Publications by authors named "Beicong Ma"

Measuring minimal residual disease in cancer has applications for prognosis, monitoring treatment and detection of recurrence. Simple sequence-based methods to detect nucleotide substitution variants have error rates (about 10-3) that limit sensitive detection. We developed and characterized the performance of MASQ (multiplex accurate sensitive quantitation), a method with an error rate below 10-6.

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Copy number variants (CNVs) underlie a significant amount of genetic diversity and disease. CNVs can be detected by a number of means, including chromosomal microarray analysis (CMA) and whole-genome sequencing (WGS), but these approaches suffer from either limited resolution (CMA) or are highly expensive for routine screening (both CMA and WGS). As an alternative, we have developed a next-generation sequencing-based method for CNV analysis termed SMASH, for short multiply aggregated sequence homologies.

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Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively.

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Exome sequencing of 343 families, each with a single child on the autism spectrum and at least one unaffected sibling, reveal de novo small indels and point substitutions, which come mostly from the paternal line in an age-dependent manner. We do not see significantly greater numbers of de novo missense mutations in affected versus unaffected children, but gene-disrupting mutations (nonsense, splice site, and frame shifts) are twice as frequent, 59 to 28. Based on this differential and the number of recurrent and total targets of gene disruption found in our and similar studies, we estimate between 350 and 400 autism susceptibility genes.

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Cancers are highly heterogeneous and contain many passenger and driver mutations. To functionally identify tumor suppressor genes relevant to human cancer, we compiled pools of short hairpin RNAs (shRNAs) targeting the mouse orthologs of genes recurrently deleted in a series of human hepatocellular carcinomas and tested their ability to promote tumorigenesis in a mosaic mouse model. In contrast to randomly selected shRNA pools, many deletion-specific pools accelerated hepatocarcinogenesis in mice.

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Topoisomerase poisons are chemotherapeutic agents that are used extensively for treating human malignancies. These drugs can be highly effective, yet tumors are frequently refractory to treatment or become resistant upon tumor relapse. Using a pool-based RNAi screening approach and a well characterized mouse model of lymphoma, we explored the genetic basis for heterogeneous responses to topoisomerase poisons in vitro and in vivo.

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The RNA polymerase (pol) II and III human small nuclear RNA (snRNA) genes have very similar promoters and recruit a number of common factors. In particular, both types of promoters utilize the small nuclear RNA activating protein complex (SNAP(c)) and the TATA box binding protein (TBP) for basal transcription, and are activated by Oct-1. We find that SNAP(c) purified from cell lines expressing tagged SNAP(c) subunits is associated with Yin Yang-1 (YY1), a factor implicated in both activation and repression of transcription.

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The transcription factors TFIIB, Brf1, and Brf2 share related N-terminal zinc ribbon and core domains. TFIIB bridges RNA polymerase II (Pol II) with the promoter-bound preinitiation complex, whereas Brf1 and Brf2 are involved, as part of activities also containing TBP and Bdp1 and referred to here as Brf1-TFIIIB and Brf2-TFIIIB, in the recruitment of Pol III. Brf1-TFIIIB recruits Pol III to type 1 and 2 promoters and Brf2-TFIIIB to type 3 promoters such as the human U6 promoter.

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The core human U6 promoter consists of a proximal sequence element (PSE) located upstream of a TATA box. The PSE is recognized by the snRNA-activating protein complex (SNAP(c)), which consists of five types of subunits, SNAP190, SNAP50, SNAP45, SNAP43, and SNAP19. The TATA box is recognized by TATA box binding protein (TBP).

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