF equal to zero among all four ethnicities were omitted. The remaining SNPs were then inserted into the scatter plot. Linkage disequilibrium valves for the blocks depicted here (when obtained directly from HapMap) were robust (r² among co∶allelic SNPs shown by red circles typically = 1.0).</p

SNP incidence in human intronic and exonic DNA.

<p><u>A:</u> SNPs in 133 human genes known to be lethal or severely debilitating if deleted <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone.0109186-Fortini1" target="_blank">[90]</a> (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone.0109186.s002" target="_blank">Table S1</a>); <u>B:</u> Survey of 4857 human genes for which intron/exon boundaries are readily definable in the Exon-Intron Database (<a href="http://www.utoledo.edu/med/depts/bioinfo/database.html" target="_blank">http://www.utoledo.edu/med/depts/bioinfo/database.html</a>) and 1000 Genomes release (<a href="http://pilotbrowser.1000genomes.org/index.html" target="_blank">http://pilotbrowser.1000genomes.org/index.html</a>); <u>Panel C:</u> Composite data used to generate Panels A and B.</p

Positions exhibiting polymorphism in human CFTR are also polymorphic among other species.

<p><u>A:</u> Six of nine CFTR coding SNPs identified by unbiased analysis of individuals in 1000 Genomes were also were polymorphic among diverse species, despite approximately 50% overall nucleotide identity among the non-human CFTRs being analyzed. <u>B, C:</u> CFTR and 21 other genes (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone.0109186.s004" target="_blank">Table S3</a>) were investigated in the same fashion shown in Panel A. The majority of SNPs in exonic regions found to be polymorphic were synonymous (<i>p</i> = 2.7×10⁻⁹, versus the stochastic ratio otherwise expected for non-synonymous to synonymous polymorphism). In order to increase stringency, only those genes in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone-0109186-g002" target="_blank">Figure 2A</a> with ≥50% concordance across the six non-human species were included in the analysis. <u>D.</u> CFTR homologs in four evolutionarily distant species (horse, frog, zebrafish, and shark) were aligned with the human coding strand, both independently and collectively. In the collective alignment, ∼43% of the coding sequence was invariant. A computer simulation was conducted and the total number of differences from human placed randomly within the human CFTR reading frame of 4443 bp. The goal was to determine in a conservative fashion whether concordance observed in a multiple species alignment could be accounted for by chance. The simulation was performed 120,000 times and the numbers of differences from human tabulated. The mean concordance (35.4%) and standard deviation (∼0.05) for this set of simulation data was calculated and differed significantly from the higher level of identity observed in nature for the multiple species alignment (p = 6.6×10⁻⁶³).</p

Frequency of SNPs on the Y and other representative human chromosomes.

<p>Number of SNPs is given for each of the chromosomes shown, according to data in dbSNP, HapMap, or 1000 Genomes.</p><p>*1000 Genomes Pilot Release 7.</p><p>Frequency of SNPs on the Y and other representative human chromosomes.</p

Synonymous and non-synonymous SNP incidence.

<p><u>A:</u> Exonic SNPs in 98 genes known to be lethal or severely debilitating if deleted (a subset of genes in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone-0109186-g001" target="_blank">Figure 1A</a> with at least one exonic SNP (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone.0109186.s003" target="_blank">Table S2</a>)); <u>B:</u> Survey of 13,820 genes for which data was accessible from the Exon-Intron Database (<a href="http://www.utoledo.edu/med/depts/bioinfo/database.html" target="_blank">http://www.utoledo.edu/med/depts/bioinfo/database.html</a>) and 1000 Genomes (<a href="http://pilotbrowser.1000genomes.org/index.html" target="_blank">http://pilotbrowser.1000genomes.org/index.html</a>); <u>C:</u> Composite data used to generate Panels A and B. All genes from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone-0109186-g001" target="_blank">Figure 1A</a> with at least one exonic SNP were examined. Each gene was analyzed in the 1000 Genome Pilot Browser (<a href="http://pilotbrowser.1000genomes.org/index.html" target="_blank">http://pilotbrowser.1000genomes.org/index.html</a>) including designation as synonymous vs. non-synonymous. The synonymous SNP enhancement agrees with earlier population-based studies in <i>Drosophila</i>, human, and other species <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone.0109186-Hinds1" target="_blank">[35]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone.0109186-Bustamante1" target="_blank">[36]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone.0109186-Berglund1" target="_blank">[37]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0109186#pone.0109186-Boyko1" target="_blank">[84]</a>. To confirm that the ratio of synonymous to non-synonymous SNPs calculated from the set of 98 disease-associated genes was representative of the larger population, a bootstrapping analysis was conducted. Two-thousand samples of 98 genes were randomly selected from the larger gene cohort. Synonymous to non-synonymous ratios were used to determine a mean for each set of ninety-eight chosen in this manner. The overall mean of 2,000 samples was used to calculate both confidence interval and a 2-tailed t-test comparing the means of the 98 disease-associated genes and the mean derived from bootstrap sampling of the larger gene set. At the 95% confidence level, the mean synonymous to non-synonymous ratio of the 13,000 gene data set indicated a ratio between 1.37 and 1.38. A comparison to the 98 gene cohort mean yielded a p-value of 0.12.</p