Finished sequence and assembly of the DUF1220-rich 1q21 region using a haploid human genome

BackgroundAlthough the reference human genome sequence was declared finished in 2003, some regions of the genome remain incomplete due to their complex architecture. One such region, 1q21.1-q21.2, is of increasing interest due to its relevance to human disease and evolution. Elucidation of the exact variants behind these associations has been hampered by the repetitive nature of the region and its incomplete assembly. This region also contains 238 of the 270 human DUF1220 protein domains, which are implicated in human brain evolution and neurodevelopment. Additionally, examinations of this protein domain have been challenging due to the incomplete 1q21 build. To address these problems, a single-haplotype hydatidiform mole BAC library (CHORI-17) was used to produce the first complete sequence of the 1q21.1-q21.2 region.ResultsWe found and addressed several inaccuracies in the GRCh37sequence of the 1q21 region on large and small scales, including genomic rearrangements and inversions, and incorrect gene copy number estimates and assemblies. The DUF1220-encoding NBPF genes required the most corrections, with 3 genes removed, 2 genes reassigned to the 1p11.2 region, 8 genes requiring assembly corrections for DUF1220 domains (~91 DUF1220 domains were misassigned), and multiple instances of nucleotide changes that reassigned the domain to a different DUF1220 subtype. These corrections resulted in an overall increase in DUF1220 copy number, yielding a haploid total of 289 copies. Approximately 20 of these new DUF1220 copies were the result of a segmental duplication from 1q21.2 to 1p11.2 that included two NBPF genes. Interestingly, this duplication may have been the catalyst for the evolutionarily important human lineage-specific chromosome 1 pericentric inversion.ConclusionsThrough the hydatidiform mole genome sequencing effort, the 1q21.1-q21.2 region is complete and misassemblies involving inter- and intra-region duplications have been resolved. The availability of this single haploid sequence path will aid in the investigation of many genetic diseases linked to 1q21, including several associated with DUF1220 copy number variations. Finally, the corrected sequence identified a recent segmental duplication that added 20 additional DUF1220 copies to the human genome, and may have facilitated the chromosome 1 pericentric inversion that is among the most notable human-specific genomic landmarks

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Leveraging large genomic datasets to illuminate the pathobiology of autism spectrum disorders.

"Big data" approaches in the form of large-scale human genomic studies have led to striking advances in autism spectrum disorder (ASD) genetics. Similar to many other psychiatric syndromes, advances in genotyping technology, allowing for inexpensive genome-wide assays, has confirmed the contribution of polygenic inheritance involving common alleles of small effect, a handful of which have now been definitively identified. However, the past decade of gene discovery in ASD has been most notable for the application, in large family-based cohorts, of high-density microarray studies of submicroscopic chromosomal structure as well as high-throughput DNA sequencing-leading to the identification of an increasingly long list of risk regions and genes disrupted by rare, de novo germline mutations of large effect. This genomic architecture offers particular advantages for the illumination of biological mechanisms but also presents distinctive challenges. While the tremendous locus heterogeneity and functional pleiotropy associated with the more than 100 identified ASD-risk genes and regions is daunting, a growing armamentarium of comprehensive, large, foundational -omics databases, across species and capturing developmental trajectories, are increasingly contributing to a deeper understanding of ASD pathology

DUF1220 dosage is linearly associated with increasing severity of the three primary symptoms of autism.

One of the three most frequently documented copy number variations associated with autism spectrum disorder (ASD) is a 1q21.1 duplication that encompasses sequences encoding DUF1220 protein domains, the dosage of which we previously implicated in increased human brain size. Further, individuals with ASD frequently display accelerated brain growth and a larger brain size that is also associated with increased symptom severity. Given these findings, we investigated the relationship between DUF1220 copy number and ASD severity, and here show that in individuals with ASD (n = 170), the copy number (dosage) of DUF1220 subtype CON1 is highly variable, ranging from 56 to 88 copies following a Gaussian distribution. More remarkably, in individuals with ASD CON1 copy number is also linearly associated, in a dose-response manner, with increased severity of each of the three primary symptoms of ASD: social deficits (p = 0.021), communicative impairments (p = 0.030), and repetitive behaviors (p = 0.047). These data indicate that DUF1220 protein domain (CON1) dosage has an ASD-wide effect and, as such, is likely to be a key component of a major pathway underlying ASD severity. Finally, these findings, by implicating the dosage of a previously unexamined, copy number polymorphic and brain evolution-related gene coding sequence in ASD severity, provide an important new direction for further research into the genetic factors underlying ASD

DUF1220 CON1 copy number distribution in individuals with ASD.

<p>CON1 copy numbers were determined for 170 individuals with ASD. CON1 copy number ranges are indicated. Frequency denotes the number of individuals who exhibited the indicated copy number range.</p

DUF1220 copy number is linearly associated with increased cognitive function as measured by total IQ and mathematical aptitude scores

DUF1220 protein domains exhibit the greatest human lineage-specific copy number expansion of any protein-coding sequence in the genome, and variation in DUF1220 copy number has been linked to both brain size in humans and brain evolution among primates. Given these findings, we examined associations between DUF1220 subtypes CON1 and CON2 and cognitive aptitude. We identified a linear association between CON2 copy number and cognitive function in two independent populations of European descent. In North American males, an increase in CON2 copy number corresponded with an increase in WISC IQ (R (2)&nbsp;=&nbsp;0.13, p&nbsp;=&nbsp;0.02), which may be driven by males aged 6-11 (R (2)&nbsp;=&nbsp;0.42, p&nbsp;=&nbsp;0.003). We utilized ddPCR in a subset as a confirmatory measurement. This group had 26-33 copies of CON2 with a mean of 29, and each copy increase of CON2 was associated with a 3.3-point increase in WISC IQ (R (2)&nbsp;=&nbsp;0.22, p&nbsp;=&nbsp;0.045). In individuals from New Zealand, an increase in CON2 copy number was associated with an increase in math aptitude ability (R (2)&nbsp;=&nbsp;0.10 p&nbsp;=&nbsp;0.018). These were not confounded by brain size. To our knowledge, this is the first study to report a replicated association between copy number of a gene coding sequence and cognitive aptitude. Remarkably, dosage variations involving DUF1220 sequences have now been linked to human brain expansion, autism severity and cognitive aptitude, suggesting that such processes may be genetically and mechanistically inter-related. The findings presented here warrant expanded investigations in larger, well-characterized cohorts

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press