![]() They began by using CRISPR-Cas9 technology, which is a powerful molecular tool that allows scientists to cut DNA molecules at any location they choose. Supported by a 2013 National Institute of Justice grant, Hanlee Ji, Associate Professor of Medicine at Stanford University, and his colleagues tackled this suite of problems by developing a method for isolating, enriching, and sequencing STRs. Randomly fragmenting the genome rarely results in full STR sequences (needed because fragments of repetitive DNA are impossible to align and assemble accurately), and molecular probes used to separate STRs sequences before sequencing are often misled by the repetitive sequence, leading to increased errors. However, current enhancement techniques also have problems. (Minor contributors are donors contributing less than 50% of a DNA sample.) When samples contain mixtures of individuals, the sequences of minor contributors may become so scarce that it is challenging to distinguish them from artifacts introduced during amplification and sequencing. Typically, genomic DNA extracted from a sample is randomly sheared into fragments of a suitable size for the sequencing technology, and if fragments containing STRs can be isolated first, then only those fragments can be sequenced. Any one region of the genome can be covered by hundreds of reads, enough to provide reasonable certainty in the sequence, despite artifacts introduced during PCR and sequencing.Ī common solution to the problems of sequencing STRs using NGS is to target and enrich STR regions before sequencing. Reads - often no more than a couple of hundred bases - are recorded randomly across the genome and then assembled algorithmically based upon their overlap. ![]() Millions of reads, or snippets of sequence, are generated across as much of the genome as desired, including many thousands of different STRs. Next-generation sequencing (NGS) is a relatively new method used for sequencing genomes, or portions of genomes, with a high degree of accuracy. ![]() Untangling their profiles and avoiding stutter errors can be exceedingly difficult. All of this changes, however, when samples contain mixtures from more than one person. This is a low number of markers to analyze by modern standards, but it produces a manageable data set that is powerful enough to identify individuals. There is a limit to the number of STRs that can be tested at once, and scientists typically restrict their analyses to about 20 to 30 STRs. Thus, many different STRs are copied and sorted in the same reaction. The more STRs analyzed, the more discriminating the final profile, but doing separate analyses for each STR uses precious amounts of the sample, and can be cost- and time-prohibitive. Indeed, the repetitive nature of STRs can cause a small portion of the PCR product to generate “stutter” - one less or one more of the motif repeats - thus complicating the interpretation of the DNA sample.īesides the introduction of stutter during PCR, traditional STR analysis has other challenges. However, the copying process is known to produce artifacts, making them difficult to read. Making copies of a particular region of the DNA using PCR is one of the most reliable laboratory processes used by genomic scientists. This is easily accomplished in the lab once enough copies of the STRs are available, which is done using polymerase chain reaction (PCR). ![]() As different versions of the same STR vary in the number of times its underlying short sequence is repeated, versions can be identified by length. Short Tandem Repeats (STRs) are ideal for human identification, for not only do they vary among individuals more than other genomic regions, but they can be classified without needing to obtain an actual sequence. Research for the Real World: NIJ Seminar Series.Strategic Challenges and Research Agenda. ![]()
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